UNIVERSITY of CALIFORNIA IRVINE Targeting Eif4f Translation

UNIVERSITY OF CALIFORNIA

IRVINE

Targeting eIF4F Translation Initiation Complex in order to Sensitize Blood Malignancies

to Targeted Agents

Submitted in partial satisfaction of the requirements

for the degree of

DOCTOR OF PHILOSOPHY

In Biological Sciences

Lee-or Herzog

Dissertation Committee:

Professor David A. Fruman Professor Craig M. Walsh Associate professor Mei Kong Associate Professor Olga V. Razorenova

2020

DEDICATION

To Eitan Herzog - My dearest son. You are my soul. You mean everything to me.

To my dear parents – For always believing in me, supporting me and guiding me.

To Ella, May and Ilan - For your constant encouragement, laughter and help.

To my grandparents - Who are always on my mind. I keep my promises every day.

To Dr. David Fruman – For your outstanding mentorship, for your help and for helping me become a better scientist each day.

To my committee members – for your encouragement, useful suggestions and for helping me improve my scientific skills.

To my mentees and team – I could not have done this without you. Thank you very much for all your help, your dedication and for making an impact on translational science.

To my lab mates – Thank you for your help, for making the lab such a great place to work in, for your support and the good time we shared together.

TABLE OF CONTENTS

LIST OF FIGURES………………………………………………………………….. iv

LIST OF TABLES…………………………………………………………………… vi

ACKNOWLEDGEMENTS………………………………………………………...... vii

CURRICULUM VITAE……………………………………………………………... iix

ABSTRACT OF THE DISSERTATION…………………………………………….. x

CHAPTER 1: Introduction….……………………………………………………….. 1

CHAPTER 2: Targeting eIF4F Translation Initiation Complex with SBI-756

Sensitizes B Lymphoma Cells to Venetoclax ……………………………………….. 97

CHAPTER 3: Targeting eIF4F translation complex sensitizes B-ALL cells to tyrosine kinase inhibition…….……………………………………………………….. 165

CHAPTER 4: Significance, discussion and future directions……………………….. 200

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LIST OF FIGURES

Figure Title Page number Figure 1.1 The hallmarks of cancer and therapeutic targeting of them 3 Figure 1.2 Overview of mTORC1 and mTORC2 Complexes, Key Substrates, and Inhibitors 4 Figure 1.3 mTOR acts as a nutrient sensor coordinating cellular functions 6 Figure 1.4 Mechanisms of oncogenic activation of PI3K/AKT or loss of PTEN 7 Figure 1.5 The Philadelphia Chromosome 10 Figure 1.6 Overview of BCL-2 family protein interactions 20 Figure 1.7 Extrinsic and intrinsic apoptotic signaling pathways 22 Figure 1.8 Targeting mTOR Pathway as a Therapeutic Strategy 44 Figure 1.9 Convergence of major signaling pathways involved in cancer toward the eIF4F 47 complex Figure 1.10 Components of eIF4F translation initiation machinery complex, and inhibitors 49 Figure 2.1 mTORC1 regulates eIF4E dependent translation via phosphorylation of 4E-BP1 112 Figure 2.2 Constitutively active 4E-BP1 mutant sensitizes lymphoma cells to venetoclax 114 (ABT-199) and navitoclax (ABT-263) similar to TOR-KI combination Figure 2.3 SBI-756 prevents eIF4E-eIF4G interaction 115 Figure 2.4 SBI-756 treatment suppresses cap-dependent translation 116 Figure 2.5 SBI-756 does not change mTOR substrate phosphorylation 117 Figure 2.6 Treatment with SBI-756 sensitizes DLBCL and MCL cells to venetoclax 119 combinational treatment Figure 2.7 Treatment with SBI-756 sensitizes DLBCL and MCL cells to venetoclax 120 combinational treatment Figure 2.8 SBI-756 in combination with venetoclax induces apoptosis 121 Figure 2.9 4E-BP1 KO clones are insensitive to TOR-KI treatment, yet remain sensitive to 123 SBI-756 treatment Figure 2.10 Lymphoma cell lacking 4EBP1 are resistant to TOR-KI yet are sensitive to SBI- 124 756 treatment Figure 2.11 SBI-756 sensitizes to venetoclax treatment in vivo 125 Figure 2.12 Venetoclax and SBI-756 combination is tolerable and retains mTOR 127 functionality, while reduces tumor volume in vivo

Figure 2.13 SBI-756 induces a decrease in MCL-1, BCL-xL, survivin, eIF4E and eIF4G 129 Figure 2.14 Selective reduction of mRNA translation following 4 hours SBI-756 treatment 131 Figure 2.15 SBI-756 treatment reduces protein synthesis following 16 hours of treatment 133 Figure 2.16 SBI-756 is not cytotoxic to human CD4+T cells, CD8+ T cells, NK cells or 135 monocytes Figure 2.17 B lymphocytes are more sensitive to eIF4F targeting than other PBMCs 137 Figure 2.18 Components of eIF4F translation initiation machinery complex, and inhibitors 140 Figure 2.19 Model for mechanism of venetoclax sensitization by SBI-756 142 Figure 3.1 Schematic diagram of the PI3K/ mTOR/ eIF4E signaling pathway and inhibitors 167 used in this study to target the pathway Figure 3.2 4E-BP mediates cytotoxicity of TORC1 inhibition 170 Figure 3.3 Reduced Eif4e gene dosage sensitizes to dasatinib 172 Figure 3.4 Targeting the eIF4F complex sensitizes p190 cells to dasatinib 173 Figure 3.5 Targeting the eIF4F complex suppresses colony formation to similar extent as 173 targeting mTORC1 Figure 3.6 SBI-576 sensitizes similar to mTOR inhibition but does not inhibit mTOR 174 Figure 3.7 Reduced eIF4E availability leads to reduction in protein synthesis 175 Figure 3.8 SBI sensitizes human Ph+ and Ph-like B-ALL cell lines and stromal-dependent 176 lines to dasatinib treatment Figure 3.9 SBI-756 is selectively toxic to B cells 177 Figure 3.10 SBI-576 reduces eIF4E:eIF4G1 interaction in vivo in a dose-dependent manner 178 Figure 3.11 Combination of SBI-756 and dasatinib reduces B-ALL leukemic burden while 180 suppress eIF4E:eIF4G interaction in vivo Figure 3.12 MLN0128 or SBI-756 treatment prime cells towards apoptosis 181 Figure 4.1 Strategies for evading apoptosis 206 Figure 4.2 TOR-KI and SBI-756 treatments sensitize AML cells to venetoclax combination 211 Figure 4.3 eIF4F variants reprogram the cellular translatome in response to distinct stimuli 217 Figure 4.4 Schematic diagram of the genetic model that enables conditional reduction in 219 eIF4E expression

LIST OF TABLES

Table Title Page number

Table 2.1 The sequences used for guiding Cas9 to 4EBP1 108

Table 2.2 The sequences used for guiding Cas9 to 4EBP2 108

Table 2.3 Genes found to be translationally down-regulated following eIF4F 150 suppression

Table 2.4 Negative regulators of apoptosis genes that were found to be 164 translationally downregulated following eIF4F inhibition

ACKNOWLEDGMENTS

• This study was supported by: National Institutes of Health grants R01-CA158383 (to Dr.

Fruman), UC Irvine Cancer Research Institute pilot grant from the 2018 Anti-Cancer

Challenge (to Dr. Fruman), Bridge Grant from the American Society of Hematology (to Dr.

Fruman), and by Cancer Center Support Grant P30-CA062203 to UC Irvine.

• I was supported by National Institutes of Health grant T32 AI 060573. I want to thank Dr.

Eric Pearlman, Dr. Amanda Burkhardt and Ms. Rebecca Taylor for believing in me, giving

me a chance to do the research that I wanted, and for their constant support.

• I thank Dr. Selina Chen-Kiang and Dr. Maurizio Di Liberto for providing MCL cell lines.

• I want to thank Dr. Bert Semler for providing us with the dual-luciferase reporter construct,

and for Dr. Grant MacGregor for his assistance with performance of dual-luciferase assays

and establishment of mouse models.

• I thank Dr. Adeela Syed for her great assistance with microscopy imaging, her patience and

for her training.

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CURRICULUM VITAE EDUCATION • University of California, Irvine (UCI), California 09/2015 Ph.D. in Biological sciences - Molecular Biology & Biochemistry • Tel Aviv University, Tel Aviv, Israel 06/2012 M.Sc. in Medical Sciences (Magna cum Laude) • The Hebrew University of Jerusalem, Jerusalem, Israel 06/2005 B.Sc. in Biological Sciences

RESEARCH EXPERIENCE • Oncology & Immunology, University of California, Irvine (UCI) 08/2015 - Present Graduate Student Researcher Project manager - Managing 5 research projects and 12 students to achieve goals within budget. Scientific writer - Published 3 peer-reviewed scientific publications (5 more in process) in international journals. Scientific communicator - 14 scientific presentations that received 10 awards. Collaborator - Identified and supported 5 research opportunities, that led to 3 publications.

• Weizmann Institute of Science, Rehovot, Israel 06/2014 – 05/2015 Senior Research Assistant and Lab Technician Conducted diverse biological methods at the Antibodies unit and the Microbiology unit, such as: full production of monoclonal and polyclonal antibodies, tissue culture, protein purification, antibodies labeling (CyTOF), plasmid production, directed fermentations, DASGIP controlled fermentations, microscopy and diverse microbiology methods. Managed databases constant update and drafting of lab protocols, reports and SOPs.

• CorAssist Cardiovascular, Herzliya, Israel 01/2014 – 04/2014 Preclinical and Clinical Research Assistant As research and development coordinator, oversaw the entire research process, development of medical device, ethics committees, practical work, operations and follow ups. Wrote research and quality assurance documentation (all inspected and approved during a successful ISO audit).

• HY Laboratories, Rehovot, Israel 10/2012 – 11/2013 Technical Writer and Quality Assurance Associate Researched at GMP and ISO 17025 conditions, authored all laboratory documents (e.g. protocols, reports, SOPs) for medical devices and pharmaceutical customers for submission to regulatory authorities (FDA and CE). Conducted and certified to perform all the tests offered by the lab (Sterility, LAL, Bioburden etc.). Supervised research, development and production projects for FDA approval.

• Israeli Ministry of Defense, Tel-Aviv, Israel 08/2005 – 08/2011 Nuclear, Biological and Chemical Protection Division Officer (Captain) Managed and coordinated high-budgeted, advanced scientific projects on a national level through all stages. Managed multi-million-dollar projects in advanced engineering systems & technologies. Professionally led and oversaw medical and biological projects (GMP and GLP levels). Performed biologically and medically oriented research, project management and literature research.

PUBLICATIONS • Lee J.S., et al. (2018). Statins enhance efficacy of venetoclax in blood cancers. Science Translational Medicine. 10 (445), pp. 19904. • Gotesman M., Vo T.T., Herzog L., et al. (2018). mTOR kinase inhibition enhances efficacy of dasatinib in Ph-like B-ALL cells carrying ABL1 rearrangements. Oncotarget. 9:6562-6571.

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• Moskovich O., Herzog L., Ehrlich M.,and Fishelson Z. (2012). Caveolin-1 and dynamin-2 are essential for removal of the complement C5b-9 complex via endocytosis. The Journal of Biological Chemistry. 287(24), pp. 19904.

ABSTRACTS • Herzog L. et al. (2019). Targeting eIF4F Protein Translation Initiation Complex Sensitizes Non- Hodgkin’s Lymphoma to Venetoclax Treatment. The Hematologic Malignancies Conference, FASEB Conference, Snowmass, CO • Herzog L. et al. (2019). Targeting eIF4F Protein Translation Initiation Complex Sensitizes Non- Hodgkin’s Lymphoma to Venetoclax Treatment. The American Association of Immunologists (AAI), Los Angeles, CA • Herzog L., et al. (2018). A novel inhibitor of eIF4F protein translation complex sensitizes DLBCL cells to BCL2 targeted therapy. AACR Annual Meeting 2018 in Chicago, Illinois • Herzog L., et al. (2017). Targeting Translation Initiation Complex Sensitizes DLBCL Cells to BCL2 Targeted Therapy. Institute for Clinical and Translational Science (ICTS) Conference • Herzog L., et al. (2017). Sensitization of DLBCL Cells to ABT-199 by Targeting Translation Initiation Complex. UCI Campus-Wide Symposium On Basic Cancer Research, Chao Family Comprehensive Cancer Center • Herzog L., and Leitner O. (2015). The Antibodies Unit. The Weizmann Institute of Science.

MENTORING EXPERIENCE • Dr. David Fruman’s laboratory, UCI, Irvine, CA 09/2016 Mentor and trainer of three graduate and eight undergraduate students in the laboratory. Training and supervising experimental designs, performance and data analysis of research projects with various research techniques. • CampMed at UCI, Irvine, CA 01/2016–Present CampMed counselor and mentor for the 2016 program. Counseled and mentored in non-profit educational-enrichment program that contains a mentorship program to assist high-school students faced with socio-economic barriers and encourage pursue of higher education (undergraduate and graduate) in medicine.

SCHOLARSHIPS AND AWARDS Assisted in obtaining Bridge Grant, The American Society of Hematology (ASH) ($150K) 03/2019 2nd place best presentation, UC Irvine Immunology Fair, UCI, CA ($1K) 12/2018 NIH T32 Immunology Training Grant Trainee, UCI - Institute for Immunology, CA ($38K) 09/2018 – Present AACR Annual meeting 2018: Scholar-in-Training Award, American Association for Cancer Research ($2K) 04/2018 2nd place best Biology & Medicine Presentation, UCI AGS Symposium, UCI, CA ($400) 04/2018 Student Travel Award 2018, UCI Diverse Educational Community and Doctoral Experience (DECADE) ($1K) 03/2018 Best oral presentation, Department of Molecular Biology & Biochemistry, UCI, CA ($200) 03/2018 The Art of Research Award, Chao Family Comprehensive Cancer Center, UCI, CA ($1K) 06/2017 Outstanding Graduate Counselor, CampMed, UCI, CA 04/2016 Lod Valley Municipality Scholarship for Academic Excellence, Ganot, Israel ($20K) 11/2010-11/2011

COURSES AND TRAINING Regulatory affairs (RA) of pharmaceutical products, and regulations of medical devices 07/2018-06/2019 Nature Masterclasses online course in Scientific Writing and Publishing. Nature Publishing Group 06/2017 Project management and professional coordinators officers training - IMOD, Israel 11/2009

ABSTRACT OF THE DISSERTATION

Targeting eIF4F Translation Initiation Complex Sensitizes Blood Cancers to Targeted Agents

Lee-or Herzog

Doctor of Philosophy in Biological Sciences

University of California, Irvine, 2020

Professor David A. Fruman, Chair

One of the most frequently transformed signaling networks in cancer is the PI3K/mTOR

/eIF4F signaling pathway. Through harmonized regulation of mTOR and eIF4F, as well as other overlapping signaling pathways, cancer cells achieve elevated proliferation, cell growth (increase in size), metabolism and survival. The key aim of this dissertation work is to identify and characterize critical signaling components of the PI3K/mTOR/eIF4F signaling pathway using both aggressive non-Hodgkin’s lymphoma (NHL) and Philadelphia chromosome-positive (Ph+) acute leukemia models. Our goal is to identify molecular mechanisms that could be exploited in order to improve responses to specific targeted agents: venetoclax (BCL2 inhibitor) in the case of aggressive NHL (chapter 2), and the tyrosine kinase inhibitor dasatinib for Ph+ acute leukemia

(chapter 3).

The BCL2 inhibitor venetoclax has shown efficacy in several hematologic malignancies, with the greatest response rates in indolent blood cancers such as chronic lymphocytic leukemia

(CLL). In aggressive NHL, including diffuse large B-cell lymphoma (DLBCL) and mantle cell lymphoma (MCL), there is a lower response rate to venetoclax monotherapy. At the same time,

indications about the importance of mTOR signaling pathway and regulation of mRNA translation via eIF4F complex assembly have been accumulating.

In chapter 2 of this work, we demonstrate that small molecule inhibitors of cap-dependent mRNA translation sensitize NHL cells to apoptosis induced by venetoclax. We compared the mTOR kinase inhibitor (TOR-KI) MLN0128 with SBI-756, a compound targeting eukaryotic translation initiation factor 4G1 (eIF4G1), a scaffolding protein in the eIF4F complex. Treatment of NHL cells with SBI-756 synergized with venetoclax to induce apoptosis in vitro, and enhanced venetoclax efficacy in vivo at a tolerable dose. SBI-756 prevented eIF4E-eIF4G association and cap-dependent translation in a dose-dependent manner, while retaining mTOR substrate phosphorylation – indication of a great advantage over TOR-KIs. In addition, SBI-756 retained its ability to sensitize DLBCL cells to venetoclax even when those cells were lacking eIF4E binding protein-1 (4E-BP1), while these cells were insensitive to TOR-KI treatment.

Moreover, SBI-756 treatment selectively reduced translation of mRNAs encoding ribosomal proteins and translation factors, hence leading to a delayed suppression in protein synthesis rates in sensitive cells. Furthermore, when human peripheral blood mononuclear cells were treated with SBI-756, only B lymphocytes had displayed reduced viability.

Moreover, we show the importance of eIF4E to support B-ALL survival. In chapter 3 of this work we demonstrate that treatment of Ph+ B-ALL cells with SBI-756 was able to reduce eIF4F complex formation (prevention of eIF4E-eIF4G interaction) in vitro and in vivo. At the same time, we developed a novel inducible system which enabled control of eIF4E availability.

In both chemical and genetic approaches, we have shown that reduction of eIF4F complex formation sensitizes Ph+ B-ALL cells to dasatinib treatment. Similarly to the findings in NHL, both chemical and genetic suppression of eIF4F complex formation have resulted in reduced

protein synthesis, reduced survival and sensitization to dasatinib. Lastly, treatment with SBI-756 was found cytotoxic with selectivity for B cells, while the compound was well tolerated in vivo.

Together, our findings using both NHL and B-ALL systems indicate that the eIF4F complex formation is an “Achilles heel” of aggressive blood malignancies and could be exploited for targeted therapy. Specifically, our abilities (chemically and genetically) to reduce eIF4F complex formation and mRNA translation provide a druggable and specific target with potential to improve treatment of NHL, B-ALL patients, and maybe others as well.

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Chapter One:

Introduction

Resisting cell death – a targetable hallmark of cancer

The main goal of cancer therapies has always been to deliver treatments in a specific manner that would target cancer cells, while sparing normal ones. The first effective chemotherapies took advantage of transformed cells’ addiction to rapidly proliferate1, yet toxicity towards normal dividing cells contributes to the common side effects associated with chemotherapy. Despite much advancement in modern chemotherapies ability to improve patient responses and manage toxicities, many patients fail to respond and require alternative therapies.

Therefore, much effort is given to identify effective therapies that target malignant cells specifically. Targeted therapies that aim to suppress pathways or processes on which tumor cells depend provide hope to efficiently target those cells and kill them, with minimal residual toxicity. One example of a successful targeted therapy is imatinib (Novartis commercial name

“Gleevec”), which yielded impressive responses in chronic myelogenous leukemias driven by the BCR-ABL translocation with few toxicities2,3. Concurring with this early achievement, decades of research that expanded our understanding of the characteristics of cancer cells were aggregated in the paper: “The Hallmarks of Cancer”4. In their seminal paper, Dr. Hanahan and

Dr. Weinberg summarized the features required for malignant cells to evolve and proliferate, as well as emphasize potential susceptibilities, which could be exploited via targeted therapies.

Indeed, a decade after the initial paper, a follow-up review article claimed that almost every hallmark of cancer may be targeted using an existing or newly discovered compound4 (Figure

1.1.). One of the important hallmarks of cancer, the ability to resist cell death, is a promising target for therapies to induce tumor-selective programmed cell death (apoptosis). This dissertation work extends upon this idea and focuses on identifying tolerable combination

therapies that specifically and efficiently target the cell death machinery to obtain selective killing of malignant cells, particularly B cell lymphoma and pre-B cell leukemia.

Figure 1.1: The hallmarks of cancer and therapeutic targeting of them. Various drugs have been developed to interfere with each of the acquired capabilities necessary for tumor growth and progression. These drugs are either in clinical trials or in some cases approved for clinical use in treating certain forms of human cancer. This figure illustrates some examples that were used in this study. This figure was adopted from Hanahan D., and Weinberg R.A. (2011). Cell. 4;144(5):646-74.

PI3K/mTOR pathway activation in cancer and in normal cells/growth factor signaling

One of the main challenges of cancer therapy is identification of targets whose function is critical for malignant cells’ survival yet nonessential among normal cells. This dissertation discusses the emerging genetic and pharmacologic evidence for targeting the phosphoinositide 3- kinase (PI3K) and mechanistic target of rapamycin (mTOR) to provide unprecedented balance of anti-cancer tolerability and efficacy. Like normal cells, cancer cells rely on complex signaling 3

networks and pathways to integrate external and internal signals which control an array of coordinated processes, and by that regulate their proliferation and growth. Beginning with the identification of oncogenes, many scientific advances have progressed our understanding of the molecular changes that occur and regulate those processes. The PI3K/mTOR signaling pathway is among the most notable signaling networks altered in cancer. This important pathway promotes not only cell growth (increase in cell size), proliferation (cell number), and anabolic metabolism, but also cell survival (Fig. 1.2), with elevated pathway activity driving resistance to antiproliferative and apoptotic cues5–7. Due to ubiquity of

PI3K/mTOR signaling aberrations in cancer, many attempts have been made to identify the mechanisms that drive uncontrollable proliferation and survival by this pathway, making this an area of intense investigation.

Although mTOR regulates many downstream signaling pathways, one of the most important ones is the formation of the eIF4F complex that drives cap- dependent mRNA translation. Our lab and others have shown the critical role that eIF4F complex formation Figure 1.2: Overview of mTORC1 and mTORC2 Complexes, Key Substrates, and plays in both B-cell differentiation8 as well as supporting Inhibitors. The most well-known substrates of the two complexes and different classes of survival of various malignancies7,9–11. mTOR inhibitors are shown 278. First- generation rapalogs are partial inhibitors of The two central themes of this dissertation are: 1) mTORC1 that inhibit phosphorylation of S6Ks more than 4E-BPs. Second-generation TOR-KIs fully inhibit mTORC1 and The importance of the mTOR/eIF4F signaling axis to mTORC2. Third-generation RapaLinks fully but selectively inhibit mTORC1 and also blood malignancies; and 2) The attempts that we have overcome single resistance mutations to rapalogs and TOR-KIs. Reference: Fruman D.A., et al. (2017). Cell 170.

made to target this crucial signaling axis in order to sensitize those blood malignancies to targeted agents (e.g. venetoclax and dasatinib).

The mechanistic target of rapamycin (mTOR) is an evolutionary conserved Ser/Thr kinase that belongs to the PI3K-related kinase (PIKK) family. In normal healthy cells, mTOR activity is tightly controlled by growth factor signals and the availability of nutrients. mTOR activation promotes many cellular processes including mRNA translation, lipid biogenesis, and nucleotide synthesis. mTOR activation by PI3K plays a role in a complex chain of processes both up- and downstream of AKT (protein kinase B). Upstream of AKT, the mTOR kinase forms the mTOR complex 2 (mTORC2) defined by the rapamycin-insensitive companion of TOR (Rictor) subunit and also consisting of the mammalian lethal with Sec13 protein 8 (mLST8), the endogenous inhibitor DEP-domain-containing mTOR-interacting protein (Deptor), mammalian stress- activated protein kinase interacting protein (mSIN1) and protein observed with rictor-1 (Protor)

(Fig. 1.3). Downstream of AKT, mTOR forms the mTOR complex 1 (mTORC1) defined by the regulatory-associated protein of mTOR (Raptor) subunit and containing mLST8, proline rich

AKT substrate 40 kDa (PRAS40) and Deptor (Fig. 1.3). mTORC2 phosphorylates serine473 in the hydrophobic motif of AKT which is important for its activation, though the functional importance is still debated. mTORC1 is activated by AKT and other signals to promote biosynthetic processes necessary for growth and proliferation 12.

PTEN is a lipid phosphatase that counteracts the lipid-kinase activity of PI3K, and is the

most important negative regulator of the PI3K signaling pathway13,14. In addition to its canonical,

PI3K inhibition-dependent functions, PTEN can also function as a tumor suppressor in a PI3K-

independent manner. A loss of PTEN function enables the constitutive elevation of 3-

phosphoinositide levels, leading to oncogenic transformation13,15. One way in which PTEN loss

of function can occur is through mutations in the PTEN gene itself, while another way is through

other mechanisms including dysregulation of microRNAs that affect PTEN expression16–20.

Figure 1.3: mTOR acts as a nutrient sensor coordinating cellular functions. mTOR operates within two functionally and structurally distinct complexes: mTORC1 and mTORC2. Growth factors or hormones activate the PI3K/AKT or ERK signaling pathways, which stimulates mTORC1. The activity of mTORC1 is also positively regulated by amino acid– mediated stimulation of the RAG complex of GTPases. It is suppressed under conditions where energy or glucose is limiting through AMPK signaling. mTORC1 orchestrates several anabolic processes as well as protein synthesis in part through its two main effectors: S6K and 4E-BP1. It also stimulates mitochondrial function, lysosome biogenesis, nucleotide synthesis, lipid biosynthesis, adipogenesis, and suppresses autophagy. Conversely, the activity of mTORC2 may be regulated by growth factors through PI3K activation and generation of PIP3. mTORC2 activation promotes AKT signaling involved in glycolysis, lipid biosynthesis, and cell migration. Adopted from: Papadopoli D, Boulay K, Kazak L et al. F1000Research 2019, 8(F1000 Faculty Rev):998

Another way in which mutations promote cell proliferation is activating mutations that occur in

the catalytic α subunit of PI3K (PIK3CA). These mutations are common among many solid tumors types including breast cancers (20–30% of all cases) and gliomas, and result in elevated cell growth, survival and proliferation. Moreover, these mutations are associated with earlier recurrence and shorter survival in adult glioblastoma21,22. Another widely encountered transforming event that leads indirectly to PI3K activation is the amplification or mutation of receptor tyrosine kinase (RTK), for example the epidermal growth-factor receptor (EGFR) or

HER2 (Fig. 1.3 and 1.4). Moreover, p110 interacts directly with RAS GTPases, thereby providing a potential link between transformation by oncogenic RAS mutants and PI3K signaling (Fig. 1.4). Hence the PI3K/mTOR pathway is one of the most crucial core pathways for cancer development and maintenance.

As mentioned above, mTOR regulates various cellular processes. Among them is cell growth (increase in size) which is facilitated by the S6 kinases (S6Ks) which is activated by inputs from mTORC1 and other kinases. One the other hand, mTORC1 phosphorylation of

Figure 1.4: Mechanisms of oncogenic activation of PI3K/AKT or loss of PTEN. Through mutations in either (i) receptor tyrosine kinases (RTK), (ii) loss of PTEN (bold blue), (iii) activating mutation in PI3K, or (iv) activating mutation in RAS (bold red) can lead to oncogenic activation of both PI3K/AKT/TOR and MAPK signaling pathways. Note activating mutations in AKT and RAF, or loss-of-function mutations in TSC2 are also observed but they will not be discussed. Reference: Ahmed M. et al. (2019). Science Signaling. Vol. 12, Issue 567, eaat4105

eIF4E binding proteins (4E-BPs) releases eIF4E to form the eIF4F complex that promotes translation of certain cap-dependent mRNAs23. In fibroblasts and other cell types, mTORC1- regulated growth and proliferation are controlled separately; S6Ks promote cell growth while the

4E-BP-eIF4E axis controls proliferation. In lymphocytes, however, activation, growth and proliferation are coupled through the 4E-BP axis while S6Ks are mainly dispensable 24.

mTOR plays a pivotal role in facilitating immune defense against invading pathogens by regulating the differentiation, activation, and effector functions of lymphoid cells25–28. Among T cells, mTOR deficiency impairs proliferation and prevents differentiation into T helper 1 (Th1),

Th2, or Th17 effector cells while inducing differentiation into Foxp3+ regulatory T cells 29. This phenomenon supports the use of rapamycin as a clinical immunosuppressant for organ transplantation. Genetic studies with conditional deletion of mTOR or Raptor in splenic B cells indicated a reduction in production of high affinity antibodies in mice; Also, these mTORC1- inactivated B cells had a proliferative defect. Together, these findings point at inhibition of mTORC1 preventing initial B cell activation and further differentiation. In addition, low doses of rapamycin (an allosteric inhibitor of mTORC1) which preserve B cell proliferation and maintain

IgM production while suppressing germinal center formation and class switch recombination

(CSR) 30,31. Our lab has also shown that low rapamycin concentrations suppress class switching in vitro, and have minimal effects on proliferation. Deletion of Raptor post-activation (using inducible Cre or Cγ1-Cre) also reduced germinal center B cells and antigen specific IgG1 while maintaining IgM 32. Our lab has been able to show that low concentration of mTOR kinase inhibitors (TOR-KIs) promote antibody class switching rather than inhibiting it, thus adding another layer of complexity. Mechanistic investigation and deletion of Rictor in B cells indicated that this increase in CSR resulted from inhibition of mTORC2 33. This study showed

mechanistically that mTORC2 suppression reduces AKT activity, and thus increased FOXO transcription factor activity to drive CSR. In a subsequent study our lab showed that mTORC1 promotes CSR by driving eIF4F formation and cap-dependent translation 8.

BCR-ABL translocation and leukemia induction

Many efforts are currently dedicated to developing preclinical and clinical small molecule inhibitors of the central kinases involved in the PI3K/AKT/mTOR signaling pathway. In order to most accurately simulate a constitutive PI3K/AKT/mTOR activation in the context of human malignancies, we utilize mouse models of acute lymphoblastic leukemia (ALL) driven by the

BCR-ABL fusion oncogene. The 210 kDa (p210) form of the BCR-ABL oncogene results in a myeloproliferative disorder, named chronic myelogenous leukemia (CML) (Figure 1.5). The p210 and a p190 form of BCR-ABL can also lead to a fraction of acute leukemia of B lineage progenitors known as Philadelphia-positive pre-B cell acute lymphoblastic leukemia (Ph+ B-

ALL)34. The Philadelphia chromosome (Ph) is an oncogenic lesion caused by the fusion of two chromosomes, clinically abbreviated as t(9;22)(q34;q11.2). The Ph encodes a chimeric fusion product BCR-ABL in which the cellular ABL tyrosine kinase is constitutively activated. This translocation and constitutive activation of BCR-ABL simulates extracellular cytokine signals that activate PI3K and several parallel and interconnected signaling pathways, namely the RAS-

MAPK (Mitogen-Activated Protein Kinase), and JAK-STAT (Janus Kinase–Signal Transducer and Activator of Transcription)35. BCR-ABL translocation is the most frequent cytogenetic abnormality in adult B-ALL (about 25% of cases)36,37. In all age groups, Ph+ disease represents a subgroup of acute leukemia with very poor prognosis and survival rates are low in patients treated with traditional chemotherapy only.

Figure 1.5: The Philadelphia Chromosome. Reciprocal translocation of chromosome 9 and 22 produces the Ph chromosome. This translocation leads to juxtaposition of protooncogene c-abl (tyrosine kinase encoding gene on chromosome 9) and bcr on chromosome 22. The fusion protein BCR-ABL is a primary driver of malignant transformation of white blood cell precursors in the bone marrow.

Dasatinib and tyrosine kinase inhibitors

Certain tumors are physiologically addicted to the uninterrupted activity of a major oncogenic signaling protein for tumor maintenance38. This phenomenon, termed “oncogene addiction”, has been well documented in multiple mouse models, cancer cell lines, and human clinical trials involving specific molecularly targeted inhibitors39. It is not surprising then that companies have been investing tremendous effort in developing treatments targeting these crucial oncogenes.

BCR-ABL-driven leukemias provide a prime example of oncogene addiction and therapeutic targeting. One of the major successes in the treatment of Ph+ disease has been a series of tyrosine kinase inhibitors (TKIs), such as imatinib mesylate (Gleevec®), dasatinib

(Sprycel®), and AMN107 (nilotinib) - all of which effectively suppress the BCR-ABL kinase activity, thus inducing selective growth arrest and apoptosis of the transformed cells3,40–43.

Despite providing superior responses to produce stable remission for the majority of patients with CML in chronic phase, TKIs are less effective in Ph+ B-ALL and blast crises phases of CML. Among BCR-ABL driven leukemias, the mutations E255K and Y253H lead to imatinib resistance and, in the case of T315I, resistance to imatinib and second-generation ABL

TKIs dasatinib and nilotinib. Amplification of MET (receptor tyrosine kinase of HGT) and

ERBB3 (erb-b2 receptor tyrosine kinase 3) are also common mechanisms of resistance to TKIs in the setting of lung and breast cancers, because they can bypass the inhibited receptor and maintain downstream PI3K and RAS/MAPK activation44–47. The emergence of clinical resistance to TKIs has prompted researchers worldwide to study downstream pathways that are necessary for malignant transformation and maintenance of Ph+ diseases. The inputs and insight gathered from those mechanistic studies may inform approaches to pharmacologically target important oncogenic signaling pathways in conjugation with BCR-ABL in order to prevent the expansion and survival of the leukemias. Combination of an inhibitor to a downstream oncogene with an upstream TKI may synergize the anti-tumorigenic effects of both compounds, as we show in chapter 3 of this work. Alternatively, targeting an essential signaling protein that is not oncogenic by itself, but required to support the excessive demand of tumor cells may also prove beneficial when combined with TKIs. This concept, termed “non-oncogene addiction”, and has been ascribed to many non-oncogenic cellular processes48. One example is the dependence of cancer cells on mTOR kinase, in that mTOR itself is not frequently mutated in cancer, yet progresses many essential pathways necessary to support the tumorigenic state.

One of the main objectives of this dissertation was to use pharmacological tools as well as developing novel genetic approaches in a mouse model of Ph+ B-ALL, to suppress the translation initiation complex (eIF4F), a downstream component of the PI3K/mTOR pathway.

Through these approaches we hoped to better understand signaling mechanisms in leukemia and lymphoma cells and to target oncogene and non-oncogene addiction for therapeutic benefit.

Non-Hodgkin’s Lymphoma

B and T lymphocytes (B and T cells) assist in protection of our body from infections and pathogens. Among lymphocytic malignancies, B and T cells lose their ability to regulate their proliferation, and aside from their abnormally vast numbers, tend to strand in the lymph nodes, thus causing them to swell and form cancerous tumors. Lymphomas are mainly categorized into

Hodgkin’s or Non-Hodgkin’s lymphomas, with the main differences being: (1) The type of lymphocyte that is affected. Hodgkin lymphoma is marked by the presence of Reed-Sternberg cells, while in non-Hodgkin lymphoma, these cells are not present. (2) Non-Hodgkin lymphoma is more common than Hodgkin lymphoma. (3) Hodgkin lymphoma is often diagnosed at an early stage and is therefore considered one of the most treatable cancers. Non-Hodgkin lymphoma

(NHL) is typically not diagnosed until it has reached a more advanced stage. In this work, we focused on NHLs of the B lineage. There are many types of B-cell NHL and the response of patients to treatment depends largely on the type of lymphoma and the stage at which it is diagnosed. Whereas certain NHLs spread slowly (termed “indolent”), such as follicular lymphoma, others spread much faster (termed “aggressive”). Examples of aggressive NHLs include Burkitt’s lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma. The last two are the main focus of this work.

Diffuse large B cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) globally represents about 30-58% of cases of non-Hodgkin lymphoma49. It is the most common type of adult aggressive NHL, and is fatal within weeks or months if left untreated50. Among the symptoms of DLBCL are swelling in the groin, armpit, or neck caused by enlarged lymph nodes. Given that DLBCL is predominantly diagnosed in elderly patients (median age ~70 (6)), tolerability of therapies is a growing concern.

Indeed, a recent retrospective study of ~400 DLBCL patients age 75 or older revealed that fewer than a quarter of patients completed the full regimen of chemotherapy (7). Five-year survival rates for those patients that receive combination immuno-chemotherapy (R-CHOP: rituximab, cyclophosphamide, hydroxydaunorubicin, oncovin and prednisone) are approaching 60%. Yet, many patients still respond poorly to the standard of care, and thus while there has been substantial progress in treating the disease, there is still a significant need for more effective alternative therapies. A microarray study of DLBCL patient samples revealed three distinct subtypes with unique expression profiles. These were named activated B cell like (ABC), germinal center-like (GCB), and primary mediastinal B cell lymphoma (PMBL)51. Importantly, each subtype is separable from another in terms of oncogenic driver mutations as well as chemo- sensitivity52–56. Moreover, while the ABC subtype relies heavily on BTK signaling for support of survival, the GCB subtype relies heavily on BCL2 survival proteins for such support57–61. As a result, targeted therapy approaches to treating each disease varies greatly between subtypes62–66.

Interestingly, poor patient responses in GCB-DLBCL are often associated with over-expression of BCL259,60,67–69, which will be discussed later. Previous work has attempted to target GCB-

DLBCL by exploiting venetoclax ability to target BCL2 specifically, and in our work we

attempted to combine venetoclax with other agents to achieve better therapeutic outcomes, than venetoclax as a single agent (see chapter 2).

Mantle cell lymphoma

Mantle cell lymphoma (MCL) is characterized by an abnormal proliferation of mature B- lymphocytes which probably derive from naive B cells expressing CD5. This tumor represents

5–10% of all NHLs and predominates in males with advanced age. The identification of the t(11;14)(q13,q32) translocation, which drives increased cyclin D1 expression, as a genetic alteration specific for this lymphoma was instrumental for more precisely defining the tumor, allowing its distinction from other lymphomas and also the recognition of other MCL morphological variants70. MCL cells have a striking tendency to disseminate throughout the body, infiltrating the lymphoid tissues, bone marrow, peripheral blood and extra nodal sites, even in territories that normally do not contain lymphoid cells71. This blood malignancy is considered one of the most aggressive lymphoid neoplasms, with poor responses to conventional chemotherapy and relatively short survival. However, recent clinical observations have identified some patients with a more indolent form of the disease that have a long survival even without the need for treatment, suggesting that the biological behavior of this tumor may be more heterogeneous than initially thought72–74. The understanding of these molecular mechanisms and the emergence of new drugs targeting key oncogenic mechanisms provide the basis for designing innovative therapeutic strategies with promising results, both in preclinical and preliminary clinical trials. For example, since MCL is characterized by an abberantly75,76 high cyclin D1- driven CDK4 activity, it is not surprising that novel targeted therapies that selectively inhibit the cyclin-dependent kinases CDK4 and CDK6, such as palbociclib, are currently in clinical studies

for treatment of MCL patients77–79. Moreover, mTOR pathway activation has been reported among refractory MCL patients and aggressive B-cell lymphomas80,81.

Approved treatments (R-CHOP, idelalisib, copanlisib, ibrutinib)

Despite DLBCL aggressive disease course, about 50% - 70% of the diagnosed patients may be cured by the current standard of care, which is abbreviated “R-CHOP”82, and is composed of the following:

• Rituximab - a humanized monoclonal antibody against the protein CD20, which is primarily

found on the surface of immune system B cells beginning at the pro-B phase. Once bound to

CD20, it triggers cell death83.

• Cyclophosphamide – a DNA damaging agent which induces strand breaks, DNA-

DNA cross-linking, and DNA-protein cross-links. It is used for treatment of

lymphoma, multiple myeloma, leukemia, ovarian cancer, breast cancer, small cell lung

cancer, neuroblastoma, and sarcoma84.

• Hydroxydaunorubicin - a compound extracted from the bacterium Streptomyces peucetius. It

is a type of anthracycline antitumor antibiotic. Due to its ability to cause DNA damage

(intercalation between base pairs, inhibition of topoisomerase II activity and prevention of

replication) and DNA production, it is mainly cytotoxic against cancerous cells. It is used to

treat many types of cancer, including leukemia, lymphoma, neuroblastoma, sarcoma, Wilms

tumor, and cancers of the lung, breast, stomach, ovary, thyroid, and bladder85–87.

• Oncovin (A brand name for vincristine sulfate) - a plant alkaloid that is administered intra-

venously and prevents cell division via inhibition of microtubule formation in mitotic

spindle. It is used for treatments of acute lymphocytic leukemia, acute myeloid

leukemia, Hodgkin's disease, neuroblastoma, and small cell lung cancer88,89.

• Prednisone - a glucocorticoid medication. Treatment with glucocorticoids for solid tumors

was found to reduce tumor volume, structure and function of lymphoid tissues via

angiogenesis suppression. Yet, they are also effective for treatment of blood malignancies as

they can be combined with chemotherapy due to non-overlapping toxicity. Moreover, they

proved effective for treatment of cancer-related nausea, pain, anorexia and other

chemotherapy-related side effects. Prednisone is also used to treat high blood calcium due

to cancer and adrenal insufficiency along with other steroids90.

R-CHOP may be administered alone or in combination with radiation therapy. However, elderly or immunocompromised patients often cannot tolerate these treatments. Furthermore, chemo- immunotherapy also becomes less effective after disease relapse and in patients with poor prognostic markers, such as disrupted function of the cell-cycle regulator p53 owing to mutations in TP53 or deletions on the short arm of chromosome 17, del (17p)91–93. Moreover, R-CHOP toxicities-related death incidents, despite being a rare event in young patients, may be observed in 5% of patients older than age 70 years89,94,95. R-CHOP failures are principally due to either primary refractoriness or relapse after reaching a complete response (CR). Although several mechanisms of resistance may account for refractoriness to R-CHOP, some DLBCL patients present with a double rearrangement of MYC and BCL2 genes, referred to as “double-hit lymphoma” (DHL). Recently, reports of cases with cytogenetic abnormalities involve chromosomal rearrangements of c-MYC, BCL2, and BCL6 genes, have led to the definition of

“triple-hit lymphoma” (THL)96–99. All studies that focused on DHLs or THLs concluded that the patients’ outcomes were poor, with R-CHOP probably not being the best therapeutic option94,96–

98. These drawbacks, as well as short-term and long-term toxicities of chemo-immunotherapy, fostered the development of alternative treatment approaches.

The importance of the PI3K pathway in cell survival and proliferation has made it an attractive target in cancer therapy100–102. PI3Ks are divided into three classes - I, II, and III. Class

I kinases contain four isoforms, designated PI3Kα, β, γ, and δ100,103,104. PI3Ks integrate and transduce signals from various surface molecules on B cells, such as the BCR105, chemokine receptors, and adhesion molecules, thereby regulating key cellular functions, including growth, survival, and migration100. PI3K activity is maintained in malignant B cells through cellular and molecular interactions with the tumor microenvironment106. These interactions occur within secondary lymphatic tissues, and result in the activation of several signaling pathways, such as the PI3K/AKT axis and BTK/NFB signaling, that are necessary for maintenance and expansion of B cells106–108. Moreover, BCR signaling is a critical pathway in the pathogenesis of several B- cell malignancies, including CLL106,109,110. PI3Kδ is the major PI3K isoform in B cells, and its expression is mainly restricted to hematopoietic cells, in which it is involved in B-cell homeostasis and function111. This isoform has an essential, non-redundant role in BCR signaling as demonstrated by the fact that PI3K signaling was able to rescue the survival of mature B cells in BCR-deficient mice112,113.

Indeed, inhibitors of B-cell receptor (BCR) signaling, such as idelalisib (trade name:

Zydelig) and ibrutinib (trade name: Imbruvica), were proved to affect the survival of neoplastic

B cells not only by destabilizing the multifactorial platform of microenvironment signals that commonly sustain the malignant clone but also by delocalizing a consistent fraction of the tumor

B-cell clone from the protective tissue compartment114. Ibrutinib was first approved in November

13th, 2013, for treatment of relapsed or refractory MCL115. Since then the outcome of relapsed

CLL improved dramatically with the appearance of BCR signaling inhibitors, especially in the elderly and unfit110,116–118. Ibrutinib is an oral irreversible inhibitor of Bruton's tyrosine kinase

(BTK), a critical kinase of the BCR signaling pathway that is expressed by various haematopoietic cells, B-cell lymphomas and leukemias. Ibrutinib has shown promising activity in patients with MCL115,119 and relapsed and/or refractory CLL, as well as in those deemed unfit to receive other agents118,120,121. Yet, relapse has been reported during treatment with ibrutinib and some patients fail to respond altogether. One of the major mechanisms of resistance to ibrutinib is the C481S mutation in the BTK tyrosine kinase domain. Thus, new therapeutic strategies are urgently needed in order to overcome ibrutinib or idelalisib resistance. While second-generation BTK inhibitors (for example: ACP-196, ONO/GS-4059, and BGB-3111) are being tested in several clinical trials with promising outcome122, an alternative strategy is to directly target BCL2 – which will be covered below. Indeed, the combination of ibrutinib with venetoclax (BCL2 inhibitor) was found effective for high-risk and older patients with CLL: 88% of the patients had complete remission (CR) or complete remission with incomplete count recovery, and 61% had remission with undetectable minimal residual disease123.

The development of small molecule inhibitors for PI3K has provided new treatment alternatives for various B-cell malignancies 124,125. Idelalisib (also known as CAL-101 or GS-

1101), the first PI3Kδ inhibitor in clinical use, has activity in patients with CLL and indolent B- cell lymphomas. Idelalisib intercepts critical communications between B cells and the microenvironment, including B-cell receptor signaling and chemokine networks. Various publications have highlighted the efficacy and safety of idelalisib117,126, a PI3Kδ inhibitor, in patients with indolent NHL (iNHL) and CLL. The advent of PI3K isoform-specific small molecule inhibitors has led to increased efficacy with avoidance of an excessive toxicity

profile124. PI3Kδ activation also induces secretion of chemokines (CCL3, CCL4) by the malignant B cells, which in turn attract accessory cells, such as T cells, to the tissue microenvironment. These activation events are turned off by PI3Kδ blockade with idelalisib.

After beginning therapy with idelalisib, patients with CLL typically experience rapid resolution of enlarged lymph nodes, along with a transient surge in blood lymphocyte counts126. These effects can be explained by the idelalisib-induced blockade of tissue anchor signals and chemokine receptor signaling, which normally retain CLL cells in lymph glands127.

Key enzymes of the PI3K pathway exhibit differing expression in tissue types and roles in tumor pathogenesis. Copanlisib (BAY 80-6946) is a pan-specific PI3K small molecule inhibitor of four key isoforms with increased activity against PI3Kα and PI3Kδ, both important in B-cell malignancies124. For example: Follicular lymphoma (FL) like other indolent NHLs is characterized by high relapse rates and the need for subsequent therapy options128,129. Based on efficacy and a limited toxicity profile, copanlisib received accelerated US Food and Drug

Administration (FDA) approval for the treatment of adult patients with relapsed FL following two lines of therapy 124. Recently, the drug duvelisib (trade name: Copiktra) was approved by the

FDA for treatment of refractory CLL, small lymphocytic lymphoma (SLL) and FL130,131.

Duvelisib is an oral inhibitor of PI3K and PI3Kγ.

The BCL2 protein family and regulation of apoptosis

One of the main hallmarks of cancer is the ability of cancerous cells to resist cell death in general and programmed cell death (apoptosis) specifically4,132. Among many malignant cells, this is achieved via overexpression of various pro-survival or anti-apoptotic proteins133–135.

Intrinsic apoptosis, also referred to as the mitochondrial pathway, is executed in response to

cellular damage and most anti-cancer agents. This process is regulated by the B-cell lymphoma 2

(BCL2) family proteins136–138. There are over 25 known proteins in the BCL2 family, each of which exerts either a pro- or anti-apoptotic effect (Fig. 1.6). Based on their function, these proteins can be divided into one of three major groups:

• The anti-apoptotic members: BCL2, BCL-XL, BCL-W, MCL-1 and A1/BFL-1. These

proteins each possess four BCL2-homology (BH) domains and form a characteristic

helical bundle fold, which is critical for their ability to bind to and inhibit the pro-

apoptotic BCL2 family members 134,135,139,140–143.

Figure 1.6: Overview of BCL-2 family protein interactions. Overview of mitochondrial apoptotic pathway, with binding interactions highlighted. Binding affinity of BH3 only proteins for anti-apoptotic BCL-2 family proteins. Venetoclax is an inhibitor that binds BCL2 anti-apoptotic factor. Adapted from: Shamas-Din A., Kale J., Leber B., Andrews D.W., (2013). Mechanisms of Action of Bcl-2 Family Proteins. Cold Spring Harb Perspect Biol. Vol. 5(4): a008714.

• The pro-apoptotic effector proteins that possess three to four BH domains: BAX, BAK

and BOK144–146. In their inactive state, their structure is similar to that of BCL2 pro-

survival proteins146, but BAX and BAK are able to undergo substantial conformational

change during apoptosis induction147. BAX and BAK bind to and are inhibited by

different BCL2-like pro-survival proteins148,149, a process that controls their

activity150,151. BOK shares significant homology across all four BH domains to BAX and

BAK; however, its role in apoptosis remains unclear152.

• The BH3-only pro-apoptotic proteins, including: BIM, BID, PUMA, BAD, NOXA,

HRK, BMF, BIK and others134,139,147,150,151,153–161. These proteins can bind members of the

BCL2-like pro-survival subfamily and some of them can also bind to BAX and

BAK137,144,145,162–164.

The BCL2 regulated apoptotic pathway is initiated through the transcriptional and/or posttranscriptional activation of the BH3-only proteins in response to various upstream signaling events. Some of the BH3-only proteins are more potent inducers of apoptosis (e.g., BIM, PUMA, tBID) than others (e.g., BAD, NOXA, BMF). Pertinently, the potent BH3-only proteins bind avidly to all pro-survival BCL2 family members and can also engage BAX/BAK, whereas the less potent ones have more select binding specificities for the pro-survival BCL2 family members and reportedly do not bind to BAX or BAK163. Together, the BCL2 protein family control mitochondrial outer membrane permeabilization (MOMP) (Fig. 1.7), which for most instances can be considered the point of no return for apoptosis165,166. This permeabilization allows the release of soluble proteins such as cytochrome c and SMAC/DIABLO, from the mitochondrial intermembrane space into the cytosol133,135,139,167. Once these proteins are released, cytochrome c binds to APAF-1 and caspase-9 in presence of dATP to form the apoptosome, which activates downstream effector caspases cascade and triggers apoptosis168,169.

Figure 1.7: Extrinsic and intrinsic apoptotic signaling pathways. In the extrinsic apoptotic pathway, upon binding to their cognate ligand, death receptors such as tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) receptor (TRAILR) and FAS can activate initiator caspases (caspase-8 and caspase-10) through dimerization mediated by adaptor proteins such as FAS-associated death domain protein (FADD). Active caspase-8 and caspase-10 then cleave and activate the effector caspase-3 and caspase-7, leading to apoptosis. The intrinsic (or mitochondrial) pathway of apoptosis requires mitochondrial outer membrane permeabilization (MOMP). Cell stresses engage BCL-2 homology domain 3 (BH3)-only protein activation, leading to BAX and BAK activity that triggers MOMP. Anti-apoptotic BCL-2 family proteins counteract this. Following MOMP, mitochondrial intermembrane space proteins such as second mitochondria- derived activator of caspases (SMAC) and cytochrome c are released into the cytosol. Cytochrome c interacts with apoptotic protease activating factor 1 (APAF1), triggering apoptosome assembly, which activates caspase-9. Active caspase-9, in turn, activates caspase-3 and caspase-7, leading to apoptosis. Mitochondrial release of SMAC facilitates apoptosis by blocking the caspase inhibitor X-linked inhibitor of apoptosis protein (XIAP). Caspase-8 cleavage of the BH3- only protein BH3-interacting death domain agonist (BID) enables crosstalk between the extrinsic and intrinsic apoptotic pathways. ER, endoplasmic reticulum; MCL1, myeloid cell leukemia 1; tBID, truncated BID. Source: A fate worse than death: apoptosis as an oncogenic process. Adopted from: Ichim G., and Tait S.W.G. (2016). Nature Reviews Cancer.

BH3 mimetics, rationale for combinations

Venetoclax (ABT-199)

Since overexpression of BCL2 pro-survival protein is one of the hallmarks of many B-cell malignancies170, several inhibitors have been developed through the years, specifically targeting

BCL2 as a critical “Achilles heel” of those cancers68,135,136,171–174. Among those BCL2 inhibitors is venetoclax (trade name: Venclexta™, formerly ABT-199) which was approved by the FDA for treatment of CLL patients with 17p chromosomal deletion (a marker of p53 deletion), in

2016134,175–177. Venetoclax belongs to a family of inhibitors, generally referred to as “BH3 mimetics”178–180. BH3 mimetic drugs were first designed based on their ability to bind specifically to the BH3 binding pocket of pro-survival proteins (hence named BH3 mimetics).

The first BH3 mimetic designed based on structure was a small molecule inhibitor ABT-737,

181–183 that was shown to bind with high affinity to BCL2, BCL-XL, and BCL-W, but not MCL-1 .

ABT-737 was shown to induce apoptosis in vitro among primary CLL cells from patients at a concentration lower than 100 nM184. Its bioavailable derivative ABT-263 (trade name: navitoclax) was later selected for clinical development185, since it presented antitumor activity against CLL and FL in early phase clinical trials186,187. However, further studies were

188 discontinued due to its inhibition of BCL-XL, a key survival factor for platelets ; patients administered navitoclax suffered from acute thrombocytopenia187.

Venetoclax was developed as a highly BCL2-selective BH3-mimetic, with a strong affinity for BCL2 (>100-fold less affinity for BCL-XL or BCL-W)189. Similarly to navitoclax, venetoclax in vitro cytotoxicity depends on the presence of BAK and BAX 189. It is worth mentioning that other compounds that were originally considered as BH3 mimetics, later turned out to not represent “true” BH3 mimetics since their mechanism of action was somewhat BAX

independent 190. One example is Obatoclax, designed as a pan-BCL-2 Inhibitor, which was found to downregulate cyclin D1 through induction of cyclin D1 proteasomal degradation191,192.

Other therapeutics (e.g. proteasome inhibitors) may act in a similar manner by activating endoplasmic reticulum-specific transcription factors ATF3 and ATF4 that regulate NOXA expression193,194. One important aspect of determining dependence on particular anti-apoptotic

BCL2 family protein is the critical decision on appropriate personalized therapy. The advent of

“BH3 profiling” using specific peptides has led the way195,196, although more recent availability of specific small-molecule inhibitors of BCL-XL (Wehi-539, A-1155463, A-

1331852)174,197,198 and MCL-1 (AMG 176, A-1210477, S63845 – see below)199–201 in addition to inhibition of BCL2 by venetoclax, has facilitated, at least in an ex vivo culture, a rapid determination of the BCL2 family protein dependence. The tools mentioned (and others) enable choosing the most effective therapeutics to be used given the functional output, and their ability to induce cell death196, as well as the ability to distinguish between potential patients that will benefit from the treatment (“responders”) from patients that will not (“non-responders”)202.

First tested in relapsed or refractory CLL patients, venetoclax was developed to induce reduction in lymphocyte counts (dose-dependent manner) without causing thrombocytopenia189.

The first clinical trial for venetoclax was a phase I dose-escalation study in which 116 patients were enrolled with relapsed or refractory CLL or small lymphocytic lymphoma: 92 (79%) patients had a response and 20% achieved complete remission (CR), including 5% with minimal residual disease (MRD) negative as assessed by flow cytometry. Objective responses were common among patients with resistance to fludarabine with del17p and unmutated IGHV, with progression-free survival (PFS) estimated for the 400-mg dose groups was 69%175. In the phase

II study of venetoclax, conducted exclusively in patients with del (17p) CLL, 107 patients were

enrolled: Overall response rate (ORR) was achieved in 85 (79.4%) patients203. Response rates were similar regardless of whether patients were refractory to prior fludarabine-based therapy.

The clinical response of CLL patients were also found to be independent of del17p, TP53 mutation, and TP53 function204. Recently, a phase II, open label, two-arm study reported the outcome of venetoclax monotherapy in 64 CLL patients who relapsed after, or were refractory to, ibrutinib or idelalisib, of whom 43 were on prior ibrutinib (Arm A) and 21 (Arm B) on prior idelalisib. ORR by an independent review for Arm A and Arm B was 70% and 48%, respectively. At the time of analysis, neither the PFS nor the overall survival has been reached.

The estimated 12-month PFS was 72%, and overall survival was 90%. This study showed that venetoclax had a robust activity in CLL patients that progressed during or post-treatment with ibrutinib or idelalisib123,205–207.

Venetoclax was also tested in a variety of other blood cancers. In a phase I study as monotherapy to treat patients with relapsed/ refractory non-Hodgkin lymphoma (NHL), the ORR varied in the different histologic subgroups, with the highest rates observed in Waldenstrom's macrogloblinemia (100%, all PR) and MCL (75%, including 21% CR). Responses were less frequent in FL (ORR: 34%, CR: 10%) and DLBCL (ORR: 15%, CR: 9%), and the median duration of response of DLBCL was only 3.3 months208.

Rationale for combinations to enhance venetoclax efficacy

Given the resistance mechanisms mentioned above, and the critical need to develop better therapeutics for B-lymphoid malignancies, combinations of BCL2 inhibitors along with other agents were reported to achieve a better clinical response. Preclinical data suggests that distinct resistant mechanisms to venetoclax can be overcome by use of monoclonal antibodies, DNA

damaging chemotherapy, proteasome inhibitors, BCR signaling inhibitors, such as ibrutinib and idelalisib, MCL-1 inhibitors, or mTOR kinase inhibitors (TOR-KIs). Moreover, constant attempts to improve outcomes of BCL2 inhibitors have resulted in development of advanced therapeutic strategies. Recent evidence from pre-clinical studies that evaluated BCL2 inhibitors in various cancer cells have indicated that combination approaches may have superior survival outcomes, compared with single-agent treatment regimens. Among the venetoclax combinations that proved most beneficial we include:

1. Combination of venetoclax with decitabine or azacitidine (DNA demethylating agents that

sensitize tumor cells to apoptosis) in treatment-naive AML Patients. Venetoclax plus

decitabine or azacitidine showed tolerable safety and favorable overall response rate (CR +

CRi rate: 67%) in elderly patients with AML. Also, this novel combination regimen

produced favorable responses in high-risk groups, such as age 75 or older, poor cytogenetics,

and secondary AML209,210.

2. The combinations of obinutuzmab (which binds to CD20 and activates intracellular apoptosis

pathways, as well as activation of the complement system to destroy B cells), ibrutinib BTK

inhibitor, and venetoclax were tested in relapsed/refractory CLL. The combination has a

tolerable safety profile in both relapsed/refractory (R/R) and treatment-naïve (TN) CLL

patients with the majority of toxicities being hematologic. This combination can be safely

administered in combination at doses standard for the treatment of CLL. Adverse events were

manageable and largely consistent with those reported in the single agent phase 2

studies. Objective responses, including MRD-negative responses, have been observed among

all RR patients211–213.

3. Combination therapy of venetoclax and rituximab for treatment of CLL or Small

Lymphocytic Lymphoma (SLL) patients. When the combination of venetoclax and rituximab

was evaluated in patients with relapsed or refractory CLL, the rate of investigator-assessed

progression-free survival was significantly higher in the venetoclax–rituximab group (32

events of progression or death in 194 patients) than in the bendamustine–rituximab group

(114 events in 195 patients). The 2-year rates of progression-free survival were 84.9% and

36.3%, respectively. Highlighting the therapeutic potential of combination strategies is the

recent FDA approval of venetoclax in combination with rituximab for treatment of patients

with CLL who had received at least one prior line of therapy119,214,215.

4. Combination therapy of venetoclax, daratumumab and dexamethasone for treatment of

relapsed/refractory multiple myeloma subjects. Treatment of human MM cell lines and

primary patient samples with dexamethasone and venetoclax combination significantly

increased cell death over venetoclax as a single agent. It was found that dexamethasone

addition elevated expression of both BCL2 and BIM, resulting in increased sensitivity to

venetoclax216. In a phase 1 and 2 studies, an analysis of patients treated with venetoclax,

daratumumab and dexamethasone with or without bortazumib demonstrate a tolerable safety

profile with encouraging efficacy, notably among t(11;14) pts treated with the combination

who had an ORR of 92%. No new safety signals were observed217.

5. Venetoclax combination with mTOR inhibitors (TOR-KIs). Combination of venetoclax with

the dual PI3K/mTOR inhibitor NVP-BEZ235 or idelalisib enabled overcoming resistance in

the DLBCL cell lines by reducing MCL-1 levels and leading to release of BIM from MCL-1

and BCL-XL, thus causing apoptosis by BAX activation6. Another study published by our

lab has shown that BEZ235 is capable of synergizing with venetoclax by an alternative

mechanism – induction of BAD and BIM accumulation in DLBCL cells218. Additionally, a

recent study evaluated that combination of venetoclax with the TOR-KI, PQR620, for its

anti-tumor activity in DLBCL and MCL lymphomas. They found PQR620 to be largely

cytostatic, but the combination with venetoclax led to cytotoxicity. Both the single agent and

the combination data were validated in xenograft models219. Furthermore, we directly

compare the combination of venetoclax with TOR-KIs to venetoclax with eIF4F complex

inhibitors in chapter 2 of this work.

6. Venetoclax combination with statins and HMG-CoA reductase inhibitors. Our lab has

published that inhibition of HMG-CoA reductase (HMGCR) using statins enhances the pro-

apoptotic activity of venetoclax in primary leukemia and lymphoma cells but not in normal

human peripheral blood mononuclear cells. By blocking mevalonate production, HMGCR

inhibition reduced protein geranylgeranylation, thus leading to up-regulation of pro-apoptotic

protein p53 upregulated modulator of apoptosis (PUMA). Dynamic BH3 profiling confirmed

that statins primed cells for apoptosis. Furthermore, in retrospective analyses of three clinical

studies of CLL, background statin use was associated with enhanced response to venetoclax,

as demonstrated by more frequent complete responses220.

MCL-1 inhibitors

Despite much progress in characterizing venetoclax therapy as a single agent or in combination, many blood malignancies including NHL221 depend heavily on MCL-1 (at least to similar extent as BCL2), and thus venetoclax proves less beneficial for them. This feature led to the development of MCL-1-selective inhibitors. One example that was published and presented is S63845, a small molecule inhibitor that specifically binds with high affinity to the

BH3-binding groove of MCL-1199,222. S63845 potently kills MCL1-dependent cancer cells, including 17 (out of 25) multiple myeloma (MM) cell lines tested, which were found highly sensitive to S63845 (IC50 < 0.1 μM). Six additional MM cell lines were found moderately sensitive to S63845 (0.1 μM < IC50 < 1 μM), and two were insensitive (IC50 > 1 μM). This finding could be attributed to the high expression levels of MCL-1 among those cells, and its requirement for their survival223,224. Other cell lines that have shown promising responses to

S63845 include leukemia and lymphoma cells. The cytotoxic activity of S63845 in these cells correlated with the impact of the BIM2A peptide, which specifically inhibits MCL-1225, or genetic deletion of MCL-1226 but did not correlate with the impact of the BIM–BAD peptide,

227 which inhibits BCL2, BCL-XL and BCL-W . When tested in vivo, S63845 presented a potent anti-tumor activity in several cancers. The ability of normal tissues in mice to tolerate doses of

S63845 that efficiently kill tumor cells indicates that a suitable therapeutic window may be achievable for MCL-1-specific BH3 mimetics. S63845 rapidly induced caspase-dependent phosphatidyl-serine exposure, poly ADP-ribose polymerase (PARP) cleavage, and cytochrome c release from mitochondria, which are all hallmarks of apoptosis. Moreover, MCL-

1 inhibition, either alone or in combination with other anti-cancer drugs, proved effective against several solid cancer-derived cell lines.

Another promising MCL-1 inhibitor that received much attention and entered clinical trials recently is AMG 176 (produced by Amgen)201,228. AMG 176 is a potent and selective MCL-1 inhibitor that induces apoptosis among various hematologic malignancies. The authors reported synergy between AMG 176 and venetoclax in models of AML at tolerated doses, highlighting the potential of BH3-mimetic combinations in hematologic cancers. They showed that MCL-1 inhibition committed toward apoptosis in subsets of hematologic cancer cell lines, tumor

xenograft models, and primary patient samples. By using human MCL-1 knock-in mouse model, they demonstrate that MCL-1 inhibition at active doses of AMG 176 is tolerated and correlates with clear pharmacodynamic effects, demonstrated by reductions in B cells, monocytes, and neutrophils.

In addition, a recent report introduced VU661013 as a potent, selective MCL-1 inhibitor that leads to apoptosis in AML and is active in venetoclax-resistant cells and patient-derived xenografts. They showed that VU661013 was safely combined with venetoclax and synergized in AML murine models. Interestingly, the authors reported that BH3 profiling of patient samples and drug-sensitivity testing ex vivo accurately predicted cellular responses to selective inhibitors of MCL-1 or BCL2 and showed benefit of the combination. The authors claim that VU661013 achieves its affects via destabilization of the BIM/MCL-1 association. Taken together, these data suggest a strategy of rationally using BCL2 and MCL-1 inhibitors in sequence or in combination in AML clinical trials229. Nevertheless, alternatives to direct targeting of MCL-1 might inhibit signaling pathways that regulate the expression of MCL-1, BIM, NOXA and PUMA.

PI3K/ mTORC1 pathway and regulation of protein translation

Phosphoinositide 3-kinase (PI3K)

The PI3K family of enzymes are lipid kinases that produce 3-phosphorylated inositol lipids

(phosphoinositides) that recruit cytoplasmic effector proteins to cellular membranes. Class I

PI3Ks function as heterodimers and preferentially phosphorylate the 3 position of phosphatidylinositol-4,5-bisphosphate (PI(4,5)P2) to generate a crucial second messenger,

PI(3,4,5)P3 (PIP3) (114,124-127). Class IA PI3Ks are activated downstream of receptor tyrosine

kinases (RTKs), a process mediated by Src homology-2 (SH2) domains in the class IA regulatory subunit that selectively bind phosphotyrosine residues. On the other hand, class IB

PI3Ks are activated by G protein-coupled receptors (GPCRs). Ultimately, both interactions localize PI3K to the plasma membrane where it can efficiently generate PIP3. PIP3 generation stimulates a rapid co-localization of enzymes containing pleckstrin-homology (PH) domains.

One of the most important proteins recruited is the serine/threonine (Ser/Thr) kinase AKT, which has many substrates and functions (Fig. 1.2, 1.5). Once recruited to the membrane, AKT is phosphorylated230–232, at Thr308 by phosphoinositide-dependent kinase 1 (PDK1) and Ser473 by mTORC2230,231,233. Through these phosphorylation events, AKT transduces many of the PI3K signaling outcomes through interactions with a diverse substrate pool. Among the important

AKT targets are Forkhead box group O (FOXO) transcription factors, tuberous sclerosis complex (TSC)-2, proline-rich AKT substrate of 40 kDa (PRAS40), and the BH3-only protein

BAD33,230,234,235. Aside from directly contributing to cell survival and proliferation, these substrates also connect the PI3K/AKT signaling pathway to mTORC1, a master regulator of cell growth and proliferation233,236.

The PI3K pathway is among the most abundantly activated pathways in human malignancies, where it drives cell growth, proliferation, metabolism, and survival. Activation of this network is associated with virtually every hallmark of cancer, and elevated activity is associated with poor prognosis and drug resistance237–239. The majority of human malignancies harbor genetic mutations that elevate 3-phosphoinositide levels, resulting in constitutive AKT activity15,240,241. Activating mutations in AKT occur in some breast cancers, identifying another critical component of the pathway whose activation facilitates transformation. PI3K-activating mutations are sufficient to confer venetoclax resistance in many cases125,237,242–246, and affect

expression or localization of many BCL2 family proteins to promote survival (Fig. 1.4)243–245,247.

Due to the interplay between the pro-survival pathway and the mTOR/eIF4F pathway, we investigate in chapter 2 the potential of using mTOR or eIF4F complex inhibitors to enhance the efficacy of BH3 mimetics.

Mechanistic target of rapamycin (mTOR)

mTOR has dozens of substrates248–250, yet the most well-characterized targets of mTORC1 include the p70 ribosomal-S6 kinases (S6Ks) and eukaryotic initiation factor 4E (eIF4E) binding proteins (4E-BPs), which coordinately regulate mRNA translation9,251,252.

• S6Ks promote ribosome biogenesis, lipid and nucleotide synthesis, and metabolic

reprogramming253–256. In addition, they promote mRNA translation via interactions with

PDCD4, eIF4B, and ribosomal protein S6 (rS6)257, There are two known isoforms of S6K

(S6K1 and S6K2) that have partially redundant functions.

• In their non-phosphorylated form, 4E-BPs bind eIF4E and prevent interaction of eIF4E with

the other subunits258–260, thus preventing formation of the eukaryotic translation initiation

complex (eIF4F). However, once phosphorylated by mTORC1, 4E-BPs release inhibition of

eIF4E. Upon release, eIF4E binds the scaffolding protein eIF4G1 and the RNA helicase,

eIF4A, to form the eIF4F protein translation initiation complex that binds to the 5’ cap of

certain mRNAs and facilitates cap-dependent translation 9,251,252. Importantly, high efficiency

of cap-dependent translation is selectively required for a subset of oncogenic mRNAs261,262,

including the proliferative proteins, MYC and cyclin D1, as well as the anti-apoptotic

protein, MCL-1263–266. Phosphorylation of 4E-BP1 correlates with high risk in B-ALL and

chronic lymphocytic leukemia267,268, while mTOR inactivation impairs B-ALL survival269,270.

Among fibroblasts (and other cells), mTORC1 regulates growth and proliferation separately:

S6Ks promote cell growth while the 4E-BP-eIF4E axis controls proliferation. However, among lymphocytes, the processes of growth, activation, and proliferation are all regulated via the 4E-

BP axis and cap-dependent translation control, while the S6K is mostly dispensable24.

Additionally, rapamycin reduces 4E-BP1 phosphorylation to a variable extent in different cell types whereas lymphocytes highly express the 4E-BP2 isoform whose phosphorylation is effectively inhibited by rapamycin 24. This might explain the mechanism by which rapamycin is a selectively potent immunosuppressant while unable to block and only delaying cell cycle progression in fibroblasts and many cancer cell lines which have higher amounts of the rapamycin-insensitive 4E-BP1271.

Apoptosis is an orderly process whose rate-limiting step is loss of mitochondrial membrane potential. Our lab has reported that ATP-competitive mTOR inhibitors or dual PI3K/mTOR inhibitors can induce significant apoptosis in murine bone marrow cells transformed with the human oncogene BCR-ABL269,272,273. However, in most human tumor cell lines and primary cells, inhibitors of the PI3K/mTOR signaling network do not cause robust cytotoxic responses unless combined with other agents273. mTORC2 activation is directly regulated by the levels of

PIP3, and is required for full activity of AKT274,275. On the other hand, mTORC1 functions by integrating growth factor signals (i.e. from the PI3K/AKT pathway) and nutrient sensors to ensure that the cell is at an appropriate bioenergetic state to support cell growth and division13,236,238. Upon activation, mTORC1 promotes key biosynthetic pathways including translation, transcription, and lipogenesis, while suppressing apoptotic and autophagic processes12,62,254,276–279.

Approaches to targeting mTORC1 in cancer

mTOR-activating mutations, though rare overall in cancer, have been identified among certain B-cell malignancies, such as DLBCL280, while elevated mTORC1 activity correlates with chemotherapy resistance and poor prognosis in pre-B acute lymphoblastic leukemia (B-ALL)267.

Due to the direct correlation between mTOR activity and B-cell malignancies, a tremendous amount of research in academic and biopharma laboratories has aimed to develop inhibitors specific to mTOR, or targeting PI3K that functions upstream of mTOR. This research has resulted in new therapeutic strategies to target one of more components of this complex signaling network. Several small molecule inhibitors have shown impressive preclinical efficacy and are now in clinical trials. Several approaches have been pursued to target the signaling pathway.

The first generation of small molecule inhibitors that target mTOR included the natural product rapamycin (from which the name mechanistic target of rapamycin is derived) and/or rapamycin analogs (e.g. RAD001, also known as everolimus) (Table 1.1). These agents partially inhibit TORC1 through allosteric binding adjacent to the catalytic site of TORC1, but do not acutely inhibit TORC2. This class of inhibitors will be referred to as rapalogs or rapamycin.

Several new generations of mTOR inhibitors have been developed to have more complete inhibition of mTORC1 kinase activity compared to rapamycin and rapalogs. These include the mTOR kinase inhibitors (also known as TOR-KIs in this thesis; elsewhere termed asTORi,

TORKi or mTORC1/2 inhibitors), ATP-competitive molecules that fully inhibit mTORC1 and mTORC2 activity269,281–287, and Rapa-links in which TOR-KI and rapamycin are chemically linked together to specifically target mTORC1 kinase activity288–290. Our lab previously showed that TOR-KIs were more effective than rapamycin at killing mouse and human leukemia cells

269. Rapa-links on the other hand showed better efficacy than rapamycin or TOR-KIs against

glioblastoma 290. Both TOR-KIs and Rapa-links caused complete 4E-BP1 de-phosphorylation compared to rapamycin; however, cancer cells can become resistant to all mTOR inhibitors by downregulating 4E-BP expression 291,292. This has provided one rationale for efforts to directly target eIF4E and other components of the eIF4F complex. In chapters 2 and 3, we make use of a novel eIF4G-binding molecule (SBI-756) to sensitize B cell malignancies to targeted agents, as well as for studies of eIF4F function among B and T lymphocytes.

Compounds targeting PI3K enzymes can also inhibit mTOR, either indirectly by suppressing upstream signals or directly by off-target inhibition of mTOR kinase. The first generation of

PI3K inhibitors developed were either isoform-selective (e.g. p110 selective inhibitor IC87114) or pan-isoform inhibitors (e.g. GDC-0941) (Table 1.1). The latter subgroup of PI3K inhibitors will be referred to herein as pan-PI3K inhibitors. Another class has dual activity towards PI3K enzymes and both mTOR complexes; these are termed dual-PI3K/mTOR inhibitors. It remains to be seen which of these approaches will best suppress oncogenic signaling while sparing normal cell homeostasis in different cancer settings. The optimal choice among the different approaches will likely only be revealed upon direct comparison in patients that encompass a variety of genetic aberrations and activating events in the pathway.

Rapamycin and rapalogs - 1st generation mTOR inhibitors

Rapamycin is a bacterial macrolide isolated from the soil microbe Streptomyces hygroscopicus in 1975 based on its anti-fungal activity 293, and later discovered to be a potent immunosuppressant 294. Upon entry into a cell, rapalogs bind to FKBP12, forming a complex that selectively suppresses mTORC1 kinase activity by limiting substrate access to the active site166,167. Importantly, the rapamycin-FKBP12 complex cannot bind to mTORC2 142,168, though

prolonged exposure may limit the assembly of mTORC2 169,295. Rapamycin was found to inhibit proliferation and differentiation in both mammalian T and B lymphocytes 296–298. Despite allosterically binding to mTORC1, rapamycin does not completely inhibit the kinase activity of the complex with differential effects on phosphorylation of distinct mTORC1 substrates 271. As its name implies, mTOR is the target of rapamycin, when bound in association with the FKBP12 protein. Despite its high specificity to mTOR, rapamycin is flawed as a tool for understanding

TOR biology, since the compound acts through an allosteric mechanism. Following the discovery that the main complexes facilitating mTOR signaling are two biochemically distinct complexes, we now understand that rapamycin cannot directly bind and inhibit mTORC2287,299–

301. Rapalogs bind with FKBP12 to the FRB (FKBP-rapamycin binding) domain, which is adjacent to the catalytic site of mTORC1, but not accessible in mTORC2 302. The rapalog–

FKBP12 complex upon binding to mTORC1 displaces Raptor 303. Raptor in complex with mTOR governs the substrate preference of mTORC1 to phosphorylate S6Ks and 4E-BPs.

Disruption of this interaction inhibits the ability of mTORC1 to access a subset of its substrates, yet at the same time might suppress negative feedback loops, elevating upstream survival signals in several malignant cells, which is a major caveat of these compounds232,304,305. S6K activity is completely inhibited by rapamycin, yet in contrast, 4E-BP1 phosphorylation on Thr37 and Thr46 is largely maintained 302,303. This incomplete inhibition of 4E-BP1 phosphorylation fails to strongly suppress eIF4F formation and suggests a prominent role for translational machinery to be a key mediator of rapamycin-resistance. Indeed, evidence suggests that 4E-BP inhibition, compared to S6K activity, is the crucial gatekeeper of regulating mRNA translation to promote cellular transformation 1,306,307.

2nd generation mTOR inhibitors

In order to overcome the limitations of rapalogs, research efforts have been devoted to developing ATP-competitive and selective inhibitors of both mTOR complexes. The first groups to report the development of a novel mTOR kinase inhibitor (inhibiting the kinase in both mTORC1 and mTORC2 complexes), documented the mechanistic differences between TOR-KI and rapamycin233,308–311. Eventually, several other groups confirmed these findings using TOR-

KI with other chemical scaffolds. In each case, the TOR-KI completely blocked mTORC1 signaling (phosphorylation of S6K on Thr389 and 4E-BP1 on Thr37/46 and Ser65) and mTORC2 signaling (AKT on Ser473)312–316. Among fibroblasts, muscle cells and solid tumor cell lines, the inhibition of rapamycin-resistant mTOR outputs was associated with stronger suppression of protein synthesis and cell proliferation, and greater reduction in cell size. Further supporting the selectivity of TOR-KI, none of the compounds strongly reduced phosphorylation of AKT on Thr308 in the cell lines tested. We describe in sections 2 and 3 similar observations in lymphoma and Ph+ models of leukemia.

The timely development of TOR-KIs directly addressed the biochemical disadvantages of rapalogs. By competing with ATP for binding to the mTOR active site, not only do TOR-KIs more completely block mTORC1 substrate phosphorylation (4E-BPs), but they also inhibit mTORC2 activity173-175,187-189. This results in reduced phosphorylation of AKT at Ser473, dampening the feedback activation of PI3K/AKT 190-192. Several structurally distinct mTOR- selective inhibitors have been developed. Among the most notable are PP242188, Torin1187,312,

Ku-0063794193, AZD8055194,310,316, AZD2014194,317–319, MLN0128 (previously INK128183),

WYE-354320, OSI-027321,322 and CC-223195. However, it is important to note that by competing with ATP, some TOR-KIs inhibit several other related kinases at higher doses, including

PI3K62,236. Conversely, several compounds that are often used pre-clinically as PI3K inhibitors

(wortmannin, LY294002) also directly inhibit mTORC1 and mTORC2 at similar concentrations

(Table 1.1). As noted above, some companies have capitalized on the similarities between PI3K and mTOR active sites, leading to the development of optimized compounds with dual specificity for both kinases (e.g. NVP-BEZ235 and GDC-0980) 185,186.

One alternative to directly targeting PI3K in tandem with mTOR has been the development of TOR-KI, which has been pursued by many groups and was tested in cancer models in vivo.

The Wyeth/Pfizer group was the first to show that the compound WYE-354 could delay growth of PTEN-null U87MG glioblastomas in nude mice 314. Lead optimization by this group led to the discovery of the compound WYE-125132 (abbrev. WYE-132), which showed strong single- agent activity in a range of xenograft models in lung, renal, glioma, and breast cancers displaying hyperactive PI3K/TOR signaling 313. The anti-tumor effect of WYE-132 was markedly stronger than that achieved by the rapalog, CCI-779. Furthermore, among two renal cell carcinoma models and one breast cancer model, rapid tumor regression was observed, which was not obtained with a clinical regimen of CCI-779 or bevacizumab (VEGF mAb developed by

Genentech)313.

Similarly, the compound AZD8055 (TOR-KI developed by AstraZeneca) demonstrated growth inhibition and/or regression in xenograft models316,323. In each of these studies, in vitro experiments confirmed that TOR-KI block rapalog-resistant outputs of both mTORC1 and mTORC2 across a range of cancer cell lines12,233,324–327. Interestingly, WYE-354 failed to inhibit protein synthesis in the colon cancer cell lines HCT116 and HT29 and this was associated with absence of pro-apoptotic effects 314,328. Moreover, our lab has compared rapamycin with PP242, a TOR-KI that inhibits the active site of mTOR in both TORC1 and TORC2 in Ph+ acute

leukemia models269,329. PP242, but not rapamycin, caused death of mouse and human leukemia cells, while PP242 delayed leukemia onset and augmented the effects of TKIs more effectively than rapamycin in vivo. Nevertheless, PP242 had much weaker effects than rapamycin on the proliferation and function of normal lymphocytes. Our lab’s findings established that Ph(+) transformed cells are more sensitive than normal lymphocytes to selective TORC1/2 inhibitors and support the development of such inhibitors for leukemia therapy269,329. Yet a clinical trial of

MLN0128 (TAK-228) in relapsed/refractory ALL patients achieved poor tolerability and clinical significance330.

Dual PI3K/mTOR inhibitors

Another class of inhibitors is dual specificity ATP-competitive inhibitors of both PI3K and mTOR, which will be referred to as dual-PI3K/mTOR inhibitors. The earliest and still widely used inhibitors of this class are wortmannin and LY294002308,331,332. Both compounds are effective at inhibiting class I PI3K activity, but they both have significant off-target effects on other kinases, namely TOR and class II, III, and PIKK family members 333. Moreover,

LY294002 was reported to inhibits PIM kinases 334, and both wortmannin and LY294002 exhibit poor pharmacokinetic properties in vivo308,331,332. Chemical improvements have led to the synthesis of PI-103, a newer ‘second’ generation inhibitor of PI3K and TOR with excellent potency for class I PI3K (low nM) and improved in vitro stability. PI-103 provides therapeutic and on-target activity in both human xenograft and mouse cancer models representing PI3KCA mutations, and PTEN null tumors of various tissues 333. However, PI-103 still exhibits drawbacks in vivo due to extensive liver ‘first-pass’ metabolism, and poor aqueous solubility.

Strong PI3K inhibition might be a liability when considering toxicity to normal cells (see

below)272. Normal cells, and particularly lymphocytes, require PI3K activity for their survival and proliferation, and thus PI3K inhibition might not only harm the malignant cells, but also the normal lymphocytes and thus minimizing the therapeutic window. Several companies have developed more optimized pan-PI3K/TOR inhibitors that are now in clinical trials, and include

BEZ235 and XL765. In a lung cancer model, BEZ235 suppressed tumor growth in vitro and in vivo by inducing cell-cycle arrest at G1 phase, but without causing cell death. It also reduced the expression of cyclin D1/D3 by regulating both its transcription and protein stability331,332,335.

Moreover, BEZ235 proved to be tolerable and highly effective against a wide range of lymphoma cell lines, including ABC and GCB-derived DLBCL cell lines336.

3rd generation mTORC1 inhibitors - Rapalinks

As mentioned above, first generation mTOR inhibitors (rapalogs) have caused responses in a few cases and second generation mTOR kinase inhibitors (TOR-KIs) are currently in clinical trials319,337. When mechanism of resistance to TOR-KIs were analyzed, the intrinsic kinase activity of mTOR was found to be increased, suggesting that tumors with activating mTOR mutations will be intrinsically resistant to second generation mTOR inhibitors. These findings led to the development of a novel class of mTORC1 inhibitors by Kevan Shokat and his group, named “rapalink-1”. These molecules combine rapamycin’s specificity to the mTOR FRB domain/rapamycin/FKBP12 (1FAP) domain with inhibition of mTOR catalytic domain bearing

TOR-KI PP242 (4JT5) via a linker. These compounds overcame the resistance to existing 1st and

2nd generation inhibitors, as they exploit the unique juxtaposition of two drug binding pockets to create a bivalent interaction that enable inhibition of the resistant mutants288. In comparison with temsirolimus, Rapalink‐1 showed significantly greater effects against proliferation, migration, 40

invasion and colony formation in renal cell carcinoma cells, which was achieved through suppression of the phosphorylation of substrates in the mTOR signal pathway such as p70S6K,

4EBP1, and AKT. RNA sequencing showed that Rapalink‐1 suppressed not only the mTOR signaling pathway but also a part of the MAPK signaling pathway, the ErbB signaling pathway and ABC transporters that were associated with resistance to several drugs288,338. Additionally, rapalink-1 showed improved potency (compared to rapamycin or MLN0128), targeted and durable inhibition of mTORC1 in a glioblastoma system, as well as ability to cross the blood- brain barrier in three brain cancer models in vivo290.

Efficacy of targeting the PI3K/mTOR pathway in cancer

Genetic evidence has provided many mechanistic insights into the role of the PI3K pathway in various aspects of tumor progression and response to treatment. Indeed, many human breast cancers with PIK3CA mutations show responses to PI3K/ mTOR and AKT inhibitors in preclinical models 339,340. PI3K/mTOR pathway inhibitors have also been evaluated in the setting of acquired resistance to tyrosine kinase inhibitor (TKI) therapy. In BCR-ABL driven leukemias, mutations E255K and Y253H render imatinib resistance and, in the case of

T315I, render resistance to imatinib and second-generation ABL TKIs dasatinib and nilotinib.

Amplification of MET and ERBB3 are also common mechanisms of resistance to TKIs in the setting of lung and breast cancers, because they can bypass the inhibited receptor and maintain downstream PI3K and RAS/MAPK activation. A strategy to combat acquired TKI resistance in a variety of tumor tissue types is to employ combinations of a PI3K inhibitor (GDC-0941), or a

PI3K/TOR inhibitor (BEZ-235) with a MEK inhibitor (ARRY-142886 or GDC-0879 to block activated RAS) 340–343. With recent availability of several approaches to inhibit the PI3K/mTOR

pathway, there have been many efforts to study and compare the activity of each agent used either singly or in combination with other targeted therapeutics in the treatment of genetically defined cancers. How the PI3K or PI3K/mTOR inhibitors will perform in clinical trials remains to be seen, but preclinical data provide very strong rationale for their testing in specific patients with HER2-amplified and PIK3CA mutated cancers. Alpelisib is an oral α-specific PI3K inhibitor that selectively inhibits p110α to nearly 50 times stronger compared with other isoforms. It has shown efficacy in targeting PIK3CA-mutated cancer based on preclinical models. When alpelisib is combined with fulvestrant, it exhibits a synergistic effect in PIK3CA- mutated, estrogen-receptor (ER)–positive xenograft models. Specifically, alpelisib combined with fulvestrant led to a complete or partial response in 29% of patients with PIK3CA-altered,

ER-positive advanced breast cancer, according to results of a phase Ib trial. These effects were evident when compared with complete or partial responses in patients without PIK3CA-mutated tumors344. Therefore, in May 2019 the FDA approved alpelisib plus fulvestrant for postmenopausal women, and men, with metastatic or otherwise advanced breast cancer that is PIK3CA-altered, HR-positive, and HER2-negative344.

Caveats of targeting mTOR in cancer

Several mTORC1 inhibitors have been developed and investigated in the treatment of B- cell malignancies (e.g. NHL), yet each of them has its caveats. Rapamycin and rapalogs

(everolimus (RAD001), temsirolimus (CCI-779)) show specific and potent (though partial) mTORC1 inhibition that has encouraged many clinical trials using rapalogs for cancer therapeutics345–347. Rapalogs can slow the proliferation of cancer cell lines and have significant activities in the treatment of patients with metastatic renal cell carcinoma (RCC), and TSC-

related harmatous lesions as single agents346,348. However, activities against other solid and hematologic tumors have been limited349,350. The major drawbacks of rapalogs biochemically and clinically that seem to limit them as cancer therapeutics are:

1. Despite drastic inhibition of the S6K substrate of mTORC1 as described above, 4E-BPs

phosphorylation and the control of mRNA translation is far less sensitive302,345,271. Due to

the high importance of mRNA translation in B cell malignancies, this feature of rapalogs

is a significant disadvantage.

2. mTORC2 activity is not acutely blocked (despite suppression upon sustained

exposure)295, and is still able to activate AKT and other targets.

3. The loss of feedback inhibition pathways mediated by S6K results in amplified PI3K

signaling, with potential to amplify RAS, MAPK, and mTORC2 itself 351–354.

4. Upon termination of treatment, regrowth or relapse of the tumor is generally observed.

5. When combined with standard-of-care chemotherapeutics, rapalogs markedly enhance

treatment related toxicities (especially with platinum-based agents) 355s.

6. Rapamycin was reported to antagonize cytotoxicity of anti-metabolites, including

methotrexate and 6-Mercaptopurine (e.g. among Ph+ and Ph-like B-ALL)356.

In an attempt to overcome these drawbacks, the pursuit of TOR-KI and pan PI3K/mTOR inhibitors has been a strong priority. As mentioned before, second generation mTOR kinase inhibitors (TOR-KI) act as ATP-competitive inhibitors and fully inhibit both mTORC1 and mTORC2 62,357 (Figure 1.8). Despite the indications that these compounds generally have stronger anti-cancer activity than rapalogs, they suffer from several important caveats:

Figure 1.8: Targeting mTOR Pathway as a Therapeutic Strategy. The PI3K/mTOR pathway can be targeted at different stages of it: pan-PI3K inhibitors directly target PI3K, while rapamycin and rapalogs partially inhibit mTORC1 through allosteric binding adjacent to the catalytic site of TORC1, but do not acutely inhibit TORC2. The mTOR kinase inhibitors (TOR-KIs) fully inhibit mTORC1 and mTORC2 activity, while Rapa-links in which TOR-KI and rapamycin are chemically linked together to specifically target mTORC1 kinase activity. In this thesis we discuss and exploit small molecule inhibitors of the eIF4F translation initiation complex, named “eIF4F inhibitors”, and compare their efficacy to TOR-KIs.

1. mTOR is involved in many cellular process, such as cell cycle progression, protein

synthesis, cell survival, cytoskeletal remodeling, angiogenesis, cell growth, etc24,358–362.

mTOR coordinates these cellular programs via phosphorylation of diverse substrates.

Therefore, inhibition of all mTOR phosphorylation activity would affect not only the

oncogenic targets which facilitate tumor progression, but also the normal pathways that

are critical for non-malignant cells.

2. TOR-KI achieve their suppression of mTOR activity via competitive binding and

inhibition of the ATP-site. This is facilitated by interaction and binding with critical

amino acids that form the ATP-site. Therefore, it is not surprising that mutations

occurring in the ATP-site of mTOR may interfere with TOR-KI binding to the site and

thus suppressing its activity. This is a critical caveat as mutations in mTOR ATP-site

prevent TOR-KI functionality.

3. One of most important mTORC1 substrates is the 4E-BP family, as they regulate eIF4E

availability and therefore cells’ ability to form the eIF4F complex and to translate mRNA

into proteins. However, several groups have reported the lack of 4E-BPs among

malignant cells, and hence lack of mTOR ability to regulate mRNA translation9,291,363.

Once mTOR losses its ability to regulate mRNA translation, oncogenic drivers are

translated with no regulation and drive the cells’ elevated proliferation and metabolism.

Moreover, certain cells have been reported to overexpress eIF4E, which enables them to

outnumber 4E-BP molecule, free eIF4E to form the eIF4F complex, and thus achieve the

mRNA translation despite mTOR activity9,364–367. Indeed, the ratio of 4E-BPs to eIF4E is

a key determinant of TOR-KI sensitivity292.

Advantages of targeting eIF4F in cancer

A promising alternative to targeting the mTOR pathway while sparing most of mTOR function is to identify and target processes downstream of mTOR that are selectively required for cancer cell survival. One such process is cap-dependent mRNA translation controlled by the eIF4F complex 9,251,252. High eIF4F activity contributes to sustained proliferative signaling, evasion of growth suppression, resistance to programmed cell death, replicative immortality, angiogenesis, invasion and metastasis 252. eIF4E is the major cap-binding protein and has long been considered as the limiting factor for translating the mammalian genome. Indeed, via generation of an Eif4e haplo-insufficient mouse, reduction of 50% in eIF4E expression has been found to allow normal development and global protein synthesis, while impeding cellular

transformation in models of KRAS-driven lung cancer. Moreover, eIF4E holds a critical role in translating a network of mRNAs enriched for a unique 5′ UTR signature (e.g. regulators of reactive oxygen species that fuel transformation and cancer cell survival in vivo)368.

Increased eIF4E and/or eIF4G expression has been linked to advanced disease and decreased patient survival 9,268, and mTORC1/eIF4E activity preferentially translates mRNAs involved in metastasis and invasion 369. eIF4F and protein synthesis were also found to be drivers in PI3K/AKT/mTOR driven lymphomagenesis 306 as well as anti-BRAF and anti-MEK resistance in BRAF(V600)-mutant melanoma, colon, and thyroid cancer cell lines 7. This makes cap-dependent translation an attractive target for cancer therapy 9, and efforts are underway to develop small molecule inhibitors of eIF4F for oncology 370,371. Compared to normal cells, cancer cells are “addicted” to high levels of eIF4F activity 9,251,252 (Figure 1.9). As proof of concept, in a mouse model of Kras-driven lung disease, haploinsufficiency of Eif4e (encoding eIF4E) significantly reduced cellular transformation. While Eif4e homozygous knock-out is embryonic lethal, these Eif4e heterozygous mice had normal development and protein synthesis suggesting that only in cancer does eIF4E activity become a limiting factor 368. Furthermore, various malignant cells rely on cap-dependent translation of specific mRNAs encoding many oncogenes, cell cycle regulators (e.g. Pim-1, or Ras) and pro-survival factors 9,251,252 including

BCL2 family members (e.g. MCL-1 265). In Chapters 2 and 3, we further explore this with NHL as well as mouse leukemia models.

Figure 1.9: Convergence of major signaling pathways involved in cancer toward the eIF4F complex. (A) The eIF4F complex comprises three proteins: the cap-binding protein eIF4E, the DEAD box RNA helicase eIF4A, and the scaffolding protein eIF4G. This complex is negatively regulated by 4EBP1–3 (eIF4E inhibitors) and PDCD4 (eIF4A inhibitor) and actively regulated by eIF4B and eIF4H (eIF4A cofactors). (B) The eIF4F complex comprising eIF4E, eIF4G, and eIF4A is regulated by the MAPK pathway, the PI3K/AKT/mTOR pathway, and transcription factors located downstream of receptor tyrosine kinases (RTK). Aberrant activation of one of these pathways leads to oncogenic processes. Consequently, many inhibitors (red text) have been designed to specifically inhibit RTKs or components of the MAPK or PI3K/mTOR pathways. Most inhibitors indicated in the figure have several targets; however, only the main one is indicated. eIF4F is positioned at the convergence of these dysregulated pathways and is, therefore, a promising target for many types of cancer. Reference: Malka-Mahieu H., Newman M., Désaubry L., Robert C., and Vagner S. (2016). Clin Cancer Res; 23(1); 21–25.

Liabilities of currently available eIF4F inhibitors

There are various ways to target the eIF4F complex, and any of the three main components of it could be targeted. Currently available eIF4E-binding molecules have liabilities. For 47

example, the antiviral compound ribavirin was proposed to function as a m7G-cap analog372,373, but instead acts in cancer cells through an off-target mechanism 373–375. Ribavirin is a nucleoside analog that displays fairly broad anti-viral properties and is currently FDA approved in the treatment of RSV and HCV. The exact mechanism of action of ribavirin in the cell has remained somewhat obscure. Therefore, it should always be kept in mind that cap-analogs might have effects other than inhibiting eIF4E-dependent protein synthesis, and that perhaps other pharmacological strategies might prove more specific in design375.

A small molecule eIF4E/eIF4G interaction inhibitor 1 (4EGI-1), disrupts the eIF4E/eIF4G interaction and promotes binding of 4E-BP1 to eIF4E364. By preventing eIF4E/eIF4G interaction,

4EGI-1 impairs the assembly of the eIF4F complex and decreases eIF4E-regulated proteins expression in myeloma cells. Moreover, 4EGI-1 was found to induce apoptosis in many myeloma cell lines. This seems to occur via 4EGI-1 triggered Noxa induction only in cells undergoing apoptosis through endoplasmic reticulum (ER) stress376. Nevertheless, it seems that

4EGI-1 suffers from low potency and is mostly effective in the mid-µM range 370. This feature reduces 4EGI-1 potential as it is very likely that mid-µM concentrations are not clinically relevant.

Another class of eIF4F inhibitors are inhibitors of the eukaryotic initiation factor 4A

(eIF4A) subunit, such as hippuristanol, and silvestrol377–379. eIF4A is a member of the DEAD- box family of putative RNA helicases whose members are involved in many aspects of RNA metabolism380,381. eIF4A, a DEAD-box RNA helicase implicated in preparing a ribosome landing pad for 43S pre-initiation complexes (40S ribosomal subunit and associated factors) by unwinding 5′ mRNA structure; and eIF4G, a large scaffolding protein involved in recruiting the

43S pre-initiation complex via its interaction with 40S-associated eIF3382. eIF4A is an abundant

translation factor that exists in a free form (eIF4Af) and as a subunit of the heterotrimeric eIF4F

complex383,384. eIF4A inhibitor function as chemical inducers of dimerization and force a non-

sequence specific engagement between eIF4A and RNA, resulting in depletion of eIF4A from

379,385,386 the eIF4F complex . They force an engagement between eIF4Af and RNA, although how

this inhibits translation initiation is not known379. Nevertheless, major disadvantages of those

inhibitors include poor bioavailability coupled with high potential to develop multidrug

resistance. Despite much promise of eIF4A inhibitors to target eIF4F complex specifically, these

two important caveats urge the need of more specific and available eIF4F inhibitors.

Recently, a class of eIF4A inhibitors have been reported, named “Rocaglates”, and the

novel lead compound, CMLD012612, was identified and characterized387. Rocaglates share a

common cyclopenta[ b]benzofuran core that inhibits eukaryotic translation initiation by

modifying the behavior of the RNA helicase, eIF4A. They function as interfacial inhibitors, thus

stabilizing the association between eIF4A and RNA, which can lead to the formation of steric

barriers that block initiating ribosomes. There is significant interest in the development and

expansion of rocaglate derivatives (e.g. amidino-rocaglates), as several members of this family

have been shown to possess potent anti-neoplastic activity in vitro and in vivo387–390.

Figure 1.10: Components of eIF4F translation initiation machinery complex, and inhibitors. A critical step in the translation initiation process is the binding of eIF4E to the mRNA cap. eIF4E mediates the formation of the eIF4F complex on the mRNA cap structure (a 7mGp bound to the first nucleotide). eIF4F complex, in addition to eIF4E, consists of eIF4G (scaffolding protein) and eIF4A (helicase). Successful formation of eIF4F complex on the mRNA cap further promotes the recruitment of the pre-initiation complex (PIC), followed by 5′ UTR scanning to reach the start codon AUG and joining of 40S ribosomal subunit.

SBI-756 - a novel and promising eIF4F inhibitor

One appealing strategy for potentiating the effectiveness of existing cancer therapies and to overcoming resistance to drugs (e.g. BRAF inhibitors) is disruption of the eIF4F complex.

Moreover, due to the caveats of currently available eIF4F inhibitors mentioned, the search for specific, effective and tolerable small molecule inhibitor proceeds. One promising candidate named SBI-0640756 (SBI-756 hereafter) was reported by Dr. Ze’ev Ronai and his group371, our collaborators in this work (Figure 1.10). They have identified and characterized SBI-756 as a small molecule inhibitor, capable of binding eIF4G1 and disrupting its binding to eIF4E at nanomolar concentrations 371. It was reported active and tolerable in vitro and in vivo in a melanoma model. SBI-756 impairs eIF4F complex assembly independently of mTOR activity and attenuates growth of BRAF-resistant and BRAF-independent melanomas. Importantly, it was found to inhibit proliferation of 4E-BP lacking cells, where mTOR inhibitors (e.g. Torin-1) lost their efficacy371. One noticeable advantage of SBI-756 over other small molecule inhibitors is its ability to suppress AKT and NF-κB signaling, while sparing mTOR activity which is important for functionality of many cells, and lymphocytes particularly. When gene expression signature analyses were performed, SBI-756 was found to suppress DNA damage and cell-cycle regulatory factors mainly. It also inhibited the growth of NRAS, BRAF, and NF1-mutant

(neurofibromin 1, negatively regulates RAS proteins through GTPase activity391) in melanoma systems in vitro. Furthermore, the report indicated a delayed onset and reduced incidence of

Nras/Ink4a melanoma in vivo, among SBI-756 treated mice. Lastly, the combination of SBI-756 with BRAF inhibitor (BRAFi) seemed to suppress BRAFi-resistant human tumor formation371.

Together, these findings have indicated a great potential of SBI-756 to abrogate the growth of the

melanoma cells tested and encouraged us to repurpose SBI-756 in the human blood malignancies that we tested and described in chapters 2 and 3.

Organization of chapters

Evasion of apoptosis is a hallmark of cancer that is now directly targetable using BH3 mimetics in general, and small molecule BCL2 inhibitors, in particular. Despite much efficacy in some settings (e.g. CLL), it is becoming apparent that BH3 mimetics induce incomplete responses in other contexts, such NHL or Ph+ B-ALL. One promising approach to improving their efficacy is through rational combinations. Several oncogenic pathways feed into regulation of the BCL2 family proteins and may contribute to poor sensitivity to BCL2-targeting therapies.

On the other hand, TKIs in general and dasatinib specifically suffer from similar liabilities in the context of Ph+ B-ALL, thus urging development of novel therapeutic strategies. A promising candidate pathway that we used in this work to sensitize for both classes of targeted agents is the mTOR/eIF4F pathway. Many attempts have been made to target the main kinase complex of the mTOR pathway, named mTORC1, yet this approach has significant caveats. Therefore, this dissertation takes a new approach and targets a direct downstream target of mTOR – eIF4F translation initiation complex. We took advantage of both a chemical approach and a novel genetic approach that we have developed to specifically target the eIF4F complex, suppressing cap-dependent translation while sparing mTOR.

In Chapter 2, we present a mechanistic investigation into the efficacy of combining the novel eIF4F inhibitor SBI-756, with venetoclax. Using pharmacological and genetic approaches, we identify a mechanism of action that complements previously published studies and strongly supports further clinical investigation. Moreover, we show that the suppression of cap-dependent

translation via SBI-756 directly sensitizes NHL to venetoclax, while sparing mTOR activity. In addition, we provide evidence that point at specific survival factors necessary for supporting

NHL survival and can be targeted, thus sensitizing to BCL2 inhibition. These findings led to a first-author publication that is under consideration by the British Journal of Cancer.

Chapter 3 investigates the potential of targeting eIF4F complex in general, and eIF4E specifically to sensitize Ph+ B-ALL cells to the targeted agent dasatinib. We have been able to target eIF4F complex via pharmacological approach or a novel genetic approach that we have developed, which enables us to control the availability of eIF4E to form the eIF4F complex.

Also, we reaffirm the efficacy of sensitization to TKIs via eIF4F inhibition. These results have led to a co-first author manuscript, currently in preparation.

Lastly, Chapter 4 summarizes the major findings of this dissertation, discusses unpublished or incomplete data, and provides insight into unanswered mechanistic questions regarding the efficacy of the two combinations presented. We also present some future directions for enhancing the efficacy of targeted agents in cancer.

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the cap recognition process. J. Biol. Chem. 1983;258(18):11398–11403.

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experimental cerebral malaria. Proc. Natl. Acad. Sci. USA. 2018;115(10):E2366–E2375.

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Chapter Two

Targeting eIF4F Translation Initiation Complex with SBI-756 Sensitizes B Lymphoma Cells to

Venetoclax

This chapter is largely derived from a manuscript under review in the British Journal of

Cancer, entitled “Targeting eIF4F Translation Initiation Complex with SBI-756 Sensitizes B

Lymphoma Cells to Venetoclax”. Supplementary materials originally included in this manuscript have been incorporated into the main text.

Abstract

The BCL2 inhibitor venetoclax has shown efficacy in several hematologic malignancies, with the greatest response rates in indolent blood cancers such as chronic lymphocytic leukemia

(CLL). There is a lower response rate to venetoclax monotherapy in diffuse large B-cell lymphoma (DLBCL). Here, we demonstrate that small molecule inhibitors of cap-dependent mRNA translation sensitize DLBCL cells to apoptosis by venetoclax. We compared the mTOR kinase inhibitor (TOR-KI) MLN0128 with SBI-756, a compound targeting eukaryotic translation initiation factor 4G1 (eIF4G1), a scaffolding protein in the eIF4F complex. Treatment of DLBCL and mantle cell lymphoma cells with SBI-756 synergized with venetoclax to induce apoptosis in vitro, and enhanced venetoclax efficacy in vivo. SBI-756 prevented eIF4E-eIF4G association and cap-dependent translation without affecting mTOR substrate phosphorylation. In TOR-KI- resistant DLBCL cells lacking eIF4E binding protein-1 (4E-BP1) SBI-756 still sensitized to venetoclax. SBI-756 selectively reduced translation of mRNAs encoding ribosomal proteins and translation factors, leading to a delayed reduction in protein synthesis rates in sensitive cells.

When normal lymphocytes were treated with SBI-756, only B cells had reduced viability and this correlated with reduced protein synthesis. Hence, our data highlights a novel combination for treatment of aggressive lymphomas, and establishes its efficacy and selectivity using preclinical models.

Introduction

The mammalian target of rapamycin (mTOR) is a central regulator of cell growth and proliferation, as well as a target for therapeutics in cancer and other diseases 1. The two complexes that facilitate signal transduction in the mTOR pathway are mTORC1 and mTORC2. mTOR-activating mutations occur in diffuse large B cell lymphoma (DLBCL) 2, and elevated mTORC1 activity correlates with chemotherapy resistance and poor prognosis in pre-B acute lymphoblastic leukemia (B-ALL) 3.

mTORC1 substrates include S6 kinases (S6Ks) and eukaryotic translation initiation factor

4E (eIF4E)-binding proteins (4E-BPs). Phosphorylation of 4E-BP releases its inhibition of eIF4E. Upon release, eIF4E binds the scaffolding protein eIF4G1 and the RNA helicase, eIF4A, to form the eIF4F protein translation initiation complex that binds to the 5’ cap of certain mRNAs and facilitates cap-dependent translation 4–6. Phosphorylation of 4E-BP1 correlates with high risk in B-ALL and chronic lymphocytic leukemia 3,7, while mTOR inactivation impairs B-

ALL survival 8,9.

Several mTORC1 inhibitors have been developed and investigated in the treatment of B- cell non-Hodgkin’s lymphoma (NHL), yet each has caveats. Rapamycin and its analogs

(rapalogs) are only partial inhibitors of mTORC1 that do not effectively suppress 4E-BP1 phosphorylation 10. Second generation mTOR kinase inhibitors (TOR-KI) act as ATP- competitive inhibitors and fully inhibit both mTORC1 and mTORC2 11,12. One candidate TOR-

KI studied in our lab, MLN0128/TAK-228 13, has entered a phase 2 clinical trial in B-ALL.

TOR-KI have shown improved pro-apoptotic activity in preclinical studies 11,12 yet their therapeutic potential is limited by several factors including toxicity 14, adaptive survival signaling 15, and mTOR resistance mutations 16.

A promising alternative is to identify and target processes downstream of mTOR that are selectively required for cancer cell survival. One such process is cap-dependent mRNA translation controlled by the eIF4F complex 4–6. Compared to normal cells, cancer cells are

“addicted” to high levels of eIF4F activity 4–6, as demonstrated using eIF4E heterozygous mice, which were healthy yet resistant to Ras-driven tumorigenesis 17. Various malignant cells rely on cap-dependent translation of specific mRNAs encoding many oncogenes, cell cycle regulators and pro-survival factors 4–6 including BCL2 family members (e.g. MCL-1 18). Hence, targeting cap-dependent translation downstream of mTOR could enhance efficacy of other pro-apoptotic therapies.

Currently available eIF4F inhibitors have liabilities, including low potency, lack of selectivity or poor pharmacological properties 5. Here we use the novel small molecule inhibitor of eIF4G1, named SBI-756, to target the eIF4F translation initiation complex 19. SBI-756 is a small molecule that binds to eIF4G1 and prevents its interaction with eIF4E 19. In our previous study, SBI-756 inhibited melanoma in vitro and in vivo 19.

Venetoclax is a small molecule BH3 mimetic drug that selectively binds BCL2 and inhibits its pro-survival function 20,21. Since initial FDA approval of venetoclax for treatment of

CLL patients with 17p chromosomal deletion 22, additional combination regimens have been approved 23,24. Novel combinations are needed to improve responses in NHL, where single agent venetoclax has limited activity 25. Here we tested the efficacy of SBI-756 in NHL cell lines, alone and in combination with venetoclax. We find that SBI-756 synergizes with venetoclax in

DLBCL and mantle cell lymphoma (MCL) cells in vitro, and promotes tumor regression in vivo.

SBI-756 at nanomolar concentrations disrupts the eIF4G1:eIF4E interaction in cells, reprogramming mRNA translation and sensitizing to apoptosis. Lymphoma cells with natural or

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engineered loss of 4E-BP1 were resistant to TOR-KIs yet retained sensitivity to SBI-756.

Mechanistic experiments showed that SBI-756 had a selective effect on translation efficiency of components of the translation machinery, leading to reduced protein synthesis rates. These results identify disruption of eIF4F assembly as a promising approach to enhance venetoclax efficacy in NHL.

Materials and Methods

Chemicals

We obtained rapamycin and MLN0128 from LC Laboratories (Woburn, MA, USA) and ABT-

199 from Active Biochem (Wan Chai, Hong Kong). SBI-0640756 was synthesized as described

19 or purchased from Selleck with comparable results. Q-VD-OPh was obtained from SA (St.

Louis, MO), and dimethyl sulfoxide (DMSO) from Fisher Scientifc (Waltham, MA, USA).

Cell culture

OCI-LY1, OCI-LY7, OCI-LY8, OCI-LY18, SU-DHL-4, SU-DHL-6, SU-DHL-10, and VAL cell lines were obtained from Dr. Laura Pasqualucci (Columbia University, NY). These cell lines were validated by STR profiling (University of Arizona Genomics Core). Cells were cultured in

IMDM (GE Healthcare Hyclone, Little Chalfont, UK) supplemented with 10% fetal bovine serum (FBS) (SA), 10 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES)

(Corning), 10 mM L-Glutamine with 100 I.U. penicillin and 100 µg/ml streptomycin (Gemini

Bio-products, Sacramento, CA). MAVER-1, JEKO-1, Mino, CCMCL1, and UPN-1 were kindly provided by Dr. Selina Chen-Kiang and Dr. Maurizio Di Liberto (Weill Cornell Medical

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College). These cells were cultured in RPMI-1640 (Corning) supplemented with 10% heat- inactivated FBS, 10 mM HEPES, 2 mM L-glutamine and 100 I.U./ml penicillin/streptomycin.

Cells were grown in a humidified 37°C incubator with 5% CO2. Cells were routinely tested to ensure absence of mycoplasma and validated by STR profiling, and were maintained at or below

2x10e6 cells/ml. Human embryonic kidney (HEK) 293T cells were cultured in Dulbecco’s

Modified Eagle Medium (DMEM; Life Technologies, Carlsbad, CA, USA) supplemented with

10% calf serum, 100 I.U. penicillin, and 100 µg/ml streptomycin. Human peripheral blood mononuclear cells (PBMCs) were isolated from blood samples by centrifugation through Ficoll-

Paque™ (GE Healthcare, Piscataway, NJ, USA) and were grown in RPMI with 10% FBS, 10 mM HEPES, 10 mM L-Glutamine, 100 I.U. penicillin, 100 µg/ml streptomycin.

Immunoblotting

Cells were lysed in radio-immunoprecipitation assay buffer (150 mM NaCl, 1.0% IGEPAL®

CA- 630, 0.5% sodium deoxycholate, 0.1% SDS, and 50 mM Tris, pH 8.0, 2 mM EDTA, 50 mM

NaF) supplemented with protease inhibitor cocktail (Calbiochem, USA) and phosphatase inhibitor cocktails 2 and 3 (SA). Protein concentrations were normalized using a Bradford protein assay (Bio-Rad, Hercules, CA). Lysates were prepared at 1 µg/µl concentration in 1X XT

Sample Buffer (Bio-Rad) and 5% BME (SA). Lysates were run on 8-12% Bis-Tris gels, and transferred onto nitrocellulose membranes (Bio-Rad). Antibodies to the following phosphoproteins and total proteins were used: phospho-Akt (S473), Akt, phospho-rS6

(S240/244), phospho-BAD (S136), phospho-4E-BP1 (Thr 37/46), 4E-BP1, 4E-BP2, GAPDH,

Actin, PARP, caspase 9, cleaved caspase 3, MCL-1, BCL-2, BCL2L1(BCL-xL), survivin, eIF4E, eIF4G1, BIM, ERK1/2, and BAD (Cell Signaling Technology, Beverly, MA, USA), and NOXA

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(Abcam, Cambridge, MA). We used the anti-mouse IgG and anti-rabbit IgG secondary HRP- conjugated antibodies from Promega (Madison, WI, USA). Antibody dilutions were performed according to the manufacturer’s instructions. Immunoreactive bands were visualized using

Amersham ECL Prime Western Blotting Detection Reagent (GE Healthcare Life Sciences,

Marlborough, MA) or Super Signal West Femto Maximum Sensitivity Substrate (Thermo Fisher

Scientific, Carlsbad, CA) and detected using a Nikon D700 SLR camera as described previously26. Images were processed and densitometry was quantified using ImageJ software

(NIH).

Cell viability

Cell viability assays were performed in 96-well U-bottom plates, with 6x10e4 cells in 200 µl.

Cells were harvested by centrifuging the 96-well plate in a plate spinner centrifuge at 1700 rpm for 5 minutes. Cells were washed and stained with Annexin V conjugated to Alexa FluorTM 647 nm (Thermo Fisher Scientific) 0.1mg/ml propidium iodide (PI)-staining solution (Life

Technologies). Cells were then analyzed on a FACSCalibur flow cytometer (Becton-Dickinson,

San Jose, CA) or ACEA NovoCyte Flow Cytometer (ACEA Biosciences, San Diego, CA) and cell cycle analysis performed using FlowJo software v.5.7.2 (TreeStar, Ashland, OR). Percentage of viable cells was determined based on the fraction of total cells that were Annexin V-negative and PI-negative.

Synergy calculation

Synergy between SBI-756 and venetoclax among GCB-DLBCL and MCL cells was perfomed as described previously27. Briefly, predicted combination indexes for cells of interest treated with

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venetoclax and SBI-756 using combination index (CI) theorem of Chou-Talalay and CalcuSyn software (CI > 1 antagonism, CI = 1 additivity, CI < 1 synergy). Data were normalized to untreated control and converted to fractional effect as the inverse of viability (in other words: fractional effect of 0 is synonymous with 100% viability). Black circles are experimental data.

Isobolograms produced for each cell line are presented.

Cell Cycle Analysis

6x10e6 cells were harvested, fixed in 50% ethanol, washed and stained in 0.1 mg/ml propidium iodide (PI)-staining solution (Life Technologies). Cells were then analyzed on a FACSCalibur flow cytometer (Becton-Dickinson), and cell cycle analysis performed using FlowJo software v.5.7.2 (TreeStar). After exclusion of cell debris, the induction of cell death was measured by calculating the percentage of intact cells with Sub-G1 DNA content.

Puromycin Incorporation Assay

We performed puromycin incorporation assays in OCI-LY1 parental, OCI-LY1 SBI-756 resistant, OCI-LY7, OCI-LY8, SU-DL6 and SU-DHL10. Cells were plated at 3 x 106 cells in 4 ml and treated with inhibitors for 16 hours. Nascent peptide chains were labeled by incubating cells in 10 µg/ml puromycin (Sigma-Aldrich) for 15 minutes. Control cells were co-treated with

20 µM cycloheximide (Sigma-Aldrich) during puromycin labeling. We then fixed and permeabilized the cells (using eBiosci Foxp3-staining kit fix/perm buffer, eBioscience, San

Diego, CA) and immune-stained them using anti-Puromycin Alexa-Fluor 488nM conjugated antibody (Sigma Aldrich) together with Zombie violet viability kit (BioLegned, San Diego, CA).

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Next, we analyzed the puromycin incorporation of the cells using ACEA Novocyte 3000 flow cytometer (ACEA, San Diego, CA), while focusing on live, single cells.

Luciferase Reporter Assays to Measure Cap-Dependent Translation

Luciferase reporter construct pRSTF-CVB3 (kindly donated by Dr. Semler (UC Irvine)) containing the 5’ NCR of the Coxsackie B3 virus28 was cloned between a firefly (Photinus pyralis) and Renilla (Renilla reniformis) luciferase. The construct was used to measure cap- dependent translation as well as IRES dependent translation. For all experiments, cells were transfected in a FBS free media using Gene Pulser Xcell modular electroporation system (Bio-

Rad) at 280V and 0.975 F. Cells were allowed to recover in complete IMDM media for three hours followed by inhibitor treatment for 16 hrs. Following treatment, cells were lysed and

Renilla was measured, followed by firefly luciferase expression. Measurements were done using the Dual-luciferase assay kit (Promega) and by using a luminometer (Titertek-Berthold,

Pforzheim, Germany). Results were expressed relative to untreated control.

Quantitative Real Time PCR

RNA was extracted from cells using Trizol (Life Technologies), and 1 mg of RNA was reverse transcribed using the iScript cDNA synthesis kit (Bio-Rad). Gene specific primers were used to amplify MCL-1, Cyclin D3 and Actin using the Step One Real time PCR system and relative quantification of the transcripts was done using the delta delta cT (ΔΔCt) method. 4EBP1,

4EBP2 and actin specific primers were used in a 30 cycle PCR reaction using the S1000 thermal cycler (Biorad) to check for expression of the relevant mRNA transcripts.

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BH3 profile

OCI-LY1 and OCI-LY8 cell lines were profiled as previously described (18), with modifications.

Cells were plated at 8 x 106 cells per 10 ml of media and treated with inhibitors for 16 hours. 4 x

105 cells were incubated in T-EB buffer (300 mM trehalose, 10 mM HEPES, 80 mM potassium chloride, 1 mM EGTA, 1 mM EDTA, 0.1% BSA, and 5 mM succinic acid) with 200 nM JC-1

(Life Technologies), 0.001% digitonin (Sigma-Aldrich), and 10 µg/ml oligomycin (Sigma-

Aldrich) with either DMSO or BH3-only peptides for 60 minutes prior to analysis using a

FACScalibur (Becton-Dickinson). The sequences and method of synthesis of BH3-only peptides were described previously (19). Percent depolarization caused by each BH3-only peptide was calculated as the percent difference in the JC-1 red fluorescence (590 nm) relative to DMSO- treated control cells.

Retro/lentiviral transductions

For all viral productions, HEK 293T cells were transfected using X-tremeGene HP DNA

Transfection Reagent (Roche, Switzerland). 293T cells were incubated for 24 hours prior to replacing medium with IMDM. These virus-containing media were then harvested after an additional 24 hours and used to transduce DLBCL cell lines. For retroviral production, 293T cells were co-transfected with pCL-ampho viral packaging vector (Novus Biologicals, Littleton,

CO, USA) whereas pCMV-VSV-G (Addgene plasmid 8454) and psPAX2 (Addgene plasmid

12260) were co-transfected for lentivirus production. To transduce DLBCL cell lines, we incubated cells in viral supernatants for 72 hours (changing supernatant every 24 hours) with 10

µg/ml 1,5-dimethyl-1,5-diazaundecamethylene polymethobromide (polybrene, SA). Cells were treated with either blasticidin (8 µg/ml) or puromycin (2 µg/ml) for 5 days after transduction to

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select for stably transduced cells. Plasmid positive cells were maintained with blasticidin (4

µg/ml) or puromycin (1 µg/ml).

Generation of Cell Lines with Inducible Expression of Wild Type 4E-BP1 or 5A Mutated 4E-BP1

To generate DLBCL cells with doxycycline-inducible expression of a gene of interest, cells were first transduced with pMA2640 (Addgene plasmid #25434) and selected for blasticidin resistance. Expression of the improved tetracycline-controlled transactivator (rtTA-Advanced) allowed for doxycycline-inducible expression of genes downstream of the modified Tet- responsive element provided in the pLVX-tight-puro vector (Takara). Full length rat wild type

4E-BP1 was obtained from Dr. John Lawrence (University of Virginia, Charlottesville, VA). The

4E-BP1 construct in which five phosphorylation sites (all Serine/Threonine phosphorylation sites) were changed to Alanine (“5A mutant”) was a kind gift from Dr. Davide Ruggero (“5A mutant”, depicted in Fig. 2.1B). These constructs were cloned into the pLVX-Tight-Puro Dox inducible system using NotI and EcoRI restriction sites. High titer lentivirus was produced using the lentiviral packing and envelope constructs mentioned above. OCI-LY1 and OCI-LY8 cell lines expressing the reverse tetracycline transactivator protein (rtTA) were infected with the lentivirus and selected in IMDM culture medium containing 8 µg/ml Blasticidin and 2.0 µg/ml

Puromycin. The wildtype (or mutant) 4E-BP1 expression was induced by addition of 1 µg/ml

Doxycycline for 16–24 hrs. All pLVX-tight-puro plasmids were sequenced using the following primer, 5’-AGCTCGTTTAGTGAACCGTCAGATC-3’.

Generation of OCI-LY1 4EBP1 and 4EBP2 KO Cell Lines

To generate OCI-LY1 cells genetically edited to express CRISPR/Cas9 system that knocks out

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(KO) 4EBP1 and 4EBP2, the lentiviral vector lentiCRISPRv2-puro (Addgene plasmid #98290)

was processed to contain 4EBP1 guided sgRNA (see sgRNA sequence in supp. table 2.1).

Transduced cells were selected for puromycin resistance and validated for 4EBP1 KO via

western blot analysis. Next, the cells isolated were transduced using the lentiviral vector

lentiCRISPRv2-Blast (Addgene plasmid #83480) following insertion of 4EBP2 sgRNA into it

Transduced cells were selected for puromycin and blasticidin resistance. Isolated cells were

validated for 4EBP1 and 4EBP2 KO via western blot analysis (Fig. 2.9).

Table 2.1: The sequences used for guiding Cas9 to 4EBP1:

Forward Sequence Backward Sequence Set 1 5’ CACCGGAGCACCACCCGGCGAGTGG 5’ AAACCCACTCGCCGGGTGGTGCTC Set 2 5’ CACCGGGGCTCATCACTGGAAGGGC 5’ AAACGCCCTTCCAGTGATGAGCCC Set 3 5’ CACCGGGGCGAATAGAAGACCCGAT 5’ AAACATCGGGTCTTCTATTCGCCC

Table 2.2: The sequences used for guiding Cas9 to 4EBP2:

Forward Sequence Backward Sequence Set 1 5’ CACCGGCTGATGGCCACGGTGCGGG 5’ AAACCCCGCACCGTGGCCATCAGC Set 2 5’ CACCGGGTGTGGCCCTCCACTCGCG 5’ AAACCGCGAGTGGAGGGCCACACC Set 3 5’ CACCGGCAGGGTGGGGTCTGAGCCA 5’ AAACTGGCTCAGACCCCACCCTGC

Generation of OCI-LY1 cell line with SBI-756 resistance

OCI-LY1 cells were cultured as described above. We introduced the cells to increasing SBI-756

concentrations in their culture media with every cell passaging (from 10 nM to 1.1 µM).

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Duolink Proximity Ligation Assay (PLA)

We performed PLA as described before 29. Briefly: 2x10e6 cells were treated for four hours as indicated. Cells were washed with 1x phosphate buffered saline (PBS) (Corning, NY) and fixed with 4% paraformaldehyde (Thermo Fisher Scientific). CometSlides (Trevigen, Gaithersburg,

MD) were coated with Poly-L-Lysine 0.1% solution (Sigma Aldrich (SA), St. Louis, MO), and cells were allowed to adhere. We followed the protocol of Duolink PLA 30; briefly: Cells were blocked using Duolink blocking solution, followed by probing with primary antibodies for eIF4G1 (Cell signaling Technologies, Danvers, MA, Cat. #2858, 1:200 dilution) and eIF4E (BD

Biosciences, San Diego, CA, Cat. #610269, 2.5 µg/ml final). Next, cells were incubated with

Duolink In Situ PLA Probe Anti-Rabbit PLUS (Cat. # DUO92002) and Duolink In Situ

PLA Probe Anti-Mouse (Cat. # DUO92004) and allowed to ligate using ligation mix. Next, amplification and washes were performed as instructed and the slides were mounted using media containing DAPI. Slides were images using Leica TCS SP8 confocal microscope. Signal obtained was quantified using ImageJ software, and normalized to the number of cells per field

(using DAPI nuclei staining). Images shown indicate the signal (Orange DuolinkTM) and nuclei for each field imaged, while graphs presented indicate ratio values of signal per cell in each field imaged.

Mice Strain and Compounds Administration in vivo

NOD scid gamma (NSG) immunodeficient mice (Jackson Laboratories, Bar Harbor, ME) were used for in vivo experiments, with equal numbers of females and males. Animal studies were approved by the Institutional Animal Care and Use Committee at UC Irvine. Female NSG mice were injected subcutaneously (s.c.) with 1x10e6 OCI-LY1 cells/mouse. Cells were injected in

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total volume of 200 µl along with Matrigel (Corning) for providing a supportive environment for tumor development. Once tumor size reached 110 mm3 volume, mice were treated daily for five days as described in Figure 3. Each mouse body weight was examined throughout the trial to identify potential toxicity or changes in dosing parameters. Also, tumor sizes were monitored daily and recorded. At the end of five days of dosing, each mouse was weighed, sacrificed and tumors were excised for analysis. Analysis of tumors included tumor size, weight and preparation of single cell suspension. Cells extracted were fixed using 4% PFA and used for intracellular staining as well as PLA.

Polysome profiling

Cells were grown to approximately 70% confluence. Cycloheximide (0.1 mg/mL final concentration) was added to the medium for 5 min at 37°C to arrest the ribosomes. The cells were washed twice with PBS containing 0.1 mg/mL cycloheximide, and then pelleted. The supernatant was removed, and the pellet was flash frozen. Cell pellets were lysed for 10 min on ice with 400 µL polysome extraction buffer (15 mM Tris-Cl, pH7.4, 15 mM MgCl2, 0.3 M NaCl,

0.1 mg/mL cycloheximide, 0.1 mg/mL heparin, 1% Triton X-100). The lysates were cleared by centrifugation at 13,200 x g for 10 min. Equal RNA concentrations were layered onto 20-50% sucrose gradients. Gradients were sedimented at 151,263 x g for 103 min in a SW55 Ti rotor at

4°C. An ISCO UA-6 (Teledyne, Thousand Oaks, CA) fraction collection system was used to collect 12 fractions, which were immediately mixed with 1 volume of 8 M guanidine HCl. RNA was precipitated from polysome fractions by ethanol precipitation and dissolved in 20 µL of

H2O. Briefly, fractions were vortexed for 20s. 600 µL of 100% ethanol was added, and fraction was vortexed again. Fractions were incubated overnight at -20°C to allow for complete RNA

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precipitation. Fractions were centrifuged at 13 200 rpm for 30 min at 4°C. The RNA pellet was washed with 75% ethanol. The pellet was resuspended in 400 µL 1x Tris-EDTA (pH 8.0). 0.1 volumes of 3M NaOAc (pH 5.3) and 2.5 volumes 100% ethanol were added and fractions were incubated at -20°C to precipitate RNA. Fractions were centrifuged at 13 200 rpm for 30 min at

4°C. The RNA pellet was washed with 75% ethanol. RNA was resuspended in 20 µL H2O. Total

RNA samples were isolated from cell lysates using Trizol per the manufacturer’s instructions.

RNA-seq and analysis

Fractions containing 4 or more ribosomes (considered well-translated) were pooled and RNA quality was measured by a Bioanalyzer (Agilent Technologies). RNA-seq was carried out by the

New York University School of Medicine Genome Technology Core using the Illumina HiSeq

4000 single read. To examine differences in transcription and translation, total mRNA and polysome mRNA were quantile-normalized separately. Statistical analysis was performed using

RIVET 31. GO analysis was performed using the DAVID online tool.

Statistical analysis

The number “n” of biological replicates for each experiment is indicated in the figure legends.

Two-way ANOVA for multiple comparisons was performed where indicated while considering sample independence, variance equality and normality. Student t-tests were applied to population means assuming equal variance (standard deviations within two-fold). The use of one- versus two-sample tests, and paired versus unpaired comparisons, was justified by the experimental design as indicated in the Figure Legends.

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Results

Constitutively active 4E-BP1 mutant sensitizes DLBCL cells to venetoclax, similar to TOR-KI treatment

mTOR inhibitors enhance killing of DLBCL cells by BH3 mimetics such as venetoclax

(ABT-199), ABT-263 or ABT-737 32. To evaluate the role of the 4E-BP/eIF4E axis in this sensitization, we used a doxycycline (DOX)-inducible system to express wild-type 4E-BP1 or a constitutively active form in which all five serine/threonine phosphorylation sites were changed into alanine (5A mutant, Fig. 2.1B). Since 4E-BP1-5A cannot be phosphorylated by mTORC1, expression of this mutant prevents eIF4E from associating with eIF4G1 and other proteins to form the eIF4F complex 33. We generated OCI-LY1 DLBCL cells expressing the reverse tetracycline transactivator (rtTA) protein and either empty vector (EV), WT 4E-BP1, or 4E-BP1

Figure 2.1: mTORC1 regulates eIF4E dependent translation via phosphorylation of 4E-BP1. Panel A shows PI3K/ mTOR pathway where 4E-BP1 is in its non-mutated version and thus can bind to eIF4E and prevent the latter’s interaction to form the eIF4F complex, unless phosphorylated by mTORC1. This process is a critical regulator of cap-dependent translation which drives many cellular processes. Panel B shows the same pathway where 4E-BP1 was mutated in its five phosphorylation sites to alanine. These mutations, named “5A”, prevent the phosphorylation process of 4E-BP1 and thus eIF4E availability for cap-dependent translation.

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mutant (5A). Addition of DOX induced expression of the mutant protein after 16 hours (Fig.

2.2A). Next, we treated cells (-/+ DOX) for 48 hours with a range of venetoclax concentrations in combination with either vehicle (DMSO), or TOR-KI (MLN0128 100 nM). As expected,

TOR-KI treatment sensitized to venetoclax as shown by reduced IC50 values (Fig. 2.2B).

Notably, OCI-LY1 cells expressing the active 4E-BP1 (5A) and treated with vehicle (lane 5, Fig.

2.2A) were as sensitive to venetoclax as control cells (WT or EV) treated with TOR-KI (lanes 2 and 4 Fig. 2.2B). TOR-KI further increased sensitization to venetoclax in cells expressing 4E-

BP1 5A MUT. This is most likely due to dephosphorylation and activation of endogenous 4E-

BPs by TOR-KI treatment, adding to the effect of 5A mutant expression. A similar sensitization was observed in OCI-LY1 cells expressing 4E-BP1 5A and treated with navitoclax (ABT-263) - an inhibitor of BCL2, BCL2L1 (BCL-xL), and BCL-W (Fig. 2.2C, D). In summary, the ability of the 4E-BP1 mutant to phenocopy the effect of TOR-KI demonstrates that targeting the 4E-

BP1/eIF4E arm of mTORC1 signaling is a promising approach for sensitization of DLBCL cells to venetoclax treatment.

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Figure 2.2: Constitutively active 4E-BP1 mutant sensitizes lymphoma cells to venetoclax (ABT-199) and navitoclax (ABT-263) similar to TOR-KI combination. (A,C) Western blot analysis of OCI-LY1 cells expressing rtTA and various TRE-linked constructs, treated with vehicle or 1 µg/ml doxycycline. EV = empty vector; WT = wild-type 4E-BP1. Mut = 4E-BP1-5A mutant. Beta actin levels serve as a loading control. (C) Cells were doxycycline treated with or without MLN0128 (TOR-KI) or BEZ235 (dual PI3K/mTOR inhibitor) for 16 hours. We performed western blot analysis for mTOR main substrates, with total AKT serving as a loading control. (B,D) OCI-LY1 derivatives described in panel A were treated with doxycycline, with (+) or without (-) MLN0128 100 nM, and titrated amounts of venetoclax (C) or navitoclax (D). Viability was measured using Annexin V and propidium iodide (PI) staining and the venetoclax IC50 was compared across conditions. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. n=4 *p<0.05; **p<0.01; ****p<0.001, Paired and unpaired t-tests vs vector, P value has been adjusted for multiple comparisons. In the absence of DOX, all three cell lines had similar venetoclax sensitivity (data not shown). Panels C and D were obtained by Dr. J. Scott Lee.

SBI-756 prevents eIF4E:eIF4G1 association and reduces cap-dependent translation in lymphoma cells

Next, we took a chemical approach to disrupting eIF4F. Previously, the Ronai lab showed that the cell-permeable compound SBI-756 binds to eIF4G1 and disrupts formation of the

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mRNA cap-binding complex in melanoma cells and in fibroblasts 19. To assess the effect of SBI-

756 on eIF4F formation in lymphoma cells, we used a proximity ligation assay (PLA) to quantitate the interaction of eIF4E and eIF4G1 in situ. As expected, treatment of OCI-LY1 cells with the TOR-KI compound MLN0128 suppressed eIF4E:eIF4G1 association whereas rapamycin, a weak inhibitor of 4E-BP1 phosphorylation 10,33, had no significant effect (Fig.

2.3A, B). Moreover, SBI-756 reduced eIF4E:eIF4G1 interaction (Fig. 2.3A, B). Similar results were observed in OCI-LY8 cells (Fig. 2.3C, D). Quantification of eIF4E:eIF4G1 interaction indicated a significant reduction by 500 nM SBI-756 in OCI-LY1 (76%, Fig. 2.3B) and 250 nM in OCI-LY8 (83%, Fig. 2.3D).

Figure 2.3: SBI-756 prevents eIF4E-eIF4G interaction. OCI-LY1 (A) and OCI-LY8 (C) cells were tested for eIF4E: eIF4G1 association via Proximity Ligation Assay (PLA)142. Cells were treated for 4 hours with either vehicle (DMSO), MLN0128 100 nM, Rapamycin 10 nM or increasing concentrations of SBI-756 (250-750 nM). Scale bar = 33µm. Representative images of at least three fields are shown. (B,D) Quantification of eIF4E:eIF4G1 interaction for each treatment. The signal indicating eIF4E:eIF4G interaction was measured from the entire field for each treatment (single channels acquired) and was normalized to the number of cells imaged (DAPI staining indicating cells/image). Relative ratios are graphed. * p<0.05; ** p< 0.01. n = 3 or 4, as indicated. Paired one-sample t-test.

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We used dual-luciferase reporter assays to test the ability of TOR-KI and SBI-756 to

reduce cap-dependent and IRES-dependent translation. Following 16 hours of treatment of OCI-

LY1 (Fig. 2.4A) and the MCL cell line Mino1 (Fig. 2.4B), SBI-756 in the range of 100 – 500 nM

selectively reduced cap-dependent luciferase expression. Similar results were observed in two

additional DLBCL lines (OCI-LY8, SU-DHL6) and in the Maver1 MCL line (Fig. 2.4C-E).

Likewise, MLN0128 significantly reduced accumulation of cap-dependent luciferase (Fig. 2.4).

Figure 2.4: SBI-756 treatment suppresses cap-dependent translation. OCI-LY1 (A), Mino1 (B), OCI-LY8 (C), MAVER1 (D), or SU-DHL6 (E) cells were electroporated to introduce the dual-luciferase reporter. This reporter contains a 5’ cap-dependent untranslated region (5’-UTR) was conjoined to a Renilla (Renilla reniformis) luciferase reporter, while the Internal Ribosomal Entry Site (IRES) was conjoined to a firefly (Photinus pyralis) luciferase reporter92,93. Cells were treated for 16 hours with vehicle (DMSO), MLN0128 100 nM, or increasing concentrations of SBI-756 (250-750 nM). The ratio of Renilla/firefly luciferases was calculated for each of the conditions, indicating the relative cap-dependent translation. *p<0.05, **p<0.01, ***p<0.005. One-sample t-test vs. DMSO control. n = 3.

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SBI-756 does not change mTOR substrate phosphorylation

A potential advantage of selective eIF4F targeting is that this approach should preserve activity of mTOR, reducing on-target toxicities associated with mTOR inhibition. Compared to the TOR-KI compound Torin-1, SBI-756 (1 µM or lower concentration) did not inhibit phosphorylation of mTORC1 or mTORC2 substrates in melanoma cells 19. To test whether SBI-

Figure 2.5: SBI-756 does not change mTOR substrate phosphorylation. OCI-LY1, OCI-LY8 or VAL DLBCL cells were treated with vehicle (DMSO), MLN0128, rapamycin or increasing SBI-756 concentration. Phosphorylation of canonical mTORC1 and mTORC2 substrates was analyzed by western blot analysis (A, C) and quantified relative to vehicle treated cells (B, D). The results were quantified using ImageJ by a blinded observer. ***p<0.005, ****p<0.001. One-sample t-test vs. normalized control, n = 3.

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756 alters mTOR activity in lymphoma cells, we measured mTORC1 and mTORC2 substrate phosphorylation. As expected, MLN0128 significantly reduced phosphorylation of both mTORC1 (p-S6, p-4E-BP1) and mTORC2 (AKT) substrates, whereas rapamycin reduced only p-S6 (Fig. 2.5A, B). In contrast, treatment with SBI-756 did not alter phosphorylation of any mTOR substrates tested, indicating that the mTOR signaling pathway was not altered by SBI-

756 treatment (Fig. 2.5A, B). Similar results were obtained in other DLBCL cell lines (Fig. 2.5C,

D). These results support the conclusion that SBI-756 directly disrupts the eIF4F complex without altering activity of mTORC1 or mTORC2.

SBI-756 synergizes with venetoclax to increase apoptosis in lymphoma cells

To test the ability of SBI-756 to promote apoptosis and sensitize lymphoma cells to venetoclax, we evaluated seven GCB-DLBCL and five MCL cell lines (Fig. 2.6 and 2.7). We treated the cells with titrated concentrations of venetoclax as a single agent, or in combination with either MLN0128 or SBI-756 and performed viability assays. Eight of the cell lines tested had reduced viability following 48hr treatment with venetoclax as a single agent. Ten cell lines showed reduced viability following SBI-756 treatment as a single agent. In five of the SBI-756- sensitive DLBCL lines (OCI-LY1, OCI-LY8, OCI-LY18, SU-DHL-4, SU-DHL-6) and four of the MCL lines (Mino, Jeko1, MAVER-1, CCMCL-1), the combination of SBI-756 and venetoclax caused more cell death than individual agents (Fig. 2.6A, B; 2.7A, B). In comparison,

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MLN0128 only sensitized to venetoclax in one cell line (OCI-LY1) despite effectively

suppressing mTOR signaling outputs in other cell lines such as OCI-LY8 (Fig. 2.5C).

Figure 2.6: Treatment with SBI-756 sensitizes DLBCL and MCL cells to venetoclax combinational treatment. Viability of (D) OCI-LY1 and (E) Mino1 cells treated for 48 hours with increasing venetoclax concentrations in combination with vehicle (DMSO) control or various inhibitors as indicated. Viability was assessed using Annexin V and PI staining. *p<0.05; **p<0.01; ****p<0.001. We performed independent t-tests (unpaired t-tests) and compared each treatment group to vehicle treated group. We also performed an adjustment for multiple comparisons for each t- test performed. We calculated IC50 values for each cell line tested based of the viability assays performed: (F) OCI- LY1 IC50s - venetoclax 23.6 nM, SBI-756 209.7 nM; (G) Mino1 IC50s - venetoclax 749.9 nM, SBI-756 340.3 nM. Isobologram plots were graphed based on Chou-Talalay method for synergy calculation (combination index)11 using median effect method for cell lines treated for 48 hours with combinations of SBI-756 and venetoclax at fixed ratios.

Supporting an apoptotic mechanism, the combination of SBI-756 with venetoclax

induced caspase-dependent death, as demonstrated by rescue of viability in cells co-treated with

the pan-caspase inhibitor QVD-OPH (Fig. 2.8A). Moreover, venetoclax treatment with or

without SBI-756 led to cleavage of caspase-3 and PARP (Fig. 2.8B). Treatment with SBI-756

alone did not induce cleavage of caspase-3 or PARP, while venetoclax by itself did (Fig. 2.8B).

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Figure 2.7: Treatment with SBI-756 sensitizes DLBCL and MCL cells to venetoclax combinational treatment. DLBCL cell lines (A) or MCL cell lines (B) were treated for 48 hours with increasing venetoclax concentrations in combination with vehicle control or inhibitors as indicated. We assessed viability using annexin V and PI staining, compare each treatment group to vehicle treated group (unpaired t-tests). *p<0.05; **p< 0.01; ****p<0.001, adjusted for multiple comparisons. (C) We calculated IC50 values for each cell line tested based on the viability assays performed. Isobologram plots were graphed based on Chou-Talalay method for synergy calculation (combination index)11 using median effect method for cell lines treated for 48 hours with combinations of SBI-756 and venetoclax at fixed ratios. GCB-DLBCL: OCI-LY8, SU-DHL-6, OCI-LY18, and MCL: MAVER-1 cell lines were tested. (D) We treated OCI-LY1 parental, OCI-LY1 that were selected for SBI-756 resistance or OCI-LY7 cells for 4 hours with either DMSO (vehicle) control or SBI-756 250 nM. The cells were fixed and eIF4E: eIF4G1 association was analyzed using PLA, as described in figure 1A, B. We quantified the results and normalize to vehicle treatment for each of the cell lines. * p<0.05; ** p< 0.01. One-sample t-test.

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Next, we chose sensitive DLBCL and MCL cells to further evaluate synergy between

venetoclax and SBI-756 (Fig. 2.6C, D and Fig. 2.7C). We measured viability in cells treated for

Figure 2.8: SBI-756 in combination with venetoclax induces apoptosis. (A) OCI-LY1 and OCI-LY8 cells were treated with vehicle (DMSO), MLN0128, venetoclax or increasing SBI-756 concentration for 16 hours. We also tested combinational treatments of venetoclax with MLN0128 or together with SBI-756. Cleavage of PARP or caspase 3 were evaluated as indications of apoptosis induction via western blot analysis. Beta actin served as a loading control. (B) OCI-LY1 or OCI-LY8 cells were treated for 48 hours with vehicle (DMSO) control or various inhibitors as indicated. Viability of the cells was tested in the presence or absence of a pan caspase inhibitor (Q-VD-OPh hydrate, 20µM). Viability was assessed using Annexin V and PI staining. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests comparing each treatment group to vehicle treated group, and adjusted for multiple comparisons.

48hr with fixed ratios of venetoclax and SBI-756 and assessed synergy using the Chou-Talalay

method 27. Indeed, SBI-756 synergized with venetoclax (combination index < 1) in both OCI-

LY1 (DLBCL) and Mino1 (MCL) cells (Fig. 2.6C, D). Furthermore, SBI-756 was found to

synergize with venetoclax in four more cell lines tested (Fig. 2.7C). SBI-756 did not reduce

viability or sensitize to venetoclax in the OCI-LY7 DLBCL line and had minimal effect in a

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subline of OCI-LY1 cells that we selected for resistance to SBI-756. In both these cell lines, SBI-

756 treatment did not prevent the eIF4E:eIF4G1 interaction measured by PLA (Fig. 2.7D), which suggests that eIF4E:eIF4G1 interaction retention is relevant for development of resistance.

Various mechanisms can result in retention of the interaction: active pumping of the compound outside of the cells, mutations occurring in the molecular targets, and activation of the eIF4F complex via isomers that compensate for the interaction suppression.

Lymphoma cells lacking 4EBP1 are resistant to TOR-KI yet remain sensitive to SBI-756

Many cancer cells exhibit a reduction of 4E-BP expression 34,35 or increase in eIF4E expression 36,37, enabling cap-dependent translation even following mTORC1 inhibition. Indeed, the eIF4E/4E-BP ratio can predict efficacy of mTOR targeted therapies 38. Previously we reported that SBI-756 can fully suppress proliferation in 4E-BP1/4E-BP2 double knockout fibroblasts that are partially resistant to the TOR-KI compound Torin1 19. To determine whether

SBI-756-induced DLBCL death is 4E-BP-dependent, we used CRISPR/Cas9 genome editing to generate clones of OCI-LY1 cells lacking 4E-BP1 (S6). In OCI-LY1 cells expressing Cas9 and empty sgRNA vector, both MLN0128 and SBI-756 sensitized to venetoclax (Fig. 2.9B, C;

2.10A, B) as observed previously (Fig. 2.6A). Notably, OCI-LY1 cells lacking 4E-BP1 were completely resistant to MLN0128 yet remained sensitive to SBI-756 alone or in combination

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Figure 2.9: 4E-BP1 KO clones are insensitive to TOR-KI treatment, yet remain sensitive to SBI-756 treatment. (A) We performed a western blot analysis to validate OCI-LY1 CRISPR/ Cas9 clones produced. The cells were lysed and ran on an SDS- PAGE gel, followed by probing for the targets indicted. CRISPR/ Cas9 clones were produced by transfection of OCI-LY1 cells stably expressing Cas9 system with guide RNAs. Clones were isolated that carried an empty vector; or sgRNAs specific for 4E- BP1 (4E-BP1 KO). For subsequent experiments we used clones with validated loss of 4E-BP1 expression (sgRNA 1-1, 1-2, 2-1). (B-C) OCI-LY1 cells stably expressing Cas9 were transfected with guide RNAs. Clones were isolated that carried an empty vector (EV); or sgRNAs specific for 4E-BP1 (4E-BP1 KO). For instance: 4E-BP1 KO sgRNA 1#2 is the same clone validated in panel (A) and named “4EBP1 sgRNA 1-2”. Cells were treated for 48 hours with titrated amounts of venetoclax without (vehicle) or with MLN0128 (B) or SBI-756 (C). Viability was assessed using annexin V + PI staining. *p<0.05, ns = not significant. Two-way ANOVA vs. control (EV). with venetoclax (Fig. 2.9B, C; 2.10C, D). Similarly, SBI-756 reduced eIF4E:eIF4G1 interaction among all cells, whereas treatment with MLN0128 reduced interaction only in control cells containing 4E-BP1 (Fig. 2.10E, F). Our findings indicate that in cells lacking 4E-BP1 expression, SBI-756 retains its effect and prevents eIF4F formation, thus sensitizing those cells to BCL2 inhibition.

To further support this conclusion, we used VAL cells, a DLBCL line lacking 4E-BP1 34

(Fig. 2.5C). Consistent with previous observations 34, MLN0128 at concentrations up to 3µM did

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not affect VAL cell viability (Fig. 2.10G) or eIF4E:eIF4G interaction (Fig. 2.10H). In contrast,

SBI-756 reduced viability of VAL cells (Fig. 2.10G) and disrupted the eIF4E:eIF4G interaction

(Fig. 2.10H). VAL cells were completely insensitive to venetoclax, with or without SBI-756, which might indicate reliance on other pro-survival proteins than BCL2 (e.g. MCL-1).

Nevertheless, these data confirm that prevention of eIF4F complex formation is achievable using

SBI-756, even among cells lacking 4E-BP1 (thus insensitive to TOR-KI).

Figure 2.10: Lymphoma cell lacking 4EBP1 are resistant to TOR-KI yet are sensitive to SBI-756 treatment. OCI-LY1 cells stably expressing Cas9 system were transfected with guide RNAs. Clones were isolated that carried an empty vector (panels A, B, E); or sgRNAs specific for 4E-BP1 (4E-BP1 KO) (panels C, D, F). Parental OCI-LY1 cells gave comparable results to EV transfected OCI-LY1 (data not shown). (A – D). Cells were treated for 48 hours with titrated amounts of venetoclax without (vehicle) or with MLN0128 (A, C) or SBI-756 (B, D). Viability was assessed using annexin V and PI staining. n=4. *p<0.05, ***p<0.01, ****p<0.005, ns = not significant. Statistics were done using Two-way ANOVA. (E, F) Dual-luciferase assays were performed to measure relative cap-dependent translation as in Figure 1C. (G) Viability assay of VAL cells (naturally lacking 4E-BP16) following 48 hours of treatment with venetoclax, MLN0128 or SBI-756 (all within 100-1000 nM range). (H) PLA comparing OCI-LY1 to VAL cells (naturally lack 4EBP16) - 4 hours treatment. Fields imaged and quantified by blinded observer. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. n=3. *p<0.05, **p<0.01, ***p<0.005, ****p<0.001, ns= not significant. Paired one-sample t-test vs. control.

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SBI-756 is effective and well-tolerated in vivo

We assessed whether sensitization of DLBCL to venetoclax treatment by co-targeting eIF4F could be recapitulated in vivo. We injected NSG mice with OCI-LY1 (s.c.) and once palpable tumors were established, treated with vehicle, venetoclax, SBI-756 or their combination for five consecutive days (Fig. 2.11A). There was no significant change in body weight among the different groups (Fig. 2.12A), indicating that the treatments were well tolerated. Both

Figure 2.11: SBI-756 sensitizes to venetoclax treatment in vivo. (A) NOD-scid-IL2-Rgamma-/- (NSG) immunodeficient mice were injected with 1x10e7 OCI-LY1 cells s.c. xenograft (7-8 mice per group). Once palpable tumors were established (>110mm3), treated with 0.1% DMSO vehicle (i.p. and p.o.), SBI-756 25 mg/kg (i.p.), venetoclax 75 mg/kg (p.o.), or combination (i.p. and p.o.) for five consecutive days (Fig. 3). The tumor weight, single cell extractions and pharmacodynamics were monitored on the day of sacrifice, while mouse body weight and tumor volume were monitored throughout the trial. (B) Tumor volume was calculated each day using the formula: v = 4/3πr1r2r3 and presented as mean +/- SEM. *p<0.05, **p<0.01, ***P<0.005, ****p<0.001, ANOVA, P value has been adjusted for multiple comparisons (using Tukey’s adjustment for multiple comparisons). (C) eIF4E:eIF4G1 association measured by PLA assay on single cells isolated from tumors. SBI-756 treatment (alone/combination) reduced association of eIF4E:eIF4G1. scale bar = 100µm. (D) Quantification of eIF4E:eIF4G1 interaction for each treatment group. Each point represent one mouse in the group that was treated for 5 consecutive days. The signal indicating eIF4E:eIF4G interaction was measured from the entire field for each treatment (single channels acquired) and was normalized to the number of cells imaged (DAPI staining indicating cells/image). Relative ratios are graphed. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. * p<0.05; ** p< 0.01, ANOVA, P value has been adjusted for multiple comparisons.

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venetoclax and SBI-756 significantly slowed tumor growth when administered as single agents

(Fig. 2.11B, 2.12B, C). Notably, venetoclax and SBI-756 combination caused tumor regression and significantly reduced tumor volume (7/7 mice) when compared to SBI-756 (1/8 mice) or venetoclax (2/8 mice) as single agents or vehicle alone (0/8 mice). Together these results indicate that a synergistic relationship between venetoclax and SBI-756 occurs not only in vitro but also in vivo.

SBI-756 has a pharmacodynamic effect in vivo

To assess whether SBI-756 treatment prevents eIF4E:eIF4G1 interaction in vivo, lymphoma tumors excised from euthanized mice were dissociated into single cells and subjected to PLA. Analysis of the samples obtained showed a reduction in eIF4E:eIF4G1 interaction among tumors treated with SBI-756 as a single agent or in combination with venetoclax, compared to vehicle or venetoclax alone (Fig. 2.11C, D). Additionally, we performed intracellular staining to measure phosphorylation levels of mTOR substrates, S6 kinase and 4E-

BP1, among the samples extracted from the tumors to test for alteration in mTOR kinase activity.

No significant changes were observed in mTOR substrate phosphorylation in mice treated with

SBI-756 and/or venetoclax in vivo (Fig. 2.12D, E). These results suggest that SBI-756 potentiates venetoclax efficacy in vivo by preventing eIF4E:eIF4G1 interaction without affecting mTOR activity.

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Figure 2.12: Venetoclax and SBI-756 combination is tolerable and retains mTOR functionality, while reduces tumor volume in vivo. (A) Body weight of each mouse was measured daily. Average body weight for each treatment group is presented as mean +/- SEM. *p<0.05, **p<0.01, ***P<0.005, ****p<0.001, ANOVA, P value has been adjusted for multiple comparisons (using Tukey’s adjustment for multiple comparisons). (B) The weight of each tumor was measured at the day of sacrifice (following five days of treatment) and plotted as individual measurements with the mean (horizontal line). *p<0.05, **p<0.01, ***P<0.005, ****p<0.001, ANOVA, P value has been adjusted for multiple comparisons (using Tukey’s adjustment for multiple comparisons). (C) Tumor volume was measured at the day of sacrifice and plotted as individual measurements with the mean (horizontal line). *p<0.05, **p<0.01, ***P<0.005, ****p<0.001, ANOVA, P value has been adjusted for multiple comparisons (using Tukey’s adjustment for multiple comparisons). (D) and (E) Tumors were excised from euthanized mice and dissociated into single cells. Cells were fixed and immune-stained for canonical mTOR substrates: phosphorylated S6 and phosphorylated 4E-BP1. Phosphorylation levels were evaluated using flow cytometry and quantification of geometric mean (G-mean). (D) Controls consisted of cell lines treated with the inhibitors indicated and tested for phosphorylation of targets mentioned. (E) In vivo samples consisted of cells excised from tumors from each treatment group, and immune-stained for the same targets.

SBI-756 has both direct and indirect effects on mRNA translation

Chemical inhibition of mTORC1 or eIF4F in cancer cells selectively suppresses

translation of mRNAs with specific features in the 5′ untranslated region (UTR) 39. These eIF4F-

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sensitive mRNAs include several that encode pro-survival proteins, including MCL-1, BCL-xL

(B-cell lymphoma-extra-large) and survivin 18. To determine whether SBI-756 affects expression of these factors in DLBCL cells, we measured expression of candidate proteins by Western blot.

In cells growing asynchronously, 4hr treatment with MLN0128 or SBI-756 did not change expression of these candidate proteins (Fig. 2.13). In a previous study we found that serum starvation of DLBCL cells, followed by re-addition of serum without or with mTOR inhibitors, revealed consistent changes in protein expression 34. Taking this approach, we observed modest and variably reduced expression (approximately 2-fold) of MCL-1, BCL-xL and survivin among

MLN0128 and SBI-756 treated cells (Fig. 2.13A, B). Expression of eIF4E or eIF4G1 were also reduced following SBI-756 or MLN0128 treatment (Fig. 2.13A, B). For each of these targets

(MCL-1, BCL-XL, survivin, eIF4E or eIF4G1), the abundance of mRNA was not significantly changed in cells treated with SBI-756 or MLN0128 (with the exception of survivin transcripts elevated in cells treated with 500 nM SBI-756) (Fig. 2.13C).

To gain a broad, unbiased view of how SBI-756 affects mRNA translation efficiency, we treated OCI-LY1 cells with vehicle (DMSO) or SBI-756 (250 nM) for 4hr, and isolated RNA from heavy and light polysome fractions, as well as total cellular RNA. The 4hr treatment did not cause detectable changes in RNA distribution from heavy to light polysomes (Fig. 2.14A) and did not change rates of overall protein synthesis (Fig. 2.14B). However, comparison of mRNAs associated with heavy polysomes to total mRNAs showed that SBI-756 selectively changed the translation efficiency of 538 mRNAs; 13 showed differences in both translation and transcription

(Fig. 2.14C, D). Only 24 genes showed changes in transcription alone (Fig. 2.14C, D), supporting the conclusion that SBI-756 is an on-target and selective inhibitor of mRNA translation.

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Figure 2.13: SBI-756 induces a decrease in MCL-1, BCL-xL, survivin, eIF4E and eIF4G. (A, B) OCI-LY1 cells were starved for 24 hours in media containing 1% FBS, then restored to complete media (10% FBS) in the presence of vehicle (DMSO) or the indicated concentrations of MLN0128 or SBI756 for 4 hours. Lysates were prepared and subjected to western blot analysis with antibodies to the proteins shown on the left. Band intensities were determined by ImageJ and normalized to the loading control (GAPDH). Panel A shows data from a representative Western blot experiment. Panel B shows quantitation over multiple experiments. *p<0.05, **p<0.01, ****p<0.001. One-sample t-test vs. normalized control. (C) OCI-LY1 cells were serum starved for 24 hours, followed by 4 hours of treatment with the inhibitors indicated. Next, we isolated RNA using Trizol-LS, and we synthesized cDNA by reverse transcription. Using unique primer sets for each target, we examined transcription levels of candidates among the samples isolated via real-time PCR. Based on the CT values obtained, we calculated ΔΔCT values that reflected the expression levels of the targets. Two-way ANOVA vs. control.

Of the 538 mRNAs with selective change in translation, the majority (385) had reduced

translation efficiency (Fig. 2.14) (Table 2.3). Gene ontology (GO) analysis showed a highly

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significant enrichment for genes involved in mRNA translation. The most enriched biological processes for the downregulated genes (Fig. 2.14E top) include translation initiation, translation, rRNA processing, and ribosomal small subunit assembly. Likewise, top molecular functions associated with the down-regulated genes include structural constituent of the ribosome, RNA binding, and poly(A) RNA binding (Fig. 2.14F). Among the translationally downregulated biological processes were negative regulators of apoptosis. This family contained 10 genes

(Table 2.4) yet did not include the candidates mentioned above (MCL-1, BCL-xL, survivin).

Among the translationally upregulated mRNAs, only one was found to contain an IRES motif

(TP53) (Fig. 2.14).

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Figure 2.14: Selective reduction of mRNA translation following 4 hours SBI-756 treatment. (A) Polysome traces of OCI-LY1 cells treated with SBI-756 or without (vehicle) for 4hr. Results are representative of three independent samples. (B) Quantification of puromycin incorporation in OCI-LY1 cells treated with vehicle, MLN0128 (30 nM), rapamycin (10 nM), or SBI-756 250 nM for 4 hours with addition of puromycin to the media for the last 20 minutes. (C) Genome-wide transcription and translation mRNA profiling of 25 million cells with or without SBI-756 treatment. Results are from two independent studies. Total mRNA and purified fractions containing four or more bound ribosomes were sequenced using Illumina HiSeq 4 single read. Volcano plots represent differences in transcription (left) and translation (right). Transcription and translation parameters were p ≤ 0.05 and -1.0 ≤ log2 ≥ 1.0. Blue dots identify mRNAs significantly changed in abundance, and red dots identify mRNAs not significantly changed. Statistical analysis was performed using the limma R package via RIVET (Ernlund AW et al, BMC Genomics 2018). (D) Venn diagram comparing significant differences in transcription and translation. (E) The top molecular functions of mRNAs significantly down (top) or up-regulated (bottom) in translation. (F) The top cellular components of mRNAs significantly down (top) or up-regulated (bottom) in translation.

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The dramatic reduction in translation of mRNAs encoding ribosomal proteins and regulators at 4hr suggested that SBI-756 might indirectly reduce overall translation efficiency and total protein synthesis rates over time (measured by puromycin incorporation assay). Indeed,

16hr treatment with SBI-756 reduced rates of total protein synthesis in parental OCI-LY1 cells

(Fig. 2.15A) but not in the SBI-756-resistant subline of OCI-LY1 cells (Fig. 2.15B). MLN0128 or SBI-756 treatment did not reduce protein synthesis in the OCI-LY7 cell line (Fig. 2.15C), in which these agents did not have cytotoxic activity (Fig. 2.6A). Nevertheless, SBI-756 did reduce protein synthesis in OCI-LY8 and SU-DHL-6 cell lines (Fig. 2.15D, E). This reduced protein synthesis could account for the sensitization to venetoclax observed among these cells (Fig.

2.7A). Considering that SBI-756 reduced protein synthesis in OCI-LY1 cells at 16hr but not 4hr, we assessed cell survival at these time points as well as 24hr and 48hr. Sensitization to venetoclax cytotoxicity was first evident 16 hours following SBI-756 treatment (Fig. 2.15F), and was significantly greater than combination with TOR-KI.

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Figure 2.15: SBI-756 treatment reduces protein synthesis following 16 hours of treatment. We treated cells with vehicle or inhibitors as in Figure 4C-F and measured puromycin incorporation after 16hr. (A) parental OCI-LY1 cells; (B) OCI-LY1 that were induced to resistance against SBI-756 (1 µM); (C) OCI- LY7; (D) OCI-LY8; (E) SU-DHL-6cells. *p<0.05, **p<0.01. One-sample t-test vs. DMSO control. n = 3. (F) OCI-LY1 cells were treated with venetoclax 10 nM, MLN0128 100 nM, SBI-756 250 nM as single agents or in combination, as indicated. We have assessed their viability after 4, 16, 24, or 48 hours of treatment using annexing V and PI staining and flow cytometry analysis. *p<0.05, **p<0.01. One-way ANOVA, compared to venetoclax as single agent.

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SBI-756 is not cytotoxic to human CD4+T cells, CD8+ T cells, NK cells or monocytes

Lastly, we evaluated whether SBI-756 cytotoxic effects are selective for transformed lymphoma cells versus normal lymphocytes. We cultured PBMCs from healthy donors for 48 hours with SBI-756 or MLN0128 alone, or in combination with venetoclax. Compared to vehicle treated cells, we observed a significant reduction in cell viability only among CD19+ B cells following MLN0128 or SBI-756 treatment (Fig. 2.16A, 2.17A). Venetoclax alone greatly reduced viability of B cells, with partial effects on CD4+ and CD8+ T cells and natural killer cells as published before 40. However, there was no further effect when venetoclax was combined with either MLN0128 or SBI-756 (Fig. 2.16A). We also tested purified lymphocytes from mice, which are more readily available in quantities needed for correlation of functional and biochemical readouts. Similarly, MLN0128 and SBI-756 were selectively cytotoxic to mouse B cells but not mouse T cells cultured in supportive cytokines (Fig. 2.16B). The cytotoxic effect of

SBI-756 in B cells at 48hr (Fig. 2.16B) correlated with suppression of protein synthesis selectively in B cells, measured after 16hr treatment (Fig. 2.16C).

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Figure 2.16: SBI-756 is not cytotoxic to human CD4+T cells, CD8+ T cells, NK cells or monocytes. (A) Peripheral blood mononuclear cells (PBMCs) were obtained from healthy blood donors and were isolated as described previously116. PBMCs (mean +/- SD, n=3) were cultured for 48 hours with each agent MLN0128 (30 nM), SBI-756 (250 nM) alone or in combination with 100 nM venetoclax. One-sample t-test vs. DMSO control. n = 3. *p<0.05, **p<0.01, ***p<0.005 vs. DMSO control. Leukocyte subsets were distinguished by surface markers using flow cytometry). (B) Mouse splenocytes were isolated from C57BL/J mice. We performed B cell or T cell purification using STEMCELL Mouse B cell or T cell isolation kit, respectively. Next, we treated the cells as indicated for 48 hours, and their viability was measured using Annexin V and PI. *p<0.05, **p<0.01. One-sample t-test vs. control. n = 3. (C) Puromycin incorporation in mouse B cells (B220+) and T-cell (CD3+) after 16h of treatment with MLN0128 30nM and SBI-756 250nM. Data are showed as percentage of puromycin incorporation reduction vs vehicle. c vs. DMSO control. n=4 **p<0.01.

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Discussion

Venetoclax is a BCL2-specific inhibitor whose use is expanding in hematologic malignancies 20,21. However, blood cancer cells frequently engage distinct mechanisms that can maintain survival following BCL2 inhibition. Therefore, responses to venetoclax are broader and more durable when the drug is combined with other agents that promote cell death through distinct mechanisms 41. In DLBCL, venetoclax combined with the standard of care (R-CHOP) is more effective than venetoclax monotherapy and components of the CHOP regimen can increase sensitivity to venetoclax in vitro 42,43. Incorporation of additional targeted agents has potential to further improve responses. Here, we report experiments showing great potential for sensitization of NHL cells to venetoclax via combination with SBI-756, a potent inhibitor of cap-dependent translation that is active in cells in the 100–500 nM range. SBI-756 synergized with venetoclax to induce apoptosis in NHL cells while not interfering with mTOR signaling. SBI-756 prevented eIF4E:eIF4G1 interaction among sensitive cells (OCI-LY1 and -LY8), but not among resistant cells (OCI-LY7 or OCI-LY1 induced to be resistant to SBI-756). After 4 hours of treatment,

SBI-756 also reduced translation efficiency of mRNAs encoding ribosomal proteins and rRNA processing factors. Consistent with reduced ribosome biogenesis, SBI-756 reduced overall protein synthesis after 16hr of treatment. Additionally, in DLBCL cell lines lacking 4E-BPs

(naturally or genetically edited), SBI-756 retained ability to inhibit eIF4F formation and sensitize to venetoclax, whereas the TOR-KI compound MLN0128 lacked activity in this setting. SBI-756 synergy with venetoclax in vitro was recapitulated in vivo, with the combination reducing tumor progression that correlated with prevention of eIF4E-eIF4G1 interaction. Treatment with SBI-

756 was tolerable in mice, and the compound selectively reduced survival of B cells in cultures of human PBMCs and murine lymphocytes. Together, these findings urge further investigation

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of eIF4F disruption for sensitization to venetoclax and possibly other BH3 mimetics. In this regard, an initial experiment to sensitize DLBCL cell lines to a MCL-1 inhibitor (S63845) using

SBI-756 (Fig. 2.17B) yielded a similar response as the venetoclax combination.

Figure 2.17: B lymphocytes are more sensitive to eIF4F targeting than other PBMCs. (A) Peripheral blood mononuclear cells (PBMCs) were obtained from healthy blood donors and were isolated as described previously116. PBMCs (mean +/- SD, n=3) were cultured for 48 hours with MLN0128 (30 nM) or SBI-756 (250 nM). One-sample t- test vs. DMSO control. n = 3. *p<0.05, **p<0.01, ***p<0.005 vs. DMSO control. Leukocyte subsets were distinguished by surface markers using flow cytometry). (B) OCI-LY1 cells were treated for 48 hours with increasing S63845 (MCL-1 inhibitor) concentrations in combination with vehicle (DMSO) control or various inhibitors as indicated. Cell lines tested are indicated in the title of each graph. Viability was assessed using Annexin V and PI staining. We performed unpaired t-tests and compared each treatment group to vehicle treated group. *p<0.05; **p<0.01; ****p<0.001, adjusted for multiple comparisons.

PI3K/mTOR signaling pathway activation has been correlated with poor prognosis and resistance to chemotherapy 3. Thus, this pathway remains an investigational target for cancer

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therapeutics, including rapalogs or TOR-KIs such as MLN0128/TAK-228 11. However, rapalogs have limited anti-cancer activity and the therapeutic window for TOR-KIs remains to be established. Targeting individual pathways downstream of mTOR might hold the key to developing better tolerated and more effective anti-cancer interventions. One process of particular interest is cap-dependent mRNA translation controlled by eIF4F 4–6. Genetic inhibition of eIF4F via inducible expression of the 4E-BP1 mutant sensitized to venetoclax in OCI-LY1 cells, an effect enhanced by the TOR-KI compound MLN0128 that re-activates endogenous 4E-

BP1. Our studies of the eIF4G-binding compound SBI-756 in human lymphoma cell line models provide proof-of-concept for eIF4F disruption by a small molecule at sub-µM concentration.

Further studies using more selective inhibitors of eIF4G1, or specific knockouts of eIF4G1 could clarify the importance of this component in lymphomagenesis or lymphocyte differentiation. In a distinct approach, rocaglate compounds targeting the eIF4A helicase can also enhance venetoclax cytotoxicity in lymphoma cells 44.

In most of the DLBCL and MCL cell lines tested, 48hr treatment with SBI-756 alone had cytotoxic effects as measured by staining with Annexin V and propidium iodide. In OCI-LY1 and OCI-LY8 cells, this cytotoxic effect was prevented by co-incubation with a pan-caspase inhibitor. However, SBI-756 alone did not cause detectable cleavage of caspase 3 or PARP after

16hr, a time point where these markers were readily induced by venetoclax. This finding was consistent with BH3 profiling analysis that we have performed, which indicated that SBI-756 does not prime the cells toward apoptosis by itself (data not shown). It is possible that SBI-756 treatment alone triggers apoptosis at a later time point. Of note, two of the sensitive cell lines

(OCI-LY1 and OCI-LY8) express mutant p53 45 suggesting that the mechanism of apoptosis is p53-independent.

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Notably, the data suggest that SBI-756 is not cytotoxic to essential cellular mediators of immune function and immunotherapy efficacy (T cells and NK cells). A potential advantage for tolerability is that SBI-756 treatment (at concentrations of up to 500 nM) does not interfere with mTOR substrate phosphorylation while disrupting eIF4F complex assembly downstream of mTORC1. We did observe that higher concentrations of SBI-756 (>500 nM) do cause inhibition of the mTOR pathway; thus, future efforts should aim to optimize the selectivity of SBI-756 and similar agents. Another advantage of SBI-756 compared to TOR-KI treatment is its ability to suppress cap-dependent translation among cells lacking 4E-BP1, a finding relevant to tumors with reduced ratio of 4E-BPs to eIF4E. We used cells that naturally lack 4E-BP1 34 or were genome edited to lack 4E-BP1 to show that these cells remained sensitive to SBI-756 yet lacked

TOR-KI sensitivity. Further experiments are needed to determine whether cells with high eIF4E or eIF4G1 retain sensitivity to SBI-756. These results suggest that B lineage cells have a unique dependence on the mTORC1/eIF4F axis for survival.

Polysome profiling showed that SBI-756 treatment in lymphoma cells alters translation efficiency of 538 genes, transcription of 24 genes, while 13 genes are regulated both transcriptionally and translationally. GO analysis of the translationally downregulated genes identified several groups related to mRNA translation, including: structural constituent of the ribosome, ribosomal biogenesis, rRNA binding, and translational elongation (Fig. 2.14).

Together, those functions indicate two main effects of SBI-756 treatment: first, direct suppression of translation efficiency of a key subset of cellular mRNAs; second, indirect inhibition of the translation machinery that is needed to sustain protein synthesis. The two effects together (direct and indirect) reprogram mRNA translation in a way that promotes lymphoma cell death and sensitizes to BCL2 inhibition. Supporting the correlation of protein synthesis

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inhibition and cell death, the OCI-LY7 cell line was resistant to SBI-756 cytotoxicity and did not show reduced protein synthesis rates. Moreover, protein synthesis was not reduced among OCI-

LY1 cells selected for SBI-756 resistance. Interestingly, the selective cytotoxic effect of SBI-756 on B cells versus T cells correlated with suppression of global protein synthesis.

The polysome profiling dataset does not definitively establish acute effects of SBI-756 on translation efficiency of survival factors, such as ones reported previously to be eIF4F- dependent. Western blotting experiments suggested that SBI-756 reduces protein amounts of

MCL-1 and survivin, whose expression is known to be sensitive to changes in cap-dependent translation 46. This reduction of pro-survival factors may block back-up mechanisms that the cells might use to adjust to BCL2 inhibition 47. Another possibility is that the broad reprogramming of translation produces subtle changes that alter the overall balance of pro-survival and pro-apoptotic proteins over time, tipping the balance towards cell death 4,48. Reducing ribosome production using inhibitors of ribosomal DNA transcription likewise promotes lymphoma cell death 49.

Figure 2.18: Components of eIF4F translation initiation machinery complex, and inhibitors. eIF4E mediates the formation of the eIF4F complex on the mRNA cap structure. Formation of eIF4F complex promotes recruitment of the pre-initiation complex, followed by 5′ UTR scanning to reach the start codon AUG and joining of 40S ribosomal subunit.

The central role of mRNA translation in hallmarks of cancer has led to many distinct approaches to target regulatory components of the translation machinery 4–6. Natural products and synthetic small molecules have been identified with various mechanisms including (Fig.

140

2.18): (i) interfering with eIF4E binding to the m7-GTP cap (for example, 4EGI-1 50); (ii) inhibiting MNK kinases that phosphorylate eIF4E (CGP57380 51; eFT508 52); (iii) disrupting the function of eIF4A helicase (Silvestrol 53 and synthetic rocaglates 44,54); (iv) inhibiting translational elongation (homoharringtonine 55). Many of the compounds have low selectivity, weak potency or cell penetrance, poor pharmacological properties or are difficult to synthesize.

In the case of 4EGI-1, activity requires 4E-BP1 expression 50. SBI-756 is a prototype of a novel class that binds to eIF4G and disrupts association of this scaffolding protein with eIF4E, independent of 4E-BP1. Active in cells in the mid-nanomolar range and in mouse models, this compound provides proof of concept for suppressing eIF4F function via blockade of key protein:protein interactions in the complex. Our data indicate that eIF4F-disrupting molecules like SBI-756 have great potential to sensitize lymphoma cells to venetoclax (Fig. 2.19). Another possible interesting combinational therapy that is worth pursing is the combination of MCL-1 inhibitor with eIF4F complex targeting. Indeed, we have begun testing of this combination and observed sensitization of SBI-756 to S63845 (MCL-1) inhibitor (Fig. 2.17B). This may result from reduction in MCL-1 pro-survival factor (and possibly others) due to inhibition of eIF4F complex formation, in addition to MCL-1 inhibition via the MCL-1 inhibitor. MCL-1 is known as a critical pro-survival factor, especially among B lymphocytes. Together with the previous finding that SBI-756 can circumvent resistance to BRAF inhibitors in melanoma19, these results support further combination studies of SBI-756 with other targeted agents.

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Figure 2.19: Model for mechanism of venetoclax sensitization by SBI-756. SBI-756 prevents eIF4E-eIF4G1 interaction and formation of translation initiation complex. venetoclax induces apoptosis by targeting BCL-2, a critical anti-apoptotic protein. (A) Diagram of mTOR signaling pathway and targets of the inhibitors used in this study. (B) Diagram of gene ontology groups whose translation efficiency is reduced 4hr after treatment of lymphoma cells with SBI- 756. Collectively, these selective changes in translation of mRNAs lead over time to reduced protein synthesis rate.

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Translationally down-regulated genes Gene Name Log Fold Change p-value MIR1282 -2.29572 0.00008 PRRT1 -1.56169 0.00025 AC007387.2 -1.97826 0.00071 RP11-499E18.1 -1.70952 0.00075 RP5-1039K5.19 -1.29711 0.00079 CRIP1P2 -1.49096 0.00085 RP11-54O7.10 -1.85293 0.00086 SNHG9 -1.71113 0.00089 RPL18AP16 -1.36988 0.00101 AC253572.1 -1.48522 0.00118 MADCAM1 -1.18364 0.00118 MSX1 -1.84798 0.00123 RP11-346C16.4 -1.41374 0.00139 RP11-345K20.2 -1.35133 0.00154 RP11-304L19.2 -1.33540 0.00156 RPL29P7 -1.64144 0.00159 OR7E55P -1.31295 0.00160 RP4-545L17.11 -1.94442 0.00161 AC016700.6 -1.27815 0.00173 HIST1H2BG -1.12598 0.00202 RP1-101A2.1 -1.16833 0.00215 RPLP0P2 -1.48870 0.00245 RP11-524O24.2 -1.20725 0.00245 CTA-276O3.4 -1.56735 0.00253 RPL39P5 -1.30669 0.00263 TMSB4XP2 -1.29664 0.00265 OSER1-AS1 -1.00591 0.00271 HIST1H2BD -1.64687 0.00272 AC012671.2 -1.43379 0.00272 RPL26 -1.22179 0.00290 RPL5P24 -1.06733 0.00299 RPS4XP7 -1.04748 0.00302 C16orf74 -1.77744 0.00304 RP11-50D9.1 -1.15642 0.00311 BRI3 -1.11918 0.00317 FTLP2 -1.18213 0.00318 RPL39P3 -1.39749 0.00319 RPL23AP38 -1.34822 0.00321 RP11-742D12.1 -1.50730 0.00326 RP11-192C21.1 -1.26565 0.00336 RNU1-1 -1.98496 0.00336 HIST1H4J -1.45056 0.00341 AC010733.5 -1.08395 0.00342 RP11-434H6.7 -2.08555 0.00348 RP11-422P24.9 -1.07248 0.00354 RP11-307O1.1 -1.38556 0.00356 AC093673.5 -1.05138 0.00358 MYL6BP1 -1.06224 0.00370 TMSB4XP4 -1.59703 0.00374 DOC2GP -1.28373 0.00389 CD248 -1.10778 0.00395 AC104978.1 -1.04723 0.00407 RP11-796G6.1 -1.13116 0.00412 FTL -1.11927 0.00418 RBM34 -1.59093 0.00424 RPL30P4 -1.11848 0.00427 RPS28P7 -1.18551 0.00427 RP11-104D3.2 -1.18185 0.00427 RP4-631H13.6 -1.10216 0.00430 GH1 -1.56817 0.00436 MT-RNR1 -1.30935 0.00437 EIF1P5 -1.00402 0.00439 RP11-452G18.2 -1.31958 0.00451 RPS15AP11 -1.00130 0.00452 AC092933.3 -1.86696 0.00468 CTD-3184A7.4 -1.38708 0.00475 RP4-798A10.4 -1.18910 0.00477 CTD-2090I13.1 -1.66016 0.00502 RP11-40C6.2 -1.23617 0.00505 AC017104.6 -1.52822 0.00514 RP11-93H24.3 -1.60617 0.00517 MT2A -1.18911 0.00521 RPS4XP20 -1.06803 0.00522 AC006128.2 -1.59295 0.00523 RP11-3P17.5 -1.89170 0.00525 TMSB4XP1 -1.12004 0.00530 TMSB4XP6 -1.18324 0.00535 RP11-2C24.9 -1.10411 0.00536 RN7SL4P -1.91467 0.00536 MTRNR2L1 -1.28033 0.00545 RPL41P2 -1.13310 0.00546 RP11-586D5.3 -1.78317 0.00551 RP5-837I24.5 -1.03628 0.00551 RP4-798A10.7 -1.24259 0.00560 RPL23AP43 -1.16217 0.00562 RP11-389O22.4 -1.07451 0.00566 C6orf226 -1.10936 0.00566 RP11-66N11.8 -1.78516 0.00578 RP11-14K2.1 -1.09274 0.00586 SH3D19 -1.48175 0.00589 MTRNR2L10 -1.39493 0.00591 AC007389.2 -1.05269 0.00597 RP11-543B16.1 -1.10875 0.00598 SNHG25 -1.84377 0.00599 RPS15AP12 -1.12023 0.00604 RP11-302F12.1 -1.34539 0.00604 RP11-627K11.1 -1.37005 0.00607 RPL13AP6 -1.53503 0.00609 RPL30P7 -1.25202 0.00614 RPS19P3 -1.19455 0.00618 RPS15AP38 -1.08242 0.00625 CLDND2 -1.96673 0.00628 RP11-867G23.10 -1.51617 0.00640 RP11-377K22.2 -1.31671 0.00641 RP11-274J15.2 -1.21503 0.00649 RP11-701P16.5 -1.48675 0.00649 MTRNR2L6 -1.22384 0.00650 RP11-447H19.4 -1.05258 0.00652 CTD-3214H19.12 -1.05941 0.00653 RPL37A -1.03097 0.00653 RP11-140K17.3 -1.33088 0.00656 RP11-566K19.6 -1.01808 0.00657 RP11-318C24.1 -1.38392 0.00661 RP11-253E3.1 -1.17798 0.00666 RP5-882O7.1 -1.33835 0.00671 AC016712.2 -1.01981 0.00673 ZFAS1 -1.19848 0.00679 RP11-404K5.1 -1.07872 0.00680 RP11-572P18.1 -1.50670 0.00684 HIST1H1C -1.80588 0.00684 RP11-553K8.2 -1.46959 0.00686 DDIT3 -1.09845 0.00688 RP11-389O22.5 -1.39014 0.00689 CYP2W1 -1.27093 0.00697 RPL17P20 -1.14312 0.00698 RPS15AP17 -1.17065 0.00711 AC004453.8 -1.05325 0.00718 RPL26P35 -1.08354 0.00726 RPS29 -1.41004 0.00730 WEE2-AS1 -1.09812 0.00733 RPL13AP20 -1.68450 0.00742 RPL37P2 -1.00319 0.00746 RP11-397E7.1 -1.02077 0.00750 AURKC -1.61470 0.00762 RP3-340B19.2 -1.05509 0.00764 RPL38 -1.01421 0.00764 RP11-332E4.1 -1.71724 0.00767 RP11-235D19.2 -1.08534 0.00767 RPL36 -1.07864 0.00771 EMP3 -1.18590 0.00771 RP11-264F23.1 -1.11251 0.00774 TMSB4X -1.12888 0.00779 RP11-247I13.3 -1.42994 0.00780 RP11-661A12.8 -1.49393 0.00785 RP4-717I23.2 -1.23535 0.00788 SYCE1L -1.32450 0.00789 DNAJC27-AS1 -1.84758 0.00791 FTLP17 -1.12543 0.00805 HSP90B1 -1.26096 0.00805 RPL32 -1.09185 0.00808 RPL37P6 -1.04458 0.00811 RP11-403P14.1 -1.22336 0.00817 VEGFB -1.00238 0.00821 AC105399.2 -1.09773 0.00836 RPS3P6 -1.22688 0.00836 AC010095.7 -1.22718 0.00836 RPL41 -1.17739 0.00848 RP11-378J18.6 -1.33925 0.00848 RP11-244J10.1 -1.28890 0.00862 RP11-331N16.1 -1.09807 0.00865 AC017080.1 -1.47179 0.00869 MTRNR2L8 -1.02014 0.00882 CTB-129O4.1 -1.43743 0.00883 CTD-2031P19.4 -1.23166 0.00890 RP11-58A11.2 -1.13364 0.00899 SNHG8 -1.03066 0.00905 VGF -1.01934 0.00920 RPS21 -1.08662 0.00927 RPS18P6 -1.01739 0.00931 ARMC12 -1.09613 0.00946 RPS2P35 -1.19377 0.00950 TMSB10 -1.20999 0.00973 RP11-440L14.1 -1.05962 0.00984 CRIP1 -1.13561 0.00989 GAS5 -1.09189 0.00992 RPS27 -1.03448 0.01003 RPL29 -1.14717 0.01005 RP3-337H4.6 -1.44038 0.01005 RPS4XP11 -1.12972 0.01023 RPL35AP21 -1.11883 0.01035 RPS11 -1.04370 0.01042 RP5-940J5.9 -1.94072 0.01044 AC005019.2 -1.06300 0.01047 FTH1P10 -1.16274 0.01052 HNRNPUP1 -1.01953 0.01059 RP11-445N18.3 -1.42865 0.01071 RPL5P10 -1.06951 0.01076 RPS17P2 -1.25591 0.01088 RP11-114H7.1 -1.10804 0.01088 HSP90B3P -1.08750 0.01088 RPL23AP57 -1.11947 0.01097 RP11-345J4.4 -1.31466 0.01108 LGALS1 -1.48588 0.01122 RPL28 -1.02810 0.01132 RP11-313M3.1 -1.03668 0.01137 NGFR -1.38111 0.01165 TMEM91 -1.35779 0.01166 RP11-289K10.1 -1.24100 0.01174 RPL18P13 -1.03491 0.01176 IFITM4P -1.52473 0.01186 LMNA -1.13954 0.01189 CRIP1P4 -1.21602 0.01190 HSP90B2P -1.22556 0.01197 AC079250.1 -1.18270 0.01197 RPL6P25 -1.10112 0.01201 YPEL3 -1.13061 0.01210 RP11-436H11.1 -1.01174 0.01221 SNHG16 -1.04342 0.01271 MRPS21P1 -1.00716 0.01274 CKB -1.00341 0.01281 AC079834.1 -1.38951 0.01290 TTC22 -1.00931 0.01306 RPL23AP65 -1.15285 0.01311 MT-TF -1.30600 0.01334 RPS10 -1.28342 0.01349 CTD-2666L21.3 -1.19666 0.01356 NOP56P1 -1.15866 0.01363 RP11-397P13.7 -1.10590 0.01369 AP001350.4 -1.16476 0.01376 RP11-467I20.3 -1.11064 0.01382 RP5-1092A3.4 -1.24347 0.01401 RPL10P3 -1.28735 0.01409 RPL30P14 -1.34350 0.01421 RP3-399J4.2 -1.17136 0.01425 RPS24P17 -1.11111 0.01426 RP11-428G5.1 -1.28128 0.01435 AC007969.5 -1.22723 0.01440 VAMP5 -1.14662 0.01442 RP11-478C6.4 -1.41582 0.01458 RPL27A -1.04761 0.01462 RP11-83N9.5 -1.07099 0.01463 RP1-130G2.1 -1.19027 0.01482 RPS18P12 -1.00798 0.01483 TBX15 -1.30086 0.01487 TMEM191B -1.05330 0.01488 RP11-832N8.1 -1.07402 0.01494 RPS15 -1.11063 0.01496 CTC-484M2.1 -1.14812 0.01497 RP11-621K7.1 -1.07340 0.01504 RP11-174N3.4 -1.10696 0.01538 UCN -1.33475 0.01572 RPL13AP7 -1.32245 0.01588 LYPD6B -1.15727 0.01592 RP11-182J1.3 -1.30881 0.01608 RPPH1 -1.32245 0.01650 RP4-630J13.1 -1.11719 0.01652 HIST2H2AA3 -2.14466 0.01656 RP1-43E13.2 -1.12182 0.01690 RP11-3L10.3 -1.17599 0.01704 PHLDA1 -1.95330 0.01734 RP11-68I3.11 -2.40372 0.01739 PPP1R32 -1.48148 0.01754 AC006445.6 -1.10593 0.01761 AC005262.4 -1.30142 0.01766 RP11-477I4.4 -1.56193 0.01796 AC016708.2 -1.06503 0.01801 RP11-366M4.17 -1.20383 0.01803 KANSL1-AS1 -1.25745 0.01805 OST4 -1.07657 0.01821 PMS2P5 -1.04458 0.01865 RPL38P3 -1.14228 0.01874 AC091133.1 -1.04863 0.01888 TMSB10P1 -1.02424 0.01897 PIK3CD-AS2 -1.04243 0.01931 RP5-827C21.4 -1.36576 0.01951 ZNF436-AS1 -1.08225 0.01995 SNORD3B-2 -1.37293 0.01997 LYG1 -1.29618 0.02036 OTUB2 -1.10551 0.02039 RP4-570O12.2 -1.00073 0.02066 RP11-12M9.3 -1.02203 0.02082 SNHG19 -1.35541 0.02086 ZSCAN16-AS1 -1.16298 0.02115 C19orf53 -1.02053 0.02119 HIST1H2BJ -1.60280 0.02134 AC007365.4 -1.17065 0.02171 DUSP2 -1.23971 0.02251 RRAS -1.00937 0.02263 EML2-AS1 -1.13878 0.02276 RPS20P5 -1.07582 0.02386 RPS17 -1.02366 0.02398 RPL32P9 -1.05618 0.02399 RP11-336K24.12 -1.08503 0.02409 HSPB1P1 -3.21334 0.02419 CTC-543D15.8 -1.02585 0.02515 RP11-380G5.3 -1.10482 0.02530 FAM89B -1.21639 0.02579 CCR7 -1.82645 0.02583 RP11-410L14.2 -1.05331 0.02597 CTC-338M12.5 -1.19353 0.02645 SNORD3A -2.70989 0.02652 RP1-72A23.3 -1.11870 0.02721 CTD-2583A14.11 -1.15361 0.02728 C6orf3 -1.78727 0.02778 RPL13AP3 -1.08014 0.02845 AL353644.10 -1.01749 0.02890 RP11-16E12.1 -1.48169 0.02893 NRARP -1.57617 0.02901 SELPLG -1.03830 0.02931 RP5-1052M9.1 -1.21103 0.02956 HSPB1 -3.31732 0.02962 TMEM191A -1.42736 0.02999 RP11-1348G14.1 -1.86696 0.03012 HIST2H2BF -2.08822 0.03026 CTC-524C5.2 -1.45266 0.03119 RP11-225H22.7 -1.24487 0.03135 RP3-395M20.12 -1.06468 0.03145 CTA-351J1.1 -1.12326 0.03184 RPL23AP31 -1.35475 0.03229 MPZ -1.13493 0.03273 MTND1P23 -1.06994 0.03363 FP671120.4 -1.01305 0.03372 RPS20P2 -1.10348 0.03405 AC005336.5 -1.08705 0.03423 RPL7P7 -1.24123 0.03511 C19orf24 -1.06609 0.03600 GPX1 -1.07312 0.03607 VKORC1 -1.04609 0.03656 MT-TQ -1.02565 0.03719 AC008753.3 -1.11548 0.03719 SMIM24 -1.05264 0.03815 HES7 -1.56387 0.03827 CTSV -1.00485 0.04006 TMEM86B -1.01580 0.04008 S100A4 -1.10114 0.04032 LA16c-329F2.2 -2.02567 0.04065 AC079150.2 -1.19429 0.04125 SLC11A1 -1.42568 0.04275 IPO4 -1.19753 0.04370 RP11-359B20.1 -1.07687 0.04444 RP11-274B21.9 -1.06878 0.04496 DPM3 -1.10229 0.04516 NUDT8 -1.03027 0.04591 RP11-386G11.10 -1.06763 0.04683 SARNP -1.07470 0.04697 TNFRSF10D -1.02887 0.04710 JUND -1.08595 0.04850 RP11-543P15.1 -1.26799 0.04861 AC139100.4 -1.12068 0.04879 TAGLN -1.01822 0.04921 MAP6D1 -1.00056 0.04969 RP11-694I15.7 -1.12219 0.04970 Translationally up-regulated genes Gene Name Log Fold Change p-value HNRNPDLP2 1.71962 0.00005 CTD-2576D5.2 1.48925 0.00016 NOL4 1.71059 0.00038 CTC-459F4.9 2.15615 0.00039 RP11-344P13.3 1.65264 0.00039 MT-TT 1.39960 0.00040 RP11-232D9.1 1.43991 0.00042 IMMP1LP1 2.11283 0.00054 RP11-553K23.2 2.55610 0.00056 MTATP8P1 1.87116 0.00075 RP4-569D19.5 1.58633 0.00087 ACVR1 1.39514 0.00104 CTC-303L1.1 1.79195 0.00111 MAP10 1.17090 0.00115 CTC-281F24.1 1.07142 0.00145 GHET1 1.18574 0.00176 PAPOLB 2.15533 0.00178 LACC1 1.08833 0.00225 RP11-673E1.3 1.69869 0.00228 GEMIN2P1 1.04267 0.00292 RP11-105N14.1 1.46865 0.00303 TSEN15P1 1.69168 0.00306 BX322557.10 1.27998 0.00310 PTPN13 1.27470 0.00317 ZC3HAV1L 1.73347 0.00319 TEX9 1.05619 0.00322 DNAJC3-AS1 1.08419 0.00328 RP4-814D15.1 1.34318 0.00353 PKD1P5 1.13799 0.00357 C5orf34 1.06144 0.00425 RP11-467L13.7 1.36133 0.00455 CCDC18 1.13117 0.00461 CENPI 1.03435 0.00469 CTC-523E23.3 1.03414 0.00471 LRRCC1 1.43305 0.00490 CCDC141 1.17867 0.00491 SRSF9P1 1.06033 0.00494 CDKL5 1.24415 0.00530 ANKRD20A17P 1.82956 0.00531 GS1-124K5.3 1.32551 0.00538 HAUS1P3 1.35486 0.00544 TPMTP1 2.06710 0.00609 CLECL1 1.08516 0.00610 ATG4C 1.19704 0.00639 MIR570 1.24219 0.00643 NSRP1P1 1.02798 0.00644 AC000068.5 1.27188 0.00720 RP11-958N24.1 1.46116 0.00725 KRIT1 1.20957 0.00739 PCDHGA1 1.30413 0.00741 HERC2P3 1.24090 0.00746 SLC35G2 1.25784 0.00801 DHFRP1 1.32685 0.00842 MPRIPP1 1.18808 0.00876 EIF2S2P3 1.19418 0.00896 AC007395.4 1.29894 0.00949 MRPL30P1 1.10500 0.00983 ZMAT1 1.21487 0.00992 MRPS10P1 2.22004 0.00998 JAK2 1.09895 0.01004 FAM135A 1.25265 0.01007 CETN3 1.07995 0.01012 RP11-332L8.1 1.16999 0.01137 ZNF85 1.17261 0.01175 ZNF534 1.13115 0.01188 PCMTD2 1.01301 0.01229 RP11-255H23.2 1.04522 0.01230 VDAC1P5 1.02372 0.01231 AC142528.1 1.46951 0.01233 HMGN2P46 1.29967 0.01235 TERF1P5 1.25387 0.01261 YEATS4 1.18990 0.01261 IGLV4-60 1.22960 0.01287 RP11-451O18.1 1.14030 0.01314 NUDT7 1.00291 0.01348 RP13-140E4.1 1.29102 0.01355 HNRNPA1P70 1.00156 0.01366 RP11-517P14.2 1.39746 0.01388 SLC25A20P1 1.06492 0.01405 SLC35A3 1.07481 0.01408 SMN1 1.01720 0.01419 GPN3 1.02396 0.01460 LYPLAL1 1.16512 0.01462 RELL1 1.14908 0.01474 GPR180 1.06428 0.01509 RP11-397E7.2 1.46906 0.01583 SPAG1 1.15182 0.01584 ZNF860 1.31319 0.01639 FAM72C 1.13617 0.01641 RP11-314A15.2 1.25028 0.01650 ANKRD26 1.01404 0.01666 CTD-2561J22.2 1.32197 0.01672 RP11-220H4.6 1.28898 0.01693 TET1 1.09620 0.01715 GATSL2 1.27971 0.01752 RP11-95M15.2 1.74557 0.01824 RP11-817I4.1 1.05795 0.01863 RP4-595K12.2 1.22062 0.01868 DUSP6 1.06803 0.01916 RP11-488L18.4 1.09733 0.01926 RP11-1319K7.1 1.10260 0.01946 ZNF711 1.24854 0.01948 GMCL1P1 1.62348 0.01966 TRAM1L1 1.31420 0.01974 AF013593.1 1.26648 0.01986 RP11-51C14.1 1.25350 0.02012 HAUS1P2 1.09354 0.02021 EEF1E1 1.08217 0.02027 CNOT6LP1 1.87528 0.02032 HTATSF1P2 1.66487 0.02041 ADAM9 1.13043 0.02046 RP11-142L4.2 1.41422 0.02069 RP11-397J20.1 1.11997 0.02071 RP11-1070N10.5 1.09700 0.02119 HPRT1 1.16421 0.02138 CCNE2 1.03343 0.02178 RP11-27I1.4 1.07352 0.02202 ENTPD1-AS1 1.46005 0.02217 CD84 1.08307 0.02244 RP11-320A16.1 1.57190 0.02292 ERBB4 2.04669 0.02300 AC097523.3 1.16614 0.02326 AC008592.3 1.20926 0.02341 REL 1.11503 0.02349 C9orf129 1.44977 0.02412 KRT8P46 1.52765 0.02456 UBASH3B 1.04394 0.02478 SLC25A15 1.12988 0.02508 ZMYM1 1.07693 0.02509 CTAGE14P 1.00051 0.02511 RSL24D1P11 1.32747 0.02526 RP11-629B11.4 1.09885 0.02542 SCN8A 1.01059 0.02594 CMTM8 1.08313 0.02609 RP1-179N16.3 1.06273 0.02623 RP11-142E9.1 1.08688 0.02695 ZNF724P 1.66031 0.02707 PTP4A1P7 1.39514 0.02765 RAD51AP1 1.14005 0.02767 PAICSP5 1.05026 0.02831 RP11-288C17.1 1.07237 0.02832 ZNF92 1.22007 0.02886 RP11-385M4.3 1.18185 0.02923 RGS18 1.28293 0.02980 RP11-553L6.5 1.53651 0.02982 RP11-498D10.8 1.07415 0.03028 RP3-510O8.3 2.34994 0.03028 TMEM9B-AS1 1.06154 0.03055 RP11-621H8.2 1.16112 0.03064 ANAPC1P1 1.17491 0.03084 FAM161A 1.20073 0.03128 ZNF680 1.19790 0.03135 RP11-134K13.2 1.06171 0.03222 HPGD 1.40895 0.03228 SNX24 1.05643 0.03268 RP11-3J10.7 1.04055 0.03271 RP3-468K18.6 1.69095 0.03280 RP11-68L18.1 1.10162 0.03289 KB-1507C5.4 1.21983 0.03308 CTA-246H3.11 1.12913 0.03329 FDX1P1 1.17708 0.03354 RP11-181C21.4 1.35097 0.03385 ATRNL1 1.77996 0.03401 CTB-133G6.1 1.60166 0.03480 BCAS2P2 1.46069 0.03495 CNTF 1.59769 0.03496 RP11-307P22.1 1.10879 0.03498 EML5 1.24066 0.03505 AP1AR 1.04129 0.03515 XPOTP1 1.04086 0.03520 RAD51AP1P1 1.49668 0.03527 FBXO4 1.01401 0.03689 RP11-5N11.1 1.05772 0.03708 STK3 1.06793 0.03720 PPATP1 1.24747 0.03859 LRRFIP1P1 1.20287 0.03876 DTX2P1 1.05410 0.03890 RP11-159G9.5 1.64843 0.03935 AC005780.1 1.25450 0.03950 RMI1 1.15523 0.04102 AC078899.1 1.57736 0.04109 CDC27P1 1.04677 0.04134 RP11-360F5.3 1.06028 0.04150 C3orf20 1.02599 0.04191 CTD-2144E22.10 1.07206 0.04337 CTD-2081C10.7 1.76633 0.04374 HAUS6P1 1.93385 0.04476 ERC2 1.09828 0.04546 RP11-700P18.2 1.50495 0.04566 LRRC37A15P 1.29220 0.04579 AC005154.7 1.05433 0.04632 RP11-206L10.2 1.68300 0.04735 AC092646.2 1.31926 0.04743 RP11-114M5.1 2.14130 0.04768 RAD1P1 1.25133 0.04945 RP11-553D4.2 1.13737 0.04994

Transcriptionally and translationally regulated genes Gene Name Log Fold Change p-value HIST1H2AE -2.53893 0.00555 AC062017.1 -2.14231 0.00006 RP11-642A1.2 -2.07267 0.01088 ASB12 -1.47970 0.00185 RBMS2 -1.45298 0.01073 HIST2H2BE -1.41652 0.03479 CD55 -1.37021 0.01929 TNNT3 -1.25827 0.00641 APOE -1.21649 0.01891 FSCN1 -1.14008 0.01831 TMEM71 -1.12347 0.01583 DLX2 -1.01694 0.01588 LINC01252 1.32780 0.01115 Negative Regulators of Apoptosis (translationally downregulated): TNF receptor superfamily member 10d (TNFRSF10D) Adipogenesis associated Mth938 domain containing (AAMDC) Heat shock protein 90 beta family member 1 (HSP90B1) Heat shock protein family B (small) member 1 (HSPB1) Msh homeobox 1 (MSX1) Myelin protein zero (MPZ) Nerve growth factor receptor (NGFR) Sequestosome 1 (SQSTM1) Urocortin (UCN) Vascular endothelial growth factor B (VEGFB)

Chapter 3

Targeting eIF4F translation complex sensitizes B-ALL cells to tyrosine kinase inhibition

165

Introduction

Tyrosine kinases (TKs) are associated with cell-to-cell communication and regulate a matrix of complex biological functions, including cell growth, motility, differentiation, and metabolism 1,2. During normal physiologic conditions, TK activity is tightly controlled by molecular mechanisms involving tyrosine phosphatases and other molecules 3. Mutations that cause TK hyperactivation or overexpression transform cells via several mechanisms, all disrupting the balance between cell growth, proliferation and cell death 4. Many blood cancers are associated with activation of cytoplasmic or receptor tyrosine kinases, as in the case of CML and Ph+ B-ALL (BCR-ABL), Ph-like B-ALL (various activated TKs), and Flt3 mutant acute myeloid leukemia (AML) 5. One of the major successes in the treatment of Ph+ disease has been a series of tyrosine kinase inhibitors (TKIs), such as imatinib mesylate (Gleevec®), dasatinib

(Sprycel®), and nilotinib (Tasigna®). These compounds all suppress the BCR-ABL kinase activity, therefore causing selective growth arrest and apoptosis of the transformed cells 6–10.

However, the incomplete responses to TKIs has urged the study of downstream pathways that are critical for malignant transformation and maintenance of Ph+ diseases. Those mechanistic studies may suggest approaches to pharmacologically target crucial oncogenic signaling pathways along with BCR-ABL in order to prevent the expansion and survival of the leukemias.

Specifically, the combination of an inhibitor to a downstream oncogene with an upstream TKI may synergize the anti-tumorigenic effects of both compounds.

Among healthy cells, the mechanistic target of rapamycin (mTOR) activity is regulated by growth factor signals and nutrient availability and is facilitated by the two main complexes: mTORC1 and mTORC2. mTOR activation promotes cellular processes leading to cell growth and proliferation, and it has dozens of substrates 11–13. Well-characterized targets of mTORC1

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include the p70 ribosomal-S6 kinases (S6Ks) and eukaryotic initiation factor 4E (eIF4E) binding proteins (4E-BPs) 14–16. S6Ks promote ribosome biogenesis, lipid and nucleotide synthesis, and metabolic reprogramming 17–20, and also promote mRNA translation via phosphorylation of

PDCD4, eIF4B, and ribosomal protein S6 (rS6) 21. 4E-BPs bind eIF4E in their non- phosphorylated state and prevent interaction of eIF4E with the other subunits 22–24, hence preventing formation of the eukaryotic translation initiation complex (eIF4F). Upon phosphorylation by mTORC1, 4E-BPs release inhibition of eIF4E, thus making it available to bind the scaffolding protein eIF4G1 and the RNA helicase, eIF4A, to form the eIF4F protein translation initiation complex that binds to the 5’ cap of certain mRNAs and facilitates cap- dependent translation 14–16. Importantly, 4E-BP1 phosphorylation was associated with high risk in B-ALL and chronic lymphocytic leukemia 25,26, while mTOR inactivation impairs B-ALL survival 27,28. The Fruman laboratory has shown that mTOR kinase inhibitors (TOR-KIs) (e.g.

PP242, MLN0128) increase the anti-leukemic potential of dasatinib in Ph+ B-ALL while

Figure 3.1: Schematic diagram of the PI3K/ mTOR/ eIF4E signaling pathway and inhibitors used in this study to target the pathway.

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inhibiting proliferation of malignant cells 29,30. Also, MLN0128 showed anti-tumor and anti- metastatic effects in prostate cancer models, as well as synergy with the TKI lapatinib in breast cancer models 31. The effects of mTOR inhibitors remain limited in clinical studies of TK-driven leukemias. On the other hand, early clinical trials have suggested that TOR-KIs are more effective than rapalogs at inhibiting tumor progression, yet they seem less tolerable32. For instance, AZD2014 administered as a single agent showed dose-limiting toxicities that were similar to rapalogs33. Also, both CC-223 and MLN0128 showed similar toxicities34,35. A clinical trial of MLN0128 (TAK-228) in relapsed/refractory ALL patients achieved poor tolerability and clinical significance36.This limited efficacy could be attributed to suppression of mTORC2 activity which leads to toxicity 37–39. Therefore, there is a rationale for seeking better therapeutic strategies for treatment of TK-driven cancers, such as Ph+ B-ALL.

One promising alternative to targeting the mTOR pathway while sparing most of mTOR function is to identify and target processes downstream of mTOR that are selectively required for cancer cell survival. Among those processes is cap-dependent mRNA translation, controlled by the eIF4F complex 14–16. Elevated eIF4F activity contributes to sustained replication, avoiding growth suppression, and resistance to programmed cell death 16. eIF4E is the major cap-binding protein and has long been considered as the limiting factor for translating the mammalian genome. Cancer cells are “addicted” to high levels of eIF4F activity, compared to normal cells

14–16. Indeed, via generation of an Eif4e haplo-insufficient mouse, reduction of 50% in eIF4E expression was found to allow normal development and global protein synthesis, while impeding cellular transformation in RAS-driven models. In this work we aimed to sensitize leukemia cells

(specifically Ph+ and Ph-like B-ALL) to dasatinib by co-targeting the eIF4F complex directly, using both chemical and genetic approaches.

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Results

Selective mTORC1 inhibition phenocopies dual mTORC1/mTORC2 inhibition

Previously we demonstrated that TOR-KI compounds (PP242, MLN0128; Fig. 3.1) sensitize Ph+ B-ALL cells to TKIs including imatinib and dasatinib40,41. Since TOR-KIs inhibit the kinase activity of both mTORC1 and mTORC2, we sought to determine whether TKI sensitization required inhibition of one or both targets. To compare different mTOR inhibitors alone or in combination with dasatinib, we used the p190 cell system in which primary murine leukemia cells are generated from bone marrow using a retroviral vector expressing p190-BCR-

ABL. We treated p190 cells with mTOR inhibitors for 2hr prior to measurement of mTOR signaling readouts. As expected, rapamycin strongly suppressed pS6 (S240/244) with lesser effect on p4E-BP1 (T37/46) and no effect on the mTORC2 substrate AKT-S473 (Fig. 3.2A). The

TOR-KI compound MLN0128 (50 nM) also blocked pS6, reduced p4E-BP1 to a greater extent than rapamycin, and partly reduced pAKT (Fig. 3.2A). To assess the effect of selective mTORC1 kinase inhibition we tested two Rapalink compounds E1035 and M1071. Both

Rapalinks selectively suppressed phosphorylation of mTORC1 readouts (p-4E-BP1, pS6) at concentrations that did not affect mTORC1 substrate phosphorylation (pAKT-S473). E1035 was mTORC1-selective at 3 and 10 nM, and M1071 at 1 nM. Both Rapalinks, especially M1071, caused more complete dephosphorylation of p4E-BP1 compared to the effect of MLN0128, as judged by mobility shift of the total 4E-BP1 protein signal (Fig. 3.2A).

Next we tested the effects of single and dual compound treatments on p190 cell viability after 48hr. None of the mTOR inhibitors affected viability as single agents, but all enhanced cytotoxicity by dasatinib (Fig. 3.2B). The two Rapalink compounds (E1035, 10 nM; M1071, 1 nM) were equally or slightly more effective than MLN0128. These data indicate that selective

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mTORC1 inhibition is sufficient to recapitulate the cell death sensitization observed with dual mTORC1/mTORC2 inhibitors.

Figure 3.2: 4E-BP mediates cytotoxicity of TORC1 inhibition. (A) Western blot analysis of p190 cells treated for 2 hours with DMSO control, mTOR inhibitors (MLN0128 and rapamycin) or the Rapalink compounds E1035 or M1071 (concentrations indicated). Expression of target proteins was evaluated and normalized to loading control (GAPDH). (B) Viability of p190 cells was assessed using annexin V and propidium iodide (PI) staining following by flow cytometry analysis. The cells were cultured with the compounds indicated for 48 hours and their viability was analyzed. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001, vs vector, unpaired t-tests. (C) Expression and function evaluation of 4E-BP1 mutant using cap-binding assay. We treated cells expressing endogenous 4E- BP1 (control) or mutated 4E-BP1 form (5A) with MLN0128 or 68doxycycline (DOX). Interaction between eIF4E, 4E-BP1 or eIF4G was tested via pull-down of m7-GTP bead and extraction of the proteins associated with them (cap-pull down analysis). The fraction associated with the beads was normalized to the total cell lysates. (D) Viability of p190 cells expressing either normal 4E-BP1 form (Rosa26) or mutated form (4E-BP1 5A) was assessed using annexin V and PI staining. The cells were cultured with the compounds indicated for 48 hours and their viability was analyzed. *p<0.05; **p<0.01; ****p<0.001, vs vector, unpaired t-tests. Data in this figure was produced by Dr. Trang T. Vo.

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Genetic inhibition of eIF4E function sensitizes to dasatinib

mTORC1 has numerous substrates that control various aspects of cell proliferation and survival. The 4E-BPs are key mTORC1 substrates whose phosphorylation releases eIF4E to form the eIF4F complex that also contains eIF4G1 and eIF4A. We first assessed the role of the

4E-BP/eIF4E axis using an inducible system to express a constitutively active mutant of 4E-BP1 in which five serine or threonine phosphorylation sites are changed to alanine (5A mutant). We generated p190 leukemia cell pools from double transgenic mice that ubiquitously express the reverse transactivator (“tet-on”) protein rtTA (Rosa26-rtTA) along with a tetracycline response element (TRE)-linked cDNA encoding 4E-BP1-5A. Control cells were generated from Rosa26- rtTA single transgenic littermates. We then tested expression and function of the 4E-BP1 mutant in a cap-binding assay. Treatment of control cells with MLN0128 but not DOX caused displacement of eIF4G1 from eIF4E (Fig. 3.2C). In the double transgenic cells, DOX induced robust expression of the 4E-BP1 mutant and this displaced eIF4G1, to a similar or greater extent than MLN0128 treatment. This biochemical effect correlated with cytotoxicity. DOX treatment of double transgenic p190 cells phenocopied the effect of MLN0128 on cell viability, both alone and in combination with dasatinib (Fig. 3.2D). DOX treatment had no effect on viability in control p190 cells. These results are consistent with the model that 4E-BP1 activation is a critical pro-death mechanism of mTORC1 inhibition.

As a distinct approach to interfere with eIF4E function, we used a genetic eIF4E loss of function model. We obtained mice with a conditional floxed allele of Eif4e from the

NorCOMM2 mouse repository (C57BL/6N-Eif4etm1c(EUCOMM)Hmgu/Tcp) and crossed them with another knockin strain in which inducible Cre is expressed in all sues (Rosa26-CreERT2). We generated p190 cells from Cre-positive Eif4efl/+ and control Eif4e+/+ mice and assessed deletion

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efficiency by Western blot. After treatment with 4OHT (1 µM) for (72 hr), eIF4E expression was reduced by 30-40% in Eif4efl/+ cells but unaltered in control p190 cells (Fig. 3.3A). Notably, deletion of one allele of Eif4e sensitized p190 cells to dasatinib cytotoxicity, and the magnitude of this effect was similar to that achieved in cells treated with MLN0128 (Fig. 3.3B).

Consistently, 4OHT treatment sensitized Eif4efl/+ cells but not Eif4e+/+ p190 cells to dasatinib

(Fig. 3.3B). Thus, reduced Eif4e gene dosage strongly sensitizes cells to BCR-ABL inhibition.

Figure 3.3: Reduced Eif4e gene dosage sensitizes to dasatinib. (A) Western blot analysis of p190 cells treated for 72 hours with or without 4- hydroxytamoxifen (4OHT) at the concentration indicated. Expression of target proteins was evaluated and normalized to loading control (tERK). (B) Viability of p190 cells was assessed using annexin V and PI staining. Cells encompassing two normal alleles of Eif4e (+/+) or cells with one normal gene and one floxed between two loxP sites (fl/+) were compared to each other were cultured with the compounds indicated for 48 hours. Their viability was analyzed using flow cytometry. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001 unpaired t-tests. Panel A of this figures was produced by Dr. Roberta V. Buono.

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Chemical inhibition of eIF4F components sensitizes to dasatinib

The genetic approaches described above build on previous evidence that the eIF4F complex has important functions on BCR-ABL-mediated transformation42,43. In accord, we found that two natural product modulators of eIF4A helicase, silvestrol and hippuristanol, sensitized p190 cells to dasatinib (Fig 3.4). As an alternative chemical approach, we tested the

Figure 3.4: Targeting the eIF4F complex sensitizes p190 cells to dasatinib. Viability of p190 cells was assessed using annexin V and PI staining. P190 cells were exposed to single agents or combinational therapies for 48 hours, as indicated (Silvestrol 10nM, Hipporistanol 10nM, MLN0128 50nM), and their viability was analyzed using flow cytometry. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001 unpaired t-tests. The figure was produced by Dr. Trang T. Vo.

compound SBI-756 that binds eIF4G1 and prevents its interaction with eIF4E. Treatment of p190 cells with a relatively low SBI-756 concentration (250 nM) sensitized to dasatinib to a comparable extent as MLN0128 (50 nM) (Fig. 3.3B). SBI-756 also blocked leukemic transformation of bone marrow cells by BCR-ABL, similar to the effects of dasatinib, MLN0128 or Rapalinks (Fig. 3.5).

Figure 3.5: Targeting the eIF4F complex suppresses colony formation to similar extent as targeting mTORC1. P190 cells were resuspended in primary media at 2 × 105 cells/condition with recombinant human SCF, IL-7, IL-3, and FLT3 cytokines. Cells and inhibitors at the concentrations indicated were then suspended in Methocult and vortexed for 90 seconds prior to plating in duplicate in 24-well plates. Colonies were counted twice at 10–14 days after plating by two different people, and number of colonies per condition were averaged for the two counts. The data was produced by Dr. Trang T. Vo, Dr. Moran Gotesman and Dr. Sharmila Mallya. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests.

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To confirm the on-target effect of SBI-756 in p190 cells, we compared the impact of SBI-

756 and MLN0128 on eIF4F assembly and mTORC1 substrate phosphorylation. Using proximity ligation assay (PLA), we found that both SBI-756 and MLN0128 strongly blocked the association of eIF4E with eIF4G1 in intact p190 cells (Fig. 3.6A, B). In contrast, SBI-756 did not suppress MLN0128-sensitive phosphorylation of S6 and 4E-BP1 (Fig. 3.6C). Thus, at concentrations that do not impact mTORC1 activity, SBI-756 has similar potential as a TOR-KI to target the eIF4F complex and sensitize to dasatinib.

Figure 3.6: SBI-576 sensitizes similar to mTOR inhibition but does not inhibit mTOR. (A) p190 cells were treated for 4 hours with either DMSO control, ML0128 100nM (TOR-KI) or SBI-756 250nM (eIF4F inhibitor). We performed proximity ligation assay (PLA) by testing interaction between eIF4E and eIF4G using orange detection reagent. A red dot indicates a place of interaction between eIF4E and eIF4G. Cells’ nuclei are stained blue due to DAPI staining. (B) Quantification of PLA by measuring PLA signal via ImageJ software and adjusting to the number of cells detected per field. Treatment applied as indicated. (C) p190 cells were treated with DMSO control, BI-756 or MLN0128 for 16 hours. western blot analysis was performed to test changes in expression levels of the targets indicated. Normalization to loading control (GAPDH) was performed. Data obtained by Dr. Trang T. Vo.

In addition, we investigated the effects of either chemical or genetic suppression of eIF4E availability on total protein synthesis among p190 cells. Indeed, both the genetic and chemical approaches yielded reductions in total protein synthesis (Fig. 3.7). Total protein synthesis was

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measured by puromycin incorporation using fluorescently labeled puromycin as described in chapter 2 and compared to vehicle treatment or cycloheximide treatment (as a positive control).

SBI-756 sensitizes human Ph+ B-ALL cells to dasatinib

To assess SBI-756 potential in human leukemia cells, we first carried out viability assays using the Ph+ B-ALL cell line SUP-B15 and the Ph-like B-ALL cell line TVA1. Both cell lines were resistant to dasatinib alone at concentrations up to 10 nM (Fig. 3.8A). MLN0128 30nM had a modest sensitization effect on both cell lines, which was recapitulated by SBI-756 (500 nM in

Figure 3.7: Reduced eIF4E availability leads to reduction in protein synthesis. (A) p190 cells were treated for with vehicle (DMSO), cycloheximide 2μM, or SBI-756 250nM. In the last 15 minutes of treatment, puromycin (10μg/ml) was added, and the incorporation of it to polypeptides was analyzed using flow cytometry. (B) p190 cells containing two normal alleles of Eif4e (+/+) or cells with one normal gene and one floxed between two loxP sites (fl/+) were treated with the compounds indicated for 72 hours. Analysis of puromycin incorporation was done as described in panel A. One-sample t-test, adjusted for multiple comparisons. ***p<0.01; ****p<0.001. Panel B of this figure was produced by Dr. Roberta V. Buono.

SUP-B15 cells; 250 nM in TVA-1 cells; Fig. 3.8A). Next we compared single and combination treatments in three patient-derived, stroma-dependent Ph+ B-ALL cell lines (MXP5, ICN1,

SFO2). In all three lines, SBI-756 alone had a significant cytotoxic effect and this was greater than the effect of MLN0128 in ICN1 and SFO2 cells: it reduced their viability by 10% and 30%,

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respectively, compared to MLN0128 which was not cytotoxic (Fig. 3.8B). In all three cell lines, the combination of SBI-756 with dasatinib was more cytotoxic compared to dasatinib alone or to dasatinib combined with MLN0128 (Fig. 3.8B).

Figure 3.8: SBI sensitizes human Ph+ and Ph-like B-ALL cell lines and stromal-dependent lines to dasatinib treatment. (A) Ph+ SUB-B15 cell line and patient-derived PH-like TVA1 cells were treated as indicated for 48 hours. The treatments with TOR-KI (MLN0128) or eIF4F inhibitor (SBI- 756) were done as single agents or in combination with dasatinib, as indicated. Viability of the cells was measured via annexin V and PI staining and flow cytometry analysis. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests. (B) Patient-derived, stroma-dependent Ph+ B-ALL cell lines (MXP5, ICN1, SFO2) were evaluated for viability following treatment for 48 hours, as indicated. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests. The results were obtained by Dr. Trang T. Vo and Dr. Moran Gotesman.

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Inhibitors of the mTORC1/eIF4F axis are selectively toxic to B lineage cells

To assess the selectivity of pathway inhibitors for leukemic cells, we carried out viability assays using PBMCs derived from healthy donors. After 48hr treatment, MLN0128, silvestrol and SBI-756 all reduced survival of B cells (Fig. 3.9). However, these inhibitors had little or no effect on CD4 T cells, CD8 T cells, NK cells or monocytes. Together with the cytotoxicity

Figure 3.9: SBI-756 is selectively toxic to B cells. Human peripheral blood or bone marrow mononuclear cells were isolated from healthy volunteers and undergone purification process using a commercial kit. The specific populations were analyzed using flow cytometry while using the following markers: CD3, CD4, CD8, CD14, CD19, CD56. Viability of the populations was tested via annexin V and PI staining and analyzed using flow cytometry. Data are plotted for individual experiments with the means of each group indicated by a horizontal line. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests. This data was obtained together with Dr. Trang T. Vo. experiments using murine and human B-ALL cells, and our previous studies of human B-cell lymphomas (in chapter 2), these data suggest that cells of the B lymphocyte lineage are selectively sensitive to SBI-756 cytotoxicity.

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Discussion

Previous work demonstrated that TOR-KIs that inhibit both mTORC1 and mTORC2 can sensitize to TKI in models of Ph+ and Ph-like B-ALL27,29,40,44,45. Here we investigated the specific role of mTORC1 and its downstream effector, the eIF4F complex. Experiments using

Rapalinks showed that selective mTORC1 inhibition can recapitulate the effect of TOR-KIs in sensitizing murine p190 (BCR-ABL+) leukemia cells to dasatinib. Using chemical inhibitors

(SBI-756 and Silvestrol) and two genetic approaches, we find that inhibiting eIF4F function also sensitizes p190 cells to dasatinib. We also observed that SBI-756 sensitized human Ph+ and Ph- like B-ALL cells to dasatinib. Consistent with data presented in chapter 2, we found that among human PBMC subsets, B lymphocytes were the only cells sensitive to the cytotoxic effects of

SBI-756 in vitro. Together these results indicate that targeting eIF4F holds promising for enhancing the anti-leukemic efficacy of TKIs such as dasatinib.

Figure 3.10: SBI-576 reduces eIF4E:eIF4G1 interaction in vivo in a dose-dependent manner. (A) PLA of bone-marrow extracted cells testing interaction between eIF4E and eIF4G change between the treatments. Representative fields of bone-marrow cells are presented. PLA was performed as described previously. (B) Quantification of the PLA signal obtained and normalized to vehicle signal. *p<0.05; **p<0.01; ***p<0.005, unpaired t-tests.

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In this study we evaluated SBI-756 effects in vivo, using a BCR-ABL-driven leukemia model. We chose this model for initial studies due to rapid engraftment of the transferred leukemia cells, relative to engraftment rates in xenograft models. In pilot dose finding studies, a daily dose of 10 mg/kg SBI-756 was sufficient to produce a significant pharmacodynamic effect based on PLA measurements in bone marrow cells from mice with leukemia (Fig. 3.10). Next we set up a combination treatment study, as described in the schematic model in Fig. 3.11A. We found that all treatments proved tolerable (Fig. 3.11B) and that treatment with a suboptimal dose of dasatinib (2.5 mg/kg) had variable impact on leukemic expansion in different mice, with an overall significant reduction compared to vehicle (Fig. 3.11C). When SBI-756 was administered as monotherapy (10 mg/kg daily dose), it did not cause a significant reduction in the percentage of leukemia cells in the bone marrow (Fig. 3.11C). Combination treatment with SBI-756 and dasatinib significantly reduced leukemic burden compared to vehicle, but not compared to each compound alone (Fig. 3.11C). Nevertheless, all treatments reduced eIF4E:eIF4G1 interaction in bone marrow cells, with the greatest effect in mice treated with the combination of SBI-756 and dasatinib (Fig. 3.11D). It is possible that better therapeutic effects are obtainable via increased dose of SBI-756 (e.g. 25mg/kg as reported in chapter 2), higher dasatinib dose (as was used in other similar studies), or the use of a molecule with better pharmacokinetics than SBI-756.

Despite serving as a helpful tool compound, better molecules are required to further evaluate the potential of targeting eIF4G1 in vivo, and associated toxicities compared to mTOR inhibitors.

Alternatively, we can use the novel genetic model that we have established and via induction

4OHT which will cause a reduction in eIF4E availability, to test the importance of eIF4F complex for tumor progression in vivo.

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Figure 3.11: Combination of SBI-756 and dasatinib reduces B-ALL leukemic burden while suppress eIF4E:eIF4G interaction in vivo. (A) Schematic diagram of the experimental design: following sub-lethal eradiation, B57BL/J mice were injected intravenously with hCD4+ p190 cells (0.8x106 cells/mouse). Upon establishment of leukemia (measured by more than 0.5% hCD4+ cells in the peripheral blood), we initiated treatment as indicated for five consecutive days. At the end of the treatment, each mouse was sacrificed, bone marrow and spleens were extracted and were subject to further analysis. Additionally, spleen size was measured. (B) Body weight of each mouse was measured as indicated and showed to toxicity. (C) Bone-marrow extracted cells were analyzed for hCD4 expression on their surface using hCD4-PE antibody and flowcytometry analysis. Percentage of hCD4+ out of the total population analyzed is shown. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests. (D) PLA of bone-marrow extracted cells testing interaction between eIF4E and eIF4G change between the treatments. PLA was performed as described previously. *p<0.05; **p<0.01; ****p<0.001, unpaired t-tests.

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Mitochondrial priming refers to the cell’s tendency towards apoptosis, given a fine balance between pro- and antiapoptotic BCL-2 family proteins at the mitochondria, and can be determined via BH3 profiling analysis 46. BH3 profiling determines mitochondrial outer membrane permeabilization (MOMP) following exposure to proapoptotic interacting BH3 peptides. In several cancers, higher mitochondrial priming was correlated with increased chemosensitivity 47 as well as clinical response 46. In experiments performed by Dr. Trang Vo in our lab, BH3 profiling showed that SBI-756 increases mitochondrial priming in p190 cells (Fig.

3.12A). However, the molecular mechanisms that increase priming and dasatinib sensitization remain to be determined. Treatment of p190 cells treated with either MLN0128 or SBI-756 did not cause consistent differences in expression of BCL2 family members, either pro-survial members (BCL2, BCL-xL, MCL-1) or pro-death (BIM, PUMA) (Fig. 3.12B, and data not shown). Therefore, a further investigation is needed to define the mechanism: (I) In order to decipher the molecular mechanism that is responsible for the apoptosis observed, we suggest

Figure 3.12: Comparison of TOR-KI and SBI-756 priming ability of p190 cells towards apoptosis. (A) p190 cells were treated with either TOR-KI (MLN0128) or eIF4F inhibitor (SBI-756) and undergone BH3 profiling. Using cytochrome C loss quantification, we tested the priming of the p190 cells treated, compared to vehicle control. Peptides used during the analysis are indicted on the X axis. (B) Western blot analysis of p190 cells treated as indicated.

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evaluation of changes in expression levels of proteins that are known to be relying on eIF4F for their translation, such as proteins critical for metabolism, proliferation or cell-cycle progression.

Examples for those sensitive proteins include: cyclin D1, c-Myc, XIAP, cyclin B1, Cdc2 and cFlip 48–55. It is possible that apoptosis is not the only mechanism of cell death that is responsible for the reduced survival of cells tested, and thus other forms of cell death should be investigated

(e.g. necrosis or autophagy). (II) We suggest taking an unbiased approach of analyzing the translatome of p190 cells after treatment with eIF4F inhibitor and comparing it to vehicle treated cells (as described in details in chapter 2 for OCI-LY1 cells). (III) Primary B cells and neutrophils are sensitive to inhibition of translation, which in turn induces Bax/Bak-mediated apoptosis 56. However, it seems that translation inhibition does not affect MCL-1 expression much. Therefore, deeper investigation into the BCL-2 protein family with special attention to downstream apoptotic sensitizers and effectors following translation inhibition is needed. (IV) eIF2 is a heterotrimeric complex composed of eIF2α, eIF2β and eIF2γ 57. Interaction between tRNA and eIF2 can occur once eIF2γ subunit is bound to a GTP molecule, a process controlled by eIF2B that possesses a guanine-nucleotide exchange activity. Therefore, inhibition of tRNA interaction with eIF2 due to phosphorylation of the eIF2α subunit blocks protein synthesis 58.

Moreover, once the apoptotic program has been engaged, eIF2α itself becomes a caspase substrate. It is important to investigate eIF2α phosphorylation status among cells treated with

SBI-756 and its effect on protein synthesis and cytotoxicity.

Our work progresses the field of cancer biology via development of a novel and efficient way to genetically reduce eIF4E levels. Here we report the development and use of a conditional knockout mouse strain in which a floxed allele the Eif4e gene can be deleted following CreER activation by 4OHT. We used this novel system to generate BCR-ABL-driven p190 leukemia

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cells from Eif4e-flox and control mice. In p190 cells with one floxed allele (Eif4e-fl/+), addition of 4OHT reduced eIF4E expression levels by 30-40% after 72hr. In other experiments that our laboratory has performed using cells homozygous for the floxed allele (Eif4e-fl/fl), there was a

60-80% reduction in eIF4E expression after 4OHT addition (data not shown). Although these analyses indicate that deletion is not 100% efficient, the reduction in eIF4E protein expression had significant functional consequences. Specifically, we found that Eif4e-fl/+ p190 cells treated with 4OHT showed increased sensitivity to dasatinib killing. It would be interesting to use the

Cre-lox conditional knockout system to target other components of the eIF4F complex and explore other possible targets for cancer therapeutics.

In parallel to these genetic strategies, additional pharmacological approaches should be evaluated. For example, it is worth testing whether promising eIF4E antagonists (such as ones developed by eFFECTOR or Pfizer) which proved highly effective and tolerable will potentiate tyrosine kinase activity and sensitize to TKIs. Recently, a new class of eIF4A inhibitors named

“Rocaglates” have been identified and characterized 59. There is much interest in these compounds as several members of this family have been shown to possess potent anti-neoplastic activity in vitro and in vivo 59–62. Hence, synthetic rocaglate compounds have received considerable attention as cancer therapies, with at least one compound in clinical development 63–

65. Rocaglates have been shown to interfere with eIF4F release from the cap complex and exert a bystander effect to inhibit translation. It would be interesting to see whether rocaglates are able to sensitize Ph+ and Ph-like B-ALL to TKIs and induce apoptosis, as well as understanding of the molecular mechanism that is responsible for it remain to be investigated.

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Materials and Methods

Chemicals

We obtained rapamycin, dasatinib and MLN0128 from LC Laboratories (Woburn, MA, USA).

SBI-0640756 was synthesized as described66 or purchased from Selleck with comparable results.

Dimethyl sulfoxide (DMSO) was obtained from Fisher Scientific (Waltham, MA, USA). The rapalinks compounds E1035 and M1071 were kind gifts from Dr. Kevan Shokat from the

University of San Francisco, CA.

Cell culture

Mouse p190-transformed bone marrow (BM) were obtained by flushing BM cells from the long bones (tibias and femurs) of 3- to 4-wk-old mice. Cells were spinoculated with retroviral supernatant in the presence of 5 μg/ml polybrene for 45 min. at 450 x g and 37°C with RPMI20 culture media (see Supplemental Methods) supplemented with recombinant mouse IL-7 (10 ng/ml, R&D Systems) to promote cell cycle entry. For studies involving retroviral transduction of established p190 L-CFC, 2 x 106 cells in 1.5 ml of culture medium were mixed with 1.5 ml viral supernatant with 8 g/ml polybrene and spinoculated in 6 well plates at 37C for 45 min. at

450 x g. After incubation overnight at 37C, 5% CO2, cells were analyzed by flow cytometry as indicated and/or expanded into fresh culture medium.

Ph+ SUP-B15 human bone marrow cell line was purchased from ATCC. These cells were cultured in RPMI-1640 (Corning) supplemented with 10% heat-inactivated FBS, 10 mM

HEPES, 2 mM L-glutamine and 100 I.U./ml penicillin/streptomycin. Cells were grown in a

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humidified 37°C incubator with 5% CO2. Cells were routinely tested to ensure absence of mycoplasma and validated by STR profiling, and were maintained at or below 2x10e6 cells/ml.

MXP5, ICN1, and SFO2 are patient-derived Ph+ ALL cells…

Additionally, we created a stromal cell-independent Ph-like cell line (termed TVA1) from a PDX model as described in details before40. Primary cells were first cultured on OP9 stroma and maintained in the same medium (Alpha-MEM, 20% FBS, sodium-pyruvate, glutamax and penicillin/streptomycin) without stroma at 1 million cells/mL and passaged every 3–4 days. After over 20 passages, the authenticity of this cell line compared to the original sample was verified by short tandem repeat testing (data not shown). TVA1 cells expressed typical B-ALL markers (CD10+CD19+CD20+)

Immunoblotting

Cells were lysed in radio-immunoprecipitation assay buffer (150 mM NaCl, 1.0% IGEPAL®

CA- 630, 0.5% sodium deoxycholate, 0.1% SDS, and 50 mM Tris, pH 8.0, 2 mM EDTA, 50 mM

NaF) supplemented with protease inhibitor cocktail (Calbiochem, USA) and phosphatase inhibitor cocktails 2 and 3 (Sigma-Aldrich). Protein concentrations were normalized using a

Bradford protein assay (Bio-Rad, Hercules, CA). Lysates were prepared at 1 µg/µl concentration in 1X XT Sample Buffer (Bio-Rad) and 5% BME (Sigma-Aldrich). Lysates were run on 8-12%

Bis-Tris gels and transferred onto nitrocellulose membranes (Bio-Rad). Antibodies to the following phosphoproteins and total proteins were used: phospho-Akt (S473), Akt, phospho-rS6

(S240/244), phospho-BAD (S136), phospho-4E-BP1 (Thr 37/46), 4E-BP1, 4E-BP2, GAPDH,

Actin, MCL-1, BCL2, BCL2L1(BCL-xL), eIF4E, eIF4G1, BAX, BIM, PUMA, ERK1/2, and

BAD (Cell Signaling Technology, Beverly, MA, USA). We used the anti-mouse IgG and anti-

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rabbit IgG secondary HRP-conjugated antibodies from Promega (Madison, WI, USA). Antibody dilutions were performed according to the manufacturer’s instructions. Immunoreactive bands were visualized using Amersham ECL Prime Western Blotting Detection Reagent (GE

Healthcare Life Sciences) or Super Signal West Femto Maximum Sensitivity Substrate (Thermo

Fisher Scientific) and detected using a Nikon D700 SLR camera as described previously67.

Images were processed and densitometry was quantified using ImageJ software (NIH).

Cell viability

Cell viability assays were performed in 96-well U-bottom plates, with 6x10e4 cells in 200 µl.

Technologies). Cells were then analyzed on a FACSCalibur flow cytometer (Becton-Dickinson,

Colony Forming Assay

Cells were resuspended in primary media at 2 × 105 cells/condition with recombinant human

SCF, IL-7, IL-3, and FLT3 cytokines at 10 ng/mL (Thermo Fisher Scientific). Cells and inhibitors at the designated concentrations were then suspended in Methocult (StemCell

Technologies) and vortexed for 90 seconds prior to plating in duplicate in 24-well plates.

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Colonies were counted twice at 10–14 days after plating by two different people, and number of colonies per condition were averaged for the two counts.

Duolink Proximity Ligation Assay (PLA)

2x10e6 cells were treated for four hours with the treatments indicated. Following treatment, cells were washed with Phosphate Buffered Saline 1x (PBS) (Corning) and fixed with 4% paraformaldehyde (Thermo Fisher Scientific). Comet Slides (2 Well) (Trevigen, Gaithersburg,

MD) were pre-coated with Poly-L-Lysine 0.1% solution (Sigma Aldrich), and fixed cells were allowed to adhere for at least 20 minutes. Protocol of Duolink PLA was followed, as described previously68. Briefly: Cells were blocked using Duolink blocking solution, followed by probing with primary antibodies for the proteins of interest from two different origins (for eIF4G1, Cell signaling Technologies Cat. #2858, 1:200 dilution; for eIF4E, BD Biosciences Cat. #610269,

2.5µg/ml final). Cells were next incubated with Duolink In Situ PLA Probe Anti-Rabbit PLUS

Affinity purified Donkey anti-Rabbit IgG (H+L) (Cat. # DUO92002) and Duolink In Situ

PLA Probe Anti-Mouse MINUS Affinity purified Donkey anti-Mouse IgG (H+L) (Cat. #

DUO92004) and allowed to ligate using ligation mix (1:5 dilution). Next, amplification and washes were performed as instructed by manufacturer and the slides were mounted using media containing DAPI (Sigma Aldrich, DUO82040-5ML). Slides were images using Leica TCS SP8 confocal microscope. Signal obtained was quantified using ImageJ software, and normalized to the number of cells per field (using DAPI nuclei staining). Images shown indicate the signal

(Orange DuolinkTM) and nuclei for each field imaged, while graphs presented indicate ratio values of signal per cell in each field imaged.

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Puromycin Incorporation Assay

We performed puromycin incorporation assays in p190 eIF4E +/+ or p190 eIF4E fl/+. Cells were plated at 3 x 106 cells in 4 ml and treated with vehicle, 4OHT or cycloheximide for 16 hours.

Nascent peptide chains were labeled by incubating cells in 10 µg/ml puromycin (Sigma-Aldrich) for 15 minutes. Control cells were co-treated with 20 µM cycloheximide (Sigma-Aldrich) during puromycin labeling. We then fixed and permeabilized the cells (using eBiosci Foxp3-staining kit fix/perm buffer, eBioscience, San Diego, CA) and immune-stained them using anti-Puromycin

Alexa-Fluor 488nM conjugated antibody (Sigma Aldrich) together with Zombie violet viability kit (BioLegned, San Diego, CA). Next, we analyzed the puromycin incorporation of the cells using ACEA Novocyte 3000 flow cytometer (ACEA, San Diego, CA), while focusing on live, single cells.

BH3 profiling

BH3 profiling was performed as described previously69. Briefly, cells were pretreated for 16 hours with either DMSO or indicated compounds. Cells were then harvested and washed with phosphate-buffered saline and then incubated in trehalose-based buffer (300 mM trehalose, 10 mM Hepes, 80 mM potassium chloride, 1 mM EGTA, 1 mM EDTA, 0.1% bovine serum albumin, and 5 mM succinic acid) with 200 nM JC-1 (Life Technologies), 0.001 to 0.005% digitonin (Sigma-Aldrich), and oligomycin (10 g/ml; Sigma-Aldrich) with either DMSO or

BH3-only peptides for 60 min before analysis using a FACSCalibur (Becton Dickinson). The sequences and method of synthesis of BH3-only peptides were described previously70. The

PUMA2A peptide contains alanine substitutions that abolish its binding interactions with BCL2 family proteins and therefore served as a negative control. Percent depolarization caused by each

188

BH3-only peptide was calculated as the percent difference in the JC-1 red fluorescence (590 nm) relative to DMSO-treated control cells. Doses of peptides for each cell line were empirically chosen on the basis of minimal effects on mitochondrial depolarization (akin to an IC10 concentration).

Generation of Cell Lines with Inducible Expression of Wild Type 4E-BP1 or 5A Mutated 4E-BP1

To generate Ph+ p190 B-ALL cells with doxycycline-inducible expression of a gene of interest, we obtained mice that are either single of double transgenic (Rosa26-rtTA, or Rosa26- rtTA/TRE-4EBP1M). Next, we obtained BM cells and used retroviral transduction ofextablished p190 L-CFC, as described above. The wildtype (or mutant) 4E-BP1 expression was induced by addition of 1 µg/ml Doxycycline for 16–24 hrs. All pLVX-tight-puro plasmids were sequenced using the following primer, 5’-AGCTCGTTTAGTGAACCGTCAGATC-3’.

Generation of conditional knockout (cKO) eIF4E mice

We obtained cryopreserved sperm from mice with a conditional-ready allele of Eif4e, with exons

5 and 6 floxed, from the NorCOMM center in Toronto (affiliated with the Knockout Mouse

Consortium. See link: http://www.cmmr.ca/gene-detail.php?gene=MGI:95305). Following confirmation of the NorCOMM sperm, we reanimated this line performed breedings to obtain an allelic series with different gene dosage (+/+, +/Δ, Δ/Δ). This allelic series enables modeling od partial and complete inactivation of the targets. Moreover, the cKO approach allows tissue- specific and temporal control of endogenous gene function, and overcome the issue that Eif4e- null homozygous mutations are early embryonic lethal71. Another important advantage of cKO

189

models is that Cre-mediated deletion mimics acute inactivation or removal of eIF4E or eIF4G1 protein, as could potentially be achieved using emerging protein-specific degrader technology 72.

Mice Strain and Compounds Administration in vivo

C57BL/J mice were purchased from the Jackson Laboratory (Bar Harbor, ME) and irradiated

(400 centi-gray) for enabling foreign BM cells engraftment. Mouse p190-transformed BM cells were used to initiate leukemia among the irradiated mice via intravenous injection of 0.8 x 106 cells per mouse. In all in vivo experiments p190 transformed BM was prepared fresh (< 4 week old cultures) to initiate leukemia. Leukemic engraftment was determined in anesthetized animals by retro-orbital bleeds and analyzed by flow cytometry where indicated. Once leukemic engraftment was obtained, each mouse was treated for five consecutive days as indiated. Mice were euthanized as judged by signs of extreme hunched posture with piloerection, labored breathing, or weight loss.

Statistical analysis

The number “n” of biological replicates for each experiment is indicated in the figure legends.

190

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Chapter 4 Significance, Discussion and Future Directions

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Premise and Significance

The significance and premise of work in the Fruman lab is to advance understanding of molecular mechanisms that drive both normal lymphocyte proliferation and differentiation, as well as progression of malignancies. Only through advancement of this knowledge will we be able to offer better therapeutic strategies and develop novel compounds to serve our communities. Below are some examples that show the significance of the work in this thesis:

• In this project we have established the interaction of eIF4E:eIF4G1 as a quantifiable and

reliable readout for mTOR signaling, that can be targeted (via different agents) for

therapeutic development in B-cell malignancies.

• We have pioneered the evaluation of first-in-class eIF4G1 antagonist SBI-756 in blood

cancer models. The use of SBI-756 as an eIF4F inhibitor was first reported in a melanoma

system and showed great potential for suppressing melanoma progression and overcoming

resistance to BRAF inhibitors 1. In this research work, we have expanded the use of SBI-756

from solid tumors to blood malignancies, while covering both NHL and ALL systems.

Combination therapy involving SBI-756 is capable of specifically targeting the translation

initiation machinery (eIF4F complex) of B lymphoid cells and sensitizing them to venetoclax

(BCL2 inhibitor) in NHL and dasatinib (BCR-ABL inhibitor) in B-ALL. Moreover, using

advanced genetic tools, we have created NHL cells that are lacking 4E-BPs. Despite similar

cell lines being reported earlier by other groups, we are the first group to exploit those novel

genetically edited clones of NHL cells to pinpoint the effects of mTOR inhibitors and

compare them to eIF4F inhibitors.

• Conditional knockouts of mTOR and raptor have enabled broad progress in understanding

the functions of mTORC1 in B and T cells2–10. To our knowledge, we are the first group to

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have established conditional knockout mice to determine the cell-intrinsic and temporal

functions of eIF4E. These mice are crucial to the next wave of understanding of mTORC1

signaling networks in normal tissues and tumor cells, opening new research horizons in the

study of translation initiation in both normal and malignant biology.

• In this work, we have gathered evidence that enables us to suggest a mechanism for

sensitization to venetoclax via eIF4F inhibitors in general and SBI-756 specifically, via

suppression of cap-dependent translation which leads to reduction in ribosomal biogenesis.

Despite much research performed to identify molecular targets that could be targeted to

reduce blood cancers’ survival, no single model has been offered. In this work, we suggest

that targeting eIF4F via SBI-756 (or reduced eIF4E availability) causes reduced cap-

dependent translation which in turn reduces ribosomal biogenesis due to reduced production

of ribosomal components. This phenomenon leads to suppression of total protein synthesis.

Previous work has already established much reliance of blood cancers on cap-dependent

translation to support their survival and proliferation, and thus it is not surprising that

suppression of ribosomal biogenesis sensitizes the tumors tested to venetoclax.

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Discussion and future directions

mTOR is a central regulator of cell growth and proliferation, and an important target for therapeutics in cancer and other diseases11. The therapeutic rationale for using mTOR pathway inhibitors is well established, and indeed, several compounds have been developed to target the mTOR complex, or specific components of it. However, their therapeutic potential is limited due to several factors, including toxicity 12–15, compensatory survival signaling 16–18, evolution of mTOR resistance mutations 19,20, and suppression of T-cell function 21. Hence, new therapeutic strategies are needed to overcome these caveats, and indeed one of the main goals of this work is to evaluate novel therapeutic strategies and compare them to the current ones.

In chapter 2 of this work, we presented experiments showing great premise for sensitization of NHL cells to venetoclax by combining with SBI-756. We found that SBI-756 inhibited cap-dependent translation and eIF4E:eIF4G1 interaction in the nanomolar range and sensitized several DLBCL and MCL cell lines to venetoclax. SBI-756 enhanced cytotoxicity to a greater extent than the TOR-KI compound MLN0128, yet maintained mTOR substrate phosphorylation, suggesting that mTOR retains its regulation of the essential cellular processes.

Moreover, the sensitization to venetoclax by SBI-756 was observed both in vitro and in vivo, and involved suppression of ribosomal biogenesis which led to reduction in pro-survival factors expression (apoptosis GO group from polysome profiling), as well as ribosome components as well. Those findings suggest that targeting eIF4F may prove more tolerable than targeting mTOR, indicating potential clinical relevance and need for further investigation. In a DLBCL xenograft model, SBI-756 was well tolerated and caused tumor regression when combined with venetoclax.

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An advantage of SBI-756 compared to TOR-KI treatment is its ability to suppress cap- dependent translation among DLBCL cells lacking 4E-BP1. Cancer cells that lack 4E-BP1 have been described among blood cancers22–25, prostate cancer23,26, pancreatic cancer27, head and neck cancers28, breast cancers29,30 and others31. In our study, we investigated DLBCL cells that lack

4E-BP1 either naturally22 or that were engineered to lack 4E-BP1. We were able to show that among cells lacking 4E-BP1, TOR-KIs lost their efficacy to suppress eIF4F formation and sensitization to venetoclax, while SBI-756 retained its cytotoxic activity in vitro. To confirm the distinct dependence of 4E-BPs in vivo, I suggest evaluating TOR-KIs vs. eIF4F inhibitors in treatment of 4E-BP1 lacking cells in vivo. To accomplish that aim, I suggest injecting subcutaneously WT OCI-LY1 to a mouse, and 4E-BP1 KO OCI-LY1 cells (obtained and described in chapter 2) to the same mouse on the other flank. These mice will then be divided into treatment groups: vehicle, TOR-KI, SBI-756 alone or together with venetoclax. I expect that among 4E-BP1 lacking tumors, TOR-KI will sensitize to venetoclax very little, if anything. I would expect SBI-756 to retain its effects – sensitizing to venetoclax while preventing eIF4E:eIF4G1 interaction.

Treatment with venetoclax can lead to the development of resistance through the upregulation of alternative antiapoptotic proteins. FL cells treated with venetoclax developed resistance associated with the upregulation of MCL-1 and, conversely, loss of MCL-1 sensitized

NHL to BCL2 inhibition with venetoclax32,33. AML cell lines conditioned for venetoclax resistance developed a dependence for MCL-1 and, to a lesser degree, BCL-xL (BCL2L1)34.

Elevated MCL-1 protein levels, specifically, have been noted in the setting of resistance to cytotoxic therapies and to therapies targeting BCL2/BCL-xL in myelodysplastic syndrome35, and venetoclax treatment failure most strongly correlated with elevated MCL-1 protein in a clinical

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trial of relapsed and refractory AML36,37. Given these findings, it would be interesting to test the ability of SBI-756 to sensitize NHL to other BH3 mimetics in general and MCL-1 inhibitors is particular. Several promising MCL-1 inhibitors have been reported and proved tolerable in preclinical studies, including: AMG 176, VU661013, A-1210477 and S63845 38–40. Indeed,

S63845 potently kills MCL1-dependent cancer cells, such as: multiple myeloma, leukemia and lymphoma cells. Given the importance of MCL-1 (and BCL-xL) for many lymphocytes, and B- cells in particular, it is very likely that targeting the eIF4F complex would synergize together with MCL-1 inhibition (see preliminary results in chapter 2).

Trying to decipher the molecular mechanism through which SBI-756 sensitizes blood cancers to targeted agents, we took two different approaches: unbiased polysome profiling as well as a candidate approach. The polysome profiling performed suggests that eIF4F suppression via SBI-756 treatment reduces the translation efficacy of many mRNAs involved in RNA processing and translation. Using a panel of DLBCL cell lines that are sensitive or resistant to

SBI-756 cytotoxicity, we observed a correlation of protein synthesis inhibition and cell death.

Certain survival proteins heavily rely on eIF4F-dependent translation for their production; these include MCL-141–47, BCL-xL43,48–50, Myc51–53, eIF2α54–57 and ATF458–60. Other proteins that depend on eIF4F function and drive cellular transformation, tumorigenesis, and malignant progression include: CCDN1/3, SNAIL, MMP3, PRPS261,62. The polysome profiling dataset that we gathered from OCI-LY1 cells did not definitively establish acute effects of SBI-

756 on translation efficiency of these survival factors. I believe that a further and deeper investigation is needed to decipher the broader proteome changes through which suppression of eIF4F complex assembly reduces viability and sensitizes to targeted agents. To this end, we have collaborated with Dr. Paul Gershon (UC Irvine) to initiate a study using high resolution mass

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spectrometry in which we profile the proteome of DLBCL cells treated with vehicle compared to cells treated with SBI-756 for 4hr. Despite initial challenges that slowed down the progress of this project, we anticipate initial analyses in the near future which will help us understand the cellular pathways altered by eIF4F suppression. Combining the results from proteomic and polysome profiling analyses, we can correlate the datasets obtained and determine which of the differences that we observe in the actively translated mRNAs are also detected in the protein expression.

As part of our investigation of the mechanism of apoptotic sensitization, we identified a reduction in MCL-1, BCL-xL, survivin, eIF4E and eIF4G1 among OCI-LY1 cells treated with

Figure 4.1: Strategies for evading apoptosis. Evading apoptosis is a hallmark of cancer, as such there are many strategies that cancer cells use to achieve this. For example, cancers can silence apoptotic activators (option 1) or effectors (option 2) to limit induction of MOMP. Alternatively, some cancers over-express anti- apoptotic factors to prevent BAX/BAK activation (option 3).

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SBI-756 - detailed in chapter 2 (Fig. 4.1). We could not confirm translational control in our polysome profiling analysis, yet this could have been the results of the time point that we chose to analyze. While protein expression was reduced, mRNA levels were unchanged suggesting translational control. Following up on reports describing a direct connection between 5’ UTR motifs and cap-dependent translation of oncogenes63, I would like to further investigate the molecular mechanism by which SBI-756 affects translation of these factors. In order to evaluate the relevance of candidates identified here as regulated by cap-dependent translation (e.g. MCL-

1, BCL-xL, survivin, eIF4E or eIF4G1), I would suggest the following approaches:

1. Overexpress the oncogenes and survival factors identified with their endogenous 5’UTR, or

with versions where the 5’ UTR was replaced with a version that is no longer relying on cap-

dependent translation (e.g. lack the 5’ UTR in general and CERT motifs specifically). Next,

we will test the viability of the cells following exposure to SBI-756 (or other eIF4F inhibitor)

and test the response of the cells to the inhibitors. We would expect some rescue of the cells

expressing the altered proteins as their translation is no longer inhibited by the drug.

2. Clone the 5’ UTR of oncogenes and survival factors upstream of luciferase reporter genes,

which will enable quantification of the expression levels. Next, I suggest using transient

transfections to examine sensitivity of the 5’ UTR to inhibition of either mTORC1

specifically (e.g. Rapalink-1) or eIF4F (e.g. SBI-756).

To test the importance of survivin downregulation, one approach would be a combination treatment with venetoclax and YM155, a small molecule inhibitor of survivin. YM155 potently inhibited the viability of immortalized and patient-derived renal cell carcinoma (RCC) cell lines64. In RCC cells YM155 diminished the transcription of survivin which led to retention of

NF-κB heterodimers in the cytosol. This activity suggests that YM155 could be used to treat

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cancers that rely on NF-κB signaling to support their survival, such as MCL or ABC-DLBCL64–

68. In addition, in multiple myeloma (MM) cells, YM155 inhibited cell growth and rapidly directed Mcl-1 protein for proteasome degradation. Moreover, it abrogated interleukin-6-induced

STAT3 phosphorylation, subsequently blocked MCL-1 expression and induced apoptosis in MM cells69,70. YM155 also synergized with STAT3 inhibitors (AG490 and STA-21) and induced apoptosis in DLBCL cell lines. Taken together, these reports suggest the possible therapeutic strategy of combining a survivin inhibitor like YM155 with venetoclax. Alternatively, combination of venetoclax and SBI-756 have been shown to reduce survivin and thus the two approaches result in reduced survivin functionality among the malignant cells. Those combinations are expected to suppress BCL2 pro-survival activity, while reducing MCL-1 an alternative survival protein.

SBI-756 is a tool compound that needs further optimization to be a candidate for clinical development. For example, treatment with higher concentrations of SBI-756 (750 nM or greater) did cause inhibition of the mTOR pathway (data not shown). This finding suggests that there is a narrow range of concentrations at which SBI-756 has selective on-target effects. These caveats urge future efforts to optimize the selectivity of SBI-756 and similar agents.

Even though we did not observe changes in mTOR signaling in cells treated with SBI-

756 concentrations between 100 – 500 nM, we considered the possibility that other off-target effects occur at these concentrations. Providing indirect support for drug selectivity, we observed that in OCI-LY1 cells selected for resistance to SBI-756, there was an apparent increase in expression of eIF4E (data produced by a rotation student, Giulia Giammo). In addition, we showed in Chapter 2 that the eIF4E:eIF4G interaction is less affected by SBI-756 in these resistant cells. To address more directly the selectivity of SBI-756, we attempted to overexpress

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eIF4E or eIF4G1 in OCI-LY1 cells. Although we tried different vectors to deliver these constructs to the cell line, we were not able to isolate clones with overexpression of the test cDNAs. Future efforts could employ CRISPR activation to increase expression of the endogenous genes of interest. The prediction is that overexpression of eIF4F components would decrease sensitivity to SBI-756 if the effects are on-target via eIF4F disruption. We can conduct similar experiments to increase expression levels of MCL-1, BCL-xL or survivin in OCI-LY1 cells and test whether this reduces sensitivity to SBI-756. Alternatively, we can aim to reduce expression levels of eIF4E, eIF4G, BCL-xL, MCL-1 or survivin and test whether the cells become more sensitive to eIF4F inhibitor.

We have made initial efforts to test SBI-756/venetoclax combinations in additional blood cancers, such as acute myeloid leukemia (AML). AML is a blood cancer in which the bone marrow makes abnormal myeloblasts, red blood cells, or platelets. Acquisition of resistance to venetoclax is the main cause of treatment failure in venetoclax-based AML treatment approaches. Intrinsic resistance in AML cells is attributed to increased levels of MCL-1 and/or

BCL-xL, which lead to sequestration of pro-apoptotic proteins that are released from BCL2 upon venetoclax treatment. We tested the ability of TOR-KI and SBI-756 to sensitize to venetoclax among two AML cell lines: OCI-AML2 (contains mutations in driver genes such as DNMT3A, and high p53 expression levels) and MOLM-13 (contains MLL gene rearrangement arising via chromosomal insertion, as well as other common trisomies). These cell lines represent two of the subtypes of AML, characterized by the factors that affect the prognosis and treatment of each subtypes. Indeed, we have observed interesting findings among those cells (Fig. 4.3):

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• High concentrations of the TOR-KI compound MLN0128 (≥ 30nM) were required to

sensitize to venetoclax.

• Compared to OCI-LY1 cells, higher concentrations of SBI-756 were required to sensitize

AML cell lines to venetoclax. These results may indicate a difference in reliance on

eIF4F-dependent translation among the cells for expression of survival factors, which is

supported by the reports of reduced eIF4E phosphorylation inducing apoptosis only

slightly among AML cells61,71–74.

• In several tests performed, a significant reduction in eIF4F-dependent translation was

observed following treatments with either TOR-KI or SBI-756, compared to IRES-

dependent translation. It is worth mentioning that higher concentrations of TOR-KI or

SBI-756 were needed to reduce translation among AML cells than among DLBCL,

which may indicate different reliance on mTOR/eIF4E axis to facilitate translation.

• It would be interesting to see whether the sensitization we observed stems from a p53

regulation of MEK/ERK pathway which induces MCL-1 phosphorylation and

degradation. p53 negative regulation of MEK/ERK pathway has been reported to activate

GSK3 to modulate MCL-1 phosphorylation and promote its degradation, thus

overcoming AML resistance to BCL2 inhibition75–77. SBI-756 might alter p53 function

due to interference with one of the main end point targets of the MEK/ERK pathway,

eIF4E, and thus reduction in p53 functionality. In turn, BCL2 inhibition enables

overcoming apoptosis resistance to p53 activation by switching cellular response from

G1 arrest to apoptosis. It is possible that targeting MEK/ERK pathway (e.g. L-783,27778)

or GSK3 itself would prove beneficial for AML patients and may even synergize with

venetoclax or BH3 mimetics.

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Figure 4.2: TOR-KI and SBI-756 treatments sensitize AML cells to venetoclax combination. (A) Viability of AML2 and MOLM13 cells treated for 48 hours with increasing venetoclax concentrations in combination with vehicle (DMSO) control or various inhibitors as indicated. Viability was assessed using Annexin V and PI staining. *p<0.05; **p<0.01; ****p<0.001. (B) AML2 or MOLM13 cells were introduced the dual-luciferase reporter in which 5’ cap-dependent untranslated region (5’-UTR) was conjoined to a Renilla (Renilla reniformis) luciferase reporter, while the Internal Ribosomal Entry Site (IRES) was conjoined to a firefly (Photinus pyralis) luciferase reporter92,93. Cells were treated for 16 hours with vehicle (DMSO) or increasing concentrations of MLN0128 or SBI- 756. The ratio of Renilla/firefly luciferases was calculated for each of the conditions, indicating the relative cap- dependent translation. *p<0.05, **p<0.01, ***p<0.005. One-sample t-test vs. DMSO control. n = 3.

Recent reports have offered a novel mechanism of venetoclax resistance by genomic deletion of BAX in resistant AML cell lines79. BAX is an essential gateway to mitochondrial apoptosis, and as a result of BAX gene deletion, the inhibitors of BCL2, BCL-xL, and MCL-1 are rendered ineffective in inducing apoptosis. Another interesting report used a CRISPR/Cas9 screening and have identified 234 candidate genes that may yield venetoclax resistance among

AML cells. Indeed, among those genes TP53, BAX, and PMAIP1 (encoding NOXA) were identified as key genes whose inactivation establishes resistance, centering on regulation of the mitochondrial apoptotic network as a mechanism of controlling drug sensitivity. p53 acts a

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sensor of cellular stress and transcriptional regulator of several proapoptotic genes; TFDP1 activates and translocate NOXA into the mitochondria; NOXA is a BH3-only protein that promotes activation of the apoptotic program; and BAX/BAK function as its effectors. Other candidate genes indicated an enrichment in genes involved in mitochondrial processes, such as apoptosis transcriptional regulation (TP53 and TFDP180,81) and apoptosis sensitization [PMAIP1

(NOXA)82], genes required for mitochondrial membrane pore formation (BAX, BAK, SLC25A6, and TMEM14A80,81), and additional genes involved in apoptosis (proapoptotic BNIP3L83). An interesting approach would be generating AML cells that lack NOXA, BAX, p53, or combinations of them (for instance via genome editing), and compare their sensitivity to eIF4F inhibitors to WT cells (not altered). This approach could teach us more about the molecular mechanisms that induce the resistance to venetoclax, and whether or not those could be overcome by use of eIF4F inhibitors. Nevertheless, alternative mechanisms of apoptosis induction need to be explored to overcome BAX deletion-induced resistance.

One critical advantage of SBI-756 is that it is not cytotoxic to essential cellular mediators of immune function and immunotherapy efficacy (T cells and NK cells). When human PBMCs were treated with either TOR-KI or SBI-756, the only cells that were found sensitive to the treatment were B lymphocytes. The viability of CD4+ T cell, CD8+ T cells, NK cells or monocytes was not reduced by SBI-756 at the concentration and time point tested. This difference in cytotoxicity may stem from lymphocytes’ reliance on different anti-apoptotic proteins to support their survival. For instance, B lymphocytes may rely on both BCL2 and

MCL-1 anti-apoptotic factors for supporting their survival, while T cells or monocytes rely mostly on BCL2 84. While MCL-1 is known to depend mostly on cap (eIF4F)-dependent translation for its expression, BCL2 relies mostly on internal ribosome entry site (IRES)-

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dependent translation. Due to its specific mechanism of action that targets the eIF4F complex, it is not surprising that eIF4F-dependent translation will be suppressed, and thus MCL-1 expression will be reduced. An interesting way to test this idea is by treating PBMCs with TOR-

KIs or eIF4F inhibitors for various times. The treated cells would then be analyzed via multiplex single-cell flow cytometry (CyTOF) analysis that can distinguish whether MCL-1 levels are selectively reduced in different lymphocyte populations within the PBMCs. This system is now available at UC Irvine.

A complementary approach would be to purify primary B cells (e.g. using EasySep™

Human B Cell Isolation Kit) and profile them after various drug treatments by Western blot to detect expression of pro-survival factors (e.g. MCL-1, BCL2, BCL-xL etc.). Comparisons will be made between isolated primary B cells treated with eIF4F inhibitor to non-treated cells, primary

B cells and other PBMCs (e.g. CD4+ T cells). Alternatively, high resolution mass spectrometry could be used to obtain proteome-wide data. In this case, primary B cells will be purified and treated with the drug treatments mentioned for 24 hours, followed by high-level mass spectrometry (LC-MS/MS) together with HPLC systems to perform analysis of biomolecules and protein analyses. These protein identification and proteomics are important new tools in cancer research, and these comparisons will teach us about the pro-survival mechanisms that support B cells, and how these are suppressed by SBI-756.

In chapter 3 of this work, we evaluated the option of targeting the eIF4F complex in order to sensitize B-ALL cells to targeted agents. By using chemical inhibitors (Silvestrol and SBI-

756) and two genetic approaches, we observe suppression of eIF4F function which in turn sensitize human Ph+ and Ph-like B-ALL cells to dasatinib. Moreover, we found that among human PBMC subsets, B lymphocytes were the only cells sensitive to the cytotoxic effects of

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SBI-756 in vitro. Our results indicate that targeting eIF4F holds promising for enhancing the anti-leukemic efficacy of TKIs such as dasatinib.

In chapters 2 and 3 we evaluated the ability of SBI-756 to sensitize NHL or BCR-ABL+

B-ALL to targeted agents in vivo. In the case of NHL cells, we used OCI-LY1 cells injected subcutaneously in NSG mice (Chapter 2). In this model observed that 5 days of treatment with

SBI-756 (at 25 mg/kg) sensitized to venetoclax in vivo and reduced tumor progression dramatically compared not only to placebo but also to each drug by itself. Importantly, we verified the pharmacodynamic effect of SBI-756 in this system by showing a significant reduction in eIF4E:eIF4G1 interaction in the tumor cells, whereas mTOR substrate phosphorylation was not altered. In the case of B-ALL, we used BCR-ABL-dependent p190 cells injected i.v. into syngeneic mice (Chapter 3). In this model, we did not observe a significant anti- leukemia effect of SBI-756 or enhancement of the effect of dasatinib. It is possible that the lack of efficacy in this model was due to a lower dose of SBI-756 (10 mg/kg/day), which we chose based on a pilot study. However, this dose was sufficient to significantly reduce the eIF4E:eIF4G1 interaction in bone marrow cells from SBI-756-treated animals compared to controls. Taken together, our findings indicate some promise but additional development necessary to employ eIF4F disrupting molecules to sensitize to targeted agents in animal models.

The use of newer SBI-756 analogs (or other eIF4F inhibitors), as well as adjustments of doses may help us target the therapeutic window better and achieve optimal pharmacological properties while sustaining tolerability.

A question that arises from the OCI-LY1 model relates to the sustainability of targeting eIF4F complex and whether this synergy remains over time. Our experiments were limited to

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treating the mice for maximum of five consecutive days due to disease progression of the control groups and costs of materials required. Future studies are required to decipher:

• Are there any changes in production of either eIF4E or other eIF4F components due to the

treatment in vivo? We observed reduction in eIF4E and eIF4G1 expression by SBI-756 in

vitro, which may indicate on a feed-forward mechanism. Therefore, it would be interesting

to see how would eIF4F complex suppression affect expression of its components over

time.

• Does eIF4E:eIF4G1 interaction disruption remain longer than 5 days, become more severe

with time or rather is overcome somehow? A possible scenario includes a reduction in

eIF4E and/or eIF4G1 components due to the feed-forward mechanism described in a

transient manner which lasts as long as the drug is administered. However, since the cells

might have other mechanisms to overcome eIF4F complex suppression, or use of eIF4E or

eIF4G isoforms that have been described85–88, it is possible that they are selected to use

those once the alternative is suppressed. Moreover, cells that were selected for SBI-756

resistance (e.g. OCI-LY1 cells described in chapter 2) could also alter eIF4E or eIF4G1

expression levels to adjust with eIF4F suppression and worth exploring further. Among the

main components of the eIF4F complex are eIF4E (cap-binding protein) and eIF4G

(scaffold protein) - each of which has three known homologs (numbered 1, 2, and 3,

respectively)85 (Fig. 4.2). The basal eIF4F variant contains eIF4G1 and eIF4E1, and

produces the normoxic translatome, yet under hypoxic conditions, when eIF4F is inhibited,

cells activate the hypoxic eIF4F (eIF4FH) to produce an adaptive, cap-dependent hypoxic

translatome. On the other hand, other stimuli, such as those regulating MNK activity, can

potentially activate eIF4E3-containing eIF4F variants (eIF4FM) to produce a stimulus-

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specific, cap-dependent translatome63,71,85,89–91. Therefore it is possible that while SBI-756 prevents the interaction of eIF4E1 with eIF4G185, it might not be able to suppress the interaction between eIF4E2 or eIF4E3 with eIF4G1 or eIF4G3. Although those interactions are less prevalent, it is possible that the cells adapt to use those isoforms when the main complex is suppressed. This can be tested by use of specific antibodies to the different isoforms and using PLA to profile the interactions occurring in the cells following SBI-756 treatment. I suggest supplementing this method with high resolution mass-spectrometry to profile the cells following treatment and learn about the expression levels of the different isoforms.

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Figure 4.3: eIF4F variants reprogram the cellular translatome in response to distinct stimuli. (Top panel) eIF4F- mediated cap-dependent translation in humans involves three major components, eIF4E (cap-binding protein), eIF4G (scaffold protein), and eIF4A (ATP-dependent RNA helicase), each of which has three known homologs (numbered 1, 2, and 3, respectively). Permutations of homolog-specific interactions facilitate adaptation to various stimuli through translatome reprogramming. (Bottom left panel) The basal eIF4F variant contains eIF4G1 and eIF4E1, and produces the normoxic translatome. (Bottom middle panel) Under hypoxic conditions, when eIF4F is inhibited, cells activate the hypoxic eIF4F, eIF4FH, to produce an adaptive, cap-dependent hypoxic translatome. (Bottom right panel) Other stimuli, such as those regulating MNK activity, can potentially activate eIF4E3-containing eIF4F variants (eIF4FM) to produce a stimulus-specific, cap-dependent translatome. The differential utilization of eIF4A variants in distinct eIF4F complexes remains to be tested. Adapted from: Ho J.D.D., and Lee S. (2016). Trends in Biochemical Sciences. Volume 41, Issue 10, 821-823.

• Does eIF4F complex disruption leads the cells to exploit alternative translation mechanisms

that do not rely on eIF4E:eIF4G1 interaction? Coots et al. showed that eIF4F inhibition

partially represses global protein synthesis92. This report matches our findings that among

most of the NHL cells tested (e.g. OCI-LY1) suppression of eIF4F complex assembly

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reduced protein synthesis in general and cap-dependent translation specifically. Moreover, it is possible that the SBI-756 resistance cells that we have selected for (chapter 2) may exploit those alternative translation pathways to overcome eIF4F suppression. Interestingly, different cellular pathways have been suggested to rely on various translation methods: cell cycle and growth are associated with IRES-dependent translation93–95, cell maintenance and metabolism with N6-methyladenosine (m6A)-dependent translation92,96–98, while cell survival and metabolism are associated with eIF4F-dependent translation92. The differences in regulation of these processes seem to stem from structural and molecular modifications that dictate loading of different translational factors, that in turn induce translation of transcription factors (among others) which drive the cells during the process. Among the most abundant internal transcriptional modification, m6A modification has a tremendous effect on RNA production/metabolism and participates in the pathogenesis of multiple diseases including cancers92,99,100. Installed by the m6A methyltransferases (METTL3/14,

WTAP, RBM15/15B and KIAA1429, termed as “writers”), m6A in the 5’UTR causes

RNA stabilization and initiation of translation via facilitation of eIF4F-independent mRNA translation. Moreover, it was found the mTORC1 is required for m6A methylation as mTORC1 inhibition reduced global m6A methylation levels and WTAP functionality.

These results suggest that upon suppression of eIF4F translation (e.g. by SBI-756), the cell may turn to alternative mechanisms to facilitate translation (either via m6A or IRES dependent mechanisms). In particular, this kind of switch has been suggested in the context of critical oncogenes and survival factors, such as HIF1, cMyc, VEGF, BCL2,

BCL696,99,101,102. Moreover, m6A mRNA methylation has been shown to regulate AKT activity to promote the proliferation and tumorigenicity of certain cancers103. Nevertheless,

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the exact targets of mTORC1 that are regulated via m6A methylation remain to be

determined via a high throughput assay (e.g. miCLIP).

Among the most important tools developed in this project is the eIF4E conditional knock out system described in chapter 3. This system enables us to regulate the expression levels of eIF4E, based on exposure of cells to 4-Hydroxytamoxifen (4OHT). In this system, exons 5 and 6 of the Eif4e gene are flanked by loxP sites, allowing inactivation of the cap-binding protein eIF4E in cells expressing active Cre recombinase. By using a mouse strain (Rosa26-CreER) in which Cre is expressed in all tissues but maintained inactive in the cytoplasm via fusion to the estrogen receptor (ER) hormone binding domain, we can induce deletion in any cells of interest by adding 4OHT to release and activate Cre (Fig. 4.4). To our knowledge, this is the first genetic tool developed that enables conditional deletion of one or both alleles of Eif4e to study the eIF4F complex. The Fruman lab has also commissioned the UCI Transgenic Mouse Facility to produce a conditional Eif4g1 knock out mouse, an effort that is still in progress and we expect will be completed shortly.

Figure 4.4: Schematic diagram of the genetic model that enables conditional reduction in eIF4E expression. We established a conditional knockout system for controlling eIF4E expression levels, which is based on Cre- recombinase and LoxP sites floxing exons 5 and 6 of Eif4e gene. Panel 1 shows a brief summary of the breedings that we performed to establish this system. Panel 2 shows a schematic diagram of floxed Eif4e tm1c allele from NorCOMM.

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Using these novel genetic models to reduce expression of different eIF4F components, the following goals are achievable:

1. Learning the requirements of eIF4F complex in general and either eIF4E or eIF4G1

specifically among the different stages of lymphocyte differentiation. For example, we can

use strains in which we can conditionally delete genes: among early B cell development

using MB1-Cre, or among mature B cells using CD21-Cre, or in mature B cell activation

using Cgamma1-Cre.

2. Identifying reliance of different malignant cells on specific components of the eIF4F

complex, and tailor therapeutic strategies based of that reliance. We will use mouse leukemia

or lymphoma models to test eIF4F targeting ability to sensitize to targeted agents.

Considering the results described in chapter 2, I suggest focusing on DLBCL mouse model in

particular. One example is the transgenic murine model MYC-BCL2104,105 which our lab is

experienced with. An advantage of this model is the partial sensitivity to venetoclax, yet

MYC-driven cancers might not be sensitive to eIF4F complex disruption. Another

suggestions may be to use a model expressing active AKT and BCL2, where we can test the

sensitivity to venetoclax among mice with mTORC1 activation.

3. The effect of acute deletion of eIF4F constituents can be compared to the effects of specific

inhibitors of different components of the eIF4F complex. These inhibitors include SBI-756 as

well as various eIF4E and eIF4A antagonists that are in advanced preclinical studies or even

clinical trials. Among those molecules are:  Zotatifin (eFT226) that was developed by the

eFFECTOR company. This inhibitor was proven effective in preclinical models of receptor

tyrosine kinase (RTK) driven cancers. Zotatifin reduces RTK protein levels and connects

with AKT and MAPK signaling, thus leading to anti-tumor activity in FGFR1, FGFR2 and

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HER2 driven models. Deeper investigation of predictive markers of sensitivity or resistance

showed that RTK tumor models with mTOR mediated activation of eIF4A are most sensitive

to zotatifin. Importantly, a Phase 1/2 clinical trial of zotatifin in patients with KRAS- or

RTK-mutant solid tumors is ongoing (NCT04092673)106.  Recently, eFFECTOR reported

that it has received an exclusive worldwide license and collaboration agreement to develop

small-molecule inhibitors of eIF4E with substantial funding from Pfizer company. Our

laboratory is currently negotiating with Pfizer to obtain eIF4E inhibitor tool compounds to

compare with conditional eIF4E deletion in leukemia cells and normal lymphocytes.

Chemical disruption of the eIF4E:eIF4G association with SBI-756 is mechanistically distinct from genetic depletion of eIF4E or eIF4G proteins. To produce a more accurate genetic model of chemical inhibition, we can modify specific amino acids involved in the binding of eIF4F components. The molecular interactions between eIF4E and 4E-BP1 or eIF4E and eIF4G have been thoroughly investigated and reported107. Indeed, crystal structures of eIF4E:eIF4G complexes indicated lateral contacts of eIF4E, with stronger lateral binding with 4E-BPs that enables their inhibitory effects and displace eIF4G from eIF4E. Knowing the specific amino acids responsible for the interactions enables us to use CRISPR site-directed mutagenesis of these amino acids (e.g. into alanine) and test the effects of these alterations on the interactions with 4E-BPs or eIF4G. Among cells that are knocked out for the proteins of interest, I aim to express (add back) the mutant versions of them. I suggest performing single point mutations at first, and later on advance to double or triple mutations. I expect the changes in those canonical amino acids to reduce binding drastically, and that double or triple mutations to reduce it drastically (or abolish it altogether).

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Rapalinks are third generation of mTOR inhibitor compounds developed to specifically target mTORC1. Rapalinks exploit the high affinity and selectivity of rapamycin binding to the

FRB domain of mTORC1 together with ATP-competitive inhibition provided by the linked

TOR-KI moiety 108. The first compound reported by Shokat and colleagues, named Rapalink-1, was found to overcome mTOR mutations that lead to resistance and showed promise when evaluated in breast cancer and glioma cell lines109. Chapter 3 of this thesis presents data showing that two rapalink compounds (provided by the Shokat group) could sensitize p190 cells to dasatinib. At concentrations that selectively inhibit mTORC1, these compounds had similar cytotoxic activity as the dual mTORC1/mTORC2 inhibitor MLN0128. I have initiated studies comparing Rapalink-1 (M1071) with SBI-756 in DLBCL cell lines. To better distinguish how mRNA translation is regulated by mTORC1 vs. eIF4F, I suggest performing polysome profiling for cells treated with Rapalink-1, and comparing the global changes in translation efficiency to vehicle treated, or SBI-756 treated cells. Once specific mRNA that are bound by ribosomes are identified, they will be considered as “candidates” for supporting survival and regulated by mTORC1. Another way to profile those cells is to use high-resolution mass spectrometry to achieve a broad and detailed understanding about protein expression among those cells. We can use these methods (or others) to characterize the pro-survival factors, metabolism drivers, tumor microenvironment and proliferation indicators that drive the blood malignancies and compare them to normal population. In collaboration with Dr. Schneider (NYU, described in chapter 2), we have performed polysome profiling of SBI-756 treated OCI-LY1 cells, as well as Rapalink-1 treated cells, and compared the results to vehicle treated. Analyses and comparison of Rapalink-1 to SBI-756 is currently in progress, but I would expect some overlap between the targets of the two treatments (as they both regulate eIF4E availability). However, due to mTORC1

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involvement in many other outputs, aside from eIF4E, I would also expect significant differences between the proteome of the SBI-756 vs. Rapalink-1 treated cells. Validation of expression changes can be done using quantitative western blot analysis (LI-COR Odyssey system) in separate biological replicates of lymphoma cells treated under the different conditions.

Moreover, we have included samples treated with Rapalink-1 in the proteome experiments with

Dr. Paul Gershon, described above.

Our laboratory has collaborated to study other compounds with similar properties as

Rapalink-1. Specifically, we are working with Revolution Medicine (RevMed) to assess their compound RMC-4267 in our leukemia models. RevMed calls this compound a “bi-steric” mTORC1 inhibitor since like Rapalink-1 it targets two regions of mTORC1 by joining together rapamycin with a TOR-KI via flexible linker. Our lab has shown that in p190 cells and SUP-B15 cells, RMC-4267 suppresses 4E-BP1 phosphorylation more effectively than rapamycin or

MLN0128 without inhibiting mTORC2. RMC-4267 also potentiates the anti-leukemic effect of dasatinib in vitro and in vivo. The main goals of our ongoing investigations are to identify advantages of bi-steric mTORC1inhibitors to reduce B-ALL proliferation and survival, as well as to learn about the molecular mechanisms for the sensitization. I will assess effects of bisteric mTORC1 inhibitors on protein synthesis and cap-dependent translation, as well as IRES- or m6A-dependent translation. It would be interesting to see changes in cap-dependent translation compared to other translation methods, which might compensate for cap-dependent translation suppression. Those measurements could be done using dual-luciferase reporter assays, together with PLA to specifically learn about eIF4E:eIF4G1 or eIF4E:4E-BPs interaction. In order to measure m6A methylation and the key methyltransferase complex (METTL14), I suggest using

LC-MS/MS quantification of m6A/A ratio in poly(A) RNA isolated from the treated cells103.

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This measurement can be done with collaboration with Dr. Gina Lee (UCI faculty).

Alternatively, we can learn about m6A or IRES translation by mutating the m6A or IRES motifs via site-directed mutagenesis and learn about translation change before and after the mutations, and compare them to eIF4F-dependent translation92,110.

This dissertation was written during the Coronavirus disease 2019 (COVID‐19) pandemic, caused by a highly pathogenic human coronavirus, SARS-CoV-2. As we continue to learn the risk factors and characteristics of the viral vector causing this pandemic, as well as reflect on other viral vectors, we realize that several viral infections share certain characteristics.

Among those are cytokine storm and inflammation, which may be counteracted via overall immune suppression. As the mTOR pathway has been shown to directly be involved in immune suppression8,111,112, and the immune suppression characterizes COVID-19 infection113, one might consider mTOR inhibition as a therapeutic strategy. As shown before, targeting mTOR directly might alter many cellular pathways other than the ones involved in regulation of viral replication, inflammation and lymphocyte response. In that case, it might be beneficial to consider downstream targets of mTOR as a therapeutic strategy, such as the 4E-BP–eIF4E axis which promotes growth and proliferation in lymphocytes114 or antibody class switch recombination115.

Indeed, recent reports have indicated potential for targeting the eIF4A component of the translation initiation complex using zotatifin (eFT226)116. Recently, it has shown in vitro antiviral activity against SARS-CoV-2. It is also worth testing inhibitors of eIF4E or eIF4G1 in these assays. Those novel therapeutics might assist with control (or minimizing) the spread of the current pandemic and the infectious SARS-CoV-2 virus.

224

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