Amy Elizabeth Defnet Contact Information: [email protected] Degree and Date to Be Conferred: Ph.D

Amy Elizabeth Defnet Contact Information: Amy.Defnet@Gmail.Com Degree and Date to Be Conferred: Ph.D

Targeting the Activator Protein-1 Complex to Inhibit Airway Smooth Muscle Cell Hyperproliferation in Asthma

Item Type dissertation

Authors Defnet, Amy Elizabeth

Publication Date 2021

Abstract Hyperproliferation of airway smooth muscle (ASM) cells leads to increased ASM mass causing airway obstruction in inflammatory diseases such as asthma. Currently, there are no effective therapies to modulate ASM cell proliferation that contributes to ...

Keywords Activator Protein-1; airway smooth muscle; retinoic acid; Airway Remodeling; Asthma; Protein Kinases; Transcription Factor AP-1; Tretinoin

Download date 29/09/2021 14:19:54

Link to Item http://hdl.handle.net/10713/15769 Amy Elizabeth Defnet Contact Information: [email protected] Degree and Date to be Conferred: Ph.D. Pharmaceutical Sciences, May 2021 PROFESSIONAL OBJECTIVE My career objective is to work in academic institution where I can develop myself as an educator and researcher. My research employs a cross-disciplinary training regimen, including frequent opportunities for scientific/public speaking and inter-departmental engagement. In preparation for future teaching responsibilities, I have cultivated core pedagogical techniques through the JHU-UMB Collaborative Teaching Fellowship and Quality Matters Online Teaching Program. Additionally, participation in several societies and volunteer groups have helped cultivate my leadership and communication skills. EDUCATION University of Maryland, Baltimore 2016-present • Ph.D. Pharmaceutical Sciences, anticipated completion 2021 Fairleigh Dickinson University, Florham 2012-2016 • B.S. Biological Sciences with a Minor in Chemistry, 2016 RESEARCH Graduate Research Dr. Paul Shapiro and Dr. Maureen Kane, University of Maryland, Baltimore Fall 2016- Present This study hopes to overcome therapeutic limitations in asthma treatment that lead to bronchoconstriction and airway remodeling through evaluation of a novel function- selective ERK1/2 inhibitor and a RAR agonist. The goal is to regulate AP-1 activity and retinoid levels to inhibit airway smooth muscle cell proliferation.

Undergraduate Research

Dr. James Salierno, Fairleigh Dickinson University, Florham Spring 2015-Spring 2016

Effect of road salt (NaCl, CaCl2, and mixture) and Zinc Oxide from the breakdown of tires on feeding behavior and population density of local freshwater crayfish. Dr. Jia Bei Wang, University of Maryland, Baltimore Summer 2014 Worked with a HINT1 knockout transgenic mouse model to perform open field locomotion studies to determine the effectiveness of a drug, originally developed for breast cancer, to combat bipolar depression.

Dr. June Middleton, Fairleigh Dickinson University, Florham Fall 2013 Isolated strains of E. Coli to test for triclosan resistance towards antibiotics. Dr. Edith Myers, Fairleigh Dickinson University, Florham Spring 2013 Exploration of two different non-lethal strains of Enterococcus faecalis on the behavior of Caenorhabditis Elegans after prior exposure to determine the percentage of C. Elegans that stayed on an E. faecalis lawn. PROFESSIONAL PUBLICATIONS 1. Defnet, A.E.; Huang, W.; Polischak, S.; Kane, M.A.; Shapiro, P.; Deshpande, D.A. Effects of ATP-Competitive and Function-Selective ERK Inhibitors on Airway Smooth Muscle Cell Proliferation. Federation of American Societies for Experimental Biology. 2019, 33(10), 10833-10843. 2. Defnet, A.E.; Hasday, J.D.; Shapiro, P. Kinase inhibitors in the treatment of obstructive pulmonary diseases. Current Opinion in Pharmacology. 2020, 51, 11-18. 3. Shannon, S.R.; Yu, J.; Defnet, A.E.; Bongfeldt, D.; Moise, A.R.; Kane, M.A.; Trainor, P.A. Identifying vitamin A signaling by visualizing gene and protein activity, and by quantification of vitamin A metabolites. Methods in Enzymology: Retinoid Signaling Pathways, 2020, 637, 367-415. 4. Next Generation Kinase Inhibitors: Moving Beyond The ATP/Catalytic Site (Springer 2020) a) Ch 1: Introduction to Kinases, Cellular Signaling, and Kinase Inhibitors (Shapiro, P.; Martinez, R.; Defnet, A.E.) b) Ch 3: Avoiding or Co-Opting ATP Inhibition: Overview of Type III, IV, V, and VI Kinase Inhibitors (Martinez, R.; Defnet, A.E.; Shapiro, P.) c) Ch 4: Protein Kinase Interactions with Regulatory and Effector Proteins (Defnet, A.E.; Martinez, R.; Shapiro, P.) 5. Huang, W.; Yu, J.; Liu, T; Tudor, G.; Defnet, A.E.; Zalesak, S.; Kumar, P.; Booth, C.; Farese, A.M.; MacVittie, T.J.; Kane, M.A. Proteomic Evaluation of the Natural History of the Acute Radiation Syndrome of the Gastrointestinal Tract in a Nonhuman Primate Model of Partial-body Irradiation with Minimal Bone Marrow Sparing Includes Dysregulation of the Retinoid Pathway. Health Physics, 2020, 119(5), 604-620. 6. Huang, W.; Yu, J.; Liu, T.; Defnet, A.E.; Zalesak, S.; Farese, A.M.; MacVittie, T.J.; Kane, M.A. Proteomics of Nonhuman Primate Plasma after Partial-body Radiation with Minimal Bone Marrow Sparing. Health Physics, 2020, 119(5): 621-632.

POSITIONS AND EDUCATIONAL EXPERIENCES 2021-Present Department of Pharmaceutical Sciences Dean’s Teaching Fellowship, University of Maryland, Baltimore 2020 Quality Matters Online Teaching Certificate Program 2019-2020 JHU-UMB Collaborative Teaching Fellows Program, Notre Dame of Maryland University 2017-2020 UMBC/UMB NIH Chemistry-Biology Interface Program, University of Maryland, Baltimore County 2017-2020 Graduate Research Assistant, University of Maryland, Baltimore 2016-2017 Graduate Teaching Assistant, University of Maryland, Baltimore 2015-2016 Honors Research Thesis Student, Fairleigh Dickinson University-Florham 2014 Pharmaceutical Sciences Department Summer Intern, University of Maryland, Baltimore 2014 Sophomore Research Experience, Fairleigh Dickinson University-Florham 2012-2013 Florham Scholars in Science, Fairleigh Dickinson University-Florham AWARDS 2019-2020 Department of Pharmaceutical Sciences PSC Graduate Merit Award Fall 2019 Biochemical Journal Poster Prize at IUBMB Focused Meeting on Inhibitors of Kinases, Warsaw, Poland Spring 2019 First Place in Poster Session at UMB Graduate Research Conference Spring 2019 Rho Chi International Honor Society for Pharmaceutical Sciences 2016-Present University of Maryland, Baltimore Dean’s List Fall 2015 Outstanding Junior Honors Thesis, FDU Honors Program Summer 2015 Novo Nordisk Undergraduate Research Award/Stipend EXTRACURRICULAR/ COMMUNITY OUTREACH Graduate SACNAS JHU-UMB Chapter, Member and President 2018-2019 Coordinated several events including a volunteer event at Patterson High School, a Graduate Student Panel for local undergrads, a Native American Tribal Health Panel, a collaborative event with the CURE program, and several seminars from minority professors.

UMB CURE Program, Mentor 2016-2017 Mentored several middle school students from West Baltimore including teaching them about research in science, planning activities and mock research symposiums, helping with classwork, and discussing possible career options in the sciences. Undergraduate Becton Student Leadership Network, Mentor Spring 2015- 2016 Beta Beta Beta Biological Honors Society, Member and Volunteer Spring 2014- 2016 FDU Honors Program, Mentor and Member Fall 2012-Spring 2016 Order of Omega Greek Honors Society, President Fall 2014-Spring 2016 Theta Phi Alpha Fraternity, Philanthropy Chair Spring 2013-Spring 2016 FDU Varsity Field Hockey Team, Goalkeeper and Captain Fall 2012-2015 PROFESSIONAL/SOCIETY AFFILIATIONS Spring 2019-Present American Society for Biochemistry and Molecular Biology (ASBMB) Fall 2018-Present UMB-JHU Society for the Advancement of Chicanos and Native Americans in Science (SACNAS) Fall 2017-Present University of Maryland, Baltimore County, Chemistry-Biology Interface Program (CBI) Fall 2016-Present American Association of Pharmaceutical Scientists (AAPS) Fall 2016-Present UMB Pharmaceutical Graduate Students Association (PGSA) PRESENTATIONS 1. Novel function-selective kinase inhibitors for the treatment of asthma Amy Defnet Seminar at Coppin State University to Senior Level Undergraduate Class, Baltimore, MD, February 2020. 2. Comparisons of ATP-competitive (Type I) versus function-selective (Type IV) ERK Inhibitors to Prevent Airway Smooth Muscle Cell Proliferation in Asthma. Amy Defnet, Weiliang Huang, Maureen Kane, Deepak Deshpande, and Paul Shapiro Poster IUBMB Focused Meeting on Inhibitors of Protein Kinases, Warsaw, Poland, September 2019. Biochemical Journal Best Poster Prize.

3. Comparisons of ATP-competitive (Type I) versus function-selective (Type IV) ERK Inhibitors to Prevent Airway Smooth Muscle Cell Proliferation Amy Defnet, Weiliang Huang, Maureen Kane, Deepak Deshpande, and Paul Shapiro Poster 12th Annual Frontiers at the Chemistry Biology Interface Symposium, Rockville, MD, May 2019. 4. Comparisons of ATP-competitive (Type I) versus function-selective (Type IV) ERK Inhibitors to Prevent Airway Smooth Muscle Cell Proliferation Amy Defnet, Weiliang Huang, Maureen Kane, Deepak Deshpande, and Paul Shapiro Poster Experimental Biology 2019- ASBMB Society, Orlando, FL, April 2019. 5. Function Selective ERK Inhibition and Restoration of Retinoic Acid as a Therapeutic Approach to Prevent Airway Smooth Muscle Cell Proliferation in Allergic Asthma. Amy Defnet, Weiliang Huang, Jace Jones, Deepak Deshpande, Paul Shapiro, and Maureen Kane Poster- Origins of Allergic Disease: Microbial, Epithelial, and Immune Interactions, Tahoe City, CA, March 2019 6. Function Selective ERK Inhibition and Restoration of Retinoic Acid as a Therapeutic Approach to Prevent Airway Smooth Muscle Cell Proliferation in Allergic Asthma. Amy Defnet, Weiliang Huang, Jace Jones, Deepak Deshpande, Paul Shapiro, and Maureen Kane Poster- First Place 41st Annual Graduate Research Conference, University of Maryland, Baltimore, MD, March 2019. 7. Targeting the ERK1/2 Pathway to Prevent Airway Smooth Muscle Cell Proliferation- Implications in Asthma Treatment Amy Defnet, Weiliang Huang, Maureen Kane, Deepak Deshpande, and Paul Shapiro Poster 11th Annual Frontiers at the Chemistry Biology Interface Symposium, Philadelphia, PA, May 2018. 8. Involvement of Retinoid Signaling in Airway Smooth Muscle Cell Proliferation and Tissue Remodeling in Asthma Amy Defnet, Weiliang Huang, Jace Jones, Deepak Deshpande, Paul Shapiro, and Maureen Kane Poster, The 4th International Conference on Retinoids, Steamboat Springs, CO, June 2018.

9. Targeting the ERK1/2 Pathway to Prevent Airway Smooth Muscle Cell Proliferation- Implications in Asthma Treatment Amy Defnet, Weiliang Huang, Maureen Kane, Deepak Deshpande, and Paul Shapiro Oral Presentation 40th Annual Graduate Research Conference, University of Maryland, Baltimore, MD, March 2018. 10. Targeting the ERK1/2 Pathway to Prevent Airway Smooth Muscle Cell Proliferation and Tissue Remodeling in Asthma Amy Defnet, Bhavya Bhardwaj, Weiliang Huang, Deepak Deshpande, and Paul Shapiro Poster The Pharmaceutical Sciences and Regulatory Science Grad Gathering, Baltimore, MD, Sept. 2017

Abstract

Title of Dissertation: Targeting the Activator Protein-1 Complex to Inhibit Airway Smooth

Muscle Cell Hyperproliferation in Asthma

Amy E. Defnet, Doctor of Philosophy, 2021

Dissertation Directed by: Maureen A. Kane, PhD, Associate Professor of Pharmaceutical

Sciences and Paul Shapiro, PhD, Professor of Pharmaceutical Sciences

Hyperproliferation of airway smooth muscle (ASM) cells leads to increased ASM mass causing airway obstruction in inflammatory diseases such as asthma. Currently, there are no effective therapies to modulate ASM cell proliferation that contributes to debilitating bronchoconstriction in severe asthmatics. Previous studies suggest that activator protein-1

(AP-1) transcription factor expression is upregulated in airway cells in asthma and inhibition of AP-1 could mitigate the hyperproliferation of ASM cells. AP-1 activity has been shown to be enhanced by upstream extracellular signal-regulated kinase (ERK1/2) signaling or antagonized by retinoic acid receptor (RAR)-mediated signaling. The overall goal of the current study was to evaluate the therapeutic potential of a combination therapy of an ERK1/2 inhibitor and RAR agonist to modulate AP-1 complex formation and activation.

Aim 1 studies tested the hypothesis that a novel function-selective ERK1/2 inhibitor, referred to as SF-3-030, would mitigate off-target toxicity while regulating platelet-derived growth factor (PDGF) induced AP-1 activity and ASM cell proliferation.

In Aim 2 studies we evaluated the role of retinoids in controlling AP-1 complex formation and identified a RARγ isoform-specific agonist, CD1530, as a potential therapeutic option

for inhibition of AP-1 activity and ASM cell hyperproliferation. Aim 3 studies determined whether a polypharmacological approach of combining ERK1/2 inhibition and RAR agonism to target two different aspects of the AP-1 complex activation and formation would have an additive effect in preventing ASM hyperproliferation.

Overall, these studies help further our understanding of how AP-1 signaling causes the hyperproliferation of ASM cells while elucidating possible therapeutic treatment options through ERK1/2 inhibition and RAR agonism.

Targeting the Activator Protein-1 Complex to Inhibit Airway Smooth Muscle Cell Hyperproliferation in Asthma

by Amy Elizabeth Defnet

Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, Baltimore in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2021

Dedication

To my parents, Sarah and Mike Defnet,

and husband, Chuck Miller

iii

Acknowledgements

First and foremost, I would like to thank my two amazing mentors, Dr. Maureen A.

Kane and Dr. Paul Shapiro, for their endless support and guidance throughout these past five years. When I first came to UMB I was very lost and unsure of myself. I had only a small understanding of what graduate school entailed and had a million questions. Maureen was brave enough to take me into her lab for my first rotation and I immediately knew I had to have her as a mentor. Her genuine love of science and optimism toward all different kinds of research topics inspired me every day. That next semester I rotated in Paul’s lab and once again knew I wanted to have him as a mentor. The projects in his lab, combined with his passion for research, challenged me to think in new and innovative ways. When it came time to decide what lab I would choose I was torn. But then Paul presented a project that Maureen saw as an opportunity for collaboration, and I no longer had to choose. I remember feeling so relieved and happy and it has been a crazy, amazing ride ever since.

I hope one day I can be as great of a mentor as you both are.

I am also very lucky to have worked with some exceptional scientists in both the

Kane and Shapiro labs. From my first rotation, through these past five years, the endless guidance of Dr. Jianshi Yu from the Kane Lab has been invaluable to me. I am beyond grateful to have been able to work alongside such an insightful, detail-oriented biologist. I would like to thank him for taking the time to train me, trouble shoot problems, and for passing on so much of his wisdom. I would also like to thank Dr. Lenka Šlachtová, a former post-doc in the Shapiro Lab, for her endless support and guidance. Whether it was a problem in lab or life she was always there to support me. Even from half-way around the world in the Czech Republic I know I can still count on her help. I would also like to thank

all the current and past members of both labs: Dr. Wenjing Li, Dr. Luke Brewer, Dr.

Dominique Figueroa, Dr. Claire Carter, Dr. William Temple Andrews, Dr. Ludo Muller,

Dr. Praveen Kumar, Tian Liu, Stephanie Shiffka, Stephanie Zalesak, Aaron Tocker, and

Ramon Martinez. From the Kane Lab I would especially like to thank Dr. Wenjing Li for showing me around my first retinoid conference, Stephanie Shiffka for her constant help in my plight to understand affect vs effect, and Stephanie Zalesak for helping with countless retinoid extractions, answering my crazy questions, being my gym buddy, and for all of the cookie breaks. Additionally, my experience in the Shapiro Lab would not have been complete without my big brother Ramon who taught me endless things in lab and life.

I would also like to thank my committee members: Dr. Hongbing Wang, Dr. Lisa

Jones, Dr. Jace Jones, and Dr. Deepak Deshpande. I appreciate all their support and insightful questions that brought different perspectives to my project. I especially want to thank Deepak who was integral to the completion of this project through his immense knowledge of asthma and techniques surrounding its study.

Throughout my time at UMB I had the opportunity to participate in two different fellowship programs including the Chemistry-Biology Interface (CBI) program, and the

UMB-JHU Collaborative Teaching Fellows (CTF) program at Notre Dame of Maryland

University. My mentors in both programs, Dr. Katherine Seley-Radke and Dr. James

Culhane respectively, have both been extremely involved in preparing me for my career goals and I am thankful for their endless support.

Finally, I would like to thank my family and friends for their support and encouragement throughout these past five years. To my cohort that became family, Garrick

Centola, Lizzy Robinson, Jordan Pritts, Tyree Wilson, and Paige Lane, I am thankful the

stars aligned for us all to enter the program at the same time. To Kristina San Juan, our infamous program director, from my summer internship to the past five years, I am so thankful to have had her there every step of the way. Our department would not be the same without her. To my parents, Sarah and Mike Defnet, and sisters, Lori Defnet and

Holly Loh, I am so thankful for your endless support that has given me the confidence to pursue this career and continue to challenge myself every day. Finally, to my husband,

Chuck Miller, thank you for always being my number one fan and pushing me to be a better version of myself every day.

Table of Contents

Dedication ...... iii

Acknowledgements ...... iv

Chapter 1. Overview of current treatments and new therapeutic approaches to treating asthma ...... 1

1.1. Kinase inhibitors in the treatment of obstructive pulmonary diseases ...... 1

1.1.1. Highlights ...... 1

1.1.2. Abstract ...... 1

1.1.3. Introduction ...... 2

1.1.4. Targeted inhibition of kinases in lung and immune cells ...... 8

1.1.5. Conclusions and future directions ...... 13

1.2. Retinoid signaling in inflammatory diseases ...... 16

1.2.1. Introduction ...... 16

1.2.2. Identifying vitamin A signaling by visualizing gene and protein activity, and by biochemical isolation of vitamin A metabolites ...... 16

1.2.3. Retinoids as therapeutics ...... 30

1.3. Aims of the thesis ...... 34

Chapter 2. Effects of ATP-competitive and function-selective ERK inhibitors on airway smooth muscle cells proliferation ...... 37

2.1. Abstract ...... 37

2.2. Introduction ...... 38

2.3. Materials and Methods ...... 40

2.3.1. Chemicals and Reagents ...... 40

2.3.2. ASM cell isolation ...... 40

2.3.3. Cell culture ...... 41 vii

2.3.4. Cell proliferation assays ...... 41

2.3.5. Cytotoxicity assays ...... 41

2.3.6. AP-1 promotor luciferase assays ...... 41

2.3.7. ASM cell treatments and lysate preparation ...... 42

2.3.8. Immunoassays ...... 42

2.3.9. IL-6 ELISA assay ...... 43

2.3.10. Sircol assay ...... 43

2.3.11. Mass spectrometry ...... 43

2.4. Results ...... 45

2.4.1. Function-selective ERK inhibitors block PDGF-induced ASM cell proliferation ...... 45

2.4.2. Function-selective ERK inhibitors prevent AP-1-mediated gene expression . 47

2.4.3. ATP-competitive and function-selective ERK inhibitors have similar, yet distinct, effects on the expression of PDGF-regulated proteins...... 50

2.5. Discussion ...... 57

Chapter 3. Dysregulated retinoic acid signaling in airway smooth muscle cells in asthma ...... 62

3.1. Abstract ...... 62

3.2. Introduction ...... 63

3.3. Materials and Methods ...... 66

3.3.1. Chemicals and Reagents ...... 66

3.3.2. Human lung tissue isolation ...... 66

3.3.3. Murine model of asthma ...... 66

3.3.4. ASM cell isolation and cell culture ...... 67

3.3.5. Sample preparation for retinoid quantification ...... 67 viii

3.3.6. Quantification of retinoids (RA, retinol, and retinyl ester) ...... 68

3.3.7. RNA isolation and real-time qPCR analysis ...... 69

3.3.8. Cell proliferation assays ...... 70

3.3.9. AP-1 promoter luciferase assays ...... 70

3.3.10. Proteomic mass spectrometry ...... 71

3.3.11. Statistical Analysis ...... 72

3.4. Results ...... 72

3.4.1. Altered RA homeostasis in lung tissues obtained from human donors with asthma and HDM-challenged mice...... 72

3.4.2. Genes related to retinoid transport, metabolism, and signaling are altered in lungs from human donors with asthma...... 74

3.4.3. Expression of proteins involved in RA metabolism and signaling are altered in asthmatic lungs...... 78

3.4.4. Levels of RA are reduced in ASM cells derived from human asthmatic lung tissue...... 82

3.4.5. RAR agonist and ATRA inhibit PDGF-induced cell proliferation in ASM cells...... 84

3.4.6. RARγ agonist and ATRA inhibit AP-1 activity in human ASM cells...... 86

3.5. Discussion ...... 86

Chapter 4. Targeting the ERK and RA pathway has an additive effect in controlling ASM cell proliferation via the AP-1 complex ...... 92

4.1. Abstract ...... 92

4.2. Introduction ...... 93

4.3. Materials and Methods ...... 95

4.3.1. Chemicals and Reagents ...... 95

4.3.2. ASM cell isolation ...... 95

4.3.3. Cell culture ...... 95

4.3.4. Sample preparation for retinoid quantification ...... 95

4.3.5. Retinoid quantification ...... 96

4.3.6. Cell proliferation assays ...... 96

4.3.7. AP-1 promotor luciferase assays ...... 96

4.3.8. ASM cell treatments and lysate preparation ...... 97

4.3.9. Immunoassays ...... 97

4.4. Results ...... 98

4.4.1. PDGF does not influence retinoid production within ASM cells...... 98

4.4.2. RAR agonists in combination with SF-3-030 have an additive effect on inhibiting ASM cell proliferation...... 98

4.4.3. AP-1 promoter activity and downstream targets are inhibited by a combination of RAR agonists and SF-3-030...... 100

4.5. Discussion ...... 101

Chapter 5. Conclusions and Future Directions ...... 104

Appendix 1. Introduction to Kinases, Cellular Signaling, and Kinase Inhibitors...... 108

Appendix 2. Avoiding or Co-opting ATP Inhibition: Overview of Type III, IV, V, and VI Kinase Inhibitors ...... 124

Appendix 3. Protein Kinase Interactions with Regulatory and Effector Proteins ...... 156

Appendix 4: Identifying vitamin A signaling by visualizing gene and protein activity, and by quantification of vitamin A metabolites ...... 180

References ...... 218

List of Tables Table 1.1. Clinical trials evaluating kinase inhibitors for treatment of asthma or COPD. . 8

Table 1.2 Summary of Retinoic Acid Signaling Reporters ...... 30

Table 1.3 Naturally occurring pan-RAR agonist, ATRA, and isoform-specific RAR agonists...... 33

Table 2.1. List of proteins that increase/decrease after 8 or 24 hour exposure to ERK inhibitors...... 52

Table 2.2. Changes in proteins associated with ASM cell proliferation and airway remodeling induced by PDGF followed by treatment with SF‐3‐030 or ulixertinib for 8 or 24 h...... 56

Table A3.1. Typical MAP2K (MEK) isoforms and their corresponding MAPK substrates...... 160

Table A3.2. Sequence alignment of amino acid residues in the N-terminus of MAP2K (MEK) isoforms...... 161

Table A3.3. Sequence alignment of C-terminal acidic residues (green shading) that form the common docking (CD) residues and contribute to the D-domain recruitment site (DRS) on human MAPK isoforms...... 161

Table A3.4. Sequence alignment of amino acid residues in the N-terminus that contribute to the DRS...... 161

Table A4.1. Select RA levels in mouse embryos and tissues...... 187

Table A4.2. Comparison of Different Reporters and Quantification Methods for Cellular Systems ...... 199

Table 4.3. Troubleshooting for Common Problems When Using In Situ Hybridization 209

Table 4.4. Troubleshooting for Common Problems When Immunostaining...... 217

List of Figures Figure 1.1. Graphical abstract for kinase inhibitors in the treatment of obstructive pulmonary diseases ...... 2

Figure 1.2. Kinase signaling pathways involved in obstructive pulmonary disease ...... 4

Figure 1.3 Summary diagram of transport, signaling and degradation of vitamin A metabolism and RA synthesis ...... 19

Figure 1.4. Summary of ERK and RA signaling that leads to AP-1 complex formation and ASM cell proliferation ...... 36

Figure 2.1. ERK1/2 inhibitors block PDGF‐induced ASM cell proliferation ...... 46

Figure 2.2. SF‐3‐030 does not affect the phosphorylation of ERK1/2 or Akt1 ...... 48

Figure 2.3. SF‐3‐030 inhibits AP‐1 activity ...... 49

Figure 2.4. SF‐3‐030 differentially affects the expression of AP‐1 proteins ...... 49

Figure 2.5. Summary of proteins that significantly increased/decreased after 8 or 24 h exposure to ERK inhibitors ...... 51

Figure 2.6. Effect of ulixertinib and SF‐3‐030 on TGF‐β, IL‐6, and collagen signaling . 55

Figure 2.7. Pathways and networks affected by ERK inhibitors ...... 60

Figure 3.1. Retinoic Acid Signaling Pathway...... 64

Figure 3.2. Levels of RA, ROL, and RE are reduced in lung tissues obtained from donors with asthma and HDM-challenged mice...... 74

Figure 3.3 (next page) mRNA expression of retinoid chaperones, pathway enzymes, receptors, and targets genes are dysregulated in human lungs from asthmatic donors .... 76

Figure 3.4. Enzyme abundances, as determined by proteomic analysis, show retinoic acid homeostasis is dysregulated similarly in human and murine lung ...... 80

Figure 3.5. Protein expression of retinoid-related, ASM marker, AP-1 regulated, and asthma associated proteins in human asthmatic lung tissue ...... 81

Figure 3.6. RA basal levels and RA biosynthesis capacity reduced in human ASM cells derived from lung donors with asthma ...... 83

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Figure 3.7. Treatment with RAR agonists inhibits PDGF-induced proliferation and AP-1 promoter activity in ASM cells ...... 85

Figure 3.8 RAR agonists do not change RA production within normal or asthmatic airway smooth muscle cells ...... 85

Figure 3.9. Summary of genes and proteins identified in this study that affect RA signaling in the human lung ...... 88

Figure 4.1. PDGF does not affect retinoid production within ASM cells ...... 99

Figure 4.2. Effect of RAR agonists in combination with SF-3-030 on ASM cell proliferation...... 100

Figure 4.3. Effect of RAR agonists in combination with SF-3-030 on ASM cell AP-1 activity and downstream targets...... 101

Figure A1.1. FDA-approved small-molecule kinase inhibitors (1999-2018)...... 113

Figure A1.2. Receptor-mediated kinase signaling networks ...... 121

Figure A1.3. General overview of protein kinase structure ...... 122

Figure A2.1. Graphical description of the various approaches to manipulate kinase activity...... 125

Figure A2.2. Structure of MEK1 and allosteric regions near ATP-binding site ...... 128

Figure A2.3. Structure of MEK1 and cobimetinib ...... 129

Figure A2.4. Interactions between Akt1 and a type III inhibitor ...... 130

Figure A2.5. Interactions between Akt1 and ARQ 092 ...... 131

Figure A2.6. Interactions between TrkA and compound 23 ...... 132

Figure A2.7. Interactions between a type IV biaryl tetrazole and JNK1 ...... 137

Figure A2.8. Interactions between compound 10 (magenta lines) and p38α MAP kinase ...... 138

Figure A2.9. Type IV inhibition of Abl ...... 140

Figure A2.10. Interactions between PDK1 and compound RS1 ...... 142

Figure A2.11. Structural domains in c-Src (PDB:2SRC) ...... 145 xiii

Figure A2.12. Structure of bivalent compound SBP3 and ERK2 [PDB: 5V62] ...... 147

Figure A2.13. The chemical structures of (a) afatinib, (b) osimertinib, (c) dacomitinib, and (d) neratinib are shown ...... 152

Figure A2.14. Structure of borussertib in complex with Akt1 (PDB: 6HHF) ...... 155

Figure A3.1. The D-domain recruitment site (purple and green spheres) sits adjacent to the DFG motif (yellow) and opposite of the activation sites (blue)...... 162

Figure A3.2. Spatial organization of the DRS and FRS on MAP kinases ...... 164

Figure A3.3. Structural interactions between ERK2 and activator (MEK2) and substrate (RSK1) peptides (magenta lines) ...... 166

Figure A3.4. Structural interactions between ERK2 and the kinase domain of RSK1 .. 167

Figure A3.5. Structural interactions between p38α MAPK activator (MEK3) and substrate (MEF2A) peptides ...... 168

Figure A3.6. Structural interactions between p38α MAP kinase and full length MK2 (pdb: 2ONL)...... 169

Figure A3.7. Structural interactions between p38α MAP kinase, TAB1, and a TAB1 inhibitor ...... 171

Figure A3.8. Structural interactions between JNK1 and peptides representing activator (MEK7) or regulatory (JIP1) proteins...... 172

Figure A3.9. Structural interactions between JNK3 and the D-domain peptides representing (a) JIP1 [pdb:4H39], (b) SAB [pdb:4H3B], and (c) ATF2 [4H36]

Figure A3.10. Structural interactions between JNK1 and the catalytic domain of MKP7 [pdb:4YR8] ...... 176

Figure A4.1. Example of retinoid absorbance spectra that are typically used for determining the concentration of retinol, RA and retinal ...... 183

Figure A4.2. Evaluating RA reporter response in the F9 RARE-LacZ stable cell line: β- Galactosidase reporter assay indicating RA-Signaling Activity as compared to RA levels ...... 192

Figure A4.3. Evaluating RA reporter response in the two-hybrid Gal4-RAR;UAS-tk- Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels ...... 196

xiv

Figure A4.4. Evaluating RA reporter response in the two-hybrid Gal4-RAR;UAS-tk- Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels produced from retinol treatment ...... 196

Figure A4.5. Comparison of temporal responses of different cellular assays to determine RA levels or RA signaling ...... 200

Figure A4.6. Comparison of representative reproducibility between the two-hybrid Gal4- RAR;UAS-tk-Gaussia luciferase reporter in HEK293 cells as compared to RA levels . 201

Figure A4.7. Methods to identify components of vitamin A metabolism and RA synthesis ...... 202

List of Abbreviations ABCA1 ATP-binding cassette family A member 1 AHR airway hyper-responsiveness AhR aryl hydrocarbon receptor Akt protein kinase B AP‐1 activator protein‐1 ASM airway smooth muscle ATRA all-trans-retinoic acid CASP1 caspase 1 CCND1 cyclin d-1 COL collagen CRABP2 cellular retinoic-acid binding protein 2 CREB cAMP response element binding CYP Cytochrome P450 DHRS Dehydrogenase/reductase SDR family member DRS D-recruitment site ECM extracellular matrix EGFR epidermal growth factor receptor ERK extracellular signal-regulated kinase FABP5 Fatty acid-binding protein 5 FRS F‐recruitment site GSK-3β glycogen synthase kinase 3β HDM house dust mite HMGB1 high mobility group box 1 IPA ingenuity pathway analysis ITGA integrin subunit α JNK c-Jun N-terminal kinase LDH lactate dehydrogenase

xvi

MAPK mitogen-activated protein kinase PDGF platelet‐derived growth factor PI3K phosphoinositide 3-kinase Phospho phosphorylated PTX3 pentraxin 3 RA retinoic acid RAR retinoic acid receptor RBP retinol binding protein RDH retinol dehydrogenase REA retinyl acetate RSK ribosomal s6 kinase RTK receptor tyrosine kinase TCAF1 TRPM8 channel associated factor 1 TF transcription factor TNFRS11B tumor necrosis factor receptor superfamily member 11b TP53 tumor protein p53 TRE TPA-responsive elements VEGFA vascular endothelial growth factor A

xvii

Chapter 1. Overview of current treatments and new therapeutic approaches to treating asthma

1.1. Kinase inhibitors in the treatment of obstructive pulmonary diseases1

1.1.1. Highlights

• Obstructive pulmonary disease is caused by inflammation.

• Inflammatory signals activate kinase signaling pathways.

• Kinases regulate transcription factors that modulate the proliferative and secretive functions of airway cells.

• Chronic inflammation leads to airway remodeling and exacerbation of airflow obstruction.

• Kinase inhibitors may mitigate airway remodeling and pathology of obstructive pulmonary disease.

1.1.2. Abstract

Chronic pulmonary diseases, including chronic obstructive pulmonary disease (COPD) and asthma, are major causes of death and reduced quality of life. Characteristic of chronic pulmonary disease is excessive lung inflammation that occurs in response to exposure to inhaled irritants, chemicals, and allergens. Chronic inflammation leads to remodeling of the airways that includes excess mucus secretion, proliferation of smooth muscle cells, increased deposition of extracellular matrix proteins and fibrosis. Protein kinases have been implicated in mediating inflammatory signals and airway remodeling associated with reduced lung function in chronic pulmonary disease. This review will highlight the role of

1 Defnet, A.E.; Hasday, J.D.; Shapiro, P. Kinase inhibitors in the treatment of obstructive pulmonary diseases. Current Opinion in Pharmacology. 2020, 51, 11-18.

protein kinases in the lung during chronic inflammation and examine opportunities to use protein kinase inhibitors for the treatment of chronic pulmonary diseases (Fig 1.1).

Figure 1.1. Graphical abstract for kinase inhibitors in the treatment of obstructive pulmonary diseases.

1.1.3. Introduction

Obstructive pulmonary disease

Asthma and chronic obstructive pulmonary disease (COPD) are the two most common chronic pulmonary diseases, affecting approximately 300 million and 250 million individuals worldwide, respectively, and causing 250 000 and 3.1 million deaths annually, respectively (1). Asthma and COPD share symptoms of cough and dyspnea, the presence of chronic airway inflammation driven by exposure to inhaled immune stimuli, airway wall thickening, and the contribution of cellular senescence of airway epithelium. But the two diseases differ in the segment of the bronchial tree affected, the nature of the inflammation, the inciting immune stimulants, and their long-term course.

In asthma, the entire airway is involved while in COPD, pathologic changes are most pronounced in the small airways. Inflammation in asthma is typically allergen-driven and IgE-driven, and involves TH2 lymphocytes, mast cells and eosinophils (2). In COPD,

inflammation is driven by inhaled toxins and irritants, including those in tobacco smoke, non-tobacco biomass smoke, air pollution, and inhaled endotoxin, and is characterized by

TH1 and TH17 lymphocytes, CD8+ lymphocyte predominance, neutrophil infiltration, and macrophage activation (3). Inhaled therapy with short-acting and long-acting beta agonists and corticosteroids are effective in both diseases. However, airway obstruction in asthma is usually more reversible with beta agonist therapy and more responsive to corticosteroid therapy than in COPD (4). Corticosteroids have been shown to reduce the rate of exacerbations, airway inflammation, and the rate of quality of life deterioration in COPD patients; however, an increased risk of pneumonia along with local and systemic adverse effects has also been observed (5). Inhaled long-acting muscarinic agonists are more effective in COPD than asthma (6). More recently a growing number of injectable biologics targeting specific inflammatory pathways have become available for treating subclasses of asthma, but do not appear to be effective in most patients with COPD. It should be noted that asthma and COPD are both heterogenous diseases with a substantial overlap between the two, including a defined asthma-COPD overlap syndrome (7).

Inflammatory signals and protein kinases

The chronic release of inflammatory cytokines and growth factors from epithelial and immune cells enhances protein kinase signaling pathways and underlies the pathology of asthma and COPD. Several cytokines and growth factors are implicated in chronic pulmonary disease and include the interleukins (IL) IL-1β IL-4, IL-5, IL-6, IL-13, IL-17A,

IL-27, IL-33, interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), epidermal growth factor (EGF), and platelet-derived growth factor

(PDGF) (8-13). Many protein kinases have been implicated in the signal transduction

pathways linking inflammatory mediators and the hyper-contractility of airways, mucus hypersecretion, immune cell infiltration, and airway remodeling that leads to debilitating lung function observed in chronic pulmonary disease (14, 15). Figure 1.2 summarizes protein kinases that are involved in the pathology of asthma and COPD.

Figure 1.2. Kinase signaling pathways involved in obstructive pulmonary disease. Receptor tyrosine kinases (RTK) and non-receptor tyrosine kinases (NRTK; Abl, c-Src, Syk, Lyn) regulate mitogen-activated protein (MAP) kinases including the extracellular signal-regulated kinases (ERK), p38 MAP kinases, and c-Jun N-terminal Kinases (JNK). MAP kinases are activated by the MAP/ERK kinases (MEK1/2/3/4/6/7) which are regulated by the MEK kinases (MEKK). Cytokine receptors (CR) activate Janus kinases (JAK) and the phosphatidylinositide 3-kinases (PI3K), which regulate protein kinase B (AKT), mechanistic target of rapamycin (mTOR), and IκB kinase (IKK). Increased adenosine in the lungs of asthma and COPD patients activates the A2B adenosine receptor (A2BAR), which regulates ERK through protein kinase C (PKC) and protein kinase A (PKA) through adenylate cyclase (AC) production of cyclic 3′5′-adenosine monophosphate (cAMP). Transcription factor (TF) targets include signal transducer and activator of transcription proteins (STAT), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), activator protein-1 (AP-1), and cAMP response element-binding protein (CREB).

Protein kinases involved in obstructive lung disease

Inflammatory signals mediate the pathology of obstructive lung disease through the activation of protein kinase activity (16). Cytokine receptors (CR) and receptor tyrosine kinases (RTK) at the plasma membrane communicate cytokine and growth factor signals through several mitogen-activated protein (MAP) kinases, phosphatidylinositide 3-kinases

(PI3K), and Janus kinases (JAK). Inflammation causes increased adenosine generation, which via activation of G-protein coupled adenosine receptors (A2BAR) and downstream kinase signaling cascades, contributes to the pathologic changes in asthma and COPD (17).

Gene expression associated with inflammation and tissue remodeling is regulated predominantly by a subset of transcription factors that include nuclear factor kappa-light- chain-enhancer of activated B cells (NF-κB), activator protein-1 (AP-1), cAMP response element-binding protein (CREB), and signal transducer and activator of transcription

(STAT) proteins (18).

MAP kinases that respond to cellular stress, such as the c-Jun N-terminal kinases

(JNK) and p38 MAP kinases, have long been implicated in mediating inflammatory signals relevant to lung disease (16, 19). However, to date, none of the JNK or p38 MAP kinase inhibitors have shown efficacy in clinical trials and are dose limiting due to unwanted toxicity and side effects. Targeted inhibition of pro-inflammatory p38 MAP kinase substrates such as mitogen-activated protein kinase activated protein kinase-2

(MAPKAPK-2 or MK2) may overcome toxicity issues associated with p38 inhibitors and treating chronic pulmonary disease (20). MK2 is a mediator of inflammatory signals such as TNF-α, IL-6, and IL-1β so MK2 mediators might further reduce the inflammatory response (21). Eynott et al. provided evidence that targeted inhibition of JNK could

mitigate allergen-induced inflammation and proliferation of airway epithelial and smooth muscle cells (22). While one phase II clinical trial evaluating the JNK inhibitor Tanzisertib for treating idiopathic pulmonary fibrosis ended due to lack of efficacy, no JNK inhibitors are currently being tested for asthma or COPD.

Mitogen activation of the extracellular signal-regulated kinases (ERK) MAP kinases in airway smooth muscle (ASM) cells stimulates cell proliferation and subsequent airway remodeling associated with asthma (23). This was supported by studies that showed that serum from atopic asthma patients enhanced the expression of cyclin D1, which increases proliferation of human ASM cells (24). Activated ERK signaling enhances cell proliferation by increasing the expression of cyclin D1.

There is evidence that protein kinases associated with deregulated angiogenesis contribute to the progression of chronic lung disease including COPD (25). Angiogenic factors such as cytokines and growth factors that are released as a result of obstructive pulmonary disease progression leads to the stimulation of direct and indirect proangiogenic markers that generate and stabilize new blood vessels (26). This microvascular dysfunction leads to re-modulation and inflammation of the bronchi. Recent studies suggest that targeted inhibition of inflammation-mediated activation of the receptor tyrosine kinases vascular endothelial growth factor receptor (VEGFR) and fibroblast growth factor receptor-2 (FGFR-2) reduces angiogenesis associated with lung remodeling in COPD (26).

Similarly, a small clinical study suggested that inhibition of PDGF and the related c-Kit receptor tyrosine kinase with Masitinib is effective in severe corticosteroid-dependent asthma (27).

In COPD patients, protein kinases play an important role in the loss of tissue architecture by enhancing degradation of the extracellular matrix by proteinases such as matrix metalloproteinases-9 (MMP-9) (28). Proinflammatory triggers including allergens, cigarette smoke, bacterial lipopolysaccharides (LPS), interleukins (IL-17 and IL-1β), and other inflammatory signals that induce an oxidative stress response, activate MAP kinases and PI3K signaling, which enhances AP-1-mediated expression of MMP-9 (22, 29-31).

Another key regulator of inflammatory signals is the NF-κB transcription factor. Targeted inhibition of the inhibitor of κB kinase (IKK) is a potential approach to prevent NF-κB translocation to the nucleus and inflammatory gene expression. The status of past and current clinical trials evaluating protein kinase inhibitors for treatment of asthma or COPD is listed in Table 1.1.

Target Compound Stage Disease Route Current Status Identifier p38 MAPK Dilmapimod Phase 2 COPD Oral No Results Posted NCT005647 46 Losmapimod Phase 2 COPD Oral Discontinued: Not NCT022993 effective (32) 75 COPD Oral Discontinued: Not NCT015418 effective (33) 52 PH-797804 Phase 2 COPD Oral No Results Posted NCT005599 10 PF-03715455 Phase 2 Asthma Inhaled Terminated NCT022190 48 Phase 2 COPD Inhaled Terminated NCT023666 37 AZD7624 Phase 2 COPD Inhaled Discontinued: Not NCT022384 Effective (34) 83 Phase 2 Asthma Inhaled No Results Posted NCT027537 64 p38 and RV-568 Phase 2 COPD Inhaled No Results Posted NCT014752 Src 92 PI3K GSK2269557 Phase 2 COPD Inhaled Completed: NCT021306 Acceptable safety 35 profile for progression to larger study (35) Phase 2 COPD Inhaled Completed: NCT031895 Progression to 89 Phase IIb study supported (36) RV-1729 Phase 1 COPD Inhaled No Results Posted NCT021403 46 RTK BIBW 2948 Phase 2 COPD Inhaled Not effective (37) NCT004231 37 Masitinib Phase 3 Asthma Oral Ongoing NCT037710 40 Phase 3 Asthma Oral Ongoing NCT014491 62 Imatinib Phase 2 Asthma Oral Completed: NCT010976 Decreased airway 94 hyperresponsivene ss, mast-cell counts, and tryptase release (38) c-Kit/Abl Imatinib Phase 2 Asthma Oral Recruiting NCT041299 JAK1 Itacitinib 31 Table 1.1. Clinical trials evaluating kinase inhibitors for treatment of asthma or COPD.

1.1.4. Targeted inhibition of kinases in lung and immune cells

Epithelial cells

Inflammation-inducing chemicals and irritants disrupt airway epithelium and stimulate aberrant kinase signaling both within epithelial cells. Increased expression of the receptor tyrosine kinase EGFR, and its ligands have been reported in the epithelium of

asthmatic airways (39, 40). Activation of epithelial EGFR can lead to corticosteroid- insensitivity and plays a key role in airway remodeling, mucus secretion, and inflammation.

The EGFR-tyrosine kinase inhibitors, Erlotinib and Osimertinib, attenuate EGFR signaling and expression of IL-6 and IL-8 in a dose-dependent manner in human bronchial epithelial cells in vitro stimulated with house dust mite (HDM) allergen (41). However, Osimertinib was more effective than Erlotinib at inhibiting EGFR auto-phosphorylation and downstream PI3K/AKT and STAT3 signaling (41). In COPD patients, lung fibrosis can be caused by the epithelial-mesenchymal transition (EMT). Giacomelli et al. recently determined that activation of the A2B adenosine receptor (A2BAR) decreased the expression of epithelial marker E-cadherin while increasing the mesenchymal markers vimentin and N-cadherin. Upon further investigation, these studies found that PKA signaling can counteract EMT while ERK signaling can promote EMT. The use of PKA or

ERK inhibitors, which enhanced or inhibited the EMT, respectively, suggested that targeted manipulation of kinase signaling could be a mechanism to control EMT related to

COPD (42).

Goblet cells

The mucus secreting goblet cells normally provide protection to the epithelial layer of cells but, inappropriate mucus secretion can contribute to chronic cough and sputum production that reduces quality of life in patients with chronic pulmonary disease.

Cytokines released during lung inflammation lead to an increase in the number of goblet cells causing enhanced mucus production, which reduce the airway luminal diameter and increase airway resistance. The goblet cell number increases due to basal cell differentiation shifting from a ciliated epithelial cell fate toward a goblet cell fate.

Strategies to prevent goblet cell hyperplasia or persistent goblet cell differentiation (GCD) include pharmacological inhibition of kinase signaling pathways (43). Several signaling pathways regulate goblet cell differentiation; however, the EGFR family and downstream

PI3K and ERK signaling pathways are all viewed as candidates for inhibition in preventing persistent GCD (43). Unfortunately, an EGFR inhibitor (BIBW 2948) failed to show efficacy in reducing epithelial mucin in COPD clinical trials (37). While these studies postulated that higher doses may improve efficacy, there is also a strong probability for increased adverse drug events.

The role of Rho kinases in airway hyperresponsiveness and inflammatory events has prompted their examination as potential drug targets to treat asthma (44). A recent study by Zhang et al. found that Rho-kinase inhibitors can attenuate airway mucus hypersecretion and inflammation via the downregulation of IL-13 and AP-1 signaling in a model of HDM-induced asthma (45). The studies also provided evidence that inhibition of

Rho-kinase was as effective as dexamethasone in mitigating asthma pathology in this model, suggesting it could be another treatment option in cases of corticosteroid resistance.

Rho kinase inhibitors are currently being evaluated for the treatment of ocular disorders

(46).

Airway smooth muscle cells

Inflammatory signals in asthma and COPD lead to an increase in ASM cell proliferation that contributes to basal narrowing of airway lumens and bronchoconstriction which combine to cause airway obstruction. Increased ASM cell mass is primarily driven by growth factors such as PDGF and EGF in cooperation with cytokines and chemokines

(47). Since ERK signaling through the AP-1 transcription factor is a central regulator of

PDGF and EGF expression, AP-1 plays a key role in mediating inflammatory signals associated with tissue remodeling in asthma and COPD (48, 49). In a study by Defnet et al., an ATP-competitive ERK inhibitor that blocks all ERK signaling was compared to a novel function-selective ERK inhibitor for inhibition of ASM cell proliferation through

AP-1 (50). This study found that both inhibitors effectively inhibited PDGF-mediated

ASM cell proliferation, AP-1 promoter activity, collagen production, and IL-6 secretion in

ASM cells. Additionally, the function-selective inhibitor allowed some ERK activity, which potentially reduced selective pressure to develop drug resistance, and caused fewer changes in protein expression compared to the ATP-competitive inhibitor suggesting there would be less off-target effects (50).

Alternatively, studies have taken a polypharmacology approach to inhibit kinases for the treatment of patients that have corticosteroid-resistant airway inflammation COPD.

Knobloch et al. evaluated a narrow-spectrum protein kinase inhibitor (NSKI) referred to as

RV1088 that reduces inflammatory signals by targeting p38 MAPK and the c-Src, Syk, and JAK tyrosine kinases (51). The authors found that RV1088 was able to suppress corticosteroid-sensitive and –insensitive cytokine production in in vitro models of COPD and are more effective than single kinase inhibitors of p38 MAPK, Src, or Syk alone.

However, off-target effects of these kinase inhibitors will need further investigation as the promiscuity of some of the current kinase inhibitors has limited their clinical applications.

A phase II clinical trial (NCT01867762) evaluating the efficacy and safety of another NSKI

(RV568) that targets p38 MAPK and c-Src for treatment of moderate to severe COPD has yet to post results.

Immune cells

Targeted inhibition of kinases in immune cells has potential to mitigate airway remodeling and hyperresponsiveness associated with obstructive pulmonary disease. Mast cells, T-cells, eosinophils, and neutrophils all play key roles in the inflammatory response seen in obstructive pulmonary diseases (2). Mast cell activation involves the RTK c-Kit, non-receptor tyrosine kinases, such as Lyn and Syk, PKC, and ERK MAP kinase signaling

(52). PI3K isoforms play a prominent role in the differentiation, proliferation, survival, and cytokine production of immune cells (53) and pharmacological inhibition of PI3K suppresses T-helper cell cytokine production and eosinophil infiltration in mice challenged with ovalbumin (54). Similarly, inhibition of the JAK-STAT signaling pathway suppresses the activity of neutrophils, mast cells, eosinophils, and T-cells (55, 56).

The significant role of the JAK-STAT signaling pathway in the expression of cytokines and interferons involved in pulmonary disease makes it an attractive therapeutic target. Previous work utilized an orally administered JAK1/2 inhibitor in a mouse model of asthma that showed promising physiological changes, but due to systemic side effects, it did not move into patients (57, 58). To address this setback, Dengler et al. synthesized an inhalable small molecule JAK1 inhibitor called iJak-381 for local JAK1 inhibition in the lung (55). This inhibitor shows local inhibition of ovalbumin-induced JAK1 activity in rodents with no observed changes in systemic JAK1 activity. Furthermore, iJAK-381 suppressed STAT6 and IL-13, reduced airway hyperresponsiveness in mice, and was more potent than corticosteroids in suppressing neutrophil-driven inflammation caused by clinically relevant allergens (55). As indicated above, new clinical trials evaluating oral

JAK1 inhibitors for asthma therapy began recruiting patients at the end of 2019. Time will

tell whether systemic side effects due to oral delivery will limit the efficacy of these compounds.

1.1.5. Conclusions and future directions

Currently, obstructive lung disease treatments focus on counteracting episodes of bronchospasm and reducing allergic inflammation through corticosteroids, which, although such strategies have shown success, they neither cure nor prevent disease progression (59-61). Kinase inhibitors could provide a more targeted therapeutic option to meet this unmet need.

The effectiveness of protein kinases inhibitors will likely depend on delivery methods that limit off-target effects. The ubiquitous functions of protein kinases in many cell types have prompted new approaches to deliver inhibitors through an inhaled route and reduce systemic off-target effects when the drugs are taken orally. Promising clinical results with Nemiralisib (GSK2269557), a PI3Kδ isoform-selective inhibitor, support the efficacy of the inhaled route of delivery (36). Bach et al. have identified potent pan-JAK inhibitors that show good retention in the lung following intra-tracheal administration (62).

Importantly, these compounds reduced LPS-induced lung inflammation in a mouse model and had poor oral bioavailability suggesting reduced unwanted systemic effects (62).

Mitigation of off-target effects of kinase inhibitors requires new approaches to block kinase functions associated with disease but preserve functions that may be desirable.

Most protein kinases have dozens of substrates with some involved in promoting a response such as proliferation or inflammation while other substrates are inhibiting that response.

To date, nearly all small molecule protein kinase inhibitors approved for clinical use compete with ATP in the catalytic site, which blocks all enzymatic activity. Not only does

this approach block desirable kinase functions but given the highly conserved nature of the

ATP binding site on kinases, ATP-competitive inhibitors are generally non-specific and affect the activity of other kinases. In addition, cells invariably develop resistance to ATP- competitive kinase inhibitors. One approach to mitigate off-target effects and the development of drug resistance is to identify compounds that are function-selective.

Currently, this approach is being used to develop inhibitors of the ERK and p38 MAP kinases (50, 63, 64). These approaches use structural information on the interactions between kinases and substrates and apply computational predictions and experimental testing to identify compounds that disrupt specific interactions between the kinase and substrates involved in disease. In the context of obstructive pulmonary disease, the goal would be to identify compounds that block pro-inflammatory signals that cause tissue damage and remodeling while preserving beneficial anti-inflammatory signals.

Alternatively, polypharmacology approaches could mitigate tissue remodeling in chronic obstructive pulmonary disease. Targeted inhibition of signaling pathways that regulate key transcription factors involved in the pathology of asthma and COPD may provide therapeutic benefits. For example, ERK activation of AP-1 promotes increased

ASM cell proliferation, while activation of the retinoic acid receptor (RAR) is a negative regulator of AP-1 and ASM cell proliferation (65, 66). Loss of retinoic acid (RA) signaling has been linked to hypertrophy and hypercontractility of ASM cells, suggesting defects in

RA may contribute to obstructive pulmonary disease (67). Thus, combining ERK inhibitors and RAR agonists could effectively control ASM cell proliferation and airway remodeling in asthma.

Obstructive lung diseases pose many therapeutic challenges due to the diversity of inflammatory signals released and cell types affected. Further, chronic inflammation leads to airway remodeling and exacerbation of airflow obstruction. However, protein kinases play a key role in regulating transcription factors that modulate the proliferative and secretive functions of airway cells. As such, appropriately designed and targeted kinase inhibitors may mitigate airway remodeling and pathology of obstructive pulmonary disease. Further research on the basic mechanisms involved in the pathology of obstructive lung disease will help identify the most appropriate kinase targets, the best approach to design selective inhibitors, and the development of efficacious drugs to combat obstructive lung diseases.

1.2. Retinoid signaling in inflammatory diseases

1.2.1. Introduction

Literature about the direct role of Vitamin A in obstructive pulmonary diseases, such as asthma and COPD, is currently limited. To learn more about how Vitamin A signals within the body and how it can be quantitatively studied, we participated in a collaborative study with Dr. Alexander Moise and Dr. Paul Trainor. This work provides a basis for studying retinoids in the lung through the context of other inflammatory diseases. The introductory portion of this paper is included in the following section 1.2.2. as it is pertinent to the current study. The remaining protocol sections, data, and overall conclusions can be found in Appendix 4. In section 1.2.3. the concept of retinoids as therapeutics is discussed in the context of other inflammatory diseases.

1.2.2. Identifying vitamin A signaling by visualizing gene and protein activity, and by biochemical isolation of vitamin A metabolites 2

Abstract

Vitamin A (retinol) is an essential nutrient for embryonic development and adult homeostasis. Signaling by vitamin A is carried out by its active metabolite, retinoic acid

(RA), following a two-step conversion. RA is a small, lipophilic molecule that can diffuse from its site of synthesis to neighboring RA-responsive cells where it binds retinoic acid receptors within RA response elements of target genes. It is critical that both vitamin A and RA are maintained within a tight physiological range to protect against developmental disorders and disease. Therefore, a series of compensatory mechanisms exist to ensure appropriate levels of each. This strict regulation is provided by a number synthesizing and

2 Shannon, S.R.; Yu, J.; Defnet, A.E.; Bongfeldt, D.; Moise, A.R.; Kane, M.A.; Trainor, P.A. Identifying vitamin A signaling by visualizing gene and protein activity, and by quantification of vitamin A metabolites. Methods in Enzymology: Retinoid Signaling Pathways, 2020, 637, 367-415.

metabolizing enzymes that facilitate the precise spatiotemporal control of vitamin A metabolism, and RA synthesis and signaling. In this chapter we describe protocols that 1.) biochemically isolate and quantify vitamin A and its metabolites and 2.) visualize the spatiotemporal activity of genes and proteins involved in the signaling pathway.

Keywords vitamin A, retinol, embryonic development, adult homeostasis, retinoic acid, retinoic acid receptors, retinoic acid response elements

Introduction

Vitamin A and retinoic acid synthesis and signaling

Vitamin A (retinol) is an essential nutrient, critical for all stages of life from embryonic development through adult homeostasis. It is found in the diet in two primary forms, provitamin A carotenoids and preformed vitamin A (68). Provitamin A carotenoids are derived from plant sources whereas preformed vitamin A comes largely from animal products such as liver, milk and eggs (68). Once taken into the body vitamin A is metabolized to its active metabolite retinoic acid (RA), which directly regulates gene activity and function. It is critically important to maintain appropriate levels of vitamin A and RA throughout life as both excess and deficiency are associated with birth defects and adult disorders.

Vitamin A (retinol) enters the body as either preformed vitamin A or provitamin A carotenoids. Preformed vitamin A is hydrolyzed and taken up by enterocytes of the intestinal lumen (Figure 1.3). Once inside the cell, it is esterified and packaged into chylomicrons that are secreted into circulation (69). A large proportion of the retinol within these chylomicrons is acquired by liver hepatocytes and stored as retinyl esters in hepatic stellate cells (70). Stores of retinol esters can then be mobilized when needed via hydrolysis back to retinol, which is transported throughout the vasculature by retinol binding protein,

RBP4 (71, 72). Target cells express the stimulated by retinoic acid 6 receptor (STRA6), which binds to circulating retinol, internalizing it for conversion to retinoic acid (73, 74).

Once inside a cell, retinol is bound by cellular retinol binding proteins (CRBP) and then undergoes two consecutive oxidation reactions to become retinoic acid (Figure 1.3).

In the first reaction, retinol is oxidized to all-trans-retinal (also called retinaldehyde) by microsomal retinol dehydrogenase 10 (RDH10) or other short-chain retinol dehydrogenases that recognize CRBP-bound retinol as substrate (75, 76). RDH10 is the critical enzyme necessary for the regulation of this first oxidation step during embryonic development (77) whereas other RDH enzymes contribute postnatally (75, 78). In situations of vitamin A excess, where retinol exceeds the amount of CRBP protein, members of the cytosolic alcohol dehydrogenases (ADH) family may catalyze this reaction postnatally (79, 80). An important feature of this oxidation step is that it is reversible, allowing for the conversion of retinal back to retinol. The reduction of retinal to retinol is performed by the retinaldehyde reductase, dehydrogenase/reductase (SDR) member 3

(DHRS3, or retSDR1), which in doing so provides a mechanism for helping to regulate and balance appropriate levels of retinol, retinal and RA (81-84). An alternative pathway to produce retinal is via conversion of -carotene (Figure 1.3), the principal source of which comes from the provitamin A carotenoids in various fruits and vegetables (68). Similar to retinol, -carotene is transported by chylomicrons, and converted into retinal in target cells by BCDO1 (b-carotene-15,15-dioxygenase) (85-87). This secondary pathway may be used

for RA synthesis, as well as vitamin A storage via DHRS3 conversion of retinal back to retinol.

Figure 1.3 Summary diagram of transport, signaling and degradation of vitamin A metabolism and RA synthesis. Retinol is transported throughout the vasculature by retinol binding protein 4 (RBP4) and taken up by target cells that express the retinoic acid receptor (STRA6). Once in a cell, retinol is transported by cellular retinol binding proteins (CRBP) and oxidized in a two-step reaction into retinoic acid (RA). In the first step, retinol is converted in a reversible reaction by microsomal retinol dehydrogenase 10 (RDH10) or cytosolic alcohol dehydrogenases (ADH) into retinal (also called retinaldehyde), which can be reduced back to retinol by the retinal reductase, DHRS3. Alternatively, b-carotene can be converted by BCDO1 (b- carotene-15,15-dioxygenase) into retinal. In a second conversion, retinal is oxidized by retinaldehyde dehydrogenases, ALDH1A1, ALDH1A2, and ALDH1A3 into RA. RA then diffuses from the synthesizing cell and is either degraded by CYP26 enzymes or participates in regulating cell signaling in target cells. RA is transported in RA-responsive cells by cellular retinoic acid binding protein (CRABP2) to the nucleus where it functions as a ligand for retinoic acid receptors bound to retinoic acid response elements (RAREs) of target genes. The binding of RA initiates disassociation of corepressors and recruitment of coactivators to initiate transcription of target genes.

The second oxidative step in retinol metabolism converts retinal to RA (Figure 1.3).

This irreversible reaction is carried out by retinaldehyde dehydrogenases including,

ALDH1A1, ALDH1A2, and ALDH1A3 (previously RALDH1, RALDH2 and

RALDH3)(88-90). RA is then transported from the cytosol by cellular retinoic acid binding protein (CRABPII) to the nucleus where it binds to the retinoic acid receptors (RAR)

RAR, RAR and RAR (91). These RARs form heterodimers with the retinoid X receptors (RXR) RXR, RXR or RXR (92), which then regulate gene transcription through their binding to RA response elements (RAREs) of target genes. In the absence of

RA, RAR-RXRs associate with RAREs and repress gene expression through recruitment of co-repressors that include nuclear receptor corepressor (NCoR), silencing mediator of

RA and thyroid hormone receptor (SMRT), as well as histone deacetylases and methyltransferases. In contrast, when RA is present, it binds as a ligand to RAR-RXR and through direct association with RAREs, initiates transcription of target genes by disassociating the corepressors and recruiting co-activators that include steroid receptors

(SRC-1, SRC-2 and SRC-3)(93).

RA is a small, lipophilic molecule and not only does it regulate gene activity within the cell in which it is produced, but it also acts as an autacoid acting in non-cell autonomous fashion on neighboring, RA-responsive cells. The distribution of RA creates spatial and temporal gradients that control signaling within target tissues (94). However, the synthesis and diffusion of RA is constrained by catabolizing cytochrome p450 enzymes of the

CYP26 family which degrade RA (95).

The ability to tightly regulate Vitamin A metabolism and RA synthesis and signaling is essential for proper embryogenesis and adult homeostasis. Cells and tissues therefore employ multiple feedback mechanisms to govern the levels of retinol, retinal and retinoic acid. When endogenous levels of RA are too high, Cyp26 genes are activated to

help degrade excess RA. Furthermore, the enzymes responsible for oxidizing the first and second metabolic steps of vitamin A metabolism, such as Rdh10, and Aldh1a1, Aldh1a2,

Aldh1a3, are downregulated. Conversely, Dhrs3 is upregulated to further convert the intermediate molecule retinal back to retinol (81, 96-99). In the opposite situation, whereby the levels of RA are too low, upregulation of Rdh10, Aldh1a1, Aldh1a2 and Aldh1a3, together with downregulation of the Cyp26 degradation enzymes (100) can collectively lead to an increase in RA synthesis and maintenance. In addition, many of the proteins responsible for transporting Vitamin A and RA are encoded by genes that contain RAREs

(101-103). This therefore provides additional opportunities for modulating vitamin A metabolism, and RA synthesis and signaling.

The role of vitamin A and retinoic acid signaling in development and disease

Vitamin A, and RA synthesis and signaling play vital roles during embryo development and throughout adult homeostasis. Vitamin A is required for proper bone development, protection of the skin and mucosa, immune system defense, epithelial integrity, and normal development and function of the reproductive organs, hair and teeth

(104-109). However, both excess and deficiency of Vitamin A or RA causes dysfunction, hence the need to maintain appropriate levels of vitamin A and RA throughout life. The deleterious effects of excess RA were first inferred in teratogenesis studies of embryo development, whereby an excess of RA produced congenital anomalies that included defects in the formation of the brain, nervous system, heart and limbs, together with malformed eyes, jaws and palate (110, 111). Retinoids are synthetic forms or derivatives of vitamin A and are typically used to treat dermatological conditions. The most well- known is isotretinoin (13-cis-retinoic acid), which is marketed as Accutane, and used to

treat severe acne. However, vitamin A is contraindicated during pregnancy and fetal retinoid syndrome, which is characterized by craniofacial, nervous system and cardiovascular anomalies, can occur as a consequence of a mother taking retinoids during pregnancy. Conversely, congenital abnormalities and even fetal death can result from a deficiency in vitamin A or RA. Major organ systems affected by a deficiency in vitamin

A, and RA synthesis and signaling include the craniofacial, cardiovascular and ocular tissues, circulatory, respiratory and urogenital systems (112-114).

Appropriate levels of vitamin A are also essential for the health of the mother and adults in general, not just during embryo development. In particular, vitamin A plays an essential role in vision which relies on the 11-cis-retinaldehyde metabolite as the light- absorbing chromophore of opsin proteins (115, 116). Through its effects on epithelial integrity and function, vitamin A is important in the prevention of xerophthalmia, which is defined by dryness of the conjunctiva and cornea of the eye. As xerophthalmia progresses, it eventually leads to blindness, thus making vitamin A deficiency the main cause of preventable blindness (WHO Report 1995-2005). Vitamin A deficiency is therefore still considered to be a major health issue, particularly in developing countries (WHO Report

1995-2005).

Interestingly, an excess of vitamin A or RA can result in a pattern of defects similar to those caused by a deficiency of RA. This is particularly true with respect to craniofacial anomalies such as cleft palate, and cardiovascular malformations. This phenomenon is thought to occur via overcompensation to excess vitamin A or RA. Under conditions of excess, the RDH and ALDH enzymes are shut down to prevent further synthesis of RA, while Cyp26 enzymes are upregulated to catabolize pre-existing RA. However, rather than

reversing these actions when RA levels return to normal, the system remains off, leading to a prolonged period of RA deficiency and consequently developmental anomalies (99).

In summary, maintaining proper levels of vitamin A and RA are essential for embryo development and adult homeostasis. This is accomplished through a series of compensatory mechanisms that have evolved to maintain an appropriate balance of vitamin

A and RA to protect against developmental disorders and disease. Differential and dynamic patterns of synthesizing and metabolizing enzymes facilitate the precise spatiotemporal control of vitamin A metabolism, and RA synthesis and signaling. In this chapter we describe protocols for visualizing the spatiotemporal activity of genes and proteins involved in this process as well as biochemically isolating and quantifying vitamin A and its metabolites.

Direct quantification of RA levels and retinoid homeostasis

Numerous analytical approaches have been developed to quantify retinoids including gas chromatography-mass spectroscopy (GC/MS) (117, 118), liquid chromatography with ultraviolet absorption (LC-UV) (119-122), liquid chromatography- electrochemical detection (LC/ECD) (123-125), liquid chromatography-tandem mass spectroscopy (LC-MS/MS) (122, 126-128), and liquid chromatography-multiple reaction monitoring cubed (LC-MRM3 also known as liquid chromatography-multistage tandem mass spectrometry) (129). The most rigorously validated quantitative methodologies for determination of endogenous RA concentrations in cell systems and tissues as well as for in vitro cell metabolism assays are liquid chromatography-tandem mass spectrometry- based techniques (122, 126-129). Absolute quantification via LC-MS/MS-based approaches rely on a unique precursor to product ion m/z transition, termed multiple

reaction monitoring (MRM) or selected reaction monitoring (SRM), to yield specificity

(126, 127). Tandem quadrupole instruments yield the most robust and reproducible analytical detection with typical linear ranges of 3 to 5 orders of magnitude and typical instrument coefficients of variation of <5% (126, 127). Quantitation is derived from calibration curves constructed from authentic standards. Stable isotope-labeled retinoids or non-endogenous retinoid derivatives are typically used as internal standards to correct for extraction efficiency and variability during data acquisition (122).

Recent work has shown that a variation of LC-MS/MS-based detection that includes an additional mass transition during detection yields additional specificity for RA quantification (129). This liquid chromatography-multistage tandem mass spectrometry methodology is also interchangeably known as LC-MS3 and LC-MRM3. Although MRM detection in LC-MS/MS methods is one of the most selective detection modalities, abundant species in extracts of complex matrices that coelute with the analyte of interest can interfere with quantification (129, 130). Because most extraction methods for retinoids also extract (more abundant) lipids of similar nominal mass, the potential for interferences is significant and requires additional caution and careful method validation. Current strategies typically include the use of chromatographic separation to move interfering species to retention times away from RA and/or the inclusion of additional mass transitions to impart additional selectivity (129, 130).

RA quantification poses several additional significant analytical challenges including low endogenous concentrations, often spatially localized occurrence, and existence of endogenous geometric isomers with distinct biological functions (122).

Isobaric geometric isomers present an additional analytical challenge as they must be

chromatographically resolved before mass spectrometric detection. Additional experimental challenges that are critical to control include the susceptibility of retinoids to light-induced isomerization and oxidation, as well as adherence to plastic surfaces. Yellow or red laboratory lights (blocking UV wavelengths <~500 nm) are recommended for experimental and sample preparation work in addition to efforts toward protecting samples from light by cover and/or amber vials in often non-UV blocking laboratory settings during analysis. Samples should be kept cold (on ice) during sample preparation and glass pipets, vials and containers, should be used as much as possible to prevent sample loss by adsorption to plastic (122).

Typical detection limits for LC-MS/MS detection of RA are low fmol on column, which enables the determination of low nanomolar concentrations of endogenous RA in either cell systems or tissues. Typical linear ranges extend from low fmol to up to ~ 1-10 pmol on column. Typical cell culture requirements range between 1 x 105 and 1 x 106 cells, depending on the cell type, level of RA present, and LLOQ of the assay being used. Tissue requirements typically range from 1-100 mg of tissue, with the minimum amount of tissue required depending on the LLOQ for the assay being used and the levels of RA present. If multiple assays are required, then tissue requirements can be higher. Minimum amounts of tissue required and efficiency of extraction from matrices should be evaluated before quantitative experiments are undertaken. The amount of RA is typically expressed as mol of RA per g tissue (requires accurate weight of tissue), mol of RA per g protein (requires a separate protein determination), mol of RA per million cells (requires accurate cell count), or mol RA per mL of fluid, such as media or plasma (requires an accurate volume determination) (122, 126, 127, 129).

Quantification of retinoids that serve as the substrates for RA biosynthesis as well as vitamin A storage can inform the basis of homeostatic mechanisms (121, 131). Retinoids can differ by as much as six orders of magnitude, making methods that simultaneously detect all retinoids not technically practical. For example, retinyl ester levels can reach high micromolar levels whereas endogenous RA is typically low nanomolar in concentration.

Quantification of RE and retinol can be accomplished by LC-UV (121, 122). These more abundant retinoids (typical concentrations in micromolar range) can be feasibly detected by UV detection due to their favorable molar absorptivity (typically ε=~30,000 – 60,000

M-1cm-1 ), and unique absorption wavelengths, which are red-shifted from many other biological molecules (121, 122). LC-MS/MS methodology also exists for quantification of these more abundant RE and retinol species, which have less of a requirement for the sensitivity of LC-MS/MS-based approaches (131).

Retinal, or retinaldehyde, requires derivatization due to its reactive aldehyde group for accurate quantification. Retinaldehyde forms covalent Schiff base adducts with amine groups of proteins, phospholipids and other compounds, making it necessary to react the extract with with hydroxylamine or O-ethylhydroxylamine to release the bound retinal and covert it to the respective syn and anti-retinaloxime adducts (121, 122, 131, 132). This is an important consideration for zebrafish, frog and avian models since retinaldehyde- vitellogenin Schiff-based adducts are the main storage form for retinoids in eggs and oocytes of oviparous animals (133, 134). Whereas, LC-UV methods have been popular, recent LC-MS/MS methodology provides more sensitive detection of retinal, which is important for samples of limited quantity that are often encountered in developmental studies (131, 132).

Additional, specialized analytical approaches for retinoids include tissues where cis-retinoid isomers have significant biological roles, such as the eye and pancreas.

Methods for isomeric retinoid detection has been previously reviewed (130) ((122). For the measurement of geometric isomers of retinoids found in the visual system, an isocratic or step-gradient normal-phase HPLC method has been developed to resolve 11-cis and all- trans-retinol and retinyl esters, as well as all-trans, 9-cis, and 11-cis-retinaloximes (132,

135). Chiral-HPLC can also be employed to resolve (13R)- and (13S)-enatiomers of all- trans-13,14-dihydroretinol (136). For more specialized methods to measure cytotoxic lipofuscin chromophores formed in the eye such as pyridinium bisretinoids (N-retinyl-N- retinylidene ethanolamine or A2E) and retinal dimers, we refer the reader to several reviews (132, 137, 138).

Assessing retinoic acid signaling in cellular and animal models via reporter assays

Reporter screens can provide crucial information about the spatial resolution or extent of RA signaling within cells or tissues (reviewed in Table 1.2). These reporters are based on the expression of a readily assayable enzyme (beta-galactosidase or luciferase) or a fluorescent protein driven by a promoter controlled by RA signaling. Some RA signaling reporters are based on a RARE derived from the promoter of the Rarb gene consisting of a canonical GTTCAC direct repeat separated by 5 nucleotides (DR5) (139). These reporters have been incorporated in cell models (140), as well as transgenic mice (141, 142) and zebrafish (143, 144). However, a disadvantage of the use of DR5 based-reporters is that

RA-signaling via other types of RAREs (145) may not be detected. In addition, the DR5 enhancer is also recognized by other nuclear receptors such as COUP-TF (146).

Other reporters of RA signaling use a two-hybrid approach based on expression of a fusion protein of the ligand-binding domain (LBD) of RAR and the DNA-binding domain (DBD) of the GAL4 transcription factor. Expression of GAL4-nuclear receptor fusions has been a very valuable tool for high-throughput screening of compounds with agonist/antagonist activity against various nuclear receptors including RAR and RXR

(147-149). In these systems binding of RA to the LBD of RAR induces expression of

GAL4-regulated reporters (luciferase, GFP) controlled by upstream activation sequences

(UAS). In comparison to DR5-based reporters, both binding of RA to the RAR-LBD and the induction of UAS-controlled reporters by GAL4-RAR chimeric receptors are very specific. Another advantage of the use of GAL4-RAR; UAS-reporter systems is that they do not rely on endogenous RAR receptors for reporter expression. However, the generation of compound GAL4-RAR;UAS-reporter expressing transgenic lines is cumbersome and time consuming since both the UAS-reporter and Gal4-RAR transgenes need to be present for activity. GAL4-RAR;UAS-reporter genes have also been introduced in mice and in zebrafish (150-153). Constitutive overexpression of chimeric receptors based on fusions of the Gal4-DBD to the RAR-LBD leads to phenotypic effects in mice. Therefore, a feedback- inducible nuclear-receptor-driven (FIND) expression system was generated to control the expression of the GAL-RAR chimeric receptor in mice (150, 151). Expression of similar chimeric receptors in zebrafish encoding the Tg(β-actin:GDBD-RLBD);(UAS-reporter) or the Tg(β-actin:VPBD-RLBD);(UAS:EGFP) transgenes have not been reported to cause phenotypic effects (152, 153).

Whereas reporter systems offer valuable spatial information and RA signaling read-outs, caution should be exercised in the interpretation of reporter assay response in

terms of concentration and temporal relationships. It is important to stress that reporter- based methods are non-quantitative and do not provide a linear response to the level of RA in tissues and thus reflect a qualitative extent of RA signaling which is correlated with RA levels. And, whereas valuable qualitative relationships can be assessed under comparable conditions, specific, absolute quantitation for RA cannot be achieved via reporter assays.

Some reporter assays have cited that in addition to all-trans-RA, other endogenous retinoids can produce signals to varying extents including 3,4-didehydro-RA, 9cRA, 4- oxo-RA, 4-hydroxy-RA, and 4-hydroxy-retinol (140, 154-156). Temporal relationships should also be cautiously and carefully interpreted. Since reporter assays reflect RAR activation, they reveal the longer term consequences of receptor activation with a delay in the reporter signal appearance often hours after a change in RA concentration (140, 154-

156). Moreover, the half-life of the RAR reporters employed thus far generally outlasts the

RA input. Thus, reporter assays may not accurately correlate with RA concentration via

RA signaling in real-time. Temporal delays should be considered as well as the possibility that RA may even be significantly catabolized by the time the reporter signal is visualized.

Lastly, experimental caution and consideration should be paid to reports that high levels of

RA can turn off reporter response in some cases (156).

The most recent addition to the RA reporter systems allows for detection of RA in transgenic zebrafish expressing genetically encoded probes for RA(GEPRAs) (94). These reporters express the RAR-LBD flanked by Förster resonance energy transfer (FRET) partners CFP and YFP. Binding of RA causes a conformational change in the chimeric receptor which can be detected via FRET. Since this reporter does not require any additional substrates, it allows for the visualization of endogenous RA gradients in vivo in

zebrafish embryos. This approach has great potential in studying the formation of RA in tissues in real-time, however, more studies are needed to establish the sensitivity of the

GEPRAs-based reporter and its RA concentration-dependent correlation.

Transgenic reporter mice

RARE-LacZ (141) available Mice expressing a beta- Feedback-inducible nuclear-receptor-driven from Jackson Labs Stock No: galactosidase reporter (FIND) expression of GAL4-RAR/ UAS-hsp- 008477 | RARE-hsp68LacZ under the control of a lacZ (151) Transgenic mice express a chimeric express a beta-galactosidase minimal tk promoter receptor fusion of Gal4-DBD and RAR-LBD. reporter under the control of a containing 3 RARE A second transgene UAS-hsp-lacZ expresses minimal hsp68 promoter and derived from Rarb a lacZ reporter driven by a minimal hsp68 three copies of RARE from (142) promoter including four UAS. The expression Rarb of the chimeric receptor Gal4-RAR is itself autoregulated by incorporating 4 UAS in a minimal hsp68 promoter.

Transgenic zebrafish lines

Tg(3XRARE-tk- Tg(12XRARE- Tg(β-actin:GDBD- Transgenic zebrafish GFP) ef1a:gfp)sk71 RLBD);(UAS-reporter) or Tg(β- expressing genetically Tg(3XRARE-gata- zebrafish line actin:VPBD- encoded probes for 2-GFP) expresses a GFP RLBD);(UAS:EGFP) zebrafish RA(GEPRAs) Transgenic reporter driven by a lines express chimeric receptors Based on chimeric zebrafish promoter under the based on Gal4-DBD or VP16- receptors of RAR-LBD expressing GFP control of 12 Gal4-DBD fused to the RARA- fused at the N and C- under the control concatenated RARE LBD. Ligand binding triggers termini to CFP and of a minimal (144) receptor activation and is YFP, respectively. promoter (tk or detected via an UAS-driven Binding of RA causes gata-2) including 3 reporter a conformational copies of RARE (152, 153) change in the chimeric (143) receptor detected via FRET (94)

Table 1.2 Summary of Retinoic Acid Signaling Reporters

1.2.3. Retinoids as therapeutics As has been shown in the last few sections, retinoids play important roles in many physiological processes within the body including immune responses, cellular differentiation, development, and proliferation. The bioactive metabolite of vitamin A all- trans-retinoic acid (ATRA) regulates the expression of genes via nuclear receptors in various target tissues (157). Nuclear receptors are activated by ligands which bind to the

DNA regulatory elements in the promotor region of genes leading to repression or activation of transcription. ATRA is capable of binding to three different isoforms of retinoic acid receptors (RAR), which belong to the family of nuclear receptors, including

RARα, RARβ, and RARγ (158-160). These RAR isoforms then heterodimerize with one of three retinoid X receptors (RXR), RXRα, RXRβ, and RXRγ, and associates with the retinoic acid response element (RARE) to affect transcriptional changes (158, 159). RXR is a heterodimeric partner with approximately one-third of nuclear receptors found in humans including the thyroid receptor, vitamin D3 receptor, peroxisome proliferator activated receptors (PPARs), and many more, so using an agonist for RXR could influence the activity of any of these heterodimer complexes (161).

Once the RAR heterodimeric complex is formed it undergoes a conformational change that allows it to couple to co-activator proteins that mediate transcriptional effects

(162, 163). One example is the activator protein 1 (AP-1) complex. AP-1 transcription factors have been shown to be negatively regulated by RAR, but not RXR, through forming a nonproductive complex with c-Jun (164). In a mammalian two-hybrid system developed by Zhou et al., they showed that the inhibition of AP-1 dimerization by RAR is cell specific and only occurs in cells that exhibit RA-induced repression of AP-1 transcriptional activity

(65). This specificity makes RAR an attractive target for AP-1 activity inhibition.

RAR can be pharmacologically modulated in an isoform-specific manner via agonists, inverse agonist, partial agonists, and antagonists. An important consideration when using retinoids, as well as any pharmacological agent, is balancing their therapeutic use with off-target effects. Retinoids can have deleterious effects including teratogenesis if over-exposure occurs (99), however, there is hope that the development of more receptor-

selective agonists will obtain therapeutic efficacy without these toxic effects. Retinoids have been successfully used in the treatment of several diseases and disorders. One of the safest and most impactful uses of retinoids is the all-trans-retinol supplementation to improve vitamin A deficiency in developing countries that saves millions of lives every year (165). Dermatological use of ATRA and 13-cis-RA for acne and other conditions is common as well (166). Retinoids have also been used as cancer therapies, including treatment of Acute Promyelocytic Leukemia (APL), due to their chemo-preventative and chemotherapeutic effects (167). This is achieved through several mechanisms including inducing cell differentiation and apoptosis in tumor cells (167-170).

There are three retinoic acid isomers approved in the clinic including ATRA

(tretinoin) (Table 1.3), 9-cis RA (alitretinoin) and 13-cis RA (isotretinoin). ATRA is a high affinity ligand for RAR and is detected is ubiquitously detected in vivo, 9-cis RA is a high affinity ligand for both RAR and RXR but has limited detection in vivo, and 13-cis RA has low affinity for RAR. All of the isomers can be degraded by the same enzymes that regulate the levels of ATRA. In addition, there are numerous RAR isoform specific agonists currently available. In the current studies, we will be focusing on RARα-specific agonist

AM580 (171), RARβ-specific agonist AC55649 (172), and RARγ- specific agonist

CD1530 (173) (Table 1.3). These RAR isoform specific agonists have all shown anti- proliferative effects in the context of cancer and other diseases with aberrant cell proliferation (174-176). Since one of the pathogenic mechanisms that leads to obstructive lung diseases, such as asthma, is the promotion of ASM cell proliferation (177-179), we hypothesize that the use of RAR inhibitors to inhibit AP-1 formation and consequent proliferation could have a potential therapeutic effect.

Compound Name Activity/Specificity Structure all trans Retinoic Acid Pan-RAR agonist (ATRA) (tretinoin)

AM580 RARα agonist

AC55649 RARβ2 agonist

CD1530 RARγ agonist

Table 1.3 Naturally occurring pan-RAR agonist, ATRA, and isoform-specific RAR agonists.

1.3. Aims of the thesis Increased airway smooth muscle (ASM) cell mass and secretory functions are hallmark characteristics of airway inflammatory diseases, such as asthma (177). To date, there are no effective therapies to combat ASM cell proliferation that contributes to hyperresponsive airways and debilitating bronchoconstriction. Previous studies suggest that inhibition of the activator protein-1 (AP-1) transcription factor could prevent ASM cell proliferation (65, 180). Previous work has shown that the extracellular signal-regulated kinase 1/2 (ERK1/2) pathway is an important mediator of the growth factor response and the phosphorylation events that lead to AP-1 activation (181). In addition, ligand-activated retinoic acid receptor (RAR) has been shown to antagonize AP-1 formation and transactivation (65). Since both ERK and RAR play major roles in mediating the AP-1 complex formation and activation, we propose a combined therapeutic approach of inhibiting ERK activation and increasing retinoic acid (RA) activity to prevent ASM cell proliferation (Fig 1.4).

ASM migration and proliferation have previously been shown to be blocked by

ERK pathway inhibitors targeting the ATP binding site (66). However, ATP-competitive kinase inhibitors have invariably led to drug resistance in many diseases (182). Therefore, to regulate ERK signaling in disease, we propose the use of function-selective ERK1/2 inhibitors to inhibit growth factor induced AP-1 activity and ASM cell proliferation.

Previous work from our group has shown that SF-3-030, a novel non-ATP competitive function selective ERK2 inhibitor, is able to inhibit AP-1 transcription factor activity in melanoma cells (183). Our recently published paper suggests that SF-3-030 has similar effects as an ATP-competitive inhibitor in preventing ASM cell proliferation and inhibiting

AP-1 activity in ASM cells with less protein changes as shown by proteomic analysis (50).

Our goal is to further investigate the use of SF-3-030 and other function-selective inhibitors to evaluate their therapeutic potential for asthma treatment.

Additionally, deficiency of vitamin A has been shown to exacerbate allergic asthma (184).

Previous studies have shown that RA, an active metabolite of vitamin A and high-affinity ligand for RAR, is reduced in inflammatory conditions where altered RA metabolism contributes to inflammation (185). We propose that patients with asthma will have altered vitamin A metabolism and reduced RA in their ASM cells so enhancing RAR-mediated antagonism of AP-1 would be beneficial for reducing hyperproliferation and tissue remodeling.

In this project, the overarching goal will be to find an effective therapy to combat debilitating bronchoconstriction in asthma through a non-ATP competitive ERK inhibitor and targeting RAR-mediated antagonism of AP-1. We hypothesize that targeted inhibition of AP-1 activity will reduce airway smooth muscle cell hyperproliferation that leads to bronchoconstriction in asthma.

Specific Aim 1 is to determine whether targeted inhibition of ERK1/2 will decrease

AP-1 activity in ASM cells. Experiments will (1) determine how AP-1 activity changes in the presence of SF-3-030 using a luciferase assay and evaluating the effect on downstream proteins and (2) determine whether a function-selective inhibitor is as efficacious as an

ATP-competitive inhibitor while minimizing off-target effects.

Specific Aim 2 is to determine how AP-1 activity is affected by changes in retinoid metabolism and RA homeostasis due to asthma/inflammation. Experiments will (1) determine how endogenous retinoid activity changes between healthy and diseased cells

and lung tissue to determine the most important effectors in AP-1 complex antagonism and

(2) evaluate whether an RAR agonist can restore RA activity to inhibit AP-1 signaling.

Specific Aim 3 is to determine whether targeting of the ERK and RA pathway will have an additive effect in controlling ASM cell proliferation. Experiments will (1) evaluate the effect of combining SF-3-030 and restoration of RA in decreasing AP-1 activity and

(2) determine how proliferation of ASM cells change in the presence of SF-3-030 and a

RAR agonist.

Figure 1.4. Summary of ERK and RA signaling that leads to AP-1 complex formation and ASM cell proliferation. ERK inhibitors (Aim 1), RAR agonists (Aim 2), and a combined therapeutic approach (Aim 3) will be used to target AP-1 activity to reduce ASM cell hyperproliferation that leads to bronchoconstriction in asthma.

Chapter 2. Effects of ATP-competitive and function-selective ERK inhibitors on airway smooth muscle cells proliferation3

2.1. Abstract

Increased airway smooth muscle (ASM) cell mass and secretory functions are characteristics of airway inflammatory diseases, such as asthma. To date, there are no effective therapies to combat ASM cell proliferation, which contributes to bronchoconstriction and airway obstruction. Growth factors such as platelet‐derived growth factor (PDGF) and the activation of the ERK1/2 are major regulators of ASM cell proliferation and airway remodeling in asthma. However, given the ubiquitous expression and multiple functions of ERK1/2, complete inhibition of ERK1/2 using ATP‐competitive inhibitors may lead to unwanted off‐target effects. Alternatively, we have identified compounds that are designed to target substrate docking sites and act as function‐selective inhibitors of ERK1/2 signaling. Here, we show that both function‐selective and ATP‐ competitive ERK1/2 inhibitors are effective at inhibiting PDGF‐mediated proliferation, collagen production, and IL‐6 secretion in ASM cells. Proteomic analysis revealed that both types of inhibitors had similar effects on reducing proteins related to TGF‐β and IL‐6 signaling that are relevant to airway remodeling. However, function‐selective ERK1/2 inhibitors caused fewer changes in protein expression compared with ATP‐competitive inhibitors. These studies provide a molecular basis for the development of function‐ selective ERK1/2 inhibitors to mitigate airway remodeling in asthma with defined regulation of ERK1/2 signaling.

Keywords activator protein-1, airway inflammation, asthma, kinase inhibitor, proteomics

3 Defnet, A.E.; Huang, W.; Polischak, S.; Kane, M.A.; Shapiro, P.; Deshpande, D.A. Effects of ATP- Competitive and Function-Selective ERK Inhibitors on Airway Smooth Muscle Cell Proliferation. Federation of American Societies for Experimental Biology. 2019, 33(10), 10833-10843.

2.2. Introduction

The promotion of proliferative (resulting in increased mass) and synthetic

[secretion of extracellular matrix (ECM) proteins and chemokines] phenotypes of airway smooth muscle (ASM) cells are now recognized as pathogenic mechanisms of obstructive lung diseases (177-179). Increased ASM mass in asthma appears driven primarily by growth factors [e.g., epidermal growth factor, platelet‐derived growth factor (PDGF)] in cooperation with pro‐contractile GPCR agonists and possibly by some cytokines and chemokines, which may have direct effects on ASM (186-188). Many in vitro and in vivo studies have implicated the ERK1/2, PI3K, and 70 kDa ribosomal S6 kinase signaling pathways as primary mediators of the effects of mitogens on ASM growth (47, 186, 189-

193). Among these, the ERK1/2 signaling pathway plays a major role in ASM proliferation and represents a potential drug target for reducing hyperplasia and tissue remodeling associated with asthma (193-197). ERK1/2 phosphorylates numerous target proteins to regulate multiple cellular functions, including transcription factors that make up the activator protein‐1 (AP‐1) transcription factor complex (181, 198).

The AP‐1 transcription factor complex includes Jun, Fos, activating transcription factor (ATF) and MAF bZIP transcription factor (MAF) proteins that homo‐ and heterodimerize in different combinations using a conserved basic leucine zipper DNA‐ binding domain (199, 200). Expression of c‐Fos is reported to be higher in the airway epithelial cells obtained from asthmatics compared with healthy individuals (48, 201). In addition, growth factors, cytokines, chemokines, and cellular stress induce signaling through MAPK and AP‐1 in airway cells (191). In addition, AP‐1 proteins interact with other transcription factor proteins such as the p65 subunit of NF‐κB, CREB‐binding

protein/ E1A binding protein p300 (CBP/p300), and retinoblastoma (Rb) to control the expression of multiple genes regulated by those proteins. Also, many of the inflammatory stimuli regulate NF‐κB and AP‐1 activity concurrently (49). Therefore, we predict that inhibiting ERK1/2‐mediated activation of AP‐1 will effectively inhibit ASM cell growth associated with airway remodeling in the asthmatic lung.

Several potent ATP‐competitive or catalytic site inhibitors of ERK1/2 have been developed and are being tested for the treatment of cancer (202-205). Given the large number of ERK1/2 substrates and their capacity to regulate numerous cellular signaling pathways and functions, we have identified substrate‐selective ERK1/2 inhibitors with the goal of inhibiting specific kinase functions associated with disease while preserving other

ERK1/2 functions needed for normal cell functions (206-208). Using known structural requirements for ERK2 interactions with substrate proteins, computer‐aided drug design and biologic screening identified compounds that are designed to target ERK2 on 2 different functional domains: D‐domain recruitment or F‐recruitment sites (DRS or FRS, respectively), which mediate interactions with protein substrates containing D‐domains

(basic residues followed by a hydrophobic Leu‐X‐Leu motif) or F‐sites (Phe‐X‐Phe motif within 6–10 aa of the Ser/Thr phosphorylation site, and X is any amino acid), respectively

(209-211). We have previously shown that compounds targeting the FRS on ERK2 can inhibit c‐Fos phosphorylation and AP‐1 activity in cancer cell lines (183). In the current studies, we investigated the effects of function‐selective ERK1/2 inhibitors on PDGF‐ mediated ASM proliferation and protein expression. In addition, we compared the effects of ATP‐competitive vs. function‐selective ERK1/2 inhibitors on PDGF‐mediated ASM cell proliferation and protein expression. Our findings reveal a new pharmacologic

approach that antagonizes some kinase functions to reduce proliferative and inflammatory signals in ASM cells associated with airway remodeling in asthma.

2.3. Materials and Methods

2.3.1. Chemicals and Reagents

The function‐selective ERK1/2 inhibitors SF‐3‐026, SF‐3‐027, SF‐3‐029, and SF‐3‐030 were synthesized and characterized as previously described (183). Ulixertinib (BVD‐523) was kindly provided by BioMed Valley Discoveries (Kansas City, MO, USA). U0126 was purchased from Selleckchem (Houston, TX, USA) and VX‐11E was purchased from Bio

Vision (Milipitas, CA, USA). Antibodies recognizing total c‐Fos, total c‐Jun, total FOS‐

Related Antigen‐1 (Fra‐1), total FosB, β‐actin, phosphorylated (phospho)–protein kinase

B (Akt) 1 (Thr308), phospho‐p90RSK1 (Thr359/Ser363), and phospho–GSK‐3β (Ser9) were purchased from Cell Signaling Technology (Danvers, MA, USA). The anti‐MAPK, activated diphosphorylated ERK1/2 (Thr183, Tyr185) antibody was purchased from

MilliporeSigma (Burlington, MA, USA). The total ERK2, Glycogen Synthase Kinase 3β

(GSK‐3β), Ribosomal s6 Kinase (RSK)1, and cyclin D1 antibodies were purchased from

Santa Cruz Biotechnology (Dallas, TX, USA). The phospho–c‐Fos (Thr325) antibody was purchased from Thermo Fisher Scientific (Waltham, MA, USA). Recombinant human

PDGF‐BB was purchased from BioLegend (San Diego, CA, USA). All reagents used for

Wes Simple Western were purchased from ProteinSimple (San Jose, CA, USA).

2.3.2. ASM cell isolation

Human ASM cells were obtained from healthy donors. Primary ASM cell cultures were generated using deidentified primary bronchi per Panettieri et al. (212), and studies

performed with these cells have been determined not human subjects by the Jefferson

University Institutional Review Board.

2.3.3. Cell culture

ASM cells were cultured in DMEM (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (MilliporeSigma). The cells were cultured at 37°C in a 95% O2/5%

CO2 humidified incubator. ASM cells were passaged no more than 7 times.

2.3.4. Cell proliferation assays

Cells were serum starved for 24 h and then treated with 5–100 µM of function‐selective

ERK1/2 inhibitors or ATP/catalytic site inhibitors of MEK1/2 (U0126) or ERK1/2 (VX‐

11e) in the presence of PDGF‐BB (10 ng/ml) for 48 h. Measurement of cellular DNA was determined by CyQuant Cell Proliferation Assay (Thermo Fisher Scientific).

2.3.5. Cytotoxicity assays

ASM cells were plated in a 96‐well plate, serum starved for 24 h, and then treated with different concentrations of function‐selective ERK1/2 inhibitors, VX‐11e, or U0126 in the presence of PDGF for 48 h. Cytotoxicity of compounds was measured by the Lactate

Dehydrogenase (LDH) Cytotoxicity Assay (Thermo Fisher Scientific).

2.3.6. AP-1 promotor luciferase assays

Cignal Lenti luciferase reporter viral particles for AP‐1 were purchased from Qiagen

(Germantown, MD, USA), and ASM cultures were infected with lentivirus per the manufacturer's recommendation. Stable lines were selected using puromycin and maintained in complete medium containing selection antibiotic as previously described by

Sharma et al. (213). ASM cells were seeded in 12‐well plates (50,000 cells/well) and incubated for 24 h to achieve ∼60–70% confluence. Cells were then incubated in serum‐

free medium for 24 h. Cells were pretreated with 0–50 µM of compounds for 15 min, followed by stimulation with 10 ng/ml PDGF for 24 h. The luciferase activity in the cell extracts was determined with a Bright‐Glo Luciferase Assay System (Promega, Madison,

WI, USA) according to the manufacturer's instructions. Luciferase activities [luminescence

(relative light units/well)] were monitored with a microplate luminometer (Molecular

Devices, San Jose, CA, USA). Relative light units data were normalized using total protein loaded onto each well.

2.3.7. ASM cell treatments and lysate preparation

ASM cells were seeded in 24‐well plates (50,000 cells/well) and incubated for 18 h to achieve ∼85% confluence. Cells were then pretreated with 0–50 µM SF‐3‐030 or 10 µM ulixertinib for 15 min, followed by stimulation with 10 ng/ml PDGF for 0–8 h, as indicated.

Cells were washed twice with cold PBS 1× (Quality Biological, Gaithersburg, MD, USA), harvested in RIPA buffer (MilliporeSigma) supplemented with Protease Inhibitor Cocktail

Set III (MilliporeSigma), and subjected to a freeze‐thaw cycle followed by sonication 3 times for 3 s, resting on ice in between. Lysates were centrifuged at 5000 g for 15 min, and the supernatant was transferred to a new microcentrifuge tube. Protein concentrations were determined using a Bradford assay (Bio‐Rad, Hercules, CA, USA). Lysates were stored at

−80°C in aliquots to minimize freeze‐thaw cycles.

2.3.8. Immunoassays

Immunoblotting following electrophoresis on 10–15% SDS‐polyacrylamide gels was previously described (183). Immunoassays were also performed on Wes Simple Western as previously described by Pera et al. (214). Primary antibodies were diluted as follows:

1:10 (c‐Fos, c‐Jun, Fra1, FosB), 1:25 (β‐actin, ERK2, phospho‐90RSK, phospho–GSK‐3β,

and total GSK‐3β). Incubation times were changed from normal factory settings for the primary antibodies at 60 min with 30 min separation time to optimize signal/noise and separation. Quantification of electropherograms was performed with Compass 225 for

Simple Western software (v.3.1.7; ProteinSimple) using a gaussian peak fit distribution for area under the curve.

2.3.9. IL-6 ELISA assay

Human ASM cells were treated with PDGF with or without the test compounds, and after

48 h the cell culture medium was harvested for determining IL‐6 secretion by ASM cells.

Total IL‐6 content in the cell culture media was determined by ELISA (R&D Systems,

Minneapolis, MN, USA) as previously described by Pera et al. (214) in 96‐well plates coated with anti–IL‐6 antibody.

2.3.10. Sircol assay

Human ASM cells were cultured on a 6‐well plate and were treated with PDGF with or without the test compounds for 48 h, and cell lysates were obtained. Total soluble collagen content in the cell lysates was assessed using Sircol Collagen Assay (Biocolor,

Carrickfergus, Northern Ireland, United Kingdom) according to the manufacturer's protocol, as previously described (213). Human ASM homogenate was mixed with Sircol dye reagent, and absorbance was measured using a plate reader at 550 nm. Collagen content was quantified using a standard curve generated by reference standards and was normalized to the total protein content in each sample.

2.3.11. Mass spectrometry

ASM cells were seeded in 10‐cm plates (4 × 106 cells/well), incubated overnight to achieve

∼70% confluence, and then serum starved for 24 h. Cells were pretreated with 10 or 25

µM of ulixertinib or SF‐3‐030, respectively, for 15 min, followed by stimulation with 10 ng/ml PDGF for 8 or 24 h. Cells were washed 2 times with cold PBS and then scraped with

1.5 ml of PBS into a microcentrifuge tube. The cells were centrifuged at 2000 rpm for 30 s at 4°C, and the supernatant was discarded. The cell pellets were placed in −80°C until analysis by mass spectrometry. Cells were lysed in 4% sodium deoxycholate, reduced, alkylated, and trypsinolyzed on filter as previously described by Wiśniewski et al. (215).

Tryptic peptides were separated on a nanoAcquity Ultra‐Performance Liquid

Chromatography Analytical Column (CSH130 C18, 1.7 µm, 75 µm × 200 mm; Waters

Corporation, Milford, MA, USA) over a 180‐min linear acetonitrile gradient (3–43%) with

0.1% formic acid on a Waters nanoAcquity Ultra‐Performance Liquid Chromatography

System and analyzed on a coupled Thermo Scientific Orbitrap Fusion Tribrid mass spectrometer as previously described by Williamson et al. (216). Full scans were acquired at a resolution of 120,000, and precursors were selected for fragmentation by higher‐energy collisional dissociation (normalized collision energy at 30%) for a maximum 3‐s cycle.

Tandem mass spectra were searched against a UniProt (https://www.uniprot.org) human reference proteome using a Sequest HT algorithm (217) with a maximum precursor mass error tolerance of 10 ppm. Resulting hits were validated at a maximum false discovery rate of 0.01 using a semisupervised machine learning algorithm, Percolator (218). Abundance ratios were measured by comparing the mass spectrometry (MS)1 peak volumes of peptide ions, whose identities were confirmed by MS2 sequencing as previously described. Label‐ free quantifications were performed using an aligned Accurate Mass and Retention Time cluster quantification algorithm (219). Pathway and gene ontology analysis were

performed with Qiagen Ingenuity and Panther Gene Ontology databases, as previously described (220, 221).

2.4. Results

2.4.1. Function-selective ERK inhibitors block PDGF-induced ASM cell proliferation

We previously identified a class of compounds containing a 1,1‐dioxido‐2,5‐ dihydrothiophen‐3‐yl 4‐benzenesulfonate scaffold that targeted specific ERK2 substrate docking sites and were effective inhibitors of melanoma cells containing constitutively active ERK1/2 signaling due to mutated BRaf (183). In the current studies, we compared these compounds to known ATP‐competitive ERK inhibitors for their ability to prevent

PDGF‐mediated ASM cell proliferation. As shown in Fig. 2.1A, B, all 4 analogs (SF‐3‐

026, SF‐3‐027, SF‐3‐029, and SF‐3‐030) inhibited PDGF‐mediated ASM cell proliferation in a dose‐dependent manner and had similar efficacy as U0126 and VX‐11e, known

ATP/catalytic site inhibitors of MEK1/2 and ERK1/2, respectively. LDH assays for general cytotoxicity indicated some dose‐dependent cytotoxic effects that were similar between the lead compounds and control kinase inhibitors (Fig. 2.1C). However, at concentrations of

50 µM or less, the differences between control and treated cells showed no statistical significance, and there were no differences between the lead compounds and the

ATP/catalytic site inhibitors of MEK1/2 or ERK1/2 in terms of the cytotoxicity. The remaining studies tested the compounds at doses of 50 µM or less.

Figure 2.1. ERK1/2 inhibitors block PDGF‐induced ASM cell proliferation. A) The structures of function‐selective ERK1/2‐targeted inhibitors SF‐3‐026, SF‐3‐027, SF‐3‐029, and SF‐3‐030 are shown from left to right, respectively. B) Cells were serum starved for 24 h and then treated with 5–100 µM of function‐selective ERK1/2 inhibitors or ATP/catalytic site inhibitors of MEK1/2 (U0126) or ERK1/2 (VX‐11e) in the presence of 10 ng/ml PDGF for 48 h. Measurement of cellular DNA was determined by CyQuant cell proliferation assay (n = 3). C) ASM cells were plated in a 96‐well plate, serum starved for 24 h, and then treated with ERK1/2 or MEK1/2 inhibitors in the presence of PDGF for 48 h. Cytotoxicity of compounds was measured by the LDH Cytotoxicity Assay (n = 8). P, PDGF, Veh, vehicle. Error bars represent se. Significance was determined using 1‐way ANOVA with Bonferroni's multiple comparison test. *P < 0.001, as compared with the PDGF‐treated control.

At doses of 5–50 µM, SF‐3‐030 showed little effect on PDGF‐mediated ERK1/2 phosphorylation at 30 min or 3 h (Fig. 2.2A). In addition, none of the SF‐3‐030 analogs at

25 µM affected the PDGF‐mediated phosphorylation of ERK1/2 or Akt1 in ASM cells after 30 min (Fig. 2.2B) or up to 8 h of exposure to PDGF (unpublished results). The similar effects of SF‐3‐030 and its analogs on PDGF‐induced cell proliferation and ERK1/2 phosphorylation suggest a common mechanism of action. As such, SF‐3‐030 was used in subsequent studies on downstream effectors and proteomic changes. Although SF‐3‐030 reduced the relative phosphorylation of the F‐site containing substrate c‐Fos, the D‐domain containing substrate RSK‐1, and the Akt1 substrate GSK‐3β, the reduction was not statistically significant (Fig. 2.2C). Ulixertinib, which is a VX‐11e analog, inhibited phosphorylation of RSK‐1 and GSK‐3β but had no effect on c‐Fos phosphorylation at this time point (Fig. 2.2C).

2.4.2. Function-selective ERK inhibitors prevent AP-1-mediated gene expression

As we observed in other cell lines (183), SF‐3‐030 inhibited PDGF‐induced AP‐1 promoter activity in ASM cells along with the ATP‐competitive inhibitor VX‐11e (Fig.

2.3A). PDGF induction of cyclin D1, an AP‐1 target, was also inhibited after 8 or 24 h of treatment with SF‐3‐030 or ulixertinib (Fig. 2.3B, C). Immunoblot analysis of AP‐1 proteins showed that PDGF induced a rapid and transient increase in c‐Fos expression in

ASM cells (Fig. 2.4A, B). Whereas PDGF induction of c‐Fos was inhibited by ulixertinib,

SF‐3‐030 caused a sustained increase in c‐Fos expression for up to 8 h (Fig. 2.4A, B).

PDGF treatment transiently increased FosB expression; however, similar to c‐Fos, SF‐3‐

030 sustained the increase in FosB expression over time (Fig. 2.4A, C). PDGF‐induced

Fra1 expression, which peaked at 3 h, was inhibited by both SF‐3‐030 and ulixertinib (Fig.

2.4A, D). The expression of c‐Jun, which is primarily controlled through phosphorylation by the JNK pathway, was induced by PDGF over time but not affected by ulixertinib or

SF‐3‐030 (Fig. 2.4A, E).

Figure 2.2. SF‐3‐030 does not affect the phosphorylation of ERK1/2 or Akt1. A) ASM cells were treated with 0–50 µM of SF‐3‐030 in the presence of PDGF (10 ng/ml) for 30 min and 3 h. Lysates were immunoblotted for active ERK1/2 (ppERK1/2). β‐Actin and total ERK2 were used as a protein loading control. B) ASM cells were treated with 25 µM of function‐selective ERK1/2 inhibitors or 10 µM of U0126 or VX‐11e in the presence of PDGF (10 ng/ml) for 30 min. Lysates were immunoblotted for ppERK1/2 or active Aktl (pAkt1, T308). β‐Actin was used as a protein loading control. C) ASM cells were treated with 25 µM of SF‐3‐030 or 10 µM of ulixertinib (Ulix) in the presence of PDGF (10 ng/ml) for 1 h. Lysates were separated and probed using capillary electrophoresis for RSK1 (pT359/S363), c‐Fos (pT325), and GSK‐3β (pS9) and normalized over total protein (n= 3). Error bars represent SE. Significance was determined using 1‐way ANOVA with Bonferroni's multiple comparison test. *P < 0.05.

Figure 2.3. SF‐3‐030 inhibits AP‐1 activity. A) ASM cells were infected with lentiviral particles expressing AP‐1–Luc followed by treatment with 0–50 µM of SF‐3‐030 or Vx‐11e in the presence of 10 ng/ml PDGF for 24 h. The luciferase activity was determined with a luciferase assay system, and the fold change over untreated was determined (n = 4). B, C) ASM cells were treated with 25 µM of SF‐3‐030 or 10 µM of ulixertinib (Ulix) in the presence of PDGF (10 ng/ml) for 8 (B) or 24 (C) h. Lysates were separated and probed using capillary electrophoresis for cyclin D1. Fold change over untreated was determined (n = 4). Ap‐1‐Luc, activator‐protein 1‐ luciferase; P, PDGF. Error bars represent se. Significance was determined using 1‐way ANOVA with Bonferroni's multiple comparison test. *P < 0.05.

Figure 2.4. SF‐3‐030 differentially affects the expression of AP‐1 proteins. A) ASM cells were treated with 25 µM of SF‐3‐030 or 10 µM of an ATP/catalytic site inhibitor ulixertinib (Ulix) or VX‐11e in the presence of PDGF (10 ng/ml) for 0–8 h. Lysates were immunoblotted for c‐Fos, FosB, Fra1, and c‐Jun. Total ERK2 was used as a protein loading control. B–E) ASM cells were treated with 25 µM of SF‐3‐030 or 10 µM of Ulix in the presence of PDGF (10 ng/ml) for 3 h. Lysates were separated and probed using capillary electrophoresis for c‐Fos (B), FosB (C), Fral (D), and c‐Jun (E), respectively (n = 3). Error bars represent SE. Significance was determined using 1‐way ANOVA with Bonferroni's multiple comparison test. *P < 0.05.

2.4.3. ATP-competitive and function-selective ERK inhibitors have similar, yet distinct, effects on the expression of PDGF-regulated proteins.

To provide further insight into the mechanism of action of the lead compounds, we evaluated SF‐3‐030–mediated changes in protein expression after 8 and 24 h exposure using mass spectrometry. Over 4500 proteins per condition were identified in untreated,

PDGF‐treated, and PDGF‐treated cells in the presence of SF‐3‐030 or ulixertinib. Figure

2.5 summarizes the number of ASM cell proteins that showed statistically significant increases or decreases (>2‐fold) after 8 or 24 h treatment with PDGF and SF‐3‐030 or ulixertinib compared with PDGF treatment alone. Approximately 40% of proteins that increased and 20% of proteins that decreased after 8 and 24 h were common to both treatments, indicating SF‐3‐030 and ulixertinib share overlapping mechanisms of action

(Fig. 2.5). Whereas the total number of proteins that increased with SF‐3‐030 or ulixertinib was similar, ulixertinib inhibited 20 or more proteins than SF‐3‐030 at the time points examined, which supports the concept that function‐selective ERK inhibitors have more targeted regulation of ERK1/2 signaling and functions than ATP‐competitive ERK inhibitors (Fig. 2.5). A summary of all proteins quantified to have a statistically significant increase or decrease is shown in Table 2.1.

Proteomic analysis supported that SF‐3‐030 and ulixertinib caused similar responses in ASM cells. Ingenuity Pathway Analysis (IPA; see Materials and Methods) bio‐informatics indicated that PDGF‐treated ASM cells increased TGF‐β responsive markers and that both SF‐3‐030 and ulixertinib inhibited expression of these proteins that respond to TGF‐β signaling (Fig. 2.6 and Table 2.2). For example, TNF receptor superfamily member 11B was inhibited at 8 h by both SF‐3‐030 and ulixertinib (Fig. 2.6

and Table 2.2). In addition, at 8 and 24 h, SF‐3‐030 and ulixertinib inhibited TGF‐β– regulated collagens, including Collagen (COL)1A1 and COL3A1 (Fig. 2.6). The ATP‐ binding cassette family member, ATP‐binding cassette family A member 1 (ABCA1), was only inhibited by ulixertinib at each time point (Fig. 2.6). However, the aryl hydrocarbon receptor (AhR), a positive regulator of TGF‐β signaling, was increased by ulixertinib or

SF‐3‐030 treatments at 24 h (Fig. 2.6).

Figure 2.5. Summary of proteins that significantly increased/decreased after 8 or 24 h exposure to ERK inhibitors. ASM cells were treated with 25 µM of SF‐3‐030 or 10 µM of ulixertinib (Ulix) in the presence of PDGF (10 ng/ml) for 8 or 24 h. Cells were then lysed, and tryptic peptides were separated and analyzed via proteomic analysis. Tandem mass spectra were searched against a UniProt human reference proteome, and resulting hits were validated at a maximum false discovery rate of 0.01 (see Materials and Methods). Abundance ratios were determined by comparing the peak volumes of peptide ions to MS2 sequencing. The number of genes causing a significant increase or decrease (fold change >2, P < 0.05) were determined compared with a sample treated with PDGF alone (n = 3).

Table 2.1. List of proteins that increase/decrease after 8 or 24 hour exposure to ERK inhibitors. Proteins showing >2 fold increase or decrease (p<0.05) following treatment with PDGF plus SF-3-030 or ulixertinib as compared to cells treated with PDGF alone (n=3) were identified as described in Figure 2.5. The gene name for each protein is listed. Accession numbers are provided for genes with no names at the end of each list in the table.

Proteins that increase at 8h with SF-3-030 treatment AATF CELF1 CYTH2 HMOX1 MACROD1 OTUD6B RBM42 SREK1 TRAPPC4 CALCOCO2 CHCHD2P9 DAXX HYI MRPL43 PFDN6 RNF7 SRXN1 WTAP CARHSP1 CISD2 EPS8 KRT1 MRPS18A PGAM5 RPS3 STAT6 ZFP36L2 CCDC58 CTBS FBLIM1 LACTB2 MYPN PLCD3 S100A9 TDH

CDKN1A CWC27 GDF15 LMOD1 NTAN1 PRPSAP2 SCYL2 TNFAIP2 Proteins that increase at 8h with Ulixertinib treatment ABCB6 CIAPIN1 DCTD FXN HLA-A MAP3K20 NF2 OR5AC2 RGS10 TBCC APPL1 CLTC DGCR8 GATAD2A KIF1BP MARK1 NUP153 PITPNA RSL1D1 TMEM205 TMEM87 CAPNS2 CPM DIAPH2 GLRX KRT27 MBD1 NUP210 PLP2 SCAMP4 B CDC27 CYP27A1 ENOPH1 GNG2 LOX MCRIP1 NUP35 RBM17 STRN4 VPS26B CHMP1B CYR61 ERMP1 HBS1L MAN1B1 MRPL46 OGT RELA TBC1D5 Proteins that increase at 8h with both SF-3-030 and Ulixertinib treatment AAMP CASP1 DHX57 FAM107B KRT2 MRVI1 NSMCE1 PIAS1 SLC9A6 ANXA5 CCDC94 DNAAF5 GABARAPL2 LRCH3 NAA35 OAS3 PPP3CB SSBP3 ATE1 CDK6 DNAJB12 GRIPAP1 LUC7L3 NCAPH OVCA2 PPP6R3 SYNRG ATG2A CEP128 EEF1E1 GTF2E1 LXN NDUFAF2 P4HB RABL3 TOX4 BLOC1S6 CHPF2 EIF2B1 GUSB LYAR NDUFAF4 PCYOX1L RETREG2 TRIP10 BTF3 CLMP AL136295.1 HFE MGAT4B NELFA PEX5 SERPINF1 TRIP6 CARD6 CUL4A EXOSC2 HIP1R MRPL54 NOP14 PFDN4 SHARPIN UHRF2 Proteins that decrease at 8h with SF-3-030 treatment ACSS3 BCL2L13 CDC42EP1 DDX24 GDAP1 MMTAG2 PCCB PTPRK SUMF1 VPS18 ACTR1B BDKRB2 CENPB DNAJB2 ITGA6 MPP6 PDLIM3 RAE1 TBL3 VRK1 ADAM10 BTF3 CIAPIN1 EOMES JAGN1 MRPL13 PITPNA RBM26 TMEM259 WASF2 ADH1B C19orf57 CORO7PAM16 EPHA2 KCMF1 MRPL4 PNKP S100A7 TRAPPC11 WDR77 AGPAT1 C8orf82 CPSF7 FABP3 LRCH4 MRPL53 POLR2L SACS TST YRDC AKT2 CCNY CYP27A1 FGL2 MAP2K4 MRPS23 PPP2R5C SCOC TXNIP No Name B4GALT1 CD46 CYP51A1 FRMD8 MAP3K4 MSH6 PSMD10 SMARCA5 UPF2 A0A087W BCL10 CD97 DCTD FTO MLLT1 NAA40 PTP4A1 SPPL2A VASN V05 Proteins that decrease at 8h with Ulixertinib treatment ABCA1 ASIC1 CFAP20 EIF4E GOPC LPAR1 NT5C RBMS1 SULF1 ZC3H7A ACAT2 ATG9A CHD1 EMP3 GPN1 LYPLA2 NUCB1 REEP3 SYDE1 ZNF622 ACOX2 BUD31 CNOT9 EOGT HNRPLL MAP1S PCOLCE RHOBTB3 TJAP1 ZRANB2 ADAM9 C14orf119 CRNKL1 ERCC2 IFI35 MCL1 PDS5B RPAP3 TNRC6B No Name AES C2orf69 CYP26B1 FADD IGFBP7 MGAT2 PIGK RPRD1A TSPAN31 F5H5P2 AGL CALCOCO2 DDX47 FAM136A INTS6 MINPP1 PIK3C3 SDF4 TSPAN6 AKR1C3 CARHSP1 DDX58 FBLN2 IRF2BPL MRPS26 POLE3 SEC23B UBA5 ANK2 CARMIL1 DNAJC11 FLAD1 KMT2C MRPS6 PRPF38A SOD1 UBE2S ARFGEF2 CD248 DNAJC21 FUNDC1 LAMTOR5 MX1 PTCD3 SP1 VIPAS39 ARL1 CDC123 EDEM3 GADD45GIP1 LEMD3 NDUFAF3 RABEP2 SPATA32 YKT6 ARMC9 CERCAM EFR3A GLA LMF2 NR2C2AP RBFOX2 SPTLC1 YY1 Proteins that decrease at 8h with SF-3-030 and Ulixertinib treatment ANO6 CCDC9 COL3A1 DPY19L1 HSPA1L MRPS34 SLC2A6 STRN3 TRIM38 VPS39 ARFIP1 CCNDBP1 COMMD9 DVL2 IFIT2 MSRA SLC38A2 TBCE USP11 ZBTB38 ARHGEF40 CHMP6 DARS2 GNG5 MFAP1 PTX3 SMARCB1 TCAF1 VAC14 No Name C10orf76 COL1A1 DCTPP1 HNRNPK MRPL16 SLC25A22 SSFA2 TNFRSF11B VPS16 Q9Y676 Proteins that increase at 24h with SF-3-030 treatment AKR1C1 CHMP1B FABP3 HMOX1 MARK1 MRPS34 PLAU SRXN1 TNRC6B ZBTB38 APOOL CORO7PAM16 FCGRT HSPA1B MCCC1 NUBPL PPL SUPT5H TRIP6 BCL10 CREG1 FN3K HSPA1L MFAP1 OVCA2 PRIM2 SYNRG UBE2V2 BNIP3 DGCR8 GCLM KRT10 MMTAG2 P4HB RABL3 TBC1D5 VPS18 CALCOCO2 ELMOD2 GDAP1 LRCH4 MPC2 PEX5 SNX17 TDH VPS26B CEMIP EPS8 GTF2E1 LSM14A MRPL58 PIAS1 SPATA32 TMEM2 XPNPEP3

Table 2.1 continued Proteins that increase at 24h with Ulixertinib treatment TMEM87 AASDHPPT CCNY CLMP ELP1 GPR176 LOX PACSIN3 PRRC2A SLC30A1 B AP1S2 CDC42EP2 COL4A3BP EPHA2 GUSB MRVI1 PLIN2 RHOT2 SLC7A5 WRB ASAP1 CDK6 COMMD6 GDF15 H1FX NAA35 PMVK RSL1D1 SLC9A6 YKT6 ASNS CHPF COMMD9 GIPC1 HMGN2 NOL9 PNPO SCD SMAP2 C10orf76 CIAPIN1 CREB3L1 GNG2 KIF1BP NUFIP2 POTEI SCFD2 SPTBN4 CARD6 CISD2 DIRAS1 GOPC LEMD3 OSBPL9 PPP2R5C SIRT3 TBC1D15 Proteins that increase at 24h with SF-3-030 and Ulixertinib treatment AAMP CENPB DCK GNG5 MCAM NF2 PPIG RBFOX2 SSFA2 YLPM1 ACOX2 CFAP20 DDX20 HNRPLL MCRIP1 NSMCE1 PPP1R21 RPS15A STX16NPEPL1 No Name ADAM9 CHERP DDX47 IK MPHOSPH10 NTMT1 PPP3CB SACS TBC1D22A H7BYZ3 AHR CNOT3 EIF2B1 JAGN1 MRPL16 OAS3 PRPSAP2 SCO1 TNFRSF11B ATP6AP1 COG1 EOGT KLC4 MRPL46 PAM PRTFDC1 SCYL2 TRIM38 BPNT1 CSNK1A1 FBLIM1 KRT27 MT-ND4 PLEC PSMG2 SEC23B UHRF2 CASP1 DAPK3 GABARAPL2 KRT9 NAV3 PLP2 RAB4A SMARCB1 WDR3 Proteins that decrease at 24h with SF-3-030 treatment ANK2 CHPF2 DTX3L GLT8D1 KYAT3 NBN OGT RNF7 STRN3 VCAN ARFGEF2 CLTC DVL2 GOPC LIG1 NCK1 PARP14 RPA2 SYDE1 VIPAS39 ATG9A COL4A3BP EXOSC2 GPX4 LSM5 NCOA5 PITPNA RPL22L1 SYNGR1 WTAP BCAM COL5A1 FAM234A GSDME MBD1 NDUFAF2 PKN2 SEPT10 SYPL1 BLOC1S6 COMMD6 FAM45BP HLA-B MKRN1 NECAP2 PLCD3 SFRP1 TBCE C17orf62 CPM FAM91A1 IFI35 MSRA NEK9 PSEN2 SHARPIN TCOF1 C2orf69 CSF1 FDX1 IFIT3 MXRA7 NT5C RAB4B SLC12A9 TMEM259 CCDC9 CUL4A FTO ITGA2 MYPN NUDT16 RB1 STAT2 TPM4 CDC42EP1 DNAAF5 FYTTD1 ITGA6 MZT1 NUP35 RBMXL1 STAT6 TST CERCAM DNAJC11 GATAD2A ITSN1 NAPG NUP88 RELA STBD1 VAC14 Proteins that decrease at 24h with Ulixertinib treatment ABCA1 CEP128 DYNLL1 INTS6 MMTAG2 NDUFS5 PPARG SCOC TDH VPS16 AES CHCHD2P9 DYNLT3 LPAR1 MRPL17 NDUFS6 PRPF38A SDF4 TES VRK1 ALG1 CNBP ECSIT LXN MRPL18 NDUFS8 PSIP1 SERPINF1 TMA16 WDR74 ANXA5 COL12A1 EFR3A LYPLA2 MRPL50 NHS PTCD3 SLC25A22 TMEM106B ZBTB38 BCKDHB COL18A1 EMC4 MACROD1 MRPS18B NUCB1 RBM10 SLC38A2 TMEM230 ZC3H7A C14orf119 COL1A2 EMP3 MAGED1 MRPS23 PCGF5 RDH14 SLC8A1 TMEM41B CAMSAP2 CREG1 FAM136A MAOA MRPS28 PCOLCE RHOBTB3 SNRPE TOX4 CD302 CSNK2B FUNDC1 MAP1S MRPS30 PDS5A RPS3 SPTAN1 TPMT CD46 DCTD GLS MAP3K20 MRPS31 PFDN6 RPTOR SRXN1 TRAPPC8 CDC123 DCTPP1 HLA-C MAP3K4 MT-ND2 PIGK RRAGA SYNPO TSPAN31 CDKN2AIPNL DNAJC21 IGFBP7 MCL1 NDUFAF3 POLR2B RRM1 SYNRG UBQLN1 CEBPB DUSP3 IL6ST MINPP1 NDUFB8 POP4 SCAMP4 TBCC UQCC2 Proteins that decrease at 24h with SF-3-030 and Ulixertinib treatment ABCC4 ASAP2 CYP27A1 ERCC2 HGSNAT MRPL4 NQO2 PRUNE2 SP1 ACSS3 BRI3BP CYTH2 FADS2 IFIT1 MRPS16 OAS1 PTX3 SPPL2A ADH1B CARHSP1 DDX60 FBLN2 IFIT2 MRPS26 PDLIM3 PVR SULF1 AK5 COL1A1 DHX16 FN1 ISG15 MTFR1L PDS5B RBM42 TCAF1 AKT1S1 COL3A1 DIP2B FXN MCM7 MX1 PLSCR1 RETREG2 TIA1 AL136295.1 CTHRC1 DIS3 GHITM MGAT2 NCBP2 PLSCR4 RRP8 YRDC ANO6 CWC27 EMG1 HBS1L MLLT1 NOP14 POLR2L SEPT6 ZFP36L2

Other similarities between SF‐3‐030 and ulixertinib were observed with proteins involved in NF‐κB, IL‐6, epidermal growth factor receptor (EGFR), and cAMP response element binding (CREB) protein. However, each inhibitor showed unique effects on protein expression related to these signaling molecules. For example, NF‐kB–related

proteins TRIM38, SLC2A6, pentraxin 3 (PTX3), and HSPA1L were inhibited by SF‐3‐030 and ulixerinib after 8 h, and PTX3 remained inhibited by both treatments after 24 h (Table

2.2). However, only SF‐3‐030 increased the expression of HMOX1 and DAXX (Table

2.2). Proinflammatory IL‐6 signaling was elevated upon PDGF treatment at both 8 and 24 h, whereas SF‐3‐030 and ulixertinib suppressed markers of IL‐6 activation at 8 and 24 h.

SF‐3‐030 showed a stronger effect than ulixertinib at 8 h on IL‐6 signaling proteins including AKT2 and MAP2K4 (Table 2.2). The inhibition of PDGF‐induced IL‐6 by SF‐

3‐030 and Vx‐11e as suggested by IPA (Fig. 2.6A) was confirmed experimentally by

ELISA (Fig. 2.6B).

Whereas both SF‐3‐030 and ulixertinib inhibited the expression of various collagens, including COL1A1 and COL3A1, at 8 and 24 h, differential effects at 24 h were observed with SF‐3‐030 inhibiting COL4A3BP and COL5A1, and ulixertinib inhibited

COL12A1, COL18A1, and COL1A2 (Table 2.2). These findings were confirmed by analysis of soluble collagens, which were inhibited by SF‐3‐030 and Vx‐11e (Fig. 2.6C).

Although both SF‐3‐030 and ulixertinib tended to inhibit PDGF‐mediated signaling, SF‐3‐

030 inhibited more proteins related to EGFR signaling in ASM cells 24 h after treatment with PDGF, as evidenced by decreases in FBLN2, integrin subunit alpha (ITGA) 2, ITGA6,

RELA, and TCOF1 (Table 2.2).

IPA also suggested that SF‐3‐030 and ulixertinib had differential effects on PDGF induction of proteins related to the pro-inflammatory mediator high mobility group box 1

(HMGB1) and CREB protein. HMGB1 signaling pathway was activated by PDGF, and only ulixertinib showed an inhibitory effect on its activation at 8 h, as suggested by decreased expressions of PIK3C3 and SP1, whereas SF‐3‐030 showed no observable effect

(Table 2.2). At both 8 and 24 h, ulixertinib repressed proteins related to PDGF‐induced

CREB activity, as indicated by reduced expressions of MCL1, PCOLCE, SOD1, and

TRPM8 channel associated factor 1 (TCAF1) and increased expressions of FXN, CYR61, and caspase 1 (CASP1) (Table 2.2). Although SF‐3‐030 had fewer effects on CREB‐related proteins, similar to ulixertinib, this compound also enhanced CASP1 expression and inhibited TCAF1 after 8 and 24 h (Table 2.2).

Figure 2.6. Effect of ulixertinib and SF‐3‐030 on TGF‐β, IL‐6, and collagen signaling. A) Pathway and gene ontology analysis on proteins identified in Fig. 5 indicated a decrease in TGF‐β signaling. Line shape indicates inherent signaling upon activation of TGF‐β based on literature in which an arrow indicates activation and a straight line indicates inhibition. The color of the line indicates inhibition (blue) or activation (orange) in the current study. The color of the shape behind the genes indicates an increase (red) or decrease (green) compared with a PDGF‐treated sample. The relative fold changes are summarized in Table 2.2. Cells treated with PDGF alone or in the presence of SF‐3‐030 or ulixertinib were analyzed by ELISA for IL‐6 (B) or by Sircol assay for collagen expression (C). FN1, Fibronectin 1; P, PDGF; SP1, transcription factor specificity protein 1; TNFRS11B, tumor necrosis factor receptor superfamily member 11b; Ulix, ulixertinib. *P < 0.05, compared with PDGF‐ treated cells.

Signaling molecule Gene of 8 h 24 h implicated protein PDGF vs. PDGF + PDGF + PDGF vs. PDGF + PDGF + identified untreated SF‐3‐030 Ulix vs. untreated SF‐3‐030 Ulix vs. vs. PDGF PDGF vs. PDGF PDGF TGF‐β ABCA1 NC NC 0.001⋁ 1000⋀ NC 0.001⋁ AhR NC NC NC 0.001⋁ 1000⋀ 1000⋀ CD248 NC NC 0.001⋁ NC NC NC CD46 NC 0.001⋁ NC NC NC 0.001⋁ FN1 NC NC NC NC 0.437⋁ 0.5⋁ TNFRS11B 2.019⋀ 0.052⋁ 0.236⋁ 0.122⋁ 7.278⋀ 3.544⋀

SP1 1000⋀ NC 0.001⋁ 1000⋀ 0.001⋁ 0.001⋁ NF‐κB B4GALT1 NC 0.433⋁ NC NC NC NC

DAXX 0.001⋁ 1000⋀ NC 0.001⋁ NC NC HMOX1 NC 9.987⋀ NC NC 6.76⋀ NC HSPA1L 1000⋀ 0.001⋁ 0.001⋁ NC 1000⋀ NC PTX3 1000⋀ 0.001⋁ 0.351⋁ NC 0.001⋁ 0.001⋁ SLC2A6 NC 0.001⋁ 0.493⋁ NC NC NC TRIM38 NC 0.384⋁ 0.288⋁ 0.001⋁ 1000⋀ 1000⋀ IL‐6 MAP3K4 NC 0.001⋁ NC NC NC 0.001⋁ AKT2 NC 0.001⋁ NC NC NC NC MAP2K4 1000⋀ 0.367⋁ NC 2.302⋀ NC NC ECM COL1A1 NC 0.436⋁ 0.422⋁ NC 0.333⋁ 0.234⋀ COL12A1 NC NC NC NC NC 0.48⋁

COL18A1 NC NC NC NC NC 0.001⋁

COL1A2 NC NC NC NC NC 0.359⋁ COL3A1 NC 0.46⋁ 0.344⋁ NC 0.446⋁ 0.174⋁ COL4A3BP 2.117⋁1 NC NC 1000⋀ 0.001⋁ 2.285⋀

COL5A1 NC NC NC NC 0.358⋁ NC EGFR FBLN2 NC NC 0.001⋁ NC 0.001⋁ 0.448⋁ ITGA2 NC NC NC NC 0.487⋁ NC ITGA6 1000⋀ 0.001⋁ NC NC 0.001⋁ NC RELA 0.001⋁ NC 1000 NC 0.001⋁ NC TCOF1 NC NC NC NC 0.001⋁ NC HMGB1 PIK3C3 1000⋀ NC 0.001⋁ NC NC NC CREB CASP1 0.001⋁ 1000⋀ 1000⋀ 0.001⋁ 1000⋀ 1000⋀ CYR61 0.412⋁ NC 3.044⋀ NC NC NC FXN 0.001⋁ NC 1000⋀ 1000⋀ 0.001⋁ 0.001⋁ MCL1 1000⋀ NC 0.001⋁ 1000⋀ NC 0.001⋁ PCOLCE NC NC 0.181⋁ NC NC 0.417⋁

SOD1 NC NC 0.497⋁ NC NC NC TCAF1 NC 0.001⋁ 0.001⋁ 1000⋀ 0.001⋁ 0.001⋁ Table 2.2. Changes in proteins associated with ASM cell proliferation and airway remodeling induced by PDGF followed by treatment with SF‐3‐030 or ulixertinib for 8 or 24 h. IPA analysis of proteins identified to increase or decrease following treatments indicated in Fig. 5 was used to determine signaling molecules affected. Relative protein expression level changes are presented with an upper limit of 1000 and a lower limit of 0.001. All values shown are abundance ratios with FC > 2 and P < 0.05. NC indicates no significant change under that condition. “⋀”, indicates an increase; “⋁”, indicates a decrease in protein expression relative to untreated controls or PDGF‐treated ASM cells. FC, fold change; Ulix, ulixertinib.

2.5. Discussion

Airway inflammatory diseases such as asthma and chronic obstructive pulmonary disease are characterized by inflammation, mucus production, airway remodeling, and hyperresponsiveness resulting in severe broncho‐constriction. The chronic nature of these diseases leads to structural and functional changes in resident airways cells including ASM cells. Histologic evaluation of asthmatic lung samples reveals a significant increase in the

ASM mass (222-224), which is correlated with asthma severity (47, 194, 225). Current anti‐asthma and anti–chronic obstructive pulmonary disease therapies have only modest effects in inhibiting ASM growth in vitro, and although reports of their effects on ASM mass in vivo from animal studies are mixed, there is little evidence to date that current asthma therapies deter airway remodeling and ASM growth with chronic disease (224).

Thus, new approaches to reduce ASM cell proliferation have the potential to mitigate the detrimental effects of airway remodeling associated with asthma.

In the current studies, we compared the effects of ATP‐competitive and novel function‐selective ERK1/2 kinase inhibitors in reducing the proliferation of ASM cells.

Targeted inhibition of ASM cells is viewed as an important approach to treat asthma (226).

The novel compounds presented in this paper had minimal cytotoxic effects and were able to prevent ASM cell proliferation and reduce downstream AP‐1 activity. Cyclin D1 is a well‐characterized gene whose expression is regulated by AP‐1 that was inhibited by

ERK1/2 inhibitors (Fig. 2.3). Cyclin D1, which is dysregulated in asthmatic models, positively correlates with airway reactivity and is a key regulator of ASM cell proliferation during airway remodeling in asthma (227).

As predicted, the function‐selective SF‐3‐030 compound and the ATP‐competitive inhibitor VX‐11e had differential effects on downstream substrates of ERK1/2. For example, PDGF‐mediated phosphorylation of the ERK1/2 substrate RSK‐1 was inhibited by ulixertinib but not by SF‐3‐030 (Fig. 2.2). In contrast, SF‐3‐030 increased RSK‐1 phosphorylation but inhibited phosphorylation of c‐Fos (Fig. 2.2). Even though SF‐3‐030 or VX‐11e had no apparent effect on phosphorylation of Akt1 on its Ser308 activating site,

VX‐11e inhibited phosphorylation of the Akt1 substrate GSK‐3β. GSK‐3β contains an F‐ site and has been shown to interact with ERK2 at its FRS to allow phosphorylation of

Thr43, which primes GSK‐3β for phosphorylation on Ser9 by RSK‐1 (228). This provides additional evidence that SF‐3‐030 targets ERK2 at the FRS and disrupts the ability for

ERK2 to prime GSK‐3β for additional phosphorylation by active RSK‐1.

Mass spectrometry analysis of relative protein expression levels in PDGF‐treated

ASM cells supports the prediction that SF‐3‐030 is a more selective inhibitor than the ATP‐ competitive ERK1/2 inhibitors. Several pathways implicated in airway remodeling associated with the pathogenesis of asthma were shown to be affected by the ERK1/2 inhibitors. Figure 2.7 summarizes PDGF‐regulated signaling pathways that are affected in

ASM cells in the presence of the ERK inhibitors and include TGF‐β signaling that promotes ECM proteins and inflammation‐related signaling molecules. Both SF‐3‐030 and ulixertinib affected the expression of proteins, consistent with reduced TGF‐β signaling, which has been implicated in the pathology of asthma, including airway remodeling (229).

TGF‐β1 contributes to the vascular remodeling in the asthmatic airway by inducing the production and release of vascular endothelial cell growth factor and plasminogen activator inhibitor, and it induces the secretion of ECM proteins leading to increased thickness of

airway tissue. Suppression of TGF‐β1 activity inhibits epithelial shedding, mucus hypersecretion, angiogenesis, ASM cell hypertrophy, and hyperplasia in an asthmatic mouse model (230). Several of the proteins identified in the current study that are relevant to TGF‐β signaling include tumor necrosis factor receptor superfamily member 11b

(TNFRS11B), ABCA1, AhR, and several collagen isoforms (Fig. 2.7 and Table 2.2).

TNFRS11B (osteoprotegerin), which was inhibited by both SF‐3‐030 and ulixertinib at the

8 h time point, has been implicated as a marker of childhood asthma (231). However, SF‐

3‐030 and ulixertinib increased the expression of TNFRS11B compared with PDGF‐ treated controls after 24 h (Table 2.2). Decreased inflammatory signals through the NF‐kB signaling pathway could be a potential role for the elevated expression of TNFRS11B at this later time point (232).

Other TGF‐β–regulated proteins affected included the collagens COL1A1 and

COL3A1, which have increased deposition in and around ASM cells in human asthmatic airways and promote proliferation of ASM cells (233). Whereas both ERK1/2 inhibitors prevented PDGF‐mediated expression of COL1A1 and COL3A1, only ulixertinib inhibited the ATP‐binding cassette transporter ABCA1, which is involved in cholesterol metabolism

(234). Loss of ABCA1 functions have been linked to increased risk of cardiovascular disease (235); thus, inhibition of this protein may be an off‐target toxicity associated with

ATP‐competitive ERK1/2 inhibitors. We showed that both ERK inhibitors increased the expression of the AhR after 24 h (Fig. 2.7 and Table 2.2). AhR is a multifunctional transcription factor that responds to environmental pollutants and has

Figure 2.7. Pathways and networks affected by ERK inhibitors. Schematic of signaling occurring in ASM cells in the presence of MEK and ERK inhibitors. An arrow indicates activation, and a perpendicular line indicates inhibition. AP‐1 components are italicized and underlined. Proteins marked with an asterisk surrounded by a blue box indicates a signaling molecule implicated to be affected based on changes in associated proteins during proteomic analysis. DRS, D‐recruitment site; RTK, receptor tyrosine kinase; Ulix, ulixertinib.

been linked to the pathogenesis of asthma (236). Deficiencies in AhR have been shown to worsen lung inflammation in response to cockroach allergens (237).

Several inflammatory and proliferative signaling molecules were implicated to be preferentially inhibited by SF‐3‐030, including IL‐6, NF‐κB, CREB, and EGFR (Table

2.2). Increased IL‐6 expression has been linked to the pathogenesis of asthma and other lung diseases (238). In addition, viral infections may exacerbate asthmatic conditions by increasing IL‐6 release from ASM cells (239). NF‐κB is another transcription factor involved in airway remodeling and asthma through regulation of inflammatory and immune mediators (240). HMGB1 and CREB pathways were primarily inhibited by

ulixertinib. HMGB1 is a key proinflammatory mediator in airway hyper‐responsiveness and airway inflammation (241). In addition, CREB modulates the acetylation of chromatin and the transcription of proinflammatory genes in asthma (242). Increases in EGFR expression on epithelial and smooth muscle cells have been associated with the pathology of asthma (243, 244). Several EGFR‐related integrins and ECM proteins were inhibited by

SF‐3‐030 after 24 h treatment (Table 2.2), suggesting a decrease in EGFR‐mediated proliferative signals.

These studies provide evidence that a new class of function‐selective kinase inhibitors are effective at inhibiting proliferative and inflammatory signals associated with

ASM cells. The findings support the concept that selective or targeted inhibition of ERK1/2 signaling functions is an effective approach to mitigate growth factor–mediated proliferation and secretion of ASM cells associated with airway remodeling in asthma with fewer off‐target effects.

Chapter 3. Dysregulated retinoic acid signaling in airway smooth muscle cells in asthma

3.1. Abstract

A deficiency of vitamin A has been shown to exacerbate allergic asthma. Previous studies have shown that Retinoic Acid (RA), an active metabolite of vitamin A and high-affinity ligand for Retinoic Acid Receptor (RAR), is reduced in airway inflammatory conditions where altered RA metabolism contributes to multiple features of asthma including airway hyperresponsiveness and excessive accumulation of airway smooth muscle (ASM) cells.

In this study we aimed at determining the molecular basis for reduced RA and RA- mediated signaling in lung and ASM cells obtained from donors with asthma. Levels of

RA and basal retinol were significantly lower in the lung tissues obtained from human lung donors with asthma and from mice challenged with house dust mite (HDM) compared to healthy human lungs and PBS-challenged mice respectively with no change in the levels of retinyl ester. qPCR analysis revealed a decrease in the expression of Retinoid Binding

Protein-2 and RARγ (not RARα and RARβ) while retinol dehydrogenase (RDH)-10, aldehyde dehydrogenase (ALDH)-1A1, -1A2, and -1A3 and cytochrome P450 (CYP)-

26B1 were upregulated in asthmatic (vs healthy) lung tissues. Quantification of protein abundance in lung tissue by proteomics analysis showed increased expression of DHRS4 and RDH11 proteins and decreased expression of ALDH1A1in murine and human lungs obtained from HDM-challenged (vs. PBS-challenged) mice or human lung donors with asthma (vs. healthy donors) suggesting dysregulated retinoic acid homeostasis. Proteomics analysis also confirmed upregulation of smooth muscle markers and extracellular matrix proteins suggestive of airway remodeling in asthma. Studies in human ASM cells suggest

that basal RA levels and RA biosynthetic capabilities are decreased in asthmatic (vs healthy) ASM cells. Further, treatment of human ASM cells with all-trans RA and RAR subtype specific agonist resulted in inhibition of mitogen-induced cell proliferation and

AP-1 activity by ATRA and RARγ agonist (CD1530). These data suggest that RA metabolism is decreased in lung during asthma with an associated change in expression of proteins in RA pathway, and enhancing RAR signaling using ATRA or RARγ agonist attenuate ASM proliferation providing a basis for exploring RAR agonists in the treatment of asthma.

Keywords retinoic acid, asthma, airway inflammation, airway smooth muscle, vitamin A, retinoids

3.2. Introduction

Asthma is an inflammatory disease of the lower airways (245) and chronic inflammation leads to structural remodeling of airways in the lung that is characterized by increased airway smooth muscle (ASM) mass, accumulation of excessive extracellular matrix and sub-epithelial fibrosis (177-179). Clinical studies reveal a positive correlation between the increase in ASM mass and asthma severity (246). To date, there are no effective pharmacological therapies to mitigate excessive ASM cell proliferation in asthma that contributes to airway remodeling leading to debilitating bronchoconstriction. Further elucidation of the mechanisms involved in asthma pathogenesis are needed for developing effective treatment targeting ASM mass and other features of airway remodeling.

Vitamin A, through its active metabolite retinoic acid (RA), is a master regulator of proliferation, apoptosis, and cellular differentiation in a variety of cell types (101, 105,

109, 247, 248). Deficiency of vitamin A is correlated with reduced airway function and is

shown to exacerbate allergic asthma in humans (249-251) and in rats (252). A study by

Chen et al. showed that all-trans retinoic acid (ATRA) supplement mitigates airway inflammation and ASM cell proliferative responses in asthma using a murine model of asthma (67). In addition, RA and RA-controlled signaling has been shown to suppress platelet-derived growth factor (PDGF)-induced migration of ASM cells and regulate lung development (66) (250). Collectively, these studies demonstrate that RA regulates ASM cellular functions and modulation of the RA signaling pathway contributes to asthma pathogenesis. However, the molecular changes to RA metabolism that occur at the airway cellular level due to allergic inflammation have not been established. RA synthesis from its precursor retinoids and storage in cells are regulated by multiple enzymes, and the cellular functions of RA are determined by the subtypes of RA receptor (RAR) (Fig. 3.1).

In this study, we aimed to comprehensively evaluate RA signaling, including proteins involved in synthesis, transport, and metabolism using advanced proteomics approaches in lung tissues and ASM cells obtained from healthy and asthmatic donors.

Figure 3.1. Retinoic Acid Signaling Pathway. Upon entering the cell, retinol can either be converted to its storage form, retinyl esters, or undergo a two-step oxidation from retinaldehyde to retinoic acid. Retinoic acid is a ligand binding partner of the three RAR isoforms RAR-α, -β, and - γ which, upon ligand binding, lead to changes in transcription and downstream gene expression. Arrows represent the different ways the retinoid metabolites can be reduced or oxidized by various enzymes catalysts.

Further, while the findings from previous study suggest that ATRA treatment inhibits ASM cell proliferation in a murine model of asthma the mechanism by which RA signaling modulates pro-mitogenic signaling in ASM cells is not known. RA effects are mediated via three different subtypes of RAR that are classified as RARα, RARβ, and RARγ. The expression and functional effect of activation of RAR subtypes is cell-type specific.

Furthermore, pro-mitogenic signal transduction mechanisms including mitogen-activated protein (MAP) kinase and phosphatidyl inositol (PI) 3 kinase that have been shown to predominantly regulate ASM cell proliferation converge on transcription factors (17). In this context, activator protein-1 (AP-1), a complex formed by the Jun and Fos protein families, is a convergence point for regulation of ASM cell proliferation by mitogens such as growth factors (e.g. PDGF), cytokines, and chemokines that are relevant in asthma (18,

19). In other cell types, RAR activation is known to negatively regulate AP-1 by inhibiting the binding of Jun protein to target DNA or by inhibiting assembly of transcription factors and cofactors on AP-1-regulated promoters (18). In this study, we investigated the potential for RAR isoform-specific agonists to regulate PDGF-induced ASM cell proliferation and further established RAR-mediated regulation of AP-1 activity in human ASM cells.

Our findings suggest that RA levels are diminished and RA signaling is disrupted in lung tissues and ASM cells obtained from lung donors with asthma compared to healthy controls. RA deficiency in lungs due to asthma are associated with altered expression of key genes and proteins related to retinoid homeostasis and signaling. Further evaluation of the molecular changes in the RA biosynthetic machinery showed human ASM cells obtained from asthmatic lung donors had significantly lower levels of RA due to a diminished ability of ASM cells to synthesize RA. Interrogation of pan- and isoform-

specific RAR agonists suggests that RARγ isoform is a predominant regulator of ASM cell proliferation via regulation of AP-1 activity.

3.3. Materials and Methods

3.3.1. Chemicals and Reagents

AM580, AC55649, CD1530, and ATRA were all purchased from Tocris

Bioscience (Minneapolis, MN, USA). Recombinant human PDGF‐BB was purchased from

BioLegend (San Diego, CA, USA). Cignal Lenti luciferase reporter viral particles for AP-

1 were purchased from Qiagen (Germantown, MD, USA). DMEM was purchased from

Thermo Fisher Scientific (Waltham, MA, USA) and fetal bovine serum was purchased from MilliporeSigma (Burlington, MA, USA).

3.3.2. Human lung tissue isolation

Lung tissues from healthy and asthmatic donors were obtained from National

Disease Research Interchange (NDRI, Philadelphia). Lung tissues were cleaned using ice- cold PBS containing antibiotics (penicillin and streptomycin) and antimycotic

(amphotericin B), cut into small pieces, and frozen in liquid nitrogen for further analysis.

3.3.3. Murine model of asthma

We used 8-10 weeks old female BALB/c mice challenged with PBS or house dust mite (HDM) extract (Dermatophagoides pteronyssinus, Greer Labs, USA) in this study. Mice were challenged with 25 g/35 l/mouse HDM or PBS via intranasal instillation for 5 days a week for a total of 3 weeks as described previously (213). Twenty-four hours post final dosing, mice were anesthetized with Avertin (250 mg/kg) and tracheotomized for assessing respiratory mechanics. Following this, bronchoalveolar lavage (BAL) fluid was collected and lung tissues were harvested and frozen in liquid nitrogen for further analysis of RA

metabolism. The protocol for allergen sensitization and phenotyping is reviewed and approved by the Thomas Jefferson University’s Institutional Animal Care and Use

Committee.

3.3.4. ASM cell isolation and cell culture

Human ASM cells were isolated from deidentified primary bronchi or trachea obtained from healthy donors and donors with asthma as described by Panettieri et al. (212) and studies performed with these cells have been determined not human subjects by the

Institutional Review Board of Thomas Jefferson University. ASM cells were cultured in

DMEM (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum

(MilliporeSigma), 100 units/ml penicillin, and 100 mg/ml streptomycin. The cells were cultured at 37°C in a 95% O2/5% CO2 humidified incubator. ASM cells were passaged no more than 7 times. For RA biosynthesis assays, cells were cultured in serum-free media for

24 h and then were treated with 2 µM holo-Retinol Binding Protein 4-Retinol (RBP4-ROL) for 3 h at 37o C. HoloRBP4-retinol was prepared and used to treat ASM cells as described previously (253).

3.3.5. Sample preparation for retinoid quantification

Lung tissue samples were frozen upon collection and kept at -80o C until assay.

Samples were prepared under yellow light and all retinoids were handled with glass syringes and containers during extraction and quantification procedures. For retinoid quantification, approximately 45 mg murine or 90 mg human lung tissue per replicate was assayed. Tissues were homogenized in 0.9% normal saline as described previously prior to extraction (126). For retinoid quantification in ASM cells, approximately 1.5 x 106 cells in 800 µl 0.9% saline or DMEM media were assayed per replicate. A two-step liquid-liquid

extraction procedure was used to extract retinoids as described previously in detail (121,

126, 129). Briefly, the first extraction was done by mixing cell or tissue lysates with 1 ml or 3 ml 0.025M KOH in ethanol, followed by 5 ml or 10 ml hexane, respectively. The mixture was vortexed and subjected to centrifugation at 1000xg for 30 seconds. The hexane phase containing retinol and retinyl esters was transferred to a new tube and put on ice. For the second extraction, the cell and tissue lysates were mixed with 65 μl or 200 μl 4M HCl followed by 5 ml or 10 ml hexane respectively. The mixture was vortexed and subjected to centrifugation at 1000xg for 30 seconds. The solvent from the second hexane phase containing retinoic acid was transferred to a new tube and put on ice. All samples were then placed under a gentle stream of nitrogen with heating at 30°C until dry. Samples were then resuspended in 60 μl acetonitrile, placed in HPLC vials outfitted with low-volume deactivated glass inserts, and stored at -20°C until analyzed. Each cell or tissue lysate sample was mixed with 2.2 µM all-trans-4,4-dimethyl-RA and 0.9 µM retinyl acetate as internal standards.

3.3.6. Quantification of retinoids (RA, retinol, and retinyl ester)

RA levels were quantified using liquid chromatography-multistage-tandem mass spectrometry using a Shimadzu Prominence UFLC XR liquid chromatography system

(Shimadzu, Columbia, MD) coupled to an AB Sciex 6500 QTRAP hybrid triple quadrupole mass spectrometer (AB Sciex, Framingham, MA) using atmospheric pressure chemical ionization (APCI) operated in positive ion mode as described previously in detail (129). .

RA quantification was performed in 20 l samples and the assay was carried out in the columns maintained at 25°C. Data was analyzed using Analyst (AB Sciex, Framingham,

MA) and RA content in each sample was normalized to tissue weight or cell number.

Levels of retinol and RE were quantified by HPLC-UV using a Waters H-Class

UPLC system equipped with a photodiode array detector operated in single wavelength detection mode according to previously published methodology (254, 255). HPLC-UV chromatograms were generated at 325 nm and peaks were measured for retinol at 4.8 min, the internal standard retinyl acetate at 8.9 min, and RE at 16.6 min using Waters Empower

Software. Total retinol and RE were normalized to tissue weight or cell number.

3.3.7. RNA isolation and real-time qPCR analysis

Total RNA was isolated from whole human lung using Qiagen RNAeasy Maxi Kit

(Qiagen) per manufacturer’s instructions. cDNA was synthesized from 1µg total RNA using Superscript ΙΙΙ reverse transcriptase primed by Oligo (dT) and random primers

(Invitrogen). Real-time qPCR was performed with Power SYBR® Green PCR Master Mix kit (Life Technologies) using the StepOnePlus-Real time PCR System (Applied

Biosystems, Canada). Real-time qPCR primers were obtained from Applied Biosciences and included RBP1 (Hs00161252_m1), RBP2 (Hs00188160_m1), RBP7

(Hs00364812_m1), RDH5 (Hs01123934_g1), RDH10 (Hs00416907_m1), DHRS9

(Hs00608375_m1), DHRS3 (Hs00191073_m1), ALDH1A1 (Hs00167445_m1),

ALDH1A2 (Hs00180254_m1), ALDH1A3 (Hs00167476_m1), ALDH8A1

(Hs00988965_m1), CYP26B1 (Hs00219866_m1), RARα (Hs00940446_m1), RARβ

(Hs00977140_m1), RARγ (Hs01559234_m1), BTG2 (Hs00198887_m1), CASP9

(Hs00154261_m1), CRABP2 (Hs00275636_m1), FABP5 (Hs02339439_g1), GJA1

(Hs00748445_s1), VEGFA (Hs00900055_m1), CCND1 (Hs00765553_m1), and TP53

(Hs01034249_m1). qPCR data were analyzed with the StepOne software (Applied

Biosystems). Relative expression was determined by calculating the ΔCt for each target

gene by subtracting the Ct value of the control gene eu18s (4352655, Applied Biosystems) from the Ct value of each of the target genes. Mean ΔCt of an n=4-7 for healthy lung donors was calculated and was used to determine the ΔΔCt in each of the lung samples from donors with asthma. ΔΔCt values were used to determine the relative expression of target genes using a log scale (base 2).

3.3.8. Cell proliferation assays

Human ASM cells were serum starved for 24 h and then treated with 1–1000 nM of vehicle (basal), AM580, AC55649, CD1530, or ATRA (Tocris Bioscience) with or without 10 ng/ml PDGF for 24 h. Total cellular DNA content was determined by CyQuant

Cell Proliferation Assay (Thermo Fisher Scientific) as described previously (50).

Fluorescence values in each of the treatment conditions were normalized to the fluorescence values in cells treated with vehicle and data are expressed as fold change from the basal.

3.3.9. AP-1 promoter luciferase assays

Cignal Lenti viral particles encoding for luciferase under the control of AP-1 (AP-

1-luc) were purchased from Qiagen (Germantown, MD, USA), and ASM cultures were infected with lentivirus per the manufacturer’s recommendation. Human ASM cells transiently transfected to express AP-1-luc were selected using puromycin and maintained in complete medium containing selection antibiotic as described previously in Sharma et al. (213). ASM cells were seeded in 12-well plates (50,000 cells/well) and cultured for 24 h to achieve ∼60–70% confluency. Cells were then incubated in serum-free medium for

24 h and pretreated with 0–50 nM of compounds for 15 min, followed by stimulation with

10 ng/ml PDGF for 24 h. The luciferase activity in the cell extracts was determined with a

Bright-Glo Luciferase Assay System (Promega, Madison, WI, USA) according to the manufacturer’s instructions. Luciferase activities [luminescence (relative light units/well)] were monitored using a microplate luminometer (Molecular Devices, San Jose, CA, USA).

Relative light units data were normalized using total protein loaded onto each well.

3.3.10. Proteomic mass spectrometry

Murine and human lung tissue was stored at −80 °C until analysis by mass spectrometry. Tissues were homogenized in 50 mM ammonium bicarbonate buffer (pH

7.8) by bead beating using Precellys CK14 lysing kit (Bertin Corp., Rockville, MD) as described previously (256). The lysates were further washed, reduced, alkylated and trypsinolyzed in filter as described previously (257).

Tryptic peptides were separated on a nanoACQUITY UPLC analytical column

(BEH130 C18, 1.7 μm, 75 μm x 200 mm, Waters) over a 165-minute linear acetonitrile gradient (3 – 40%) with 0.1 % formic acid on a Waters nano-ACQUITY UPLC system and analyzed on a coupled Thermo Scientific Orbitrap Fusion Lumos Tribrid mass spectrometer as previously described (257). Full scans were acquired at a resolution of

240,000, and precursors were selected for fragmentation by collision induced dissociation

(normalized collision energy at 35 %) for a maximum 3-second cycle.

Tandem mass spectra were searched against UniProt reference proteomes of Homo

Sapiens and Mus musculus using Sequest HT algorithm (217) and MS Amanda algorithm

(258) with a maximum precursor mass error tolerance of 10 ppm. Carbamidomethylation of cysteine and deamidation of asparagine and glutamine were treated as static and dynamic modifications, respectively. Resulting hits were validated at a maximum false discovery rate of 0.01 using a semi-supervised machine learning algorithm Percolator (218). Label-

free quantifications were performed using Minora, an aligned AMRT (Accurate Mass and

Retention Time) cluster quantification algorithm (Thermo Scientific, 2017). Protein abundance ratios between groups were measured by comparing the MS1 peak volumes of peptide ions, whose identities were confirmed by MS2 sequencing as described above.

Pathway, upstream regulator, and statistical analysis were performed as described previously (259). Proteins showing a false discovery rate (FDR) adjusted ANOVA p-value

< 0.05 were considered significantly changed and used for further analysis. Canonical pathways and upstream regulators were considered significantly perturbed if Benjamini-

Hochberg corrected Fisher's exact test p-value is < 0.05.

3.3.11. Statistical Analysis

Levels of retinoids in lung tissues and ASM cells were normalized to tissue weight or cell number respectively for each experiment. ASM cell proliferation and AP-luc activity data are expressed as fold change from vehicle-treated cells. An unpaired, two- tailed student’s t-test or one-way ANOVA with Bonforonni post-hoc test was used to determine statistical significance (p<0.05). Data analyses were performed using Prism 8

(GraphPad) software.

3.4. Results

3.4.1. Altered RA homeostasis in lung tissues obtained from human donors with asthma and HDM-challenged mice.

Retinol is the substrate from which RA is synthesized in cells. Retinol can also be stored in the form of retinyl esters (RE) (Fig. 3.1). To determine if RA homeostasis is dysregulated in lung due to airway inflammation in asthma, we quantified retinoids (RA, retinol and RE) in lung tissues obtained from human donors with asthma and from HDM-

challenged murine model of allergic asthma using quantitative LC-MS/MS methodology developed by our laboratory (121, 122, 126, 127, 129). RA levels were significantly

(p<0.05, n=3-6) lower in the lung tissues obtained from human lung donors with asthma and from mice challenged with HDM compared to healthy human lungs and PBS- challenged mice respectively (Fig. 3.2A-B). Decrease in RA levels in asthmatic lungs could be due to a decrease in the availability of the substrate. Therefore, we determined the levels of retinol, the substrate for RA synthesis and RE, the stored form of vitamin A in asthmatic and healthy lungs using quantitative HPLC-UV methodology (121). Basal retinol level trended lower reduced in the asthmatic (vs. healthy) human lung and HDM (vs. PBS)- challenged murine lung (Fig. 3.2C-D). The levels of RE in human lung tissues from asthmatic donors, and murine lung tissues from HDM-challenged animals were similar to the levels in lungs obtained from healthy donors and PBS-challenged mice respectively

(Fig. 3.2E-F).

Figure 3.2. Levels of RA, ROL, and RE are reduced in lung tissues obtained from donors with asthma and HDM-challenged mice. A-B. Levels of RA in human lung tissues from healthy or asthmatic lung donors (A) and murine lung tissues from PBS- or HDM-challenged mice (B). C-D. Levels of ROL in human lung from healthy or asthmatic donors (C) and murine lung from PBS- or HDM-challenged mice (D). E-F. Levels of RE in human lung from healthy or asthmatic donors (E) and murine lung from PBS- or HDM- challenged mice (F). Data are mean ± SEM with n=3-6 per condition. *p<0.05 using unpaired, two-tailed student’s t-test. H-healthy, AS- asthmatic, PBS- phosphate buffer saline, HDM- house dust mite.

3.4.2. Genes related to retinoid transport, metabolism, and signaling are altered in lungs from human donors with asthma.

To interrogate the dysregulation of retinoid homeostasis in asthma, we quantified transcript levels of proteins involved in retinoid transport and synthesis, RAR subtypes, and RA targets in lungs from human donors with or without asthma using real-time qPCR.

Relative expression was determined by calculating the ΔCt for each target gene based on the control gene eu18s, averaging the ΔCt of an n=4-7 for healthy donors to calculate the

ΔΔCt value for each of the target genes in RNA obtained from individual asthmatic lung tissue, and determining relative expression using a log scale. Expression of Retinoid

Binding Protein (RBP)-2 was significantly decreased with no change in the expression of

RBP1 and RBP7 in lungs from asthmatic vs. healthy donors (Fig. 3.3). Among the retinoid pathway enzymes which catalyze the reaction from retinol to retinaldehyde, an

intermediate in the biosynthesis of RA, expression of retinol dehydrogenase (RDH)-10 was significantly (p<0.05, n=4-5) increased in lung tissues obtained from donors with asthma compared to healthy controls while there was no change in the relative expression of RDH5 and dehydrogenase/reductase SDR family member (DHRS)-9 in asthmatic lungs (Fig. 3.3).

There was no change in the expression of retinoid pathway enzyme, DHRS3, which is a reductase that catalyzes the conversion of retinaldehyde to retinol, between asthmatic and healthy lungs (Fig. 3.3). Expression of aldehyde dehydrogenase (ALDH)-1A1, -1A2, and

-1A3, which convert retinaldehyde to RA, was significantly (p<0.05) increased while the expression of ALDH8A1 remained unchanged in lung tissues from asthmatic donors compared to healthy lung tissues (Fig. 3.3). There was no change in expression of fatty acid-binding protein 5 (FABP5) which delivers RA to its alternative pathway receptor

Peroxisome proliferator-activated receptor beta/delta (PPAR /), and cellular retinoic acid-binding protein 2 (CRABP2) which delivers RA to the classical retinoic acid receptors

(RAR) in lungs obtained from donors with asthma compared to healthy donors (Fig. 3.3).

Finally, expression of cytochrome P450 (CYP)-26B1 which catabolizes RA into its various metabolites showed a significant increase in relative expression in the lungs from asthmatic vs. healthy donors (Fig. 3.3).

RA signaling in mammalian cells is mediated via three subtypes of RARs.

Expression of RARγ, not RARα and RARβ, was significantly (p<0.05) decreased in the lungs from asthmatic vs. healthy donors. (Fig. 3.3). Regulation of cellular functions by RA is mediated by changes in expression of genes by RA via RAR. Changes in the availability of RA ligand or the expression of RAR receptor can result in modulation of expression of

RA target genes and therefore, we further determined the expression of RA target genes in

human lungs. The expression of select RA target genes BTG anti-proliferation factor 2

(BTG2), caspase 9 (CASP9), Gap junction alpha-1 protein (GJA1), vascular endothelial growth factor A (VEGFA), Cyclin D1 (CCND1), and tumor protein p53 (TP53) showed no significant changes in relative expression in the lungs from asthmatic vs. healthy donors

(Fig. 3.3). Collectively these data shows that transcription of proteins involved in RA homeostasis and RA signaling is disrupted in asthmatic lung.

Figure 3.3 (next page) mRNA expression of retinoid chaperones, pathway enzymes, receptors, and targets genes are dysregulated in human lungs from asthmatic donors. Relative gene expression changes from asthmatic and healthy human lungs were determined. Retinoid chaperones include retinol binding proteins (RBP)-1, 2, and 7. Retinoid pathway enzymes include (1) Retinol dehydrogenase (RDH)-5, and 10, and Dehydrogenase/reductase SDR family member (DHRS)-9 which all catalyze the reaction from retinol to retinaldehyde, an intermediate in the biosynthesis of RA, (2) DHRS3 which is a reductase of retinaldehyde to retinol, (3) Aldehyde dehydrogenase (ALDH)- 1A1, 1A2, 1A3, and 8A1 that convert retinaldehyde to RA, (4) Fatty acid-binding protein 5 (FABP5) which delivers RA to its alternative pathway receptor PPAR /, and cellular retinoic acid-binding protein 2 (CRABP2) which delivers RA to the classical retinoic acid receptors (RAR), and (5) Cytochrome P450 (CYP)-26B1 which catabolizes RA into its various metabolites. The three subtypes of retinoic acid receptors (RAR) include RAR-α, β, γ which regulate downstream effects of RA. Select RA targets include BTG2, CASP9, GJA1, and VEGFA, CCND1, and TP53 which are all downstream targets of RA signaling. n=4-7 per condition. *p<0.05 using unpaired, two-tailed student’s t-test.

R B P 1

R e t in o id R B P 2 * C h a p e r o n e s

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R D H 1 0 *

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D H R S 3

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A L D H 8 A 1

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C YP 2 6 B 1 *

R A R  R e t in o ic A c id R A R  R e c e p t o r s R A R  *

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C C N D 1 H e a lth y A s th m a tic T P 5 3

0 5 1 0 1 5

E x p re s s io n F o ld C h a n g e (2 ^ -  C T )

3.4.3. Expression of proteins involved in RA metabolism and signaling are altered in asthmatic lungs.

To determine the impact of asthma on expression of proteins involved in RA signaling, we used label-free quantitative proteomics to determine changes in protein expression in human lung obtained from normal and asthmatic donors as well as PBS- and

HDM-challenged mice. Data is shown as an abundance ratio of asthmatic lungs versus normal lungs. Proteins that are reduced or not detectable in lungs from asthmatic donors are shown as an abundance ratio of 0.001. Proteins that are reduced or not detectable in lungs from normal donors are shown as an abundance ratio of 1000. Quantification of protein abundance in lung tissue showed increased expression of DHRS4 and RDH11 proteins in murine and human lungs obtained from HDM-challenged (vs. PBS-challenged) mice or human lung donors with asthma (vs. healthy donors) suggesting dysregulated retinoic acid homeostasis (Fig. 3.4 and Fig. 3.5). Further, our proteomic quantitation data shows changes in expression of proteins previously associated with low retinol and RA,

ASM markers and other proteins associated with asthma (Fig. 3.5). The abundance of

RBP4 and Transthyretin (TTR), which are involved in transport of retinol in circulation, and for which reduced expression has been associated with low retinol, are decreased in the asthmatic lung compared to healthy controls (Fig. 3.5). The abundance of proteins for which an increase or decrease in expression are correspondingly associated with low RA include RDH11 and DHRS4 which are increased in abundance while the expression of

ALDH1A1 is decreased in lungs obtained from donors with asthma (Fig. 3.4 and Fig. 3.5).

Airway remodeling in asthma includes increases in ASM mass and our proteomic analysis revealed increased expression of smooth muscle markers, smooth muscle alpha (α)-2 actin

(ACTA2) and Myosin Heavy Chain 11 (MYH11) in the asthmatic lung (Fig. 3.5). Previous studies have demonstrated that RA deficiency in ASM is associated with an increased mRNA expression of Collagen Type III Alpha 1 Chain (COL3A1), Collagen Type IV

Alpha 1 Chain (COL4A1), Collagen Type IV Alpha 2 Chain (COL4A2), Collagen Type

VI Alpha 3 Chain (COL6A3), Amine Oxidase Copper Containing 3 (AOC3), and

Microfibril Associated Protein 4 (MFAP4). Our proteomics study revealed increased abundance of COL3A1, COL4A1, COL4A2, COL6A3, AOC3, and MFAP4 in asthmatic lungs (Fig. 3.5). Increased expression of MMPs have been associated with reduced RA conditions. HCK, a Src family tyrosine kinase, matrix metalloproteinases (MMPs), and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs), are all downstream targets of AP-1 that are associated with airway remodeling in asthma. Our proteomic analysis also revealed a significant decrease in TIMP3 and TIMP1, and a significant increase in HCK,

MMP8, and MMP9 in asthmatic lungs (Fig. 3.5). Other proteins associated with asthma including Serpin Family A Member 1 (SERPINA1), Apolipoprotein E (APOE), and

Cytochrome B5 type B (CYB5B) all had decreased abundance ratios while Disintegrin and

Metalloproteinase Domain-containing protein 10 (ADAM10) showed a high abundance in the asthmatic lung (Fig. 3.5) further validating our experimental model and proteomics approach.

Collectively, findings described above suggest that RA metabolism is altered in lungs obtained from human donors with asthma as well from HDM-challenged mice with an associated alteration in the expression of proteins involved in RA synthesis, storage, transport, and breakdown.

Figure 3.4. Enzyme abundances, as determined by proteomic analysis, show retinoic acid homeostasis is dysregulated similarly in human and murine lung. Changes in protein expression obtained from LC-MS/MS based proteomic profiling of (A) asthmatic and non- asthmatic human lungs and (B) PBS and HDM treated murine lungs. Abundance ratio derived from n=3/condition. *p<0.05 using unpaired, two-tailed student’s t-test.

a s s o c . T T R * w ith lo w R B P 4 R O L *

a s s o c . AL D H 1 A1 w ith D H R S 4

lo w R A R D H 1 1

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M F AP 4

AO C 3 m R N A w as p re v io u s ly re p o rte d C O L 6 A3 a s e n ric h e d in C O L 4 A2 R A -d e fic ie n t A S M C O L 4 A1

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0 5 0 5 0 5 0 0 ...... 0 0 0 1 1 2 2 3 0 1 A b u n d a n c e R a tio (a s th m a /h e a lth y )

Figure 3.5. Protein expression of retinoid-related, ASM marker, AP-1 regulated, and asthma associated proteins in human asthmatic lung tissue. Changes in protein expression obtained from LC-MS/MS based proteomic profiling of asthmatic and non-asthmatic human lungs. +abundance ratio = 0.001 (reduced to not detectable in asthma). Proteomic profiling in lungs from HDM model shows similar results (see examples in Fig 3.4). Abundance ratio derived from n=3/condition. *p<0.05 RBP4, TIMP1, MMP9, and APOE have expression changes consistent with reduced RA.

3.4.4. Levels of RA are reduced in ASM cells derived from human asthmatic lung tissue. To further evaluate the molecular changes in the RA biosynthetic machinery, we used human ASM cells obtained from healthy and asthmatic lung donors and determined the capabilities of ASM cells to synthesize RA. Basal cellular, secreted, and total RA levels were reduced (n=3, p<0.05) in ASM cells obtained from donors with asthma compared to healthy controls (Fig. 3.6A-C). Further, treatment with 2 µM holo-Retinol Binding Protein

4-Retinol (holoRBP4-ROL) for 3 h to assess RA biosynthesis capacity resulted in reduced levels of cellular, secreted and total RA in asthmatic ASM cells (Fig. 3.6D-F). To determine whether basal substrate (ROL) levels or storage capabilities (RE) were affected in asthmatic ASM cells we determined the amount of retinol and RE in the untreated ASM cells and culture media. There was no significant difference in the total, cellular and secreted retinol and RE levels in ASM cells obtained from asthmatic vs. non-asthmatic lung donors (Fig. 3.6G-L).

Together these studies suggest that there is a disruption in RA homeostasis since basal RA levels and RA biosynthesis capacity are reduced with no change in the substrate

(ROL) availability and storage capabilities (RE) in human ASM cells derived from lung donors with asthma.

Figure 3.6. RA basal levels and RA biosynthesis capacity reduced in human ASM cells derived from lung donors with asthma. (A-C) Basal levels of RA (A-C) and RA biosynthesis capacity (D-F) are reduced in ASM cells isolated from human lung donors with asthma vs. healthy donors. RA biosynthesis was quantified after treatment with (2 µM) holo-Retinol Binding Protein 4-Retinol (holoRBP4-ROL) for 3 h. Basal levels of ROL (G-I) and basal levels of RE (J- L) are increased in ASM cells isolated from human lung donors with asthma. Levels of RA, ROL and RE were determined in cells and media, and shown as cell, media, and total for each condition. Data are mean  SEM with n=3 per condition. *p<0.05 using unpaired, two-tailed student’s t-test.

3.4.5. RAR agonist and ATRA inhibit PDGF-induced cell proliferation in ASM cells.

Our data suggest that RA metabolism is dysregulated in lung tissues and ASM cells isolated from donors with asthma with an associated reduced capacity of asthmatic ASM cells to synthesize RA. We hypothesized that exogenous RA supplementation would modulate ASM function and tested whether RAR agonists affect PDGF-induced ASM cell proliferation. We treated ASM cells with different concentrations of vehicle, all-trans RA

(ATRA) or RAR isoform-specific agonists. Pretreating human ASM cells with CD1530

(RAR agonist) and ATRA (RAR pan-agonist), not AM580 (RAR agonist) and AC55649

(RAR agonist) inhibited PDGF-induced cell proliferation in a dose-dependent manner

(Fig. 3.7A). Large differences in RAR agonist affinities have been previously reported and the more robust inhibition of cell proliferation by RARγ compared to the pan-ATRA agonist is likely due to the stronger affinity of the RARγ agonist (260). To confirm that these changes are not a result of feedback regulation of production of RA, ASM cells were treated with holo-RBP4-ROL and the RAR-agonists at two different concentrations and

RA levels were quantified after a 3h treatment. RA production did not change in the presence of the RAR subtype-specific agonists at 10 nM or 1 µM concentrations after 3 h of treatment with holo-RBP4-ROL (Fig. 3.8) as expected.

Figure 3.7. Treatment with RAR agonists inhibits PDGF-induced proliferation and AP-1 promoter activity in ASM cells. A. Vehicle or PDGF-stimulated (10 ng/ml) ASM cells were treated with different concentration of pan-RAR agonist ATRA, RARα agonist AM580, RARβ agonist AC55649, or RARγ agonist CD1530 and total cellular DNA content determined (as a marker of cell proliferation) using CyQuant dye at 24h (n=3). B. RAR agonist and ATRA inhibited PDGF-induced AP-1 activity in ASM cells (n=5) (* p<0.05 vs. vehicle).

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R 0 H A S H A S H A S H A S H A S H A S H A S

h o lo R B P 4 -R O L h o lo R B P 4 -R O L h o lo R B P 4 -R O L h o lo R B P 4 -R O L h o lo R B P 4 -R O L h o lo R B P 4 -R O L h o lo R B P 4 -R O L + 1 0 n M AM 5 8 0 + 1 u M AM 5 8 0 + 1 0 n M AC 5 5 6 4 9 + 1 u M AC 5 5 6 4 9 + 1 0 n M C D 1 5 3 0 + 1 u M C D 1 5 3 0

Figure 3.8 RAR agonists do not change RA production within normal or asthmatic airway smooth muscle cells. The effect of agonists of RAR-α (AM580), RAR-β (AC55649), and RAR-γ (CD1530) on RA biosynthesis was determined by treating healthy (H) vs asthmatic (AS) human ASM cells with holoRBP4-retinol (2 µM) for 3 h. Data are mean ± SEM with n=3 per condition. *p<0.05 using unpaired, two-tailed student’s t-test.

3.4.6. RARγ agonist and ATRA inhibit AP-1 activity in human ASM cells.

AP-1 is activated by mitogens such as PDGF and acts as a convergence point for regulation of ASM cell proliferation. Our proteomics quantitation data shows changes in protein expression of AP-1 regulated genes including increased abundance of MMP9,

MMP8, and HCK, and decreased abundance of TIMP1 and TIMP3 in the asthmatic lung compared to lung tissues obtained from healthy donors (Fig. 3.5). In other cell types, AP-

1 has been shown to be negatively regulated by ligand-bound RAR (65, 180). Based on this, we next determined whether RAR agonists affect AP-1 activity in ASM cells. ASM cells transiently expressing AP-1-luc were treated with PDGF ± veh/RAR agonists and luciferase activity was assessed after 24 h of treatment. Treatment of human ASM cells with ATRA or CD1530 significantly (p<0.05) inhibited PDGF-induced AP-1 activity in

ASM cells (Fig. 3.7B). These data demonstrate that AP-1 activity is negatively regulated by RARγ in ASM cells.

These data suggest that treatment of human ASM cells with ATRA or RAR subtype-specific agonist results in inhibition of AP-1 activity thereby inhibiting ASM cell proliferation.

3.5. Discussion Physiological functions of vitamin A are mediated by its active metabolite RA and deficiency of vitamin A is correlated with reduced airway function and severity of asthma in humans (184, 249-251, 261) and in rats (252), and other obstructive airway diseases

These studies suggest that dysfunctional RA pathway may contribute to asthma pathogenesis. To establish the molecular basis for dysfunctional RA homeostasis in asthmatic lungs and airway cells (e.g., ASM cells) comprehensively we employed multiple biochemical approaches. Our findings suggest that levels of RA, retinol and retinol esters

are reduced in lungs and in ASM cells obtained from donors with asthma and HDM- challenged murine lungs.

To further interrogate changes in retinoid metabolism in lung due to asthma we investigated changes in expression of genes involved in retinoid transport, metabolism, and signaling. Consistent with reduced RA levels, expression of RBP2, a retinol binding protein, was significantly decreased in the lungs from asthmatic vs. healthy donors (Fig.

3.3 and Fig. 3.9). Increased relative expression of RDH10, an enzyme that catalyzes retinol to retinaldehyde, and ALDH1A1, ALDH1A2, and ALDH1A3, aldehyde dehydrogenases that convert retinaldehyde to retinoic acid, all show significant increases in mRNA expression in the asthmatic vs. healthy donors which could result in increased levels of RA

(Fig. 3.3 and Fig. 3.9). However, the significantly increased levels of CYP26B1, and significantly decreased levels of RARγ, indicate that RA is being catabolized into its more polar catabolites rather than interacting with RAR to effect transcriptional change.

Collectively, these changes in gene expression are consistent with dysregulated RA homeostasis and signaling in lung cells in asthma.

Further, our findings from LC-MS/MS-based label-free quantitation of protein expression in lung tissue demonstrated increased expression of two retinal reductases

(RDH11 and DHRS4) that catalyze the conversion of retinal to retinol as part of the reversible first step of RA biosynthesis (40) in asthmatic lungs compared to healthy controls (Fig. 3.5). We have previously shown that retinal reductase expression is essential to RA homeostasis (28, 29, 41-43).

Figure 3.9. Summary of genes and proteins identified in this study that affect RA signaling in the human lung. Retinoid chaperones include retinol binding proteins (RBP)-1, 2, 4, and 7. Retinoid pathway enzymes include (1) Retinol dehydrogenase (RDH)-5, and 10, and Dehydrogenase/reductase SDR family member (DHRS)-9 which all catalyze the reaction from retinol to retinaldehyde, an intermediate in the biosynthesis of RA, (2) DHRS3, DHRS4, and RDH11 are reductases of retinaldehyde to retinol, (3) Aldehyde dehydrogenase (ALDH)-1A1, 1A2, 1A3, and 8A1 that convert retinaldehyde to RA, (4) Fatty acid-binding protein 5 (FABP5) which delivers RA to its alternative pathway receptor PPAR /, and cellular retinoic acid-binding protein 2 (CRABP2) which delivers RA to the classical retinoic acid receptors (RAR)-α, -β, and -γ, and (5) Cytochrome P450 (CYP)-26B1 which catabolizes RA into its various metabolites. Select RAR targets include BTG2, CASP9, GJA1, and VEGFA, CCND1, and TP53 which are all downstream targets of RA signaling.

Further, the expression of ALDH1A1 was reduced in asthmatic lungs; ALDH1A1 is a key retinal dehydrogenase that catalyzes the conversion of retinal to RA (67, 75).

Increased ALDH1A1 mRNA did not translate to increased ALDH1A1 protein levels (Fig.

3.3, Fig. 3.5). The reduced levels of endogenous RA and observed enzyme changes provide a molecular basis for dysregulation of RA metabolism in lung cells in asthma and are consistent with reduced RA signaling. Our findings also demonstrate: i) increases in ASM

marker proteins, ACTA2 and MYH11, which have been reported to be upregulated when

RA signaling is blocked resulting in increased ASM mass (67); ii) increases in several collagens, AOC3, and MFAP4 that were consistent with previous reports of mRNA enriched in both human and mouse RA-deficient ASM (67); and iii) protein changes consistent with impaired retinoid transport (RBP4 and TTR) (262, 263) as well as RA biosynthetic enzyme changes consistent with reduced RA (RDH11, DHRS4, ALDH1A1)

(264) providing a molecular basis for RA dysregulation in asthma that is consistent with reduced RA signaling (Fig. 3.9). Changes in protein expression in asthmatic human lung were consistent with increased AP-1 activity, including increases in matrix metalloproteases (MMP-8/9) as well as decreases in tissue inhibitors of matrix metalloproteases, (TIMP1/3) (Fig. 3.5) (30, 265).

RA-mediated signaling is known to regulate a variety of cellular functions (266,

267). In this study, we focused our attention on ASM cells considering the role of ASM cells in physiological regulation of lung functions and asthma pathogenesis. In this context, the RA-controlled signaling regulate ASM cell differentiation during lung development

(268). A study by Chen et al. showed that all-trans retinoic acid (ATRA) supplement mitigates multiple features of allergen-induced asthma using a murine model of asthma

(67). Since ASM mass plays a key role in airway remodeling and hyperproliferation of

ASM cells is correlated with asthma severity (47, 194, 225) we hypothesized that ASM cells obtained from donors with asthma would have reduced RA and enhancing RAR- mediated signaling would be beneficial for reducing proliferation of ASM cells. In support of this hypothesis our findings suggest that ASM cells from donors with asthma have reduced RA levels and asthmatic ASM cells lack the ability to synthesize RA from a

physiological substrate (Fig. 3.6D-F). To assess if RA activity could be restored and modulate ASM cell proliferation we treated PDGF-induced ASM cells with isoform- specific RAR agonists and ATRA, a pan-RAR agonist. CD1530, a RARγ agonist and

ATRA inhibited PDGF-induced ASM cell proliferation in a dose-dependent manner in

ASM cells (Fig. 3.7A). Although RARα and RAR-specific agonists have previously been shown to be able to inhibit cell proliferation in a cancer model (269) these agonists failed to inhibit ASM cell proliferation. CD1530 was previously shown to be effective in reducing murine oral-cavity carcinogenesis (270). An interesting future direction would be to investigate the effect of CD1530 and other RAR subtype specific agonists in mitigating features of allergic asthma in murine model. In fact, CD1530 has been shown to be more effective than other isoform-specific RAR agonists in preventing heterotopic ossification with minimal side effects in vivo (176). Of note, Vitamin A diet supplementation has previously shown no association with decreased risk in asthma (271), which is consistent with our finding of impaired RA biosynthesis where increasing substrate via supplementation would be hampered by the defects in RA biosynthesis. As such, an RAR agonist treatment would be a more effective therapeutic approach to restore RA signaling while limiting off-target effects.

We further investigated the mechanism of anti-proliferative action of RAR agonists in human ASM cells by focusing on the effect of RAR activation on AP-1 activity. Our findings demonstrate that activation of RAR by RAR agonist or ATRA inhibited PDGF- induced activation of AP-1 in human ASM cells (Fig. 3.7B). Transrepression of AP-1 by

RAR activation has been shown in other cell types (269). The AP-1 complex is formed through the homo- or hetero-dimerization of TFs belonging to Jun, Fos, and ATF family

proteins in various ways (272). In other cell types, RAR activation is known to negatively regulate AP-1 by inhibiting the binding of Jun protein to target DNA or by inhibiting assembly of transcription factors and cofactors on AP-1-regulated promoters (65). The physiological and pathophysiological conditions under which AP-1 is activated effects the composition of AP-1 and its phosphorylation status to affect different transcriptional promotors downstream (273). Our gene expression and proteomics studies demonstrated increased expression of AP-1-regulated genes in lung tissues obtained from donors with asthma. While our studies in ASM cells suggest inhibition of AP-1 activity by RAR agonists future studies will establish the mechanism by which RAR activation inhibits AP-

1 activity in human ASM cells.

In summary, our findings establish the molecular basis for reduced RA metabolism and RA-mediated signaling in lung tissues and ASM cells obtained from asthmatics.

Further, our findings also provide a proof-of-concept that RA signaling can be explored to mitigate ASM mass which is a component of airway remodeling associated with asthma.

Interestingly, RAR- subtype appears to be a critical regulator of RA-mediated cellular functions in ASM cells which could be explored further as a potential anti-asthma therapeutic.

Chapter 4. Targeting the ERK and RA pathway has an additive effect in controlling ASM cell proliferation via the AP-1 complex

4.1. Abstract

ASM cell hyperproliferation in asthma is one of the main causes of increased ASM cell mass that leads to bronchoconstriction and is a determinant of disease severity. ERK1/2 and RAR both play important roles in regulating pathways that signal for the formation of the AP-1 complex that leads to hyperproliferation of ASM cells. ERK1/2 plays a major role in the regulation of Fos proteins while RAR antagonizes Jun proteins to disrupt dimerization in many cell types. Therefore, in combination, they could disrupt two of the major players in the AP-1 complex formation and activation. To establish if separate mechanisms occur in ASM cells, we first looked at the effects of PDGF on retinoid production. While ERK1/2 signaling and downstream effectors have been shown to be induced by PDGF, we have shown that PDGF does not influence retinoid production within

ASM cells. Previous work showed that RAR agonists and ERK1/2 inhibitors are capable of inhibiting ASM cell proliferation and AP-1 activity. In this study we have shown that a co-treatment of RAR agonists and ERK1/2 inhibitors results in an additive inhibitory effect on ASM cell proliferation and AP-1 activity versus either treatment alone. Overall, these studies show that an ERK1/2 inhibitor and RAR agonist combination therapy could be a potential form of treatment for preventing AP-1 activation to prevent hyperproliferation of

ASM cells.

Keywords activator protein-1, airway smooth muscle, asthma, kinase inhibitor, retinoid agonist

4.2. Introduction

Asthma is an obstructive lung disease that is characterized by airway remodeling that leads to airway obstruction, inflammation, and persistent airway hyperreactivity (274).

Airway smooth muscle (ASM) cells play a critical role in airway remodeling through ASM cell hyperproliferation that results in narrowing of the airways and secretion of mucus and cytokines (275). To date, there are no effective therapies to combat ASM cell proliferation that contributes to hyperresponsive airways and debilitating bronchoconstriction.

Polypharmacology has been shown to have unprecedented efficacy while mitigating the development of drug resistance (276). Current COPD clinical studies are using a polypharmacological approach to suppress corticosteroid-sensitive and –insensitive cytokine production through the use of multikinase inhibitors (51). The use of multikinase inhibitors to treat cancer has been used clinically since 2005 to disrupt multiple processes that sustain cancer growth including proliferation and angiogenesis (277). In addition, the use of multi-target drugs can also be safer than single-target drugs as demonstrated by tapentadol, an μ-opioid receptor agonism with norepinephrine reuptake inhibition, that showed fewer side-effects than classical opioids alone (278). With its record of unprecedented efficacy while mitigating off-target effects, a polypharmacological approach could be used to fill the therapeutic gap in combatting ASM cell hyperproliferation in asthma.

ASM cell proliferation is induced by several growth factors and bronchoconstrictors that result in the activation of two main pathways, the mitogen‐ activated protein kinase (MAPK)/extracellular signal regulated kinase (ERK1/2) pathway and the phosphoinositide 3 kinase (PI3K) pathway (279, 280). We have previously shown

that ERK1/2 inhibitors can be used to inhibit PDGF-induced AP-1 activity that leads to

ASM cell proliferation by preventing the phosphorylation and activation of AP-1 transcription factors (50). Additionally, as shown in the previous chapter, ASM cell AP-1 activity and proliferation are inhibited by a pan-RAR (ATRA), and RARγ-specific

(CD1530) agonist. In other cell types, retinoic acid receptor (RAR) activation negatively regulates AP-1 by inhibiting Jun proteins from binding to target DNA or by inhibition of the assembly of transcription factors and cofactors on AP-1-regulated promoters (65).

ATRA has also been shown to be an effective inhibitor of ASM cell migration induced by

PDGF via inhibition of the PI3K pathway, but not ERK1/2 (66). Therefore, since they are working through separate mechanisms of action, without interfering with the other, we hypothesized that a combined treatment of ERK1/2 inhibition and RAR agonism will have an additive effect in controlling ASM cell proliferation.

While ERK1/2 signaling and downstream effectors have been shown to be induced by PDGF, we have shown that PDGF does influence retinoid production within ASM cells establishing a separate mechanism of action for AP-1 regulation. Our findings also suggest that a co-treatment of RAR agonists and ERK1/2 inhibitors results in an additive inhibitory effect on ASM cell proliferation and AP-1 activity versus either treatment alone. Overall, these studies show that a polypharmacological, combination therapy of an ERK1/2 inhibitor and RAR agonist could be an effective therapeutic option for preventing AP-1 activation that leads to the hyperproliferation of ASM cells and debilitating bronchoconstriction in asthma.

4.3. Materials and Methods

4.3.1. Chemicals and Reagents

The function‐selective ERK1/2 inhibitors SF‐3‐030 was synthesized and characterized as previously described (183). An antibody recognizing β‐actin was purchased from Cell

Signaling Technology (Danvers, MA, USA). The total cyclin D1 antibody was purchased from Santa Cruz Biotechnology (Dallas, TX, USA). Recombinant human PDGF‐BB was purchased from BioLegend (San Diego, CA, USA). CD1530 and ATRA were purchased from Tocris Bioscience (Minneapolis, MN, USA).

4.3.2. ASM cell isolation

Human ASM cells were obtained from healthy and asthmatic donors. Primary ASM cell cultures were generated using deidentified primary bronchi per Panettieri et al. (212), and studies performed with these cells have been determined not human subjects by the

Jefferson University Institutional Review Board.

4.3.3. Cell culture

ASM cells were cultured in DMEM (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (MilliporeSigma). The cells were cultured at 37°C in a 95% O2/5%

CO2 humidified incubator. ASM cells were passaged no more than 7 times.

4.3.4. Sample preparation for retinoid quantification

Samples were prepared under yellow lights and all retinoids were handled with glass syringes and containers. Cells were seeded in 6-well plates and grown to ∼85% confluence.

Media was replaced with serum-free media and then cells were treated with PDGF 10ng/ml or 2 µM RBP4-ROL alone or in combination for 3h at 37°C. HoloRBP4- retinol was prepared and used to treat ASM cells as previously described in Shannon et al (253). For

retinoid quantification in ASM cells, approximately 1.5 x 106 cells in 800 µL 0.9% saline or 800 µL media were assayed per replicate. A two-step liquid-liquid extraction was used to extract retinoids as previously described in detail (121, 126, 129).

4.3.5. Retinoid quantification

RA was quantified using liquid chromatography-multistage-tandem mass spectrometry using a Shimadzu Prominence UFLC XR liquid chromatography system (Shimadzu,

Columbia, MD) coupled to an AB Sciex 6500 QTRAP hybrid triple quadrupole mass spectrometer (AB Sciex, Framingham, MA) using atmospheric pressure chemical ionization (APCI) operated in positive ion mode as previously described in detail (281).

Retinol and RE were quantified via HPLC-UV using a Waters H-Class UPLC system equipped with a photodiode array detector operated in single wavelength detection mode according to previously published methodology (254, 255).

4.3.6. Cell proliferation assays

Cells were serum starved for 24 h and then stimulated with PDGF‐BB (10 ng/ml) and co- treated with 100- 5µM of SF-3-030 and 0-50nM of ATRA or CD1530 for 72 h.

Measurement of cellular DNA was determined by CyQuant Cell Proliferation Assay

(Thermo Fisher Scientific).

4.3.7. AP-1 promotor luciferase assays

Cignal Lenti luciferase reporter viral particles for AP‐1 were purchased from Qiagen

Sharma et al. (213). ASM cells were seeded in 12‐well plates (50,000 cells/well) and

incubated for 24 h to achieve ∼60–70% confluence. Cells were then incubated in serum‐ free medium for 24 h. Cells were pretreated with 0-5 µM of SF-3-030 alone or in combination with 0-50M of ATRA or CD1530 for 15 min, followed by stimulation with

10 ng/ml PDGF for 24 h. The luciferase activity in the cell extracts was determined with a

Bright‐Glo Luciferase Assay System (Promega, Madison, WI, USA) according to the manufacturer's instructions. Luciferase activities [luminescence (relative light units/well)] were monitored with a microplate luminometer (Molecular Devices, San Jose, CA, USA).

Relative light units data were normalized using total protein loaded onto each well.

4.3.8. ASM cell treatments and lysate preparation

ASM cells were seeded in 24‐well plates (50,000 cells/well) and incubated for 18 h to achieve ∼85% confluence. Cells were treated with 10ng/ml PDGF with vehicle, 1 µM

CD1530, 25µM SF-3-030, or 25µM SF-3-030 + 1 µM CD1530 for 24 h. Cells were washed twice with cold PBS 1× (Quality Biological, Gaithersburg, MD, USA), harvested in RIPA buffer (MilliporeSigma) supplemented with Protease Inhibitor Cocktail Set III

(MilliporeSigma), and subjected to a freeze‐thaw cycle followed by sonication 3 times for

3 s, resting on ice in between. Lysates were centrifuged at 5000 g for 15 min, and the supernatant was transferred to a new microcentrifuge tube. Protein concentrations were determined using a Bradford assay (Bio‐Rad, Hercules, CA, USA). Lysates were stored at

−80°C in aliquots to minimize freeze‐thaw cycles.

4.3.9. Immunoassays

Immunoblotting following electrophoresis on 10–15% SDS‐polyacrylamide gels was previously described (183).

4.4. Results

4.4.1. PDGF does not influence retinoid production within ASM cells.

Retinol (ROL) is the substrate from which RA is synthesized in cells. Retinol can also be stored in the form of retinyl esters (RE). To determine if retinoid levels are influenced by PDGF signaling in ASM cells, we quantified retinoids (RA, ROL and RE) in ASM cells obtained from healthy and asthmatic human lung donors. We first looked at whether PDGF influenced the basal levels of RA, ROL, and RE in ASM cells. ASM cells were treated with DMSO-vehicle only or Platelet Derived Growth Factor-BB (PDGF) at

10ng/ml for 3h at 37°C (n=3-5 per condition). Upon quantification, no significant changes in the cell or media were observed for any of the retinoids (Fig. 4.1).

Next, we looked at whether RA biosynthesis was affected by PDGF treatment in

ASM cells. Cells were treated with 2 µM holo-Retinol Binding Protein 4-Retinol

(holoRBP4-ROL) alone or in combination with PDGF (10ng/ml) for 3h at 37°C (n=3-5 per condition). Similar to the basal condition, upon quantification no significant changes in the cell or media were observed for any of the retinoids suggesting PDGF does not influence retinoid production in ASM cells. Since ERK1/2 signaling and downstream effectors have been shown to be induced by PDGF, this data further establishes a separate mechanism of action for AP-1 regulation in ASM cells.

4.4.2. RAR agonists in combination with SF-3-030 have an additive effect on inhibiting ASM cell proliferation.

Previous data from our lab shows that RAR agonists and SF-3-030 inhibit PDGF- induced ASM cell proliferation (50). To test whether a combination of an RAR agonist and

SF-3-030 would have an additive inhibitory effect we treated PDGF- stimulated

Figure 4.1. PDGF does not affect retinoid production within ASM cells. ASM cells were treated with DMSO vehicle only (grey bars), PDGF 10ng/ml (black bars), 2 µM holoRBP4-ROL (RBP4) (white bars), or in combination (black and white bars) for 3h at 37°C (n=3-5 per condition). RA in cell (A) or media (B), ROL in cell (C) or media (D), and RE in cell (E) or media (F) showed no significant changes when PDGF was added either alone or in combination with holoRBP4-ROL.

ASM cells with SF-3-030 (100nM- 5µM) in combination with pan-RAR agonist ATRA or

RARγ agonist CD1530 (0-50nM) for 72h (n=3). The combination of either RAR agonist with 1 or 5 µM of SF-3-030 showed significant inhibition of ASM proliferation. This data suggests that there is an additive effect between the two classes of molecules in inhibiting

ASM cell proliferation.

Figure 4.2. Effect of RAR agonists in combination with SF-3-030 on ASM cell proliferation. Co-treatment of PDGF-stimulated ASM cells with ATRA or CD1530 (50 nM) and different concentrations of SF-3-030 showed a significant inhibition of ASM proliferation by SF-3-030 at 1 and 5 µM at 72h (n=3) suggesting a synergy between the two classes of molecules in inhibiting ASM cell proliferation.

4.4.3. AP-1 promoter activity and downstream targets are inhibited by a combination of RAR agonists and SF-3-030.

AP-1 is a convergence point for regulation of PDGF-induced ASM cell proliferation. Since the combination of RAR agonists and SF-3-030 showed additive inhibition of PDGF-induced ASM cell proliferation, we wanted to elucidate whether the regulation of AP-1 activity is additive as well. ASM cells were pretreated with 0-5 µM of

SF-3-030 alone or in combination with 0-50M of ATRA or CD1530 for 15 min, followed by stimulation with 10 ng/ml PDGF for 24 h. AP-1 promoter luciferase activity was reduced by SF-3-030 and RAR agonists alone, and further inhibited by a combination of both. This finding is consistent with the additive inhibition of proliferation by a combination treatment of RAR agonists and SF-3-030. To further elucidate how AP-1 activity is affected, we looked at one of its downstream markers of proliferation cyclin-D1.

ASM cells were treated with 10ng/ml PDGF and DMSO vehicle (veh), 1 µM CD1530,

25µM SF-3-030, or 25µM SF-3-030 (SF) + 1 µM CD1530 (CD) for 24 h. Cyclin D1 levels

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were determined by immunoblotting which showed that cyclin-D1 was inhibited by SF-3-

030 alone or in combination with CD1350.

Figure 4.3. Effect of RAR agonists in combination with SF-3-030 on ASM cell AP-1 activity and downstream targets. (A) Cells were pretreated with 0-5 µM of SF-3-030 alone or in combination with 0-50M of ATRA or CD1530 for 15 min, followed by stimulation with 10 ng/ml PDGF for 24 h. AP-1 activity was reduced by SF-3-030 and RAR agonists alone, and further inhibited by a combination of both (n=5, * p<0.05 v.s. PDGF vehicle, # p<0.05 v.s. SF-3-030 veh). (B) ASM cells were treated with 10ng/ml PDGF and vehicle (veh), 1 µM CD1530, 25µM SF-3- 030, or 25µM SF-3-030 (SF) + 1 µM CD1530 (CD) for 24 h and cyclin D1 levels were determined by immunoblotting. PDGF-induced cyclin D1 (an AP-1 target gene) was inhibited by SF-3-030 alone or in combination with CD1350. β-actin was used as a loading control.

4.5. Discussion

Asthma is an obstructive pulmonary disease that is characterized by inflammation, airway remodeling, and hyperresponsiveness that leads to debilitating bronchoconstriction.

Although ASM cells are a major contributor to bronchoconstriction, current treatment options are not effective against ASM cell proliferation. Therefore, new therapeutic approaches for the treatment of asthma are needed. Since polypharmacological approaches have previously shown unprecedented efficacy while mitigating off-target effects, this study aimed to determine if this strategy could be used to fill the therapeutic gap in combatting ASM cell hyperproliferation in asthma.

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Increased ASM mass in asthma is driven primarily by growth factors, such as

PDGF, and cytokines and chemokines, which directly effect ASM (186-188). Both in vitro and in vivo studies have implicated the ERK1/2 signaling pathway is one of the primary mediators of these mitogenic effects on ASM growth (191). We have previously shown that a function-selective ERK1/2 inhibitor, referred to as SF-3-030 (50), an RAR agonist,

CD1530, and a pan-RAR agonist, ATRA, inhibit PDGF-induced AP-1 activity that leads to ASM cell proliferation. To determine whether a polypharmacological approach using these two molecules would be beneficial, we first wanted to establish separate mechanisms of action in AP-1 inhibition.

ERK1/2 inhibitors are known to inhibit PDGF-induced AP-1 activity in ASM cells by preventing the phosphorylation and activation of AP-1 transcription factors (50). While not characterized in ASM cells, in other cell types, retinoic acid receptor (RAR) activation has been shown to antagonize AP-1 transcription factor binding to target DNA and inhibit of the assembly of transcription factors and cofactors on AP-1-regulated promoters (65).

To further establish these separate mechanisms of action within ASM cells, we determined if retinoid levels are influenced by PDGF signaling. Quantification of retinoids (RA, ROL and RE) in ASM cells obtained from healthy and asthmatic human lung donors showed no significant change at basal levels or in RA biosynthesis upon treatment with PDGF (Fig.

4.1). Since ERK1/2 regulation of AP-1 is primarily driven through PDGF induction, and retinoids are not affected, the inhibition of AP-1 by RAR is likely through some other mechanism.

To test our hypothesis that a combination of an RAR agonist and SF-3-030 would have an additive inhibitory effect we treated PDGF- stimulated ASM cells with SF-0-030

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and RAR agonists. Co-treatment resulted in an additive inhibitory effect, greater than that of SF-0-030 or RAR agonists alone, on ASM cell proliferation (Fig. 4.2) and AP-1 activity

(Fig. 4.3). Further studies to evaluate the effects of this polypharmacological approach are needed, however, this study sets a precedent for the use of a function-selective ERK1/2 inhibitor and RAR agonist in the treatment of AP-1 mediated ASM cell proliferation that leads to bronchoconstriction in asthma.

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Chapter 5. Conclusions and Future Directions

In this project, the overarching goal was to determine the effectiveness of a novel therapy involving a non-ATP competitive ERK1/2 inhibitor and targeting RAR-mediated antagonism of AP-1 in inhibiting proliferation of airway smooth muscle (ASM) cells.

Chapter 1 discussed how protein kinases and retinoic acid play a role in obstructive lung and other inflammatory diseases, as well as the need for innovative therapeutic approaches for treating asthma due to steroid-resistance and gaps in current treatment options. In chapter 2, function-selective ERK1/2 inhibition was shown to prevent AP-1 activity and

ASM cell proliferation. This sets a precedent for the therapeutic use of a function-selective inhibitor since it shows similar efficacy to an ATP-competitive inhibitor while minimizing off-target effects. The findings discussed in Chapter 3 suggest that RA signaling is dysregulated in asthma as demonstrated by lower levels of retinoids and altered expression of key genes and proteins in asthmatic lungs and ASM cells. Further, our findings demonstrate that pan-RAR and RARγ-isoform specific agonists are predominant regulators of ASM cell proliferation via regulation of AP-1 activity. Therefore, RAR agonist could be another potential therapeutic agent in mitigating ASM cell proliferation. Finally, findings presented in Chapter 4 suggest the use of a combined therapy of a function- selective ERK1/2 inhibitor and RAR agonist could have therapeutic benefit in inhibiting

AP-1 activity and proliferation of ASM cells.

While the focus of this study was on how ASM cell proliferation can be targeted to prevent bronchoconstriction in asthma, future studies are needed to investigate the effects of these therapies on other cell types in the lung. Since cells in the lung all interact closely in response to stimuli (186, 279), co-culturing ASM cells with airway epithelial cells could

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provide insight into interaction between ASM and epithelial cells in regulating AP-1 activity via ERK1/2 or RAR pathways. Lung fibroblast are another key pulmonary cell type known to play a role in airway remodeling in asthma. The effect of function-selective

ERK1/2 inhibitor and RAR agonists alone or in combination of fibroblast proliferation and myofibroblast differentiation needs to be investigated. Beyond cell culture, investigating the effectiveness of ERK1/2 inhibitors and RAR agonists alone or in combination in mitigating multiple features of asthma (airway inflammation, remodeling and hyperresponsiveness) using a murine in vivo model of allergic asthma.

In addition to asthma, there are several other airway diseases where this research could potentially be applied including chronic obstructive pulmonary disease (COPD) and lymphangioleiomyomatosis (LAM) disease. Both diseases are characterized by aberrant cell proliferation that leads to shortness of breath and airway obstruction. Although asthma and COPD have a lot of overlap, the two diseases differ in the segment of the bronchial tree affected, the nature of the inflammation, the inciting immune stimulants, and their long-term course (280). Current COPD treatments are limited and can lead to more severe diseases, such as pneumonia so innovative treatment strategies are needed. LAM disease is a rare disease that occurs exclusively in young and middle-aged woman and there is no effective treatment for LAM disease currently (281). It is often mistaken for asthma or

COPD due to the overlap of symptoms presented. This disease is of particular interest for future studies because one of the main problems in disease pathogenesis is the proliferation of smooth muscle-like cells called “LAM cells”. Since we have shown that function- selective ERK1/2 inhibition and RAR antagonism of AP-1 reduces ASM cell proliferation,

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it would be interesting to see if this could be translated to LAM cells to help fight this rare disease.

One of the main goals of this study was to test whether a function-selective ERK1/2 inhibitor would be an effective therapeutic approach for asthma. The use of function- selective inhibitors has come about to try to mitigate off-target effects and drug resistance that occurs with ATP competitive inhibitors. The first three appendices contain chapters from a book project that the Shapiro Lab worked on collaboratively, in whole titled “Next

Generation Kinase Inhibitors: Moving Beyond the ATP Binding/Catalytic Sites” Ed. Paul

Shapiro, Springer 2020 (Appendix 1,2,3). The chapters summarize, in part, the current innovative approaches to inhibit kinases beyond the ATP binding/catalytic site. Appendix

1 contains an introduction to kinases including a historical overview, how kinase signaling occurs in the cell, as well as current approaches to inhibiting kinases (282). Appendix 2 describes how type III, IV, V, and VI kinase inhibitors can be used to avoid or co-opt the

ATP binding/catalytic site including examples of current inhibitors being developed (283).

Appendix 3 highlights structural features that determine specific protein kinase–substrate interactions that could serve as potential drug targets to inhibit disease-causing activities while preserving beneficial activities (284). Collectively, this project offers insights into how kinases can be targeted in innovative ways to have beneficial clinical effects while minimizing potential off-target effects. These novel and innovative approaches targeting kinases could prove beneficial in many obstructive lung diseases.

Appendix 4 contains the materials, protocols, and analysis associated with this manuscript cited in the introductory section of this dissertation (256). This was the first project I worked on in the Kane lab and provided me with the basis for the RA quantitation

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studies I performed throughout this dissertation study. The protocols and analysis techniques outlined in this appendix offer insights into the most effective and efficient ways to quantify retinoids in cells, tissues, and in vivo. Proper quantitation of retinoids is essential for understanding the aberrant signaling that leads to disease and these techniques can be applied to future studies.

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Appendix 1. Introduction to Kinases, Cellular Signaling, and Kinase Inhibitors4

Abstract Protein kinases are essential regulators of cellular functions and responses to extracellular signals. Through phosphorylation of substrates, protein kinases control cell proliferation and survival. Proliferative disorders, such as cancer, are often observed to have excess protein kinase activity due to genetic mutations. Thus, the development of specific drugs to inhibit protein kinases in cancer cells has been a major goal of academic and pharmaceutical industry research during the last three decades. This chapter will provide a brief historical overview of groundbreaking discoveries describing the importance of protein kinases and the identification of clinically relevant kinase inhibitors. An outline of protein kinase classes, signaling pathways, and structural features will introduce current kinase inhibitor approaches and provide the rationale for identifying alternative approaches to block excess protein kinase activities that promote disease.

Keywords Kinase, Inhibitors, Disease, Drug Discovery

Historical Overview of Protein Kinases and Targeted Inhibition

Kinases, derived from the Greek word kinein meaning “to move,” are ubiquitous enzymes that have become prominent therapeutic targets in the treatment of a variety of diseases. Kinase enzymatic activity is in every cell of every species and facilitates physiological responses to both intracellular and extracellular signals. Through the process of phosphorylation, kinases move or transfer cellular information that regulates a variety of other proteins essential for the survival of the organism. The presence and appreciation

4 Shapiro P.; Martinez R.; Defnet A. Introduction to Kinases, Cellular Signaling, and Kinase Inhibitors. In: Shapiro P. (eds) 2020. Next Generation Kinase Inhibitors. Springer, Cham. https://doi.org/10.1007/978-3- 030-48283-1_1

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of phosphorylated proteins and their importance in biological processes began in the early

1900s. It was in Phoebus Levene’s laboratory at the Rockefeller Institute for Medical

Research where phosphorylated serine residues were identified on the proteins casein and phosvitin, which are abundant in milk and egg yolks, respectively (282). Subsequently, in the 1940s, Gerty and Carl Cori’s research at Washington University in St. Louis discovered active and inactive forms of the phosphorylase enzymes that transfer inorganic phosphate to acceptor molecules and are involved in the process of glycogen metabolism. Cori’s research was awarded a Nobel Prize in Physiology or Medicine in 1947 and provided the foundation for understanding the process of reversible phosphorylation (283). Following this award, the significance of the enzymatic activity of kinases and the process of phosphorylation received a significant boost from the pioneering work of George Burnett and Gene Kennedy at the University of Chicago. Their 1954 publication in the Journal of

Biological Chemistry conclusively demonstrated that rat liver mitochondria extracts contained a protein enzymatic activity, which the authors referred to as a phosphokinase, that extracts a phosphate group from the energy molecule ATP and covalently links it to another protein (284). These studies revealed a new area of biology that describes how cells use the mineral phosphorus, and its biological form phosphate, to convey information and regulate biological molecules via phosphorylation to accomplish specific cellular functions.

Subsequent discoveries by Edmond Fischer and Edwin Krebs in 1956, at the

University of Washington, demonstrated that kinases regulate protein functions in response to extracellular signals and that kinase-mediated phosphorylation events are reversible

(285). The significance of the work by Dr. Fischer and Dr. Krebs, who had trained in the

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previously mentioned Cori laboratory, was recognized with the Nobel Prize in Physiology or Medicine in 1992. The balance between the activities of kinases that mediate phosphorylation and phosphatase enzymes that facilitate de-phosphorylation is essential for regulation and maintenance of most cellular functions. There are numerous genetic alterations, which will be highlighted in subsequent chapters, responsible for dysregulated kinase activity and the disruption of the balance between phosphorylation and dephosphorylation events. These dysregulated phosphorylation events alter the steady state, or homeostasis, of cellular functions and, ultimately, contribute to the pathology of a variety of diseases.

Over the last several decades, a vast amount of research has discovered and described specific kinases and their functions in regulating specific physiological functions. These findings have revolutionized our understanding of the role of kinases in disease processes and the development of kinase-specific drug therapies. In most cases, the therapeutic objective is to inhibit constitutively active kinase activity found in proliferative disorders, like cancer. Despite a detailed understanding of kinase structures and functions, as well as the availability of potent and selective kinase inhibitors, the ability to achieve sustained patient responses to most of the current kinase inhibitors is limited. This raises the questions of how much is really known about the regulation of kinases in complex biological systems and their role in regulating disease. Furthermore, the multifaceted nature of diseases like cancer may limit the use of potent and selective kinase inhibitors that only target one aspect of the disease but allow compensatory kinase signals that protect cancer cell proliferation and survival. In contrast to the development of very selective kinase inhibitors, there is growing interest in developing inhibitors that target multiple kinases

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simultaneously or polypharmacologic properties that are uniquely effective against several dysregulated kinases associated with specific diseases (286).

The first, and arguably most successful, program to develop specific small- molecule kinase inhibitors to treat a specific type of cancer was realized by Drs. Nicholas

Lydon and Brian Druker in the 1990s with the drug imatinib for the treatment of chronic myelogenous leukemia (CML) (287). It was well known that CML cells contained a genetic translocation resulting in the fusion of the breakpoint cluster region (BCR) gene on chromosome 22 with the Abelson tyrosine kinase (ABL) gene from chromosome 9. The resulting BCR-Abl fusion protein is constitutively active, and this mutant tyrosine kinase drives the proliferation of white blood cells in nearly every CML patient. Dr. Druker hypothesized that BCR-Abl is a viable drug target and that inhibition of BCR-Abl would improve the therapeutic outcomes of CML patients. Dr. Lydon, working on drug discovery programs at Ciba-Geigy (now part of Novartis), provided the compound STI571, also referred to as imatinib mesylate (brand name Gleevec® or Glivec®), which is an ATP competitive inhibitor of BCR-Abl and other tyrosine kinases. As Drs. Lydon and Druker pointed out, there was skepticism from other scientists and the pharmaceutical industry that specific kinases inhibitors could be developed and that targeted inhibition of a single kinase would be effective against cancer cells with multiple genetic defects (288). However, the results of the first clinical trials in 1998 and 1999 testing imatinib in CML patients had remarkable outcomes with almost every patient showing improvement. Moreover, the patients had very few side effects and a 5-year follow-up showed patient survival approaching 90% compared to 50% for patients on traditional chemotherapies (288). While the success of imatinib in treating CML patients could be partially attributed to its off-

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target effects on other tyrosine kinases, these groundbreaking trials provided the justification for the Food and Drug Administration (FDA)’s approval in 2001 for clinical use. Imatinib remains one of the top-grossing cancer drugs with over $1.5 billion in sales in 2018. Importantly, the introduction of tyrosine kinase inhibitors such as imatinib has significantly improved the survival of CML patients as compared to before these drugs were available (289). With the therapeutic success of imatinib, scientists and the pharmaceutical industry were provided the framework to pursue the development of other kinase-selective inhibitors for treating disease.

Despite the clinical success of imatinib in treating CML, sustained treatment responses using inhibitors of kinases for other cancer types or diseases have been difficult to achieve. The current approaches used to inhibit protein kinases involved in disease consist of small-molecular-weight compounds (e.g., small molecules) or monoclonal antibodies. As of June 2019, there were approximately 50 small-molecule inhibitors of protein kinases approved by the FDA for clinical use. The number of FDA-approved small- molecule kinase inhibitors from 1999 to 2018 shows an increasing trend over the last decade (Fig. A1.1). An excellent comprehensive description of the pharmacological properties of FDA approved small-molecule kinase inhibitors is available (290). In addition, there are more than 30 FDA-approved monoclonal antibodies developed to block the activity of mostly receptor and nonreceptor tyrosine kinases involved in disease.

Several reviews outline the development of monoclonal antibodies along with their therapeutic potential and limitations (291, 292). However, the development of kinase- targeted monoclonal antibodies will not be the focus of subsequent chapters.

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Figure A1.1. FDA-approved small-molecule kinase inhibitors (1999-2018).

A major goal of this book project is to convey that the current approaches to block kinases, with either small molecules or monoclonal antibodies, have mostly failed to produce effective or sustained clinical responses despite the significant evidence supporting kinases as key drivers of disease. As such, new approaches to block important kinase activities involved in disease need to be explored. It is reasonable to suggest that the lack of effective kinase inhibitors can be explained by an inadequate understanding of the biological and genetic determinants that drive the disease. As such, inhibition of a key kinase predicted to drive the pathology of a specific disease is not enough and additional biological targets need to be considered. While this is likely true for many conditions, it can also be argued that the kinase being targeted is appropriate; it is just that the approach used to target a specific kinase is ineffective at producing durable clinical responses. To set the stage for the discovery of new approaches to inhibit kinases, the first chapters will provide an overview of the kinase structure, kinase-signaling networks, and the current approaches to develop small-molecule inhibitors of kinases involved in disease.

Therapeutic uses and limitations of the current kinase inhibitors, including the emergence of drug resistance will be highlighted.

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Small-molecule kinase inhibitors are classified into six categories commonly referred to as type I–VI kinase inhibitors that are grouped largely based on the structural interactions between the inhibitor and target kinase (293). Chapter 2 provides a concise summary of the basic features of the type I and II kinase inhibitors, which are currently the most common approach to target kinases, and act by preventing interactions with ATP when the enzyme is in an active or inactive state, respectively. Chapter 3 will summarize recent developments in the type III–VI kinase inhibitors. Type III kinase inhibitors target allosteric sites in the kinase domain but do not affect ATP binding whereas type IV kinase inhibitors target allosteric sites outside the kinase domain and are generally designed to interfere with the interactions between kinases and other regulatory proteins or substrates.

Type V kinase inhibitors are referred to as bivalent compounds that target both the ATP- binding site and unique allosteric sites outside the kinase domain. Finally, type VI kinase inhibitors form covalent interactions with cysteine and other amino acids in the ATP- binding site or other regions of the kinase. A recent review of approaches to target the extracellular signal-regulated kinases-1 and 2 (ERK1/2) provides an excellent visual description of the mechanism of action for type I–VI kinase inhibitors (64).

The second major goal of this book will be to highlight new approaches to target protein kinases, including the development of novel type IV small-molecule kinase inhibitors and kinase-targeted peptides that selectively inhibit specific kinase functions.

Function-selective kinase inhibitors account for the diversity of protein substrates that are regulated by kinases involved in proliferative diseases, such as cancer, or inflammatory disorders. There are documented examples of how kinase-mediated regulation of substrates can drive a cellular response, but regulation of other substrates is involved in modulating

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that response through negative feedback mechanisms. Thus, kinases contribute to maintaining homeostasis in normal and diseased cellular responses through both positive and negative feedback regulation. Inhibition of kinase activity with the current type I and

II inhibitors block all positive and negative enzyme activity whereas disruption of key kinase-substrate interactions has the potential to block undesirable kinase functions (e.g., protumorigenic) while maintaining desirable kinase functions (e.g., antitumorigenic negative feedback). Lack of durable responses of many kinase inhibitors used in the clinic may be attributed to inhibition of both positive and negative kinase functions. It will be interesting to see whether novel proteolysis targeting chimera (PROTAC) approaches that can be designed to selectively degrade kinases and other proteins involved in disease (294) will also have similar issues with efficacy.

The design of function-selective kinase inhibitors is based on a large body of information describing the structural features that determine specific protein-protein interactions (PPIs) and the biological consequences of those interactions. Chapter 4 will provide examples of PPIs focusing on specific kinase interactions with substrate proteins.

These studies have helped in the design of new approaches to target key PPIs involved in disease. In addition, Chap. 4 will overview the emergence of acquired drug resistance to current kinase inhibitors used in the clinic, which presents a major barrier to sustained and durable patient responses. It is hypothesized that function-selective kinase inhibitors will prevent or mitigate the emergence of drug resistance observed with current kinase inhibitors that block all enzyme activity.

The final chapters will describe specific examples of theoretical and experimental approaches to develop kinase inhibitors that act outside of the ATP/catalytic site and inhibit

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specific kinase functions. Chapter 5 describes how computational models can facilitate the rationale design and analysis of new compounds that target specific PPIs and, in particular, those that involve kinase interactions with specific protein substrates. Chapter 6 provides a comprehensive description of known substrate-docking sites on the extracellular signal- regulated kinases (ERK1/2) and opportunities to develop type IV inhibitors that target these sites for treating cancer. Chapter 7 will describe the synthesis of novel peptide sequences that lock into secondary structures that recognize specific kinase sites involved in substrate recognition. Finally, Chap. 8 expands on the use of peptides that selectively modify kinase functions and outlines the challenges that need to be overcome before these agents can be used in the clinic. In conclusion, the evidence presented in these chapters will provide support for the discovery and development of novel kinase inhibitors that selectively block some, but not all, enzymatic functions. The development of new approaches aimed at partial inhibition of kinase functions involved in disease is predicted to lead to more effective and sustained therapeutic responses.

Overview of Protein Kinase Signaling Pathways

Protein kinases are essential regulators of cellular functions and responses to external signals. Protein kinases accomplish their regulatory role mostly, but not always, by catalyzing the transfer of phosphate from ATP onto substrates. Of the more than 500 distinct genes that encode for human protein kinases (295), it is estimated that ~80% fall into the category of serine or threonine kinases while the remaining 20% consist of tyrosine or histidine kinases (296). However, it is estimated that roughly 90% of all phosphorylation events in human cells occur on serine residues while approximately 10% occurs on threonine residues, and less than 1% of phosphorylation events occur on tyrosine residues

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(296). Given that most of the kinase inhibitors used in the clinic today block the actions of tyrosine kinases, these numbers suggest there are tremendous opportunities for the discovery of new kinase inhibitors.

Protein kinases are classified into AGC, CAMK, CMGC, CK1, STE, TK, and TKL subgroups based on their phylogenetic tree (295). The AGC protein kinase group consists of approximately 60 serine/threonine kinases related to protein kinases A, G, and C. One feature key to the regulation of AGC kinase activity is a hydrophobic region in the C- terminal that interacts with a pocket in the catalytic region. This interaction site was named the PIF, 3-phosphoinositide-dependent protein kinase–1 (PDK1)-interacting fragment, unique to the ACG family (297). The CAMK group is the abbreviation for around 80 serine/threonine kinases related to the calcium-calmodulin–dependent protein kinases. The identification of a unique calcium/calmodulin (CaM)-binding domain is a regulatory feature found in about half of kinases in the CAMK family (298).

There are roughly 62 members of the serine/threonine kinase CMGC group that include the cyclin-dependent kinases (CDK), mitogen-activated protein kinases (MAPK), glycogen synthase kinases (GSK), and CDC-like kinases (CLK). The CK1 group, or casein kinase-1 family, is a small group of 12 serine/threonine kinases that are the most structurally distinct group of eukaryotic protein kinases. A unique aspect of the CK1 proteins is a variable C-terminal region that does not directly affect ATP catalysis but is important for regulating intracellular location and kinase functions (299, 300). The STE kinase group, named for yeast sterile genes involved in mating signals, comprises approximately 46 serine/threonine kinases that act primarily as upstream activators of the mitogen-activated protein kinase (MAPK) proteins and include the MAP2K, MAP3K, and

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MAP4K proteins. The MAP2K subfamily is unique in that it is a dual specificity kinase and can phosphorylate MAPK proteins on threonine (T) and tyrosine (Y) residues within a conserved TXY motif (X is any amino acid) that regulates kinase activation. The last kinase groups consist of approximately 90 receptor and nonreceptor tyrosine kinase (TK) proteins and another 43 tyrosine kinase-like (TLK) proteins. While the TLK group shares amino acid sequence similarity to TK proteins, these proteins function as serine/threonine kinases.

The process of phosphorylation adds a negative charge to a biological molecule, which alters the molecule’s structure and ultimate function in the cell. The functions of biological molecules such as proteins, nucleic acids, carbohydrates, and lipids are all regulated by phosphorylation events. Phosphorylation is a highly regulated and reversible process. Cellular functions depend on the balance between the addition of phosphates by kinases to achieve a specific cellular response and the removal of the phosphate by protein phosphatases when that cellular response is no longer needed. A consequence of disrupted balance between protein phosphorylation and dephosphorylation often results in elevated protein phosphorylation, which contributes to the development and progression of many types of cancer and inflammation-related disorders. Excess protein phosphorylation is a consequence of genetic mutations or altered expression of kinases and phosphatases.

Dysregulated and constitutively active protein kinases are the primary culprits that disrupt the balance between phosphorylation and dephosphorylation. As such, inhibition of dysregulated kinase activity is a major goal in the development of safe and effective therapies for cancer, inflammatory disorders, and many other diseases.

There are currently more than 200 kinases that have been linked to various disease states and most involve proliferative disorders such as cancer (301, 302). However,

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dysregulated kinase activity is also recognized to contribute to cardiovascular, metabolic, and neurodegenerative diseases (303-308). The causes of kinase dysregulation and its role in driving disease have been studied extensively and can be narrowed down to three genetic changes. These genetic alterations consist of point mutations that change single amino acids, gene amplification, and the fusion of two different genes, all of which result in kinases with elevated or constitutive activity (301). Further analysis of over 1000 putative cancer causing or “driver” genes, which are essential for the cells proliferative advantage, identified 91 of these genes to be protein kinases (309). Interestingly, a remarkable 40% of the protein kinase drivers were tyrosine kinases, which is consistent with the higher emphasis on the development of tyrosine kinase inhibitors. However, despite the prevalence of clinically available tyrosine kinase inhibitors, less than half of these kinase drivers have been targeted with therapeutic agents (309).

Protein kinases serve an important function in regulating cellular responses to extracellular signals. Figure A1.2 shows a simplified overview of major kinase signaling pathways that respond to extracellular signals, have been found to be dysregulated in disease, and are the targets of kinase inhibitors. Extracellular cytokines and growth factors regulate cellular responses by interacting with plasma membrane–bound receptor tyrosine kinases (RTK), G-protein coupled receptors (GPCR), cytokine receptors (CR), and receptor serine/threonine kinases (RSTK). Engagement of the extracellular ligands induces receptor conformational changes that result in the dimerization and activation of monomeric receptor proteins and the recruitment of intracellular nonreceptor tyrosine kinases (NRTK) and other adapter proteins. The recruitment of intracellular adaptor proteins to the activated receptors led to the activation of kinase cascades and regulation of

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specific transcription factors and gene expression. However, kinases can regulate many other nongenomic processes by phosphorylating cytoplasmic substrates that affect the size or shape of the cell and its ability to migrate and interact with other cells. To add to the complexity, there are several examples of protein kinases regulating other proteins and biological outcomes through catalytic-independent functions (310). In most of the cases where there is no phosphate transfer, the physical interaction between a kinase and a particular protein is sufficient to modulate the protein’s function and a subsequent biological outcome.

The mitogen-activated protein kinase (MAPK) and protein kinase B (Akt) signaling cascades are classic examples of RTK and GPCR-mediated signaling pathways that regulate cellular functions (311-316). In the case of receptor serine/threonine kinases

(RSTK), transcription factor activation is coupled directly to the ligand-activated receptor.

The transforming growth factor-β (TGF-β) family is an example of secreted extracellular proteins that activate receptors with primarily serine/ threonine kinase activity to modulate the cellular responses in many physiological systems (317). Membrane-bound receptors, directly or through adaptor proteins, activate intracellular kinases, which in turn regulate a variety of substrates including transcription factors to alter gene expression and cellular responses. Dimerization of RTK monomers following ligand engagement facilitates inherent kinase activity of these receptors. In contrast, the ligand-activated cytokine receptors lack kinase activity and engage associated nonreceptor tyrosine kinases to initiate downstream signaling. In the case of the receptor serine-threonine kinases, only one of the monomers has kinase activity that directly phosphorylates transcription factors after receptor dimerization following ligand engagement. Several comprehensive reviews of

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these receptor-mediated kinase-signaling pathways are available (318, 319). In addition, a more detailed description of specific kinase-signaling networks will be presented in later chapters.

Figure A1.2. Receptor-mediated kinase signaling networks. Kinases (red) target transcription factors (brown) to mediate changes in gene expression and cellular responses to extracellular signals. Adaptors (green) include G-proteins and associated proteins that couple receptors to kinase cascades. Key: CR cytokine receptor, RTK receptor tyrosine kinase, NRTK nonreceptor tyrosine kinase, RSTK receptor serine/threonine kinase, PM plasma membrane, TFs transcription factors, MAP3K/MAP2K/MAPK mitogen-activated protein kinase cascade, MAPKAPK MAP kinase- activating protein kinase, PKA/B/C protein kinase A, B, or C

Overview of Protein Kinase Structural Features

The typical eukaryote protein kinase has a conserved bilobed 3-D structure consisting of amino- (N) and carboxy-(C) terminal lobes that are coordinated in their movement in relation to each other depending on kinase activity. Most protein kinases

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contain a conserved ATP-binding site, substrate interaction sites in the C-terminal lobe, and activation sites as shown in the example of protein kinase A (Fig. A1.3).

The N-terminal lobe consists mainly of beta sheets while the C-terminal lobe contains alpha-helices. At the base of the N-terminal lobe sits the ATP-binding and

3− catalytic site that serves the function of removing the terminal phosphate (PO4 ) from magnesium-ATP (MgATP) and catalyzing its transfer onto the hydroxyl (OH−) group of a serine, threonine, or tyrosine residue located on the substrate protein. The Mg2+ helps stabilize and position the negatively charged phosphate on ATP for transfer onto the substrate. Additional coordination of ATP involves a conserved glycine rich loop and lysine residue in the N-terminal lobe. Substrate proteins interact with specific residues in the C-terminal lobe and along a cleft formed between the N- and C-terminal lobes.

However, the specific kinase residues involved in recognizing most protein substrates are

Figure A1.3. General overview of protein kinase structure. A model of protein kinase A (pdb: 3FJQ) highlights the N-terminal lobe containing the ATP-binding site (conserved lysine, K73, in green) and ATP (purple). The C- terminal lobe contains the activation sites (T196 and T198 in yellow) and substrate-binding site (residues 230-260 in orange)

not known. An overview of some of the known structural features and residues involved in kinase recognition of protein substrates will be the topic of Chap. 4. This information will be important for the identification of type IV kinase inhibitors that disrupt key kinase functions.

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Human protein kinases are dynamic structures, and multiple regions distal to the catalytic site have been implicated in coordinating activity. For a more detailed analysis of the structural features involved in protein kinase regulation, the reader is directed to several intriguing studies and comprehensive reviews. For example, McClendon et al. have presented compelling molecular modeling data showing that kinases also have unique local regions, consisting of 40–60 amino acid segments that undergo unique dynamic changes that provide allosteric regulation and additional control over kinase activity and function

(320). Wang and Cole provide an excellent review of the catalytic mechanisms of protein kinases and the transfer of a phosphoryl group from ATP onto substrates (321). This review highlights the work of many scientists who have made significant contributions to our understanding of kinase structure and catalytic mechanisms. Although protein kinases share many conserved structural features that define the core region involved in phosphoryl transfer onto protein substrates, there are regions outside of the kinase core that facilitate catalytic activity, kinase complexes, and signaling events. Gógl et al. describe the presence of intrinsically disordered regions (IDRs) in protein kinases that help fine tune kinase catalytic activity and assembly of kinases in multiprotein signaling complexes (322).

Expanding knowledge of the regulatory features of protein kinases will provide opportunities to develop new approaches to modulate protein kinase functions in disease.

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Appendix 2. Avoiding or Co-opting ATP Inhibition: Overview of Type III, IV, V, and VI Kinase Inhibitors5

Abstract

As described in the previous chapter, most kinase inhibitors that have been developed for use in the clinic act by blocking ATP binding; however, there is growing interest in identifying compounds that target kinase activities and functions without interfering with the conserved features of the ATP-binding site. This chapter will highlight alternative approaches that exploit unique kinase structural features that are being targeted to identify more selective and potent inhibitors. The figure below, adapted from Sammons et al. (64), provides a graphical description of the various approaches to manipulate kinase activity.

In addition to the type I and II inhibitors, type III kinase inhibitors have been identified to target sites adjacent to the ATP-binding site in the catalytic domain. New information on kinase structure and substrate-binding sites has enabled the identification of type IV kinase inhibitor compounds that target regions outside the catalytic domain. The combination of targeting unique allosteric sites outside the catalytic domain with ATP-targeted compounds has yielded a number of novel bivalent type V kinase inhibitors. Finally, emerging interest in the development of irreversible compounds that form selective covalent interactions with key amino acids involved in kinase functions comprise the class of type VI kinase inhibitors.

Keywords Allosteric, Docking domains, Protein-protein interactions, Bivalent,

Irreversible inhibitors

5 Martinez R., Defnet A., Shapiro P. Avoiding or Co-Opting ATP Inhibition: Overview of Type III, IV, V, and VI Kinase Inhibitors. In: Shapiro P. (eds) 2020. Next Generation Kinase Inhibitors. Springer, Cham. https://doi.org/10.1007/978-3-030-48283-1_3

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Figure A2.1. Graphical description of the various approaches to manipulate kinase activity.

Part A: Type III Kinase Inhibitors

The identification of new details about the structural features of kinases, their role in enzyme activity, and their functions in regulating substrate recognition and phosphorylation have prompted research endeavors to develop kinase inhibitors that do not interfere with the highly conserved ATP-binding site. For example, type III kinase inhibitors are compounds that interact with specific structural features in the catalytic site that are adjacent to the ATP-binding pocket. These sorts of innovations are aimed at identifying drugs with reduced promiscuity and associated toxicities as well as avoiding the development of ATP-binding site gatekeeper mutations that are commonly observed to be responsible for acquired resistance to type I and II kinase inhibitors (323).

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Type III MEK1/2 inhibitors. The most studied type III kinase inhibitors have been developed against the MAP or ERK Kinase-1/2 (MEK1/2) proteins, which are primary mediators of constitutively active extracellular signal-regulated kinase (ERK1/2) signaling that is observed in many cancers and proliferative disorders. In the early 1990s, researchers, at what was then Parke-Davis & Company, screened a library of small molecules using an in vitro kinase assay consisting of MEK1, ERK2, and the generic substrate myelin basic protein (MBP) (324). This screen identified the compound PD98059 to inhibit MEK1 activation of ERK2, to inhibit subsequent phosphorylation of MBP in an in vitro assay, and to block ERK activation in cells. PD98059, which turned out to be ~10 fold more selective for MEK1 than MEK2, was the first non-ATP-competitive inhibitor that paved the way for the development of additional type III MEK1/2 inhibitors. In the early 2000s, the orally bioavailable MEK1/2 inhibitor, PD184352 (CI-1040), was the first type III kinase inhibitor to enter clinical trials (325).

The first structural description of the allosteric-binding pocket on MEK1/2 (326) laid the groundwork for the discovery of additional type III MEK1/2 inhibitors, including selumetinib, cobimetinib, and trametinib that are currently being used to treat several types of cancer. As single agents, the type III MEK1/2 inhibitors have not had the anticipated clinical success (327). However, the use of the type III MEK1/2 inhibitors in combination with other kinase inhibitors has provided clinical benefits in treating cancer, especially in the context of inhibitors of mutated BRaf where a single amino acid change from a valine to glutamate in the catalytic site causes constitutive activation of the kinase (328). For example, progression-free survival was greatly improved in melanoma patients receiving cobimetinib (GDC-0973) in combination with the type I BRaf inhibitor vemurafenib to

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treat mutated BRaf expressing melanoma (329). Similarly, the MEK1/2 inhibitor trametinib is used in combination with the type I BRaf inhibitor dabrafenib to treat mutant

BRaf expressing metastatic melanoma, thyroid cancer, and non-small cell lung cancer

(330-332).

The unique structural features adjacent to the ATP-binding site of MEK1/2 have been used to identify compounds that inhibit MEK1/2 activity and may have applications targeting other kinases. Zhao et al. have presented an excellent review of the type III kinase inhibitor-binding mode with a focus on interactions with MEK1/2 proteins (333). These studies provide evidence that unique structural features in catalytic/kinase domains can be exploited to design more selective kinase inhibitors. The authors compared 29 known structures of MEK1 with type III kinase inhibitors and identified three different allosteric regions in the catalytic site that represent structural targets for inhibitor development (Fig.

A2.2). The first region is a hydrophobic pocket that interacts with hydrophobic groups of inhibitor compounds. The second region is a key lysine involved in enzyme catalysis. The third region includes the DFG motif and parts of the activation loop. The activation loop of the MEK1/2 proteins is unique in that it forms a short helix that allows specific interactions with type III inhibitors (326). While the activation loop is typically disordered in kinases where structural information is available, other kinases including p38α MAP kinase and B-Raf kinase, along with MEK1/2, have been reported to adopt these short helix structures in the activation loop (333). Thus, this unique structural feature could be used to develop type III inhibitors for other kinases. Computational modeling further supports the formation of unique helix structures in the activation loop of other kinases and the potential for selective drug targeting (333).

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Figure A2.2. Structure of MEK1 and allosteric regions near ATP-binding site. Shown is the structure of MEK1 (pdb:1S9J) and three regions, (1) a hydrophobic pocket (L115, L118, V127, and M143) in red, (2) lysine (K97) in green, and (3) residues in the activation loop (C207DFGVS212, I215, M219) in yellow, involved in allosteric drug binding. The type III inhibitor, PD318088, is shown in black lines

The structure of cobimetinib bound to MEK1, highlighted in Chap. 2, demonstrates key features that determine the efficacy of type III MEK inhibitors in blocking MEK1/2 in cancers driven by mutations in Ras or BRaf. Previous studies indicate that wild-type and mutant BRaf proteins have differences in their mechanism of MEK1/2 activation (334).

Wild-type BRaf is dependent on the upstream Ras-G proteins whereas mutant BRaf signals through the MEK-ERK pathway in a Ras-independent manner. Based on these differences in BRaf-mediated signaling, the efficacy of MEK1/2 inhibitors in blocking mutant Ras or

BRaf cancer cell lines was shown to have qualitative differences (335). These studies went on to provide evidence that the strength of the type III MEK1/2 inhibitor’s interactions with serine 212 (S212, numbering according to MEK1) in the activation loop helix determined the compound’s potency in cancers with different ERK pathway driving mutations (335). For example, the MEK inhibitors that had strong interactions with S212 resulted in stabilized Raf-MEK complexes in the context of wild-type BRaf but not with mutant BRaf. This suggests that the stabilization disrupted the ability of wild-type BRaf to access and phosphorylate MEK in cancer cells expressing mutant Ras. Alternatively, weaker interactions with S212, as is the case with cobimetinib, were more effective against cancer cells with activating BRaf mutations due to the compound’s preferential binding to the activated form of MEK1. The structure of MEK1 with cobimetinib highlights the

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proximity of the drug with S212 (Fig. A2.3). These findings provide a novel example where information on kinase regulation, structural features, and chemical synthesis can be combined to design type III inhibitors with optimal efficacy depending on the genetic mutation.

Figure A2.3. Structure of MEK1 and cobimetinib. The strength of MEK1 binding to S212 is implicated in affecting the efficacy of MEK inhibitors in mutant BRaf or Ras-driven cancers. The ribbon structure of MEK1 (pdb:4LMN) is shown in complex with cobimetinib (magenta) and S212 (orange). The conserved catalytic lysine (K97) is in yellow

Type III PI3K and Akt inhibitors. Significant effort has gone into identifying compounds that block the phosphoinositide-3-kinase (PI3K) or downstream Akt effector proteins, which are frequently dysregulated and active in many cancer types (336).

Constitutively active PI3K signaling provides cancer cells with survival advantages including inhibiting apoptosis signals and promoting the expression of proteins that promote proliferation (336, 337). One of the major targets of Akt in protecting cancer cell survival is the mammalian/mechanistic target of rapamycin (mTOR) protein complex.

Although there have been a number of research programs aimed at the development of

ATP-competitive inhibitors of PI3K or Akt, compounds identified have shown limited clinical efficacy or cause unacceptable toxicity (336). Nonetheless, several ATP- competitive PI3K inhibitors are in development and at least three (idelalisib, copanlisib, and alpelisib) have been approved for clinical use in treating types of lymphoma/leukemia

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and breast cancer (338). However, as with other ATP-competitive protein kinase inhibitors, acquired drug resistance is a common feature preventing sustained clinical responses.

In addition to type I/II kinase inhibitors, Akt proteins have been the focus of type

III kinase inhibitor development. A unique structural feature of Akt proteins is a pleckstrin homology (PH) domain that interacts with the phosphoinositides on the intracellular side of the plasma membrane and regulates Akt activation. Based on the structural differences between a pocket formed by the PH and kinase domains in the inactive versus the active membrane bound Akt protein, a compound called Inhibitor VIII was identified and found to promote Akt1 adoption of an inactive state (339). The crystal structure reveals key interactions with a tryptophan in the PH domain and residues in the kinase domain that are selective for the Akt1 isoform (Fig. A2.4). One key finding was the formation of a hydrogen bond between Inhibitor VIII and serine 205, which is not conserved amongst Akt isoforms, and could be used to design Akt1-selective inhibitors (339). A similar allosteric inhibitor scaffold, referred to as compound Akt-I-1, that was dependent on the PH domain, was also reported to be a selective inhibitor of the Akt1 isoform (340).

Figure A2.4. Interactions between Akt1 and a type III inhibitor. Akt1 (pdb:3O96) is shown in complex with Inhibitor VIII (black lines) interacting with a tryptophan (W80) in the PH domain (red), and residues 189–198 of the αC-helix in the kinase domain (cyan), and S205 (green)

Additional type III compounds with similar structures and mechanism of action, in targeting allosteric sites near the PH and kinase domains of Akt proteins, have entered clinical trials, including MK-2206 (341), BAY1125976 (342), and ARQ 092/Miransertib

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(343). Given the significance of other Akt isoforms (e.g. Akt2 and 3) in mediating mTOR signaling and survival advantages in cancer cells, ARQ 092 was engineered to potently inhibit Akt1, -2, and -3 proteins. Structural studies between ARQ 092 and Akt1 revealed key interactions with W80 and T82 in the PH domain as well as Y272 and D274 in the kinase domain (Fig. A2.5). These residues are conserved in all Akt isoforms, which may explain the similar potencies of ARQ 092 against these proteins. Phase 1/2 clinical trials with ARQ 092 was recently reported to show beneficial effects in treating patients with diseases containing constitutively active PI3K or Akt1 including PIK3CA-related overgrowth spectrum, Proteus syndrome, and ovarian carcinoma (344, 345).

Figure A2.5. Interactions between Akt1 and ARQ 092. Akt1 (pdb:5KCV) is shown in complex with ARQ 092 (black lines) interacting with a tryptophan and threonine (W80, T82) in the PH domain (green) and residues Y272 and D275 in the kinase domain (cyan). Lysine (K97) involved in enzyme catalysis is shown in yellow

Type III Trk inhibitors. The tropomyosin receptor kinase (Trk) family consists of receptor tyrosine kinases that are mostly expressed in neuronal tissue and respond to neurotrophin stimuli to regulate nervous system function (346). The discovery of elevated

Trk activity, as a result overexpression or genetic fusions, in many cancer cell types has promoted the discovery of Trk inhibitors (347). As a result, a number of broad-spectrum

ATP-competitive inhibitors of Trk isoforms, such as FDA-approved larotrectinib and others compounds in clinical trials, are showing promising results for treating cancers with high Trk activity (348, 349).

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The broad spectrum of functions performed by Trk proteins in regulating neuronal tissue has led to the investigation of isoform specific inhibitors. Of the TrkA/B/C isoforms,

TrkA has been the primary isoform implicated to treat pain in mediating pain associated with inflammation (350). Specifically, TrkA responds to nerve growth factor to maintain the growth and survival of sensory nerves that mediate pain sensation. Thus, TrkA- selective inhibitors are viewed to have clinical potential in treating pain associated with inflammation. However, the current type I and II Trk kinase inhibitors cannot discriminate between Trk isoforms. To overcome this obstacle, Bagal et al. used a cell-based assay to screen for TrkA-selective compounds and identified a type III TrkA kinase inhibitor (351).

Importantly, the compounds showed selectivity for peripheral nociceptor neurons due to enhanced recognition by blood-brain barrier efflux transporters, which reduced undesirable effects on TrkA signaling in the central nervous system (351). The key features of the lead

TrkA-selective inhibitor, compound 23, reveal interactions with amino acids in a pocket behind the ATP-binding site of TrkA including D668 and R673 (Fig. A2.6).

Figure A2.6. Interactions between TrkA and compound 23. TrkA (pdb:6D20) are shown in complex with compound 23 (magenta lines) making key interactions with residues R673 and D668 (green). The conserved catalytic lysine (K544) near the ATP-binding site is shown in yellow

The characterization of unique allosteric sites adjacent to the ATP-binding site has promoted the development of selective type III inhibitors that have shown clinical benefits in cancer therapy. Type III kinase inhibitors may help overcome drug resistance to type I/II

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inhibitors that occurs with mutations in the ATP-binding site of kinases such as EGFR

(352). Additional examples of non-ATP-competitive type III kinase inhibitors have been reported for cyclin-dependent kinase-2 (CDK2) (353) and glycogen synthase kinase-3β

(GSK3β) (354). It is expected that the future clinical landscape will have more small- molecule protein kinase inhibitors that adopt non-ATP-competitive approaches in their mechanism of action.

Part B: Type IV Kinase Inhibitors

A relatively new area in the development of selective kinase inhibitors has focused on targeting unique structural features outside of the ATP-binding or catalytic sites. These allosteric regions are targets of the type IV kinase inhibitor compounds and have the potential to alter enzymatic activity by disrupting the access to upstream activators or prevent the phosphorylation of select downstream substrates. As discussed in Chap. 1, most kinases have pleiotropic functions involving the phosphorylation and regulation of a variety of diverse substrates. Thus, a potential advantage of type IV kinase inhibitors is the opportunity to disrupt the phosphorylation of some but not all substrates. In other words, the type IV kinase inhibitors may enable new approaches to selectively block only the kinase functions associated with a particular disease while preserving other kinase functions that have potential benefits.

A major challenge in targeting allosteric sites outside the ATP binding/catalytic site is determining what sites are important for relevant biological functions. Chapter 4 will present information on studies that have evaluated kinase interactions with regulatory proteins or downstream substrates. This information provides a starting point to identify compounds that could disrupt these interactions. In addition, the Kinase Atlas is a publicly

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available resource that used FTMap computational resources to help predict potential allosteric kinase hot spots that could be targeted for the development of potential inhibitors or modulators of kinase signaling functions (355, 356). The FTMap algorithm examined nearly 5000 kinase structures from 376 different kinases that have been deposited into the

Protein Data Bank for predicted binding of small organic molecules. From this, the Kinase

Atlas identified ten hot spots outside the ATP-binding/catalytic site that are predicted to contribute to binding free energy of a ligand and are potential drug targets for the development of type IV kinase inhibitors. This section will highlight some recent examples of the discovery of type IV kinase inhibitors and potential applications in modulating kinase functions in disease. Wu et al. have previously reviewed several allosteric inhibitors that fall into the type III and IV categories (357).

Type IV inhibitors of MAP kinases. New understanding of the binding sites that regulate kinase interactions with substrates has facilitated the development of type IV kinase inhibitors targeting the mitogen-activated protein (MAP) kinases. Focus will be on the three major family members of MAP kinases: ERK, JNK, and p38 MAP kinases. The first studies describing type IV inhibitors of ERK2 were published nearly 15 years ago

(207, 208). These studies used computational approaches to predict molecular structures that would interact with D-domain recruitment site (DRS)-involved substrate docking to inactive or active ERK2. Several compounds that contained a thiazolidinedione scaffold were shown to reduce ERK-mediated phosphorylation of downstream substrates such as p90 ribosomal S6 kinase (RSK-1) and the transcription factor ELK-1 and inhibited several cancer cell lines in a dose-dependent manner (208). However, the limitations of these studies were the lack of definitive experimental evidence for the binding interactions

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between the compounds and ERK2 and the relative low potency of the compounds. Recent studies (64, 358) highlighting the design of new type IV inhibitors targeting the DRS on

ERK2 will be the topic of discussion in Chap. 6.

Additional type IV ERK2 inhibitors have been designed to target ERK2 at the F- recruitment site (FRS), which is involved in regulating the activation of protooncogene transcription factors including members of the Fos family and c-Myc (183). Bioactive compounds from these studies contained a thienyl benzenesulfonate scaffold and inhibited activator protein-1 (AP1) transcription activity and melanoma cells containing activating mutations in BRaf or NRas. The specific interactions between these compounds and ERK2 have not been experimentally determined.

Dimerization between kinase monomers may affect the activation and subcellular localization of the ERK and JNK MAP kinases (359, 360). Although dimerization between active ERK2 monomers was initially reported to be essential for nuclear localization (360), other studies provide evidence that active ERK2 dimerization may be related to nonphysiological interactions between histidine tags used for protein purification and that untagged ERK2 exists as a monomer under physiological conditions (361). Similarly, other studies using fluorescence imaging of live cells indicate that ERK2 dimerization is not required for nuclear entry (362). However, active ERK2 dimers reportedly function to regulate substrate phosphorylation in the cytoplasm but not in the nucleus (363). As such, research efforts have examined the potential to inhibit ERK2 dimerization and selectively block kinase functions in subcellular locations. Herrero et al. reported the identification of a small molecule inhibitor of ERK2 dimerization that inhibited cytoplasmic activity of

ERK2 and tumor progression in mouse xenograft models (364). Using in silico modeling,

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compound DEL-22379 reportedly disrupted ERK2 dimer interactions by forming contacts in a cleft near the activation loop consisting of residues D175, H176, F181, and F329. A nonhelical leucine zipper consisting of residues L333, L336, L344 and ion pairs between

H176 and E343 on ERK2 monomers have been shown to be important for the formation of ERK dimers (365).

Type IV inhibitors have also been recently developed to target BRaf dimers (366).

Based on the dimerization interface, cyclized peptides were designed to disrupt BRaf dimers and activation of downstream ERK1/2 pathway signaling. Importantly, this approach may be beneficial in treating cancers with wild-type BRaf and overcome the observed paradoxical activation of ERK1/2 signaling seen with ATP-competitive BRaf inhibitors (367).

The c-Jun N-terminal kinase (JNK) family has been implicated in a number of diseases including diabetes (368). JNK activity is regulated through interactions with a

JNK-interacting protein (JIP1), which acts as a scaffold that facilitates the interactions between JNK and its upstream kinases. Taking advantage of the structural interactions between JIP1 and JNK1, which will be highlighted in Chap. 4, new small molecules that block this interaction and inhibit JNK substrate phosphorylation were identified (369).

These studies used a fluorescence-based assay that screened compounds for their ability to disrupt the interactions between a JIP1 peptide and JNK1. Several compounds were identified to disrupt the JIP1-JNK interactions with IC50 values in the 500 nM range. One compound, BI-78D3, was effective at inhibiting JNK activity but was several orders of magnitude less active against related MAP kinases or unrelated kinases. While the exact

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binding mode of BI-78D3 with JNK1 is not known, these studies provide the basis for generating effective type IV JNK inhibitors.

Additional type IV inhibitors of JNK1 have been identified to target a unique allosteric site that sits below the activation loop (370). These studies used mass spectrometry to screen ~500,000 compounds based on their affinity to JNK1. Of the 68 candidate JNK1 ligands identified from the screen, NMR analysis revealed compounds that bound the ATP site or allosteric sites. Figure A2.7 shows the interactions between JNK1 and an allosteric-binding type IV inhibitor referred to as compound 3, which contains a biaryl tetrazole scaffold. These compounds are binding to a region that has been shown to regulate interactions with substrates and regulatory proteins (371). However, there is no evidence that compound 3 modulates kinase function through disruption of interactions with substrates. Modifications of compound 3 yielded non-ATP-competitive compounds that may stabilize JNK1 in a way that interferes with phosphorylation by the upstream

MEK7 activator kinase (370).

Figure A2.7. Interactions between a type IV biaryl tetrazole and JNK1. Shown is a JNK1 dimer (PDB:3O2M) with activation loop residues T183 and Y185 (red), the MAPK insert sites G242, A267(cyan), and substrate-docking site residues Y230, I231, W234 (orange) involved in interactions with compound (magenta lines). The conserved K55 involved in ATP catalysis is shown in green

In addition to small molecules, synthetic peptides targeting the JIP1 site on JNK have entered clinical trials to reduce ocular inflammation (372). Brimapitide (XG-102) has completed phase II trial with 145 patients, and the effects were reported to be comparable

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to standard dosing with dexamethasone. Brimapitide is also being tested to reduce JNK- mediated inflammation associated with hearing loss and Alzheimer’s disease (373, 374).

A phase III clinical trial at sites in Europe and Asia indicate brimapitide is effective against idiopathic sudden sensorineural hearing loss (375).

The failure of ATP-competitive p38 MAP kinase inhibitors in clinical trials for the treatment of inflammatory disorders (376) has encouraged new approaches to target p38 isoforms including the identification of novel allosteric type IV inhibitors. Like the previous studies identifying allosteric JNK inhibitors, Comess et al. screened for compounds that targeted allosteric sites on p38α MAP kinase (370). An allosteric inhibitor, called compound 10, was identified and found to interact with p38α MAP kinase in a region below the activation loop similar to what was observed with the allosteric compound targeting JNK that was described in Fig. A2.7. Compound 10 interacted with residues below that activation site that are also adjacent to a substrate-docking site (Fig. A2.8). Like the JNK inhibitor compound, compound 10 is thought to cause an allosteric structural change that disrupt p38α MAP kinase activation by upstream kinases.

Figure A2.8. Interactions between compound 10 (magenta lines) and p38α MAP kinase. (PDB: 3NEW). Interacting residues W197, S252, I250, P191, L246, L292 (cyan). Activation site resides T180 and Y182 (green). The conserved catalytic lysine (K53) is shown in yellow

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Shah et al. used computational approaches to identify compounds that target a pocket adjacent to the DRS of p38α MAP kinase (63). Unique to these compounds were their isoform preference for interactions with p38α over p38β MAP kinase, which may help mitigate excess toxicity observed with the ATP-competitive inhibitors tested previously

(377, 378). Another potential advantage of these compounds is their ability to inhibit proinflammatory substrates involved in acute lung injury associated with acute respiratory distress syndrome (ARDS) but preserve the activation of anti-inflammatory signals that might be beneficial (379). For example, Shah et al. describe a lead compound, UM101, that inhibited the proinflammatory substrate MAPK-activated protein kinase-2

(MAPKAPK2 or MK2) but preserved the activation of the anti-inflammatory p38 substrates mitogen- and stress-activated protein kinase-1/2 (MSK1/2) (63). The authors went on to demonstrate that UM101 protected against lung damage by reducing endothelial cell damage and neutrophil leakage in a mouse model of lipopolysaccharide (LPS)-induced acute lung injury. These studies provide compelling evidence that function-selective type

IV p38α MAP kinase inhibitors have the potential to reduce toxicity observed with blocking all p38 MAP kinase functions while maintaining in vivo efficacy.

BCR-Abl inhibitors. Efforts to overcome resistance to ATP-competitive inhibitors in the treatment of chronic myelogenous leukemia (CML) have led to the identification of allosteric inhibitors of BCR-Abl (380, 381). Adrian et al. designed a compound, GNF-2, that targeted the interactions between an N-terminal myristoyl group and a hydrophobic region in the C-terminus of the c-Abl kinase (382). Myristoylation is a posttranslational modification where a fatty acid derivative of myristic acid is linked to proteins and facilitates localization to cell membranes. It is estimated that 0.5–0.8% of all eukaryotic

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proteins are myristoylated (383). GNF-2 was more effective at inhibiting nonmyristoylated c-Abl than the myristoylated kinase. Similarly, GNF-2 bound to c-Abl and could be competed off with a myristoylated peptide. Furthermore, mutations in the myristoylated- binding pocket of c-Abl blocked GNF-2 inhibitory effects. NMR studies provided further evidence for GNF-2 binding to the myristoylated pocket of c-Abl (380). GNF-2 was demonstrated to make key interactions with residues in the myristoyl-binding site (Fig.

A2.9).

Figure A2.9. Type IV inhibition of Abl. (a) Structure of c-Abl with myristoylated peptide (red) and the ATP-competitive inhibitor PD166326 (black lines) (pdb: 1OPK). (b) c-Abl interactions with GNF-2 (red) and the ATP-competitive inhibitor imatinib (black lines) (pdb:3K5V). The conserved catalytic lysine (K271) is in yellow. Myristate-binding site residues L340, D381, C464, P465, V506 are shown in cyan

Small allosteric compounds targeting the myristoyl-binding site of c-Abl have also been shown to induce conformational changes that activate kinase activity (384). Yang and colleagues took advantage of structural studies that suggested that interactions between the myristoyl group and the myristoyl-binding site regulated c-Abl activity and identified the kinase activator DPH (5-(1,3-diaryl-1H-pyrazol-4-yl) hydantoin). In contrast to GNF-2,

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which locks a key α-helix (see Fig. A2.9) required for catalytic activity in a closed inhibited state, DPH caused an extension of this α-helix observed when c-Abl is activated (384).

While the inhibition of Abl activity is desired in the context of cancers with constitutively active BCR-Abl fusion proteins, activation of wild-type c-Abl may limit breast cancer cell proliferation and metastasis (385).

PDK1 inhibitors. An important co-activator of Akt proteins is phosphoinositide- dependent protein kinase-1 (PDK1), which co-localizes with Akt at the plasma membrane through the PH domain. PDK1 is unique because it is required for the full activation of Akt and other members of the AGC protein kinase family (386). PDK1 interactions with substrates occur through a PDK1 interacting fragment (PIF) pocket (387). The PIF pocket occupies an allosteric site referred to as helix αC that regulates protein-protein interactions and kinase activity. Rettenmaier et al. identified small molecules based on a diaryl sulfonamide chemical scaffold that interact with the PIF pocket and inhibit PDK1 (388).

Structural studies revealed key interactions between their compound RS1 and residues

R131 and L155 in the PIF pocket (Fig. A2.10). Although ATP-competitive PDK1 inhibitors had limited efficacy as a monotherapy in mice with acute myeloid leukemia xenografts (389), combining them with the PIF pocket inhibitors may provide greater inhibition of Akt signaling and subsequent tumor suppression (388).

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Figure A2.10. Interactions between PDK1 and compound RS1. PDK1 (pdb:4RQK) is shown in complex with RS1 (magenta lines) interacting with a R131 and L155 in the PIF pocket (green). ATP is highlighted as yellow lines

Inhibitors of CDK2 interactions with cyclin A. Allosteric type IV inhibitors have been developed against cyclin-dependent kinase-2 (CDK2) (390). Cell cycle progression depends on the activity of CDK proteins, which are regulated by association with cyclin proteins. CDK2 activity is essential for progression through G1 and S-phase of the cell cycle and requires association with cyclin A. Based on structural features of CDK2, a type

IV inhibitor compound, 8-anilino-1-naphthalene sulfonate (ANS), was identified to bind an allosteric site near the DFG region and causes a structural change that disrupts interactions with cyclin A. The CDK2-ANS structure was shown previously in Chap. 2.

However, ANS-binding affinity for CDK2 is relatively low (37 μM); therefore, it can be readily displaced by cyclin A (391). To improve the binding affinity of compounds targeting CDK2 interactions with cyclin A, Rastelli et al. did a virtual screen for compounds that are predicted to interact with CDK2 in the ANS-binding site (353).

Experimental analysis of several lead compounds revealed displacement of ANS from the cyclin A–binding site, which suggested higher potency and targeting to the cyclin A–

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binding site. Although experimental analysis of structural interactions between these new compounds and CDK2 was not done, these studies provide the basis for targeting the activity of CDK proteins through disruption of interactions with cyclins.

Inhibitors of mTOR. Contrary to compounds that disrupt protein-protein interactions and prevent kinase activation, allosteric compounds that promote protein- protein interactions and disrupt kinase functions have been well described in the example of the mammalian target of rapamycin (mTOR) kinase. The mTOR kinase complexes

(mTORC1 and mTORC2) are critical regulators of the immune system and are upregulated in many cancer cells (391, 392). Targeted inhibition of mTOR has clinical uses as an immunosuppressant during organ transplants and as anticancer drugs (393). The natural product rapamycin and related analogues (or rapalogs such as the FDA-approved sirolimus, temsirolimus, and everolimus) indirectly inhibit mTOR by forming a complex with FK506- binding proteins (FKBP). The rapalog-FKBP complex associates with a binding domain on mTOR that is outside the active site and involved in facilitating the activation of substrates involved in protein synthesis. In addition to their immunosuppressant roles, the mTOR inhibitors have been FDA approved to treat renal cell carcinoma, breast cancer, and neuroendocrine tumors.

IKK inhibitors. Inflammatory diseases such as arthritis, asthma, and atherosclerosis are thought to be a result of overactivation of the Nuclear Factor kappa-light-chain- enhancer of activated B cells (NFκB) transcription factor (394). As such, dozens of compounds have been identified to inhibit NFκB activity (395). To develop more specific inhibitors, efforts to target kinases involved in NFκB activation have been pursued. The

NFκB inhibitory protein, IκB, is phosphorylated by the IκB kinase (IKK), which targets

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IκB for degradation. Loss of IκB allows cytoplasmic NFκB to translocate into the nucleus and regulate the expression of inflammatory genes. In addition to ATP-competitive inhibitors, allosteric inhibitors of IKK have been identified (395). Scientists at Bristol-

Myers Squibb, using an in vitro kinase assay consisting of IKK isoforms and IκB to screen for compounds that inhibit IκB phosphorylation, identified the IKK inhibitor BMS-345541 that was ~10 fold more selective for IKKβ versus IKKα (396). Although BMS-345541 does not compete with ATP binding, the exact allosteric-binding mode of this compound is currently unclear. In addition, clinical applications with this or related allosteric inhibitors of IKK have yet to be reported.

Part C: Type V Kinase Inhibitors

The conserved structure of the ATP-binding site of protein kinases makes it challenging to develop specific inhibitors that block kinases through type I or II mechanisms of action. However, developing compounds that target both the ATP-binding site and a unique structural feature found on a specific protein kinase is the basis for the development of type V or bivalent inhibitors. With the characterization of binding sites and peptide motifs that determine protein-protein interactions, highly selective and potent type

V inhibitors against tyrosine and serine/threonine kinases have been identified. Gower et al. provided a relatively recent review of type V bivalent protein kinase inhibitors that have been described (397). These compounds typically consist of a small molecule that targets the ATP-binding site coupled to a peptide representing the substrate targeted by the specific kinase. This section will describe some of these compounds and the approaches to develop selective type V protein kinase inhibitors.

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Early proof of concept studies for the development of bivalent protein kinase inhibitors used the Src tyrosine kinase as a model (398). Src and related tyrosine kinases contain an SH2 domain that recognizes phosphorylated tyrosine and surrounding amino acids on substrate proteins. Xu et al. provided the first structural information of Src describing the coordination between the SH2 and SH3 domains involved in protein-protein interactions and the catalytic site regulating kinase activity (399) (Fig. A2.11). Using this information, a SH2 domain–targeted peptide containing a phosphorylated tyrosine was linked to a nonphosphorylatable peptide that interacts with the Src active site through a γ- aminobutyric acid linker (398). The key findings from these studies indicated that the targeting peptides were most potent when linked together and that the number of γ- aminobutyric acid monomers in the linker was important for maximum Src inhibition.

More recent studies linked the SH2 targeting peptide with an ATP-competitive inhibitor to achieve potent bivalent c-Src inhibitors (400, 401).

Figure A2.11. Structural domains in c-Src (PDB:2SRC). The SH2 and SH3 domains are shown in blue and red, respectively. The kinase domain and ATP- binding site are shown in yellow and green, respectively. A potential peptide substrate (magenta lines) interacting with the SH-2 domain and an ATP analog (black lines) are shown

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Bivalent kinase inhibitors based on a protein scaffold. Bivalent protein kinase inhibitors as research tools have been developed using the DNA repair protein O6- alkylguanine-DNA alkyltransferase (AGT) as a scaffold (402). AGT contains a cysteine in the active site that reacts with O6-benzylguanine (BG). This conveniently allows the coupling of an ATP-competitive inhibitor to AGT through a linkage with BG. Unique AGT fusion proteins can be expressed with a specific peptide ligand that contains the second binding moiety that determines specificity for protein recognition. This technology, referred to as SNAP-tag, provides a convenient approach to generate and test the specificity of a variety of ligand targeting sequences and their ability to achieve kinase inhibition in combination with ATP-binding site compounds (403). Specific AGT fusion proteins containing peptide ligands against Abl1, PIM1, p38α MAPK, c-Src, and EGFR protein kinases have been described (403-405). Another advantage of the SNAP-tag approach is that promiscuous ATP-competitive inhibitors can be designed to be quite specific for a particular kinase (406).

Wong et al. described an analysis of three ATP-competitive inhibitors and nine

SNAP-tag fusion proteins to determine the contribution of each targeting moiety to the potency of the bivalent inhibitor (407). These studies indicated that the potency of the bivalent compound was less dependent on the affinity of the specific peptide-targeting ligand but more on the affinity of the ATP-competitive ligand. Nonetheless, even targeting peptides with low affinity can help improve selectivity and potency of bivalent kinase inhibitor compounds (407). While the utility of these types of bivalent inhibitors will be relegated to research tools for evaluating kinase functions, these approaches provide the basis to design bivalent kinase inhibitors for clinical applications.

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Small-molecule peptide bivalent Inhibitors. Several MAP kinases have been the target of bivalent inhibitors. Stebbins et al. identified compound 19 that consisted of an

ATP-competitive inhibitor coupled to a short D-domain peptide, which was sufficient to displace the JIP1 protein from the D-recruitment site on JNK1, and a cell penetrating peptide (408). Compound 19 inhibited JNK1 kinase activity in vitro and in cell-based assays at low nM and μM concentrations, respectively. This compound also improved glucose tolerance in a mouse model of type 2 diabetes, which is a potential clinical application for JNK inhibitors. A similar strategy was used to generate an ERK1/2 selective bivalent inhibitor (SBP3) consisting of an ATP-competitive inhibitor (FR180204) and a

16-amino-acid peptide corresponding to the D-domain of the ERK1/2 substrate, ribosomal

S6 kinase (RSK1) (409). Combining the targeting moieties into the bivalent compound increased the potency more than 50 times as compared to either the ATP-competitive inhibitor or the D-domain peptide alone. Figure A2.12 shows the reported structure of

SBP3 with active ERK. As shown, SBP3 forms contacts with ERK2 through the RSK1 peptide and FR180204; however, the linker of these targeting agents does not appear to be involved in ERK2 interaction (409). Despite the intended design for SBP3 to target

ERK1/2, this compound also potently interacts with JNK and p38 MAP kinase isoforms.

Figure A2.12. Structure of bivalent compound SBP3 and ERK2 [PDB: 5V62]. SBP3 shown consisting of a RSK1 peptide (magenta lines) and the ATP-competitive compound FR180204 (green lines). D-recruitment site residues T158, T159, D316, D319 (cyan). The conserved catalytic residue (K52) is in yellow

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A study reported the use of a cyclic decapeptide that corresponds to an extracellular region of the epidermal growth factor receptor (EGFR) regions involved in dimerization

(410). Combining two of these peptides together using a polyproline linker created a bivalent ligand that inhibited EGFR autophosphorylation presumably by preventing the two EGFR monomers from dimerizing. Ephrin type-A receptor 3 (EphA3) is another receptor tyrosine kinase targeted by bivalent compounds (411). These studies highlight the potential of using longer linkers to couple ATP-competitive inhibitors with small peptides that target unique regions far away from the ATP-binding site. Not only did this approach enhance the potency of a weak ATP-competitive inhibitor, it supports the advantage of using structural information to design a wide range of bivalent targeting moieties.

The PIM kinases (referring to the proviral insertion site in Moloney murine leukemia virus) are overexpressed in several cancer types and appear to exacerbate proliferative disorders (412). Bivalent PIM kinase inhibitors have been developed using D- arginine-rich peptides (ARCs) and adenosine analogs (413). Arginine-rich sequences are found on many substrates recognized by basophilic protein kinases found in the AGC protein kinase group. Even though PIM kinases fall in the calcium-calmodulin-dependent protein kinase (CAMK) group, Ekambaram et al. provided evidence that potent bivalent inhibitors using ARCs can be selective for PIM-1 kinase but not members of the AGC protein kinases (413).

These studies provided evidence that targeting two separate structural features on protein kinases with bivalent compounds could be an effective approach to inhibit the activity of a specific kinase. While many of the approaches to develop bivalent protein kinases inhibitors have yielded useful research tools for understanding signaling pathways

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and biological mechanisms, the clinical applications of these compounds in treating disease have yet to be realized. The large size of bivalent inhibitors may present barriers to their use in targeting intracellular protein kinases. The potential to design smaller peptidomimetic compounds that target specific substrate interaction sites may overcome drug delivery and bioavailability issues associated with using peptides as targeting moieties or therapeutic agents (414).

Part D: Type VI Kinase Inhibitors

There has been resurgence in the development of compounds that form covalent, and generally irreversible, interactions with protein kinases to provide sustainable inhibitory effects primarily to treat cancer. The prospect of developing covalent inhibitors faced criticism of extensive off-target effects. However, there is historical precedence for the benefits and potential risks of developing covalent-binding drugs. Probably the best example of the benefits of covalent bond–forming drugs is acetyl salicylic acid or aspirin.

Although the beneficial anti-inflammatory and analgesic effects of aspirin have been recognized since its discovery in the late 1890s, it was not until the 1970s that its mechanism of action was identified to involve the formation of covalent adducts on cyclooxygenase enzymes and the reduced production of inflammatory cytokines (415).

However, other drugs like acetaminophen metabolize into highly reactive species that form toxic covalent adducts with liver proteins and can cause liver damage at high doses. Despite the understandable concerns about the off-target effects of covalent-binding drugs, advances in structural and computational biology have made it feasible to develop inhibitors that form covalent interactions with protein kinase inhibitors that are selective, efficacious, and have reduced toxicity. This section will highlight some of the features of

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clinically relevant covalent kinase inhibitors and the potential for expanding the development and use of covalent kinase inhibitors in disease.

Recent reviews of covalent small-molecule protein kinase inhibitors provide an excellent summary of the compounds identified to target specific kinases (416, 417).

Covalent type VI protein kinase inhibitors utilize chemical features of the noncovalent type

I–IV kinase inhibitors that interact with the ATP-binding or other regions near the kinase domain. What makes the type VI protein kinase inhibitors unique is the inclusion of reactive electrophilic groups or warheads that react primarily with nucleophilic cysteines although reactions with lysine, aspartic acid, and tyrosine residues can be used to form covalent interactions. Like other drug discovery approaches, type VI kinase inhibitors use structure-guided design approaches that take advantage of noncovalent interactions with the targeted kinase in order to increase specificity and position the warhead component for targeted covalent interaction that locks the inhibitor in place. The covalent adduct typically forms through a Michael addition reaction, and many of the electrophilic moieties used to develop type VI inhibitors utilize an acrylamide group that favors interactions with cysteine residues. In addition, alterations in the reactivity of the electrophile warhead may be used to create reversible covalent protein kinase inhibitors whose duration of inhibition may need tighter control (418). For example, most protein kinase inhibitors that are used to treat cancer might be more effective by a sustained mechanism of irreversible inhibition. In contrast, shorter-acting reversible type IV inhibitors might expand the clinical applications and reduce off-target reactivity and toxicity (418, 419).

An early example of type VI covalent protein kinase inhibitors was the discovery of the mechanism of action for the fungal metabolite wortmannin (420). Wortmannin was

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identified to be an irreversible inhibitor of PI3K isoforms through the formation of a covalent adduct with a conserved lysine (K802) in the catalytic site (420). However, wortmannin is nonspecific, causing overt toxicity, which limits its use to research studies.

Dalton et al. optimized reversible interactions to design compounds that covalently interacted with the analogous conserved lysine (K779) near the active site of PI3Kδ isoform (421). PX-866 is a wortmannin analog that also forms a covalent bond with K802 that entered clinical trials but did not show promising efficacy (422). It remains to be determined whether other type VI PI3K inhibitors will provide an advantage over the current reversible PI3K inhibitors in clinical trials (338).

The success of type VI protein kinase inhibitors has been realized with the development of EGFR- and Bruton’s tyrosine kinase (BTK)-targeted compounds. Afatinib, osimertinib, dacomitinib, and neratinib are FDA-approved type VI inhibitors that target the

EGFR family and are used to treat a variety of cancers (423) (Fig. A2.13). All these drugs form a covalent adduct with a key cysteine (C797 for EGFR) in the active site and are expected to improve treatment options especially in patients who develop drug resistance

(424, 425). While the irreversible nature of these compounds provides a more durable inhibitory response, not all type VI inhibitors may be able to overcome the development of acquired drug resistance observed with first generation type I/II reversible inhibitors (426).

Afatinib, which was designed based on the reversible inhibitor gefitinib, is not effective against the common EGFR T790M mutation that is often responsible for acquired drug resistance.

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Figure A2.13. The chemical structures of (a) afatinib, (b) osimertinib, (c) dacomitinib, and (d) neratinib are shown. The reactive site of the acrylamide moieties is circled in red.

In addition to causing the T790M mutation, afatinib resistance mechanisms include increased expression of the c-Met receptor tyrosine kinase and V843I mutation on EGFR

(427). New structures, such as osimertinib, are less restricted by the T790M mutation and may have better treatment outcomes for patients resistant to first-line EGFR inhibitors

(426).

Ibrutinib is a type VI inhibitor that forms a covalent bond on cysteine 481 (C481) in the active site of BTK and is used to treat B-cell cancers such as chronic lymphocytic leukemia (CLL) (428). Several months after treatment, nearly 80% of relapsing patients contained a cysteine to serine (C481S) mutation that limited the efficacy of ibrutinib (429).

Alternative reversible BTK targeted compounds that tolerate the C481S mutations are showing promise in treating CLL relapses (430). Ibrutinib has also been associated with several adverse drug events, which likely occurs due to the covalent interactions with other targets and presents a barrier for its use in some patients. Acalabrutinib is a second- generation type VI BTK inhibitor that targets C481 that reportedly causes fewer adverse

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events and is showing more sustained patient responses in clinical trials evaluating relapsed or refractory chronic lymphocytic leukemia (431).

The MAP kinases have been the target of several type VI inhibitors. Zhang et al. described the use of the type II kinase inhibitor imatinib to design covalent inhibitors against JNK1/2/3 isoforms (432). The authors noted that several kinases targeted by imatinib have a potentially reactive cysteine that precedes the DFG motif of the activation loop. By attaching an electrophilic acrylamide, a compound was identified that targeted not only expected tyrosine kinases but also JNK isoforms. Further modifications identified compounds with improved JNK selectivity and potency to allow their use as reagents to examine cellular functions for the JNK pathway (432). In a study by Ward et al., new reversible ERK1/2 inhibitors, with a pyrimidine scaffold, were identified and modified with an acrylamide functional group to make irreversible covalent inhibitors that targeted

C166, which is directly adjacent to the DFG motif at the beginning of the active loop (433).

This cysteine is conserved in ERK1/2 but not in p38 or JNK MAP kinases, which is expected to provide some degree of selectivity. More recent studies have identified

ERK1/2-targeted compounds that form covalent bonds with a cysteine (C159) located in the D-recruitment site (DRS) outside the ATP-binding site (358). The lead compound, BI-

78D3, appears to block interactions between ERK2 and its activator MEK1. Despite C159 being conserved in other MAP kinases, such as p38 and JNK, BI-78D3 modifications were only observed on ERK1/2 suggesting other DRS structural features facilitated selectivity

(358).

New approaches for cancer therapy through targeted inhibition of transcriptional regulation by cyclin-dependent kinases (CDKs) have utilized covalent-binding compounds

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(434). These studies identified a compound THZ1 that covalently binds to a cysteine

(C312) that resides outside of the ATP-binding site and inhibits CDK7, and to a lesser extent CDK12 and 13, phosphorylation of RNA polymerase II. Modifications to THZ1 that improved potency and drug-like properties led to the generation of the covalent CDK7 inhibitor SY-1365, which is currently in cancer clinical trials (435). A common problem that reduces the efficacy of THZ1 and other drugs is their efflux by the ABC transporters.

Gao et al. provided evidence that upregulation of ABC transporters by THZ1 can be overcome by compounds that covalently target CDK12 and are not ABC transporter substrates (436).

Downstream of PI3K, Akt protein kinases have been targeted by covalent inhibitors

(437). Weisner et al. posited that allosteric inhibitors, such as the previously mentioned

MK-2206, that targeted the PH-domain were proximal to cysteines that could be targeted to generate selective and irreversible Akt inhibitors (437). The result of these studies is the compound borussertib, which forms a novel covalent interaction on C296 and has been shown in preclinical studies to be effective in combination with the type III MEK1/2 inhibitor trametinib for inhibiting pancreatic and colorectal cancers expressing KRas mutations (438). The structure of borussertib in complex with Akt1 is shown in Fig. A2.14.

Borussertib covalently binds C296 and forms hydrophobic interactions between the PH domain and the ATP-binding site.

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Covalent type VI protein kinase inhibitors have provided new options for more durable responses and target selectivity. Significant benefits have been observed with type

VI inhibitors, such as afatinib and ibrutinib, versus reversible type I/II inhibitors for the treatment of lung cancers (439) and lymphocytic leukemias (440). Nonetheless,

Figure A2.14. Structure of borussertib in complex with Akt1 (PDB: 6HHF). Borussertib (magenta lines) interacts with C296 (green) and makes hydrophobic interactions with L210, L264, and I290 (cyan). PH domain residues 5–108 (orange), and ATP site residues 156–164 (yellow) are shown

acquired drug resistance through mutations in the targeted cysteine and off-target interactions remain barriers to durable patient outcomes. Expanding the repertoire of amino acids targeted by type VI inhibitors beyond the common cysteine targets may provide advantages. For example, targeting lysine residues in the active site of protein kinases with type VI compounds may be effective at disabling enzyme activity. However, surface- exposed lysines are generally thought to be poor nucleophiles because they are protonated

(pKa ~10.5) at physiological pH (417). Recent studies using computational predictions suggest that localized pKa values may shift several units, allowing lysines to be amenable to reacting with electrophilic warheads (441). Given the success of current covalent inhibitors targeting EGFR and BTK protein kinases, the future will likely see the development of new type VI inhibitors for treating disease.

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Appendix 3. Protein Kinase Interactions with Regulatory and Effector Proteins6

Abstract

The previous chapters discussed the general structure of protein kinases and signaling networks that kinases use to transmit extracellular signals from plasma membrane receptors through the cell to cause changes in gene expression and cellular responses. This chapter will take a closer look at the interactions between protein kinases and their substrates and interacting partners. Despite the well-conserved organization of the ATP-binding and - catalytic site, kinases have quite diverse functions depending on the substrate that is phosphorylated. Some kinases may phosphorylate and regulate only a couple of substrates whereas other kinases may phosphorylate hundreds of different substrates. The mechanisms by which kinases recognize specific substrates are still being revealed. This chapter will describe some of the structural features that determine kinase recognition of specific protein substrates. Experimental evidence that specific kinases can phosphorylate dozens of substrates will lend support to the idea that complete inhibition of specific disease-related kinases, as currently done with type I–III kinase inhibitors, may also inhibit kinase functions that have beneficial effects. The theme of this and subsequent chapters is to show the structural features that determine specific protein kinase–substrate interactions and to highlight new approaches that inhibit the kinase interactions and functions that are involved in disease while preserving kinase activities that have clinical benefits.

Keywords Protein kinase, Substrates, Protein-protein interactions, Docking domains, Function-selective inhibition

6 Defnet A., Martinez R., Shapiro P. Protein Kinase Interactions with Regulatory and Effector Proteins. In: Shapiro P. (eds) 2020. Next Generation Kinase Inhibitors. Springer, Cham. https://doi.org/10.1007/978-3- 030-48283-1_4

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Introduction

In 2002, significant progress in understanding kinases was made with the determination of the human kinome and the phylogenetic classification of more than 500 kinases encoded in the human genome (295). Research over the last 30 years has revealed the pleiotropic effects of protein kinases through their ability to regulate a diverse set of substrates and cellular functions. However, the functions for many of these kinases and their substrates are still being elucidated. To facilitate the understanding of protein kinase functions, several bioinformatics tools are available that have collated current information on kinase signaling networks and are used to determine potential substrates. In addition, several computational and structural biology tools available allow experimental examination of the exquisite and unique structural features that determine how kinases interact with specific substrates. These resources provide starting points for the development of new approaches to inhibit specific protein kinase functions through targeted disruption of select substrates.

Many of these bioinformatics resources are publicly available and provide important information on known kinases and substrate phosphorylation events. The

Universal Protein Resource (UniProt; www.uniprot.org; Swiss-Prot Protein

Knowledgebase (442)) contains excellent information on all identified proteins, and a list of all protein kinases is available (https://www.uniprot.org/docs/pkinfam).

PhosphoSitePlus is a database that was developed over 15 years ago and has compiled nearly 300,000 phosphorylation sites based on peer-reviewed publications and unpublished data using mass spectrometry (443). This compilation of data provides extensive information on individual phosphorylation sites, their potential function in vivo and in

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vitro, and primary supporting references. Protein phosphorylation events and other posttranslational modifications have also been well-documented on the bioinformatics resource iPTMnet (https://research.bioinformatics.udel.edu/iptmnet/). Other publicly available databases, such as KinaseNET: Human Protein Kinase Knowledgebank

(www.kinasenet.ca), have archived extensive information on specific protein kinases, their substrates, and regulation by phosphorylation (444). In cases where phosphorylation regulation of a protein is not known, there are resources available that use computational predictions to identify phosphorylation sites and the putative kinase involved. For example, putative phosphorylation events for a select number of kinases can be evaluated using

NetPhos (445) and Phosphopredict bioinformatics (446).

Docking Interactions Between Protein Kinases and Other Proteins

Despite a remarkable similarity in the three-dimensional structure, protein kinases have the unique ability to be quite selective in the substrates they target and the amino acids they phosphorylate. Parameters such as proximity within intracellular locations and protein expression levels will certainly impact the ability for proteins to interact. Additional key determinants that facilitate protein kinase recognition and phosphorylation of a unique substrate include the amino acids that surround the serine, threonine, or tyrosine phosphorylation sites and other distant structural features that coordinate protein-protein interactions. A review by Ubersax and Ferrell provides a comprehensive description of protein kinase recognition of substrates and the determinants of phosphorylation specificity (447). As was described in previous chapters, the kinase domain is the major determinant of whether serine/ threonine versus tyrosine phosphorylation will occur depending on the size of the catalytic cleft and its ability to

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accommodate the bulkier tyrosine residue. In addition, the consensus basic, acidic, hydrophobic, or proline residues that surround the serine, threonine, or tyrosine phosphorylation sites will determine protein kinase specificity. Several other reviews provide detailed summaries of consensus phosphorylation site sequences on substrates and the kinases that target them (447-449).

Protein kinases also coordinate with substrates through specific interactions on regions that are distal from the catalytic cleft. Miller and Turk (449) provide an excellent summary of the features that determine interactions between kinases and substrates including the phosphorylation motif and adjacent docking interactions, distal docking sites, and the coordination with adaptor proteins to help facilitate interactions. This section will focus on the mitogen-activated protein kinases (MAPKs) as the paradigm for examples of kinase-substrate interactions. Previous chapters outlined the major MAPK signaling pathways from the plasma membrane receptor to the kinase cascade that mediates changes in gene expression and cellular functions. This chapter will summarize the general features that regulate protein-protein interactions in MAPK signaling networks. Subsequent chapters will expand upon these structural interactions and provide additional details on the critical features that determine how protein kinases regulate specific substrates.

Understanding the features that regulate these protein-protein interactions will facilitate the rationale design of molecules that disrupt the interactions that are relevant in the progression of disease.

The individual MAPK proteins represent key nodes where signaling information converges on the activation of MAPK through phosphorylation of a conserved threonine- any amino acid-tyrosine (TXY) motif by selective MAP2K (MEK) proteins. The pairing

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of the conventional MAP2K and corresponding MAPK is shown in Table A3.1. While the conventional MAP2K-MAPK interactions will be the starting point for discussions on protein kinase–substrate interactions, it should be noted that there are also atypical MAPK isoforms that do not follow this mode of regulation (313). The atypical MAPKs, including

MAPK6/4/15 (ERK3/4/7/8), while structurally similar to conventional MAPK proteins, do not appear to have corresponding MAP2K activators but are regulated through autophosphorylation or other kinases (450-452).

Table A3.1. Typical MAP2K (MEK) isoforms and their corresponding MAPK substrates.

As indicated, MAP2K isoforms phosphorylate TXY motifs to activate their respective MAPK. However, another determinant of selectivity of MAP2K-MAPK pairing is through protein-protein interactions that are distal to the site of phosphorylation. The

MAP2K proteins contain unique D-domain motifs consisting of basic residues in the N- terminal domains connected through a short linker to hydrophobic residues. Table A3.2 shows a sequence alignment of the major MAP2K isoforms and the sequences that have been identified to form the D-domain (453). Except for MAP2K7, which will be discussed in more detail later, MAP2K isoforms have a single consensus D-domain sequence. The

D-domain residues on MAP2K proteins selectively interact with specific sequences on

MAPK proteins that form the D-domain recruitment site (DRS). The DRS of MAPK isoforms is made up of C-terminal acidic residues that are referred to as the common

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docking (CD) domain (Table A3.3) and N-terminal hydrophobic and variable residues

(Table A3.4). The variable residues on p38 MAPK isoforms include a glutamate (E) and aspartate (D) and are referred to as the ED domain. Although the ED residues are different on other MAPKs, the ED designation is used as a general descriptor of this site within the

DRS of all MAPK sequences (Fig. A3.1).

Table A3.2. Sequence alignment of amino acid residues in the N-terminus of MAP2K (MEK) isoforms. Highlighted in green are the basic, linker, and underlined hydrophobic residues that contribute to the D-domain as previously described in Bardwell et al. (2009). The N-terminal methionine is highlighted in red

Table A3.3. Sequence alignment of C-terminal acidic residues (green shading) that form the common docking (CD) residues and contribute to the D-domain recruitment site (DRS) on human MAPK isoforms.

Table A3.4. Sequence alignment of amino acid residues in the N-terminus that contribute to the DRS. Hydrophobic and variable residues of the ED domain are underlined and highlighted in purple. The conserved DFG motif and activating phosphorylation sites of MAPK isoforms are shown in yellow and cyan, respectively on human MAPK isoforms

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Figure A3.1. The D-domain recruitment site (purple and green spheres) sits adjacent to the DFG motif (yellow) and opposite of the activation sites (blue). The conserved lysine in the ATP- binding site is shown in red. Protein Data Bank structures used for ERK2 (MAPK1), p38α (MAPK14), and JNK1 (MAPK8) were 4GT3, 5ETI, and 3O17, respectively.

A second docking domain that has been identified on MAP kinase regulatory and downstream substrate proteins is referred to as the docking site for ERK, F-X-F (DEF) motif (210, 454). The FXF motif is typically separated from the serine or threonine phosphorylation sites by 6–20 amino acids and is found on transcription factors, scaffold proteins, and MAP kinase phosphatases (455). The F-site recruitment site (FRS) on MAP kinases consists primarily of hydrophobic amino acids C-terminal to the activation loop

(Table A3.5) that form specific contacts with hydrophobic phenylalanine residues in the

FXF motif.

Table A3.5. Sequence alignment of the FRS between major MAPK proteins. Amino acids in the FRS are underlined and highlighted in green. The numbering of the C-terminal residues in the FRS is indicated. The conserved activating phosphorylation sites and APE motif at the end of the activation loop for major human MAPK isoforms are shown in cyan and yellow, respectively

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The spatial organization of the combined CD and ED amino acids to form the DRS and the FRS residues on the ERK2, p38α, and JNK1 MAP kinases is depicted in Fig. A3.2.

The DRS and FRS are positioned on opposite sides of the kinase in these static models. It is also likely that other transient interactions occur that determine substrate interactions depending on the kinase activation state. For example, structural studies on ERK2 using hydrogen deuterium exchange mass spectrometry suggest that accessibility to the FRS by substrates is limited prior to activation, and it is only after phosphorylation of ERK2 at the active sites does a conformational change in the FRS facilitate the interactions with substrates containing the DEF motif (210). The structural features of the DRS and FRS have previously been used to identify function-selective small-molecular-weight type IV inhibitors of ERK2 and p38α MAP kinases (63, 183, 207, 208).

MAP Kinase Interactions Through the DRS

The DRS on MAP kinases provides a docking domain for specific interactions with an upstream MAP2K activator and downstream effector proteins. The number and type of substrates regulated by the specific MAP kinases can vary extensively. For example, it has been suggested that the ERK1/2, p38α/β, and JNK1/2 MAP kinases may have more than

300, 100, and 80 substrates and binding partners, respectively (456-458). Although some overlap exists, many of these substrates and binding partners selectively interact with their respective MAP kinase. Given the sequence similarity of the DRS across MAP kinases, the question arises as to how do MAP kinases identify and interact with their unique substrate? Earlier reports provided evidence that ED domain residues provided selectivity for substrate recognition (211, 459). Tanoue et al. demonstrated that exchanging the ED

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Figure A3.2. Spatial organization of the DRS and FRS on MAP kinases. The ribbon structures of ERK2 (pdb:4GT3), p38α (pdb:5ETI), and JNK1 (pdb: 3O17) are shown highlighting the conserved lysine in the ATP catalytic site (green), the DFG motif (yellow), and TXY activation sites (magenta). The DRS comprising CD (cyan) and ED (red) residues and the FRS (orange) are highlighted. As shown here and in all subsequent figures, the N-terminal and C-terminal lobes of the protein kinase are positioned at the top and bottom, respectively, of each image. residues between p38α and ERK2 MAP kinases could alter substrate recognition so that p38α could interact with an ERK2 substrate and vice versa (459). This demonstrated the importance of the ED domain residues in determining substrate selectivity between structurally similar MAP protein kinases. Using D-domain peptides that represented substrates of ERK2, p38α, and JNK1 MAP kinases, Garai et al. examined structural

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features that determined selectivity between MAPKs and peptides representing interacting proteins (460). These studies provided additional insight to key interactions within a docking groove that sits between the CD and ED residues and allow MAP kinases to discriminate between their substrates and binding partners.

The following section will highlight structural studies that describe DRS interactions between the major MAP kinases and activator, effector, or regulatory proteins.

Co-crystallization of the kinase with a peptide representing the interacting partner provides useful information as to how interaction with the DRS can discriminate between an activator protein and a downstream effector. Figure A3.3 depicts the interactions between

ERK2 and peptides representing D-domain containing activator (MEK2) or p90 ribosomal

S6 kinase (RSK1) effector proteins (461). Each peptide appears to occupy the groove between the CD and ED domains. However, the interactions with a region just below the

ED domain appears to show differences that could be potentially exploited to inhibit

ERK1/2 activation of RSK1 while preserving ERK1/2 activation by upstream MEK proteins. Inhibition of RSK signaling may benefit the treatment of triple negative breast cancer (462), and at least one RSK-selective inhibitor, PMD-026, has entered breast cancer clinical trials as of October 2019. Additional structures of ERK2 interactions with peptides representing regulatory phosphatase proteins have been solved. The structures of ERK2 in complex with D-domain peptides of hematopoietic protein tyrosine phosphatase (HePTP)

(463) and dual-specific MAP kinase phosphatase-3 (MKP3) (464) reveal similarities and differences. In both examples, peptide interactions with the ERK2 DRS involve electrostatic interactions and hydrophobic interactions, which is also the case with p38α and JNK1 MAP kinase as discussed below. Differences that occur in the nonconserved

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amino acids in the DRS are thought to determine the selectivity of interacting partners with

MAP kinases.

Figure A3.3. Structural interactions between ERK2 and activator (MEK2) and substrate (RSK1) peptides (magenta lines). The DRS of ERK2 consists of CD (cyan) and ED (red) domain residues. The conserved lysine in the ATP catalytic site is shown in green. (a) MEK2 peptide (RRKPVLPALTINP) interactions with the DRS (PDB:4H3Q). (b) RSK1 peptide (PQLKPIESSILAQRRVRKLSPTTL) interactions with the DRS (PDB:4H3P)

The use of peptides to determine structural interactions has limits as they do not readily form secondary structures as found in the full-length protein, and they may not reflect allosteric effects of other domains. More recently, a cocrystal structure of inactive

ERK2 and the kinase domain of RSK1 was determined (465). This structure showed similar interactions between the D-domain of RSK1 and the ERK2 DRS as to what was described previously in Fig. 3 for the RSK1 D-domain peptide, although in this case the

D-domain is connected to the rest of the RSK1 kinase domain through an unstructured linker (Fig. A3.4). The two kinases are inverted in relation to each other with the N-terminal lobe of ERK2 facing the C-terminal lobe of the RSK1 kinase domain (Fig. A3.4). As suggested by this inactive complex, the threonine residue that is phosphorylated by ERK2

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is positioned near the catalytic site. However, molecular dynamics simulations have suggested that structural changes occurring when ERK2 becomes activated allow positioning of the threonine close enough to the active site for phosphoryl transfer to occur

(465).

Figure A3.4. Structural interactions between ERK2 and the kinase domain of RSK1. The DRS of ERK2 (MAPK1) consists of CD (cyan) and ED (red) amino acids. RSK1 (light yellow ribbon) and ERK2 (grey ribbon) are shown as a heterodimer (PDB:4NIF). The RSK1 D-domain peptide (magenta) interacts with the docking groove between the ERK2 CD and ED domains. Threonine 573 (blue) on RSK-1 is positioned for phosphorylation by ERK2. The conserved lysine in the ATP catalytic site is shown in green

The interactions of p38α MAP kinase with peptides representing activator (MEK3) and effector (MEF2A) proteins that use the DRS have been described (466). Figure A3.5 shows the positioning of DRS-interacting peptides that correspond to an activator of p38α

(MKK3) and a downstream transcription factor effector (MEF2). Unlike the involvement of basic residues of D-domain peptides that interact with acidic CD domain residues on

ERK2, the CD domain did not appear to be involved in MEK3 and MEF2A interactions

(Fig. A3.5) (466). There were key differences between the interactions of MEF2A or

MEK3 with p38α that could be exploited to develop a MEF2A-selective inhibitor. First,

MEF2A interactions are more extensive and occupy a larger part of the groove between

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the CD and ED domains. Second, the common DLR sequence on both MEF2A and MEK3 peptides does not interact in the same way with the docking groove of p38α. Thus, these differences in DRS interactions could help guide the identification of inhibitors that preserve desirable p38α interactions with MEK3 and overall signaling functions but selectively block interactions between p38α and MEF2A to inhibit signaling events associated with disease (467).

Figure A3.5. Structural interactions between p38α MAPK activator (MEK3) and substrate (MEF2A) peptides. The DRS of p38α (MAPK14) consists of CD (cyan) and ED (red) amino acids. (a) MEK3 peptide (SKGKSKRKKDLRISCNSK) interaction with the DRS (pdb:1LEZ). (b) MEF2A peptide (RKPDLRVVIPPS) interaction with the DRS (pdb: 1LEW). The conserved lysines in the ATP catalytic sites are shown in green

To gain further insight into p38α MAP kinase interactions with downstream effector proteins, the structure of the inactive heterodimer complex of p38α and full length

MAPKAPK2 (MK2) was determined (468). MK2 is a major mediator of inflammatory signals regulated by p38 MAP kinases and targeted inhibition of MK2 could mitigate inflammatory processes involved in acute and chronic lung disease as well as rheumatoid arthritis (20, 63, 469). The crystal structure shows a face-to-face interaction with the ATP- binding sites of each kinase positioned adjacent to each other (Fig. A3.6). The MK2 C- terminal residues from 368 to 400 wrap around p38α and include the D-domain residues

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that form a helix that fits in the DRS docking groove, which is the major contributor of the heterodimer formation. There is also evidence to suggest some interactions between the disordered MK2 activation loop (residues 207–233 shown in black, Fig. A3.6) and p38α through C-terminal α helices. In this inactivated conformation, the major MK2 residues phosphorylated by p38α are spatially separated from the catalytic site (Fig. A3.6).

However, conformational changes upon p38α activation allow ATP catalysis and phosphate transfer to these threonine residues. An interesting aspect of the MK2 D-domain residues is that they interact with p38α in a reverse order as compared to the MEF2A and

MEK3 peptides shown in Fig. A3.5 (468). These studies highlight subtle differences in the interactions between distinct activator and effector proteins to a common docking groove formed by the DRS of p38 MAP kinase that could be exploited in the development of inflammation-modulating agents.

Figure A3.6. Structural interactions between p38α MAP kinase and full length MK2 (pdb: 2ONL). The heterodimer structure of p38α (grey ribbon) and MK2 (light yellow ribbon) shows the C-terminal D-domain residues of MK2 (magenta) interacting with a groove between the CD (cyan) and ED (red) domains of the DRS. The activation loops of both proteins are shown in black. The conserved lysines in the ATP catalytic sites of p38α and MK2 are shown in green and MK2 sites phosphorylated by p38α (T222 in the activation loop and T334 in the C-terminus) are shown as blue spheres

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Structural information on p38α MAP kinases’ interactions with substrate proteins has informed the development of function-selective p38α inhibitor compounds that may mitigate tissue damage following acute myocardial infarction (470). Stress signals associated with ischemia/reperfusion tissue injury following a heart attack result in the auto-activation of p38α though interactions with the transforming growth factor-β- activated protein kinase 1–binding protein 1 (TAB1) scaffold protein (471). De Nicola et al. provided evidence that TAB1 interacts with noncanonical sites and the canonical FRS residues on p38α through hydrophobic interactions (Fig. A3.7a) (470). Although the predicted interacting TAB1 hydrophobic residues were disordered and not visible in the X- ray structure, mutating these residues to alanine within the putative p38α-binding site (e.g. residues V390A, Y392A, V408G, M409A) disrupted interactions with p38α and provided protection from tissue-damaging effects of myocardial infarction in a mouse model (470).

The structural information was used to identify a small molecule, 3-amino-1-adamantanol, that can interact with hydrophobic leucine residues in a noncanonical site near the FRS of p38α and inhibit interactions with TAB1 (Fig. A3.7b). Although this compound was not evaluated for mitigating tissue damage due to ischemia/reperfusion injury, it does provide an example of how protein structural information can inform the discovery of small molecular weight compounds that disrupt clinically relevant protein-protein interactions.

The c-Jun-N-terminal kinases (JNK) are the other major MAP kinase family member with information on the structural interactions between activators and effector proteins. Unique to the JNK MAP kinase signaling pathway is the presence of three putative D-domains on the MEK7 activator (see Table A3.2) that have the potential to

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Figure A3.7. Structural interactions between p38α MAP kinase, TAB1, and a TAB1 inhibitor. The CD (cyan) and ED (red) domain residues of the DRS and the conserved lysine in the ATP catalytic site (green) are shown for reference. (a) Heterodimer complex of p38α (gray) and TAB1 (orange/yellow) [pdb: 5NZZ]. TAB1 residues 384–412 interact with FRS residues on p38α (yellow). (b) Structure of p38α with the TAB1 disrupting compound, 3-amino-1-adamantanol (magenta), shown interacting with leucine residues (orange) near the FRS [pdb: 6SPL] interact with the DRS on JNK proteins. Kragelj et al. demonstrated that all three D-domains bind with similar affinity to JNK1 suggesting that a single MEK7 protein has the potential to engage three JNK1 molecules simultaneously (472). These studies also provided a more detailed structural analysis of the interactions between JNK1 and the second D-domain

(amino acids QRPRPTLQLPLA) that suggest MEK7 may adopt different binding modes depending on the JNK1 activation state and function. One of the MEK7-binding modes shows electrostatic interaction with the CD domain along with hydrophobic interactions with D-domain peptide leucine residues (Fig. A3.8a).

The JNK-interacting protein-1 (JIP1) scaffold protein is an important regulator of stress-induced JNK activity through interactions with DRS (473). JIP1 is highly expressed in brain and adipose tissue and may have particularly important roles in regulating JNK activity associated with obesity, the development of type II diabetes, and neurodegenerative disorders (474). A structure of a JIP1 D-domain peptide interacting with

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JNK1 has been determined (475). Typical of other D-domain sequences, hydrophobic leucine residues contact α helices between the CD and ED domain of JNK1 (Fig. A3.8b).

However, unlike the MEK7 peptide where prominent interactions with basic lysine residues and acidic residues on the CD domain of JNK1 are observed, this interaction was not evident from the JIP1-JNK1 structure (compare the peptide interactions with CD domain in Fig. A3.8a, b). The structural features of JIP1 interactions with JNK1 have helped facilitate the development of new compounds that target the JIP1 docking site and show improved management of glucose levels in animal models of diabetes (369, 408).

While these studies provide proof of principle that disruption of JIP1 interactions with JNK proteins has clinical benefits, translating these concepts to patient studies has yet to be achieved.

Figure A3.8. Structural interactions between JNK1 and peptides representing activator (MEK7) or regulatory (JIP1) proteins. The DRS of JNK1 (MAPK8) consists of CD (cyan) and ED (red) amino acids. Lysine in the ATP catalytic site is shown in green. (a) MEK7 peptide (magenta) interacting with DRS (pdb:4UX9). (b) The JIP1 peptide (magenta) interacting with DRS (pdb:1UKI)

While many upstream activators, regulatory proteins, and substrates contain D- domains that facilitate interactions with their respective MAP kinases, few studies have examined how differences between D-domains impact protein-protein binding affinities and subsequent signaling events that control cellular responses. Laughlin et al. provided structural insight into three D-domain-containing proteins and their interactions with the

DRS of JNK3 to explain differences in their binding affinities (476). JNK3 shares a high

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degree of sequence identity with other JNK isoforms, including 75% sequence identity with JNK1. These studies used 11 amino acid peptides representing two scaffold proteins,

JIP1 and SAB (SH3-binding protein 5 or SH3BP5), or the transcription factor ATF2 to examine how each D-domain coordinated interactions with JNK3 (476). As previously discussed, JIP1 plays several roles in regulating JNK activity, including regulation of obesity-induced insulin resistance, while SAB is localized to the mitochondria and involved in JNK-mediated reactive oxygen species (ROS) generation associated with acetaminophen-induced liver injury (477). ATF2 is a member of the AP-1 transcription factor family that can heterodimerize with several other transcription factors to modulate cell survival especially in response to stress (478).

A major objective addressed by Laughlin et al. was to determine the D-domain differences that were responsible for the JIP1 peptide having ~20-fold higher JNK3- binding affinity compared to the SAB or ATF2 peptides (476). Cocrystallization studies indicated that the SAB and ATF2 peptides caused the disordered JNK3 activation loop to coil into an inhibitory helix that interacted with the ATP-binding site (Fig. A3.9). These structural changes suggested a potential mechanism for a docked substrate to inhibit JNK catalytic activity prior to activation loop phosphorylation. JIP1 peptide interactions with carboxy (C)-terminal residues induced a rotation of the amino (N)-terminal lobe in agreement with previous studies describing how overexpressed JIP1 inhibits JNK activity

(475). Binding of the SAB and ATF2 peptides caused a similar allosteric rotation of the N- terminal lobe.

Several differences between the peptides were observed that could explain the higher binding affinity of JIP1 (476). For example, the electrostatic interactions between

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basic residues of the D-domain and acidic residues (cyan in Fig. A3.9) of the DRS were ~1

Å closer with JIP1 as compared to ATF2. Another difference observed was extensive hydrogen (H)-bond interactions of the middle amino acids of the JIP1 peptide compared to fewer H-bonds with the SAB peptide. Finally, hydrophobic residues in the C-terminus of the JIP1 peptide formed additional van der Waals interactions that were not observed with the ATF2 peptide. The higher binding affinity of JIP1 compared to SAB was attributed to a C-terminal proline in the SAB peptide that altered the positioning of an adjacent leucine and helped stabilize the inhibitor helix formed by the activation loop. Since all three of these DRS-interacting proteins have diverse cellular functions, these structural studies provide the basis to rationally design compounds that target select protein-protein interactions to achieve maximal therapeutic benefits.

Figure A3.9. Structural interactions between JNK3 and the D-domain peptides representing (a) JIP1 [pdb:4H39], (b) SAB [pdb:4H3B], and (c) ATF2 [4H36]. The peptides are represented as magenta lines. The CD and ED domains of the DRS are highlighted in cyan and red, respectively. The activation loop (residues 207–230) shown in blue forms a helix (b and c) that fits in the catalytic site. The conserved lysine (K93) in the catalytic site is shown in green

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MAP Kinase Interactions Through the FRS

The F-recruitment site (FRS) on MAP kinases represent another docking site that controls interactions with substrates and regulatory proteins. All MAP kinases have a putative FRS (see Fig. A3.2 and Table A3.5), and the use of X-ray crystallography and other approaches to define the structural role for this site in mediating interactions with

DEF-motif containing proteins has been examined in a few examples. Other biophysical studies have provided compelling evidence that several transcription factors (e.g., Elk-1, c-Fos, and c-Myc) and phosphatases (e.g. MKP3 and MKP7) require a DEF motif to interact with MAP kinases (479-481). In addition, some MAP kinase substrates and regulators (e.g. Elk-1, MKP3, and KSR1) have both a D-domain and DEF motif that coordinate MAP kinase interactions (209, 482). Tzarum et al. provided biochemical evidence that the FRS of p38α is required for the efficient phosphorylation of the transcription factors Elk-1 and ATF2 (483). As was previously described in Fig. A3.9,

ATF2 contains a D-domain peptide but does not contain a consensus FXF sequence characteristic of the DEF motif, suggesting that the FRS on MAP kinases can adapt to other peptide motifs.

The MAP kinase phosphatases (MKP) family, also referred to as the dual specificity phosphatases (DUSP), are key DEF motif-containing regulators of MAP kinase activity through their ability to specifically dephosphorylate threonine and tyrosine residues in the activation loop. Targeted inhibition of MKP proteins may have a beneficial role in modulating the immune response and enhancing the treatments for cancer and inflammatory disorders (484, 485). One of the few examples of structural interactions between the DEF motif and FRS of a MAP kinase has recently been described for JNK1

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interactions with the catalytic domain of MKP7 in cocrystallization studies (371). The complex reveals the expected bilobed JNK1 kinase structure consisting mostly of N- terminal β-sheets and C-terminal α-helices adjacent to the MKP7 catalytic domain, which contains the typical MKP configuration consisting of a central β-sheet that is surrounded by six α-helices (Fig. A3.10). Extensive hydrophobic and electrostatic interactions between the DEF motif and the FRS orient the active site of MKP7 adjacent to the phosphorylated activation loop of JNK1 (Fig. A3.10). Unique to these studies was the assignment of distinct roles for the phenylalanine residues in the consensus DEF motif (371). Interactions with the first phenylalanine (F285) appeared to be important for JNK1 binding whereas the second phenylalanine (F287) was more involved in positioning the MKP7 active site for efficient dephosphorylation.

Figure A3.10. Structural interactions between JNK1 and the catalytic domain of MKP7 [pdb:4YR8]. JNK1 and the catalytic domain of MKP7 are shown as grey and orange ribbons, respectively. The FRS of JNK1 (residues I197, L198, D229, Y230, I231, W234, Y259) are shown in yellow. The MKP7 active site (residues 245–250; CLAGISR) and DEF motif (residues 285– 288; FNFL) are shown in green and magenta, respectively. Electrostatic interactions between MKP7 (black lines) and JNK1 (blue lines) are indicated. The DRS of JNK1 consisting of the CD (cyan spheres) and ED (red spheres) amino acids and the conserved lysine in the ATP catalytic site (green spheres) are shown for reference. Inset shows an expanded view of the DEF motif interaction with the FRS

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Conclusions

This chapter provided some examples of the structural determinants based on X- ray crystallography describing the interactions between protein kinases and activator, regulatory, and effector substrate proteins. Protein kinase signaling networks depend upon these protein-protein interactions to coordinate the appropriate phosphorylation events for cellular responses. The examples provided in this chapter focused on well-characterized docking sites, the DRS and FRS, found on MAP kinases that interact with D-domain and/or

DEF motif regions found on interacting protein partners. There are similarities between each docking site across MAP kinases, which may explain why some substrates (e.g., Elk-

1, ATF2, and c-Fos) are phosphorylated on the same site by several MAP kinase family members. However, MAP kinase members also retain selectivity in their ability to recognize unique substrates and interacting partners, which can be attributed to subtle differences in each MAP kinase docking site and the likely existence of additional contact points on MAP kinases that regulate specific protein-protein interactions. A detailed characterization of the determinants of the contact between a protein kinase and its substrate or regulatory proteins will provide opportunities to develop function-selective protein kinase inhibitors that reduce dysregulated signaling events in disease.

There are several experimental approaches available for determining protein- kinase-interacting partners. As an example, specific antibodies can be used to immunoprecipitate a protein kinase from a complex protein mixture, and counteracting proteins can be identified by mass spectrometry. This approach has been used to identify an ERK1 MAP kinase interactome in the context of neuronal cell differentiation (457).

Most of the ERK1-interacting proteins identified contained D-domains. However,

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variability in binding affinities and immunoprecipitation conditions may bias some protein interactions and fail to identify other interactions that occur in vivo. Other experimental approaches to identify protein kinase substrates include the phosphatase inhibitor and kinase inhibitor substrate screening (PIKISS) method, which was later renamed the kinase- oriented substrate screening (KIOSS) method to take into account the use of kinase activators and inhibitors (486). This approach enriches phosphorylated proteins from cells or tissue following the treatment of specific kinase activators or inhibitors and then uses mass spectrometry to identify the substrates. A compilation of many protein kinase interaction networks can be found at the STRING Consortium (https://string-db.org/), which provides a database of thousands of known or predicted protein-protein interactions based on experimental evidence. While these experimental approaches and database compilations provide the basis for manipulating specific protein-protein-interactions, a detailed analysis of the structural features involved will allow the rational identification and development of compounds that modulate these interactions.

A variety of methodologies for structure-based drug design, including X-ray crystallography, nuclear magnetic resonance, and cryo-electron microscopy, have been widely used to generate structural information on protein kinases (487). Other approaches such as hydrogen-deuterium exchange mass spectrometry can evaluate dynamic structural movements within a protein to evaluate regions of flexibility or rigidity under various conditions (488). With new information on the structural details of protein kinases, new opportunities to develop function-selective inhibitors of protein-protein interactions involved in disease will emerge. The next chapter will describe the use of computational

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approaches, which consider the structural features of protein-protein interactions identified by experimental approaches to design new small-molecule inhibitors of protein kinases.

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Appendix 4: Identifying vitamin A signaling by visualizing gene and protein activity, and by quantification of vitamin A metabolites7

2. DIRECT QUANTIFICATION OF RETINOIC ACID PRODUCTION AND

ENDOGENOUS RETINOID LEVELS IN CELLS

Basal levels of RA can be determined in primary or cultured cells. If basal RA level determination is desired, skip to part 3 in section 2.2 under ‘Protocols’, Retinoid Extraction.

However, amounts of RA can be low in cellular systems necessitating large numbers of cells for analysis (e.g., 1x106 cells or greater depending on the cell type). Alternatively, assessment of RA production is also a useful metric for evaluating RA homeostasis. RA production assays where the amount of RA produced from a given substrate over a defined time typically utilizes 1 x 105 cells (or greater, if available) per replicate. For RA production evaluation, similar to standard enzyme activity assays, timepoint and concentration ranges should first be determined by performing a time-course experiment and a concentration- course experiment to determine conditions within the linear range (122, 489). The RA production assay is amenable to a wide variety of cell types and culture conditions.

2.1 Reagents

1. all-trans-Retinol (store at -20°C with desiccant)

2. all-trans-Retinoic Acid (store at -20°C with desiccant)

3. all trans-Retinal (store at -20°C with desiccant)

4. Acetone (HPLC)

5. Saline (0.9% NaCl): 9 g NaCl in 1 L water

7 Shannon, S.R.; Yu, J.; Defnet, A.E.; Bongfeldt, D.; Moise, A.R.; Kane, M.A.; Trainor, P.A. Identifying vitamin A signaling by visualizing gene and protein activity, and by quantification of vitamin A metabolites. Methods in Enzymology: Retinoid Signaling Pathways, 2020, 637, 367-415.

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6. 0.025 M KOH in 100% ethanol

7. 4 M HCl (to make 50mL)

20 mL 10 M HCl

30 mL H2O

8. Hexanes (Certified or highest grade available)

2.2 Protocols

Part 1. Retinol solution preparation

1. Under yellow light or red light, bring the all-trans retinol (Sigma R7632) and all-trans-

Retinoic Acid (Toronto Research Chemicals Cat# R250200) to room temperature.

2. Add 10 mL ethanol to a clean borosilicate glass scintillation vial.

3. Use a clean disposable borosilicate glass Pasteur pipette to take up the desired amount

of retinoid powder. The powder in the pipette tip should be about 1 mm in diameter.

4. Put the pipette in the borosilicate glass scintillation vial containing 10 mL ethanol.

5. Make sure the powder gets off the glass pipette tip.

6. Put the cap onto the vial and close the cap securely.

7. Vortex the solution for 20 seconds.

8. Repeat step 7 two more times.

9. Measure the retinoid absorbance spectrum using a UV/Vis spectrophotometer by

scanning wavelength from 250nm to 450nm.

10. Use ethanol to blank the spectrophotometer.

11. If the absorbance is too high (typically absorbance should be below 1 on most

spectrophotometers), dilute the retinol solution with ethanol and repeat the

measurement.

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12. Make at least 3 measurements.

13. Calculate the retinol concentration based on Beer’s law: Absorbance=εLc (don’t forget

the dilution factor if you dilute the solution).

Technical notes o Work under yellow or red light. o Always use borosilicate glass pipettes and containers. No plastic tubes or tips or

pipettes. Retinoids stick to many plastics and variable loss of up to 40% can occur when

pipetting retinoid solutions with regular (plastic) pipette tips. Loss due to surface

adherence is especially pronounced at low concentrations. o For determination of UV absorbance of retinoid solutions, cuvettes should be cleaned

thoroughly before and after use with ethanol and/or acetone and then dried completely.

If acetone is used, complete removal is particularly important as acetone will absorb

significantly at low wavelengths. For more stringent cleaning, rinse cuvettes with

concentrated nitric acid followed by water, then 100% ethanol and completely dry. o λmax of all-trans-retinol in ethanol is 325nm. Molar absorptivity (ε) is wavelength (λ)

and solvent dependent. Use the appropriate solvent blank according to the solvent

defining the ε value. Molar absorptivity of all-trans retinol in ethanol at 325 nm is

ε=52770M-1cm-1. λmax of all-trans-retinoic acid in ethanol is 350nm. Molar

absorptivity of all-trans retinoic acid at 350nm in ethanol ε=45,300M-1cm-1. Path length

L=1cm for standard cuvette. For example, if the absorbance of the all-trans-retinol

ethanol solution at 325nm is 0.8, the concentration will be:

퐴 o 푐 = = 0.8/(52770 × 1)=15.16×10-6M=15.16µM 휀퐿 o Retinol solution preparation procedures are also applicable to other retinoids.

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o Preparation of retinal can be accomplished with a similar procedure. All-trans-retinal

has a max of 338 and  of 42,880 in ethanol or a max of 368 and  of 48,000 in hexane. o The typical absorbance spectra of selected retinoids in ethanol is shown in Figure A4.1

Figure A4.1. Example of retinoid absorbance spectra that are typically used for determining the concentration of retinol, RA and retinal. Reproduced from (122).

Part 2. Treating cells with retinol

1. Follow existing protocols for culturing your cells of interest. Typically, the number of

cells needed is at least 0.1 million live cells per extraction. If possible, use 0.5 or 1

million live cells per replicate. Prepare a minimum of 3 replicates. The culture volume

should be at least 1mL. Adjust your culture vessel configuration if necessary. Typically,

a culture of 0.1 million cells per well uses a 12-well plate with 1mL culture media.

Determine the live/total cell ratio by Trypan Blue staining. The ratio should be at least

90% to be consistent with high viability and experimental conditions, which yields

reproducible and representative results.

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2. In most cases, cell culture media should be replaced with serum-free media

immediately preceding the retinol treatment period. Serum contains retinol and will

provide an additional (and possibly variable) amount or retinol as substrate. Serum-free

media with added retinol (or other retinoid substrate) provides a defined substrate

concentration. Most cell lines and types can tolerate serum-free conditions during the

treatment period, which is typically on the order of hours.

3. If you expect some cell death during your treatment or transfection, try to get a live cell

estimate at the time of assay.

4. Under yellow or red light, transfer desired amount of retinoid solution (described herein

as retinol) to the culture using a Hamilton syringe. Typically, the final all-trans retinol

concentration should be 2 µM or another physiologically relevant concentration

(typically 1 – 10 µM). For example, if your culture volume is 2 mL, and your fresh

prepared retinol solution is 400µM, then you need add 10 µL all trans retinol solution

to the culture media. You do not have to remove 10 µL culture media before adding

all-trans retinol solution, but you need to add an equal volume of ethanol (or selected

vehicle) to the control wells. You don’t have to use Hamilton syringe for ethanol /

vehicle controls.

5. After adding retinoid solution to the culture media, mix the media gently and return the

culturing cells to the incubator for the desired period of time.

6. Collect both culture media samples and cell pellet samples under yellow light or red

light.

7. Put the samples in -80°C immediately until extraction.

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Technical notes: o For accurate delivery of a solution of defined retinoid concentration, proper cleaning

of the Hamilton syringe used for delivery is a critical element. Typically, it is necessary

to clean the Hamilton syringe by flushing before and after each experiment with

acetone. To flush, draw up clean acetone and expel to waste. Repeat 30 times. Very

important! This will ensure there is no retinol carry-over. After cleaning the syringe,

dry the syringe. Make sure both the glass barrel and the plunger are completely dry of

residual acetone. o RA production from retinal as a substrate can be performed with a similar procedure.

Typical treatment concentrations range from 0.1-1 µM. o Catabolism of RA can be evaluated by determining the remaining RA over time and

calculating the turnover of RA via the elimination half-life.

Part 3. Retinoid extraction and quantification

1. For the RA extraction, collect 800 µL of media in a 16x125 mm borosilicate glass

disposable culture tube as previously described (122).

2. Remove the remaining media and use a cell scraper to harvest the cells for LC-

MS/MS-based analysis.

3. If immediate sample preparation is not possible, add 300 µL of 0.9% Saline to each

well to store the cells.

4. Cover collected cell and media samples in foil to protect from light and store at -

80°C.

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RA can then be extracted from cells and media using a two-step liquid-liquid

extraction, and quantified using liquid chromatography-multistage tandem mass

spectrometry (122, 126, 127, 129).

3. DIRECT QUANTIFICATION OF RA IN EMBRYONIC TISSUES

3.1 Reagents and materials

1. Acetone (HPLC)

2. Saline (0.9% NaCl)

3. 0.025 M KOH in 100% ethanol

4. 4 M HCl

5. Hexanes (Certified or highest grade available)

6. Internal standard(s) (choose according to desired analyses)

7. Glass homogenizer

8. Glass culture tubes and glass transfer pipets

3.2 Protocol

1. Tissue collection, homogenization, and extraction methodology has been described in

detail previously (122). Procedures and key points for analyses in developmental

models are provided here.

2. Determine the minimum amount of tissue required for your RA assay by systematically

testing a range of tissue quantities. Typical tissue amounts range from 1 -100 mg,

depending on the RA content of the target tissue.

3. Collect tissue under yellow (or red) lights; if using a dissecting microscope use a yellow

(or red) filter.

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4. Freeze tissue upon collection in liquid nitrogen or on dry ice and store at -80°C until

assay.

5. Determine an accurate tissue weight or determine the total protein content for

normalization.

6. It is important to thaw tissue on ice and keep tissue on ice while homogenizing and

extracting.

7. Homogenize tissue in saline (0.9% NaCl), typically 1mL saline. (Be sure to rinse all

homogenizing glassware with water followed by ethanol and/or acetone before and

after use to remove retinoid residue.)

8. Extract tissues using a two-step liquid-liquid extraction that allows for extraction of

both neutral retinoids (retinol, retinyl esters) and polar retinoids (RA, RA metabolites)

from the same sample (122).

9. If retinaldehyde quantitation is desired, an aliquot of homogenate or a separate sample

is required to allow for derivatization of the aldehyde group by O-ethylhydroxylamine

(121, 122, 131).

Note: RA levels that have been reported in embryo and embryonic tissues are compiled in

Table A4.1.

Table A4.1. (next page) Select RA levels in mouse embryos and tissues. In some cases, values have been rounded from reported data and/or estimated from graphical representations. See references indicated for specific RA data including error, statistical significance, and numbers of N as well as full description of accompanying phenotype. Note that data expressed as per g protein is typically a ~25-250X greater value than per g tissue – depending on protein content of sample type.

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Day Type of Reported value RA Model of Ref** sample for RA*, **, *** Phenotype** assay Mouse: wild-type Whole embryo E12.5 20 pmol/g tissue normal (490) Mouse: Dhrs3+/- Whole embryo E12.5 21 pmol/g tissue Similar to (490) normal Mouse: Dhrs3-/- Whole embryo E12.5 27 pmol/g tissue Excess RA (490) Mouse: wild-type Whole embryo E14.5 5.2 pmol/g tissue normal (81) Mouse: Dhrs3+/- Whole embryo E14.5 5.2 pmol/g tissue Similar to (81) normal Mouse: Dhrs3-/- Whole embryo E14.5 7.7 pmol/g tissue Excess RA (81) Mouse: wild-type Whole embryo E10.5 350 pmol/g normal (491) protein Mouse: Whole embryo E10.5 275 pmol/g Reduced RA (491) Rdh10m366Asp protein Mouse: wild-type Whole embryo E12.5 275 pmol/g normal (491) protein Mouse: Whole embryo E12.5 100 pmol/g Reduced RA (491) Rdh10m366Asp protein Mouse: wild-type Whole embryo E14.5 210 pmol/g normal (491) protein Mouse: Whole embryo E14.5 110 pmol/g Reduced RA (491) Rdh10m366Asp protein Mouse: Rbp4-/- Whole embryo E12.5 120 pmol/g (492) VAS protein Mouse: Rbp4-/- Whole embryo E12.5 57 pmol/g Reduced RA (492) VAD protein Mouse: Foxc1+/ meninges E14.5 740 pmol/g normal (493) protein Mouse: Foxc1l/l meninges E14.5 590 pmol/g Reduced RA (493) (Foxc1-null) protein Mouse: Foxc1+/ cortex E14.5 280 pmol/g normal (493) protein Mouse: Foxc1l/l cortex E14.5 140 pmol/g Reduced RA (493) (Foxc1-null) protein Mouse:wild-type hippocampus E19 20 pmol/g tissue normal (494) Mouse: wild-type hippocampus E19 30 pmol/g tissue Excess RA (494) +ethanol, low BAC% Mouse: wild-type hippocampus E19 400 pmol/g Excess RA (494) +ethanol, high tissue BAC% Mouse:wild-type cortex E19 12 pmol/g tissue normal (494) Mouse: wild-type cortex E19 24 pmol/g tissue Excess RA (494) +ethanol, low BAC% Mouse: wild-type cortex E19 600 pmol/g Excess RA (494) +ethanol, high tissue BAC%

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3.3 Analysis

Quantification of RA:

Quantify RA using an LC-MS/MS-based assay. Quantification of other retinoids is also possible using a variety of methods (121, 122, 126, 127, 129, 131). Typical sample numbers range from 5-10 biological replicates. However, the sample numbers required to demonstrate statistical significance may be more or less depending on the normal variability of RA within the target tissue and the magnitude of change in RA observed in the experimental model.

Considerations for RA quantification in tissue:

LC-MS/MS-based quantification in tissue is applicable to any tissue and yields a direct, absolute quantification of RA. It imparts temporal accuracy and represents the level of RA at the time of collection. However, LC-MS/MS-based quantification of RA is fairly time- intensive and requires specialized instrumentation. The spatial resolution of LC-MS/MS- based analysis, which relies on homogenization of tissue regions before analysis, is limited to the ability to dissect regions of interest and does not yield any intact visualization of RA.

Additionally, the typical tissue requirements for RA analysis may necessitate pooling of samples.

4. CELL-BASED ASSAYS OF RA SIGNALING: F9 RARE-LACZ REPORTER

4.1 Materials and reagents

1. 0.2% gelatin coated plates

2. Dulbecco’s Modified Eagle Medium: Nutrient Mixture F-12 (DMEM/F12)

supplemented with 10% Heat-Inactivated Fetal Bovine Serum (FBS)

3. 1X Penicillin-Streptomycin

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4. 0.4 mg/mL G418, Geneticin

4.2 Reporter Reagents (available upon request)

The RARE reporter cell line F9-RARE-lacZ (SIL15-RA) was a kind gift from Dr. Michael

Wagner (SUNY Downstate Health Sciences University) and Dr. Peter McCaffery

(University of Aberdeen). The RA-responsive F9 cell line expresses the E. coli lacZ gene under the control of a RARE element derived from the human retinoic acid receptor-β gene

(RARβ) (140).

4.3 Protocols

Culture of F9-RARE-LacZ cells:

F9-RARE-LacZ cells can be cultured and maintained as previously described (140, 495) using 0.2% gelatin coated plates and Dulbecco’s Modified Eagle Medium: Nutrient

Mixture F-12 (DMEM/F12) supplemented with 10% Heat-Inactivated Fetal Bovine Serum

(FBS), 1X Penicillin-Streptomycin, and 0.4 mg/mL G418, Geneticin.

F9 RARE-LacZ Assays of RA-signaling activity: concentration dependent response

1. Set up each each replicate of RA-treated F9 RARE-LacZ cells in duplicate assays to

allow for the measurement of RA levels by LC-MS/MS in parallel with assessment of

the RA-signaling activity observed at the same time point.

2. Cells should be minimally seeded at 5x104 cells per well in a 0.2% Gelatin Coated 12-

well cell culture plate.

3. Incubate cells with 1 mL of media supplemented with either all-trans RA (final

concentration 0.5, 5 or 50 nM as in Figure 3 or with desired concentration(s)), or

unsupplemented culture media as a control.

Determination of RA levels via LC-MS/MS in F9 RARE-LacZ stable cell line

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1. At the desired time points (e.g., 0, 0.5, 1, 2, 3, 6, 12, 24, 48, 72, and 96h as in Figure

A4.2 or desired timepoint(s)) collect media aliquots.

2. Remove remaining culture media.

3. Use a cell scraper to harvest cells for LC-MS/MS analysis.

4. Media and cell pellets can be frozen at -80C until sample extraction.

F9 RARE-LacZ stable cell line sample collection and β-Galactosidase enzyme reporter assay

1. For the assessment of reporter response via β-Galactosidase, remove growth medium

and wash cells twice with 200µL of PBS Buffer.

2. Add 200 µL of Reporter Lysis Buffer to the cells and rock at room temperature for 15

minutes.

3. Scrape off cells and transfer to a 1.5 mL centrifuge tube.

4. Vortex for 10 seconds, and centrifuge at 4°C for two minutes at top speed.

5. Transfer the supernatant into a 1.5 mL DNA LoBind Tube (Eppendorf) and store at -

80°C until all required timepoints are collected.

6. A β-Galactosidase Enzyme Assay System with Reporter Lysis Buffer (RLB)

(Promega) kit can be used to assay the samples according to the manufacturer’s 96-

well plate format. Absorbance is monitored at 420nm with a POLARstar Omega plate

reader (BMG Labtech) or comparable plate reader.

4.4 Analysis

Evaluating RA reporter response in the F9 RARE-LacZ stable cell line: cellular assay of

RA-signaling activity as compared to RA levels: In Figure A4.2, an example of data obtained from the F9 RARE-LacZ stable cell is shown in comparison to RA determined by

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LC-MS/MS-based detection. Cells were treated with varying concentrations of RA (0.5, 5, and 50 nM RA) and reporter response via β-galactosidase staining as well as RA levels were assessed over time up to 96h. Figure A4.2A, the β-Galactosidase reporter assay showed an increase in signal starting at 3 hours, followed by a peak in signal at 24 hours, which subsequently decreased at 48h for all atRA concentrations. No difference was seen between the 5 and 50 nM ATRA treatment. Figures A4.2B and A4.2C show the RA levels in the cell and media, respectively. Figure A4.2B and A4.2C showed a sustained, concentration dependent level of RA through 12 hours before decreasing, likely due to metabolism of RA.

Figure A4.2. Evaluating RA reporter response in the F9 RARE-LacZ stable cell line: β- Galactosidase reporter assay indicating RA-Signaling Activity as compared to RA levels. Cells were treated with 0-50nM of all-trans retinoic acid (atRA or RA) and reporter response and RA levels were measured over time for 0-96h. (A) The β-Galactosidase reporter assay cell (B) RA in cell as determined by LC-MS/MS (C) RA in media as determined by LC-MS/MS. Cell culture for (A)-(C) and reporter assay conditions for (A) described in section III. LC-MS/MS quantitation for (B) and (C) as described in section I and in Jones et al. Error bars represent standard deviation (n=3).

5. CELL-BASED ASSAYS OF RA SIGNALING: TWO-HYBRID Gal4-RAR;UAS- tk-Gaussia LUCIFERASE REPORTER

5.1 Materials and reagents

1. 0.2% gelatin coated plates

2. Dulbecco’s Modified Eagle Medium:

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Nutrient Mixture F-12 (DMEM/F12) supplemented with 10% Heat-Inactivated Fetal

Bovine Serum (FBS)

3. 1X Penicillin-Streptomycin

4. 0.4 mg/mL G418, Geneticin

5.2 Reporter reagents (available upon request)

Human Embryonic Kidney (HEK293) cells were obtained ATCC (496). A construct expressing a fusion of the DNA-binding domain of the GAL4 protein (aa 1–147) to the ligand binding domain (aa 156–457) of zebrafish RARαb under the control of a CMV promoter was obtained as a kind gift from Joshua Waxman (University of Cincinnati/

Cincinnati Children’s Hospital) and has been previously described (152, 153). A construct expressing Gaussia luciferase under the control of the HSV thymidine kinase minimal promoter was generated by cloning 5 tandem copies of upstream activating sequences

(UAS) in the Bgl2 site of the pGluc-mini-TK-2 plasmid (New England Biolabs)

5.3 Protocols

Culture HEK293 cells in Eagle’s Minimum Essential Media (MEM) with 10% FBS.

Two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter of RA presence reagents

1. Reverse co-transfect HEK293 cells with pGluc-mini-TK-2-UAS and pCS2p+Gal4-

RAR reporter plasmids at 500ng each, per well, using Lipofectamine 2000

(ThermoFisher) in Opti-MEM (Invitrogen), and seed at 0.2 million cells per well in a

12-well cell culture plate.

2. After allowing the cells to attach, approximately 3 hours, add 1 mL of Eagle’s MEM

to each well and incubate overnight.

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3. The next day, remove cell media and replace with 1 mL of media supplemented with

either all-trans Retinoic Acid (ATRA) (0.5,5,50 nM as in Figure A4.3 or desired

concentration(s)), holo-Retinol Binding Protein 4 (RBP4) (0.4,2,10 µM as in Figure

A4.4 or desired concentration(s)), or unsupplemented Eagle’s MEM, as a control at 0h.

4. Collect samples at 0, 0.5, 1, 2, 3, 6, 12, 24, 48, 72, and 96h as in Figure A4.3, Figure

A4.4 or desired timepoint(s).

Determination of RA levels via LC-MS/MS in HEK293 cells expressing the two-hybrid

Gal4-RAR;UAS-tk-Gaussia luciferase reporter

1. At the desired time points, collect media aliquots.

2. Remove the remaining culture media and use a cell scraper to harvest cells for LC-

MS/MS analysis.

Gal4-RAR;UAS-tk-Gaussia luciferase expressing cells sample collection and Gaussia luciferase reporter assay

1. Collect 100 µL of media in a 1.5 mL DNA LoBind Tube (Eppendorf) for use in the

reporter assay as previously performed (152, 153).

2. A Gaussia Luciferase Flash Assay Kit (ThermoFisher) with a Corning 96-Well Solid

White Polystyrene Microplate can then be used to determine luciferase activity

according to the manufacturer’s instructions.

3. Luciferase activities [luminescence (relative light units/well)] should be monitored

with a POLARstar Omega plate reader (BMG Labtech) or comparable plate reader.

Technical Notes: o For detachment of cells use TrypLE Express Enzyme, no Phenol Red (1X) (Invitrogen)

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o F9 RARE-LacZ Stable Cells should be passaged frequently and should not reach more

than 80-90% confluency to prevent differentiation o For better transfection efficiency: 1) briefly vortex the Lipofectamine before use and

2) mix the Lipofectamine 2000 and plasmids in a flat dish, rather than a microcentrifuge

tube, for optimal lipid formation o For LC-MS/MS-based quantitation, do not use enzyme-based detachment procedures

(e.g., trypsin). Remove culture media and gently use a cell scraper to detach cells. o All experiments should be conducted under yellow light to prevent light-induced

isomerization and degradation of retinoids. o Glass pipettes and glass tubes should always be used when handling retinoids. o Retinoid samples can be stored in DMSO or DMF at 5-10mM at -80 C, but long term

storage at any temperature should be avoided. o The concentration of dissolved retinoids should be confirmed by measuring the

absorption of a 1000-fold dilution of the stock solution in ethanol (or hexane for more

apolar carotenoids or retinyl esters) using a UV-visual spectrophotometer and deriving

the concentration via the Lambert-Beer law Aλ = (ε)(c) for a pathlength L = 1cm (as

described in Protocol I, Part 1). In the case of all-trans-RA dissolved in ethanol, the

maximum absorption wavelength (λmax) =350nm, and the molar extinction coefficient

-1 -1 (ε max) =45,300 M cm . For other retinoids spectral values and absorption coefficients

can be found in (122) and references therein). In addition, LC-UV can be used to assess

the purity and isomerization state of various retinoid compounds employed.

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Figure A4.3. Evaluating RA reporter response in the two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels. Cells were treated with 0-50nM of all-trans retinoic acid (atRA or RA) and reporter response and RA levels were measured over time for 0-96h. (A) two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter (B) RA in cell as determined by LC-MS/MS (C) RA in media as determined by LC-MS/MS. Cell culture for (A)- (C) and reporter assay conditions for (A) described in section IV. LC-MS/MS quantitation for (B) and (C) as described in section I and in Jones et al. Error bars represent standard deviation (n=3).

Figure A4.4. Evaluating RA reporter response in the two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels produced from retinol treatment. Cells were treated with 0-10nM of holoRBP4-Retinol (RBP4-ROL) followed by quantification of reporter response and all-trans retinoic acid (RA) levels over time for 0-96h. (A) two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter (B) RA in cell as determined by LC- MS/MS (C) RA in media as determined by LC-MS/MS. Cell culture for (A)-(C) and reporter assay conditions for (A) described in section IV. Retinol treatment and LC-MS/MS quantitation for (B) and (C) as described in section I and in Jones et al. Error bars represent standard deviation (n=3).

5.4 Analysis

Evaluating RA reporter response in the two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter as compared to RA levels:

Figure A4.3, shows an example of data obtained from the two-hybrid Gal4-RAR;UAS-tk-

Gaussia luciferase reporter in HEK293 cells in comparison to RA determined by LC-

MS/MS-based detection. Cells treated with varying concentrations of RA (0.5, 5, and 50

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nM RA) and reporter response via luciferase as well as RA levels were assessed over time up to 96h. Figure A4.3A, the luciferase levels in the two-hybrid Gal4-RAR;UAS-tk-

Gaussia luciferase reporter showed an increase in signal starting at around 12 hours with sustained signal through 96h. Figures A4.3B and A4.3C show RA levels in the cell and media, respectively. Figure A4.3B and A4.3C show a sustained, concentration dependent level of RA through 48 hours before declining, likely due to metabolism of RA.

Figure A4.4, shows an example of the two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter in HEK293 cells as used to evaluate reporter response from RA produced from (added) retinol substrate using the protocol described in section 2. Similarly to Figure A4.3A, the luciferase levels in the two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter assay showed an increase in signal starting at around 12 hours and continuing through 96h. Figures A4.4B and A4.4C show the RA levels in the cell and media, respectively. Figure A4.4B and A4.4C showed an increase in RA produced up until

12h with sustained, concentration dependent level of RA through 72 hours in both cells and media. Media maintains similar levels of RA at 96h, whereas cellular levels of RA decline at 96h, likely due to metabolism of RA.

5.5 Pros and cons

Considerations for various cellular assays:

Each of the cellular assays has advantages and limitations to be considered when choosing an experimental approach as Summarized in Table A4.2. RA Extraction and

Quantification via LC-MS/MS (part 3 of section 2.2 ‘Protocols’) offers the advantage of direct, absolute quantitation of RA that is applicable to cell lines and tissues. The quantitation of RA has temporal accuracy and represents the levels of RA that are present

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at the time of collection (Figure A4.5). Results are very reproducible as documented in methodology publications (126, 127, 129) and reproducibility representative cellular assay data are shown in Figure 7. Limitations of this approach include more experimental effort than reporter assays and the requirement for expensive, specialized instrumentation. For tissue quantitation in embryo, LC-MS/MS approaches do not provide intact spatial visualization, and measurement of specific spatial regions is limited by the ability to dissect those regions. Additionally, LC-MS/MS approaches have minimum tissue requirements that may necessitate pooling. The F9 RARE-LacZ Stable Cell Line β-Galactosidase

Reporter (section 4) offers the advantage of rapid results with no transfection required and reproducible results for comparable conditions. Limitations include the possibility that cells can differentiate if not maintained properly and the requirement for cell lysis. The F9

RARE-LacZ stable cell line β-galactosidase reporter is also limited by a response that saturates at moderate levels of RA (Figure A4.2A), is non-quantitative, and displays a temporal delay post increase in RA accompanied by a transient signal response (Figure

A4.5). The two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter (section 5) has the advantage that it can be applied to any cell line amenable to transfection and does not require cell lysis. The reporter offers rapid results and remains on once activated (illustrated in Figure A4.3, Figure A4.5) thereby eliminating concerns of a transient response as is encountered in the F9 RARE-LacZ cell line. Results are very reproducible as shown in

Figure A4.6. Limitations of the two-hybrid Gal4-RAR;UAS-tk-Gaussia luciferase reporter include transfection difficulty in some cell lines, a non-quantitative response, and a temporal delay exposure to RA (Figure A4.5).

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For RA production evaluation, similar to standard enzyme activity assays, the timepoint and concentration ranges for the retinoid substrate of interest should first be determined by performing a time-course experiment and a concentration-course experiment to determine conditions within the linear range (122, 489).

F9 RARE-LacZ Stable Cell two-hybrid Gal4-RAR;UAS-tk- RA Extraction and Line β-Galactosidase Gaussia luciferase reporter Quantification via LC-MS/MS Reporter PROS PROS PROS -No transfection required -Can be used in multiple cell lines -Applicable to cell lines and tissues -Quick results (yes/no) -Reporter stays on once activated -Direct, absolute RA quantification -Very reproducible -Does not require cell lysis -Temporal accuracy, represent levels at -Fastest results (yes/no) the time of collection -Very reproducible -Very reproducible CONS CONS CONS -Cells can differentiate if not -Depending on cell line, transfection -More time intensive maintained properly can be difficult -Expensive, specialized -Requires cell lysis -Non-quantitative instrumentation required -Reporter response saturates at -Temporal delay moderate levels of RA - Non-quantiative -Temporal delay then transient signal

Table A4.2. Comparison of Different Reporters and Quantification Methods for Cellular Systems

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Figure A4.5. Comparison of temporal responses of different cellular assays to determine RA levels or RA signaling. (A) RA reporter response after 50nM RA treatment in the F9 RARE-LacZ stable cell line via β-Galactosidase reporter assay and RA levels measured via LC-MS/MS (B) RA reporter response after 50 nM RA treatment in the two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels (C) RA reporter response from RA produced after 10 µM RBP4-ROL treatment in the two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter in HEK293 cells as compared to RA levels. Reporter assays for (A) as in section III, reporter assays for (B) and (C) as in section IV. LC-MS/MS quantitation as described in section I and in Jones et al. Error bars represent standard deviation (n=3).

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Figure A4.6. Comparison of representative reproducibility between the two-hybrid Gal4- RAR;UAS-tk-Gaussia luciferase reporter in HEK293 cells as compared to RA levels. Two sets of cells were treated with 5nM of all-trans retinoic acid (atRA or RA) and reporter response and RA levels were measured over time for 0-96h. (A) two-hybrid Gal4-RAR;UAS-tk-Gaussia Luciferase Reporter (B) RA in cell as determined by LC-MS/MS (C) RA in media as determined by LC-MS/MS. Cell culture for (A)-(C) and reporter assay conditions for (A) described in section IV. LC-MS/MS quantitation for (B) and (C) as described in section I and in Jones et al. Error bars represent standard deviation (n=3).

6. IN SITU HYBRIDIZATION CAN BE USED TO VISUALIZE GENE ACTIVITY

OF VITAMIN A SIGNALING COMPONENTS

The ability to accurately detect gene activity of components from the vitamin A pathway allows for the study of its role in development and disease. This section describes the use of in situ hybridization (ISH) as a sensitive method to identify spatiotemporal gene activity by localizing mRNA transcripts from a gene of interest (Figure A4.7). To do this,

ISH utilizes anti-sense RNA probes of varying length that are synthesized with nucleotides that contain a digoxigenin (DIG) moiety that can be bound by an enzyme linked anti-DIG antibody. Transcripts that are bound by the labeled riboprobe and antibody may be detected by a colorimetric reaction, whereby an NBT/BCIP substrate solution is metabolized to create a purple reaction product. Following the reaction, visualization of the bound mRNA transcripts can be detected in the regions of the purple color development and imaged by light microscopy.

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Figure A4.7. Methods to identify components of vitamin A metabolism and RA synthesis. (A- C) Visualizing vitamin A metabolizing enzymes by in situ hybridization. (A) Raldh2 is expressed in the whole embryo at E9.5 in the foregut and caudal somites. Rdh10 (B) is expressed at E9.5 in the regions of the gut, forelimb and somites. In a transverse section (C), Rdh10 activity can be observed within the somites and forelimb. (D-F) The RARE-LacZ reporter mouse contains a RA response element under the control of a minimal promoter and is used to visualize RA signaling. LacZ staining of an E13.5 embryo (D) demonstrates the spatiotemporal activity of RA signaling throughout the head and trunk including the eye, neural tube, and limbs. High levels of RA signaling are present in many organs including the gut at E17.5 (E) as well as in tissue around the optic vesicle and telencephalon as evident in a transverse section of an E10.5 embryo (F). Immunostaining for Rdh10, a component of vitamin A metabolism, reveals expression the dorsal root ganglia, neural tube and motor nerve projection in a transverse section (G) and inset (G’) of an E10.5 embryo. Abbreviations: (s) somite; (nt) neural tube; (fl) forelimb; (ov) optic vesicle; (t) telencephalon; (drg) dorsal root ganglia.

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6.1 Reagents

1. 4% Paraformaldehyde in PBS

Microwave to boiling 100 mL of DEPC-PBS and then add 4 g of paraformaldehyde

powder (toxic) and stir to dissolve in a fume hood.

2. PBT (0.1% Triton in PBS)

1 mL Triton X-100 in 1 L DEPC-PBS

3. Hybridization Buffer (to make 50 mL)

25.0 mL 100% formamide (deionized if available)

12.5 mL 20X SSC

0.5 mL EDTA

0.5 mL 10% Triton X-100

0.5 mL 10% Chaps

50.0 l 50 mg/mL Heparin

50.0 mg Yeast torula-RNA

1.0 g Boehringer blocking powder

Make up to 50 mL with DEPC-H2O in a 50 mL Falcon tube and store at -20C

4. KTBT (to make 50 mL)

2.5 mL 1 M Tris/HCl, pH 7.5

7.5 mL 1 M NaCl

0.5 mL 1 M KCl

0.5 mL Triton X-100

39.0 mL DEPC-H2O

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5. Alkaline Phosphatase Buffer (to make 5 mL)

500 l 1 M Tris/HCl, pH 9.5

500 l 1 M NaCl

250 l 1 M MgCl2

5.0 l Tween20

3.75 mL DEPC-H2O

6. MABT (to make 50 mL)

10 mL 500 mM Maleic acid, pH 7.5 (adjust pH with NaOH)

7.5 mL 1M NaCl

0.5 mL Triton X-100

Make up to 50 mL with DEPC-H2O

Note: All stock solutions should be DEPC treated and autoclaved or prepared with DEPC-

H2O.

6.2 Protocols

RNA probe synthesis

1. Mix the following at room temperature:

Sterile distilled water (DEPC-H2O) 11.5 µl 5X transcription buffer 5.0 µl 100mM DTT 2.5 µl DIG 10X nucleotide mix 2.5 µl Linearized plasmid (1 µg/µl) 1.5 µl Rnasin ribonuclease inhibitor 0.5 µl Polymerase (SP6, T3 or T7) 1.5 µl Total 25µl

2. Incubate at 37C for 2 hours up to 6 hours.

3. Remove 1 µl aliquot and run on 1% TAE gel to check synthesis. Expect to see RNA

band 10-fold more intense than plasmid band, suggesting 10-15 µg probe.

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4. Add 2 µl of DNAse1 (ribonuclease free) and incubate at 37C for 15 minutes.

5. Add:

50 µl dH2O

25 µl 10 M ammonium acetate

200 µl 100% ethanol

6. Mix and leave on dry ice for 30 minutes or store at -80C overnight.

7. Spin in centrifuge at 4C for 20 minutes at 13000 to 15000 rpm.

8. Wash pellet in 50 µl of 70% ethanol and spin at 4C for 5 minutes at 13000 to 15000

rpm.

9. Air dry pellet for 5 to 10 minutes until obvious traces of ethanol have evaporated.

10. Re-dissolve pellet in 50 µl hybridization solution and store at -20C. If a higher

concentration of probe is needed the pellet may be resuspended in 30 µl of

hybridization solution.

In situ hybridization staining method

1. Dissect embryos in DEPC-PBS and fix in 4% paraformaldehyde for 2 hours to

overnight (use scintillation vials).

2. Wash embryos in PBT at room temperature for 10 minutes.

3. Dehydrate the embryos through a graded series of methanol diluted in PBT: wash in

25% methanol, 50% methanol, 75% methanol and 100% methanol for 10 minutes each.

4. Embryos can be stored at -20C up to several weeks at this stage.

5. Rehydrate the embryos through a graded series of methanol diluted in PBT: wash in

75% methanol, 50% methanol, 25% methanol for 10 minutes each.

6. Wash in PBT for 5 minutes at room temperature.

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7. Incubate in 10 g/mL proteinase K (diluted in PBT) for 5 to 10 minutes at room

temperature. Incubation time will vary depending on the embryo’s stage.

Incubation time by embryo stage:

E6.5: 4 minutes

E7.5: 4-5 minutes

E8.5: 6 minutes

E9.5: 10 minutes

E10.5: 15 minutes

8. Stop the proteinase K reaction by washing with 2 mg/mL glycine (diluted in PBT) for

5 minutes at room temperature (make the same day of use).

9. Wash for 5 minutes in PBT at room temperature.

10. Re-fix the embryos in 4% paraformaldehyde/0.25% glutaraldehyde for 20 minutes at

4C.

11. Wash for 10 minutes in PBT at room temperature.

12. Transfer the embryos to 2 mL Eppendorf tube with a round bottom (up to 10 embryos

can be processed in a single tube).

13. Incubate embryos for at least 1.5 hours in 1-2 mL of pre-warmed hybridization buffer

at 62C to 70C.

14. Incubate embryos with 2 l of RNA probe per 1 mL of hybridization buffer at 62C to

70C overnight in hybridization oven (1 mL of buffer is enough for 10 mouse embryos

at E10.5).

15. Wash embryos twice in 2 mL of 2xSSC/0.1% chaps for 45 minutes at 62C.

16. Wash embryos in 2 mL of 0.2xSSC/0.1% chaps for 30 minutes at 62C.

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17. Wash in KTBT for 5 minutes at room temperature.

18. Incubate the embryos in 2 mL of 20% goat serum (or lamb serum) in KTBT for at least

1 to 1.5 hours at room temperature with continual rocking.

19. Replace blocking solution with fresh 20% goat serum in KTBT. Add 2 l of DIG-

alkaline phosphatase antibody and incubate at 4C overnight with continual rocking.

20. Rinse the embryos at least twice in KTBT.

21. Wash the embryos between 4 to 5 times in KTBT for 1 hour at room temperature with

continual rocking.

22. Replace with 2 mL of fresh KTBT and wash overnight at 4C with continual rocking.

23. In the morning, wash the embryos at least twice with KTBT for a combined time of 30

minutes at 4C.

24. Wash the embryos in 1 mL of alkaline phosphatase buffer for 10 minutes at room

temperature with continual rocking.

25. Add 3.375 l of NBT (100mg/ml in DMF) and 3.5 l of BCIP (50mg/ml in DMF)

directly to the embryos in alkaline phosphatase buffer with shaking at room

temperature in the dark (wrap the Eppendorf tube in foil or place in a covered

container).

26. Stop the reaction once the desired color intensity is achieved by fixing the embryos in

4% paraformaldehyde. This can take from 15 minutes to overnight, however 1 to 2

hours is more common. Continual observation of the color development is not

advisable as the background will increase.

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6.3 Safety considerations and standards

Paraformaldehyde is a toxic chemical and extreme caution should be used when handling.

Be sure to always use proper personal protective equipment and handle under a fume hood.

6.4 Related techniques

In addition to the technique described above, other RNA in situ hybridization assays are available that include RNAscope, ViewRNA and SABER-FISH. An advantage of these techniques is their ability to use fluorescent probes which provide a multiplexed approach to characterize the activity of many genes within the same sample. The use of fluorescence additionally provides an option to quantify gene expression (497-499).

6.5 Alternative methods/procedures

Alternative post-hybridization washes in MABT:

After hybridizing the embryos overnight at 62C in step 14, wash the embryos in a 1:1.5 mix of hybridization buffer and MABT (described in section 2.1 ‘Materials, equipment and reagents’) at 65C for 1 hour. Then wash the embryos for 30 minutes at 65C in MABT.

For steps 17 through 23 replace KTBT with MABT.

Alternative color development:

The color development described in step 25 of the protocol may also be carried out by using BMPurple solution in the place of NBT/BCIP. To do this, pre-warm BMPurple to

37C. Spin the tubes for 15-20 seconds in micro-centrifuge to pellet precipitate. Place supernatant onto embryos that have already incubated in alkaline phosphatase buffer. Be sure to protect from light while color develops.

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6.6 Troubleshooting & Optimization

Problem Solution Riboprobes with consistently high Wash the embryos in MABT instead of background staining SSC/SDS as described in section 6.5 ‘Alternative Methods/Procedures’. Riboprobes with consistently high To help alleviate probe trapping in the background staining from probe trapping head in embryos at E9.5 and older, it is beneficial to poke the heads of the embryos during harvest to help clear riboprobe during washes. Poor staining quality from incomplete To increase riboprobe penetration in riboprobe penetration whole embryos it is recommended to test increasing the incubation times with proteinase K listed in step 7. Poor staining quality from incomplete To optimize riboprobe hybridization, the hybridization of the riboprobe temperature of hybridization in step 14 may be increased between 62C to 70C. Table A4.3. Troubleshooting for Common Problems When Using In Situ Hybridization

6.7 Summary

In situ hybridization is a sensitive method to detect gene activity by localizing mRNA transcripts within a sample. Embryos are first harvested and fixed overnight in 4% PFA (it is important all solutions are DEPC treated to prevent rnase contamination). The samples are then permeabilized using proteinase K, re-fixed with 4% PFA/0.25% glutaraldehyde and then hybridized with riboprobe overnight between 62C to 70C. The following day, samples are processed through a series of post-hybridization washes, blocked in a 20% goat serum solution and incubated at 4C overnight with an anti-DIG-Alkaline Phosphatase antibody. Samples then undergo a series of washes and begin a colorimetric reaction in an

NBT/BCIP substrate solution. Once color development is complete samples are post-fixed in 4% PFA and can be imaged and/or stored at 4C.

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7. DETECTION OF RA SIGNALING USING A β-GALACTOSIDASE ASSAY

WITH X-GAL

Retinoic acid signaling can be visualized in vivo using transgenic mouse lines containing a LacZ reporter. The method described in this section outlines the use of the transgenic RARE-LacZ mouse line to visualize retinoic acid (RA) activity by β-

Galactosidase staining with X-gal (figure A4.7). To do this, the RARE-LacZ mouse line possesses a transgene with an RA response element (RARE) that drives expression of β-

Galactosidase by RA binding to RA receptors on the RARE sequence (500). The addition of the X-gal substrate, detailed in the below protocol, creates a purple product in the regions of RA activity, which provides an effective means to visualize the spatiotemporal activity of RA signaling. Further, other LacZ transgenic mouse lines, such as Rdh10βgeo (100), may be used to analyze the spatiotemporal activity of other components of the vitamin A pathway.

7.1 Reagents

1. Tissue Fixative: 0.2%glutalaldehyde/2%formalin

2. Wash Solution (to make 500 mL)

0.1 mL NP40 in 500 mL PBS

3. Stain Solution (to make 500 mL)

5.0 mL 0.5M K3Fe(CN)6

5.0 mL 0.5M K4Fe(CN)6-3H2O

1.0 mL 1.0M MgCl2

5.0 mL 1% Sodium deoxycholate

make up to 500 mL with Wash Solution and store in dark at 4C

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4. Stock Substrate

40mg/mL X-gal dissolved in DMF

Store in dark at 4C

5. Working Stain Solution: add 1 mL of X-gal stock to 39 mL of stain solution.

store at 4C in the dark

7.2 Protocol

1. Wash embryos in PBS at room temperature.

2. Fix embryos in cold 0.2%glutalaldehyde/2%formalin for 30 to 90 minutes at 4C.

Fixation time depends on the embryo stage.

Fixation time by embryo stage:

E7-8: 15 minutes

E9-10: 30 minutes

E11-12: 1 hour

E13 and older: 1.5 hours

3. Wash embryos three times for 15 minutes each in wash solution at room temperature

with no rocking.

4. While the samples are washing, warm the stain solution at 37C in the dark. Then add

the X-gal substrate to the pre-warmed stain solution and return to the dark at 37C until

ready to begin step 5.

5. Replace the wash solution with the pre-warmed working stain solution and incubate in

the dark at 37C for up to 36 hours. Check the development periodically to determine

when the stain is complete.

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6. After staining, rinse the embryos thoroughly in PBS and store long-term in PBS/0.01%

sodium azide at 4C.

7.3 Alternative methods/procedures

Alternatives to using X-gal in the stain solution in step 4 include Salmon-gal with

tetrazolium salts, or S-gal with TNBT, which may provide a faster and more sensitive

reaction in mouse embryos. It has been noted in comparative studies that Salmon-gal or S-

gal were capable of detecting β-galactosidase activity with higher sensitivity than X-gal

(501, 502).

7.4 Summary

The β-Galactosidase assay with X-gal is a straightforward method that can be used to detect

gene activity of components of the vitamin A pathway by staining embryos from transgenic

mouse lines, such as RARE-LacZ and Rdh10βgeo (77, 100). In the six-step protocol,

embryos are harvested and then fixed for a varying length of time depending on embryo

stage. Once fixed, samples are washed and then incubated at 37C in the dark with the

working stain solution containing the X-gal substrate for up to 36 hours. When staining is

complete the embryos can be imaged and/or stored at 4C with sodium azide.

8. IMMUNOSTAINING CAN BE USED TO VISUALIZE PROTEIN ACTIVITY OF

VITAMIN A SIGNALING COMPONENTS

An alternative method to study the vitamin A pathway is to detect protein activity

of vitamin A signaling components. The immunostaining technique described in this

section is a method to identify the spatiotemporal activity of proteins that are essential in

the vitamin A pathway, such as the enzyme Rdh10 (Figure A4.7). To do this, either whole

embryo or sections are fixed to preserve the protein of interest and then permeabilized to

212

allow penetration and binding of a primary antibody to the protein. Secondary antibodies, conjugated with either an enzyme or fluorophore, are then used to bind the primary antibody. Localization of the bound protein can be achieved by either a colorimetric reaction with an enzyme conjugated secondary antibody, or by fluorescent imaging of antibodies associated with a fluorophore. Detection by either method allows for the ability to visualize the spatiotemporal activity of the protein wherever it is bound within the sample.

8.1 Reagents

1. Dent’s Bleach (to make 50 mL)

33.3 mL 100% MeOH

8.3 mL DMSO

8.3 mL 30% H202

2. 4% Paraformaldehyde in PBS

Microwave to boiling 100 mL of PBS (DEPC treated) and then add 4 g of

paraformaldehyde powder (toxic) and stir to dissolve in a fume hood.

3. PBT (0.1% Triton in PBS): 1 mL Triton X-100 in 1 L PBS

4. BABB clearing solution (to make 50ml)

16.7 mL Benzyl alcohol

33.3 mL Benzyl benzoate

8.2 Protocols

Section protocol

1. Section whole embryos by cryosectioning at 10 µm (slides can be stored at -20C).

2. Let slides defrost for a few minutes at room temperature.

213

3. Heat-dry with a hair dryer or slide warmer for about 15-20 seconds on the back of each

slide.

4. Wash in PBT for 10 minutes.

5. Prepare a slide holder for staining. Place a piece of tissue in each slot of that container

that fits perfectly and soak with water.

6. Block the sections in 3% BSA (diluted in PBT) for 30 minutes at room temperature

(add about 200 l of blocking solution on each slide and cover with a paraffin strip in

the slide holder container).

7. Remove excess blocking solution and add about 150 l of the primary antibody diluted

in 3% BSA.

8. Cover each slide with a paraffin strip after adding the antibody solution to prevent the

slides becoming dry.

9. Seal the container with a paraffin strip and store at 4C overnight.

10. Wash the sections 3 times for 5 minutes with PBT at room temperature.

11. Add 150 l of the secondary antibody (typically a 1:500 dilution) and cover with a

paraffin strip.

12. Incubate at room temperature for 1 hour.

13. Wash the sections 3 times for 5 minutes with PBT at room temperature.

14. Add DAPI at a 1:1000 dilution and incubate for 20 minutes at room temperature

(alternatively, DAPI can be added with the secondary antibody. Avoid co-incubation

if doing TUNEL or using a nuclear antibody).

15. Wash sections 3 times for 5 minutes with PBT at room temperature.

214

16. Use vectashield to mount the slides (you can skip adding DAPI in the previous step

and use vectashield with DAPI instead).

17. Store the slides in the dark at 4C for long-term storage.

Whole embryo protocol

1. Incubate embryos in Dent’s bleach for 2 hours at room temperature (This is a critical

step that promotes antibody penetration and quenches auto-fluorescence).

2. Remove Dent’s bleach and replace with 100% methanol.

3. Equilibrate through a graded series of methanol diluted in PBT: wash in 100%

methanol, 75% methanol, 50% methanol and 25% methanol for 10 minutes each (the

tissue will become sticky during this procedure so be aware not to suck it up into

pipettes etc.).

4. Wash embryos in PBT for 10 minutes.

5. Block in 3% BSA (diluted in PBT) for two hours at room temperature.

6. Apply the primary antibody diluted in 3% BSA and incubate overnight at 4C with

gentle rocking (dilution varies per antibody, determine empirically for each).

7. Wash 5 times for 1 hour with PBT.

8. Apply the secondary antibody diluted in 3% BSA and incubate overnight at 4C with

gentle rocking in the dark (wrap the Eppendorf tube in foil or place in a covered

container).

9. Wash 3 times for 20 minutes with PBT.

10. Incubate 20 minutes in PBS with DAPI at a 1:1000 dilution (for small tissues 20

minutes DAPI incubation is enough. To completely stain a whole E10.5 embryo,

incubate overnight at 4C with gentle rocking).

215

11. Rinse embryos in PBT.

12. Dehydrate the embryos through a graded series of methanol diluted in PBT: wash in

25% methanol, 50% methanol, 75% methanol and 100% methanol for 10 minutes

each.

13. For long term storage, the tissue can be stored for weeks or months at 4C without loss

of fluorescent intensity.

8.3 Safety considerations and standards

Paraformaldehyde is a toxic chemical and extreme caution should be used when handling.

Be sure to always use proper personal protective equipment and handle under a fume hood.

If using the alternative procedure in section 8.3 to clear whole embryos for imaging, it is important to use extra caution when handling benzyle alcohol-benzyl benzoate (BABB) as it is a powerful organic solvent that dissolves most plastics. Be sure to use and store BABB in a glass container

8.4 Alternative methods/procedures

Prior to imaging, clearing stained embryos can help visualize internal structures in larger embryos. This can be achieved with benzyl alcohol-benzyl benzoate (BABB) by adding 1 part Benzyl alcohol to 2 parts Benzyl benzoate. Incubating the embryos for 10 minutes should be enough to render the tissue almost completely transparent, but also fragile.

Embryos can be imaged using a glass depression slide with a ring of silicon grease to hold a coverslip in place. A Teflon ring can be used between the grease ring and coverslip if additional space is needed for the sample. After imaging, the embryos can be transferred back to 100% methanol for long term storage at 4C.

216

Problem Solution High levels of auto-fluorescence Test increasing incubation time with Dents bleach to help reduce levels of auto-fluorescence. Additionally, the head and heart region can be poked for whole embryos at E9.5 and older to help prevent trapping by allowing the antibody to clear during washing steps. Consistently high levels of background The blocking time in step 5 of the ‘whole staining embryo protocol’ can be increased to help reduce high levels of background. Additionally, the number and duration of washes can be increased in step 7 after incubation with the primary antibody. Poor staining quality from incomplete Test increasing incubation time with penetration of the antibody Dent’s bleach to help increase antibody penetration in whole embryos.

Table A4.4. Troubleshooting for Common Problems When Immunostaining

8.6 Summary

Immunostaining can be used to detect protein activity within the vitamin A pathway by first harvesting samples and then fixing overnight in 4% PFA. Following fixation, the samples can either be sectioned or used for whole embryo staining. If using whole embryos, incubation with Dent’s bleach helps to promote antibody penetration and quench auto- fluorescence (503). Both sections and whole embryos are blocked in a 3% BSA solution and incubated overnight with primary antibody followed by secondary antibody incubation the next day. Samples are then ready to be imaged and whole embryos can be cleared using benzyl alcohol-benzyl benzoate (BABB) to better visualize internal structures (section 4.3).

217

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