The Role of Eif5a Hypusination in Mediating Oncogenic Mtor Signaling

The role of eIF5A hypusination in mediating oncogenic mTOR signaling

Yutian Cai Faculty of Medicine Department of Biochemistry McGill University, Montreal, Quebec, Canada December 2016

A thesis submitted to McGill University in partial fulfillment of the requirements of the

degree of Master of Science

©Yutian Cai 2016

TABLE OF CONTENTS

TABLE OF CONTENTS ...... 2 TABLE OF FIGURES ...... 4 PREFACE...... 5 ACKNOWLEDGEMENTS ...... 6 ABSTRACT ...... 7 RÉSUMÉ ...... 9 LIST OF ABBREVIATIONS ...... 11 CHAPTER 1: INTRODUCTION ...... 14 1.1 mRNA TRANSLATION ...... 14 1.1.1 TRANSLATION INITIATION...... 15 1.1.2 TRANSLATIONAL EFFICIENCY ...... 20 1.1.3 TRANSLATION AND CANCER ...... 25 1.2 POLYSOME FRACTIONATION ...... 27 1.3 mTOR PATHWAY ...... 30 1.3.1 UPSTREAM ACTIVATORS OF mTOR ...... 31 1.3.2 DOWNSTREAM EFFECTORS OF mTOR IMPLICATED IN TRANSLATIONAL REGULATION...... 34 1.3.3 PHARMACOLOGICAL INHIBITORS OF mTOR ...... 36 1.4 OBJECTIVES ...... 39 1.4.1 EUKARYOTIC TRANSLATION INITIATION FACTOR eIF5A ...... 42 1.4.2 DEOXYHYPUSINE HYDROXYLASE/MONOOXYGENASE (DOHH) ...... 47 CHAPTER 2 RESULTS ...... 49 2.1 EXPRESSION OF DOHH AND eIF5A mRNA IS UPREGULATED ACROSS A VARIETY OF DIFFERENT CANCER TYPES ...... 49 2.2 DOHH IS A DOWNSTREAM TARGET OF THE mTOR PATHWAY ...... 50 2.3 CHANGES IN mTOR SIGNALING DO NOT EXERT A MAJOR EFFECT ON DOHH PROTEIN STABILITY ...... 51 2.4 DOHH mRNA LEVELS ARE NOT MODULATED BY mTOR SIGNALING ...... 51 2.5 mTOR INCREASES TRANSLATIONAL EFFICIENCY OF DOHH mRNA ...... 51 2.6 DOHH PROTEIN EXPRESSION IS INDEPENDENT OF THE 4E-BP STATUS IN THE CELL ...... 56

2 2.7 IDENTIFYING THE ROLE OF eIF5A HYPUSINATION IN mTOR DEPENDENT TUMORIGENESIS ...... 57 CHAPTER 3 DISCUSSION ...... 67 CHAPTER 4 MATERIALS AND METHODS ...... 76 4.1 CELL CULTURE AND DRUG TREATMENTS ...... 76 4.2 LENTIVIRUS shRNA AND INFECTIONS ...... 77 4.3 CELL LYSIS AND WESTERN BLOTTING ANALYSIS ...... 77 4.4 POLYSOME PROFILING AND RNA EXTRACTION ...... 79 4.5 REVERSE TRANSCRIPTASE-QUANTITATIVE PCR (RT-qPCR) AND PRIMERS ...... 80 4.6 SOFT AGAR COLONY FORMATION ASSAY ...... 82 CHAPTER 4 REFERENCES ...... 84

3 TABLE OF FIGURES FIGURE 1.1 A BRIEF OVERVIEW OF TRANSLATIONAL INITIATION IN EUKARYOTES ...... 20 FIGURE 1.2 SHEMATIC REPRESENTATION OF POLYSOME PROFILING TECHNIQUE ...... 29 FIGURE 1.3 THE SCHEMATIC REPRESENTATION OF THE mTOR SIGNALING NETWORK ...... 36 FIGURE 1.4 mTOR INHIBITORS SUPPRESS TRANSLATION OF A SUBSET OF mRNAS THAT ENCODE PROTEINS INVOLVED IN AMINO ACID METABOLIC PROCESSES INCLUDING DOHH ...... 41 FIGURE 1.5 A SCHEMATIC REPRESENTATION OF THE HYPUSINATION REACTION ...... 46 FIGURE 2.1 EXPRESSION OF DOHH AND EIF5A MRNA IS UPREGULATED ACROSS A VARIETY OF DIFFERENT CANCER TYPES ...... 59 FIGURE 2.2 DOHH IS A DOWNSTREAM TARGET OF THE mTOR PATHWAY ...... 60 FIGURE 2.3 CHANGES IN MTOR SIGNALING DO NOT EXERT A MAJOR EFFECT ON DOHH PROTEIN STABILITY ...... 61 FIGURE 2.4 DOHH MRNA LEVELS ARE NOT MODULATED BY mTOR SIGNALING ...... 62 FIGURE 2.5 MTOR INCREASES TRANSLATIONAL EFFICIENCY OF DOHH mRNA ...... 63 FIGURE 2.6 DOHH PROTEIN EXPRESSION IS INDEPENDENT OF THE 4E-BP STATUS IN THE CELLS ...... 65 FIGURE 2.7 DOHH IS REQUIRED FOR THE NEOPLASTIC GROWTH OF HCT116 PTEN-/- CELLS ...... 66

4 PREFACE

This thesis was written based on the Guidelines for Thesis Preparation from the

Faculty of Graduate Studies and Research of McGill University.

Our lab manager Shannon McLaughlan initiated the project and helped me optimize the experimental conditions throughout the project. Also, our collaborator

Dr. Ola Larsson at Karolinska Institute in Sweden helped to develop the R script for polysome analysis.

5 ACKNOWLEDGEMENTS

I first wish to thank my supervisor Dr. Ivan Topisirovic for his patience, guidance, and expertise in science. Moreover, I wish to thank him for giving me the opportunity to attend R programming workshop in Sweden and broaden my knowledge in bioinformatics.

I would also like to thank my colleagues in the lab Valentina Gandin, Shannon

McLaughlan, Marie Cargnello and Laura Hulea for teaching me the experimental techniques and helping me to develop critical thinking. Last but not the least, I would like to thank all my friends and family for the moral support I needed throughout the master study.

6 ABSTRACT

Protein synthesis (or mRNA translation) is a major step in the regulation of gene expression and one of the most energy consuming processes in the cell. eIF5A is activated by a unique post-translational modification called hypusination

(modification of Lys50 on eIF5A to hypusine), which is catalyzed by deoxyhypusine synthase (DHS) and deoxyhypusine hydroxylase (DOHH). eIF5A hypusination is thought to play a significant role in translation, but little is known about its regulation. Our recent genome-wide interrogation of the translatome identified DOHH mRNA as a potential translational target of the mechanistic/mammalian target of rapamycin (mTOR). We were able to validate these findings and demonstrate that treatment with mTOR inhibitors, rapamycin and torin1 causes a substantial decrease in DOHH protein levels. Using proteasome inhibitors and measuring mRNA levels by RT-qPCR, we concluded the mTOR neither controls stability of DOHH protein nor the transcription of the corresponding gene. We next conducted polysome-profiling experiments using mTOR inhibitors, which revealed that mTOR regulates DOHH expression at the level of translation. Since both mTOR and eIF5A hypusination are often found to be upregulated in cancer, and we established the link between mTOR and eIF5A hypusination, we hypothesized the DOHH/eIF5A pathway at least in part mediates oncogenic effects of mTOR. Using soft agar assay, we demonstrated

7 that DOHH depletion was sufficient to attenuate anchorage-independent growth induced by hyperactivated mTOR signaling. These findings suggest that DOHH and consequently eIF5A hypusination may play a major role in mTOR-driven oncogenesis.

8 Résumé

La synthèse des protéines (ou traduction des ARN messagers) est une étape clé de la régulation de l’expression des gènes dont la dérégulation est associée au développement de nombreuses pathologies humaines telles que le cancer. Le facteur d’initiation de la traduction eIF5A est activé par hypusination, une modification post-traductionnelle unique à eIF5A, qui est catalysée par deux enzymes : deoxyhypusine synthase (DHS) et deoxyhypusine hydroxylase (DOHH). Bien que l’hypusination de l’eIF5A joue un rôle majeur dans la régulation de la traduction et semble être impliquée dans l’oncogénèse, les mécanismes moléculaires participant à son contrôle sont peu connus. Nos travaux récents d’analyse à large échelle du profil d'expression des gènes ont identifié l’ARNm de DOHH comme potentiellement régulé au niveau traductionnel par la kinase mTOR (mechanistic target of rapamycin), un régulateur majeur de la traduction et de la croissance cellulaire. Nous avons montré que l’inhibition de mTOR avec des inhibiteurs catalytiques (torin1) et allostériques (rapamycine) conduit à une diminution des niveaux protéiques de

DOHH. Cette réduction ne s’accompagne de changements ni au niveau transcriptionnel ni au niveau de la stabilité de la protéine, déterminés respectivement en mesurant les niveaux totaux d’ARNm de DOHH par RT-qPCR et par l’utilisation d’inhibiteurs du protéasome ce qui suggère que mTOR régule

9 l’expression de DOHH au niveau post-transcriptionnel. Afin de déterminer si mTOR contrôle l’expression de DOHH au niveau traductionnel, nous avons réalisé du profilage de polysomes et avons trouvé que l’inhibition de mTOR avec la torin1 diminue l’association de l’ARNm de DOHH avec les polysomes indiquant une répression de sa traduction. Finalement, étant donné le rôle de mTOR et de l’hypusination d’eIF5A dans le cancer, nous avons émis l’hypothèse que la voie eIF5A/DOHH contribue, au moins en partie, aux effets oncogéniques de mTOR.

En utilisant des essais de formation de colonie en agar mou nous avons montré que la réduction de l’expression de DOHH par interférence à ARN était suffisante pour atténuer la formation de colonies induites par la suractivation de mTOR.

Ensemble, ces résultats suggèrent que l’hypusination d’eIF5A et l’expression de

DOHH sont des facteurs importants dans l’oncogenèse induite par la suractivation de mTOR.

10 LIST OF ABBREVIATIONS

Abbreviation Full Name

4E-BPs eukaryotic translation initiation factor 4E (eIF4E) binding proteins

4EHP 4E-homologous protein

AKT/PKB protein kinase B

BCL-2 B-cell lymphoma 2

DMSO dimethyl sulfoxide

DHS deoxyhypusine synthase

DOHH deoxyhypusine hydroxylase/monooxygenase eEF eukaryotic translation elongation factor eEF2K eEF2 kinase eIF eukaryotic translation initiation factor eRF eukaryotic translation termination factor

FBS fetal bovine serum

FGF5 fibroblast growth factor 5

GAP GTPase-activating-protein

GAPDH glyceraldehyde 3-phosphate dehydrogenase

GCN2 general control nonderepressible 2

GDP guanosine diphosphate

11 GTP guanosine 5' triphosphate

IRS-1 Insulin receptor substrate 1

HRI hepatic heme-regulated inhibitor

IRP Iron regulatory protein

MAPK mitogen activated protein kinase

MCF7 Michigan Cancer Foundation-7

MDM2 mouse double minute 2 homolog

MEFs mouse embryonic fibroblast

Met-tRNA methionyl-initiator tRNA mRNA messenger RNA mTOR The mechanistic/mammalian target of rapamycin

RBP RNA binding protein

PDCD4 programmed cell death 4

PERK protein kinase RNA-like endoplasmic reticulum kinase

PI3K phosphatidylinositol-3-kinase

PIK3A phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha

PIP2 phosphatidylinositol-4,5-biphosphate

PKR protein kinase R

PTEN phosphatase and tensin homologue deleted on chromosome 10

12 Raptor regulatory associated protein of TOR

Rheb Ras homologue enriched in brain

Rictor rapamycin insensitive component of TOR rpS6 40S ribosomal protein S6

S6K ribosomal protein S6 kinase

TOP terminal oligopyrimidine tracts

TSC tuberous sclerosis uORF upstream open reading frame

UTR untranslated region

13 CHAPTER 1: INTRODUCTION

1.1 mRNA TRANSLATION

Protein synthesis (or mRNA translation) is a pivotal biological process that requires an extensive amount of energy and coordinated action of the components of the translational machinery1, 2. mRNA translation plays a central role in cellular homeostasis and is a major step in the regulation of gene expression3. For instance, translation provides means to rapidly modulate the proteome in response to a plethora of external stimuli including nutrients, hormones, growth factors and the number of stressors including osmotic shock and ionizing radiation4. Therefore, it is not surprising that dysregulated translation contributes to a variety of pathological states including cancer, diabetes, and neurological disorders5.

In eukaryotes, translation can be subdivided into four steps: initiation, elongation, termination and ribosome recycling6. Translation initiation involves orchestrated action of a number of translation initiation factors which recruit and stabilize the ribosomes on the messenger RNA (mRNA), are participating in the selection of the appropriate initiation codon, and delivery of the initiator tRNA7. During elongation phase of translation, mRNA is decoded into the nascent polypeptide chain by tRNAs which deliver amino acids and are recruited to the scanning 80S ribosomes by auxiliary proteins referred to as eukaryotic translation elongation

14 factors (eEFs)8. Protein synthesis is terminated as the ribosome reaches the stop codon on the mRNA thereby triggering a release of the newly synthesized polypeptide. This step is regulated by eukaryotic translation termination factors

(eRFs)9. Subsequently, ribosome recycling factors mediate the disassembly of the 40S and 60S ribosome subunits, which allows ribosome subunits to re-enter the translation process10. Amongst the four phases of translation, it is thought that the rate-limiting initiation phase is where the most of the regulation takes place4.

1.1.1 TRANSLATION INITIATION

Translation can be initiated by cap-dependent or cap-independent mechanisms11.

In eukaryotes, nuclear-encoded messenger RNAs contain a 5’ mRNA cap structure at their 5’ terminus which stimulates the association of the translation initiation machinery to the mRNA during cap-dependent mRNA translation12. eIF4F is a 5’ mRNA cap-binding complex responsible for recruiting mRNA to the ribosome, the assembly of which together with ternary complex assembly constitutes two major rate-limiting checkpoints of translation initiation10 (Figure

1.1). The eIF4F complex comprises the scaffold protein eIF4G, cap-binding protein eIF4E, and a DEAD-box RNA helicase eIF4A, which unwinds secondary structure in the 5’ UTR during ribosome scanning10. eIF4G binds to poly-A binding protein (PABP) at the 3’ end of mRNAs which stimulates mRNA circularization13.

15 mRNA circularization is thought to increase translational efficiency as well as to stabilize mRNA13. The importance of the eIF4F function in translation initiation step is illustrated by findings showing that overexpression of eIF4F subunits leads to perturbations in protein synthesis that underlie various human diseases including neoplasia11, which will be discussed below.

Although required for cap-dependent translation of all nuclear-encoded mRNAs, it became apparent that translation efficiency of some mRNAs is more affected by the changes in the eIF4F levels than others14. For instance, an increase in the eIF4F levels caused by eIF4E overexpression, which is thought to be the least abundant subunit of the eIF4F complex, leads to selective upregulation of translation of a subset of mRNAs15. To elaborate, eIF4E overexpression bolsters translation of mRNAs that possesses long and structured 5’ UTRs such as those encoding tumor promoting proteins including cyclins, c-MYC and BCL-2 family members, while inducing only minimal changes in translation of the vast majority of cellular mRNAs which contain 5’ UTRs of optimal length for efficient translation initiation (50-100 nt long) including those encoding house-keeping proteins such as β-actin and GAPDH16. Increased sensitivity of mRNAs that harbor long and structured 5’ UTRs to fluctuation in eIF4F levels is thought to stem from the requirement of eIF4A helicase to unwind secondary structures and facilitate ribosome scanning, whereby processivity of eIF4A is strongly enhanced when

16 eIF4A is a part of the eIF4F complex17. More recently, we and others have shown that different components of the eIF4F complex affect translation of partially overlapping, but also distinct subsets of mRNAs16. For instance, mRNAs encoding proteins with mitochondrial functions (e.g. ATP5O, ATP5D) harbor extremely short 5’ UTRs and are sensitive to changes in eIF4E, but not eIF4A levels16. Similarly, eIF4G appears to affect translation of a number of mRNAs encoding factors implicated in DNA damage response18. Notwithstanding that the precise mechanisms underlying the observed phenomena remain to be established, these findings show that eIF4F subunits may play specific, non-overlapping roles in translation regulation16.

Assembly of the eIF4F complex is largely regulated via the target of rapamycin

(TOR) kinase4. In mammals, the mechanistic/mammalian TOR complex 1

(mTORC1) regulates eIF4F assembly by phosphorylating and inactivating a family of small translational repressors called 4E-binding proteins (4E-BPs,

4E-BP1, 2 and 3)19. 4E-BPs bind to the overlapping surface on eIF4E as eIF4G, thereby preventing eIF4E-eIF4G association and eIF4F complex assembly20. In response to a number of extracellular stimuli and intracellular cues including hormones and growth factors, nutrients, oxygen and cellular energy status, mTORC1 phosphorylates 4E-BPs, which stimulates their dissociation from eIF4E thus allowing the eIF4F complex assembly21.

17 eIF2 delivers the methionyl-initiator tRNA (Met-tRNAi) to the ribosome as a part of the ternary complex which also contains GTP22 (Figure 1.1). eIF2 is a heterotrimer that consists of three subunits – eIF2α, eIF2β, eIF2γ22. Ternary complex along with the 40S ribosome subunit and other components of the multifactor complex

(MFC; eIF1, eIF1A, eIF3, and eIF5) forms 43S pre-initiation complex, which is recruited to the mRNA structure via the eIF4F complex through the interaction of eIF3 with eIF4G16.

The activity of eIF2 is regulated by the coordinated action of the eIF2α kinases that phosphorylate eIF2α and guanine nucleotide exchange factor (GEF) eIF2B23.

Upon delivery of Met-tRNAi, GTP is hydrolyzed to GDP via the GTPase activity of eIF2γ subunit, upon which a large multisubunit complex eIF2B exchanges eIF2:GDP to eIF2:GTP thereby allowing TC recycling24 (Figure 1.1). Stress signals, such as amino acid deprivation, viral infection, ER stress and hem deficiency induce eIF2α kinases such as general control nonderepressible 2

(GCN2), protein kinase R (PKR), protein kinase RNA-like endoplasmic reticulum kinase (PERK) and hepatic heme-regulated inhibitor (HRI) that phosphorylate eIF2α25. eIF2α phosphorylation increases binding of eIF2 to eIF2B which blocks the exchange of GDP bound eIF2 to eIF2:GTP and impedes TC recycling17,26.

This decrease in TC levels coincides with the reduction in global translation, accompanied by the selective upregulation of synthesis of proteins encoded by

18 mRNAs that contain inhibitory upstream open reading frames (uORFs) in their 5’

UTR, which encode stress-response transcription factors including ATF4 and

CHOP27. In non-stressed cells wherein TC levels are abundant, translation of the latter transcripts is suppressed due to preferential initiation on the inhibitory uORFs, which impedes initiation on the main ORF28. When TC levels are limiting, translation is initiated preferentially on the major ORF, which leads to increase in the synthesis of the corresponding proteins28.

Once the AUG start codon is recognized by Met-tRNAi, 43S pre-initiation complex switches from open to closed position, followed by the release of eukaryotic initiation factors and subsequent 80s complex assembly22 (Figure 1.1). This signifies beginning of the elongation phase of translation.

FIGURE 1.1 A BRIEF OVERVIEW OF TRANSLATIONAL INITIATION IN EUKARYOTES Translation initiation in eukaryotes encompasses two rate-limiting steps: ternary complex (TC) recycling and the eIF4F complex assembly4. TC contains eIF2, GTP and the initiator tRNA (tRNAiMet) and is a part of the multifactor complex (MFC) which also comprises eIF1, eIF1A, eIF3 and eIF522. MFC along with the small ribosomal subunit forms the 43S pre-initiation complex (PIC)16. Upon recognition of the initiation codon of the mRNA, GTP bound to eIF2 is hydrolyzed into GDP, which stimulates delivery of tRNAiMet to the P site of the ribosome23. eIF2B acts as a guanine nucleotide exchange factor (GEF) which exchanges eIF2:GDP for eIF2:GTP thereby allowing its re-association with tRNAiMet and thus TC recycling24. Phosphorylation of the eIF2α subunit of eIF2 by PERK, PKR, GCN2 or HRI kinases inhibits GEF activity of eIF2B, impedes TC recycling and

20 decreases TC levels, which leads to reduction of protein synthesis17,26. The eIF4F complex consists of the 5’mRNA cap binding subunit eIF4E, large scaffolding protein eIF4G, and DEAD-box helicase with ATPase activity eIF4A10. eIF4G associates with eIF3 which allows recruitment of 43S PIC to the mRNA, and also to poly(A)-binding protein (PABP), which facilitates circularization of the mRNA13. eIF4A helicase along with its accessory factors eIF4B and eIF4H unwinds the secondary structure of the mRNA which stimulates scanning of the 43S PIC towards the initiation codon17. Upon recognition of the initiation codon translation initiation factors are released which results in association of the small and large ribosomal subunits and signifies the end of initiation, and the beginning of the elongation phase of translation17. (adapted from Hinnebusch AG, The scanning mechanism of eukaryotic translation initiation. Annu Rev Biochem. 2014;83:779-812.)

21 1.1.2 TRANSLATIONAL EFFICIENCY

The composition of the proteome is determined by orchestrated action of the various regulatory steps of gene expression including transcription, pre-mRNA splicing, nuclear mRNA export, mRNA stability, mRNA translation and protein stability29. Changes in global protein synthesis rates as well as reprograming translation by altering translational efficiencies of discrete pools of mRNAs have a significant impact on fundamental cellular processes such as proliferation, growth, and survival, whereas dysregulation of translation leads to pathological states including cancer and metabolic and neurological disorders30. Moreover, although synonymous mutations at the gene level do not alter the amino acid sequence of the protein31, they may have a dramatic impact on translational efficiency by modifying elongation rates and thereby the levels of the corresponding protein which is in part determined by the codon bias32. Collectively, these findings demonstrate that mRNA translation constitutes a pivotal step in the gene regulation pathway and thereby plays a significant role in cellular and organismal homeostasis33.

Translational efficiency of specific mRNAs is controlled via the interplay of cis-elements of the transcripts including UTR features and trans-acting factors including RNA binding proteins and rate-limiting translation factors such as eIF4E and eIF24. Secondary structures and the length of 5’ UTR, as well as the RNA

22 elements in the 3’UTR including microRNA (miRNA)-binding sites are important determinants of translational efficiency. For instance, in our previous study we were able to distinguish mTOR-regulated mRNAs that are sensitive to changes in eIF4E and eIF4A levels vs. those that are only sensitive to eIF4E levels on a genome-wide scale16. As outlined in section 1.1.1 RNA helicase eIF4A is required to unwind secondary structures in the 5’ UTR to permit the ribosomes attachment and scanning towards the initiation codon31. Transcripts with long and structured

5’ UTR that are enriched in those encoding for proliferation and survival promoting proteins are highly sensitive to alteration in both eIF4E and eIF4A function34, 35. In turn, those mRNAs that contain extremely short (5-20nt) 5’ UTRs and are enriched for transcripts encoding nuclear-encoded components of mitochondrial electron transport chain complexes, although sensitive to changes in eIF4E levels were only marginally affected by inhibition of eIF4A16. These and similar findings outlined in the section 1.1.1 indicate that translation efficiencies of a specific subset of mRNAs can be modulated based on their 5’ UTR features via alterations in the activity of specific translation initiation factors14.

Secondary structure in 5’ UTRs are also thought to be a major determinant of translation efficiency36. Stable secondary structures such as hairpins are thought to be prevalent in 5’UTRs of mRNAs encoding transcription factors (i.e. c-Myc), proto-oncogenes (i.e. MDM2), and growth factors (i.e. FGF5)37. DEAD box RNA

23 helicase eIF4A hydrolyses ATP and unwinds secondary structures in the 5’ UTR to permit the ribosomes attachment and codon scanning31. Therefore, the mRNAs with long and structured 5’ UTR exhibit high sensitivity towards changes in eIF4A availability and/or activity38.

In addition, selective increase in cap-dependent translation efficiency has been reported in the context of “specialized” translation initiation factors. For instance,

Drosophila eIF4E homologous protein (4EHP) is an example of such specialized translation initiation factor which binds to the cap structure at 5’ UTR and blocks the loading of eIF4E to bicoid mRNA, thereby preventing its translation39.

Moreover, RNA binding proteins (RBPs) are also implicated in selective regulation of translational efficiency. To this end, RBPs allow rapid changes in translational efficiency of subsets of mRNAs that harbor specific mRNA elements in their

5’UTR in response to a variety environmental cues40. For example, when iron levels are low, Iron regulatory proteins (IRP 1 and 2) bind to the iron response element (IRE) present in the 5’ UTRs which inhibits the translation of ferritin mRNAs, whereby ferritin is an intracellular protein with a pivotal role in iron storage and metabolism40. In this way, IRP 1- and 2-dependent regulation of ferritin mRNA translation plays a pivotal role in cellular iron homeostasis.

These and other studies established a wide variety of mechanisms to regulate translational efficiency of specific mRNAs thereby allowing rapid adaptive

24 responses to a bevy of environmental stimuli and intracellular cues. Factors that incite and govern selective modulation of mRNA translation therefore act as a major part of the gene expression pathway which is integral for maintenance of cellular homeostasis2.

1.1.3 TRANSLATION AND CANCER

Neoplasia is characterized by increased levels of protein synthesis as well as by the qualitative alterations in the pools of mRNAs that are being translated41.

These changes are thought to critically contribute to the alterations in the proteome that are required for cancer initiation and progression41.

As described in section 1.1.1, eIF4F complex formation is a rate-limiting step of the translation initiation that is tightly regulated by numerous pathways including phosphoinositide-3-kinase PI3K/Akt/mTOR pathways and mitogen-activated protein kinase (MAPK)42. Collectively, these pathways respond to a large variety of extracellular stimuli and intracellular signals, which they integrate to alter eIF4F levels and translational efficiency of a subset of mRNAs encoding proliferation- and survival-promoting proteins and oncogenes (e.g. cyclins, BCL-2 family members, and c-MYC). Hyperactivation of the eIF4F engendered either by overexpression of its subunits or dysregulation of the corresponding regulatory pathways, therefore steers the cell towards malignancy. In particular, high

25 expression of eIF4E is observed in the majority of solid cancers (e.g. head and neck, breast, prostate, colon cancer, etc) and malignancies of the blood (leukemia and lymphomas) where it has been associated with high tumor grades, chemoresistance and reduced patient survival43, 44. In turn, 4E-BPs which bind to eIF4E and decrease the eIF4F complex levels act as tumor suppressors19, 45. In addition, increased eIF4G levels are observed in cervical cancer, inflammatory breast cancer, and lung carcinomas46, 47. Finally, overexpression of eIF4A is found in lung and cervical cancer, whereas reduced eIF4A expression after brachytherapy is predictive of better patient survival48. Accordingly, diminished levels of eIF4A inhibitor PDCD4 are found in a variety of cancers including lung, ovarian, and kidney cancer49. Therefore, increased levels of the eIF4F complex and/or its components are observed in the vast majority of human malignancies.

In addition, dysregulation of the most if not all translation factors as well as aberrant ribosome biogenesis and alterations in tRNA levels are frequently reported in neoplasia5. This indicates significant remodeling of the translational apparatus in cancer cells. These differences in the function of the translational apparatus in normal vs. cancer cells are thought to provide sufficient therapeutic window to impair protein synthesis and selectively eradicate cancer cells5. For instance, inhibitors which directly target eIF4F function (e.g. eIF4A inhibitors such as rocaglates and hippuristanol; 4EGI-1 which inhibits eIF4G:eIF4E interaction)

26 have demonstrated promising anti-neoplastic effects in a number of preclinical models50.

1.2 POLYSOME FRACTIONATION

During elongation step of translation, more than one ribosome can load onto the same mRNA, which leads to the formation of polyribosomes (also referred to as polysomes)51. Translational efficiency is proportional to the number of ribosomes that are associated with the transcript52. By consensus, heavy polysomes are designed to represent the mRNAs associated with more than three ribosomes, and these transcripts are considered being efficiently translated53.

Steady-state mRNA levels represent the genome-wide composition of mRNAs, the fluctuation of which reflects changes in mRNA stability and gene transcription54. Along with mRNA translation and protein stability, they determine the composition of the total proteome in the cell55. Considering that steady-state mRNA levels are not perfectly mirrored in the proteomes, the collection of mRNAs associated with polysomes is thought to represent a closer representation of the protein composition in the cell52. Polysome profiling is a technique which is used to separate mRNAs based on the number of ribosomes they bind, which is achieved by sedimenting cellular extracts through sucrose gradients by ultracentrifugation56 (Figure 1.2). This allows separation of inefficiently vs.

27 efficiently translated mRNAs, which are associated with heavy (localized closer to the bottom of the gradient) or light (localized towards the top of the gradient) polysomes, respectively56. Polysome profiling, coupled with the reverse transcriptase polymerase chain reaction (RT-PCR) or techniques used to interrogate gene expression on a genome-wide scale (e.g. RNAseq, DNA microarrays) is, therefore a method that can be utilized to capture changes in mRNA translation. The levels of polysome-associated mRNAs are influenced by the changes in steady-state mRNA levels, whereby changes in steady-state mRNAs may mask changes in translational efficiency (i.e. higher abundance of mRNA which typically results in higher polysomal binding to the mRNA may be interpreted as an increase in translation efficiency). This can be avoided by normalizing mRNA associated with polysomes over total mRNA for individual genes, whereas the anota analysis captures differential translation by correcting changes in polysome-associated mRNAs for alterations in total mRNAs levels on a genome-wide scale57.

FIGURE 1.2 SHEMATIC REPRESENTATION OF POLYSOME PROFILING TECHNIQUE Cells are lysed in hypotonic buffer containing translation elongation inhibitor cycloheximide to immobilize the ribosomes onto mRNA56. The lysate is loaded on a 5%-50% sucrose density gradient and subjected to ultracentrifugation before collecting the fractions56. During ultracentrifugation, free ribonucleoprotein complexes (RNPs), monosomes (80s), and polysomes are separated and the gradients are fractionated with continuous monitoring of the absorbance at 254nm56. After fractionation, translationally active mRNAs (heavy polysomes) and total mRNA are subjected to DNA microarrays or RNA sequencing to capture changes in translation on a genome-wide scale57. (adapted from Larsson O, Sonenberg N, Nadon R. anota: Analysis of differential translation in genome-wide studies. Bioinformatics. 2011;27(10):1440-1441.)

29 1.3 mTOR PATHWAY mTOR is a serine/threonine kinase, which is a major regulator of mRNA translation. mTOR senses nutrient availability to orchestrate energy production with protein synthesis and proliferation rates58. In mammals, two functionally and structurally distinct mTOR-containing complexes have been recognized, and they are referred to as mTORC1 and mTORC259. Both complexes share the catalytic subunit mTOR and differ in their composition, upstream inputs, downstream targets and sensitivities towards naturally occurring allosteric inhibitor rapamycin60. mTORC1 contains five components in addition to mTOR: a scaffold protein regulatory-associated protein of mammalian target of rapamycin

(RAPTOR), mammalian lethal with sec-13 protein 8 (mLST8, also referred to as

GβL), the Tti1/Tel2 complex, DEP domain containing mTORC-interacting-protein

(DEPTOR), and proline-rich AKT substrate 40kDa(PRAS40)61. mTORC1 stimulates anabolic processes including lipid and protein synthesis, mitochondrial metabolism, suppresses autophagy, and bolsters proliferation and cell growth in response to extracellular and intracellular signals such as growth factors, energy status, oxygen levels and amino acid availability62. mTORC1 is also acutely sensitive to the allosteric inhibitor rapamycin63. mTORC2 contains seven subunits– scaffolding protein RPTOR/Rapamycin Independent Companion Of mTOR Complex 2 (RICTOR), mLST8 (GβL), PRR5/Protor-1, SIN1, Tti1/Tel2

30 complex, DEPTOR, and mTOR64. mTORC2 phosphorylates and activates AGC kinases [e.g. Akt, serum and glucocorticoid-regulated kinase 1 (SGK1)], and it has been implicated in cytoskeleton organization, lipid and glucose metabolism in the liver as well as in co-translational protein degradation65. Opposite to mTORC1, mTORC2 is largely insensitive to acute rapamycin treatment. The aberrant mTOR function is implicated in diverse pathophysiological conditions, including diabetes, obesity, and cancer66.

1.3.1 UPSTREAM ACTIVATORS OF mTOR

Upstream signals such as hormones and growth factors activate receptor tyrosine kinases on the cellular membrane which triggers the activation of PI3K and Ras pathways67 (Figure 1.3). The dimerization of the receptors drives the recruitment of adaptors (e.g. IRS-1) and creates a docking site for PI3K to the cellular membrane68. PI3K directly interacts with Phosphatidylinositol 4,5-bisphosphate

(PIP2), which is a phospholipid present in the cellular membrane and phosphorylates it to phosphatidylinositol (3,4,5)-trisphosphate (PIP3)69. This reaction is reversely regulated by phosphatase and tensin homolog (PTEN) which is lipid phosphatase that acts as a tumor suppressor70. PTEN is mutated in several syndromes with increased predisposition to cancer including Cowden disease and Proteus syndrome71. PIP3 recruits PDK1 and AKT to the plasma

31 membrane wherein PDK1 to phosphorylate and activates AKT72. AKT phosphorylates and inhibits the heterodimeric tuberous sclerosis complex (TSC) which consists of TSC1 and TSC273. TSC1/2 is an upstream negative regulator of mTOR pathway and functions as a tumor suppressor74. As its name suggests, loss-of-function mutations in TSC1 and TSC2 are associated with an autosomal dominant disease called tuberous sclerosis, which in mild cases lead to benign tumor growth and in severe pathological forms mental retardation, lung and kidney failure75. TSC1/2 is a GTPase-activating-protein (GAP) for GTP-bound

Ras homolog enriched in brain (Rheb). TSC1/2 hydrolyzes GTP and converts

Rheb to its GDP-loaded inactive form. Rheb-GTP stimulates mTORC1 kinase activity76. Thus, activation of mTORC1 via the PI3K pathway is mediated by

Akt-dependent inhibition of TSC1/277. In addition, oncogene RAS which is also activated by growth factors, can not only directly activate PI3K kinase activity, but also triggers the signaling cascades in MAPK pathway78. MAPK pathway collaborates with the mTOR pathway and leads to an increase in cell survival and proliferation, whereby several positive and negative feedbacks between the mTOR and the MAPK pathways have been established79. mTORC1 activity is also tightly regulated by the amino acid, glucose, and oxygen supply80. Deprivation of amino acid leads to a drastic inhibition of the mTORC1 function, implicating amino acid sufficiency as indispensable for mTORC1

32 activity81. In mammals, RAG GTPases interact with raptor subunit of the mTORC1 in the presence of amino acids and promote its localization on the lysosomal membrane that contains activator Rheb, which result in the activation of mTORC182. The AMP-activated protein kinase (AMPK) senses cellular energy balance and is activated in response to energy stress including low glucose level and hypoxia83. AMP directly binds to the AMPK regulatory γ subunit to enhance phosphorylation of Thr172 by LKB1 within the activation loop which is critical for the AMPK activation84. LKB1 is a tumor suppressor which underlies cancer predispositioning Peutz-Jeghers syndrome and LKB1 is frequently inactivated in malignancies and in particular in lung cancer85. Activated AMPK inhibits mTORC1 in part by phosphorylating TSC2 and raptor86, which suppresses protein synthesis and cellular growth87. In response to hypoxia, mTORC1 signaling is downregulated by DNA damage response 1 (REDD1) through stabilizing the

TSC1/2 complex88.

In contrast to mTORC1, upstream regulation of mTORC2 is poorly understood89.

It has been proposed that the kinase activity of mTORC2 is stimulated by growth factors via a PI3K-dependent manner and not affected by amino acid availability and energy status90. Moreover, the activation and signal transduction by mTORC2 appears to require mTORC2-ribosome interaction in the presence of ribosome maturation factor mNIP791.

33 1.3.2 DOWNSTREAM EFFECTORS OF mTOR IMPLICATED IN

TRANSLATIONAL REGULATION mTORC1 is thought to stimulate protein synthesis via the phosphorylation of a plethora of substrates92. Two best studied substrates of mTORC1 which regulate mRNA translation are eIF4E-binding proteins (4E-BP1, 4E-BP2 and 4E-BP3 in mammals), and S6 kinases (S6K1 and S6K2 in mammals)33. As discussed in section 1.1.1, 4E-BPs interact with and antagonize the assembly of the eIF4F complex93. mTORC1 stimulates phosphorylation and dissociation of 4E-BPs from eIF4E and assembly of the eIF4F complex94. This coincides with induction of translation of eIF4E-senstivie mRNAs such as c-myc, BCL-2, cyclin D1 and survivin95. The role of S6Ks in regulating translation is less clear. S6Ks phosphorylate a number of substrates including the component of 40S ribosomal subunit - ribosomal protein S6 (rpS6), programmed cell death 4 (PDCD4) and eEF2 kinase (eEF2K)96. Phosphorylation of rpS6 has been implicated in translational activation of TOP (terminal oligopyrimidine tract) mRNAs97. 5’TOP motif consists of C immediately after the mRNA cap, accompanied by the uninterrupted stretch of 4–15 pyrimidines97. 5’TOP mRNAs are translated in an mTOR-dependent manner and encode components of translational apparatus such as ribosomal proteins and translation factors98. Although initial studies implicated both the mTORC1/S6K/rpS6 and mTORC1/4E-BP/eIF4E pathways in

34 the regulation of TOP mRNA translation, subsequent experiments revealed that it is unlikely that this is the case99, 100. To this end, a recently identified mTORC1 substrate La-related protein 1 (LARP1) has been proposed to be a major mediator of the effects of mTORC1 on TOP mRNA translation101. S6Ks also phosphorylates and inhibits eEF2 kinase (eEF2K) whereby inhibition of eEF2K leads to activation of translation elongation factor eEF2102. S6Ks are additionally thought to impact on eIF4A activity inasmuch as they have been shown to phosphorylate eIF4B which is an auxiliary protein that stimulates eIF4A activity and to induce degradation of programmed cell death 4 (PDCD4) which acts as eIF4A inhibitor103. Finally, mTORC1 has been shown to phosphorylate other translation initiation factors (e.g. eIF4G) as well as to stimulate ribosome biogenesis and tRNA synthesis via TIF-IA activation and alleviation of MAF1 repression of RNA polymerase III, respectively104, 105. Collectively, these findings indicate that mTORC1 plays a multifaceted role in regulating both global protein synthesis and translation of specific subsets of mRNAs via a multitude of different substrates106. This apparent plasticity of mTORC1-dependent regulation of translation is consistent with the divergence of the physiological roles of its downstream substrates that impinge on the translational machinery, whereby for instance in mammals 4E-BPs are thought to act as major effectors of mTORC1 on cell proliferation whereas S6Ks play a major role in the regulation of cell size107.

FIGURE 1.3 THE SCHEMATIC REPRESENTATION OF THE mTOR SIGNALING NETWORK Growth factors, amino acids and energy status converge to control the activity of mTOR signaling. Growth factors bind to the growth factor receptors and activate mTORC1 via the PI3K/AKT pathway67. AKT phosphorylates and inactivates TSC1/2 complex which in turn serves as a GTPase activating protein and inhibitor of Ras homolog enriched in brain (Rheb) that activates mTORC168. Low intracellular ATP induces the phosphorylation of AMPK by serine/threonine protein kinase STK11/LKB1, which results in the phosphorylation and activation of TSC2 leading to inhibition of mTORC184. RAS-related GTP-binding protein (RAGs) are small GTPases that activate mTORC1 in response to amino acids82. In response to these stimuli, mTOR regulates a bevy of cellular processes such as protein synthesis via a multitude of substrates including 4E-BPs and S6 kinases33. (adapted from Marcotte L, Crino PB. The neurobiology of the tuberous sclerosis complex. Neuromolecular Med. 2006;8(4):531-546.)

36 1.3.3 PHARMACOLOGICAL INHIBITORS OF mTOR

The mTOR signaling is commonly hyperactivated in cancer108. This is a consequence of the loss of tumor suppressors (PTEN, TSC1/2, LKB1) or activation of oncogenes (PIK3CA, RAS)108. Hyperactivated mTOR signaling pathway increases global mRNA translation, as well as translation of mRNAs that encode proteins that bolster neoplastic growth, and leads to reprograming of metabolism to provide building blocks and ATP to fuel cancer109. mTOR signaling pathway inhibitors are therefore thought to exhibit a promising potential in the cancer therapy. In fact, there is a handful of mTOR inhibitors that are used in the clinic and/or are in clinical trials60. Rapalogs including the naturally occurring compound, rapamycin, form a complex with immunophilin FKBP-12 to allosterically inhibit mTORC1 activity by binding to FRB domain of mTOR110.

Although FKBP12-rapamycin complex does not interact with mTORC2111, prolonged rapamycin treatment leads to binding of FKBP12-rapamycin complex to de novo synthesized mTOR. Therefore, long-term exposure of rapamycin inhibits mTORC2 assembly112. Despite the initial promise, the effects of rapamycin and rapalogs as an antitumor treatment in the clinic were less than expected63. This is thought to be a consequence of the activation of AKT which is caused by the inhibition of a negative S6K1-IRS1-PI3K-feedback, as well as the limited efficacy of rapamycin in suppressing phosphorylation of some of the

37 mTORC1 substrates including 4E-BPs113. To overcome these issues and increase the drug potency, the next-generation of drugs targeting the active site of mTOR and thereby inhibiting both mTORC1 and mTORC2 was developed, including PP242 and torin160. Torin1 is an ATP-competitive mTOR inhibitor that exhibits high selectivity towards mTORC1 and mTORC2114. In addition, although at much higher concentration, torin1 suppresses activity of Wee1, a protein kinase that negatively regulates the G2/M checkpoint, which results in G2 arrest115.

ATP-competitive mTOR inhibitors show higher potency that rapamycin in pre-clinical models as they target rapamycin-resistant outputs of mTORC1 and suppress AKT via inhibition of mTORC260. However, recent data suggest that their anti-neoplastic efficacy in the clinic will be limited in at least a subset of patients as their activity is strongly attenuated in cancer cell lines in which eIF4E/4E-BP ratio is high116. The third generation of bivalent mTOR inhibitors has been recently designed to overcome the drug resistance caused by mutations in mTOR by simultaneously targeting allosteric and kinase sites117.

38 1.3 OBJECTIVES

Our lab has previously identified translational targets of mTOR signaling by interrogating the effects of direct and indirect mTOR inhibitors on the translatome

(pool of mRNAs that are actively being translated at a given time point) on a genome-wide scale using polysome profiling/DNA micro-array approach coupled with anota analysis and nanostring validation57. To minimize the possibility that the observed perturbations in the translatome are caused by non-specific effects of the drugs, we used three compounds that inhibit mTOR by a different mechanism of action118. To this end, we employed rapamycin, which is naturally occurring allosteric inhibitor of mTOR, PP242 which targets the active site of mTOR, and anti-diabetic biguanide metformin, that inhibits mTOR by multiple mechanisms including activation of AMP-activated protein kinase (AMPK)60, 119, 120.

Gene ontology analysis using Generally Applicable Gene-set Enrichment (GAGE) method121 revealed that a number of mRNAs that encode components of cellular

“amino acid metabolic processes”, are translationally suppressed by mTOR inhibitors (Figure 1.4). This suggests that mTOR stimulates the mRNA translational activity of mRNAs implicated in amino acid metabolism, including deoxyhypusine hydroxylase (DOHH). Notably, translation of DOHH mRNA was suppressed by all three inhibitors (Figure 1.4), thereby minimizing the possibility that the observed reduction in DOHH mRNA translation was due to the off-target

39 effects of the drugs. Oncogenic mTOR signaling depends on the perturbation in translation machinery that to date are incompletely understood. Considering that

DOHH catalyzes a unique modification of eukaryotic translation initiation factor 5A

(eIF5A), which plays a central and yet underexplored role in the regulation of mRNA translation122, the major objective of this thesis is to explore the role of

DOHH in mediating the effects of mTOR on protein synthesis and neoplastic growth.

40 Color Key cellular_amino_acid_metabolic_process

−1 −0.5 0 0.5 Value

GARS

MTHFD2L

TARS

CARS

PSPH

ASNS

GHR

HPDL

KYNU

PHGDH

FAH

EEF1E1

SLC25A21

DOHH

PSAT1

THNSL1

MAT2A RAP MET DMSO PP242

FIGURE 1.4 mTOR INHIBITORS SUPPRESS TRANSLATION OF A SUBSET OF mRNAs THAT ENCODE PROTEINS INVOLVED IN AMINO ACID METABOLIC PROCESSES INCLUDING DOHH The heat map shows that metformin, PP242 and rapamycin exert distinct perturbations in the translatome as compared to the vehicle (DMSO) in a subset of genes that belong to gene ontology category: “AMINO ACID METABOLIC PROCESSES”121. The difference in mRNA translation (log2 scale) across treatments was calculated using anota57. The translational activity of DOHH mRNA decreases drastically with all three mTOR inhibitor treatments relative to the control, suggesting that DOHH may be a translational target and downstream effector of the mTOR pathway.

41 1.4.1 EUKARYOTIC TRANSLATION INITIATION FACTOR eIF5A eIF5A exists in two isoforms, eIF5A1 and eIF5A2, both highly conserved in sequence across all eukaryotes, underlying their importance in the regulation of cellular homeostasis123. The more abundant form eIF5A1 isoform is ubiquitously expressed, whereas the eIF5A2 isoform appears to be specifically expressed in tissues including brain and testis, while being substantially elevated in the most malignancies124. Besides cancer, dysregulation of eIF5A has been linked to several pathological conditions including infectious diseases and diabetes125. eIF5A was initially characterized as a translation initiation factor as it was observed that it enhances the methionyl-puromycin production in a model translation system comprising ribosomes, other initiation factors and capped mRNAs with the AUG initiation codon126, 127. More recently it has been demonstrated that eIF5A preferentially plays a role in early stages of translation elongation (i.e. transition between initiation and elongation step) inasmuch as it was demonstrated that it stimulates peptidyltransferase activity of the ribosome128,

129. Moreover, a number of studies implicated eIF5A in regulation of mRNA turnover and nuclear mRNA export130. Notwithstanding these findings, although eIF5A was identified over 40 years ago, its precise molecular and physiological functions remain incompletely understood. Recent studies have provided evidence showed that eIF5A promotes translation of mRNAs that encode proteins

42 with polyproline motifs, which induce ribosome stalling128. eIF5A undergoes a unique post-translational modification termed hypusination shortly after being synthesized, which is essential for its function131. Hypusine modification of eIF5A involves two sequential reactions132 (Figure 1.5). First, the

4-aminobutyl moiety is transferred from spermidine to the amino group on a specific lysine residue (Lys-50 in the human protein) of eIF5A which is catalyzed by deoxyhypusine synthase(DHS)133. This generates eIF5A intermediate, which is then hydroxylated by deoxyhypusine hydroxylase (DOHH) to form the mature, hypusinated eIF5A133, 134. [3H] spermidine, labeling indicated that eIF5A is the only protein in eukaryotes which is hypusinated135. This modification of eIF5A is also essential for its function136. For instance, in purified translation systems, eIF5A requires to be hypusinated to stimulate methionyl-puromycin synthesis, and eIF5A hypusination is required for induction of translation of mRNAs encoding polyproline motifs126. Furthermore, eIF5A hypusination plays an evolutionarily conserved role in essential cellular processes including proliferation, growth and survival137. Accordingly, the previous study showed that the growth and viability of

S. Cerevisiae are impaired when spermidine, which is essential for hypusination is depleted from the media138. Moreover, the mutant yeast strains in which lysine residue that is hypusinated is replaced by arginine is less viable as compared to

43 its wild-type counterparts. The knockout mouse models of eIF5A and DHS are lethal in the early stage of the embryonic development139. Accordingly, in mammalian cells, eIF5A depletion or inhibition of hypusination dramatically suppress cell growth and proliferation140, whereas the eIF5A expression and hypusination levels are found to be upregulated in the premalignant pancreatic tissue in mice141. Overexpression of eIF5A1 is observed in several malignancies including lung adenocarcinoma, colorectal carcinoma, pancreatic ductal adenocarcinoma, glioblastoma and cervical carcinoma and adenocarcinoma142-144.

As with eIF5A1, upregulated eIF5A2 often leads to more advanced cancer stage, higher risk of recurrence, and lower survival rate145. Collectively, these findings point out that eIF5A and hypusination machinery play a major role in homeostasis and when dysregulated cause aberrant proliferation and growth ultimately leading to cancer development. Indeed, recent studies suggest the inhibitor of DOHH or

RNA interference-mediated silencing of eIF5A suppresses the development of cervical cancer146. Considering the emerging role of eIF5A hypusination in human diseases including cancer, inhibitors of biosynthetic enzymes involved in hypusination have been developed, most notably GC7 (DHS inhibitor), ciclopirox and deferiprone (DOHH inhibitors)146. GC7 has exhibited promising results in preclinical cancer models (e.g. CML147, 148). However, although eIF5A and its hypusination have been shown to promote protein synthesis and tumorigenesis,

44 the underlying mechanisms of these phenomena, including cellular pathways that regulate eIF5A hypusination are largely unknown. This limited understanding of the molecular underpinnings of eIF5A and hypusination machinery severely limits the applicability of hypusination inhibitors in the clinic. The objective of this thesis is therefore to decipher the role of mTOR in regulating eIF5A hypusination in the context of cancer, which in long-term may provide the molecular basis to improve the efficacy of both mTOR and DHS/DOHH inhibitors in the clinic.

SPERMIDINE NH2 eIF5A (Lys) NH

NH DHS 2 NH2 GC7 CICLOPIROX eIF5A DEFERIPRONE (Dhp) DOHH eIF5A NH (Hyp)

NH2 NH HO

NH2

FIGURE 1.5 A SCHEMATIC REPRESENTATION OF THE HYPUSINATION REACTION Hypusine is a modified amino acid (Nϵ-(4-amino-2-hydroxybutyl)-lysine) in eukaryotes that is present only in eIF5A132. Deoxyhypusine synthase (DHS) induces NAD-dependent cleavage of the polyamine spermidine and transfers the amino-butyl group to the ϵ-amino group of a single lysine residue (Lys50 for human eIF5A) on the newly synthesized eIF5A133. Subsequently, the enzyme deoxyhypusine hydroxylase/monooxygenase (DOHH) hydroxylates the intermediate to form the hypusinated mature eIF5A133. The modification happens shortly after the eIF5A synthesis as there is no pool of nascent eIF5A in the cell131. Moreover, hypusination is essential for the eIF5A function131. (adapted from Mathews MB, Hershey JW. The translation factor eIF5A and human cancer. Biochim Biophys Acta. 2015;1849(7):836-844)

46 1.4.2 DEOXYHYPUSINE HYDROXYLASE/MONOOXYGENASE (DOHH)

As pointed out in the section 1.4.1, DOHH is the enzyme that catalyzes the second step of hypusination reaction (Figure 1.5). DOHH is a Fe(II)-dependent enzyme that is thought to be the rate-limiting enzyme in eIF5A hypusination149. In the absence of the catalytic activity of DOHH, intermediate deoxyhypusine residue on eIF5A is destabilized and rapidly reverted to nascent lysine residue150.

Whereas eIF5A and DHS determine the cell viability and growth across all studies species123, the effects of DOHH on cell growth and survival appear to be organism specific. For instance, although DOHH-null yeast strain exhibits increased sensitivity to oxidative stress, it does not display defects in overall growth relative to wild type strains151. In contrast, DOHH inactivation in Drosophila melanogaster,

C. elegans, and mice is embryonic lethal152. Intriguingly, deletion of DOHH in mouse embryonic fibroblast (MEFs) and D. melanogaster cells leads to upregulation of eIF5A mRNA levels which suggest a presence of compensatory feedback loop that bolsters eIF5A expression when DOHH activity is downregulated152. This suggests that hypusinated eIF5A may play a much more fundamentally important role than the nascent/intermediate eIF5A in multicellular eukaryotes. It has also been demonstrated that DOHH plays a pivotal role in carcinogenesis153. For instance, depletion of DOHH suppresses proliferation of cervical cancer and osteosarcoma cell lines144. Accordingly, genetic and

47 pharmacological approaches (i.e. ciclopirox), to suppress DOHH activity were paralleled by strong anti-neoplastic effects in pancreatic tumor cell lines and well as human breast cancer and leukemia xenograft in mice137. Based on these findings, ciclopirox has been used in phase I clinical trial in acute myeloid leukemia154. Altogether, these data demonstrate that DOHH plays the crucial role in normal development, whereas its aberrant activity is required for maintenance of malignant phenotype.

Based on these findings, the overarching objective of this thesis is to investigate the role of DOHH and eIF5A hypusination in mTOR-driven tumorigenesis. Since both mTOR and eIF5A hypusination play a major role in cancer, and our preliminary data show that mTOR may regulate eIF5A hypusination via modulation of DOHH levels we hypothesize that the DOHH/eIF5A pathway at least in part mediates the effects of oncogenic mTOR signaling.

48 CHAPTER 2 RESULTS

2.1 EXPRESSION OF DOHH AND eIF5A mRNA IS UPREGULATED ACROSS

A VARIETY OF DIFFERENT CANCER TYPES

To establish the role of DOHH in cancer, we first set out to determine whether the expression of DOHH or its substrate eIF5A is upregulated in cancer using The

Cancer Genome Atlas (TCGA) database155. TCGA is a collaborative project of the

National Cancer Institute (NCI) and National Human Genome Research Institute

(NHGRI) that collects biospecimens of the tumor and normal tissues from over

10,000 patients that were subjected to high-throughput genome and RNA sequencing and categorized according to tumor types and clinical end points156.

Using TCGA database, the mRNA expression levels of DOHH and eIF5A were compared between primary tumor and respective normal tissue on a log2 scale using the programming language R. The mRNA expression of both DOHH and eIF5A were found to be upregulated at the statistically significant level (p-value

<0.05), and this effect was the most prominent in breast invasive carcinoma

(BRCA) and colon adenocarcinoma (COAD) (Figure 2.1). Of note, to reach adequate statistical power (0.8) we only used datasets where results were obtainable for at least 100 specimens. Collectively with reported clinical findings discussed in the Objectives chapter, these findings suggest that upregulation of

49 DOHH and eIF5A may play an important role in neoplasia, and in particular cancers of breast and colon.

2.2 DOHH IS A DOWNSTREAM TARGET OF THE mTOR PATHWAY

A preliminary study from our lab has suggested that the translational activity of

DOHH mRNA is negatively regulated by rapamycin, PP242 and metformin, which inhibit mTOR via drastically different mechanisms of action118. To validate these findings, we first investigated the effects of mTOR inhibitors on DOHH protein levels using Western blotting. To modulate mTOR signaling, EBNA1 transformed human embryonic kidney 293 (HEK293E) and MCF7 breast cancer cells were serum starved for 2 hours followed by stimulation with 20% serum in the presence of the vehicle (control; DMSO) or mTOR inhibitors rapamycin (50nM) and torin1

(250nM) for 2 hours or 24 hours. We used two cell lines to ensure that the observed effects were not a consequence of artifacts associated with potential cell-line specific inadvertent alterations. Rapamycin and torin1 inhibited serum-induced activation of mTOR as illustrated by diminished phosphorylation of its downstream targets 4E-BP1 and ribosomal protein S6(rpS6) as compared to control (Figure 2.2). Whereas 4E-BP1 is directly phosphorylated by mTOR, rpS6 is phosphorylated by a downstream effector of mTOR, Ribosomal Protein S6

Kinases 1 and 2 (S6K1/2)33. As reported previously, torin1, which is an active-site

50 mTOR inhibitor more strongly inhibited 4E-BP1 phosphorylation than rapamycin

(Figure 2.2), which suppresses mTOR signaling in an allosteric fashion60. Notably, a decrease in mTOR signaling engendered by rapamycin and torin1 was paralleled by the reduction in DOHH protein levels as compared to vehicle DMSO control (Figure 2.2). This further corroborates the tenet that mTOR regulates

DOHH expression. Repression of DOHH by mTOR inhibitors was stronger at the

24h relative to 2h treatment, thus suggesting that sustained mTOR inhibition is required to efficiently downregulated DOHH level (Figure 2.2). As expected, the level of the housekeeping protein β-actin, which was also used a loading control was unaffected by alterations in mTOR signaling. Taken together these data suggests that mTOR stimulates DOHH expression.

2.3 CHANGES IN mTOR SIGNALING DO NOT EXERT A MAJOR EFFECT ON

DOHH PROTEIN STABILITY.

Gene expression is regulated at multiple levels including DNA transcription, mRNA processing, mRNA export, mRNA stability, mRNA translation and protein degradation. We therefore next sought to establish the level(s) of gene expression at which mTOR modulates expression of DOHH. Our preliminary studies strongly suggested that the effects of mTOR on DOHH expression occur at the translational level118. To ascertain this, we first decided to exclude the possibility

51 that mTOR influences DOHH protein levels by altering its stability. The steady state cellular protein abundance is determined by the difference in the rates of protein synthesis and degradation157. To this end, we first determined the effects of mTOR on DOHH protein half-life using cycloheximde chase approach, wherein cycloheximide is used to block protein synthesis and protein decay is monitored over time by Western blotting158. Cycloheximide blocks the elongation phase of translation in eukaryotic cells by binding to the E site of the ribosome and preventing ribosome translocation158. These experiments revealed that DOHH protein has a relatively fast turnover (half-life less than 2 hours), inasmuch as

DOHH protein levels showed significant reduction [over 50% relative to the control as shown in the densitometry analysis of DOHH/β-actin] after 2 hours of cycloheximide treatment (Figure 2.3A). Importantly, mTOR signaling was upregulated by cycloheximide treatment as illustrated by higher levels of phospho-4E-BP1 in cycloheximide-treated versus control cells (Figure 2.3A).

Cycloheximide is thought to increase mTOR signaling by suppressing protein synthesis and thereby increasing intracellular amino acid levels159. Considering that DOHH levels were downregulated by 2-hour cycloheximide treatment, which coincided with mTOR activation, we concluded that it is unlikely that mTOR increases DOHH expression by increasing its protein stability.

52 The stability of the vast majority of cellular proteins is controlled by ubiquitin-dependent degradation by proteasome160. To further exclude the possibility that mTOR inhibitors suppress DOHH expression by increasing turnover of DOHH protein, we investigate whether the effects of mTOR inhibitors on DOHH protein levels will be affected using a proteasome inhibitor MG132

(carbobenzoxy-Leu-Leu-leucinal). MG132 did not exert a major effect of mTOR inhibitor-induced downregulation of DOHH expression, whereby the levels of

DOHH in cell treated with the combination of MG132 and mTOR inhibitors were dramatically lower than those observed in control untreated cells (Figure 2.3B). As a positive control for proteasome inhibition by MG132, we used p53, a tumor suppressor protein that exhibits extremely rapid turnover in non-stressed cells, which is in large part mediated by MDM2/HDM2 E3 ubiquitin ligase161. As expected, MG132 increased p53 protein levels as compared to the control (Figure

2.3B). Collectively, these data show that mTOR does not exert a major effect on

DOHH protein stability.

2.4 DOHH mRNA LEVELS ARE NOT MODULATED BY mTOR SIGNALING

Genome-wide translatome analysis suggested that DOHH mRNA is translated in an mTOR-dependent manner in MCF7 cells118. To this end, we confirmed that mTOR regulates DOHH expression, by showing that mTOR inhibitors induce

53 dramatic downregulation of DOHH protein levels in both MCF7 and HEK293E cells (Figure 2.4). Moreover, we show that the effects of mTOR on DOHH protein expression are not majorly affected by the changes in DOHH protein stability. We next examined whether mTOR regulates steady-state DOHH mRNA abundance.

Steady-state mRNA abundance is positively influenced by DNA transcription, and negatively affected by mRNA decay162. To this end, HEK293E cells and MCF7 cells were maintained in full media supplemented with fresh serum and incubated in the presence of a vehicle (DMSO), or rapamycin (50nM) or torin1 (250nM), for

2 hours. After treatments, cells were lysed in Trizol; mRNA was isolated and subjected to RT-qPCR analysis as described in the methods section. Levels of

DOHH mRNA relative to GAPDH mRNA were comparable between mTOR inhibitor-treated and control samples (Figure 2.4A, 2.4C). Housekeeping GAPDH mRNA was used for normalization of DOHH mRNA levels, as it is well established that mTOR inhibitors do not affect the abundance of GAPDH transcripts16.

Nonetheless, to avoid possible misrepresentation of the results stemming from the spurious correlation (i.e. that the congruent alteration in GAPDH levels masks potential effects of mTOR inhibitors on DOHH mRNA levels), we normalized

GAPDH mRNA levels over β-actin mRNA which is encoded by another mTOR-insensitive housekeeping gene16. This revealed that mTOR inhibitors indeed do not alter GAPDH transcript levels (Figure 2.4B, 2.4D). Collectively,

54 these findings demonstrate that mTOR does not control DOHH expression at the level of transcription or mRNA stability.

2.5 mTOR INCREASES TRANSLATIONAL EFFICIENCY OF DOHH mRNA

Thus far, we excluded the possibility that mTOR regulates transcription or stability of DOHH mRNA as well as DOHH protein turnover. To confirm that the regulation of DOHH expression by mTOR takes place at the level of mRNA translation, we next performed polysome profiling analysis. As above, MCF7 cells were stimulated with serum in the presence of a vehicle (DMSO), rapamycin (50nM) or torin1 (250nM) for 2 hours, upon which cytosolic extracts were obtained by lysing cells in the hypotonic buffer. Cytosolic extracts were overlaid over 5-50% sucrose gradients and subjected to ultracentrifugation to separate efficiently and inefficiently translated mRNAs (see methods section). As described in section 1.2, polysome profiling separates mRNAs based on the number of ribosomes they bind, whereby efficiently translated mRNAs that bind many ribosomes (i.e. heavy polysomes) sediment towards the bottom of the gradient, while transcripts that are inefficiently translated and associate with less ribosomes (i.e. light polysomes) stay close to the top of the gradient (Figure 1.2). Number of polysomes relative to monosome (80S) and ribosomal subunits (40S and 60S) is illustrative of the global translational activity in the cell56. As expected, mTOR inhibitors suppressed 55 global protein synthesis as evidenced by the reduction in polysomes and the concomitant increase in monosome peak (Figure 2.5A, 2.5C). Next, we isolated

RNA from each fraction of the sucrose gradient and determined the quantity of

DOHH and β-actin mRNA using RT-qPCR. Rapamycin induced a substantial shift of DOHH mRNA towards the top of the gradient (light polysome fractions) as compared to a vehicle (Figure 2.5B, 2.5D, 2.5F). This indicates that rapamycin decreases the number of ribosomes that associate with DOHH transcripts, and thus represses translation of DOHH mRNA. Notably, rapamycin exerted a minimal effect on the distribution of mTOR-insensitive β-actin mRNA across the gradient relative to the control (Figure 2.5F). Parallel results were obtained for torin1 treatment, except in this case individual fractions of sucrose gradient were pooled into pre-polysomal, light- and heavy-polysomal fractions as indicated in the figure 2.5A before RNA isolation and RT-qPCR analysis (Figure 2.5B). Overall, these findings indicate that mTOR controls DOHH expression by stimulating translation of the corresponding mRNA.

2.6 DOHH PROTEIN EXPRESSION IS INDEPENDENT OF THE 4E-BP STATUS

IN THE CELL

We and others have previously shown that 4E-BPs play a major role in the selective regulation of translation downstream of mTOR93. Moreover, 4E-BPs are

56 major effectors of mTOR signaling on cell proliferation and neoplastic growth93.

As outlined in detail in section 1.1.1, 4E-BPs bind to the overlapping surface on eIF4E as eIF4G, which prevents eIF4E-eIF4G association and the eIF4F complex assembly163. mTOR phosphorylates 4E-BPs, which leads to their dissociation from eIF4E, thereby allowing the eIF4F complex assembly93. Changes in the eIF4F levels affect translation of subsets of mRNAs more than the others, whereby the dependence of a given mRNA to the eIF4F complex or its subunits levels is largely predetermined by the 5’ UTR features16. Therefore, we next investigated whether 4E-BPs mediate effects of mTOR on DOHH translation. To this extent, MEFs cells depleted of 4E-BP1 and 2 using shRNA, or as a control infected with scrambled shRNA, were treated with a vehicle (DMSO), rapamycin

(50nM) or torin1 (250nM) for 2 hours. Unexpectedly, Western blotting analysis showed that mTOR inhibitors decreased DOHH protein levels to the same extent in 4EBP1/2 knockout and control cells. This indicates that although mTOR stimulates translation of DOHH mRNA, these effects are most likely not mediated by 4E-BPs, which raises plausibility that other mTOR effectors such as S6Ks, or yet to be identified factors affect DOHH protein synthesis downstream of mTOR.

2.7 IDENTIFYING THE ROLE OF eIF5A HYPUSINATION IN mTOR

57 DEPENDENT TUMORIGENESIS

Considering that mTOR regulates DOHH levels, and that mTOR, DOHH and eIF5A hypusination have been implicated in cancer, we next investigated whether

DOHH mediates oncogenic mTOR signaling. To examine this, we used the advantage of PTEN-/- HCT116 colon cancer cells, in which mTOR activity is hyperactivated due to the loss of its negative regulator PTEN164. This mimics a number of cancers, including those of colon and prostate in which oncogenic mTOR signaling is activated via the loss of PTEN function165. To test the role of

DOHH in mTOR-driven oncogenesis, we depleted DOHH levels in PTEN-/-

HCT116 colon cancer cells and monitored their anchorage-independent growth using soft agar colony formation assay. The ability of cells to grow and form colonies in soft agar is a measurement of their neoplastic potential in vitro inasmuch as non-transformed cells do not form colonies in soft agar due to contact inhibition166. DOHH depletion by shRNA was confirmed by Western blotting, whereby DOHH levels in cells infected with shRNA targeting DOHH were dramatically lower than those observed in control cells infected with scrambled shRNA (Figure 2.7C). Strikingly, the number of colonies formed by PTEN-/-

HCT116 was reduced by ~ 2.5-3 fold upon DOHH depletion (Figure 2.7A). These data demonstrate that DOHH is likely to play a pronounced role in mTOR-driven tumorigenesis induced by loss of PTEN function.

FIGURE 2.1 EXPRESSION OF DOHH AND eIF5A mRNA IS UPREGULATED ACROSS A VARIETY OF DIFFERENT CANCER TYPES mRNA levels of DOHH and eIF5A presented on a log 2 scale in normal vs. tumor tissue of breast and colon cancers according to The Cancer Genome Atlas (TCGA) datasets. The DOHH and eIF5A transcripts are overexpressed in primary tumor as compared to normal tissue across different cancer types. P < 0.05, as determined by the student t-test.

FIGURE 2.2 DOHH IS A DOWNSTREAM TARGET OF THE mTOR PATHWAY A, B. HEK293E (A) and MCF7 cells (B) were serum starved for 2 hours followed by 2-hour or 24-hour 20% serum stimulation in the presence of a vehicle (DMSO) torin1 (250 nM), or rapamycin (250 nM). The expression levels and phosphorylation of indicated proteins were determined by Western blotting. β-actin served as a loading control. A representative of 3 independent experiments is shown (n = 3).

FIGURE 2.3 CHANGES IN mTOR SIGNALING DO NOT EXERT A MAJOR EFFECT ON DOHH PROTEIN STABILITY A. MCF7 cells were treated with 100μg/ml cycloheximide for indicated times in full growth medium to block de novo protein synthesis. Cell lysates were subjected to Western blotting and probed with the indicated antibodies were used. β-actin served as a loading control. A representative of 3 independent experiments is shown (n = 3). B. The MCF7 cells were starved for 2 hours followed by a 4-hour 20% serum stimulation in the presence of vehicle (DMSO), torin1 (250nM), rapamycin (250nM) or MG132 (50μM) as indicated. The cell lysates were subjected to Western blotting with the indicated antibodies. β-actin was used as a loading control. A representative of 3 independent experiments is shown (n = 3). C. The intensity of DOHH and β-actin bands from A were analyzed using densitometry and the relative intensities are plotted. Bars represent SD values of 3 independent experiments.

FIGURE 2.4 DOHH mRNA LEVELS ARE NOT MODULATED BY mTOR SIGNALING A-D MCF7 (C-D) and HEK293E (A-B) cells were starved for 2 hours and then treated with DMSO, rapamycin (50 nM) or torin1 (250 nM) in the presence of 20% serum for 2 hours. RNA was extracted using Trizol and the levels of DOHH, GAPDH, and β-actin mRNAs were determined by reverse transcriptase-quantitative PCR (RT-qPCR). A relative fold changes of DOHH against housekeeping gene GAPDH and GAPDH against another housekeeping gene β-actin are presented. Data were expressed as mean ± standard deviation of three independent experiments. The student’s t-test was used to show the relative mRNA level of DOHH between treatments and vehicle control were not statistically significant.

FIGURE 2.5 mTOR INCREASES TRANSLATIONAL EFFICIENCY OF DOHH mRNA A, C. MCF7 cells were serum starved overnight and then stimulated with 20% serum in the presence of a vehicle (DMSO) or Torin1 (250 nM) for 2 hours. Cell extracts were isolated and separated in 5-50% sucrose gradients by ultracentrifugation. Fractions were collected with continuous monitoring of the absorbance at 254nm.

63 B. mRNAs from the fractions corresponding to ribosomal subunits and the monosome (80S) (pre-polysomes), 2-3 (light polysomes), and 4 and more ribosomes (heavy polysomes) were pooled and quantified by RT-qPCR. Data are presented as the mean percentage of the mRNA in each pooled fraction relative to the total mRNA. Bars represent SD values of three independent experiments (n = 3). D, E, F. mRNAs from each fraction were isolated and RT-qPCR were performed on the indicated genes. Data are presented as the mean percentage of the mRNA in each pooled fraction relative to the total mRNA. Bars represent SD values of three independent experiments (n = 3).

FIGURE 2.6 DOHH PROTEIN EXPRESSION IS INDEPENDENT OF THE 4E-BP STATUS IN THE CELLS MEFs cells depleted of 4E-BP1 and 2 (shRNA-4E-BP1/2) or infected with scrambled control shRNA (Scramble) were serum starved for 2 hours and then stimulated with 20% serum in the presence of a vehicle (DMSO), torin1 (250 nM), or rapamycin (250 nM) for 2 hours. The levels of indicated proteins were monitored by Western blotting using appropriate antibodies. β-actin served as a loading control. A representative of 3 independent experiments is shown (n = 3).

65 PTEN-/- Scramble PTEN-/- ShDOHH

FIGURE 2.7 DOHH IS REQUIRED FOR THE NEOPLASTIC GROWTH OF HCT116 PTEN-/- CELLS PTEN-deficient HCT116 cells were infected with shRNA against DOHH or control scrambled mRNA. Anchorage-independent foci assays were performed by plating 5000 cells into the soft agar. Two to three weeks post-plating, the colonies were stained and colonies number were counted. A. Representative photographs of stained HCT116 PTEN-/- colonies. B. Bar graph represents the number of stained colonies per well in scrambled or shRNA-DOHH expressing cells. Error bars show standard deviations of 3 independent experiments. C. Western blotting of DOHH, PTEN and loading control β-actin demonstrates the effectiveness of the knockout.

66 CHAPTER 3 DISCUSSION mRNA translation is a major step in the regulation of gene expression which plays a major role in the maintenance of cellular homeostasis3. Dysregulation of mRNA translation is therefore implicated in a variety of human pathologies including cancer, diabetes and neurological disorders5. A wide range of studies has shown that mTOR is one of the major regulators of mRNA translation that integrates divergent intracellular and extracellular stimuli to regulate a variety of downstream effectors thereby inciting biological responses involving an increase in cell proliferation, growth, survival, and anabolic metabolism66. Aberrant activation of mTOR signaling, which is caused by mutations in a number of oncogenes (e.g.

PIK3CA, K-RAS) or tumor suppressors (e.g. PTEN, TSC1/2) results in neoplastic transformation108. The effects of oncogenic mTOR signaling are thought to be at least in part mediated by the translational apparatus33. Considering that cellular processes which are regulated by mTOR pathway are frequently dysregulated in human cancer, mTOR emerged as one of the most attractive therapeutic targets167. However, the efficacy of mTOR inhibitors in the clinic was less than expected, which highlights the importance of improving the understanding of the molecular underpinnings of the oncogenic mTOR signaling168. Notwithstanding that it has been well established that the major mediators of the effects of mTORC1 on protein synthesis are 4E-BPs and S6 kinases, recent findings

67 demonstrate that the role of the mTOR pathway in regulating protein synthesis is much more complex than previously appreciated92. In this study, we aimed to establish the role of DOHH protein and eIF5A hypusination in mediating oncogenic mTOR signaling. eIF5A hypusination is thought to play a central role in the regulation of protein synthesis, and therefore the goal of our study was to determine the role of the DOHH/eIF5A axis in hitherto unknown facets of mTOR-dependent dysregulation of mRNA translation in neoplasia.

DOHH is a rate-limiting enzyme which catalyzes a unique post-translational modification - hypusination of eIF5A133, 134. eIF5A hypusination is required for its functions and eIF5A is the only known eukaryotic protein that undergoes this modification131. Our previous study wherein we interrogated the effects of direct

(i.e. rapamycin, PP242) and indirect (i.e. metformin) mTOR inhibitors on the genome-wide changes in the translatome of MCF7 breast cancer cells, revealed that mTOR might bolster translation of DOHH mRNA118. In the present study, we validated these findings and demonstrated that mTOR indeed stimulates DOHH protein expression. DOHH protein levels were dramatically downregulated by allosteric (rapamycin) and active-site mTOR inhibitors (torin1) in MCF7 and

HEK293E cells. These results established that mTOR positively regulates DOHH protein expression. We next confirmed that mTOR regulates DOHH protein levels at the level of translation, and not at the level of mRNA abundance (which reflects

68 changes in transcription and mRNA stability) or protein stability. Collectively, these findings indicate that mTOR induces DOHH expression by increasing translation of the corresponding mRNA.

Notwithstanding that mTOR inhibition leads to suppression of global protein synthesis, we and others have demonstrated that a subset of mRNAs exhibits much higher sensitivity to the alterations in mTOR signaling than others97. To this end, “mTOR-sensitive” mRNAs comprise those that harbor 5’ terminal oligopyrimidine motifs (5’TOP) which encode components of translational machinery, mRNAs with long and structured 5’ UTRs that are enriched for proliferation- and survival-promoting factors and oncogenes (e.g. cyclins, BCL-2 family members and c-MYC), and transcripts with extremely short 5’ UTRs which encode proteins with mitochondrial functions including components of the electron transport chain complexes16. In contrast, mTOR inhibition, and in particular in the acute setting (e.g. mTOR inhibitor treatments for 12h and less), has only a marginal effect on the translation of other cellular mRNAs including those encoding housekeeping proteins (e.g. GAPDH, β-actin)16. In this way, changes in mTOR signaling reprogram the proteome at least in part by engendering selective changes in the translatome.

It is thought that the effects of mTOR on the selective changes in the translatome are chiefly induced by the mTORC1 complex-dependent inactivation of 4E-BPs,

69 which as outlined in the “introduction section” of the thesis allows eIF4G:eIF4E interaction and the assembly of the eIF4F complex93. The recruitment of eIF4F to the cap structure on the mRNAs is particularly important for the translation of mRNAs with long and complex 5’ UTR features22. This is thought to be a consequence of the enhanced requirement of such mRNAs for the unwinding activity of the eIF4A helicase subunit of the eIF4F complex169. More recently, we demonstrated, that the mTORC1/4E-BP axis also controls translation of mRNAs harboring extremely short 5’ UTRs, whereby translation of these transcripts is extremely sensitive to the changes in eIF4E, but not eIF4A levels16. Unexpectedly, we found that 4E-BP1/2 depletion in MEFs cells, that uncouples mTOR inhibition from eIF4F disassembly, does not exert a major effect on DOHH protein levels.

We, therefore, concluded that mTOR regulates DOHH expression independently of 4E-BPs. In addition, according to the RefSeq database, DOHH harbors a long 5’

UTR with the length of 452 nt, which implies the translation of DOHH mRNAs could be sensitive to eIF4A.

The ribosomal protein S6 kinase 1 and 2 (S6K1/2), is another major substrate of mTORC1, which plays a crucial role in translation regulation96. S6Ks phosphorylates serine residues within the C-terminus of rpS6 (S235, 236, 240 and 244 in mammals)170. Moreover, S6Ks have been implicated in the regulation of translation initiation via phosphorylating translation initiation factor eIF4B, which

70 is an auxiliary protein that bolsters eIF4A activity97. Besides initiation, S6Ks also plays a role in the regulation of elongation step of translation by regulating the function of the eukaryotic translation elongation factor 2 (eEF2)102. This occurs through S6K1-mediated phosphorylation of the eEF2 kinase on S366 which results in its inhibition and consequent reduction in eEF2 phosphorylation, which results in enhancement of eEF2 activity102. Notwithstanding that dysregulation of

S6K signaling has also been linked to various pathologies including cancer96, the effects of S6Ks on the translatome are less well understood, than those mediated by 4E-BPs. To this end, we will test whether S6Ks may mediate the effects of mTOR on DOHH mRNA translation and protein levels. Moreover, it is becoming apparent that S6K1 and S6K2 functions may not be redundant. For instance, in some cancer types such as breast cancer, S6K1 and S6K2 appear to exert opposite effects on cell survival171. Therefore, using genetic (CRISPR/Cas9, overexpression of constitutively active S6K1 and S6K2) and pharmacological means (S6K1/2 inhibitors) we will dissect the role(s) of S6K1 and S6K2 in the regulation of DOHH translation downstream of mTOR.

In addition to 4E-BPs and S6Ks, mTOR has been demonstrated to regulate several other components of the translational initiation machinery and associated factors including eIF4G and La-related protein 1 (LARP1)101. We will therefore also investigate plausible role(s) of these proteins in mediating the effects of

71 mTOR on DOHH protein synthesis. Finally, 5’ UTR features of mRNAs are thought to be a major determinant of the translation initiation efficiency, whereby 5’

UTR length and complexity have been demonstrated to ascribe translational dependence of mRNAs to mTOR signaling4. In our recent study, we observed that databases such as RefSeq or UCSF Genome browser often contain incorrect information regarding 5’ UTRs of mRNAs expressed in a given cell line. To this end, we adapted the nano Cap analysis gene expression (nanoCAGE) method, which is a next-generation sequencing based method that allows precise capturing of 5’ ends of transcripts in cells172. We will use nanoCAGE to map 5’

UTR of DOHH mRNA in MCF7 cells, whilst simultaneously monitoring its translational activity using polysome profiling. This will not only reveal features of

5’ UTR of DOHH mRNA in MCF7 cells, but also indicate the potential presence of

DOHH isoforms that differ in their 5’ UTR that could be differentially translationally regulated. Taken together, our data show that mTOR controls expression of

DOHH at the level of translation by yet unknown 4E-BP-independent mechanism.

The hypusination pathway activates eIF5A, which in turn stimulates translation of a limited number of mRNAs including those mRNAs that encode proteins harboring poly-proline motifs128. In addition, eIF5A has been implicated in various other aspects of post-transcriptional regulation of gene expression including nuclear mRNA export and mRNA degradation130. Our findings show that mTOR, a

72 master regulator of mRNA translation, stimulates the hypusination pathway by inducing an increase in levels of the rate-limiting enzyme DOHH. These findings suggest that in addition to its effects on translation via established substrates (e.g.

4E-BPs and S6Ks), mTOR may indirectly modulate translation and more globally post-transcriptional gene expression programs via the DOHH/eIF5A axis, which is a possibility that we will explore in the future.

Dysregulation of mTOR signaling, DOHH and eIF5A hypusination are frequently associated with malignant tumors161,125. Though the role of hypusinated eIF5A has not been fully characterized, it is known to be upregulated in many cancers141. mTOR signaling is also commonly dysregulated in cancer and mTOR inhibitors have been used in a plethora of clinical trials108. We established a link between mTOR and eIF5A hypusination inasmuch as we demonstrated that mTOR induces expression of DOHH which is a rate limiting enzyme in hypusination reaction. PTEN is a tumor suppressor that is frequently inactivated in multiple cancer types including hepatocellular carcinoma, glioblastoma, melanoma, lung carcinoma, prostate cancer and endometrial carcinomas as well as in hereditary cancer predisposition syndromes referred to as Cowden disease70. PTEN is involved in multiple cellular processes such as cell survival, proliferation, energy metabolism and cellular architecture, which in large part is achieved via suppression of mTOR activity70. Anchorage independent growth of colon cancer

73 HCT116 PTEN-/- cells, wherein deficiency in PTEN function leads to hyperactivation of mTORC1 was debilitated by DOHH depletion. This suggests that DOHH and the hypusination pathway constitute a hitherto unrecognized arm of the oncogenic mTOR signaling.

Due to the singularity of eIF5A hypusination and its involvement in a variety of cancers, the hypusination pathway represents an attractive therapeutic target130.

Several inhibitors of the hypusination pathway that target DHS/DOHH axis have been developed and exhibited promising results in pre-clinical studies and are now entering clinical trials145. DHS inhibitor GC7 is presently used in clinical trials on neuroblastoma173. In addition, DOHH inhibitor ciclopirox suppressed the pancreatic cancer cell growth in vitro145. Our results suggest that the use of eIF5A hypusination inhibitors may also be warranted in malignancies wherein mTOR signaling is upregulated including those exhibiting a loss of PTEN function.

In conclusion, in this work we show that mTOR stimulates expression of DOHH protein by bolstering the translational efficiency of DOHH mRNA, and provide evidence that the eIF5A hypusination pathway plays a role in mediating oncogenic mTOR signaling. Our findings therefore suggest the presence of an additional axis of mTOR signaling towards translational machinery. Notably, although a number of mTOR inhibitors entered cancer clinical trials, the results were far less than expected168. Therefore, more fundamental research is required

74 to grasp the entire complexity of mTOR signaling as this knowledge is essential to provide the molecular basis for more rational application of mTOR inhibitors in cancer treatment. I hope that the findings presented in this thesis will contribute to such efforts.

75 CHAPTER 4 MATERIALS AND METHODS

4.1 CELL CULTURE AND DRUG TREATMENTS

MCF7 and HEK293E cells were obtained from American Type Culture Collection and maintained in DMEM (HEK293E) and RPMI-1640 (MCF7) medium supplemented with 10% fetal bovine serum, 1% penicillin/streptomycin and 1%

−/− L-glutamine, at 37 °C and 5% CO2. HCT116 PTEN cells (a generous gift from Dr.

Waldman) were cultured in DMEM supplemented with 10% fetal bovine serum, 1%

penicillin/streptomycin and 1% L-glutamine, at 37 °C and 5% CO2. 4EBP1/2 double knockout MEFs were obtained from Dr. Sonenberg (Petroulakis et al.,

2009) and maintained in DMEM supplemented with 10% fetal bovine serum, 1%

penicillin/streptomycin and 1% L-glutamine, at 37 °C and 5% CO2. MCF7 cells infected with control, non-targeting scrambled shRNA or shDOHH harboring lentiviruses were maintained in RPMI-1640 supplemented with 10% fetal bovine

serum, 1% penicillin/streptomycin and 1% L-glutamine, at 37 °C and 5% CO2 media in the presence of 2 µg/ml puromycin.

The drugs and their concentrations used in the indicated experiments are as following: 250 nM torin1 (Tocris), 50 nM rapamycin (Calbiochem), 50 µM MG132

(Z-Leu-Leu-Leu-al) and 100 µg/ml cycloheximide were from Sigma-Aldrich. All compounds were dissolved in DMSO and stocks were maintained at -80 °C. An equal volume of DMSO was used as a vehicle control in the experiments.

4.2 LENTIVIRUS shRNA AND INFECTIONS

1.2 μg/ml Lentiviral vectors (pwpi vector from addgene as the scramble

(https://www.addgene.org/12254/), DOHH shRNA plasmid

(CCGGAGGTGGCTCTGGACATGTATGCTCGAGCATACATGTCCAGAGCCAC

CTTTTTTG) for DOHH silencing) were transfected independently into HEK293FT cells along with 0.8 μg/ml lentivirus packaging plasmid (psPAX2) and 0.4 μg/ml

VSV-G envelope expressing plasmid (PMD2.G) using 800 μl/ml lipofectamine p2000 (Invitrogen). The virus containing supernatants were collected 48 and 72 hours post-transfection, and filtered through a 0.45 mm nitrocellulose filter to remove any cell debris. The supernatants were then overlaid over target cells

(HCT116 PTEN−/− cells) in the presence of 1 μg/ml polybrene. 48 hours post-infection, the targeted cells were selected with puromycin (2 µg/ml). The extent of DOHH knockdown was estimated by monitoring DOHH protein levels by

Western blotting.

4.3 CELL LYSIS AND WESTERN BLOTTING ANALYSIS

Cells were washed with ice-cold 1x PBS, and scraped lysed in RIPA buffer [10 mM Tris (pH 7.3), 150 mM NaCl, 1% (v/v) Triton, 1% (w/v) sodium deoxycholate,

1 mM EDTA, 50 mM NaF, 10 mM β-glycerophosphate and EDTA-free protease 77 inhibitors (Roche)]. Cell lysates were clarified by centrifugation at 13,000 rounds per minute (rpm) for 7 minutes at 4°C. Protein concentration in the lysates was determined using the bicinchoninic acid assay (kit purchased from Thermo Fisher

Scientific) and 20-80 μg of protein were loaded onto 10% or 15%

SDS-polyacrylamide gels (SDS-PAGE; depending the size of the protein of the interest) and were separated by electrophoresis in the Tris-glycine running buffer

(0.0025 M Tris, 0.0192 M glycine, 0.01 % SDS, pH 8.5). This was followed by transfer onto a nitrocellulose membrane (Bio-rad) using transfer buffer (25 mM

Tris, 190 mM glycine, 20% methanol). The quality of the transfer was assessed using Ponceau S staining and the membrane were blocked in 5% skim milk (w/v) in Tris-buffered saline containing 0.1% Tween 20 (TBST) for 30 minutes at room temperature. The primary antibodies were diluted as indicated below in 5% (w/v) bovine serum albumin (Sigma-Aldrich) in TBST and incubated with membranes overnight at 4 °C. The following primary antibodies were used: anti-4E-BP1(53H11) antibody #9644 (1:2000), anti-p-4E-BP1(S65) antibody

(174A9) #9456 (1: 1,000), anti-p-rpS6 antibody (S240/ 244) #2215 (1: 1,000), anti-PTEN antibody (138G6) #9559 (1: 1,000), anti-p-53 antibody #9282 (1: 1,000) from Cell Signaling Technologies; anti-rpS6 (C-8) antibody #sc-74459 (1: 2,000), anti-DOHH antibody (1: 1,000) sc-55161 from Santa Cruz Biotechnologies; anti-β-actin (AC15; 1:5,000) #A1978 from Sigma; anti-DOHH antibody (1: 1,000)

78 ab122946 from Abcam. The next day, membranes were washed with TBST three times for 10 minutes at room temperature, before incubating them with the corresponding secondary antibody (1:5,000; Amersham, goat anti-mouse/anti-rabbit) for 1 hour at room temperature. After incubation with secondary antibodies, membranes were washed with TBST three times for 10 minutes at room temperature, and the signal was visualized on X-ray film using enhanced chemiluminescence according to the manufacturer’s instructions (ECL,

GE Healthcare Life Science). Where possible, membranes were reused and incubated with other primary antibodies after being stripped using stripping buffer

(0.1 M glycine, 20 mM magnesium acetate, 50 mM KCl, pH 2.2).

4.4 POLYSOME PROFILING AND RNA EXTRACTION

MCF7 cells were cultured in 15cm Petri dishes and serum starved overnight. The next day, cells were treated with mTOR inhibitors (250 nM torin1 or 50 nM rapamycin) or the equal volume of the vehicle (DMSO) in the presence of 20% fetal bovine serum for 2 hours. Cells were washed and scraped in 1x PBS containing 100 µg/ml cycloheximide. After 2 hour of centrifugation at 4°C and

36000 rpm, the pellets were lysed in 500 μl of hypotonic lysis buffer [5 mM

Tris-HCl (pH 7.5), 2.5 mM MgCl2, 1.5 mM KCl, 2 mM dithiothreitol (DTT), 100 units of RNase inhibitor, 0.5% Triton, 0.5% sodium deoxycholate, 100 μg/ml

79 cycloheximide]. The cell lysates were centrifuged at 14000 rpm for 7 minutes at

4 °C to remove cellular debris. The absorbance of the resulting supernatants at

254 nm was measured using nanodrop. 10 ODs (optical densities) at 254 nm were loaded on top of 5-50% sucrose gradient, which was made in sucrose buffer (200 mM HEPES (pH 7.6), 1 M KCl, 50 mM MgCl2, 100 µg/ml cycloheximide, 1x protease inhibitor cocktail (EDTA-free), 100 units/ml RNase inhibitor) using gradient maker. Gradients were loaded into the SW41 rotor (Beckman) and sedimented at 41,000 rpm for 2-hours at 4 °C. Upon ultracentrifugation, gradients were fractionated in 750 μl fractions on ISCO FOXY fractionator equipped with a

UV detector with continuous absorbance monitoring at 254 nm. The obtained polysome profiles were normalized and aligned based on the same under the curve area with the R script code developed with the help of Dr. Ola Larsson at

Karolinska Institutet. For RNA analysis, each collected sample was mixed with 750

µl Trizol from Thermo Fisher Scientific and RNA was isolated as directed by the manufacturer. The isolated RNA was analyzed using RT-qPCR as outlined below.

4.5 REVERSE TRANSCRIPTASE-QUANTITATIVE PCR (RT-qPCR) AND

PRIMERS

RNA in each was quantified using nanodrop and the 500ng of each RNA fraction was used in the subsequent RT-qPCRs. RNA was first reverse transcribed to

80 complementary DNA (cDNA) using the cDNA synthesis kit (SuperScript IV VILO

Master Mix from Invitrogen) according to the manufacturer’s instructions. Levels of cDNAs indicated in figures were then quantified using quantitative real-time polymerase chain reactions (qPCR) using Fast SYBR Green Mastermix

(Invitrogen) according to the manufacturer’s protocol.

Primers were designed using NCBI Primer-Blast (http://www.ncbi. nlm.nih.gov/tools/primer-blast/), whereby the PCR product length was set between 100 and 200 nt. To avoid contamination with genomic DNA, primers were chosen to correspond to different exons. Primers were purchased from

Integrated DNA Technologies (IDT). Primer efficiency was determined using a standard curve method, whereas their specificity was verified by monitoring melting curves of corresponding PCR products and their size using agarose gel electrophoresis.

The sequences of the primers used in this study are as indicated:

DOHH forward primer 5’-TCACGTGGGCGAGAAAATGG-3’; reverse primer

5’-AACCCTGCTCAGGCTAAACC-3’ Amplicon size = 111 nt; rpS6 forward primer

5’- AATGGAAGGGTTATGTGGTCCG -3’ and a reverse primer

5’-CCCCTTACTCAGTAGCAGGC-3’ Amplicon size = 102 nt. β-actin forward primer 5’- ACCACACCTTCTACAATGAGC-3’; reserve primer

81 5’-GATAGCACAGCCTGGATAGC-3’ Amplicon size = 163 nt. GAPDH forward primer 5’- AATCCCATCACCATCTTCCA -3’ reserve primer

5’-TGAGTCCTTCCACGATACCA-3’ Amplicon size = 110 nt.

Data were analyzed using relative standard curve method as described in ABI

User Bulletin # 4 (docs.appliedbiosystems.com/pebiodocs/04306234.pdf)174. The

Ct value of each fraction of each gene is quantified as the relative percentage over input. Results represent mean values from two independent experiments each carried in triplicate +/- standard deviation.

4.6 SOFT AGAR COLONY FORMATION ASSAY

The bottom soft agar layer was generated by mixing 1% agarose and 2X DMEM medium in the 6-well plate. 5000 HCT116 cells were counted and mixed with 0.6% agarose containing 2X growth medium and the mixture was overlaid over the bottom layer. 100μl of DMEM warm medium was added every three days. In approximately 2 to 3 weeks, visible colonies were formed and stained with 200 μl nitroblue tetrazolium chloride solution overnight (1mg/ml in 1X 37 °C PBS). The

GelCount image analysis software was used to detect and automatically count the colonies in each well using the following parameters:

82 24-bit color, 1200 dpi resolution. Colony numbers per well are represented as mean value +/- standard deviation of 3 replicates.

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