REGULATION OF NOTCH SIGNALING BY γ-SECRETASE
PROTEIN MODULATORS
A Dissertation
Presented to the Faculty of the Weill Cornell Graduate School
of Medical Sciences
in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
by
Alissa H. Brandes
August 2016
©2016 Alissa H. Brandes
REGULATION OF NOTCH SIGNALING BY γ-SECRETASE
PROTEIN MODULATORS
Alissa H. Brandes
Cornell University 2016
The Notch pathway regulates many cellular processes, including development and stem and progenitor cell self-renewal and differentiation. Regulation of Notch signaling is tightly controlled and aberrant Notch activity has pathologic consequences in a wide array of diseases, including cancer and kidney disease. Notch signaling is regulated by a signaling paradigm deemed regulated intramembrane proteolysis (RIP), during which protein substrates undergo ectodomain shedding, followed by cleavage within the lipid bilayer by the γ-secretase protease complex to release intra- and extra-cellular signaling peptides, such as the transcription factor Notch intracellular domain (NICD).
γ-Secretase has many substrates and, while the exact mechanisms that regulate its activity level and substrate specificity are still unclear, many proteins have been shown to directly interact with the complex to either enhance or inhibit its cleavage activity.
In addition, only a fraction of cellular steady-state γ-secretase complexes are catalytically active and the exact function of the inactive complexes remains unknown.
Can RIP be regulated by a tissue- and context-specific modulation of γ-secretase activity? We hypothesize that Notch signaling can be regulated in response to biological environmental stimuli by interaction of γ-secretase with distinct, cell type-specific protein modulators to dynamically regulate the equilibrium between active and inactive complexes. I have addressed this research question with two projects focused on the discovery of novel Notch regulators in different tissue and disease models.
Hypoxia contributes to the metastatic progression of breast cancer by promoting
Notch signaling. We have discovered that the master regulator of hypoxia, Hif-1α, stimulates γ-secretase activity by directly interacting with the γ-secretase complex in a novel, non-canonical mechanism. The breast cancer stem cell (BCSC) population has been proposed to mediate Notch pro-metastatic effects. We hypothesize that Hif-1α- mediated activation γ-secretase/Notch is critical for the regulation of BCSCs, which we have investigated using mammospheres as a model.
Our lab has identified a putative, novel endogenous γ-secretase inhibitor in the kidney, gamma-glutamyltransferase (GGT). Notch signaling is critical for kidney development, but is pathogenic if activated in adult kidneys. We hypothesize that GGT regulation of γ-secretase activity acts as a mechanism to repress Notch signaling after kidney development. In this study, we have investigated the mechanism by which GGT inhibits γ-secretase activity in biochemical assays and evaluated if GGT regulates Notch signaling in a biological setting.
BIOGRAPHICAL SKETCH
Alissa H. Brandes was born on a snowy night in Portland, Oregon. Soon after, she migrated with her family to Northern California, eventually settling in the city of San
Jose. Alissa first fell in love with science during her high school career at Leland High
School in San Jose, CA, when her junior year biology teacher opened her eyes to the scientific method and the molecular mechanisms underpinning life. After high school graduation, Alissa spent her first two years of college at San Jose State University where she enrolled as a Chemistry major.
In her junior year of college, Alissa transferred to attend the University of
California, Berkeley (UC Berkeley). During the transition, she switched to become a
Chemical Biology major because she wanted to shift a more biology-focused field, a move that has continued throughout her career. At UC Berkeley, Alissa performed research in the lab of Dr. Judith Klinman. In her undergraduate research, Alissa utilized novel chemical biology-based techniques to study a unique, autocatalytic reaction mechanism of a copper amine oxidase enzyme and developed a foundation in laboratory skills, along with the ability to perform hypothesis-driven experiments. In 2008, Alissa graduated with Honor and B.S. in Chemical Biology from UC Berkeley.
After graduation, Alissa worked for two years as a Research Associate at
University of California, San Francisco (UCSF). She studied a novel MRI-based imaging technology, hyperpolarized [1-13C]pyruvate, as a tumor biomarker, which contributed to groundwork for current clinical trials to metabolically image prostate cancer patients. In her two year tenure at UCSF, Alissa published 3 peer-reviewed papers (including 1 first-author) & was selected to give a talk at an the ISMRM
iii conference in Stockholm, Sweden in May 2010.
In September of 2010, Alissa ventured cross-country to enter the Pharmacology PhD program at Weill Cornell Graduate School of Biomedical Sciences in New York City. In the summer of 2011, Alissa joined the lab of Dr. Yueming Li at Memorial Sloan
Kettering Cancer Center for her thesis research. Alissa was awarded the Ruth L.
Kirchstein Predoctoral Fellowship (F31) from the National Institute on Aging in 2013 for a grant entitled: “Regulation of γ-Secretase by Substrate Inhibitory Domains.” Over the past 5 ½ years, Alissa’s research has investigated the interaction of Hif-1α and γ- secretase during hypoxia-induced breast cancer metastasis and worked to elucidate the molecular mechanisms that describe how γ-secretase inhibitors target tumor-initiating cells.
iv ACKNOWLEDGEMENTS
The completion of my thesis was not a solo endeavor, but came as a result of the support of many colleagues, friends, and family who have given me invaluable support and guidance over the past 6 years and beyond.
First off, I have to thank my thesis mentor, Dr. Yumeing Li. He has been an amazing mentor during my time here at Cornell. I am very lucky to have had a mentor who is willing to invest as much time as he does to help his students and who genuinely cares about his students’ well-being. His continuous questioning of “why do you think that?” that began as soon as I started lab (along with his occasional “out there” ideas) have shaped me into the critical, inquisitive and creative scientist that I have become today. He has also been a great friend to talk to when stuck working long weekends in lab and I am especially grateful for the positive lab environment his personality has fostered.
I want to give a very big thanks to my thesis committee members, Dr. Lorraine
Gudas and Dr. Michael Kharas. I really appreciate the time and effort they took to give me critical advice during my committee meetings. Their suggestions and insight has really helped to move my project along over the past few years and I am forever grateful for that.
I also could not have done any of this without all the help I have gotten, both technically and morally, from all the other Li Lab members throughout the years. I have to thank the previous lab members (Dr. Christina Crump, Dr. Deming Chau, Dr. Jennifer
Villa and Suita Castro) who were kind enough to show me the ropes when I first joined the lab. I also have to thank all my peer lab members (Courtney Alexander, Natalya
v Gerstik, Courtney Carroll, Chelsea Paresi, and most especially, my lab twin, Dr. Danica
Chiu) who have always there commiserate or go get a coffee (or margarita) with when your experiment fails for the fourth time on a Saturday night. I don’t think I could have made it through so many long hours in lab without their support. I also want to thank all the Li Lab members, past and present, for sitting through so many practice talks and taking the time to give advice in order to help me improve.
Lastly, but definitely not least, I want to thank all my friends and family who have given me undying support during my PhD career. I have made some amazing, lifelong friends here at Cornell that have made the grad school experience so much the better. I want to thank my sister-from another mother, Ariel, who has always been there for me throughout the years and the good times and the bad. I also want to thank my Dad, who instilled me with a work ethic and humble demeanor that has served me well in my grad school career. My brother, Jonathan, has always been my motivation to keep going and do better and I want to thank him for just being Juanito. My fiancé, Chris, I want to thank for being a great role model. He has always inspired me to do better and I do not think I would have accomplished many of the things I have in the past few years if it wasn’t for his unwavering love and support. Most importantly, I have to thank my Mom, for just everything. Even though she isn’t here today, everything I have accomplished, everything that I have, and everything that I am is because of her.
vi TABLE OF CONTENTS
BIOGRAPHICAL SKETCH……………………………………………………………...….iii
ACKNOWLEDGEMENTS …………………………………………………………………..v
TABLE OF CONTENTS………………………………………………………………...... vii
LIST OF FIGURES ……………………………………………………………………….....ix
LIST OF TABLES………………………………………………………………………..…ixx
LIST OF ABBREVIATIONS…………………………………………………………...…..xiii
LIST OF SYMBOLS…………………………………………………………………………………………………...xvi
Chapter 1: Introduction…………………………………………………………………1 1.1 γ-Secretase and Regulated Intramembrane Proteolysis…………………...…..1 1.2 The Notch Pathway………………………………………………………...….4 1.3 Notch Signaling in Breast Cancer………………………………………...…...7 1.4 Notch Signaling in the Kidney…………………………………….…………27 1.5 Hypothesis and Thesis Overview…………………………………………….35
Chapter 2: Materials and Methods……………………………………………..……..39 2.1 Cell culture……………………………………………………..…………….39 2.2 Mammosphere Formation Assay………………………………..…………...39 2.3 Aldeflour Assay…………………………………………………..………….40 2.4 Inhibitors…………………………………………………………..…………40 2.5 γ-Secretase Activity Assay………………………………………….……….41 2.6 Western Blot and Antibodies……………………………………….………..43 2.7 Activity-based γ-Secretase Photolabeling and Affinity Capture…………….44 2.8 Transient Transfection……………………………………………….……....47 2.9 Generation of Stable Cell Lines……………………………………….……..48 2.10 Real-time Polymerase Chain Reaction (RT-PCR)…………………….……49 2.11 Microarray…………………………………………………………………..50 2.12 Nitric Oxide Assay………………………………………………………….51 2.13 Apoptosis Assay……………………………………………………………51 2.14 Immunohistochemistry……………………………………………………..52 2.15 Membrane Preparation……………………………………………………...52
vii 2.16 Purified GGT Protein……………………………………………………….53 2.17 GGT Activity Assay………………………………………………………..54 2.18 Purified γ-Secretase Complex………………………………………………54 2.19 Zebrafish Studies…………………………………………………………...55 2.20 Statistical Analysis………………………………………………………….56
Chapter 3: Non-transcriptional role of Hif-1α in breast cancer stem cells…………57 3.1 Background…………………………………………………………………..57 3.2 Results………………………………………………………………………..58 3.3 Discussion and Conclusion…………………………………………………..94
Chapter 4: GGT is an endogenous regulator of γ-secretase in the kidney………….96 4.1 Background…………………………………………………………………..96 4.2 Results………………………………………………………………………..99 4.3 Discussion and Conclusion…………………………………………………122
Chapter 5: Summary and Conclusions……………………………………………....124
Chapter 6: References………………………………………………………………...127
viii LIST OF FIGURES
CHAPTER ONE
Figure 1: Regulated intramembrane proteolysis (RIP)……………………………………1 Figure 2: The γ-secretase enzyme complex……………………………………………….2 Figure 3: The Notch signaling pathway…………………………………………………...6 Figure 4: The majority of breast cancer deaths are due to metastasis…………………….8 Figure 5: Hif-1α protein domain structure……………………………………………….11 Figure 6: The Hif-α signaling pathway…………………………………………………..13 Figure 7: NOS regulates proteins by S-nitrosylation…………………………………….15 Figure 8: Regulation of Hif-α during normoxia by NOS………………………...... 17 Figure 9: The “cancer stem cell” model…………………………………………………20 Figure 10: Breast cancer stem cell assays………………………………………...... 22 Figure 11: Notch is critical for development of proximal tubule and podocytes during kidney nephrogenesis…………………………………………………… ………………28 Figure 12: Gamma-glutamyl transferase (GGT) regulates cellular homeostasis of cysteine (Cys) and glutathione (GSH)…………………………………………………………….34
CHAPTER TWO
Figure 13: Notch-specific γ-secretase activity assay…………………………………….42 Figure 14: Peptomimetic active site probes used in γ-secretase activity based pull down assays…………………………………………………………………………………….45 Figure 15: γ-Secretase activity-based pull down assay…………………………………..46
CHAPTER THREE
Figure 16: Hypothesized model………………………………………………………….58 Figure 17: Map of Hif-1α constructs used in transient overexpression studies………….59 Figure 18: Hif-1α N-terminus is sufficient to stimulate γ-secretase activity…………….60 Figure 19: Hif-1α binds to and enhances active γ-secretase complexes when expressed during normoxia………………………………………………………………………….61 Figure 20: Hif-1α transcriptional activity is not required to stimulate γ-secretase activity in breast cancer cells……………………………………………………………………..63 Figure 21: GSI-34 prevents the change of many gene sets that are otherwise upregulated during hypoxia…………………………………………………………………………...65 Figure 22: GSI-34 prevents formation of mammospheres………………………………67 Figure 23: GSI-34 induces apoptosis in the mammosphere cell population…………….69 Figure 24: ALDH activity is increased in mammospheres………………………………70 Figure 25: γ-Secretase activity is increased in mammospheres...………………………..72 Figure 26: Expression of γ-secretase subunits is the same in adherent and mammosphere cell populations…………………………………………………………………………..72 Figure 27: The amount of active γ-secretase complex is increased in mammospheres….73 Figure 28: γ-Secretase activity is not affected by growth factor defined media……..…..74
ix Figure 29: Hif-1α, but not Hif-2α, is required for the stimulation of γ-secretase activity during hypoxia……………………………………………………………………………75 Figure 30: Expression of Hif-1α, but not Hif-2α, is increased in mammospheres………76 Figure 31: Hif-1α, but not Hif-2α, is required for mammosphere formation……………78 Figure 32: Hif-1α, but not Hif-2α, is required for stimulation of γ-secretase activity in mammospheres…………………………………………………………………………..79 Figure 33: Hif-1α transcriptional activity is not required for formation of mammospheres…………………………………………………………………………..80 Figure 34: Hif-1α transcriptional activity is not required for stimulation of γ-secretase activity in mammospheres……………………………………………………………….81 Figure 35: Hif-1α transcriptional activity is not required for activation of Notch target genes during mammosphere formation………………………………………………….82 Figure 36: γ-Secretase is activated early during mammosphere formation……………...83 Figure 37: Mammospheres express Hif-1α during normoxia……………………………85 Figure 38: Mammospheres are not hypoxic……………………………………………...86 Figure 39: Nitric oxide (NO) production is elevated in mammospheres………………...88 Figure 40: Chemical structures of NOS inhibitors used in this study……………………88 Figure 41: NOS activity is necessary for mammosphere formation……………………..89 Figure 42: NOS activity is necessary for increased Hif-1α expression and γ-secretase activity in mammospheres……………………………………………………………….90 Figure 43: Expression of iNOS and eNOS mRNA is increased in MCF-7 mammospheres…………………………………………………………………………..91 Figure 44: iNOS expression is increased in mammospheres…………………………….92 Figure 45: iNOS is required for mammosphere formation………………………………93 Figure 46: iNOS is required for activation of γ-secretase in mammospheres…………...93 Figure 47: Model of tumor-initiating cell signaling pathway……………………………94
CHAPTER FOUR
Figure 48: Kidney membrane contains an endogenous inhibitor of γ-secretase………...97 Figure 49: GGT was purified and identified as the endogenous inhibitor of γ-secretase in the kidney………………………………………………………………………………...98 Figure 50: Different sources of GGT inhibit γ-secretase in activity assay and activity- based photolabeling……………………………………………………………………...99 Figure 51: Purified kidney endogenous inhibitor fractions have GGT activity………..100 Figure 52: GGT inhibitors used in the study…………………………………………...101 Figure 53: Q-sephrose purification fraction inhibits γ-secretase from HeLa membrane in a GGT activity-dependent manner………………………………………………………..102 Figure 54: Human GGT purified from liver inhibits purified γ-secretase in a GGT activity-dependent manner……………………………………………………………...103 Figure 55: GGT does not add a glutamyl group to inhibit γ-secretase activity………...105 Figure 56: GGT structurally modifies presenilin from purified γ-secretase complex….107 Figure 57: GGT structurally modifies presenilin from purified γ-secretase……………108 Figure 58: Q-sephrose fraction structurally modifies presenilin from HeLa membrane……………………………………………………………………………….110 Figure 59: rGGT structurally modifies presenilin from HeLa membrane……………...111
x Figure 60: GGT and γ-secretase activity of Q-sephrose fraction and rGGT correlate with the structural modification of presenilin from HeLa membrane……………………….113 Figure 61: Stable shRNA knockdown of GGT in HK-2 human kidney cells………….115 Figure 62: Knockdown of GGT increases the amount of active γ-secretase complex in HK-2 cells………………………………………………………………………………116 Figure 63: GGT expression regulates γ-secretase activity in HK-2 cells………………117 Figure 64: Knockdown of GGT increases expression of Notch target genes in HK-2 cells……………………………………………………………………………………..118 Figure 65: Schematic of experiments to overexpress GGT1 in NICD reporter zebrafish embryos…………………………………………………………………………………119 Figure 66: Expression of Ubi-GGT1-AA-Tomato in zebrafish embryos reduces NICD levels……………………………………………………………………………………120 Figure 67: Expression of GGT1 mRNA in zebrafish embryos reduces NICD levels….122
CHAPTER FIVE
Figure 68: Hypothesized thesis model………………………………………………….126
xi LIST OF TABLES
CHAPTER ONE
Table 1: List of clinical trials for breast cancer involving γ-secretase inhibitors as CSC- targeting agents…………………………………………………………………………..26
xii LIST OF ABBREVIATIONS
Aβ: Amyloid-β peptide AD: Alzheimer’s disease ADAM: A disintegrin and metalloproteinase domain-containing protein ALDH: aldehyde dehydrogenase ALGS: Alagille syndrome Aph-1: Anterior pharynx defective-1 APP: Amyloid precursor protein ARNT: Aryl Hydrocarbon Receptor Nuclear Translocator BACE1: β-site APP Cleaving Enzyme 1, also known as: β-secretase BCSC: breast cancer stem cell bHLH: basic Helix-Loop-Helix CBP: Creb-binding protein CHAPSO: 3-[(3-Cholamidopropyl)dimethylammonio]-2-hydroxy-1-propanesulfonate CSC: cancer stem cell CSL: human CBF1, fly Suppressor of Hairless, worm Lag-1 C-TAD: C-terminal transactivation domain Cys: cysteine Cys-Gly: cysteinylglycine DAPT: N-[N-(3,5-Difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester DLL: Delta-like ligand DMSO: Dimethyl sulfoxide ECM: extracellular matrix EDTA: Ethylenediaminetetraacetic Acid EMT: epithelial to mesenchymal transition eNOS: endothelial NOS ERK: Extracellular signal-related kinases ESC: embryonic stem cells FACS: Fluorescence-activated cell sorting FIH: factor inhibiting HIF GFP: green fluorescence protein Glu: glutamate Gly: glycine GSAP: γ-secretase activating protein GSH: glutathione GSI: γ-secretase inhibitor GSK-3: glycogen-synthase kinase-3 GTT: γ-glutamyl-transferase HA: hydroxyapetite H2O2: hydrogen peroxide HEPES: 4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid HES: hairy/enhancer of split HEY: Hairy/enhancer-of-split related with YRPW motif protein HIF: hypoxia inducible factor
xiii HRE: hypoxia-response element HSC: Hematopoietic stem cells IC50: Half maximal inhibitory concentration ICD: Intracellular domain iNOS: inducible NOS L458: L-685,458 L-NAME: NG-nitroarginine methyl ester L-NMMA: L- NG-monomethyl arginine MAPK: mitogen-activated protein kinase MES: 2-(N-morpholino)ethanesulfonic acid MFE: mammosphere formation efficiency MMPs: Matrix Metalloproteinases MSC: mesenchymal stem cells N1-Sb1: Notch-1 (1733-1812) receptor protein Nct/NCT: Nicastrin NEXT: Notch Extracellular Truncation NICD: Notch intracellular domain NO: Nitric oxide NOS: Nitric oxide synthase nNOS: neuronal NOS N-TAD: N-terminal transactivation domain Ntn: N-terminal nucleophilc NSC: neural stem cells ODD: oxygen dependent degradation PAS: PER-ARNT-SIM PBS: Phosphate buffered saline PCR: Polymerase chain reaction Pen-2: Presenilin enhancer 2 PFA: paraformaldehyde PHD: prolyl hydroxylase domain PI3K: phosphatidylinositol 3-kinase PIPES: 1,4-piperazinediethanesulfonic acid PKM2: M2 isoform of pyruvate kinase PMSF: Phenylmethanesulfonyl fluoride pNA: p-nitroanilide PS: Presenilin PS1-CTF: Presenilin1 C-terminal fragment PS1-NTF: Presenilin1 N-terminal fragment pVHL: von Hippel‐Lindau tumor suppressor protein rGGT: recombinant human GGT1 RIP: Regulated intramembrane proteolysis RIPA: Radioimmunoprecipitation assay buffer ROS: Reactive oxygen species RT-PCR: Real-time Polymerase Chain Reaction SAD: Streptavidin donor beads Sb4 (WT-SB4): C-terminus region of APP
xiv SDS: Sodium dodecyl sulfate SDS-PAGE: SDS-polyacrylamide gel SO: superoxide TACE: tumor necrosis factor-α-converting enzyme TAP-ANPP: Tandem Affinity Purification- Aph1a, Nicastrin, Pen-2, PS1 cells Thr: threonine UBI: ubiquitin UV: Ultra-violet VEGF: vascular endothelial growth factor
xv LIST OF SYMBOLS
α: alpha β: beta γ: gamma Δ: delta μ: mu; for micro
xvi CHAPTER 1
Introduction
1.1 γ-Secretase and Regulated Intramembrane Proteolysis
In many cellular signaling pathways, transmembrane proteins play a critical role in signal transmission through the liberation of intra- and extracellular signaling peptides, a process deemed regulated intramembrane proteolysis (RIP). During RIP, Type I membrane proteins first undergo ectodomain shedding by a sheddase protease, which allows for γ-secretase to cleave the membrane-bound fragment within the lipid bilayer
Type 1 membrane Soluble substrate ectodomain Extracellular signaling peptide
Sheddase
Extracellular
Cytosol γ-Secretase
Intracellular signaling peptide (nucleus)
Figure 1: Regulated intramembrane proteolysis (RIP). During RIP, Type 1 membrane Figure 1: Regulated intramembrane proteolysis (RIP). During RIP, Type 1 membrane proteinprotein substrates areare sequentiallysequentially processed processed by by sheddase sheddase and and γ-secretase γ-secretase enzymes enzymes to to releaserelease intracellular and and extracellular extracellular signaling signaling peptides. peptides.
1 and liberate intra- and extracellular signaling peptides (Figure 1) [1]. The intracellular
signaling peptides, or ICD (intracellular domain), of some substrates will travel to the
nucleus to affect gene transcription. While the identity of the sheddase proteases varies,
γ-secretase enzyme is responsible for the intramembrane proteolysis step during RIP.
γ-Secretase is an aspartyl protease complex that mediates the signaling of numerous
membrane-bound proteins via a common pathway. The γ-secretase complex consists of
four subunits: presenilin 1 or 2 (PS1, PS2), nicastrin (NCT), presenilin enhancer 2 (Pen-
2) and anterior pharynx defective-1 (Aph-1) [2]. PS, the catalytic subunit, is activated
after insertion into the complex and subsequent endoproteolysis into N- and C-terminal
fragments (PS1-NTF and PS1-CTF), which form a heterodimer to release the catalytic
aspartyl duo [3-5]. All four subunits are necessary and sufficient for γ-secretase activity
Aph-1 Nct Pen2
PS-NTF PS-CTF
Figure 2: The γ-secretase enzyme complex. The γ-secretase enzyme requires assembly of fourFigure obligatory 2: The subunits:γ-secretase Pen2,enzyme Aph-1,complex .Nct The andγ-secretase PS. The enzyme catalytic requires subunit, assembly PS, must of four obligatory subunits: Pen2, Aph-1, Nct and PS. The catalytic subunit, PS, must undergoundergo endoproteolysis endoproteolysis into into N-terminal N-terminal and CC-terminal-terminal fragments fragments (PS1 -(PS1-NTF,NTF, PS1- PS1- CTF) inCTF) order in order to gain to gain activity activity by by releasingreleasing the the two two catalytic catalytic aspartyl aspartyl residues residues (depicted (depicted as stars).as stars).
2 and exist at a ratio of 1:1:1:1 in the active complex (Figure 2) [6-9].
RIP signaling is important in many diseases. Of the over 90-reported γ-secretase substrates [10], Notch and amyloid precursor protein (APP) are the two best characterized. γ-Secretase is responsible for the final proteolysis step in the processing of
APP to form Aβ40 and Aβ42, the two predominant species present in Alzheimer’s disease (AD) plaques. According to the “amyloid cascade hypothesis”, the accumulation of Aβ peptides in the brain triggers a pathological cascade that causes neurodegeneration and eventually leads to AD [11, 12]. Notch is an important developmental pathway that is also involved in regulation of adult stem cells; however, aberrant Notch signaling can cause tumorigenesis in a tissue and context specific manner [13]. Notch is activated by γ- secretase to release the Notch intracellular domain (NICD), a transcription factor that travels to the nucleus to affect gene transcription. This has made γ-secretase an appealing drug target in the treatment of both AD and cancer. However, the fact that γ-secretase controls processing of so many substrates has made it a challenging drug target due to the potential for off-target side effects. Indeed, Semegacestat (a pan GSI) recently failed in
Phase III clinical trials for AD, likely due to Notch signaling related side effects, such as skin tumors [14, 15] and cognitive decline [16]. The most important dose-limiting side effect seen with GSIs in clinical trials is gastrointestinal (GI) toxicity, which is due to the effects of Notch inhibition in intestinal progenitor cells [17].
Regulation of γ-secretase
3 While it could potentially aid in the development of γ-secretase inhibitors (GSIs) as therapeutics, little is known about the exact cellular processes that regulate γ-secretase activity and substrate selectivity [10]. Even though the subunits are widely expressed in many tissues, γ-secretase is active in only some, which indicates that enzymatic activity is regulated in a cellular and tissue specific context [18, 19]. Regulation can occur on multiple levels. γ-Secretase activity can be controlled by the assembly and expression of the four essential subunits, by the substrates themselves, or by interaction with non- essential modulatory subunits [20]. Several γ-secretase-interacting proteins, such as
CD147, TMP21, and γ-secretase-activating protein (GSAP), modulate γ-secretase activity and substrate specificity by associating with the complex [21-23]. The modulatory subunits can either inhibit or stimulate enzymatic activity. Additionally, multiple reports indicate that only a fraction of the steady-state γ-secretase complexes that exist in mammalian cells are catalytically active and the function of the inactive complexes remains poorly understood [24-26]. These finding suggest that interacting protein modulators may play an important role in the regulation of γ-secretase. A better understanding of the mechanisms controlling γ-secretase activity and specificity is needed in order to improve development of targeted therapies for RIP-related diseases.
1.2 The Notch Pathway
The Notch pathway is an evolutionarily conserved mechanism to control cell fate through cell-cell signaling interactions [27]. While first identified in Drosophilia melanogaster, Notch is expressed in a very wide array of species, from sea urchins to humans [28, 29]. Notch signaling is essential for neurogenesis, somite formation and
4 lymphoid formation during vertebrate development and also plays an important role in cell fate decisions of adult stems cells, such maintaining hematopoietic stems cells via control of self-renewal and differentiation [29, 30]. The exact role of Notch signaling, during both development and in mature organisms, is complex and its function can widely vary between different tissues and cellular contexts. For instance, Notch signaling can either inhibit or promote differentiation depending on the organ stem or progenitor cells originate from [31] and activation of Notch can act as either an oncogene or a tumor suppressor in a tissue specific manner [32].
Notch is a 300 kDa single-pass transmembrane protein receptor that is expressed on the cell surface and receives signals from adjacent cells [28, 33, 34]. There are four isoforms of Notch in mammals, Notch 1-4 [35], which exist at the plasma membrane as a
Ca2+-dependent heterodimer [36]. Activation of Notch signaling is a multi-step sequential process (Figure 3). First, Notch receptor must bind to a ligand on the surface of an adjacent cell. Notch ligands are type I transmembrane proteins that consist of five isoforms in mammals: Jagged 1,2 and Delta-like ligands (DLL) 1,3,4 [35]. Ligand- induced activation of Notch renders it sensitive to an initial cleavage at the S2 site by extracellular proteases of the ADAM/TACE/Kuzbanian family [37-39] (Figure 3). This cleavage releases a soluble Notch ectodomain, leaving the membrane bound Notch
Extracellular Truncation (NEXT), which is activated for cleavage at S3 and S4 sites within the transmembrane domain by γ-secretase [38, 40-42]. γ-Secretase then cleaves
NEXT to release an extracellular peptide of unknown function, Nβ, and the Notch
Intracellular Domain (NICD), which is a transcription factor that then travels to the nucleus to affect gene transcription [41] (Figure 3).
5 Adjacent cell
DLL1,3,4 Jagged1,2
Notch(1-4) Nβ
TACE/ADAM (S2)! Extracellular
Cytosol γ-Secretase (S3,S4) NICD
HES1! HEY1! CSL
Figure 3: The Notch signaling pathway. The Notch receptor requires multiple steps for activation. When NICD is released, it travels to the nucleus to bind cofactors and activate transcription of target genes.
Once in the nucleus, NICD forms a complex with the DNA-binding protein, CSL
(human CBF1, fly Suppressor of Hairless, worm Lag-1), the histone acetyltransferase p300, and the co-activator, Mastermind (Mam)/Lag-3, which enables binding to specific regulatory DNA sequences [43-45] (Figure 3). Only a limited set of Notch target genes have been identified; they consist of the hairy/enhancer of split (Hes) gene family that includes the Hey subfamily of Hes [46, 47]. Hes and Hey are helix-loop-helix transcription factors that function as transcriptional repressors. Although Notch has been
6 described to affect many genes in the Hes family, the best-described Notch target genes in mammals are Hes1, Hes5, and Hey1 [47, 48].
Regulation of Notch signaling
There are multiple regulatory mechanisms that ensure tight spatial-temporal control in the level and/or duration of Notch signaling activity. Tight regulation is essential considering activation of NICD is an irreversible and very dose-sensitive process (due to lack of signal amplification) and, not surprisingly, aberrant regulation can lead to disease [49]. Notch signaling is controlled at almost every activation step. Jagged and DLL ligands can be differentially expressed, cleaved by proteases (including γ- secretase), ubiquinated, and glycosylated [50-57]. The Notch receptor is endocytosed, inhibited by Numb, and NICD is degraded via Sel10 [58-60]. On the signaling level there is contextual expression of different Notch target genes, cross-talk with other signaling pathways, and activation of CSL-independent signaling [49, 61, 62]. Quite interestingly, the only step in this process that has not been previously described to be regulated is the final cleavage of NEXT by γ-secretase to form NICD.
1.3 Notch Signaling in Breast Cancer
Breast cancer overview
7 Breast cancer is the second most common cancer among American women and it is estimated that 1 in 8 women will be diagnosed with breast cancer in her lifetime [63].
Breast cancer is also the second leading cause of cancer death among women, exceeded only by lung cancer. However, there is some good news: we are getting better at treating it. According to statistics from the American Cancer Society, while the incidence has remained steady, the breast cancer death rate has been on a steady decline over the past
25 years (Figure 4A). When this data is examined more closely, however, this benefit is not evenly distributed among patients. Patients diagnosed with Localized or Regional
Stage breast cancers have a 5-year relative survival rate of nearly 100%, while for
A Trends in Female Breast Cancer Death Rates by B# Race and Ethnicity, US, 1975-2010
5-Year Relative Survival Rate 100
50
Percent
0
Distant Localized Regional Stage
Figure 4: The majority of breast cancer deaths are due to metastasis. (A) Data Figurefrom the 4: AmericanThe majority Cancer of breast Society cancer shows deaths that theare Femaledue to metastasisBreast Cancer. (A) Death Data fromRate thehas American been on the Cancer decline Society since shows1989 for that all the ethnicities. Female Breast (B) The Cancer 5-year Death RateRelative has been Survival on the Rate decline for sincepatients 1989 diagnosed for all ethnicities. with breast (B) cancer The 5 at-year the RelativeLocalized Survivalor Regional Rate Stage for patientsis nearly diagnosed100%, but withdrops breast to less cancer than 25% at thein patients Localized or Regionaldiagnosed Stage with is Distant nearly 100%,Stage breastbut drops cancer. to less than 25% in patients diagnosed with Distant Stage breast cancer. *American*American Cancer Cancer Society. Society. Breast Breast Cancer Cancer Facts Facts & Figures & Figures 2013 2013-2014-2014
8 patients diagnosed with Distant Stage breast cancer, the 5-year survival rate is less than
25% (Figure 4B).
Distant stage breast cancer (or Stage IV) is when the cancer has spread, or metastasized, to distal organs in the body. There is a clear unmet medical need for these patients, whose diagnosis remains essentially a death sentence [64]. Indeed, metastasis is responsible for 90% of deaths in breast cancer patients [63]. Therefore, there is a great need to research new therapies that can more effectively target metastasis in order to treat this form of the disease.
Hypoxia promotes breast cancer metastasis
Hypoxia, or lack of oxygen, is one of the most significant predictors of poor clinical outcome in breast cancer patients [65-68]. Growing tumors become hypoxic due to insufficient blood supply, usually as a result of outgrowth of the surrounding blood vessels or immature tumor microvessel vascularization [69]. In the context of tumors, hypoxia is defined as an internal partial pressure of less than 10-15 mm Hg [70, 71]. It is estimated that approximately 50-60% of advanced solid tumors have localized hypoxic tissue regions [72].
The hypoxia inducible factor (HIF) family of transcription factors is the master regulator of the hypoxia response. HIF proteins coordinate the cellular adaptation to hypoxia, which includes stimulation of angiogenesis via VEGF and a metabolic shift to glycolysis in order to increase ATP production [69]. These hypoxic responses are also
9 beneficial to the needs of rapidly proliferating cancer cells and, therefore, promote tumor progression.
Hypoxia also enhances many cellular functions that are pro-metastatic, such as increased cell motility and invasion into the stroma [73-79], up-regulation of extracellular proteases [80-82], and epithelial to mesenchymal transition (EMT) [83-85]. EMT is a dedifferentiation process where cells lose expression of adhesion molecules, such as E- cadherin, and dissolve cell-cell tight junctions, which allow the tumor cell to become independent of the extracellular matrix (ECM) and stroma and migrate within the vasculature [86]. Metastasis also requires the cancer cell to be able to breakdown the
ECM and migrate through the stroma in order to enable extraversion from the primary tumor site and invasion of distal organ tissue [87]. As a result of these factors, increased expression of Hif-1α is linked to metastasis and poor prognosis in patients with both sporadic and genetic breast cancers [66, 67, 88-91].
The HIF signaling pathway
The cellular response to hypoxia is mediated by the HIF signaling pathway. The
DNA-binding transcription factor HIF associates with cofactors in order to trigger an adaptive response to low O2 by affecting expression of a myriad of target genes [92].
HIF is a heterodimer that consists of an oxygen-sensitive α subunit (Hif-α) and a constitutively expressed β subunit (Hif-1β or Aryl Hydrocarbon Receptor Nuclear
Translocator [ARNT]) [92, 93]. Hif-1β also functions as a heterodimer with other members of the basic Helix-Loop-Helix (bHLH) PER-ARNT-SIM (PAS) family of
10 transcription factors. The hypoxic response if mediated by post-translational modifications of the Hif-α subunit, which has three known isoforms: Hif-1α, Hif-2α and
Hif-3α [93-95]. While both isoforms are oxygen sensitive, the biology of Hif-1α and Hif-
2α is complex, where they can have complementary or opposing functions in a tissue and context specific manner [96]. The Hif-3α isoform consists of multiple splice variants; some variants have been shown to block the hypoxic response, however, the biological function of the many Hif-3α splice variants remains to be fully elucidated [95].
Regulation of Hif-α activity is mediated through its protein domains. The N- terminal portion of Hif-α contains the bHLH and PAS domains, which are required for binding to the DNA and Hif-1β heterodimer formation, respectively (Figure 5) [97]. The
C-terminal portion of Hif-α contains domains that control degradation and
ODD DNA binding Hif-1β binding domain domain P402 P564 N803
HIF-1α bHLH PAS A PAS B N-TAD ID C-TAD
Figure 5: Hif-1α protein domain structure. The basic Helix-Loop-Helix Figure(bHLH 5:) domain Hif-1α binds protein to the domain DNA. structure The PER-ARNT-SIM. The basic Helix (PAS)-Loop domains-Helix (bHLH) domainmediate binds heterodimer to the DNA. formation The PER of -HifARNT-α and-SIM Hif (PAS)-β. The domains oxygen mediate dependent heterodimer formationdegradation of Hif(ODD)-α and domain Hif-β .confers The oxygenO sensitivity. dependent The degradation C-terminus (ODD) contains domain an confers O sensitivity. The C-terminus2 contains an independent N-terminal independent2 N-terminal transactivation domain (N-TAD) and C-terminal transactivation domain (N-TAD) and C-terminal transactivation domain (C-TAD). Thetransactivation inhibitory domain domain (ID) (C-TAD). negatively The regulates inhibitory the domaintransactivation (ID) negatively domains. Hif-1α isregulates hydroxylated the transactivation at proline residues domains. 402 Hif-1 and 564α is hydroxylated to signal for proteinat proline degradation duringresidues normoxia. 402 and Hi564f-1 toα signalis also forhydroxylated protein degradation at asparagine during 803 normoxia.during normoxia to inhibitHif-1 αC -isTAD also activity. hydroxylated at asparagine 803 during normoxia to inhibit C- TAD activity.
11 transactivation. The oxygen dependent degradation (ODD) domain confers O2 sensitivity; the two independent transaction domains (N-terminal transactivation domain
[N-TAD] and C-terminal transactivation domain [C-TAD]) regulate Hif-α activity; the inhibitory domain negatively regulates the transactivation domains (Figure 5) [98]. The
C-TAD binds to coactivators of the p300/Creb-binding protein (CBP) family in order to activate transcription of HIF target genes [99].
Hif-α has a unique regulatory mechanism; it is constitutively expressed and O2 levels directly regulate its activity on a post-translational level by signaling for protein degradation. Figure 6 depicts an overview of the canonical, O2-dependent HIF signaling pathway. Oxygen levels control Hif-α expression by hydroxylation of the protein.
During normoxia (when free O2 is available), Hif-α is hydroxylated at the proline 402 and proline 564 residues within the ODD domain by prolyl hydroxylase domain (PHD) enzymes [100-103] (Figure 5). The β‐domain of von Hippel‐Lindau tumor suppressor protein (pVHL) recognizes and binds to hydroxylated Hif-α in the ODD domain, which signals for Hif-α to be ubiquitinated by the Elongin BC/Cul2/pVHL ubiquitin–ligase complex, thereby marking Hif-α for degradation by the 26S proteasome [104, 105]. Hif-
α is also negatively regulated during hypoxia by factor inhibiting HIF (FIH) hydroxylase enzyme [106]. FIH hydroxylates the asparagine 803 residue of Hif-α, which sterically prevents binding of C-TAD to coactivators (Figure 5) [106].
During hypoxia, Hif-α is expressed because it cannot be hydroxylated, thereby resulting in inhibition of protein degradation (Figure 6). This is because, under physiological conditions, O2 is a limiting substrate for PHD and FIH hydroxylase enzymes [103, 107, 108]. Non-hydroxylated Hif-α is stabilized since it will not be
12
Normoxia Hypoxia O2
pVHL O2 HIF-α HIF-α HIF-α PHD PHD HIF-α O HIF-α HIF-α H
HIF-1α Degradation HIF-2α via proteosome
Metastasis p300 Angiogenesis HIF-α Metabolism
Figure 6: The canonical, O2-dependent HIF signaling pathway. Expression of Hif-1α and Hif-2α transcriptionFigure 6: The factors Hif-α signaling is regulated pathway by O. Oxygen via hydroxylation levels post-translationally by PHD. Hydroxylated regulate Hif- Hif-α expression in the cell. When oxygen2 is present (normoxia), PHD hydroxylates α is recognizedHif-α in bythe pVHLODD domain., which Hydroxylationresults in ubiquitination of Hif-α allows and pVHLdegradation to bind viato Hif the-α . proteasome.pVHL Hif- bindingα is ablerecruits to beassociation expressed with during a ubiquitin hypoxia ligase because complex, limiting which Opoly2 - concentrationsubiquitinates prevent Hif -PHDα in order activity. to signal Stabilized for degradation Hif-α binds via the to proteasome.Hif-1β and Duringtravels to the nucleus hypoxia,to bind HRE when promoters,O2 levels are recruit very low, coactivators PHD cannot, and hydroxylate activate HIF-responsiveHif-α, which genes. prevents binding to pVHL and degradation of Hif-α. Both HIF isoforms (Hif-1α and Hif-2α) then form a heterodimer with Hif-1β, which travels to the nucleus to associate with co-activators, such as p300, and activate transcription of Hif-α target genes.
recognized and bound by pVHL, and therefore will not be degraded via the proteasome
[104, 105]. Stabilized Hif-α is then able to form a heterodimer with its binding partner,
HIf-1β, and travel to the nucleus where it binds to hypoxia-response element (HRE)
consensus sequences promoters and recruits p300/CBP coactivators [109, 110]. The
complex activates transcription of a subset of HIF-responsive genes that mediate the
hypoxic response, which include SLC2A1 (glycolysis), VEGFA (angiogenesis) and EPO
(erythropoiesis) [111].
13
Hypoxia-independent regulation of Hif-α
Hif-α has also been shown to be regulated by O2-independent, non-canonical regulatory mechanisms [105]. Growth factors, cytokines, and other signaling molecules stimulate Hif-α by activating the phosphatidylinositol 3-kinase (PI3K) or mitogen- activated protein kinase (MAPK) pathways to increase protein synthesis; however, unlike hypoxia, this activation of Hif-α by growth factors occurs in a cell type specific manner [111]. Extracellular signal-related kinases (ERK) can also phosphorylate p300, which stimulates Hif-α transactivation [112]. The stability of Hif-α mRNA can be negatively regulated by both miRNAs and mRNA destabilizing proteins [113-115].
Post-translational modifications besides hydroxylation also regulate Hif-α in a non-canonical manner. SUMOylation, methylation and acetylation have been shown to affect Hif-α stability via proteasome-mediated mechanisms as well as modulate Hif-α transcriptional activity [116-121]. The glycolytic enzyme M2 isoform of pyruvate kinase
(PKM2) has been described as a novel Hif-α transcriptional coactivator [122]. Kinases have been suggested to mediate growth factor and hormone-mediated regulation of Hif-α during normoxia. Hif-α can be phosphorylated in numerous locations by kinases such as
ERK and glycogen-synthase kinase-3 (GSK-3), which has been described to control Hif-
α protein stabilization, nuclear translocation and transactivation activity [123, 124].
Reactive oxygen species (ROS) have also been proposed to play a role in Hif-α regulation, although a consensus on the exact aspects of this regulation has not been made due to conflicting evidence [125-127]. The ROS studied include superoxide (SO),
14 hydrogen peroxide (H2O2), and nitric oxide (NO). The mitochondrial electron transport chain has been proposed to be involved in Hif-α regulation via SO and H2O2 [128], but overall the exact effects SO and H2O2 have on Hif-α activity during hypoxia remain undetermined [126]. During normoxia, the consensus on the role of SO and H2O2 are a bit more clear as these ROS have been shown to stabilize Hif-α expression [126, 127,
129] by inhibition of PHD activity [130], by influencing miRNA-mediated Hif-α stabilization [131], and by interacting with the ERK and PI3-K signaling pathways [132].
A" NADPH NADP+ + H H2O O2 NO Protein Protein
L-arginine NOS L-citrulline S-H S-NO +"
NO
B" ODD DNA binding Hif-1β binding domain domain P S520 P S800 N HIF-1α bHLH PAS A PAS B N-TAD ID C-TAD
Figure 7: NOS regulates proteins by S-nitrosylation. (A) NOS reaction mechanism. The substrate, L-arginine, is catalyzed to produce L-citrulline and nitric oxide (NO) by NOS. The NO produced in this reaction will react with thiol groups on free cysteines of nearby proteins, resulting in a covalent nitrosylation of the cysteine residue. S- nitrosylation can affect protein function. (B) The two sites of S-nitrosylation are depicted for human Hif-1α. Nitrosylation at S520 in the ODD domain prevents binding to pVHL. Nitrosylation at S800 in the C-TAD domain enhances binding to the p300/CBP coactivators.
15 On the other hand, NO has a clear role in Hif-α regulation. Unlike ROS, NO is a regulated cellular signaling molecule; its intracellular expression is controlled by Nitric
Oxide Synthase (NOS) enzymes [133-135], which consist of 3 tissue-specific isoforms: neuronal NOS (nNOS), inducible NOS (iNOS) and endothelial NOS (eNOS) [136-138].
NOS enzymes regulate the posttranslational modification S-nitrosylation (the reversible, covalent addition of NO to protein cysteine thiols) by using L-arginine and O2 as substrates to generate NO and L-citrulline [134, 135] (Figure 7A).
NO stabilizes Hif-α during normoxia and inhibits Hif-α stabilization during hypoxia [133]. During hypoxia, high NO concentrations inhibit the cytochrome C complex, the primary site of cellular O2 consumption, which changes the intracellular O2 availability and blocks Hif-α induction via PHD-dependent degradation of Hif-α [139,
140]. However, NOS is an important positive regulator of Hif-α expression in normoxia.
Addition of NO donors or expression of NOS causes stabilization of Hif-α, increased
HRE binding and activation of Hif-α target genes under normal O2 conditions [141-144].
Hif-α is stabilized by S-nitrosylation of the key mediators of Hif-α degradation in the canonical pathway (Figure 8) [133]. Hif-α itself is nitrosylated at Cys520, in the ODD domain (which prevents binding to pVHL) and at Cys800, in the C-TAD (which enhances binding to p300 to stimulate protein transactivation) (Figure 7B) [145-147]. In addition, pVHL can be nitrosylated to prevent association with the Elongin C E3 ubiquitin ligase complex, and NO can inhibit PHD activity for Hif-α [148-150].
In the setting of breast cancer, both eNOS [151] and iNOS [152-154] expression correlate with metastasis and poor prognosis in patients and also significantly correlate with expression of VEGF and Hif-1α in tumors [155]. Genetic polymorphisms in the
16 HIF-α HIF-α
PHD NOS O2 NOS HIF-α O H HIF-α HIF-α
NOS
pVHL pVHL p300 Elongin C HIF-α pVHL HIF-α O H
p300 Degradation HIF-α via proteosome
Figure 8: Regulation of Hif-α during normoxia by NOS. NOS can activate Hif-α signaling in an O2-independent manner by affecting multiple steps in the Hif-α regulation pathway. NOS directly S-nitrosylates Hif-α in the ODD domain to prevent binding to pVHL so Hif-α cannot be degraded via the proteosome. Hif-1α is also S-nitrosylated in the C-TAD domain, which enhances binding to p300 coactivators to increase Hif-α transcriptional activity. NOS also prevents Hif-α degradation via the proteosome by inhibiting PHD activity and S-nitrosylating pVHL to prevent binding to the Elongin C ubiquitination complex.
gene for eNOS increase a woman’s risk of developing invasive breast cancer [156-158].
NO signaling promotes breast cancer progression by promoting proliferation, cellular invasion, tumor angiogenesis, and metastasis [159, 160]. Cellular and animal experiments have shown that iNOS plays a vital role in breast cancer progression and iNOS has been suggested as a target for triple negative breast cancer since iNOS inhibitors can reduce proliferation and metastasis in cell and mouse models [153, 161-
17 168]. Mechanisms for NOS pro-tumorigenic functions have been described, but vary widely in a cancer type-specific manner; overall, a clear consensus on the regulatory mechanisms of NOS in breast cancer have yet to be elucidated. It is possible that NOS- induced activation of Hif-1α may be an important aspect of its pro-tumorigenic properties.
Notch mediates hypoxia-induced metastasis
Hypoxia activates the Notch signaling pathway and stimulates expression of
Notch target genes HES1 and HEY1 [169]. Notch signaling is required for Hif-1α to promote an undifferentiated cell state and, interestingly, is a result of a direct interaction of Hif-1α with the Notch signaling pathway, rather than via activation of Hif-1α target genes [169]. Hif-1α has been suggested to increase NICD activity by binding of Hif-1α to the DNA of Notch target genes or hydroxylation of NICD by FIH, but the physiological relevance of these mechanisms remains to be determined [170, 171].
Aberrant Notch signaling is associated with the development and progression of several human cancers, however, it can have either a tumor-suppressor or oncogenic role depending on the tissue [32]. As an oncogene, Notch promotes a less differentiated, more aggressive form of cancer and induces EMT, which enhances invasion, cell motility and metastasis [172]. In many cancers, including breast, Notch expression and signaling is present in many tumors and correlates with metastasis and poor prognosis in patients
[32]. Activating mutations in Notch1 and Notch4 receptor isoforms are sufficient to
18 cause tumor formation as well as maintain tumors in transgenic breast cancer mouse models [173-175].
Importantly, Notch signaling is required for hypoxia-induced potentiation of
EMT, migration and invasion in many cancers, including breast, ovarian, prostate, melanoma, and glioblastoma [170, 176-180]. These studies reveal that Hif-1α-Notch crosstalk play an important role in the progression of many cancers, including breast cancer. It is also important to note that Notch is essential for hypoxia-induced EMT and metastasis potentiating effects, which has led to clinical research on Notch-targeting therapeutics to target breast cancer metastasis in advanced tumors [181].
A recent publication made an interesting observation that both Hif-α and Notch pathways crosstalk in Drosophila outside of their canonical roles [182]. Circulating crystal cells (similar to human myeloid cells), which have sparse interaction with other cells and Notch ligands, rely on Hif-1α to activate the Notch pathway to maintain the cell population. The crystals cells are not hypoxic, but rather depend on NOS1 to induce Hif-
1α expression [182]. These results suggest that Hif-1α may play an important role as a regulator of the Notch pathway not only as a hypoxic response, but also under normal oxygen conditions via stabilization by NOS. It is also possible that Hif-1α-Notch crosstalk has biological roles outside of cancer or other pathologic contexts.
Breast cancer stem cells
Hypoxia, NOS and Notch signaling both have important roles during development and regulate adult stems cells in many organs Notch signaling is also
19 Primary Differentiation tumor
Clone 1 Metastatic Clone 2 tumors Clone 3 Clone 4 CSC targeting = radiation/ drugs chemotherapy
Dormant CSCs
Tumor Tumor reoccurrence eradication
Figure 9: The “cancer stem cell” model. CSCs are a subpopulation of cells that can differentiate to recapitulate the original tumor, or a tumor-initiating cell (depicted in darkest color). According to the model, tumor cells are organized in a hierarchy, similar to normal tissues. Tumors contain heterogeneous populations of genetic subclones. CSCs are resistance to radiation and chemotherapy, and can survive this therapy to later recapitulate the original tumor. CSCs also colonize distant tissues and act as a “seed” to form new tumors (metastases). If this model were correct, an ideal treatment strategy would combine a CSC targeting therapy with radiation/chemotherapy to remove tumor bulk, which should result in tumor eradication. ** Figure adapted from Kreso & Dick, Cell Stem Cell. 2014.
critical for normal hematopoiesis, breast development, colorectal epithelial maturation,
immune regulation, and neural stem cell survival [31, 183]. Hif-α signaling controls
specification and maintenance of multipotent and pluripotent stem cells of many organs,
such as Hematopoietic stem cells (HSCs), embryonic stem cells (ESCs), and neural stem
cells (NSCs) [184, 185]. NOS controls renewal and differentiation of ECSs, NSCs, and
20 skin-derived mesenchymal stem cells (MSCs) and iNOS expression is induced in breast tissue lactation glands [186, 187].
It has becoming increasingly apparent that tumors consist of distinct cell populations that differ in gene expression, proliferative capacity and invasiveness in both a spatial and temporal manner [188]. One model to explain these effects is the “cancer stem cell” model, which postulates that tumors are hierarchally organized and are more of an abnormal organ than a clonal mass of cells (Figure 9) [189, 190]. According to the model, similar to normal tissues, a distinct subset population of cells, deemed cancer stem cells (CSCs) that, are able to self-renew and give rise to progeny that can regenerate all the heterogeneous cell types of the tumor.
The existence of CSCs is postulated to be responsible for tumor initiation, metastatic colonization, treatment resistance and cancer reoccurrence (Figure 9) [191,
192]. Similar to normal stem cells, CSCs are more dormant than the highly proliferative tumor mass and therefore are more resistant to traditional treatments, such as chemotherapy and radiation, and may survive treatment to form new tumors over time
[193]. In addition, breast cancer stem cells (BSCSs) are implicated as the metastatic
“seeds” that colonize new sites; only a small percentage of circulating tumor cells can initiate metastases and metastasis-initiating cells as well as newly formed micro- metastases have been shown to be highly enriched for BCSC markers [194-196]. More recently, it has also been appreciated that genetic intra-tumor heterogeneity is also a feature of many tumors and that these tumors may actually have distinct populations of
CSCs pools in addition to cellular hierarchy (Figure 9) [189].
The existence of CSCs was first identified in human leukemia [197]. Solid tumor
21 A" B" C" In vivo Tumorigenicity Cell Markers In vitro Mammosphere
Limiting Dilution • CD24Lo/CD44Hi 103 104 105 FGF br EGF • ALDH Insulin - Aldeflour Assay B-27
1° mammospheres
Bodipy-aminoacetaldehyde
Serial Passaging ALDH
2° mammospheres
Bodipy-aminoacetate
Figure 10: Breast cancer stem cell assays. There are three main assays that are used to measure BCSCs. (A) The in vivo tumorigenicity assay, or the ability of a limited number of breast cancer cells to form tumors upon injection into immunodeficient mice, is the gold standard used to measure BCSC. Self-renewal properties can be assessed when xenographs are excised, sorted, and transplanted into new recipient mice. (B) Cell surface markers, such as CD44+CD24- phenotype and/or ALDH activity, are used to identify BCSCs. (C) The mammosphere formation assay detects BCSCs based ability to form and propagate as multicellular spheroids in suspension culture. Breast cancer cells are seeded at clonal density in a defined-growth factor, suspension media to form primary mammospheres, which can be harvested, dissociated, and reseeded in a secondary mammosphere formation assay as a more rigorous test of self-renewal capacity.
CSCs were first identified in breast cancer, but have since been identified in most solid tumor malignancies [189, 198]. There are three main assays that are used to measure
BCSCs (Figure 10) [199]. BCSC assays can be used to measure the percent of BCSCs in breast cancer cell populations derived from patient tumors, mouse xenograph tumors, or breast cancer cell lines. The gold standard used to measure BCSC is the ability of a
22 limited number of cells to form tumors upon injection into immunodeficient mice [199,
200]. The xenographs can then be excised, sorted, and transplanted into new recipient mice to assess self-renewal properties.
Cell surface markers can also be used identify BCSCs. Fluorescence-activated cell sorting (FACS) allows for the separation of different cell populations based on their surface markers. The CD44+CD24- phenotype and/or ALDH (aldehyde dehydrogenase) activity (using Aldeflour assay, Stem Cell Technologies) are used as markers of BCSCs
[198, 201]. In one study, while more than 50,000 ALDH-negative breast cancer cells did not form tumors upon injection into mice, injection of only 20 cells with a CD44+CD24- and ALDHbr phenotype was sufficient to form a tumor [201]. Additionally, patients with breast cancer tumors that score ALDH+ by immunohistochemistry have significantly decreased overall survival [201].
The third BCSC assay is the mammosphere formation assay, which is based on the ability of BCSCs, but not bulk cancer cells, to propagate as multicellular spheroids in suspension culture [202]. In this assay, breast cancer cells are seeded at clonal density in a defined-growth factor, suspension media to form primary mammospheres. Primary mammospheres can be harvested, dissociated by trypsinization, and reseeded in a secondary mammosphere formation assay as a more rigorous test of self-renewal capacity. Mammospheres are highly enriched for BCSC markers as well as tumor initiating cells as measured in the xenograph transplantation assay [203, 204].
CSCs utilize many of the same signaling pathways that are the major regulators of normal stem cells. Hypoxia, Notch, and iNOS, which have roles in normal stem cell regulation, all promote an undifferentiated phenotype in breast cancer, resulting in an
23 increase in the breast cancer stem cell (BCSC) population [186, 199, 205-207]. Exposure of tumors to hypoxia or treatment with antiangiogenic agents (which induce hypoxia) has been shown to increase the BCSC population in tumors [208, 209]. Notch activity has recently been proposed to be a novel marker of BCSCs as NICD correlates with tumorigenicity and other BCSC markers [210]. The effects of these signaling pathways on tumor progression and metastasis are likely mediated (at least partially) by their function in regulation of BCSCs. As such, both iNOS and Notch have been investigated as targets for the development of inhibitors that target the BCSC population [167, 211].
Notch-targeting breast cancer therapeutics
Since most current cancer treatments target the bulk tumor, rather than BCSCs, according to the “cancer stem cell” model, new therapies are needed in order to effectively treat metastatic disease and prevent resistance. If this model were correct, an ideal therapeutic strategy to eradicate the tumor would involve simultaneous treatment with radiation/chemotherapy to reduce the tumor bulk and some CSC-targeting therapy to kill the resistance population (Figure 9) [191].
Targeting the Notch pathway with γ-secretase inhibitors (GSIs) as BCSC targeting agents has been successful in the experimental setting, which provides evidence to support the model as a viable therapeutic strategy. Multiple preclinical experiments have found that treatment with GSIs to block Notch signaling is effective to target
BCSCs [193, 211-214]. In addition, the combination of a GSI and trastuzmab in a
24 HER2+ breast cancer mouse model resulted in a complete cure and blocked reoccurrence
[215].
GSIs are currently in early stage clinical trials for metastatic breast cancer and have had some promising preliminary results [181]. Table 1 lists the current trials and results (if available). There are three different GSIs that have been tested in clinical trials as BCSC targeting agents: RO4929097 [216], MK0752 [217], and PF-03084014 [218]
(Table 1). In preclinical experiments, RO4929097 reduced clonogenicity and enhanced radiosensitivity of triple negative breast cancer cells [219]. RO4929097 showed some promising BCSC inhibitory effects in Phase I clinical trials [220-222], but its development has since been discontinued, possibly due to failure as a single agent in
Phase II trials for colon and ovarian cancer [223]. MK0752 was effective to reduce
BCSC populations in patients in a Phase Ib clinical trial, where treatment of MK0572 in combination with docetaxel reduced mammosphere formation and the percentage of
CD44+CD24- and ALDH+ cells derived from patient biopsies [211]. MK0752 also had a tolerable safety profile and inhibited Notch pathway biomarkers in a larger Phase I/II trial [224] and is still under investigation; in a recent trial, MK0752 showed clinical benefit in patients with head and neck squamous cell carcinoma (HNSCC) [225]. PF-
03084014 has shown promising BCSC targeting and anti-tumor activity in multiple preclinical experimental publications [226-228] and also shown promising clinical activity in a phase I dose-finding study in patients with advanced-stage solid tumors so future development is currently being evaluated [229]. A better understanding of the role of Notch signaling in BCSCs and its interaction with other cell signaling pathways may aid in the future development of these BCSC targeting therapeutics.
25 TABLE 1: List of clinical trials for breast cancer involving γ-secretase inhibitors as CSC-targeting agents (adapted from Lin et al. Histopathology. 2016 [181]).
Agent Phase Combined Target # of Description Result (sponsor, trial therapy population subjects number) RO4929097 Phase I (NCI, Capecitabine Refractory 30 Dose Determine NCT01158274) solid tumors escalation dose for and safety Phase II; partial response in colon and cervical cancer [222] RO4929097 Phase I (NCI, Paclitaxel Advanced 14 Side effects N/A NCT01238133) and TNBC and dose carboplatin determination RO4929097 Phase II (NCI, N/A Advanced 3 Anti-tumor N/A NCT01151449) TNBC effect assessment MK0752 Phase I (Merk, N/A Advanced 103 Dose Good NCT00106145) breast cancer escalation tolerability and other solid and safety and Notch tumours pathway inhibition [224] MK0752 Phase I (Merk, N/A Healthy 30 Notch N/A NCT00803894) population pathway assessment MK0752 Phase I (Loyola Tamoxifen Early stage 22 Safety and N/A University, or ER+ breast tolerance NCT00756717) letrozole cancer MK0752 Phase I/II Docetaxel Advanced 30 Dose Good (University of breast cancer escalation tolerability; Michigan, and safety reduced NCT00645333) BCSCs in patients [211] PF- Phase II N/A Advanced 48 Anti-tumour N/A 03084014 (Pfizer, TNBC activity and NCT02299635) Tolerance assess-ment PF- Phase Ib Docetaxel Advanced 60 Tolerability N/A 03084014 (Pfizer, breast cancer NCT01876251) PF- Phase II N/A Non- 35 HES4 gene N/A 03084014 (Pfizer, metastatic expression NCT02338531) TNBC patients level with residual disease after neo-adjuvant chemotherapy
26 1.4 Notch Signaling in the Kidney
Notch signaling plays an important role in the kidney. During development, Notch is required for proper formation of the kidney nephron in a wide array of species, from
Xenopus to mammals, but is then silenced in healthy adult kidneys. However, in many types of kidney disease, the Notch pathway is reactivated and has a causal role in disease pathogenesis. In this section, we will address different aspects of Notch signaling in the kidney and introduce a putative kidney-specific endogenous inhibitor of γ-secretase, γ- glutamyl transferase (GGT).
Notch signaling in kidney development
Kidneys function as the body’s filter by removing metabolic waste and reabsorbing or excreting electrolytes to regulate blood pH and composition. The functional unit that controls this filtration is called the nephron, an organized unit that is conserved among almost all eukaryotes [230]. The complexity of the nephron functional units differs among organisms; zebrafish kidneys consist of one nephron, mouse kidneys contain tens of thousands of nephrons, and the human kidney is made up of millions of nephrons [231]. The mature human nephron consists of several different segments, depicted in Figure 11C [230]. Blood is filtered by the glomerulus (which is enveloped by podocytes) and the filtrate then flows through the proximal tubules to the Loop of Henle to the distal tubules, where joins the collecting system and ultimately exits the kidney via the ureter [232].
27 A" B"
Nephron C" Distal convoluted Proximal tubule convoluted tubule
kidney Glomerulus renal vein and artery
Podocytes ureter Vascular loop Henle’s Collecting duct loop
Figure 11: Notch is critical for development of proximal tubule and podocytes during kidney nephrogenesis. (A) During development of the kidney, the metanephric mesenchyme first undergoes segmentation to form a comma-shaped body. (B) The comma-shaped body extends to form the S-shaped body, where the distal segments continue to extend and differentiate until it ultimately develops into the mature, patterned nephron. (C) The kidney nephron. The proximal segments of the S-shaped bodies will form the podocytes (dark green) and glomerulus (light green). The distal segments of the S-shaped bodies differentiate into Henle’s loop (orange) and the distal tubules (yellow). Notch 2 regulates patterning of the midsections of the S-shaped bodies, which give rise to the proximal tubules. ** Figure is adapted from Schedl, Nature Reviews Genetics. 2007.
The two main components of the kidney, the collecting system and the nephron, have
separate developmental processes [232]. Notch signaling plays a key role in
nephrogenesis [233]. Notch becomes involved during the first patterning stages of the
28 developing nephron. The metanephric mesenchyme, which gives rise to all renal epithelial cells (from podoctyes to distal tubule epithelial cells), undergoes condensation and then segmentation, to first form a comma-shaped body and then an S-shaped body
(Figure 11 A&B) [232, 234]. In the developing comma and S-shaped bodies, Notch regulates the fate of cells that form the proximal tubule portion of the nephron (Figure
11) [234]. Experimentally, Notch1 expression is detected in the prospective distal tubule and collecting ducts and Notch2 was present in the primitive proximal tubule and was expressed at a lower level in podocyte progenitors [235, 236].
Functional studies have demonstrated that Notch has a critical role in proximal tubule and podocyte development, which is mediated specifically by Notch2. GSI treatment reduced formation of renal epithelial structures in cultured mouse metanephroi and genetic deletion of PS1/PS2 in the kidney led to severe nephrogenesis defects and virtually no comma or S-shaped bodies or mature glomeruli [237, 238]. Additional experiments addressing the role of the different Notch isoforms found that while both
Notch1 and Notch2 are expressed in developing kidneys, knockout of Notch1 did not alter kidney development, while knockout of Notch2 caused the loss of podocytes and proximal tubule cells [239, 240]. There is also evidence that Notch signaling is important during kidney development in humans. Alagille syndrome (ALGS) is a congenital, heritable disease affecting many organ systems that was originally identified by mutations in Jagged1, but later was also correlated with mutations in Notch2 [241].
Approximately 40-50% of ALGS patients with Jagged1 mutations have renal pathologies, and every patient identified with Notch2 mutations in one study had symptoms that included renal abnormalities [241].
29 Regulation of Notch in adult kidney
While Notch is vital during kidney development, once development is complete,
Notch activity is silenced in the kidney of adult human and rodents [242-245]. The silencing of Notch in mature podocytes is necessary to maintain the glomerulus; while podocyte-specific genetic deletion of the Notch co-factor CSL in mice had no effect, transgenic mice that overexpress NICD1 post development rapidly develop glomerulosclerosis and die [244]. Additionally, tubule-specific overexpression of NICD in a mouse model caused fibrosis of the kidney [246].
The temporal context of Notch signaling in the kidney appears to be an important factor. While chronic deregulation of Notch activation is pathogenic, acute Notch activation may potentially aid in tissue repair after acute kidney injury, although this remains controversial due to conflicting published results [234, 247]. Notch signaling is transiently activated following acute kidney injury [248, 249]. Although it has not been well established, it has been postulated that acute Notch signaling following injury may be involved in the repair process during renal epithelial regeneration, possibly through stimulation of a podocyte progenitor cell population [250].
Notch and kidney disease
Over 20 million Americans suffer from chronic kidney disease, a general diagnosis to describe a gradual loss of kidney function [233]. The most common causes of chronic kidney disease are high blood pressure and diabetes. Even with treatment,
30 kidney function can continue to decline over time and eventually results in dangerous levels of fluid, electrolyte, and waste build up in the body, a state called end-stage renal disease, which is fatal unless treated with dialysis or kidney transplant [251]. Aberrant, continuous activation of Notch signaling occurs in numerous kidney diseases and has been shown to contribute to disease progression, including processes that lead to end- stage renal disease. In patients from 10 different renal disease groups, increased expression of Notch1 and Notch2 was detected and correlated with albuminuria, glomerulosclerosis, and renal function [252]. The Notch pathway plays a role in development of kidney diseases of the glomerulus/podocytes, such as glomerulosclerosis and diabetic nephropathy, and of the tubular epithelial cells, such as fibrosis and chronic kidney disease [233].
As the glomerulus is responsible for filtration of the blood, dysfunction causes loss of proteins into the urine (proteinuria), which is associated with glomerulosclerosis and leads to end-stage renal disease [251]. The importance of Notch signaling in progression of glomerulus-related kidney failure has been demonstrated in animal models. Podocyte-specific inducible expression of NICD1 in adult mice caused the animals to rapidly develop proteinuria and glomerulosclerosis and ultimately die in 3 week period [243]. In the same study, inhibition of Notch had a protective effect in a mouse model of diabetic nephropathy [243]. Both genetic deletion of the Notch transcriptional co-activator CSL or treatment with a GSI protected mice from diabetes- induced podocyte loss and albuminuria [243]. Another study found that the GSI DAPT prevented podocyte apoptosis in a rat model of diabetic nephropathy [253].
31 Chronic kidney disease is a progressive functional decline of the kidney, which ultimately leads to end-stage renal disease [254]. Kidney fibrosis (lesions found in chronic kidney disease) occurs when the balance between the interaction of the many cell types is perturbed, causing inflammation and a loss of renal epithelial cells, which perform most of the primary kidney functions. Sustained Notch signaling in tubule epithelial cells is associated with kidney fibrosis in both patients and mouse models of kidney disease [246, 252, 255, 256]. In a folic acid-induced mouse model of kidney fibrosis, the genetic deletion of CSL to inhibit Notch signaling in proximal tubules resulted in a significant decrease in tubulointerstitial fibrosis [246]. In the same study, another experiment showed that an inducible transgenic mouse with tubule epithelial- specific overexpression of NICD1 resulted in severe tubulointerstitial fibrosis and ultimately death due to kidney failure within 5 weeks [246]. Another study found that
Notch3 is overexpressed in patients and mice with kidney fibrosis, and that genetic deletion of Notch3 prevented ureteral obstruction-induced tubulointerstitial fibrosis
[256].
Even though Notch has been shown to play an important role in development of various kidney diseases, therapies targeting the Notch pathway have not yet been investigated in clinical trials. Due to the redundancy in members of the Notch pathway, pharmacological targeting remains a challenge. Although GSIs could potentially be used to treat these kidney diseases, their development has been limited by the undesirable off- target side effects that have been previously revealed in human clinical trials [17].
Identification of mechanisms to specifically target Notch signaling in the kidney may aid in the development of novel therapies for chronic kidney disease.
32
An endogenous inhibitor of γ-secretase in the kidney: Gamma-glutamyl transferase
Our lab has recently identified a putative endogenous inhibitor of γ-secretase that was isolated from the rat kidney using classical biochemical purification strategies. Mass spectrometry identified the protein as Gamma-glutamyl transferase (GGT; also called
Gamma-glutamyl transpeptidase) and biochemical assays have supported that GGT inhibits γ-secretase enzymatic activity. We hypothesize that GGT may play a role in the regulation of Notch signaling in the kidney by inhibiting the activity of γ-secretase.
GGT is a heterodimeric membrane protein that catalyzes the transpeptidation and hydrolysis of the γ-glutamyl group of glutathione (GSH) and related metabolites (Figure
12) [257, 258]. Human GGT is expressed on the luminal surface of excretive and absorptive cells, such as the kidney, intestine, brain, and liver [259]. Expression of GGT is highest on renal proximal tubule cells, where is it maintains cellular GSH homeostasis by breaking down extracellular GSH to form cysteinylglycine, which is then cleaved by dipeptidases to release cysteine [260]. The freed extracellular cysteine permits cysteine uptake into the cell since GSH cannot enter the cell [260]. Intracellular cysteine is necessary for protein synthesis and formation of intracellular GSH, an important protector against ROS oxidative damage in cells [261]. The expression of GGT is essential for the maintenance of cysteine in the body, as GGT knockout mice die at 10 weeks of age due to cysteine deficiency [262]. The GGT reaction mechanism and its role in GSH and cysteine homeostasis are depicted in Figure 12. GGT has additional cellular functions, including hydrolysis of the inflammatory-related metabolite substrate
33 leukotriene C4 and metabolism of GSH S-conjugates to cysteine S-conjugates for excretion in the detoxifying renal mercapturic pathway [263, 264].
GSH
Trans- Cys Gly Cys-Gly peptidase
+"
+" GGT Small Glu
Large Extracellular
Cytosol
GSH Glu Cys Gly
Figure 12: Gamma-glutamyl transferase (GGT) regulates cellular homeostasis of cysteine (Cys) and glutathione (GSH). The glutamyl bond of GSH is highlighted in yellow. GGT is a membrane-bound enzyme that hydrolyzes GSH at the glutamyl bond to form cysteinylglycine (Cys-Gly) and glutamate (Glu) by transferring the glutamyl group of GSH to H2O. Cys-Gly is then cleaved by transpeptidases into cysteine (Cys) and glycine (Gly). While GSH cannot cross the cell membrane, the free Glu, Cys, and Gly amino acids are transported into the cytosol. There, they can be utilized for many cellular functions, including the synthesis of GSH, which completes the “gamma-glutamyl cycle.”
GGT is a member of the N-terminal nucleophilc (Ntn) hydrolase superfamily of enzymes, which use the side chain of the N-terminal amino acid as the nucleophile during catalytic attack [265, 266]. Similar to other members of the Ntn hydrolase family, human
34 GGT1 is expressed as a 569-amino acid propeptide, which is autocleaved into large and small subunits by the catalytic threonine residue (Thr381) [267, 268]. The two subunits form a heterodimer that localizes to the cell surface. The large, N-terminal subunit is tethered to the membrane via a single pass transmembrane domain and the small, C- terminal subunit contains the catalytic Thr381 residue and enzymatic activity, which occurs in the extracellular portion of the protein [269, 270]. N-linked glycosylation at 7 extracellular sites is also required for proper folding, autocleavage and activation of GGT
[271].
There is a single GGT gene in mice and rats and three known GGT isoforms in humans, GGT1, GGT2 and GGT5 [257]. Human GGT1 (also known as GGT) is the main isoform that has been studied experimentally; its crystal structure was recently solved, which confirmed the previously described observations on the structure and function of the enzyme [272]. Whether or not GGT2 and GGT5 have biological functions remains to be determined. GGT2, although almost identical in sequence to
GGT1, is not autocleaved or catalytically active and GGT5 has only 4% of the activity of
GGT1 to hydrolyze GSH and leukotriene C4 [273, 274].
1.5 Hypothesis and Thesis Overview
Our main research question is: how can γ-secretase activity be conditionally modulated to regulate RIP in a context specific manner? While the mechanisms controlling γ-secretase activity and substrate specificity are not well-elucidated, multiple reports have described regulation of γ-secretase activity by interaction of the complex
35 with additional protein subunits, which modulate γ-secretase by either inhibiting or stimulating enzymatic activity [20-23]. In addition, it has been observed that only a fraction of steady-state γ-secretase complexes are catalytically active; the biological function of the large portion of inactive γ-secretase complexes that exist in the cell is unknown [24-26].
We hypothesize that signaling of γ-secretase substrates can be regulated during various biological processes and in response to environmental stimuli by interaction of γ- secretase with distinct, cell type-specific protein modulators. These modulators can interact with the complex to either increase or decrease the equilibrium between active and inactive γ-secretase complexes in the cell, and thereby dynamically regulate RIP.
Identification of novel γ-secretase protein modulators may have clinical relevance by offering novel drug targets to control processing of γ-secretase substrates, such as Notch, in a more specific manner. During my thesis research, I have addressed this research question with two projects, each focused on the discovery of novel regulators of the
Notch pathway in different tissues and disease models.
In the first project, we have investigated the non-transcriptional role of Hif-1α in the activation of γ-secretase in breast cancer stem cells. Tumor hypoxia contributes to the metastatic progression of breast cancer by promoting Notch signaling and increasing levels of the γ-secretase cleaved product, NICD [169, 170]. However, the effect of hypoxia on γ-secretase activity was unknown. In a recent study published in our lab, we discovered that hypoxia enhanced γ-secretase activity in multiple breast cancer lines
[275]. Hypoxia-induced stimulation of γ-secretase activity resulted from an interaction of
Hif-1α with the γ-secretase complex, which shifted the equilibrium between active and
36 inactive complexes [275]. Our findings describe a novel signaling paradigm that is consistent with our hypothesized model. Notch signaling can be regulated by Hif-1α- mediated modulation of γ-secretase activity in response to environmental stimuli, likely as an adaptive response of cancer cells to the changing tumor microenvironment. We describe a unique signaling mechanism for both γ-secretase and Hif-1α, where Hif-1α is acting outside its canonical role as a transcription factor to affect cell signaling.
What is the exact biological role of this signaling paradigm in breast cancer progression? We found that GSI treatment prevented hypoxia-induced invasion of breast cancer cells and metastasis to the lung in a mouse model [275]. Hif-1α and Notch are critical regulators of the breast cancer stem cell (BCSC) population, which is proposed to drive tumor proliferation and metastasis in breast cancer [191, 192, 206, 208]. We hypothesize that activation of Notch signaling by Hif-1α-mediated stimulation of γ- secretase activity plays an important role in the regulation of BCSCs. If γ-secretase activation is critical for BCSC proliferation, then the anti-metastatic effects of GSIs may result from a reduction in the BCSC population. Using mammospheres as a model for breast cancer stem cells, we will investigate the role of γ-secretase activity in the regulation of the BCSC population.
In the second project, we have investigated Gamma-glutamyl transferase (GGT) as a putative, novel, kidney-specific regulator of γ-secretase activity. The four components of γ-secretase are ubiquitously expressed at both the mRNA and protein levels in most tissues [18, 19], however, the protein expression of the subunits does not always correlate with γ-secretase activity [24-26]. One explanation is the existence of tissue-specific negative regulators of γ-secretase activity, such as we proposed in our
37 hypothesized model. Our lab has recently purified a novel γ-secretase inhibitor from the whole kidney organ, which completely inhibited γ-secretase activity for APP and Notch processing. Mass spectrometry identified the inhibitor as GGT, which was validated in preliminary biochemical studies.
In this work, we aim to establish GGT as a kidney-specific endogenous inhibitor of γ-secretase using biochemistry, cell, and animal models. Biochemically, we will verify that GGT inhibits γ-secretase activity directly and elucidate the inhibitory mechanism. We will also investigate if GGT plays a biological role in the regulation of γ- secretase activity and Notch signaling using a human kidney cell line with GGT knockdown and a zebrafish GGT-overexpressing model. Why does the kidney have such a potent inhibitor of γ-secretase? Notch signaling in kidney development is crucial for the formation of the proximal tubules and glomerulus, but is silenced in developed kidneys
[233]. Additionally, activation of Notch signaling plays a causative role in chronic kidney disease [233]. While our research is ongoing, we hypothesize that GGT may act as mechanism to repress Notch signaling after kidney development by inactivating γ- secretase, and that loss of this inhibition may have pathogenic consequences. If this hypothesis is correct, GGT could potentially be a novel drug target to modulate Notch signaling in chronic kidney disease.
38 CHAPTER 2
Materials and Methods
2.1 Cell culture
The human breast cancer cell lines (MCF-7, BT20, MDA-MB-157), the 4T1 mouse breast cancer cell line, and the human HK-2 kidney proximal tubule cell line were obtained from American Type Culture Collection (ATCC). All cell lines were cultured in a 37° C incubator with 5% CO2 and 21% O2. For experiments involving hypoxia, cells were cultured in a hypoxic incubator at 37° C incubator with 5% CO2 and 1% O2. Breast cancer cell lines were cultured in DME-HG : F-12 media supplemented with 10% FBS,
Non-essential amino acids (NEAA) and 1% penicillin/streptomycin. The number of viable cells was determined using the Cell Count & Viability Assay on a MUSE™ Cell
Analyzer (EMD Millipore).
2.2 Mammosphere Formation Assay
The cancer stem cell population of breast cancer cell lines were assessed in a mammosphere formation assay, which depends on the ability of cells for grow and form spheres in serum-free suspension media, as previously described (Figure 10C) [202, 203].
Mammosphere media consisted of DME-HG : F-12 supplemented with 1% penicillin/streptomycin, B27 (Invitrogen), 5 µg/mL insulin (Sigma), 10 ng/mL basic fibroblast growth factor (bFGF) (Sigma), and 20 ng/mL epidermal growth factor (EGF)
39 (Sigma). Cells were seeded at a density of 1,000-2,000 cells/mL in six well ultra-low attachment plates (Corning) and placed in a 37° C incubator with 5% CO2 and 21% O2.
After 10 days, the number of mammospheres in each well was counted under a microscope. The mammosphere formation efficiency (MFE) was determined by dividing the number of mammospheres per well by the number of cells seeded in each well. For drug treatments, drug or solvent control was added once, at the time of seeding cells for the mammosphere formation assay.
2.3 Aldeflour Assay
ALDH enzymatic activity is enriched in the breast cancer stem cell population and is used as a marker of BCSCs [201]. ALDH activity was measured using the Aldeflour assay according to the manufacturer’s protocol (StemCell Technologies) (Figure 10B).
Cell lines or mammospheres were trypsinized, filtered through a 30µm cell strainer, counted, and an equal number of cells were spun down at 800 rpm to be incubated in
Aldeflour assay buffer containing an ALDH substrate, biodipy-aminoacetaldehyde (1
µmol per 1 million cells) at 37° C for 45 minutes. As a negative control, a fraction of cells from each sample was incubated under identical conditions in the presence of
ALDH inhibitor diethylaminobenzaldehyde. Flow cytometry was used to measure
ALDH-positive cell percentage for each sample.
2.4 Inhibitors
40 γ-Secretase inhibitors L685,458 and GSI-34 were synthesized in our lab and suspended in
DMSO solvent. NOS inhibitors L- NG-monomethyl arginine (L-NMMA), 1400W, and L-
NG-nitroarginine methyl ester (L-NAME) were purchased from Sigma and suspended in
PBS pH 7.2 as a solvent. The GGT inhibitors azaserine and acivicin were purchased from
Sigma and H2O was used as a solvent.
2.5 γ-Secretase Activity Assay
γ-Secretase enzymatic activity to cleave Notch or APP substrate can be specifically and directly measured in a γ-secretase activity assay developed in our lab, as previously described (Figure 13) [276, 277]. Activity is measured by incubating γ-secretase with biotinylated recombinant APP substrate (Sb4) or Notch1 substrate (N1-Sb1). The amount of cleavage product formed (specific γ-secretase activity) is quantified using a detection mixture containing antibodies for NICD (SM320) or Aβ40 (G2-10) conjugated to
AlphaLISA acceptor beads and Streptavidin coated donor beads (Perkin Elmer) (Figure
13).
γ-Secretase activity assay reaction buffer contains 50 mM PIPES at pH 7.0, 150 mM
KCl, 5 mM CaCl2, 5 mM MgCl2, 0.25% CHAPSO, and 1 µM Sb4 or 0.4 µM N1-Sb1. In the in vitro assay, γ-secretase activity was measured in purified cell membrane (from cell lines or tissue) at a final concentration of 100 µg/mL in γ-secretase activity assay reaction buffer. In the “exo-cell” assay, γ-secretase activity was measured by directly adding γ- secretase activity assay reaction buffer to live cells to at a concentration of 500 cells/µL,
41 which causes lysis of cells during reaction incubation [278]. The reaction mixture is incubated with shaking at 37° C for 3 hours in a 96 well plate. A duplicate of each sample is also incubated with 1 µM L685,458 in order to determine the non-γ-secretase activity background signal in the assay.
Active γ-secretase complex
rNotch Biotin
γ-Secretase
rNotch Biotin
! ! ! ! NICD Biotin α-NICD Ab ! ! SA beads
AlphaLisa Detection of NICD
Figure 13: Notch-specific γ-secretase activity assay. A schematic of the γ-secretase activity assay. The specific activity of γ-secretase to cleave Notch can be directly measured in theFigure γ-secretase : Notch-basedactivity assay. A γ sample-secretase is incubated with a biotinylated recombinant Notch1 substrate. The reaction mix is then incubated and if active γ- secretase is present,activity it will assay cleave. the substrate. The amount of cleavage product formed (corresponding to the Notch-specific γ-secretase activity) can then be quantified using a detection mixture containing an NICD specific antibody that is conjugated to AlphaLISA acceptor beads and Streptavidin (SA) coated donor beads. AlphaLISA signal is used to quantify the amount of NICD formed.
42 γ-Secretase activity assay detection buffer contains 50 mM HEPES pH 7.5, 150 mM
NaCl, 0.1% BSA, and 0.1% Tween-20. For detection of NICD, the detection buffer also contains 0.2 µg/mL SM-320 antibody, 2.5 µg/mL Protein A acceptor beads and 10 µg/mL streptavidin coated donor beads. For detection of Aβ40, the detection buffer contains 1
µg/mL G2-10, 2.5 µg/mL αMouse acceptor beads, and 10 µg/mL streptavidin coated donor beads. After incubation, 20 µL of the reaction mixture for each sample is mixed with 20 µL detection buffer in a 384 well plate and incubated overnight at room temperature. The AlphaLISA signal is then detected using the EnVision multilabel plate reader (Perkin Elmer).
2.6 Western Blot and Antibodies
Cells were lysed in 1X RIPA buffer (50mM Tris pH 8.0, 150 nM NaCl, 0.1% Nonidet P-
40, and 0.5% wt/v deoxycholic acid) with protease inhibitor cocktail with PMSF (Sigma) by shaking at 4° C for 30 minutes. Lysates were centrifuged at 8,000 rpm for 5 min on a tabletop centrifuge to remove cell debris. The protein concentration was determined using the DC Protein Kit (Bio-rad). An equal amount of protein lysate was diluted to 1X in laemmli buffer, separated on an SDS-PAGE gel and transferred to PDVF-membrane.
Membranes were blocked in 5% milk TBS buffer with 0.1% Tween-20 (TBST) for 30 minutes at room temperature and then primary antibody was added in 5% milk TBST overnight at 4° C. Blots were then washed 3 times in TBST, incubated in secondary antibody 1 hour in 5% milk/TBST and developed using ECL and film.
43 For the γ-secretase activity assay, the Aβ40 specific antibody G2-10 was a gift from
Merck Research Labs and a previous lab member, Dr. Deming Chau, generated the NICD cleavage specific antibody SM-320 [277]. The antibodies used for the γ-secretase complex were: α-APH-1a (38-3600, Invitrogen), α-PS1-CTF (MAB5232, Millipore), α-
PEN-2 (18189, Abcam), α-Nct (generated in our laboratory), and α-PS1-NTF (a gift from
Dr. Min-Tain Lai at Merck Research Laboratory). The following antibodies were used for hypoxia-related proteins: α-Hif-1α (619958, BD Biosciences), α-Hif-2α (NB100-122,
Novus), α-Hif-1β (611078, BD Biosciences), α-eNOS (NB300-500, Novus), and α-iNOS
(NB300-605, Novus). The following antibodies were used for GGT: α-GGT small subunit (WH0002678M1, Sigma) and α-GGT large subunit (SAB2701966, Sigma). α-
Tubulin (ab56676, Abcam) was used as a loading control. Mouse and rabbit secondary antibodies were from GE.
2.7 Activity-based γ-Secretase Photolabeling and Affinity Capture
Since only a fraction of all the γ-secretase subunits in the cell are in an active complex, a western blot for the expression of each subunits is not necessarily representative of the amount of enzymatically active γ-secretase complex [24-26]. Instead, our lab has synthesized peptomimetic active site-directed probes that can be used to specifically determine the amount of active γ-secretase complex in a sample, as previously described
(Figure 14) [279, 280]. The probes are based on the transition state analog GSI L-
685,458 and contain a linker to a biotin moiety, which enables pull down using streptavidin beads (Figure 14). Due to the transition state analog moiety, when the
44 A" Photoactive biotin benzophenone ! !
JC-8
! biotin ! B"
GY-6
Photoactive benzophenone
C"
L685, 458
! ! Figure 14: Peptomimetic active site probes used in γ-secretase activity based pull down assays. (A) JC-8 contains a benzophenone moiety that crosslinks to PS during UV irradiation and a linker to a biotin moiety for pull down with streptavidin beads. (B) GY-6 is similar to JC-8, but has a longer linker group, which is necessary for affinity capture under non-denaturing conditions. The longer linker makes the biotin moiety available for binding to the streptavidin beads when the γ-secretase complex is intact. GY-6 also contains a disulfide bond to allow elution from streptavidin beads with β-mercaptoethanol. (C) L-685, 458 is the transition state analog, active site- directed inhibitor that JC-8 and GY-6 are based on. The hydroxyl group shown in blue interacts with the catalytic Asp residues in the active site.
peptomimetic probes are incubated with cell lysate or purified membrane they will only
associate with mature γ-secretase complexes that are in an active form (Figure 15). After
incubation, the probes (and bound γ-secretase complexes) are isolated using streptavidin
beads and then ran on an SDS-PAGE gel for analysis (Figure 15). UV irradiation of JC-8
will cause it to crosslink to the PS subunit (photolabeling) and the amount of active γ-
secretase complex can be quantified by α-PS1 western blot (Figure 14A). GY-6 can be
45 Peptomimetic active site probe biotin Peptomimetic active site probe biotin
Active γ-secretase complex
Inactive γ-secretase complex
Isolate complex with streptavidin beads
Quantify/identify proteins by western blot
Figure 15: γ-Secretase activity-based pull down assay. Peptomimetic active site probes contain the transition state analog inhibitor L-685,458 connected through a linker to a biotin moiety. The transition state analog moiety will bind to the active site of active γ-secretase complexes, but will not bind to inactive complexes. The active complexes are then isolated using streptavidin beads and quantified by western blot for γ-secretase subunits. Western blot can also identification and/or quantify proteins that associate with the complex.
utilized to pull down active γ-secretase under non-denaturing conditions without UV irradiation (affinity capture), which enables quantification of the amount of active γ- secretase (by western blot for subunits) and also identification of proteins that are bound to the γ-secretase complex (Figure 14B). For both methods, excess of the non- biotinylated inhibitor L685, 458 is always added to a duplicate sample to determine background and verify that γ-secretase pull down is specific.
In photolabeling experiments, 300 µg HeLa membrane or 1x106 cells were resuspended in 1 mL PBS containing 20 nM JC-8, 0.25% CHAPSO, and protease inhibitor cocktail
46 with PMSF (Sigma) with DMSO or 1 µM L-685,458 and incubated shaking at 37° C for
1 hour. After incubation, samples were UV irradiated at 350 nm for 35 minutes. The samples were then solubilized by dilution in 1X RIPA buffer and shaking at room temperature for 1 hour. 10 µL streptavidin ultra-link beads (Pierce) were added and samples were incubated rotating at 4° C overnight to capture complexes. The next day, the beads are pelleted and washed three times with 1X RIPA buffer, then eluted in 2X laemmli buffer by boiling at 98° C for 5 minutes. The elute was ran on an SDS-PAGE gel and a western blot for PS1-NTF was performed.
In affinity capture experiments, 5x106 MCF-7 cells were first solubilized in 1 mL PBS with 1% CHAPSO and protease inhibitor cocktail with PMSF (Sigma) by shaking at 4°C for 1 hour. Cell lysate was cleared by ultracentrifugation at 35,000 rpm for 45 minutes.
Protein was quantified using the DC Protein Kit (Bio-rad) and an equal amount of protein
(~800 µg/mL) was diluted in PBS to a final concentration of 0.25% CHAPSO. DMSO or
4 µM L-685,458 was added and the samples were incubated for 30 minutes at 37° C to pre-block. 100 nM GY-6 was then added to each sample and they were incubated at 37°
C for 1 hour. For capture, 10 µL streptavidin beads was added to each sample to be incubated overnight at 4° C. The next day, the beads were pelleted and washed with TBS buffer with 0.1% Tween-20 3 times and the samples were eluted with 30 µM β- mercaptoethanol in 2X laemmeli buffer for 10 minutes at room temperature. The elute was ran on an SDS-PAGE gel and a western blot for Hif-1α or PS1-NTF was performed.
2.8 Transient Transfection
47
All DNA constructs were purified using the HiSpeed Maxiprep kit (Qiagen). The normoxia-stable Hif-1α-Triple Mutant-Full Length-Flag-pcDNA3.1 (three point mutations at P420A, P557A, N813A, abbreviated as pcDNA3.1-Hif-1α-FL-TM), Hif-1α-
N-terminal-Flag-pcDNA3.1 (amino acid 1-364, abbreviated as pcDNA3.1-Hif-1-NTF), and Hif-1α-C-terminal-Flag-pcDNA3.1 (deletion of amino acid 10-370, abbreviated as pcDNA3.2-Hif-1α-CTF) constructs were obtained from Dr. Celeste Simon at University of Pennsylvania and have been previously described (see Figure 17, Chapter 3.2) [281].
Hif-1α-mutant bHLH-Flag-pcDNA3.1 (also provided by Dr. Celeste Simon) contains three point mutations at P420A, P557A, N813A to ensure stability in normoxia and contains four point mutations in DNA-binding residues (R24A, R26A, R27A and K29A), rendering it unable to activate transcription, as has been previously described (see Figure
17, Chapter 3.2) [282]. MCF-7 cells were seeded in a 6-well plate and then transfected 16 hours later with the normoxia-stable Hif-1α constructs using Fugene-6 (Promega) according to the manufacturer’s instructions. 24 hours after transfection, the cells were trypsinized and reseeded in a 96 well plate at a density of 10,000 cells/well for the γ- secretase activity assay. After 48 hours of transfection, cells were washed with PBS and the exo-cell γ-secretase activity assay was performed (as previously described in
Methods).
2.9 Generation of Stable Cell Lines
48 All shRNA constructs (Sigma) and CRISPR constructs were purchased from the RNAi
Core at Memorial Sloan Kettering Cancer Center and purified using the HiSpeed
Maxiprep kit (Qiagen). The shRNA constructs in the pLKO.1-puro vector (Sigma) targeted to: a control non-targeting scramble sequence (SHC002, Sigma), HIF1A (Hif-
1α), ARNT (Hif-1β), EPAS (Hif-2α), and NOS2 (iNOS) for MCF-7 cells and GGT1
(GGT1) for HK-2 cells (all from Sigma). The constructs and lentiviral packaging mix
(Sigma) were co-transfected in Hek293T cells using Lipofectamine 2000 (Invitrogen) to make viral particles, according to the manufacturer’s instructions. Media containing virus was then added to cells with 4 µg/mL hexamine bromide. 48 hours post- transduction, the cells were selected with 2 µg/mL puromycin (Sigma) for 14 days.
Protein knockdown was confirmed by RT-PCR and western blot.
For CRISPR knockout cell line generation, MCF-7 cells were transfected according to the manufacturer’s instructions using Lipofectamine LTX (Invitrogen) with px459 vector containing Cas9 and guide RNAs (sgRNAs) with a random, non-targeting sgRNA sequence or exon 2 of the HIF1A gene (Addgene). 2 µg/mL puromycin was added to cells 48 hours post-transfection. After 14 days of selection, surviving single cell clones were picked and knockout was confirmed by western blot.
2.10 Real-time Polymerase Chain Reaction (RT-PCR)
RNA from breast cancer cell lines was extracted using the RNeasy Mini kit according to the manufacturer’s instructions (Qiagen). RNA was quantified using the Nanodrop
49 machine and 1 µg of RNA was reverse transcribed to cDNA using the Superscript III
First Strand Synthesis kit according to the manufacturer’s instructions (Invitrogen).
Expression of mRNA was measured using the Fast 7500 Real-time PCR system (Applied
Biosystems) with FAM-labeled Taqman probes for the gene of interest (Applied
Biosystems) and Taqman Universal PCR Mastermix (Roche). Gene expression was normalized to the β-actin housekeeping gene. The taqman probes used in the experiments are: BACT (Hs1060665_g1), HES1 (Hs00172878_m1), HEY1
(Hs01114113_m1), SLC2A1 (Hs00892681_m1), VEGFA (Hs00900055_m1), NOS2
(Hs1075529_m1), NOS3 (Hs01574659_m1) and GGT1 (Hs00980756_m1) (Applied
Biosystems).
2.11 Microarray
4T1 mouse breast cancer cells were seeded in 12 well plates in triplicate. The following day, cells were treated with either DMSO or 1 µM GSI-34 and incubated at 37° C with either 21% or 1% O2. 48 hours after treatment, RNA was extracted from cells and cDNA was generated as described above. Gene expression was determined using the
Affymetrix microarray platform at the MSKCC Integrated Genomics Organization core facility and the data was analyzed at the MSKCC Bioinformatics core facility. Gene set enrichment analysis (GSEA) is an analytic method to extract biological insight from genomewide RNA expression analysis [283]. The method uses gene sets (groups of genes that share a common biological function, chromosomal location, or regulation) from an annotated database to compare to the ranked list of gene expression changes from
50 microarray data. GSEA analysis was used to analyze the results of our microarray in order to determine which gene sets are affected by hypoxia and/or GSI-34 treatment in
4T1 cells.
2.12 Nitric Oxide (NO) Assay
Intracellular NO levels of breast cancer cell lines were measured in the Muse™ Nitric
Oxide Kit using the Muse™ Cell Analyzer (EMD Millipore). The assay combines a membrane permeable reagent, DAX-J2 Orange, which generates a highly fluorescent product upon NO oxidation inside the cell, with the cell viability dye 7-AAD. Live cells were incubated with the kit assay buffer for 1 hour at 37° C and then sorted in the MUSE by the fluorescent signal of both the DAX-J2 Orange and 7-AAD dye. The assay was
+ - used to determine the percentage of live and dead cells that are NO or NO .
2.13 Apoptosis Assay
Apoptosis in breast cancer cell lines was measured in the Muse™ Annexin V & Dead
Cell Assay on the Muse™ Cell Analyzer (EMD Millipore). The assay is based on the detection of phosphatidylserine (PS) on the surface of apoptotic cells, using fluorescently labeled Annexin V in combination with the dead cell marker, 7-AAD. Cells were incubated with the assay buffer for 20 minutes at room temperature and then sorted on the MUSE™ based on the fluorescent signal of both Annexin V and 7-AAD. The assay was used to quantify the percentage of live, early and late apoptotic, and dead cells.
51
2.14 Immunohistochemistry
Mammospheres were washed with phosphate buffered saline (PBS) and then fixed in 4% paraformaldehyde (PFA) for 30 minutes at room temperature. After fixation, mammospheres were stored in 70% ethanol. Sectioning and staining of the mammospheres was done with the Molecular Cytology Core Facility at MSKCC.
Mammospheres were embedded in paraffin wax, sectioned into 4 µm slices, and mounted on glass slides. Slides were stained in an automated machine with DAPI (to stain cell nuclei) and fluorescent-conjugated antibodies to Hif-1α, pimonidazole, or an IgG negative control.
During the pimonidazole staining to detect hypoxia, mammospheres were incubated at
37°C for 16 hours at either 21% or 1% O2. For both conditions, either PBS or 200 µM pimonidazole (Sigma) was added to media and mammospheres were returned to the 37°
C incubator for 2 hours. Mammospheres were then washed with PBS, and fixed and stained as previously described.
2.15 Membrane Preparation
To generate purified HeLa membrane for use as a source of active γ-secretase in in vitro assays, a 10 L pellet of HeLa S3 cells (frozen) was purchased from Biovest. HeLa pellet was thawed on ice and suspended in 30 mL 2-(N-morpholino)ethanesulfonic acid (MES)
52 buffer. For isolation of membrane from tissues, the tissue was first homogenized in MES buffer (10mL/gram tissue) using a mechanical PowerGen model 125 handheld homogenizer (Fisher Scientific). MES buffer consisted of 50mM MES pH 6.0, 150 mM
KCl, 5mM CaCl2, 5 mM MgCl2, 100 µM PMSF, and protease inhibitor cocktail (Sigma).
Samples were then lysed in the MES buffer using a french press (Spectronic Instruments) to mechanically homogenize the cells. The lysate was spun down at 800 g for 10 minutes at 4° C to remove cell debris. The supernatant was removed and ultracentrifuged at
35,000 rpm for 1 hour at 4° C to pellet the membrane fraction. The membrane pellet was resuspended in MES buffer and protein concentration was determined using the DC
Protein Kit (Bio-rad).
2.16 Purified GGT protein
GGT purified from bovine kidneys (Cat. 315-10), GGT purified from porcine kidney
(Cat. 315-20) and GGT purified from human liver (Cat. 320-20) were purchased from
Lee Biosciences in lyophilized form.
Recombinant human GGT1 (rGGT) purified from yeast was a generous gift from Dr.
Marie Hanigan at University of Oklahoma Health Sciences Center. Briefly, the soluble ectodomain (residues 28-569) of human GGT1 was expressed in the yeast strain Pichia pastoris X-33 with a tobacco etch virus (TEV) protease cleavable polyhistidine (His) tag and affinity purified using a Nickel column [272]. After purification, the His tag was
53 removed with TEV and the untagged rGGT was re-run over the nickel column to purify, dialyzed, and concentrated to a final concentration of ~ 10mg/mL.
2.17 GGT Activity Assay
The GGT activity of purified GGT and HK-2 cell lysates was measured using the
γ-Glutamyltransferase (GGT) Activity Colorimetric Assay Kit (Sigma), according to the manufacturer’s protocol. In the assay, GGT activity is proportional to the transfer of the
λ-glutamyl group of the GGT substrate, L-λ-Glutamyl-p-nitroanilide, to H2O as an acceptor, liberating the product p-nitroanilide (pNA), a compound that can be detected at
418 nm. Briefly, samples were incubated in GGT Activity Assay Buffer with L-λ-
Glutamyl-p-nitroanilide at 37° C for 10 to 120 minutes and then emission at 418 nm was measured on the EnVision multilabel plate reader (Perkin Elmer). A pNA standard curve was used to quantify the signal. GGT activity was expressed as pmol of pNA produced per minute.
2.18 Purified γ-Secretase Complex
Purified γ-secretase complex was a generous gift from Dr. Sangram Sisodia at the
University of Chicago. Briefly, Tandem Affinity Purification- Aph1a, Nicastrin, Pen-2,
PS1 (TAP-ANPP) cells were created by transfecting Hek293T cells with constructs expressing N-terminal TAP-PS1, Aph1a, C-terminal Nct-CT11, and C-terminal Pen-2-
CT11 [284, 285]. The TAP-ANPP cells are cultured in suspension to expand, and then
54 collected and the membrane fraction is isolated. TAP-PS1 was purified using IgG- sephrose beads and eluted by TEV cleavage. The TEV-cleaved elute was then incubated with wheat germ aggulitin (WGA) beads, washed, eluted, added to Calmodulin beads, washed, and then the final purified mature γ-secretase complex was eluted.
2.19 Zebrafish Studies
A Danio rerio zebrafish transgenic AB strain with stable expression of a GFP-expressing construct with a NICD-driven promoter was used in all experiments. Zebrafish were housed in a temperature (28.5°C) and light-controlled (14 hours on, 10 hours off) room at a density of 10 fish per liter and fed 3 times per day. Embryos were obtained through natural mating and maintained in a 28.5° C incubator for up to 5 days post fertilization
(dpf). Approximately 1 nL of 50 ng/uL human GGT1 mRNA or 100 ng/uL Ubiquiutin- hGGT1-Tomato DNA plasmid was injected into the cell of one cell stage embryos.
Approximately half of each clutch was not injected with mRNA or plasmid as a control.
Fluorescence imaging of the injected and control embryos was performed at 48 hours post fertilization (hpf). For imaging, fish were anesthetized with Tricaine and placed onto an agarose-coated petri dish. The fish were imaged using a Zeiss Axio Zoom V16
Fluorescence Stereo Zoom Microscope. Groups of 5 fish were successively imaged using brightfield, GFP, and Rhodamine filter sets. The exposure times for each group were determined at for the first image and kept fixed throughout the entire experiment. The mean fluorescence intensity for each fish was quantified using the raw image files (CZI) and Zeiss Zen software by outlining each fish. To measure background fluorescence, the
55 mean fluorescence intensity was measured in an identical size area that did not contain any fish.
2.20 Statistical Analysis
All experiments were tested for significance using the two-tailed Student’s t-test.
A p value of less than or equal to 0.05 was considered significant. All data is represented as the mean value ± standard deviation, unless otherwise specified.
For graphs, * = p ≤ 0.05, ** = p ≤ 0.01, *** = p ≤ 0.001
56 CHAPTER 3
Non-transcriptional role of Hif-1α in breast cancer stem cells
3.1 Background
Tumor hypoxia contributes to the metastatic progression of breast cancer [66, 67, 85,
88-90]. It has been reported that hypoxia can promote Notch signaling and increase levels of the γ-secretase cleaved product NICD [169, 170, 176]. However, the effect of hypoxia on γ-secretase activity had not been previously investigated. In a recent study published in our lab, we showed that γ-secretase activity of breast cancer lines was enhanced under hypoxia [275]. In four breast cancer cell lines cultured under hypoxia, there was a significant increase in our Notch-based γ-secretase activity assay. Furthermore, hypoxia did not elevate the expression of γ-secretase subunits, but rather directly increased the amount of active γ-secretase complex formed.
The effect was dependent on Hif-1α since knockdown of Hif-1α completely prevented the increase in γ-secretase activity during hypoxia in breast cancer cells [275].
Using activity-based pull down assays and traditional IP methods, Hif-1α was shown to directly bind to the active enzyme complex to regulate γ-secretase activity during hypoxia. Biochemical assays confirmed that purified, recombinant Hif-1α alone was sufficient to stimulate γ-secretase activity in MCF-7 cell lysate, as well as in purified
HeLa membrane [275]. This study led us to our current model, depicted in Figure 16, which shows that, during hypoxia, Hif-1α binds to the γ-secretase complex, resulting in an increase in enzymatic activity, NICD production, and downstream Notch signaling.
57 Notch γ-Secretase Hypoxia O2
HIF-1α O2 NICD HIF-1α HIF-1α PHD HIF-1α HIF-1α HIF-1α
Metastasis Migration Invasion CSL Differentiation
FigureFigure 16: :Hypothesized Model. Hif-1 α Model binds. to Hif γ--secretase1α binds to to stimulate γ-secretase Notch to stimulatesignaling. Notch signaling.
The role of γ-secretase in hypoxia-inducted metastasis was investigated in cell and mouse models using GSI-34, a sulfonamide-based GSI developed in our lab [279, 286].
Treatment with GSI-34 prevented hypoxia-induced invasion of MDA-MB-231 and 4T1 breast cancer cells in the Matrigel assay and wound healing assay, indicating that γ- secretase plays a critical role in the migration and invasion of breast cancer [275].
Finally, GSI-34 treatment and knockdown of Notch signaling significantly reduced distal metastasis to the lung in the 4T1 mammary fatpad metastasis mouse model, but had a minimal effect on growth of the primary tumor [275].
3.2 Results
58 Hif-1α is sufficient to stimulate γ-secretase activity in breast cancer cells during
normoxia
γ-Secretase activity is stimulated during hypoxia, and this effect is dependent on
Hif-1α expression [275]. In order to determine if low oxygen levels are required to
stimulate γ-secretase activity during normoxia, or if Hif-1α expression in normoxic cells
DNA binding domain P402A P564A N803A
A" Hif-1α Triple Mutant (TM) bHLH PAS TAD IH TAD
P402A P564A N803A
B" Hif-1α CTF (Δ10-370) TAD IH TAD
DNA binding domain
C" Hif-1α NTF (1-365) bHLH PAS
! DNA binding domain P402A P564A ! N803A
D" Hif-1α mutant bHLH bHLH PAS TAD IH TAD
Figure 17: Map of Hif-1α constructs used in transient overexpression studies. (A) pcDNA3.1-Hif-1α-FL-TM expresses a normoxia-stable, full length (FL), triple mutant (TM) Hif-1α construct with alanine mutations in the three oxygen-sensing, hydroxylated residues (shown in red). (B) pcDN3.1-Hif-1α-CTF(Δ10-370) expresses only the C-terminal fragment of Hif-1α, which includes the N- and C- TAD domains and the IH domain. (C) pcDNA3.1-Hif-1α-NTF(1-365) expresses only the N-terminal fragment of Hif-1α, which contains the bHLH and PAS A and PAS B domains. (D) pcDNA3.1-mutant bHLH expresses a normoxia stable, full length Hif-1α construct with four mutations in the bHLH domain (R24A, R26A, R27A and K29A) to prevent DNA binding and activation of target genes. All constructs have a C-terminal FLAG tag for detection.
59 is sufficient, we transiently overexpressed an oxygen-stable Hif-1α construct (pcDNA3.1-
Hif-1α-FL-TM-FLAG) in MCF-7 cells. Hif-1α-FL-TM is a full length Hif-1α construct that has alanine mutations of the three residues (P420A, P557A, and N813A) that are hydroxylated by PHD and FIH to inhibit Hif-1α during normoxia, rendering its expression and activity insensitive to oxygen levels (Figure 17A). Expression of pcDNA3.1-Hif-1α-FL-TM in MCF-7 cells significantly increased γ-secretase activity in the Notch exocell activity assay, as compared to pcDNA3.1 vector only (Figure 18A&C)
[275].
A" B" L-685, 458 !""""""+" !""""""+" !""""""+" !"""""""+"
PS1-NTF 800 * ** 600 ns 400
(A.U.) Input: C" kDa 200 150 -Secretase activity
γ 100 Flag 0 75 50 -NTF -CTF 37 vector -FL-TM α α α PS1-NTF Hif-1 Hif-1 Hif-1
Figure 18: Hif-1α N-terminus is sufficient to stimulate γ-secretase activity during normoxia. (A) Transfection of MCF-7 cells with full-length and N-terminal portion of Hif-1α stimulated activity in the Notch-based γ-secretase activity assay, but the C-terminal fragment of Hif-1α had no effect. (B) Transfection of MCF-7 cells with full-length and N-terminal portion of Hif-1α increased the amount of active γ-complex detected by affinity capture with GY-6 (PS1-NTF), but the C- terminal fragment of Hif-1α did not. (C) All three Hif-1α constructs were expressed at similar levels in MCF-7 cells and did not affect expression of PS1 [275]. Experiments performed by Alissa Brandes.
60 Expression of Hif-1α-FL-TM in MCF-7 cells also significantly increased the amount of active γ-secretase complex as detected in our GY6 activity-based pull-down assay (Figure 18B & 19) [275]. As compared to vector only, there in the amount of active γ-secretase complex in the cell when Hif-1α-FL-TM was overexpressed (Figure
18B &19) [275]. At the same time, Hif-1α-FL-TM was specifically pulled down with the
γ-secretase complex (Figure 19), indicating that Hif-1α expression during normoxia is sufficient for Hif-1α to bind to the complex and stimulate its activity [275].
L-685,458: !""""""+" "!"""""""+" Input:
Flag
PS1-NTF
Figure 19: Hif-1α binds to and enhances active γ-secretase complexes when expressed during normoxia. MCF-7 cells were transfected with normoxia-stable Hif- 1α and the amount of active γ-secretase complex was determined by affinity capture with GY-6 to pull down active forms of the γ-secretase complex. Expression of Hif- 1α increased the specific pull down of PS1 from active complexes, but did not affect the overall expression of PS1. Hif-1α was also specifically pulled down with the active γ-secretase complex, indicating that Hif-1α directly associates with the complex, even during normoxia [275]. Experiments performed by Alissa Brandes
In order to begin to assess where the γ-secretase binding site is on Hif-1α, we also over-expressed the N- or C-terminal fragments of the Hif-FL-TM construct in MCF-7 cells in order to assess their effect on γ-secretase and determine which domains of Hif-1α associate with the complex (Figure 18B). Diagrams of the N-terminal Hif-1α-NTF and
61 C-terminal Hif-1α-CTF are depicted in Figure 17B&C. When expressed in MCF-7 cells,
Hif-1α-NTF was able to stimulate γ-secretase activity as compared to pcDNA3 vector, to a similar degree as Hif-1α-FL-TM, which was observed in both our γ-secretase activity assay and our activity-based pull down assay (Figure 18A-C). However, expression of
Hif-1α-CTF had no significant effect on γ-secretase activity (Figure 18A-C), indicating that the γ-secretase binding domain on Hif-1α lies within the first 365 amino acids of the protein.
Transcriptional activity of Hif-1α is not required to stimulate γ-secretase activity in breast cancer cells
According to our hypothesized model (Figure 16), Hif-1α directly associates with the γ-secretase complex to stimulate its activity. However, this is a non-canonical role for Hif-1α, which is a transcription factor that has previously been shown to regulate signaling pathways via transcriptional activation of Hif-1α target genes. If Hif-1α stimulates γ-secretase by associating with the complex, its transcriptional activity should not be required.
In order to prove that Hif-1α transcription is not required, we first created stable
Hif-1β shRNA knockdown MCF-7 cell lines (Figure 20A). Hif-1β is the binding partner of Hif-1α and this heterodimer formation is required for Hif-1α to travel to the nucleus and bind DNA to activate target gene transcription (Figure 6). Therefore, Hif-1α will be expressed in the Hif-1β knockdown cell lines, but Hif-1α will not be able to activate transcription. Knockdown on Hif-1β had no significant effect on the stimulation of γ-
62 secretase that occurs during hypoxia (Figure 20B), indicating that Hif-1α transcription is not required [275].
C" A" Flag
PS1-NTF
2000 B" D" * 1500
1000 (A.U.)
500 -Secretase activity γ
0
HLH β
Empty Vector-mutant α Hif1
Figure 20: Hif-1α transcriptional activity is not required to stimulate γ-secretase activity in breast cancer cells. (A) Hif-1β was stably knocked down by shRNA in MCF-7 cells, as compared to scramble shRNA control cells. (B) Stable knockdown of Hif-1β had no significant affect on stimulation of the γ-secretase activity assay in MCF-7 cells exposed to hypoxia. (C) The FLAG-tagged, normoxia stable Hif-1α mutant bHLH domain construct is stably expressed in MCF-7 cells. (D) Transfection of MCF-7 cells with Hif-1α-mutant bHLH, which cannot bind DNA to activate transcription, significantly increases activity in the Notch-based γ-secretase activity assay. N=normoxia, H=hypoxia [275]. Experiments in Figure 20A&B performed by Jennifer Villa and experiments in Figure 20C&D performed by Alissa Brandes.
To further verify that Hif-1α transcriptional activity is not required, we also expressed a transcriptionally inactive form of Hif-1α, Hif-1α-mutant bHLH, in MCF-7 cells (Figure 20C) [275]. pcDNA3.1-Hif-1α-mutant bHLH is a form of Hif-1α-FL-TM
63 that contains four alanine mutations in its DNA-binding residues (R24A, R26A, R27A and K29A) (Figure 17D), which renders it unable to bind DNA and therefore activate transcription of target genes [282]. Overexpression of Hif-1α-mutant bHLH significantly increased γ-secretase activity as compared to pcDNA3.1 vector only (Figure 20D) [275].
γ-Secretase activity was increased to a similar degree as when Hif-1α-FL-TM was overexpressed (Figure 18A), indicating that Hif-1α transcriptional activity is not required for this activation [275].
Inhibition of γ-secretase reverses many of the gene set changes caused by hypoxia
In our previous study, treatment with GSI-34 was able to block hypoxia-induced increases in migration and invasion assays in breast cancer cell lines, as well as significantly reduce metastasis to the lung in the 4T1 breast cancer mouse model [275].
However, while GSI-34 greatly reduced lung metastasis, it had only minimal effects on growth of the primary tumor [275]. To investigate which cellular pathways GSI-34 is targeting, we did a microarray to compare gene expression changes in the 4T1 mouse breast cancer cell line in response to GSI-34 treatment under both normoxic and hypoxic conditions. 4T1 cells were treated with DMSO for 24 hours at 21% O2 and 1% O2 as a control. 4T1 cells were also treated with GSI-34 for 24 hours at 21% O2 and 1% O2. The change in gene expression between each of the different conditions was determined from the microarray data.
We analyzed our data using Gene Set Enrichment Analysis (GSEA) to determine which pathways are altered by GSI-34 treatment. GSEA is an analytic method to extract
64 A" B" GSI-34 vs WT # Altered gene sets in Hypoxia
DMSO GSI-34
587 159 22
Figure 21: GSI-34 prevents upregulation of many gene sets that occurs during hypoxia. (A) Gene set enrichment analysis (GSEA) enrichment plot depicting the correlation between genes that are upregulated in hypoxic GSI-34 treated cells (as compared to normoxic GSI-34 treated 4T1 cells) with the MANOLO_HYPOXIA_DOWN gene set, which includes genes that are downregulated during hypoxia. There is a very significant positive correlation, meaning that GSI-34 treatment upregulated many genes that are typically downregulated by hypoxia (B) A comparison of the significantly upregulated gene sets in hypoxic 4T1 cells versus normoxic 4T1 cells that were treated with either DMSO or 1 µM GSI-34, as determined by GSEA.
biological insight from genomewide RNA expression analysis [283]. The method uses gene sets (groups of genes that share a common biological function, chromosomal location, or regulation) from an annotated database to compare to the ranked list of gene expression changes from microarray data and determines gene sets that are significantly correlated to the ranked list.
65 The biggest number of significantly upregulated gene sets occurred when comparing normoxia to hypoxia in DMSO treated cells (756 gene sets upregulated by hypoxia)
(Figure 21B). Treatment of with GSI-34 during normoxia had less of an effect, as there were 139 significantly downregulated gene sets in GSI-34 treated normoxic cells as compared to DMSO treated normoxic cells. Quite interestingly, there was a drastically reduced number of significant upregulated gene sets when comparing normoxia to hypoxia in GSI-34 treated cells (181 gene sets upregulated by hypoxia) (Figure 21B). A comparison of the gene sets significantly upregulated by hypoxia in DMSO treated cells versus GSI-34 treated cells reveals that GSI-34 prevented upregulation of a majority of the gene sets that are increased by hypoxia (Figure 21B). Therefore, GSI-34 treatment reversed the gene expression profile changes that occur during the normoxia to hypoxia transition. Indeed, the upregulated gene set with the most significant correlation to our data in normoxic versus hypoxic GSI-34 treated cells was the
MANOLO_HYPOXIA_DOWN gene set, which includes genes that have been experimentally shown to be downregulated during hypoxia (Figure 21A). This correlation means that GSI-34 treatment upregulated many genes that are typically downregulated by hypoxia.
We examined the pathways represented in the 587 hypoxic gene sets changes that are altered by GSI-34 treatement. Many of the gene sets that were prevented by GSI-34 in hypoxic 4T1 cells are associated with stem cell signaling pathways, including Wnt, Shh,
Myc, TGF-β, and MAPK. These pathways have also been shown to be important regulators of the BCSC population. Therefore, we decided to investigate if GSI-34
66 treatment affects invasion, migration and metastasis of breast cancer by targeting the
cancer stem cell population.
GSI-34 specifically inhibits proliferation of the breast cancer stem cell population in cell
lines
B" A" DMSO 1uM GSI-34
O NH O S Cl N S MCF-7 H O O F 150 GSI-34
150 C" D" 100 150 100 n.s. DMSODMSO n.s. n.s. 100 5 µMGSI-345 GSI µM 34 GSI 34
(% (% DMSO) 50 (% (% DMSO) 50 50 *** ** *** # of cells# of (% control)
Mammosphere forming efficiency efficiency forming Mammosphere 0 0 0 1 5 *** ** *** 2.5 BT20 MCF-7 uM GSI-34
Mammosphere forming efficiency efficiency forming Mammosphere 0 MDA-MB-157 Figure 22: GSI-34 prevents formation of mammospheres. BT20 MCF-7
Figure 22:MDA-MB-157 GSI-34 prevents formation of mammospheres. (A) Addition of 1µM GSI- 34 to the MCF-7 mammosphere formation assay completely abolished formation of mammospheres. (B) Chemical structure of GSI-34. (C) Treatment with GSI-34 significantly decreased mammosphere formation efficiency in MCF-7, MDA-MB-157 and BT20 breast cancer cell lines. (D) GSI-34 treatment of adherent MCF-7 cells did not significantly affect cell proliferation.
The mammosphere formation assay has been used to assess the cancer stem cell
population of both primary tumors and breast cancer cell lines [199]. In this assay, the
67 tumor-initiating potential of a cancer cell population is assessed by seeding cells in suspension with defined growth factor media at clonal density and then assessing the percent of cells able to form mammospheres after 10 days. Consistent with previous studies, GSI-34 completely abolished the formation of primary and secondary mammospheres in MCF-7, BT-20 and MDA-MB-157 cell lines (Figure 22A-C). Cells were seeded in a mammosphere formation assay and treated with either DMSO or GSI-
34 for 10 days, and the number of spheres formed per total cells seeded in each well was used as the mammosphere formation efficiency (MFE). At the same time, treatment of adherent MCF-7 cells with DMSO or GSI-34 did not significantly affect cell proliferation
(Figure 22D). These data indicate that the Notch pathway is specifically necessary for the survival and proliferation of the tumor-initiating cell population.
We also investigated the effect of GSI-34 on mammospheres that had grown to full size to determine if GSI-34 only affects the first stages of mammosphere formation, or whether it has a general effect on proliferation of the mammosphere cell population.
MCF-7 cells were grown for 10 days and then treated for 5 days with either one dose of
DMSO or 5 uM GSI-34. Treatment with GSI-34 caused a dissociation of mammospheres
(Figure 23A). The effect on cell viability was determined using the MUSE Apoptosis
Assay, which utilized Annexin-5 dye along with a cell viability dye and flow cytometry- based methods. Treatment of the grown mammospheres with GSI-34 caused a decrease in the percentage of live cells, and an increase in the percentage of early and late apoptotic cells (Figure 23B).
68 A" DMSO 5uM GSI-34
80 B"
60 P=0.06 n.s. Live cells Early Apoptosis 40 ** Late Apoptosis n.s. 20 % Cell Population Cell %
0
DMSO
5uM GSI-34
Figure 23: GSI-34 induces apoptosis in the mammosphere cell population. (A) MCF-7 cells were cultured as mammospheres for 10 days, and then treated with DMSO or 5 µM GSI-34. (B) Treatment of MCF-7 mammospheres with GSI-34 decreased the percentage of live cells and increased the percentage of early and late apoptotic cells.
The cancer stem cell identity of the mammospheres used in our experiments was cross-validated using another marker for breast cancer stem cells, ALDH activity. The
Aldeflour Assay uses an ALDH substrate that fluoresces and is retained in the cell upon activation by ALDH. Adherent and mammosphere MCF-7 and BT-20 cells were incubated with Aldeflour substrate and flow cytometry was performed to determine the percentage of live cells positive for ALDH activity. For both cell lines, there was a significant increase in the percent of ALDH+ cells (Figure 24), supporting that the
69 A B MCF7 Adherent BT20 MCF7 4 15
3 * 10
2 SSC-A 5 1 ALDHbr % cells Aldeflour + Aldeflour % cells 0 AldeFlour+ % cells 0 0.57
FITC: ALDEFLOUR-BIOPY
Adherent Adherent MCF7 Mammospheres
Mammosphere Mammosphere C Aldeflour Assay
250 Adherent
200 Mammosphere SSC-A ALDHbr 150 21.5 100
50 FITC: ALDEFLOUR-BIOPY Mean Flourescence Intensity (% of DEAB) (% of Intensity 0
MCF7 BT20
Figure 24: ALDH activity is increased in mammospheres. (A) There is an increase in the percentage of Aldeflour+ cells in BT20 and MCF-7 mammospheres detected in the Aldflour Assay. (B) Representative flow cytometry data from the Aldeflour assay of MCF-7 adherent cells and mammospheres. (C) The mean fluorescence intensity (based on median value) of the cell population as compared to the DEAB negative control for adherent and mammosphere cells of both the MCF-7 and BT20 cell lines.
mammospheres represent a BCSC population.
γ-Secretase activity increases during mammosphere formation
Since γ-secretase activity is increased during hypoxia to upregulate Notch and
downstream metastatic processes, and the proliferation of mammospheres is dependent
on γ-secretase activity, we hypothesized that γ-secretase is activated in mammospheres to
enhance Notch signaling and proliferation of the BCSC population. γ-Secretase activity
70 was measured using the Notch exocell activity assay and activity-based photolabeling.
MCF-7, BT-20 and MDA-MB-157 cell lines were cultured adherently (under typical cell culture conditions) or as mammospheres in a defined-growth factor, suspension media.
Both adherent cells and mammospheres were trypsinized, counted, and an equal number of cells was spun down and added to the γ-secretase exocell activity assay. Samples were also normalized to total protein concentration. In all of the cell lines, γ-secretase activity was significantly higher (from 2-4 fold) in cells cultured as mammospheres than in the same cell line cultured under adherent conditions (Figure 25).
Activity-based photolabeling of the γ-secretase complex was also used to measure the amount of active γ-secretase complex. Active γ-secretase complexes were crosslinked to JC-8 with UV radiation, isolated by pull-down with strepavadin beads, and quantified by Western blot for PS1-NTF. In all of the cells lines, there was no change in the overall protein expression of any of the γ-secretase subunits in the same cell line cultured adherently as compared to when cultured as mammospheres (Figure 26).
However, there was an increase in the amount of active γ-secretase complex (detected by activity-based photolabeling) when cells were cultured as mammospheres compared to the same cell line grown in adherent flasks (Figure 27), indicating that γ-secretase is activated by some post-translational mechanism in the mammosphere cell population.
71 500 500*** *** 400 *** 400 Adherent Mammosphere 300 300 ** Adherent ** 200 Mammosphere 200 ** (% adherent) 100 100 -Secretase Activity (AU) 0 γ -Secretase (% control)Activity -Secretase
γ 0 BT20 MCF-7
MCF-7 MDA-MB-157 BT-20
Figure 25: γ-SecretaseMDA-MB-157 activity is increased in mammospheres. There is a significant increase in the Notch-based γ-secretase activity assay in cells cultured as mammospheres, as compared to the same cell line cultured adherently.
MCF-7 MDA-MB-157 BT-20
PS1-NTF
PS1-CTF
NCT
Aph1a
Pen2
Tubulin
Figure 26: Expression of γ-secretase subunits is the same in adherent and mammosphere cells. There is no change in the expression of any of the γ-secretase subunits between adherent and mammosphere culture conditions in MCF-7, MDA- MB-157 and BT20 cell lines, as detected by western blot.
72 400 *
L-685, 458 -- + -- + 300
PS1-NTF 200 Signal (AU) PS1-NTF 100 (Input) 0 Adherent Mammosphere Adherent
Mammosphere
Figure 27: The amount of active γ-secretase complex is increased in mammospheres. There is a significant increase in amount of active γ-secretase complex detected by activity-based photolabeling with JC-8 in the MCF-7 mammosphere cell population, as compared to adherent MCF-7 cells. The graph on the right is the relative band intensity quantification of PS1-NTF from all JC8 photolabeling experiments in adherent and mammosphere MCF-7 cells.
As a control, adherent MCF-7 cells were cultured in DME-HG: F-12 media
(typical media used for adherent cell culture) or mammosphere culture media for 72
hours, and then γ-secretase activity was measured in the activity assay. However,
mammosphere media had no significant effect on the γ-secretase activity of adherent
MCF-7 cells, indicating the increased γ-secretase activity in mammospheres is likely due
to changes in the MCF-7 cell population during mammosphere formation, rather than an
effect due solely to the mammosphere media (Figure 28).
73 20000 ns
15000
10000
5000 -Secretase Activity (AU) γ 0
Normal Media
Sphere Media (+GF)
Figure 28: γ-Secretase activity is not affected by growth factor defined media. Incubation of adherent MCF-7 cells in mammosphere media does not affect activity in the Notch-based γ-secretase activity assay.
Hif-1α activates γ-secretase activity in mammospheres
γ-Secretase activity can be modulated by different proteins that associate with the
complex to regulate its activity [20]. We have shown previously that, during hypoxia,
Hif-1α acts as a modulatory subunit of the γ-secretase complex to increase the formation
of active complexes and stimulate NICD production [275]. However, while Hif-2α plays
an important role in some cancers, we only investigated the Hif-1α isoform in our
previous study. In glioma neurospheres, Hif-1α and Hif-2α differentially regulate Notch
signaling and glioma stem cell growth in an opposing manner [178]. Hif-1α and Hif-2α
also have opposing or redundant roles as tumor suppressors or activators, depending on
the context and tissue type [96, 287]. While we have previously shown that Hif-1α is
required for activation of γ-secretase during hypoxia, the role of Hif-2α remains
74 unknown. The exact relationship between Hif-1α and Hif-2α signaling has also not been
previously investigated in the mammosphere BCSC model. Therefore, we investigated
whether or not Hif-2α acts in a similar manner as Hif-1α to regulate γ-secretase activity
and BCSC proliferation.
A" B"
300 ** Adherent (H) Adherent (H) ** Normoxia Hif-2α Hif-1α 200 ! Hypoxia
n.s. ! PS1 PS1 100 ! ! Tubulin Tubulin ! 0 -Secretase Activity (% normoxia) γ ! ! shRNA shRNA α α! Hif-1 Hif-2 ! scramble shRNA ! Figure 29: Hif-1α, but not Hif-2α, is required for the stimulation! of γ-secretase activity during hypoxia. (A) Stable knockdown of Hif-1α and Hif! -2α was achieved with shRNA in MCF-7 cells. Cells were cultured at 1% O2 for 16 hours prior to lysis to detect Hif-α knockdown. (B) MCF-7 cells were cultured at 1% O2 for 16 hours, and then a Notch exocell activity assay was performed. Hypoxia significantly increased the activity of MCF-7 cells but in Hif-1α knockdown cells, no significant increase in γ-secretase activity was observed. Hif-2α knockdown cells still have a significant increase in γ-secretase activity during hypoxia.
To determine if Hif-2α also modulates γ-secretase activity, we created both Hif-
1α and Hif-2α knockdown MCF-7 cell lines using shRNA, which stably decreased Hif-1α
or Hif-2α expression under hypoxia, as compared to a scramble shRNA control (Figure
29A). These lines were then cultured either in normoxia or at 1% O2 for 16 hours and γ-
secretase activity was determined using Notch exocell activity assay. Consistent with
75 previous results, γ-secretase was activated during hypoxia in a Hif-1α dependent manner
(Figure 29B). However, knockdown of Hif-2α did not affect the activation of γ-secretase during hypoxia, indicating that the activation of γ-secretase is a Hif-1α isoform-specific process (Figure 29B).
MCF-7 MDA-MB-157 BT-20 N H N H N H
Hif-1α
Hif-2α
Tubulin
Figure 30: Expression of Hif-1α, but not Hif-2α, is increased in mammospheres. MCF-7, MDA-MB-157, and BT-20 cells were cultured either adherently or as mammospheres (both in normal oxygen conditions) and then lysed to western blot for Hif-1α and Hif-2α. Tubulin was used as a loading control. Adherent cells of each cell line were also cultured at 1% O2 for 16 hours prior to cells lysis as a positive control for Hif-α expression.
Since Hif-1α activates γ-secretase during hypoxia, we hypothesized that Hif-1α is responsible for the increase in γ-secretase activity during mammosphere formation. The amount of Hif-1α and Hif-2α was determined by western blot in MCF-7, BT-20 and
MDA-MB-157 cells cultured under typical adherent conditions and in the same cell lines grown as mammospheres. Indeed, the expression of Hif-1α was greatly increased in mammospheres as compared to adherent cells, but lower than levels induced by hypoxia in adherent cells (Figure 30). While Hif-2α levels were increased during hypoxia in
76 adherent cells, there was no change in Hif-2α expression between adherent and mammosphere cells (Figure 30).
To determine if Hif-1α or Hif-2α are required for the activation of γ-secretase,
MCF-7 cells with scramble, Hif-1α or Hif-2α shRNA stable knockdown were created.
MCF-7 control Dummy sgRNA or Hif-1α sgRNA knockout clones were also created using Cas9-CRIPSR. All cell lines were seeded in the mammosphere formation assay.
Knockdown of Hif-1α and Hif-2α expression and knockout of Hif-1α expression was stable in adherent cells and was still observed after cells were cultured as mammospheres for 10 days (Figure 29A & 31A&B). Knockdown or knockout of Hif-1α significantly decreased the mammosphere formation efficiency (MFE) of primary mammospheres, while knockdown of Hif-2α had no significant effect on primary mammosphere formation (Fig 31C). Knockdown or knockout of Hif-1α significantly decreased secondary mammosphere formation to an even greater extent than primary mammosphere formation, while knockdown of Hif-2α significantly increased secondary mammosphere formation (Fig 31D). Knockdown or knockout of Hif-1α also eliminated stimulation of
γ-secretase activity during both primary and secondary mammosphere formation, while knockdown of Hif-2α has no effect (Figure 32).
In summary, these data indicate that Hif-1α expression, and not Hif-2α expression is necessary for mammosphere formation and for activation of γ-secretase activity in the mammosphere cell population.
77
A" B" Adherent (H) Mammosphere (N) Mammosphere (N) Mammosphere (N) Hif-1α Hif-1α Hif-2α PS1 PS1 PS1 Tubulin Tubulin Tubulin
C" 1° Mammospheres D" 2° Mammospheres 4 3 *** * n.s. n.s. 3 2
*** 2 MFE (%) 1 *** *** (%) MFE 1 **
*** 0 0
shRNA KO c1 KO c2 KO c1 α α α shRNA α shRNA 1shRNA 2 α shRNA 1 shRNA 2 α α α α Hif-1 Hif-1 Hif-1 Hif-1 Hif-1 Hif-2 Hif-2 Dummy sgRNA Hif-2 Hif-2 Dummy sgRNA Scramble shRNA Scramble shRNA
Figure 31: Hif-1α, but not Hif-2α, is required for mammosphere formation. (A) MCF- 7 cells stably expressing scramble, Hif-1α or Hif-2α shRNA were seeded in a mammosphere formation assay. After 10 days, western blot of the mammospheres shows that expression of Hif-1α is still suppressed. Tubulin is used as a loading control. (B) Cas9-CRISPR was used to make two clones with Hif-1α knockout in MCF-7 cells and a clone transfected with a dummy sgRNA sequence as a control. Adherent cells were cultured at 1% O2 for 16 hours prior to western to show Hif-1α knockout. Hif-1α knockout cells were seeded in a mammosphere formation assay and western blot of mammospheres 10 days after seeding shows that Hif-1α expression is still knockedout. (C) Knockdown or knockout of Hif-1α significantly decreased primary mammosphere formation, while knockdown of Hif-2α did not significantly affect sphere formation. (D) Knockdown or knockout of Hif-1α significantly decreased secondary mammosphere formation, while knockdown of Hif-2α significantly increased secondary sphere formation. MFE=mammosphere formation efficiency.
78 n.s. 600 n.s.
400 Adherent Mammosphere
1° Mammospheres 2° Mammospheres 200 *** 800 *** 600 *** *** 600 n.s. Adherent -Secretase (% adherent) Activity -Secretase γ 0 Adherent400 Mammosphere 400 Mammosphere
shRNA shRNA shRNA 200 α 200 α ***β *** *** CRISPR KO Hif-1 α Hif-2 Hif-1 0 scramble shRNA Hif-1 -Secretase Activity (% adherent) 0 -Secretase Activity (% adherent) γ γ
shRNA shRNA shRNA α α α shRNA 1 shRNA 2 α α CRISPR KO Hif-1 α Hif-2 Hif-1 Hif-2 Hif-2 scramble shRNA Hif-1 scramble shRNA
Figure 32: Hif-1α, but not Hif-2α, is required for stimulation of γ-secretase activity in mammospheres. MCF-7 cells lines with stable knockdown or knockout of Hif-1α and knockdown of Hif-2α were seeded in mammosphere formation assay. After 10 days, a Notch exocell γ-secretase activity assay was performed. Notch exocell γ-secretase activity assay was also performed with adherent cells of the same cell lines to compare to the mammospheres.
Transcription is not required for Hif-1α-mediated γ-secretase activation in
mammospheres
Hif-1α is a transcription factor, and previously has been reported to exert its
effects by forming a heterodimer with binding partner Hif-1β /ARNT before traveling to
the nucleus to bind DNA and activate transcription of target genes [90, 92]. In a novel
79 paradigm, we have shown that Hif-1α is also able to act in a transcriptionally independent
manner by associating with the γ-secretase complex to increase NICD production and
activate the Notch pathway [275]. In order to determine if Hif-1α transcriptional activity
is required to stimulate γ-secretase activity during mammosphere formation, a stable Hif-
1β shRNA knockdown MCF-7 cell line was created to in order to prevent Hif-1α from
binding to the DNA and acting as a transcription factor. Knockdown of Hif-1β was stable
when cells were cultured adherently and when they were grown as mammospheres for 10
days (Figure 33A). Knockdown of Hif-1β had no effect on MFE or the stimulation of γ-
secretase activity of primary or secondary mammospheres, indicating that Hif-1α
transcriptional activity is not required to promote formation of mammospheres or γ-
secretase activation (Figure 33B&C, 34A&B).
A" B" C" 1° Mammospheres 2° Mammospheres Adherent (N) Mammosphere (N) 2.5 3 n.s. n.s. Hif-1β 2.0 2 PS1 1.5 1.0
MFE (%) MFE 1 Tubulin (%) MFE 0.5
0.0 0
shRNA shRNA β β
Hif-1 Hif-1 scramble shRNA scramble shRNA =
Figure 33: Hif-1α transcriptional activity is not required for formation of mammospheres. (A) Knockdown of Hif-1β with shRNA in MCF-7 was achieved and was still present in mammospheres 10 days after seeding. Tubulin was used as a loading control. (B) Primary and (C) secondary mammosphere formation is not affected by stable knockdown of Hif-1β. MFE=mammosphere formation efficiency.
80 n.s. A" 600 B" 2° Mammospheres 1° Mammospheres 600 n.s. 800 n.s. n.s. 600 400 Adherent 400Adherent Adherent Mammosphere MammosphereMammosphere 400
200 200 200 *** *** -Secretase Activity (% adherent) γ -Secretase Activity (% adherent) 0 0 -Secretase (% adherent) Activity -Secretase γ γ 0
shRNA shRNA β β
Hif-1 shRNA shRNA Hif-1 shRNA scramble shRNA α scrambleα shRNA β CRISPR KO Hif-1 α Hif-2 Hif-1
scramble shRNA Hif-1 Figure 34: Hif-1α transcriptional activity is not required for stimulation of γ- secretase activity in mammospheres. (A) Scramble shRNA or Hif-1β shRNA stable MCF-7 cells were seeded in a mammosphere formation assay and after 10 days a Notch exocell activity assay was performed. (B) The same cell lines were reseeded in a secondary mammosphere formation assay and after 10 days a Notch exocell activity assay was performed.
To verify that Hif-1α transcription is indeed inactive in the Hif-1β knockdown cell line, we did RT-PCR to determine expression of Hif-1α target genes SLC2A1 (Glut-
1) and VEGFA and Notch target genes HES1 and HEY1. Mammospheres had increased expression of Hif-1α target genes and Notch target genes, as compared to gene expression in the same cell line cultured as adherent cells (Figure 35). Knockdown of
Hif-1α in mammospheres significantly decreased the activation of both Hif-1α and Notch target genes (Figure 35). As expected, knockdown of Hif-1β significantly decreased the activation of Hif-1α target genes in mammospheres (to a similar degree as Hif-1α knockdown), but did not affect the activation of Notch target genes (Figure 35). These
81 data support our model that Hif-1α activates the Notch pathway in a manner that is
independent of Hif-1α transcriptional activity.
A" B" Hif-1α Target Genes Notch Target Genes
GLUT-1 VEGFA HES1 HEY1 10 10 25 * 4 *** *** 8 8 20 *** *** 3 *** 6 6 n.s. 15 n.s. 2 4 * 10 * 4 n.s. *** ** 5 1 2 2 n.s. Relative Quantitation Relative Quantitation Relative Quantitation Relative Quantitation 0 0 0 0 n.s. shRNA shRNA shRNA shRNA600 α β shRNA shRNA shRNA shRNA α β scramble scramble α β scramble scramble scramblen.s.scramble α β scramble scramble Hif-1 Hif-1 Hif-1 Hif-1 Hif-1 Hif-1 Hif-1 Hif-1
400 Adherent Mammosphere
200 *** Figure 35: Hif-1α transcriptional activity ***is not required for activation of Notch target genes during mammosphere formation. RNA was extracted from scramble, Hif- -Secretase (% adherent) Activity -Secretase 1α, and Hif-1β γ shRNA0 MCF-7 stable cell lines cultured as mammospheres. RNA was also extracted from scramble shRNA MCF-7 cells cultured adherently. RT-PCR was performed to assess mRNA expression shRNA of both (A)shRNA Hif-1 shRNAα target genes (VEGFA and α α β SLC2A1 [Glut-1]) and (B) Notch target CRISPR genes KO (HES1 and HEY1). Hif-1 α Hif-2 Hif-1 scramble shRNA Hif-1
Hif-1α is expressed in mammospheres during normoxia
In the canonical pathway, oxygen levels regulate Hif-1α expression [92]. Hif-1α
is continually expressed and, when oxygen is present, it is hydroxylated by PHD, leading
to its degradation via the proteasome. Hif-1α expression is higher during hypoxia, when
oxygen levels are low, because it cannot be hydroxylated and therefore is not degraded.
In our experiments, mammospheres are cultured in normal atmospheric oxygen
conditions, but we have, nevertheless, observed an increase in Hif-1α expression (Figure
82 30). The oxygen penetrance in solid tissue is in the range of 100-200 µM and the mammosphere average in size of 100 µM, so we investigated whether or not there could be a localized hypoxia in mammospheres. Additionally, alternative pathways, such as
NOS, have been described to regulate Hif-1α during normoxia [133].
A B#
Day 1 Day 2 30000
20000 Day 3 Day 4
10000 -Secretase (AU) Activity -Secretase Day 5 Day 6 γ 0
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Adhere Day 10
Day 7 Day 10
Figure : γ-Secretase is activated early during mammosphere formation Figure 36: γ-Secretase is activated early during mammosphere formation. (A) 10X images taken of MCF-7 cells seeded as mammospheres for a period of 1 to 10 days. (B) MCF-7 cells were seeded as mammospheres sequentially, and a Notch exocell γ- secretase activity assay was performed on spheres that were seeded 1 -10 days before the activity assay was done. The activity of MCF-7 cells cultured adherently was also measured.
A time course of γ-secretase activity during mammosphere formation was performed to determine at what stage of their growth and size of the spheres γ-secretase activity is increased. MCF-7 cells were seeded sequentially 10 to 1 day before a γ- secretase activity assay was performed (Figure 36). As previously, spheres were trypsinized, counter, and an equal number of cells were spun down and added to the γ- secretase activity assay. An increase in γ-secretase activity occurs around day 4-5 of
83 sphere formation (Fig 36A), when the spheres are still very small in size (Fig 36B), and it is unlikely that a hypoxic microenvironment exists within the sphere core.
In order to determine the localization of Hif-1α expression in mammospheres, spheres were fixed in 4% PFA, embedded in paraffin, and mounted on glass slides to perform immunohistochemistry for Hif-1α. Immunofluorescence staining indicates that
Hif-1α is not only expressed in the core of the mammosphere, but throughout the sphere and near the edges, where oxygen is present (Figure 37). As a positive control, mammospheres were also cultured in 1% O2 for 16 hours before fixation. Hif-1α expression was detected in mammospheres cultured under both normoxic and hypoxic conditions (Figure 37). Additionally, mammospheres were stained with pimonodizole, which is used to detect hypoxia since it covalently binding to proteins only under low oxygen conditions (Figure 38A). To more directly measure oxygen levels, mammospheres were cultured either under normoxia or 1% O2 for 16 hours and then stained with either solvent or 200uM pimonidazole for 2 hours before fixation. Although mammospheres cultured in hypoxia had positive staining for pimonodizole, mammospheres cultured in normoxia had staining similar to unstained mammospheres, indicating that the mammospheres are not hypoxic (Figure 38B).
84 Normoxia Hypoxia
α-Hif-1α
Rabbit IgG
20X Green= Hif-1α Blue= DAPI
Figure 37: Mammospheres express Hif-1α during normoxia. MCF-7 cells were cultured as mammospheres for 10 days, and then incubated under normal oxygen conditions (normoxia) or put in a 1% O2 (hypoxia) incubator for 16 hours. After fixation and embedding in paraffin, sections of the mammospheres were stained for Hif-1α by immunofluorescence (shown in green). DAPI was used to stain cell nuclei (shown in blue).
85 A Hypoxia( S"
1%(O2(
B No pimonidazole Normoxia Hypoxia
α-pimonidazole
IgG
20X Green= pimonidazole Blue= DAPI
Figure 38: Mammospheres are not hypoxic. (A) Depiction of pimonidazole and its mechanism of action. Pimonidazole will covalently bind to protein cysteine resides, but only when oxygen levels are very low (hypoxia). Pimonidazole is used as a cellular hypoxic stain as its presence can be detected using α-pimonidazole antibodies. (B) MCF-7 cells were cultured as mammospheres and then stained for hypoxia using pimonidazole. As a positive control, mammospheres were grown for 10 days, and then incubated at 1% O2 for 16 hours before pimonidazole staining.
NOS regulates expression of Hif-1α in mammospheres
Nitric Oxide Synthase (NOS) regulates the levels of the signaling molecule NO, which can post-translationally regulate proteins by S-nitrosylation [134, 135]. NOS has been reported to stabilize Hif-1α during normoxia in certain biological systems by S-
86 nitrosylation of the key mediators of Hif-α degradation in the canonical pathway (Figure
8) [133], including Hif-α at Cysteine520, in the ODD domain (which prevents binding to pVHL) (Figure 7B) [145-147]. Expression of both eNOS [151] and iNOS [152-154] isoforms also correlates with poor prognosis in breast cancer patients and have been shown to promote metastasis and cancer stem cell proliferation [205]. We hypothesized that eNOS or iNOS is stabilizing Hif-1α during mammospheres formation, which leads to activation of γ-secretase and Notch signaling.
In order to compare the levels of NO in adherent and mammosphere cells, we used the MUSE™ Nitric Oxide Assay, which utilizes DAX-2J, a dye that emits fluorescence specifically upon binding to NO in the cell (Figure 39A). The assay uses a cell viability dye and flow cytometry based methods to determine the number of viable and non-viable cells that are either positive or negative for NO. Using this assay to compare cellular NO levels between MCF-7 cells cultured either adherently or as mammospheres, we found that there is a significant increase in the number or NO+ viable cells in mammospheres (Fig 39B).
To determine if NOS activity is necessary for mammosphere formation, we used
L- NG-monomethyl arginine (L-NMMA), a substrate-based inhibitor of all NOS isoforms
(Figure 40B). Since L-NMMA is an analog of the normal NOS substrate, L-arginine, its inhibition of NOS should be able to be competed by excess L-arginine (Figure 40A). In the mammosphere formation assay of MCF-7 cells, treatment with L-NMMA significantly reduced MFE, which was rescued by co-treatment with 3mM L-arginine
(Figure 41A). MFE was also significantly reduced by treatment with another pan NOS inhibitor, L-NG-nitroarginine methyl ester (L- NAME) and with the
87 MCF7 A DAX$2J'Orange$Blocking' B
5 * 4
3
2 DAX$2J'Orange$Blocking' 1 % live cells NO(+) cells live % NO# 0
Em'570nm' Adherent
DAX'2J#Orange# Mammosphere
Figure 39: Nitric oxide (NO) production is elevated in mammospheres. (A) The MUSE™ Nitric Oxide Assay utilizes a cell permeable dye, DAX-2J Orange, which emits fluorescence specifically upon binding to NO. (B) MCF-7 mammospheres have a significantly increased percent cell population of cells that stained positive for NO.
A B
L-arginine L-methyl-arginine (L-NMMA)
C D
L-nitro-arginine-methyl ester (L-NAME) 1400W (iNOS-specific)
Figure 40: Chemical structures of NOS inhibitors used in this study. (A) The NOS substrate L-arginine. (B) The substrate-based pan NOS inhibitor, L- NG- monomethyl arginine (L-NMMA). (C) The pan NOS inhibitor, L-NG-nitroarginine methyl ester (L-NAME). (D) The allosteric, iNOS specific inhibitor, 1400W.
88 iNOS-specific allosteric inhibitor 1400W (Figure 40C&D, 41A). None of these inhibitors had significant effects on proliferation of adherent MCF-7 cells, indicating that
NOS is required specifically for the proliferation of BCSCs (Figure 41B).
A B 150 150 150 n.s. 100 100 n.s. 100
50 50 50 MFE (% control) MFE (% control)
0 0 cells# of (% control) -1 0 1 0.1 1 10 0 O mM inhibitor 2 mM inhibitor H
L-NMMA L-NMMA 20 mM L-NMMA10 mM L-NAME L-NMMA + 3mM Arginine L-NMMA + 3mM Arginine L-NAME L-NAME 1400W 1400W
Figure 41: NOS activity is necessary for mammosphere formation. (A) NOS inhibitors L-NMMA, L-NAME, and 1400W decrease formation of MCF-7 mammospheres. Excess L-arginine rescues the effet of L-NMMA. (B) L-NMMA and L-NAME do not affect proliferation of adherent MCF-7 cells.
To determine if NOS activity affects expression of Hif-1α in MCF7 mammospheres, the mammospheres were grown for 10 days, and then treated for 5 days with DMSO, 5 µM GSI-34, 20 mM L-NMMA or 20 mM L-NMMA with 3mM L- arginine. Treatment of mammospheres with both GSI-34 and L-NMMA caused the spheres to dissolve (Figure 23 & 42A). The effects of L-NMMA on mammospheres were rescued by addition of excess L-arginine (Figure 42A). Treatment of 10-day-old
89 mammospheres with L-NMMA also decreased expression of Hif-1α and γ-secretase activity for Notch cleavage, while co-treatment with 3mM L-arginine was able to rescue both expression of Hif-1α and the activation of γ-secretase, indicating that the effects of
L-NMMA are specific to NOS activity (Figure 42B&C). This data shows that NOS activity is required for expression of Hif-1α and activation of γ-secretase in MCF-7 mammospheres.
PBS 20mM L-NMMA 20mM L-NMMA A + 3mM Arg
*** B C 15000 *** Hif-1α *** 10000 PS1
5000 Tubulin -Secretase (AU) Activity -Secretase 20mM L-NMMA: - + + γ 0 3mM8000 L-arginine: - - + PBS PBS
n.s. 20mM NMMA 6000 *** 20mM NMMA+3mM Arg Adherent 4000 Mammosphere
Figure2000 42: NOS activity is necessary for increased Hif-1α expression and γ- secretase activity in mammospheres. (A) Treatment with L-NMMA caused a -Secretase (AU) Activity -Secretase γ dissociation of 10-day-old mammospheres, which was rescued with excess L- arginine.0 (B) Treatment with L-NMMA decreased expression of Hif-1α in 10- day-old mammospheres, and Hif-1 expression was recused by addition of excess L-arginine. (C) Treatment with L-NMMA reduced γ-secretase activity in shRNA shRNA mammospheres, andα was rescued αby excess L-arginine. Hif-1 Hif-2 scramble shRNA
90 iNOS is required γ-secretase activation and mammosphere formation
Since the iNOS specific inhibitor 1400W significantly decreased MFE (Figure
41A), we hypothesized that the iNOS isoform is responsible for stabilization of Hif-1α in mammospheres. We first compared mRNA and protein expression of eNOS and iNOS isoforms between adherent and mammosphere cell populations (Figure 43&44). RT-
PCR showed an increase in both eNOS (NOS3) and iNOS (NOS2) on the mRNA level
(Figure 43A). However, on a protein expression level, there was a significant increase in the expression of iNOS in MCF-7, BT20, and MDA-MB-157 mammospheres, while there was no change in the expression of eNOS (Figure 44).
8000
A B n.s. NOS2 NOS3 n.s.6000 200 2.0 *** Adherent 150 1.5 4000 Mammosphere 1.0 100
0.5 2000 50 -Secretase (AU) Activity -Secretase Relative Quantitation Relative γ Relative Quantitation Relative 0.0 0 0
Adherent Adherent shRNA shRNA Mammosphere α Mammosphereα Hif-1 Hif-2 scramble shRNA Figure 43: Expression of iNOS and eNOS mRNA is increased in MCF-7 mammospheres. RNA was extracted from adherent and mammosphere MCF-7 cells and mRNA levels of (A) iNOS (NOS2) and (B) eNOS (NOS3) were determined by RT-PCR.
91 8000
n.s. 6000 *** A B Adherent 2.5 4000 Mammosphere MCF7 MDA-MB-157 BT20 2.0 * * iNOS 2000 1.5 -Secretase (AU) Activity -Secretase γ 1.0 0 eNOS 0.5 Relative Quantitation Relative shRNA0.0 shRNA Tubulin α α
Hif-1 Hif-2 BT20 scramble shRNA MCF-7
MDA-MB-157
Figure 44: iNOS expression is increased in mammospheres. (A) The expression of iNOS and eNOS was compared in MCF-7, MDA-MB-157, and BT-20 cell lines cultured adherently or as mammospheres. Tubulin was used as a loading control. (B) Quantification of iNOS band intensity measured by western blot.
To more directly determine the role iNOS plays in mammosphere formation, we created stable, iNOS shRNA knockdown cell lines in MCF-7 cells (Figure 45A&B).
Knockdown of iNOS significantly decreased formation of primary and secondary mammospheres (Figure C&D). The effect was more significant for secondary mammosphere formation, and was similar to the effect seen for knockdown of Hif-1α in mammospheres (Figure 31C&D, 45C&D). We also compared γ-secretase activity in scramble or iNOS shRNA cell lines cultured as mammospheres or adherently (Figure
46). Knockdown of iNOS prevented the stimulation of γ-secretase activity in both primary and secondary mammospheres (Figure 46 A&B), indicating that iNOS is required for mammosphere formation and for stimulation of γ-secretase activity via stabilization of Hif-1α.
92 A C 1° Mammospheres D 2° Mammospheres iNOS 3 Tubulin 3
2 2 *** *** *** *** MFE (%) MFE 1 (%) MFE 1 B 1.0 0 0
0.5 (NOS2) * * iNOS shRNAiNOS 1 shRNA 2 iNOS shRNAiNOS 1 shRNA 2 Relative Quantitation scramble shRNA scramble shRNA 0.0
iNOS shRNAiNOS 1 shRNA 2 scramble shRNA
Figure 45: iNOS is required for mammosphere formation. (A) iNOS expression is decreased in iNOS shRNA MCF-7 cell lines as compares to control scramble shRNA cell line. (B) mRNA expression is significantly reduced in MCF-7 iNOS shRNA cell lines as compared to scramble shRNA. Knockdown of iNOS in MCF-7 cells reduced formation of both (A) primary and (B) secondary mammospheres.
8000 A B n.s. 1° Mammospheres 2° Mammospheres 800 6000 400 Adherent*** Adherent Mammosphere AdherentMammosphere 600 300 4000 Mammosphere 400 *** 200
*** (% adherent) (% adherent) 200 100 *** 2000 -Secretase (AU) Activity -Secretase γ -Secretase Activity (AU) -Secretase Activity (AU) 0 0 γ γ 0
shRNA shRNA iNOS shRNA 1 iNOS shRNA 2 α iNOSα shRNA 2 scramble shRNA scramble shRNA Hif-1 Hif-2 scramble shRNA Figure 46: iNOS is required for activation of γ-secretase in mammospheres. MCF-7 cells lines with stable shRNA knockdown of iNOS have significantly reduced activation of γ-secretase in both (A) primary and (B) secondary mammospheres, as compared to adherent cells.
93 3.3 Discussion and Conclusion
In summary, we have revealed a novel mechanism where oxygen-independent stabilization of Hif-1α by iNOS promotes proliferation of the BCSC population in a
Notch-dependent manner. We have described a novel tumor-initiating cell signaling pathway that is critical for the proliferation of this subset of breast cancer cells. A diagram of our proposed model is presented in Figure 47.
Notch γ-Secretase Normoxia
HIF-1α
HIF-1α HIF-1α
iNOS%
O2 PHD NICD pVHL Metastasis BCSC growth HIF-1α CSL O Differentiation Degradation H via proteosome
Figure 47: Hypothesized model of tumor-initiating cell signaling pathway. In the BCSC population, Hif-1α expression is stabilized by iNOS activity. The increased Hif-1α expression stimulates γ-secretase activity to enhance NICD production and activation of Notch target target genes that promote BCSC growth, metastasis and prevent differentiation.
According to our model, even during normoxia, Hif-1α is expressed in BCSCs due to stabilization by iNOS. S-nitrosylation of both Hif-1α and pVHL has been
94 proposed to stabilize Hif-1α protein expression by preventing the binding of pVHL to
Hif-1α and the Elongin C ubiquitination complex, so that Hif-1α is not degraded by the proteasome [133]. In particular, one study found that increased Hif-1α expression after radiation in non-hypoxic 4T1 mouse tumors was a direct result of NO-mediated S- nitrosylation of Hif-1α at Cys520 [147]. We hypothesize that S-nitrosylation of Hif-1α
Cys520 (or possibly pVHL) by iNOS is responsible for the iNOS-dependent stabilization of Hif-1α expression in mammospheres. The increased Hif-1α expression in the BCSC population resulted in a non-transcriptional, Hif-1α-mediated stimulation of γ-secretase activity and further downstream activation of Notch signaling. The Notch pathway promotes proliferation of the tumor initiating, mammosphere cell population, and was required for formation of mammospheres. While iNOS has previously been shown to drive BCSC proliferation [167], we have revealed for the first time that iNOS activity regulates Hif-1α expression and Notch signaling in a breast cancer stem cell model and that this interaction is required for proliferation of the BCSC population.
95 CHAPTER 4
GGT is an endogenous regulator of γ-secretase in the kidney
4.1 Background
Previous research has shown the four components of γ-secretase are ubiquitously expressed at both the mRNA and protein level in most tissues, including heart, brain, spleen, lung, liver and kidney [18, 19]. However, the protein expression of the complex does not always correlate with the amount of γ-secretase activity [24-26]. While γ- secretase subunits are expressed in almost all tissues of the mouse, γ-secretase activity can only be detected in the brain and lung (Figure 48A). One explanation for this data is the existence of tissue-specific negative regulators of γ-secretase activity. This hypothesis is consistent with our overall model that γ-secretase activity is modulated in a tissue-specific manner by regulation with interacting proteins.
By testing this hypothesis, we found that membrane purified from mouse kidney completely inhibited γ-secretase activity in our activity based photolabeling assay, while none of the other mouse tissues had any effect (Figure 48B). Kidney membrane also inhibited both APP and Notch cleavage in the γ-secretase activity assay. The inhibition of γ-secretase was rescued by heating the kidney membrane to 98° C for 5 minutes, indicating that the endogenous kidney inhibitor is heat sensitive and may be a protein.
By using classical biochemistry protein purification techniques, a previously unknown γ- secretase inhibitor was purified from whole rat kidney membrane. The output assay used during optimization of the purification process was the ability of each fraction to inhibit
γ-secretase activity in HeLa membrane. The identify of the inhibusing mass
96 A B Brain Membrane
Heart - + - - - Spleen - - + - - Liver - - - + - Kidney - - - - +
PS1-NTF
Figure 48: Kidney membrane contains an endogenous inhibitor of γ-secretase. (A) The effect of purified membrane from different mouse tissues on γ-secretase activity in HeLa membrane was determined using the Notch based γ-secretase activity assay. (B) The effect of purified membrane from different mouse tissues on JC-8 activity based photolabeling of active γ-secretase complex in mouse brain membrane. ** Unpublished data courtesy of Dr. Courtney Alexander spectrometThere was one visible band detected after the final purification scheme, which came back with four hits by mass spectrometry (Figure 49A&B). Gamma-glutamyl transpeptidase (GGT) was the only viable hit, as it was the only membrane protein, non- housekeeping protein that was the correct molecular weight.
The hit was validated using classical biochemistry methods. Expression of GGT was enriched during each of the purification steps (Figure 49C). Commercially available
GGT from bovine kidney also inhibited γ-secretase in a heat-dependent manner, suggesting that GGT is indeed an inhibitor of γ-secretase activity. However, the mechanism by which GGT inhibits γ-secretase and the biological function of GGT as an endogenous inhibitor of Notch signaling in the kidney remained to be elucidated.
97 A
Q6 Hydroxy6 Whole& Kidney& Solubilized& MiniQ& Sepharose& apa8te& Kidney& Membrane&& Kidney& Column& Column& Column&
B HA MiniQ C
70 Identify by 55 GGT 70 LC-MS/MS: 35 55 GGT 35 25 15
Figure 49: GGT was purified and identified as the endogenous inhibitor of γ- secretase in the kidney. (A) Final purification scheme used to purify the endogenous γ- secretase inhibitor from rat kidney. (B) After the final purification step, there was a single band corresponding to the kidney endogenous inhibitor. Mass spectrometry identifies the protein as GGT. (C) Expression of GGT was enriched through each of the purification steps. ** Unpublished data courtesy of Dr. Courtney Alexander
Why does the kidney have such a potent inhibitor of γ-secretase? Notch signaling in kidney development is crucial for the formation of the proximal tubular epithelial cell fate and the renal collecting system; however, the developed kidney has very low Notch signaling [231]. In fact, activation of Notch signaling occurs during kidney disease and GSIs have been proposed as a treatment for chronic kidney disease
[233]. While our research is ongoing, we hypothesize that GGT may act as a mechanism to repress Notch signaling after kidney development by inactivating γ-secretase, and that loss of this inhibition can have pathogenic consequences.
98 4.2 Results
Purified GGT inhibits γ-secretase activity
In order to validate that GGT inhibits γ-secretase activity, purified GGT was
obtained from multiple sources. GGT purified from bovine kidney, porcine kidney, and
human liver is commercially available and was purchased. However, while GGT from
these sources was active and does inhibit γ-secretase, the GGT was not completely pure. HeLa membrane
100 A HeLa membrane Q-sephrose Hydroxy Appetite 100 Mini-Q BovineQ-sephrose GGT (kidney) 50 PorcineHydroxy GGT Appetite (kidney) HumanMini-Q GGT (liver) rHumanBovine GGTGGT (kidney) 50 Porcine GGT (kidney) Human GGT (liver) -Secretase Activity (% control) (% Activity -Secretase
γ 0 rHuman GGT 0.01 0.1 1 10 100 -Secretase Activity (% control) (% Activity -Secretase
γ 0 ug protein 0.01 0.1 1 10 100 ug protein
B Brain Membrane ! ! PS1-NTF ! ! ! !
Figure 50: Different sources of GGT inhibit γ-secretase in activity assay and activity- based photolabeling. (A) The effect of different sources of purified GGT on γ- secretase activity in HeLa membrane. (B) The effect of different sources of GGT on activity based photolabeling of active γ-secretase complex from brain membrane with JC8.
99 When ran on a protein gel, multiple bands of different sizes were detectable. To obtain a
completely pure source of GGT, we obtained human recombinant GGT1 (rGGT) purified
from yeast through collaboration with Dr. Marie Hannigan. rGGT was active in the GGT
activity assay and contained only two bands corresponding to GGT large and small
subunits when ran on a protein gel [272].
GGT from all of these sources inhibited γ-secretase activity in the AB40 γ-
secretase activity assay in a dose-dependent manner, as did the fractions from each of the
purification steps (Figure 50A). Bovine GGT and Q-sephrose purification fraction also
blocked activity based photolabeling of PS1-NTF in brain membrane (Figure 50B), to a
similar degree as a known γ-secretase inhibitor, L-685,458. As a technical note, Q-
sephrose purification fraction was often used for the mechanistic biochemical
experiments since there is a very small volume of hydroxyapatite (HA) and MiniQ
purification fractions collected at the end of the purification process.
40 Mini-Q 30 Hydroxy-Apetite Q-sephrose 20
10
GGT Activity (pmol pNa) (pmol Activity GGT 0 0 20 40 60 Time (min)
Figure 51: Purified kidney endogenous inhibitor fractions have GGT activity. The GGT activity assay was used to measure the amount of GGT activity in different fractions during the kidney endogenous inhibitor purification process. The amount of each fraction added to the assay was normalized by total protein concentration.
100 It was previously shown that GGT expression is enriched during each of the purification steps (Fig 49C). To test if the fractions from each of these steps also have
GGT activity, a GGT activity assay was performed. The GGT activity assay is colorimetric and utilizes a GGT substrate that is processed by GGT glutamyl-transferase activity to form the light-emitting pNA compound, proportional to GGT activity. Each of the purification step fractions had GGT activity, further confirming GGT as the identity of the kidney endogenous inhibitor (Figure 51).
GGT inhibits γ-secretase in an activity-dependent manner
We used GGT inhibitors in order to test if GGT activity is required for γ-secretase inhibition (Figure 52). The classic GGT inhibitors azaserine and acivicin were used.
Azaserine is an analogue of glutamine, the portion of the GGT substrate GSH that binds to the enzyme active site. Acivicin is an irreversible inhibitor that covalently binds to the enzyme. Both inhibitors bind to the active site of the GGT enzyme (Figure 52).
A B C
Glutamine Azaserine Acivicin
Figure 52: GGT inhibitors used in the study. (A) Glutamine, the portion of the GGT substrate GSH that binds to the enzyme active site. (B) The GGT inhibitor azaserine. (C) The irreversible GGT inhibitor, acivicin, which covalently binds to the active site.
101 We then tested to see if GGT activity is necessary to inhibit γ-secretase activity.
The Q-sephrose fraction of our purified endogenous kidney inhibitor was pre-treated with
H2O, acivicin, or azaserine at 37° C for 30 minutes or 98° C for 5 minutes and then added to the AB40 γ-secretase activity assay assess its effect on activity. In this experiment,
HeLa membrane was used as a source of active γ-secretase complex. Addition of Q- sephrose to the activity assay significantly inhibited γ-secretase activity (Figure 53A).
While addition of acivicin or azaserine alone had minimal effects on the γ-secretase
A 150 B ns 100 ns ns ns 100 *** 50 50 *** GGT Activity (% control) Activity GGT
-Secretase Activity (% control) (% Activity -Secretase 0
γ 0
1 μg GGT: - - - + + + + 1 μg GGT: H2O + + + 98C + H2O GGT 5mM Acivicin: - + - - + - - 5mM Acivicin: - 5mM aci + - - Aci onlyAza only 10mM Aza 10mM Azaserine: - - + - - GGT+ +98 C- 10mM Azaserine: - - + - Heat 98° C: - - - GGT+5mM - Aci - - + Heat 98° C: - - - + GGT + 10mM Aza
Figure 53: Q-sephrose purification fraction inhibits γ-secretase from HeLa membrane in a GGT activity-dependent manner. (A) In vitro γ-secretase activity assay with purified HeLa membrane. Acivicin or azaserine alone do not have drastic effect on γ- secretase activity. However, 1 µg of Q-sephrose significantly reduced γ-secretase activity. 1 µg of Q-sephrose fraction had no significant effect on γ-secretase activity when it was pre-treated with GGT inhibitors azaserine and acivicin or heated to 98° C. (B) The GGT activity assay detects activity in 1 µg of Q-sephrose fraction, and the activity is inhibited by addition of GGT inhibitors azaserine and acivicin or heating to 98° C.
102 activity assay, addition of either inhibitor to the Q-sephrose fraction was able to rescue the loss of activity as compared to control (Figure 53A). Preheating the Q-sephrose fraction to 98° C for 5 minutes also rescued the loss of activity (Figure 53A). 5 µL of the
γ-secretase activity assay was also added to the GGT activity assay to confirm that the compounds inhibit GGT activity. Acivicin, azaserine, and 98° C all inhibited GGT activity (Figure 53B). These results confirm that GGT is the endogenous inhibitor of γ- secretase in the kidney. Additionally, we have shown that GGT inhibits γ-secretase in an activity-dependent manner.
150 A ns B
150 ns
100 ** 100
(% control) 50 50 (% control)
*** Activity GGT -Secretase Activity γ *** *** 0 0 1 μg GGT: - - + + + 1 μg GGT: + + + 98C 5mM Acivicin: H2O - + GGT - + - 5mM Acivicin: none - + - Aci only 5mM aci GGT+ Aci Heat 98° C: - - - -GGT +98 C+ Heat 98° C: - - +
Figure 54: GGT purified from human liver inhibits purified γ-secretase in a GGT activity-dependent manner. (A) In vitro γ-secretase activity assay with purified γ- secretase complex. Acivicin alone does not have a drastic effect on γ-secretase activity. However, 1 µg of GGT purified from human liver significantly reduced γ- secretase activity. 1 µg of GGT purified from human liver had no significant effect on γ-secretase activity when it was pre-treated with the GGT inhibitor acivicin or heated to 98° C. (B) The GGT activity assay detects activity in 1 µg of GGT purified from human liver, and the activity is inhibited by addition of acivicin or heating to 98° C.
103 In order to more directly assess the effect of GGT on γ-secretase, we used GGT purified from human liver and purified γ-secretase complex in our biochemical γ- secretase activity assay. The purified γ-secretase complex is a purified and active form of the four subunits obtained from Hek293S cells and is active in the γ-secretase activity assay [285]. A biochemical assay was set up to determine the effect of GGT on γ- secretase directly. The assay contained PIPES buffer, 0.25% CHAPSO, recombinant
APP substrate, purified human GGT, purified γ-secretase and a lipid mixture. Addition of purified GGT significantly inhibited the activity of purified γ-secretase (Figure 54A).
While addition of acivicin alone did not affect γ-secretase activity, when GGT was pretreated with acivicin, it rescued γ-secretase inhibition (Figure 54A). Inhibition of purified γ-secretase complex was also rescued by preheating GGT to 98° C (Figure 54A).
Treatment of human GGT purified from liver with acivicin or 98° C completely inhibited
GGT activity (Figure 54B).
These results further confirm that GGT is the endogenous kidney inhibitor of γ- secretase. We have also shown that GGT alone is sufficient to inhibit γ-secretase activity. GGT activity is required for this inhibition, but association with any additional co-factors is not.
GGT substrate glutathione blocks GGT inhibitory activity
GGT is an enzyme that catalyzes the transfer of glutamyl groups from metabolites to another acceptor substrate (such as metabolites or H2O). Since GGT activity is necessary for γ-secretase inhibition, we hypothesized that perhaps GGT could be
104 transferring a glutamyl group onto one of the γ-secretase subunits as its inhibitory mechanism. We used antibodies that react to glutamyl bonds or glutathione (which has a glutamyl bond) to blot kidney and brain membrane (Figure 55A). Kidney membrane has a strong band for a glutamyl bond at a molecular weight that could possibly correspond to
NCT (Figure 55A). The band is also not present in brain membrane or HeLa membrane, which have active γ-secretase complex.
A B
α-γ-glutamyl lysine α-glutathione 100 kDa kDa 250 250 Bovine GGT Porcine GGT 130 130 Bovine GGT+ 200 µM GSH Porcine GGT+ 200 M GSH 100 100 50 µ 70 70 55 55
35 35
25 25 (% control)Activity -Secretase γ 0 0.1 1 10 100 ug protein
Figure 55: GGT does not add a glutamyl group to inhibit γ-secretase activity. (A) A western blot was performed using α-γ-glutamyl lysine or α-glutathione antibodies on purified membrane from mouse brain or kidney or HeLa membrane. There is a greater amount protein with a bond recognized by these antibodies in kidney membrane, which contains the γ-secretase endogenous inhibitor. (B) Excess GSH was added to the in vitro γ-secretase activity assay of HeLa membrane. The assay was done to determine the effect of GSH on inhibition of γ-secretase by GGT purified from bovine or porcine kidney.
In order to test if a transfer of a glutamyl group is important for γ-secretase inhibition in our activity assay, we added excess of the natural GGT glutamyl donor substrate, glutathione (GSH) (Figure 55B). If glutamyl transfer to γ-secretase is occurring, addition of excess GSH should increase the potency of purified GGT.
However, addition of excess GSH significantly decreased the potency of both bovine and
105 porcine GGT (Figure 55B). Therefore, it is not likely that GGT is transferring a glutamyl group to a γ-secretase subunit. The experiment does support that GGT activity is important for the inhibition mechanism; however, it seems that the GGT activity to convert glutathione is competing for the GGT activity that inhibits γ-secretase.
GGT specifically modifies presenilin in an activity-dependent manner
GGT inhibits γ-secretase in an activity-dependent manner that is not glutamylation of the complex. We therefore hypothesized that γ-secretase might be somehow structurally modified by GGT enzyme. In order to determine if GGT causes any structural changes or covalent modifications on the purified γ-secretase complex, a γ- secretase activity assay was set up as previously described, but after the 3 hour reaction incubation, 10 µL was added to the detection mix to measure Aβ40 formation, and the remaining activity assay was mixed with SDS buffer and ran on an SDS-PAGE gel
(Figure 56A). GGT purified from human liver was used as the source of GGT in these experiments. Figure 56A is a Commassie stain of the protein gel to detect total protein.
Using this method, PS1-NTF and PS1-CTF are the only visible bands from the purified γ- secretase complex (Figure 56A). However, when GGT is added to the purified γ- secretase complex, PS1-NTF and PS1-CTF bands disappear, meaning that GGT is somehow degrading or covalently modifying presenilin (Figure 56A). The same experiment was repeated but a western blot was done on the gel to more specifically assess the effects of GGT on NCT and PS1-NTF (Figure 56B). Addition of GGT again caused a loss of PS1-NTF band, and there were no other PS1-NTF bands shifted to a
106 different molecular weight detectable in the sample (Figure 56B). However, GGT had no
effect on the expression of NCT, indicating that GGT may be specifically affecting PS.
The decrease in PS1-NTF expression that was determined by western blot corresponded
to a loss of γ-secretase as measured in our γ-secretase activity assay (Figure 56C).
A kDa 250
130 100 70 55 FL-GGT PS1-NTF-CBP 35 25
15 PS1-CTF
10
μg Human GGT (liver): 0 10 0 50 10 50 0 0 μL purified γ-secretase: 0.4 0.4 3 3 0 0 0.4 3
B C 150
NCT 100
50 PS1-NTF -Secretase Activity (% control)Activity -Secretase μg Human GGT (liver): 0 10 0 50 10 50 0 0 γ 0 μL purified γ-secretase: 0.4 0.4 3 3 0 0 0.4 0 μg Human GGT (liver): 0 10 0 50 μL purified γ-secretase: 0.4 0.4 3 3
Figure 56: GGT purified from human liver structurally modifies presenilin from purified γ-secretase complex. (A) The product of an in vitro γ-secretase activity assay using purified γ-secretase complex after a 3-hour incubation was ran on an SDS- PAGE gel and total protein was measured using Coomassie stain. Addition of 10 µg or 50 µg of GGT purified from human liver caused a loss of the protein bands corresponding to PS1-NTF and PS1-CTF. (B) The product of an in vitro γ-secretase activity assay using purified γ-secretase complex after a 3-hour incubation was ran on an SDS-PAGE gel and a western blot fot Nicastrin (NCT) and PS1-NTF was performed. Addition of 10 µg or 50 µg of GGT purified from human liver caused a loss of the protein bands corresponding to PS1-NTF but did not affect the expression of NCT. (C) 10 µl of the assay analyzed in (B) was mixed with γ-secretase activity assay detection mix to measure γ-secretase activity. Addition of 10 µg or 50 µg of GGT purified from human liver completely abrogated γ-secretase activity.
107
A B C
Nct Nct Nct
PS1-NTF (aa 1-25) PS1-NTF PS1-NTF (aa 1-25) PS1-NTF (aa 1-25) (aa 21-80)
PS1-CTF PS1-CTF PS1-CTF μg HA: 0 1 μg Human GGT (liver): 0 10 10* 10 μg Q-sephrose: 0 10 10* μL purified γ-sec: 1.5 1.5 μL purified γ-secretase: 1.5 1.5 1.5 0 μL purified γ-sec: 1.5 1.5 1.5 *= preheat @ 98°C *= preheat @ 98°C
150 150 150
100 100 100
50
(% (% control) 50 (% (% control) 50 (% (% control) -Secretase Activity Activity -Secretase -Secretase Activity Activity -Secretase γ γ -Secretase Activity Activity -Secretase
0 γ 0 0 μg Human GGT (liver): 0 10 10* μg Q-sephrose: 0 10 10* μg HA: 0 HA1 μL purified γ-secretase:control 1.5 1.5 1.5 μL purified γ-sec:control 1.5 Qseph 1.5 1.5 10ug GGT Qspeh 98 μL purified γ-sec:Control 1.5 1.5
*= preheat10ug GGT @ 98C 98°C *= preheat @ 98°C
Figure 57: GGT from Q-sephrose and HA purification fractions structurally modifies presenilin from purified γ-secretase in a heat dependent manner. (A) The product of an in vitro γ-secretase activity assay using purified γ-secretase complex after a 3-hour incubation was ran on an SDS-PAGE gel and a western blot fot Nicastrin (NCT), PS1-NTF aa1-25, PS1-NTF aa21-80, and PS1-CTF was performed. 10 µl of the assay analyzed by western was mixed with γ- secretase activity assay detection mix to measure γ-secretase activity. Addition of 10 µg GGT purified from human liver caused a loss of PS1-NTF and PS1- CTF bands and γ-secretase activity, and this effect was rescued by pre-heating GGT to 98° C. (B) The same experiment as (A) was repeated, but the Q- sephrose purification fraction was added to assay instead as a the source of GGT. Addition of 10 µg Q-sephrose fraction caused a loss of PS1-NTF and PS1-CTF bands and γ-secretase activity, and this effect was rescued by pre-heating GGT to 98° C. (C) The same experiment as (A) was repeated, but the hydroxyapatite (HA) purification fraction, which is more pure than Q-sephrose fraction, was added to assay instead as a the source of GGT. Addition of 1 µg HA fraction caused a loss of PS1-NTF and PS1-CTF bands and γ-secretase activity.
108 In order to determine if GGT is structurally modifying presenilin in an activity- dependent manner, GGT purified from human liver was preheated before addition to the
γ-secretase activity assay. Addition of GGT to purified γ-secretase complex caused a loss of PS1-NTF and PS1-CTF bands but did not affect the expression of NCT (Figure 57A).
The loss of the band could be rescued by preheating GGT and the expression of PS1-NTF and PS1-CTF correlated with γ-secretase activity (Figure 57A). No other bands that had shifted to a different size were present in the PS1-NTF blot.
The PS1-NTF antibody we typically use in our experiments recognizes presenilin amino acids 1-25. Another PS1-NTF antibody that recognizes presenilin amino acids 21-
80 was also used to determine if GGT is modifying only the first 25 amino acids of PS1-
NTF, or a greater portion of the protein. However, when the new PS1-NTF antibody was used, GGT still caused a loss of the PS1-NTF band (Figure 57A).
The GGT purified from human liver is not 100% pure and could possibly contain impurities leading to loss of presenilin. The effect of our purified kidney endogenous inhibitor on presenilin in the purified γ-secretase complex was determined in the same experimental setup. Addition of both Q-sephrose and HA purification fractions caused a loss of PS1-NTF and PS1-CTF bands, had no effect on NCT expression, and correlated with γ-secretase activity (Figure 57B&C). Preheating the Q-sephrose fraction was able to rescue the loss of presenilin bands as well as γ-secretase activity (Figure 57B). The fact that GGT purified from multiple sources has the same effect on presenilin suggests that this may be an actual mechanism by which GGT inhibits γ-secretase activity, rather than some contaminant effect.
109
A B C Nct Nct PS1-NTF PS1-NTF 1 μg GGT: - + + + PS1-CTF 5mM Acivicin: - - + - PS1-CTF Heat 98° C: - - - + 1 μg GGT: - + + + + 5mM Acivicin: - - + - - μg HA: 0 1 PI+PMSF: - - - + - Heat 98° C: - - - - +
D E F PS1-NTFPS1-NTF PS1-CTFPS1-CTF NCTNCT 150 ns ns 150 150 ns ns ns ns 100 100 100 *** 50 ** 50 50 *** Intensity (% control) Intensity Intensity (% control) Intensity 0 (% control) Intensity 0 0 1 μg GGT: - + + + + 1 μg GGT: - + + + 1 μg GGT: - + + + + GGT GGT GGT 5mM Acivicincontrol: - - + - - 5mM Acivicin: - - + - 5mM Acivicin : - - + - - GGT 98 control GGT 98 control GGT 98 PI+PMSF: - - GGT + Aci - - + Heat 98° C: - - GGT + Aci - + PI+PMSF: - - GGT + Aci - - + GGT PI/PMSF Heat 98° C: - - - + - Heat 98° C: - - - +GGT PI/PMSF -
Figure 58: Q-sephrose fraction structurally modifies presenilin from HeLa membrane. The product of an in vitro γ-secretase activity assay using HeLa membrane after a 3-hour incubation was ran on an SDS-PAGE gel and a western blot for (A) Nicastrin (NCT) and PS1-CTF and (B) PS1-NTF was performed. Addition of 1 µg of the Q-sephrose purification fraction (as a source of GGT) decreased expression of PS1-NTF and PS1-CTF bands but did not affect expression of NCT. The inhibitory effect was rescued by pre-heating GGT to 98° C or pre-treating GGT with 5mM acivicin, but was not affected by the addition of protease inhibitor cocktail with PMSF (PI+PMSF). (C) The same experiment as is (A) and (B) was repeated, but the HA purification fraction was used as a source of GGT. 1 µg of HA decreased the expression of PS1-NTF and PS1-CTF bands but did not affect expression of NCT. The band intensity for (D) PS1-NTF, (E) PSI-CTF, and (F) NCT was quantified from western blots of repeated experiments.
110 A B
Nct
Nct PS1-NTF PS1-NTF
PS1-CTF 1 μg GGT: - - + + + PI+PMSF: - - - - + 1 μg GGT: - + + + Heat 98° C: - - - + - 5mM Acivicin: - - + - Heat 98° C: - - - +
rhumanC GGT HeLa western quant-NTFD E PS1-NTF rhuman GGT HeLaPS1-CTF western quant-CTF rhuman GGT HeLaNCT western quant-NCT 150 100 150 ns ns ns 100 100 * 50 50 50 Intensity (% control) (% Intensity Intensity (% control) (% Intensity Intensity (% control) (% Intensity
0 0 0 1 μg GGT: - + + + + 1 μg GGT: - + + + 1 μg GGT: - + + + + GGT GGT GGT 5mM Acivicin: - - + - - 5mM Acivicin: - - + - 5mM Acivicincontrol: - - + GGT - 98 - control GGT 98 control GGT 98 GGT + Aci PI+PMSF: - -GGT + Aci - - + Heat 98° C: - GGT - + Aci - + PI+PMSF: - - - - + GGT PI/PMSF Heat 98° C: - - - GGT + PI/PMSF - Heat 98° C: - - - + -
Figure 59: rGGT structurally modifies presenilin from HeLa membrane. (A) The product of an in vitro γ-secretase activity assay using HeLa membrane after a 3-hour incubation was ran on an SDS-PAGE gel and a western blot for Nicastrin (NCT), PS1-CTF and PS1-NTF was performed. Addition of 1 µg of purified human rGGT decreased expression of PS1-NTF and PS1-CTF bands but did not affect expression of NCT. The inhibitory effect was rescued by pre-heating rGGT to 98° C or pre- treating rGGT with 5mM acivicin (B) The same experiment as is (A) was repeated with 1 µg of rGGT. 1 µg of rGGT decreased the expression of PS1-NTF band but did not affect expression of NCT band. The effect was not affected by the addition of protease inhibitor cocktail with PMSF (PI+PMSF).The band intensity for (C) PS1-NTF, (D) PSI-CTF, and (E) NCT was quantified from western blots of repeated experiments.
We then assessed the effect of our purified Q-sephrose and recombinant purified human GGT (rGGT) on expression of presenilin in HeLa membrane. rGGT is a very pure source of GGT due to its purification method. In this experimental setup, GGT was
111 pretreated with either H2O or 5mM acivicin at 37° C for 30 min or 98° C for 5 minutes.
The GGT was then added to our APP γ-secretase activity assay using HeLa membrane as a γ-secretase source, incubated for 3 hours, and 10 µL of the assay went to detection for
γ-secretase activity, 5 µL went to the GGT activity assay and the remaining part was loaded on an SDS-PAGE gel for western blot. Addition of both Q-sephrose and HA purification fractions significantly decreased the intensity of PS1-NTF and PS1-CTF a bands (Figure 58A-E). The effect is GGT activity-dependent as pretreatment of GGT with either acivicin or 98° C rescued the loss of NTF-PS1 band and partially rescued the loss of PS1-CTF band (Figure 58A,B,D,E). At the same time, none of the conditions had any significant effect on expression of NCT in HeLa membrane (Figure 58A, F). In order to test if there was a contaminating protease in the Q-sephrose fraction that was responsible for the results, a general protease inhibitor cocktail (PI+PMSF) was added the activity assay, but it had no effect on the inhibitory potential of GGT (Figure 58A, D, E).
The effect of Q-sephrose on γ-secretase activity assay for this experiment correlated to the expression of presenilin that was detected by western blot (Figure 58A). GGT activity of the Q-sephrose fractions also correlated with the inhibition of γ-secretase
(Figure 60).
The same experiment was repeated using rGGT and HeLa membrane, with similar results. Addition of GGT caused a significant loss of PS1-NTF and PS1-CTF bands, but had no significant effect on expression of NCT (Figure 59A-E). The expression of PS1-NTF was rescued when GGT was pretreated with acivicin or 98° C and the expression of PS1-CTF was rescued by acivicin (Figure 59A-D). These results indicate that GGT itself is specifically structurally modifying presenilin in an activity-
112
A Q-sephrose C rGGT 150 150 ns ns 100 100
50 50 (% control) *** (% control) * -Secretase Activity -Secretase Activity γ
*** γ 0 0
1 μg GGT: - GGT + + + + 1 μg GGT: - + + + + H2O GGT 5mM Acivicin:control - + + GGT - 98 - 5mM Acivicin: - + + - -
Heat 98° C: - 5mM- acivicin - +GGT PI/PMSF - Heat 98° C: - - - GGT +98 + C - PI/PMSF: - - - - + PI/PMSF: - GGT+5mM - rGGT Aci - GGT+PI/PMSF- + B# 150 D# 150
100 ns 100
50 50 (% control) (% control) GGT Activity Activity GGT GGT Activity Activity GGT *** * 0 0
1 μg GGT: + + 98C + + 1 μg GGT: + + 98C + + none none 5mM Acivicin: - + - - 5mM Acivicin: - + - - +PI/PMSF Heat 98° C: - - + - Heat 98° C: - - ++PI/PMSF - 5mM acivicin 5mM acivicin PI/PMSF: - - - + PI/PMSF: - - - +
Figure 60: GGT and γ-secretase activity of Q-sephrose fraction and rGGT correlate with the structural modification of presenilin from HeLa membrane. (A) 10 µl of the assay from the experiment analyzed by western in Figure 58 (Q-sephrose fraction addition to HeLa membrane) was mixed with γ-secretase activity assay detection mix to measure γ-secretase activity. 5 µL of the same assay was added to the GGT activity assay to measure GGT activity. (B) 10 µl of the assay from the experiment analyzed by western in Figure 58 (rGGT addition to HeLa membrane) was mixed with γ- secretase activity assay detection mix to measure γ-secretase activity. 5 µL of the same assay was added to the GGT activity assay to measure GGT activity.
dependent manner. Again, addition of PI+PMSF to GGT did not affect the loss of PS1-
NTF band, indicating that it is specifically due to GGT activity and not a contaminating protease (Figure 59B, C). The effect of rGGT on γ-secretase activity was also measured in this experiment (Figure 59C&D). Inhibition of γ-secretase activity correlates with the
113 expression of presenilin (Figure 59C) and GGT activity is inversely correlated with γ- secretase activity (Figure 60).
Overall, these biochemical experiments have validated that GGT is the true identity of the kidney-specific endogenous γ-secretase inhibitor. We have also shown that the mechanism of action is dependent on the activity of the GGT enzyme, and that
GGT is somehow structurally modifying presenilin in order to inhibit γ-secretase activity.
GGT regulates γ-secretase activity and Notch signaling in human kidney cells
We have shown that GGT is capable of inhibiting γ-secretase in biochemical assays. The question then becomes: does this inhibition have any actual biological function? To address if GGT plays a role in regulating γ-secretase activity in a biological system, we used the HK-2 kidney cell model. HK-2 is a human, immortalized renal proximal tubule cell line that expresses GGT. A stable GGT shRNA knockdown was created in the HK-2 cell line, which had effective knockdown of GGT expression as determined by western blot and RT-PCR (Figure 61).
114 GGT1 A B GGT1
1.0 GGT
** PS1-NTF 0.5
Tubulin Quantitation Relative 0.0
GGT shRNA
scramble shRNA
Figure 61: Stable shRNA knockdown of GGT in HK-2 human kidney cells. (A) GGT was stably knocked down with GGT shRNA as compared to scramble shRNA in the HK-2 cell line. Knockdown of GGT did not affect expression of PS1 or the loading control tubulin. The antibody detected the GGT small, catalytic subunit. (B) RT-PCR detected that the expression of GGT1 mRNA was significantly reduced in the GGT shRNA HK-2 cell line, as compared to the control scramble shRNA cell line.
Knockdown of GGT in HK-2 cells resulted in an increase in the amount of active
γ-secretase complex in our activity based JC-8 photolabeling assay (Figure 62). γ-
Secretase activity was also measured using the Notch γ-secretase activity assay in the
HK-2 GGT shRNA cell line (Figure 63). Knockdown of GGT resulted in a significant increase in γ-secretase activity, as well as a significant decrease in the GGT activity of
HK-2 cell lysate, as compared to scramble shRNA control cells (Figure 63B&C). These results support our hypothesis that GGT is a negative regulator of γ-secretase.
115 A B 2.0 JC8 Photolabel 1.5 Input: L-458: - - - - + 1.0 PS1-NTF 0.5 Relative intensity Relative
Scramble GGT Scramble GGT 0.0 shRNA shRNA shRNA shRNA
GGT shRNA scramble shRNA
Figure 62: Knockdown of GGT increases the amount of active γ-secretase complex in HK-2 cells. (A) JC-8 photolabeling of HK-2 cell lysate from GGT shRNA and scramble shRNA stable cell lines. Each cell line was assayed in duplicate. Blocking with excess L-458 demonstrated that JC-8 pull down of active γ-secretase complex was specific. While there was an increase in the amount of active γ-secretase complex in GGT shRNA HK-2 cells as compared to scramble shRNA, there was no change in total expression of PS1 (input). (B) Quantification of PS1-NTF bands from JC-8 activity-based photolabeling western blots.
Knockdown of GGT in the HK-2 GGT knockdown cell line was rescued by transient transfection with an shRNA-resistant, human GGT1 expressing construct, pCMV-GGT (Figure 63A). Transfection with pCMV-GGT rescued GGT protein expression and GGT activity in the HK-2 GGT shRNA cell line (Figure 63A&B). pCMV-GGT decreased γ-secretase activity in the HK-2 GGT shRNA cell line, back to a baseline activity that was not significantly different from scramble shRNA control cells
(Figure 63C). Rescue of the effects of GGT knockdown with transfection of pCMV-
GGT provides strong evidence that GGT regulates activity of the γ-secretase complex in cells.
116
A C 80000 ns GGT *** ** 60000 Scramble shRNA + - - GGT shRNA - + + pCMV-GGT - - + 40000
20000 -Secretase Activity(AU) -Secretase γ B 0 ns Scramble shRNA + - - -Secretase Specific Activity (AU) * GGT shRNAγ - + + 0.8 pCMV-GGT - - +
0.6 * 0.4 GGT 91 shRNA pCMV scramble shRNA pCMV
GGT Activity Activity GGT GGT 91 shRNA pCMV-GGT
(pmol pNA/min) 0.2
0.0 Scramble shRNA + - - GGT shRNA - + + pCMV-GGT - - +
GGT 91 shRNA pCMV scramble shRNA pCMV Figure 63: GGT expressionGGT 91 shRNA pCMV-GGT regulates γ-secretase activity in HK-2 cells. (A) GGT expression is efficiently knocked down in the GGT shRNA stable HK-2 cell line as compared to scramble shRNA control, but GGT expression is rescued when GGT shRNA cell line is transfected with the shRNA resistant GGT1-expressing plasmid pCMV-GGT. (B) Knockdown of GGT in the GGT shRNA cell line significantly decreased the GGT activity in HK-2 cell lysates, as compared to shRNA scramble HK-2 cells. Transfection of the GGT shRNA cell line with pCMV-GGT significantly increased GGT activity of the GGT shRNA cell line, to a level comparable to shRNA scramble control cells. (C) Knockdown of GGT in the GGT shRNA cell line significantly increased the γ-secretase activity of cell lysates in the exocell γ-secretase activity assay, as compared to scramble shRNA control cells. Transfection of GGT shRNA cells with pCMV-GGT significantly decreased γ-secretase activity, to a level comparable to the γ-secretase activity of scramble shRNA control cells.
The effect of GGT on γ-secretase activity also resulted in changes in Notch signaling in the HK-2 cells. The mRNA levels of HES1 and HEY1, two target genes of the Notch signaling pathway, were significantly increased in the GGT shRNA HK-2 cell
117 line, as compared to the scramble shRNA control cell line (Figure 64A&B). GGT not only regulates γ-secretase activity in human kidney cells; the regulation results in downstream changes in Notch signaling.
A HES1HES1 B HEY1HEY1 2.5 2.0 * * 2.0 1.5 1.5 1.0 1.0
0.5 0.5 Relative Quantitation Relative Relative Quantitation Relative
0.0 0.0
GGT shRNA GGT shRNA
scramble shRNA scramble shRNA
Figure 64: Knockdown of GGT increases expression of Notch target genes in HK-2 cells. RNA was extracted from the scramble shRNA and GGT shRNA stable HK-2 cells lines. RT-PCR was used to quantify the level of mRNA transcript for the Notch target genes (A) HES1 and (B) HEY1. Knockdown of GGT significantly increased the mRNA expression of both HES1 and HEY1.
GGT regulates Notch signaling in zebrafish embryos
Since we have shown that GGT regulates γ-secretase activity and Notch signaling biochemically and in cells, we decided to investigate if GGT regulates Notch signaling in vivo. Zebrafish are an attractive model system to use to study the Notch signaling pathway because the role of Notch signaling during embryo development is well studied.
118 Zebrafish embryos are also relatively easy to experimentally manipulate and their large size and clear phenotype is facilitates fluorescent imaging of live embryos. For our experiments, we used an NICD reporter zebrafish line from the AB background strain.
The fish contain a reporter plasmid that expresses GFP in response to NICD, which allows for easy visualization of Notch activity in live, developing embryos via fluorescence imaging of GFP (Figure 65).
UBI-GGT1-AA-Tomato Bright field GGT1 mRNA OR
GFP (NICD) 48 hours
NICD-GFP Reporter Zebrafish Line Tomato (GGT1)
Figure 65: Schematic of experiments to overexpress GGT1 in NICD reporter zebrafish embryos. Zebrafish was used as a model to determine the effect of human GGT1 expression of Notch signaling. The NICD-GFP reporter zebrafish line was used, which expresses GFP when Notch signaling is active. Zebrafish embryos were microinjected at the single cell stage with either UBI-hGGT1-AA-Tomato or hGGT1/Tomato mRNA and after 48 hours fluorescent images were taken of each fish embryo. The expression of GGT1 was measured by red fluorescence from Tomato in the rhodamine channel, and the expression of active Notch (NICD) was measured by green fluorescence from GFP in the GFP channel.
119 Proteins can be overexpressed in zebrafish embryos by microinjection of either mRNA or a DNA expression plasmid when the embryo is at the one cell size stage of development, which results in random, heterogeneous expression of the protein during embryo development (Figure 65). The expressed protein is linked to expression of a reporter, such as Tomato in this case, so GGT expression was tracked using red fluorescence (Figure 65). We used this method to express GGT in NICD reporter line embryos in order to assess if GGT modulates Notch signaling.
A B 800 800 Slope = -2.646 ± 0.8154 600 600 *** 400 400 NICD-GFP NICD-GFP
200 NICD-GFP 200
0 0 50 100 150
Injected GGT-Tomato
Mock-injected
Figure 66: Expression of Ubi-GGT1-AA-Tomato in zebrafish embryos reduces NICD levels. (A) Quantification of GFP expression in NICD-reporter embryos that were either mock-injected or injected with Ubi-GGT1-AA-Tomato plasmid. Injection of the GGT expressing plasmid significantly reduced NICD expression in the embryos. (B) Correlation between the expression of GGT1 (red fluorescence) and the activity of NICD (green fluorescence) for each fish embryo from the group injected with Ubi-GGT1-AA-Tomato. There was a significant correlation with a slope of -2.646 and a 95% CI of ±0.8154.
NICD-GFP reporter embryos were either mock-injected or injected with an expression plasmid containing human GGT1 linked to Tomato under the control of a
120 ubiquitin promoter, UBI-GGT1-AA-Tomato, at the single cell stage. Green, red, and brightfield images were taken of the fish 2 days post fertilization (dpf). The mean fluorescence intensity for both GFP and rhodamine channels was quantified by hand- selecting the entire body of each fish in the images. Background fluorescence was subtracted for each image for normalization between images. For the injected fish, those with a mean fluorescence intensity of less than 40 were removed from the analysis because there was no detectable expression of GGT. The mean GFP fluorescence intensity for all mock-injected fish (n=26) was compared to that of the injected fish
(n=27) (Figure 66A). Expression of GGT in the embryos significantly decreased NICD activity on average among all of the embryos (Figure 66A). The mean fluorescence intensity of NICD-GFP and GGT-Tomato of each injected fish was graphed on a scatter plot to assess correlation (Figure 66B). There was a significant negative linear correlation between NICD and GGT levels, with a slope of -2.646 ± 0.8154 ( ± 95% CI)
(Figure 66B). The results show that expression of GGT is able to inhibit Notch signaling in vivo, which is consistent with our hypothesis.
NICD embryos were also either mock-injected or injected with human
GGT1/Tomato mRNA is a separate experiment since mRNA can sometimes result in stronger protein expression. The embryos were analyzed as before, except fish with a mean fluorescence intensity of less than 20 were removed from the analysis because there was no detectable expression of GGT. Embryos injected with GGT mRNA (n=25) had a significantly lower mean GFP fluorescence intensity as compared to mock-injected embryos (n=47) (Figure 67A). There was also a significant negative correlation between
121 NICD-GFP and GGT-Tomato mean fluorescence intensity (as determined from a scatter plot of each fish), with a slope of -3.895 ± 0.9252 ( ± 95% CI) (Figure 67B).
A B 600 600 Slope = -3.895 ± 0.9252 400 *** 400
NICD-GFP 200 200 NICD-GFP
0 0 20 40 60 80 Injected GGT-Tomato
Mock-injected
Figure 67: Expression of GGT1 mRNA in zebrafish embryos reduces NICD levels. (A) Quantification of GFP expression in NICD-reporter embryos that were either mock- injected or injected with GGT1 mRNA/Tomato. Injection of GGT1 mRNA significantly reduced NICD expression in the embryos. (B) Correlation between the expression of GGT1 (red fluorescence) and the activity of NICD (green fluorescence) for each fish embryo from the group injected with GGT1 mRNA/Tomato. There was a significant correlation with a slope of -3.895 and a 95% CI of ±0.9252.
4.3 Discussion and Conclusion
Overall, these experiments support our hypothesis that GGT is a negative modulator of γ-secretase activity and Notch signaling in the kidney. Biochemical assays with purified GGT and γ-secretase complex have verified that the previously purified kidney
122 endogenous inhibitor is indeed GGT. GGT alone is sufficient to inhibit γ-secretase enzymatic activity for processing of Notch and APP. GGT inhibits γ-secretase activity in a manner that requires GGT enzymatic activity, and likely involves some sort of structural modification that is specific to the presenilin subunit. Further experiments are necessary to fully understand the GGT inhibitory mechanism of action. As a next step in the project, mass spectrometry of the purified γ-secretase and purified GGT biochemical assay may help to paint a clearer picture of the exact mechanism.
In addition to identifying GGT as the kidney specific endogenous inhibitor of γ- secretase, cellular and in vivo studies have shown that GGT can regulate Notch signaling in a biological context. In a human renal proximal tubule cell line, HK-2, GGT knockdown and over-expression have shown that GGT activity inhibits γ-secretase activity and expression of downstream Notch target genes in a cellular context. We also used zebrafish embryos as a model system to assess the effect of GGT expression on
Notch signaling in vivo. Since inhibition of Notch signaling by GGT expression was also observed in the in vivo zebrafish model, it suggests that the interaction of γ-secretase and
GGT may play a role in other biological or pathological processes as a mechanism to specifically regulate the Notch pathway in the kidney. Further experiments are needed to assess if GGT activity affects Notch signaling in kidney disease models. However, in summary, this body of work supports further investigation of GGT in kidney disease models and suggests that GGT may perhaps be a novel drug target to inhibit Notch signaling in a kidney-specific manner, which could potentially be translated into novel therapies for chronic kidney disease.
123 CHAPTER 5
Summary and Conclusions
Notch signaling is essential during vertebrate development and also plays an important role in cell fate decisions of many adult stems cells by maintaining stem and progenitor cell populations [29, 30]. The exact role of Notch signaling, during both development and in mature organisms, is complex and its function can widely vary between different tissues and cellular contexts. For instance, Notch signaling can either inhibit or promote differentiation depending on the organ stem or progenitor cells originate from [31]. Regulation of Notch signaling is tightly controlled since aberrant activation or suppression of Notch has pathologic consequences in a wide array of diseases, including cancer and kidney disease.
Regulation of the Notch signaling occurs via regulated intramembrane proteolysis
(RIP). During RIP, Notch, first undergo ectodomain shedding which allows for γ- secretase to cleave the membrane-bound fragment (NEXT) within the lipid bilayer to liberate the Notch intracellular signaling domain, NICD, which travel to the nucleus to affect gene transcription [1]. The mechanisms that regulate γ-secretase activity during
RIP remain to be fully understood; however, many studies on γ-secretase regulation have described an interaction of the complex with unique, modulatory protein subunits, which can either inhibit or stimulate enzymatic activity [20]. Only a fraction of cellular steady- state γ-secretase complexes are catalytically active, which begs the question as to what is the biological function of the inactive complexes [24-26].
124 The main research question we aimed to address in this thesis is: can γ-secretase activity be modulated to regulate RIP of Notch in a tissue- and context-specific manner?
Our hypothesis was that signaling of Notch is regulated during biological processes and in response to environmental stimuli by interaction of γ-secretase with distinct, cell type- specific protein modulators. We propose a model where these γ-secretase protein modulators dynamically regulate the equilibrium between active and inactive complexes in order to modulate γ-secretase enzymatic activity and processing of the Notch substrate.
In my thesis, I have investigated this hypothesis in two projects; both projects aimed to elucidate the biological role of a novel γ-secretase protein modulator in two different tissue and disease models: the kidney nephron and breast cancer stems cells (Figure 68).
Gamma-glutamyl transferase (GGT) was recently identified in our lab as a putative, novel, endogenous inhibitor of γ-secretase activity in the kidney. We have also recently published a discovery that, in hypoxic breast cancer, Hif-1α directly associates with and activates the γ-secretase complex to induce cleavage of Notch, resulting in increased tumor progression and metastasis [275]. The results of my thesis work are consistent with the hypothesis that Notch can be regulated in a tissue and context specific manner by γ- secretase protein modulators. In both models, GGT and Hif-1α directly modulate γ- secretase activity in order to affect downstream Notch signaling. GGT inhibits γ-secretase activity, but GGT expression is restricted a few tissues, with by far the highest levels in the renal tubule cells of the kidney nephron [257]. Hif-1α activates γ-secretase activity, but Hif-1α expression is directly modulated by environmental (hypoxia) or biological
(mammosphere formation) changes. In one system, Notch signaling is regulated in a tissue-specific manner by patterned expression of GGT and, in the other system, Notch is
125 regulated in a contextual-manner by oxygen-mediated post-translational regulation of
Hif-1α or expression of NOS in a cancer stem cell subpopulation (Figure 68).
Kidney nephron! Breast cancer stem cells !
GGT Notch Notch γ-Secretase Small γ-Secretase Extracellular Large
HIF-1α O2 Cytosol HIF-1α
iNOS%
Degradation NICD via proteosome Renal epithelial Metastasis CSL cell proliferation CSL BCSC growth
Fibrosis Differentiation Glomerulsclerosis
Figure 68: Hypothesized thesis model. A depiction of two distinct cellular signaling pathways in different tissue and disease models that utilize γ-secretase modulatory proteins to regulate Notch signaling. In the kidney nephron, GGT inhibits the γ- secretase complex and Notch transcription. Silencing of Notch is required for proliferation of renal epithelial cells and to prevent two kidney pathologies that are major contributors to end-stage renal disease, kidney fibrosis and glomerulosclerosis. In breast cancer stem cells, Hif-1α expression is increased in an oxygen independent manner, resulting from S-nitrosylation of Hif-1α by NOS in order to prevent Hif-1α degradation via the proteasome. The stabilized Hif-1α is then able to bind to and activate the γ-secretase complex. γ-Secretase activation increased NICD production and transcription of Notch target genes, which promotes metastasis, BCSC growth, and dedifferentiation in breast cancer cells.
126 In the first project, we investigated the non-transcriptional role of Hif-1α in breast cancer stem cells (BCSCs). Tumor hypoxia contributes to the metastatic progression of breast cancer by promoting BCSC proliferation and activation of Notch signaling [169,
275, 288]. We hypothesized that Hif-1α- mediated activation γ-secretase/Notch is critical for the regulation of BCSCs. Mammospheres were used as a model to investigated the role of γ-secretase activity in the regulation of the BCSC population.
In the present study, we show, for the first time, that γ-secretase activity is upregulated by Hif-1α in the BCSC-like mammosphere cell population. Hif-1α signaling is necessary for mammosphere formation; however, its transcriptional activity is not required. We show that Hif-1α association with γ-secretase serves as a mechanism to promote Notch signaling and BCSC proliferation. While Hif-1α is known to regulate
BSCSs [199], our work has described an unconventional mechanism of action for Hif-1α in this cell population, where it acts as an enzyme subunit, rather than its canonical role as a transcription factor.
Our study has also discovered a non-canonical, oxygen-independent regulation of
Hif-1α by NOS that has not been previously described in breast cancer stem cells.
Inhibitor-based studies have implicated iNOS in BCSC proliferation [167]; however, we have revealed that the iNOS isoform of NOS regulates Hif-1α expression and Notch signaling in a BCSC model, and that this interaction is required for mammosphere formation. NOS has previously been described to regulate Notch signaling in only two published studies (in glioma and cholangiocarcinoma) [289, 290]. In addition, NO has been suggested as a key mediator of inflammation-induced tumorigenesis, so it may be interesting to investigate if Notch signaling plays a role in that process as well [291]. It
127 has become increasing clear that Hif-1α expression can be expressed in normoxic tumors
[292], which has important implications for many therapies currently under development.
Multiple studies have reported that Hif-1α expression is induced by chemotherapy and radiation in an oxygen independent manner that is possibly mediated by NOS [147, 166,
293].
The results of this project may have broader implications for the function of Hif-1α outside its canonical role as a transcription factor and oxygen-sensitive moiety in other biological contexts and systems. Future questions include: does this signaling mechanism play a role in other biological systems, such as other cancers or even normal stem cell function? In addition, these studies demonstrate that inhibition of γ-secretase or NOS has therapeutic potential to ameliorate the progression of metastasis from highly aggressive and poorly differentiated breast tumors, which is potentially relevant for current clinical trials involving GSIs as BCSC-targeting agents [181].
In the second project, we have investigated a recently purified, novel γ-secretase inhibitor in the kidney. Biochemical experiments established that GGT is sufficient to inhibit the γ-secretase complex in an activity-dependent manner and began to elucidate the inhibitory mechanism of action. We also found that GGT expression regulates γ- secretase activity and Notch signaling in both a human kidney cell line and an in vivo zebrafish embryo model.
Our work has identified GGT as a novel regulator of both γ-secretase activity and
Notch signaling. It also describes a novel function for GGT, which functions as an enzyme to break down GSH and regulate cellular cysteine levels. There is very little
128 published on GGT function outside its canonical role; however, one study found that
GGT functioned as a bone growth factor to promote osteoblast proliferation in a non- canonical mechanism that did not involve GSH catalysis [294]. This is quite interesting as Notch signaling is known to regulate differentiation of osteocyte progenitors [295]. In addition, Notch was previously shown to be enzymatically deglycinated by a negative regulator, Botch, which is a gamma-glutamyl cyclotransferase enzyme [296].
While identification GGT as a γ-secretase inhibitor might be interesting, why would
γ-secretase or Notch need a negative regulator in the kidney to begin with? Notch signaling is critical for kidney development, but is silenced in healthy adult kidneys; reactivation of Notch contributes to the progression of chronic kidney disease [233].
Notch signaling is high in renal proximal tubule cell precursors during development, but almost no Notch activity remains in these cells post development [234]. On the other hand, GGT expression is very low in the kidney neonate, but is increased after birth and localized mainly to the renal proximal tubule cells [257].
We hypothesize that GGT may act as mechanism to repress Notch signaling after kidney development by inactivating γ-secretase, and that loss of this inhibition can have pathogenic consequences. If this hypothesis is correct, GGT could potentially be a novel drug target to modulate Notch signaling in chronic kidney disease. However, future studies are necessary to determine experimentally if GGT expression affects kidney disease models. While Notch has been an attractive drug target for multiple kidney diseases, clinical development of GSIs has been limited by off-target side effects resulting from non-specific Notch inhibition [17]. Identification of novel γ-secretase protein modulators may aid in the future development therapeutics by offering new drug
129 targets that modulate Notch signaling in a more specific manner to reduce the dose- limiting toxicities that occur with GSIs.
130 CHAPTER 6
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