Repression of the Protein Kinase PIM3 by an Mtorc1-Regulated Microrna

Repression of the protein kinase PIM3 by an mTORC1-regulated microRNA

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A dissertation presented

Ilana Ashley Kelsey

The Division of Medical Sciences

in partial fulfillment of the requirements

for the degree of

Doctor of Philosophy

in the subject of

Biological and Biomedical Sciences

Harvard University

Cambridge, Massachusetts

August 2017

Repression of the protein kinase PIM3 by an mTORC1-regulated microRNA

Abstract

The mechanistic target of rapamycin complex 1 (mTORC1) is a central regulator of cell growth that is often aberrantly activated in cancer. However, mTORC1 inhibitors, such as rapamycin, have limited effectiveness as single agent cancer therapies, with feedback mechanisms inherent to the signaling network thought to diminish the anti-tumor effects of mTORC1 inhibition. The goals of this dissertation were to characterize pro-survival effectors activated upon mTORC1 inhibition, and to determine the functional significance of these downstream targets, including relevance to the development of targeted therapies in combination with mTORC1 inhibitors.

I identify the repression of protein kinase and proto-oncogene PIM3 downstream of mTORC1 signaling. PIM3 expression is suppressed in cells with loss of the tuberous sclerosis complex (TSC) tumor suppressors, which exhibit growth factor-independent activation of mTORC1, and in the mouse liver upon feeding-induced activation of mTORC1. Inhibition of mTORC1 with rapamycin induces PIM3 transcript and protein levels in a variety of settings. Suppression of PIM3 involves the sterol regulatory element-binding (SREBP) transcription factors SREBP1 and 2, whose processing and mRNA expression are stimulated by mTORC1 signaling. I found that PIM3 repression is mediated by miR-33, an intronic microRNA encoded within the SREBP loci, the expression of which is decreased with rapamycin.

I sought to better understand the functional implications of miR-33 induction by mTORC1, and the subsequent induction of PIM3 upon mTORC1 inhibition. Specifically, I show that PIM inhibition in combination with mTOR inhibitors may be a promising therapy in some cancer settings. I also identify several additional mTORC1-regulated miR-33 targets that contribute to cell survival and metabolism,

iii including PIM1, which is closely related to PIM3. Finally, I explore the metabolic changes affected by

PIM inhibition, providing an additional rationale for the regulation of PIM3 by mTORC1.

Collectively, these studies identify a pro-survival kinase that is activated upon mTORC1 inhibition while highlighting the importance of further characterization of miR-33 targets altered downstream of mTORC1. Our results will guide future studies of mTORC1-regulated microRNAs and pro-survival pathways, with potential implications for the effects of mTORC1 inhibitors in TSC, cancer, and the many other disease settings influenced by aberrant mTORC1 signaling.

TABLE OF CONTENTS

ABSTRACT iii

LIST OF FIGURES viii

GLOSSARY OF TERMS x

DEDICATION xv

ACKNOWLEDGEMENTS xvi

CHAPTER 1: INTRODUCTION 1

1.1 mTORC1 is a major regulator of cell growth and metabolism

1.1.1 Overview

1.1.2 Upstream regulation of mTORC1

1.1.3 Downstream processes regulated by mTORC1

1.1.4 mTORC1 control of coding and non-coding RNA expression

1.1.5 mTORC1 signaling in disease

1.2 The PIM kinase family in signaling and disease

1.2.1 Overview

1.2.2 Upstream regulation of PIM kinases

1.2.3 Downstream targets of PIM kinases

1.2.4 PIM kinases in cancer

1.3 Specific Aims and Overview of the Dissertation

1.4 References

CHAPTER 2:

mTORC1 SUPPRESSES PIM3 EXPRESSION VIA miR-33

ENCODED BY THE SREBP LOCI 50

2.1 Abstract

2.2 Introduction

2.3 Materials and Methods

2.4 Results

2.4.1 PIM3 expression is repressed downstream of mTORC1 and induced by mTOR inhibitors

2.4.2 A survey of mTORC1-regulated transcription factors identifies SREBP1 and 2 as

upstream of PIM3

2.4.3 miR-33, an intronic microRNA within the SREBP loci, targets PIM3 downstream of

mTORC1

2.5 Discussion

2.6 Acknowledgements

2.7 Author Contributions

2.8 References

CHAPTER 3:

BIOLOGICAL SIGNIFICANCE OF miR-33 INDUCTION AND

PIM REPRESSION BY mTORC1 75

3.1 Abstract

3.2 Introduction

3.3 Materials and Methods

3.4 Results

3.4.1 miR-33-targeted transcripts are changing downstream of mTORC1

3.4.2 Additive effects of dual inhibition of mTORC1 and PIM kinases in Tsc2-/- MEFs

3.4.3 Implications for PIM effects on metabolism, particularly cellular NAD+ levels

3.5 Discussion

3.6 Acknowledgements

3.7 References

CHAPTER 4: CONCLUSIONS 102

4.1 Overview

4.2 Challenges of targeting the mTORC1 signaling axis in disease

4.2.1 Overview

4.2.2 Crosstalk and feedback pathways contribute to rewiring of the signaling network in

response to specific inhibitors

4.2.3 Redundancies in the greater mTORC1 network enable sustained signaling

4.2.4 Resistance to targeted therapies is intrinsic to the wiring of the network

4.3 Future directions

4.4 References

vii

LIST OF FIGURES

FIGURE 1.1 – Regulation of mTORC1 by a variety of upstream inputs 4

FIGURE 1.2 – Amino acid sensing and mTORC1 activation at the lysosome 7

FIGURE 1.3 – mTORC1 stimulates anabolic pathways to support cell growth and proliferation 9

FIGURE 1.4 – mTORC1 controls a vast transcriptional program in order to regulate anabolic 13 processes and stimulate cell growth

FIGURE 1.5 – microRNA regulation downstream of mTORC1 16

FIGURE 1.6 – A wide network of transcription factors regulates the expression of the PIM kinases 20

FIGURE 1.7 – The PIM kinases promote cell survival through a variety of pathways 24

FIGURE 1.8 – The PIM kinases stimulate Myc expression and transcription at multiple steps 27

FIGURE 2.1 – PIM3 is repressed downstream of mTORC1 57

FIGURE 2.2 – PIM3 repression by mTORC1 is observed in a variety of human cancer settings 59

FIGURE 2.3 – Identification of the mTORC1 effectors SREBP1 and 2 as being upstream of 61

PIM3 regulation

FIGURE 2.4 – PIM3 is induced upon inhibition of SREBP1 and 2 63

FIGURE 2.5 – An SREBP-intronic microRNA, miR-33, targets PIM3 expression downstream 64 of mTORC1

FIGURE 3.1 – miR-33 targets are induced by rapamycin 81

FIGURE 3.2 – Combined inhibition of PIM3 and mTORC1 has an additive effect in MEFs 83

FIGURE 3.3 – Metabolomic profiling in high/low PIM3 settings reveals changes in NAD+ levels 86 and synthesis upon PIM inhibition

FIGURE 3.4 – Supporting metabolomics data for Figure 3.3 88

viii

FIGURE 4.1 – Graphical summary of the dissertation 104

FIGURE 4.2 – Feedback pathways in the mTORC1 signaling network 106

FIGURE 4.3 – Pathway convergence on shared effectors 110

GLOSSARY OF TERMS

25-HC 25-hydroxycholesterol

4E-BP eIF4E binding proteins

ABCA1 ATP-binding cassette transporter A1

AMP adenosine monophosphate

AMPK AMP kinase

ATF4 activating transcription factor 4

ASK1 apoptosis signaling kinase 1

ATG7 autophagy-related 7

C/EBP-α CCAAT/enhancer-binding protein-α

CAD carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, dihydroorotase

CDC25A/C cell division cycle 25 homolog A and C

C-TAK1 Cdc25 C-associated kinase 1

DEPTOR DEP domain-containing mTOR-interacting protein eEF2K eukaryotic elongation factor 2 kinase

EGF epidermal growth factor

EGFR EGF receptor eIF4B eukaryotic translation initiation factor 4B eIF4E eukaryotic translation initiation factor 4E

ER endoplasmic reticulum

ERK/MAPK mitogen-activated protein kinase

FAS fatty acid synthase

FBS fetal bovine serum

FKBP12 FK506 binding protein of 12 kDa

FOXO forkhead box O

GAB1/2 GRB2-associated binder 1 and 2

GAP GTPase-activating protein

GEF guanine nucleotide exchange

GRB10 growth factor receptor bound protein 10

GSK3 glycogen synthase kinase 3

HCC hepatocellular carcinoma

HIF-1α hypoxia-inducible factor alpha

HK2 hexokinase 2

HOXA9 homeobox protein A9

HSP90 heat shock protein 90β

IGF1 insulin-like growth factor 1

IR insulin receptor

IRS-1/2 insulin receptor substrates 1 and 2

INSIG insulin-induced gene

JNK c-Jun N-terminal kinase

KLF5 Kruppel-like factor 5

LAM lymphangioleiomyomatosis

LC-MS/MS liquid chromatography-mass spectrometry/mass spectrometry

Lipin1 phosphatidic acid phosphatase LPIN1

MAX Myc-associated factor X

MEF mouse embryonic fibroblast

MEK MAPK kinase mLST8 mTOR-associated protein, LST8 homologue mRNA messenger RNA

MTHFD2 methylene tetrahydrofolate dehydrogenase 2 mTOR mechanistic target of rapamycin

xi mTORC1 mTOR complex 1 mTORC2 mTOR complex 2

MuLV Moloney murine leukemia virus

NADH nicotinamide adenine dinucleotide nCoR1 nuclear receptor co-repressor 1

NF1 neurofibromin 1

NF-Κb nuclear factor- Κb

Nrf1 nuclear factor, erythroid 2-like 1 p21Cip1/WAF1 cyclin dependent kinase inhibitor 1A p27KIP1 cyclin dependent kinase inhibitor 1B

PA phosphatidic acid

Pax-5 paired box gene 5

PDCD4 programmed cell death 4

PDGF platelet-derived growth factor

PDGFR PDGF receptor

PDK1 phosphinositide-dependent kinase-1

PGC1α peroxisome proliferator-activated receptor gamma coactivator-1

PI propidium iodide

PI3K phosphoinositide 3-kinase

PIM proviral integration site MuLV

PIP2 phosphatidylinositol-4,5-bisphosphate

PIP3 phosphatidylinositol-3,4,5-triphosphate

PKC protein kinase C

PKM2 pyruvate kinase M2

PP2A protein phosphatase 2A

PPAR peroxisome proliferator-activated receptor

xii

PRAS40 proline-rich Akt/PKB substrate 40 kDa

Protor1/2 protein observed with Rictor-1 and -2

PTEN phosphatase and tensin homologue qRT-PCR quantitative reverse transcriptase polymerase chain reaction

Rag RAS-related GTP-binding protein

Raptor regulatory-associated protein of mTOR

REDD1 regulated in development and DNA damage responses 1

Rheb RAS homolog enriched in brain

Rictor rapamycin insensitive companion of mTOR rRNA ribosomal RNA

Rsk MAPK-activated protein kinase-1

RTK receptor tyrosine kinase

S6 ribosomal protein S6

S6K ribosomal S6 kinase

SCAP SREBP cleavage-activating protein

SCD steroyl-CoA desaturase

SGK serum/glucocorticoid regulated kinases

STAT signal transducer and activator of transcription mSIN1 mammalian stress-activated protein kinase-interacting protein 1 siRNA small interfering RNA

SRE sterol response element

SREBP sterol regulatory element binding protein

TBC1D7 TBC1 domain family, member 7

TFEB transcription factor EB

THF tetrahydrofolate

TIF1A tripartite motif-containing protein-24

xiii

TNFα tumor necrosis factor alpha

TOP terminal oligopyrimidine

TSC1/2 tuberous sclerosis complex tumor suppressors 1 and 2

ULK1 Unc51-like kinase 1

UTR untranslated region

UVRAG UV radiation resistance-associated gene product

VEGF vascular endothelial growth factor

VEGFR VEGF receptor

YY1 yin-yang 1

xiv

To my Blue Grandparents, whose unmitigated love and pride still buoys me from beyond the grave.

ACKNOWLEDGEMENTS

First, I would like to thank the Manning lab for having been such a stimulating place to learn and work these past six years. I would like to thank Brendan for his scientific guidance at all stages of my graduate career. Many thanks to Sue Menon for getting me started in the lab and for always being available for advice even after moving on from the lab. Thank you to all the postdocs of the lab, past and present, who were always ready to pause for a question, no matter how small. Thanks in particular to

Issam and Gerta, for your advice and for sharing your unquenchable love of science – you inspire me every day. Thank you to the graduate students and lab technicians for our many lunches, for answering the occasional crossword question, for attending movie nights even when you were busy at the bench.

Special shout out to Stéphane, Laura, Erika, Steve, Marc, and Rebecca for always being available for a laugh or a drink, to celebrate when things worked, and to commiserate when things didn’t.

I would like to thank Andrea McClatchey, Alex Toker, and Cyril Benes for their scientific and career advice in my DAC meetings. Thank you to Alex Toker, Ben Turk, Elizabeth Henske, and Zhi-Min

Yuan for taking the time to serve on my defense committee.

Thank you to my sorority sisters, who disprove all the bad stereotypes and prove all the good ones every day – for the road trips, concerts, brunches, and fantasy football leagues; for visiting and providing couches to crash on in return; for answering the phone at any time of day; and for supporting me from afar all of these years.

To the Kelseys and our chosen extended family (who for unknown reasons still hangs out with us): thanks for being the safe harbor to come home to. Thanks to my parents for your support and love, and particularly for babysitting my tiny dog all the time; to Malia, Terin, and Jalyn for all the shenanigans we’ve gotten up to over the years and all the adventures we’ll have in the future; and to Curtis for providing trustworthy fantasy book recommendations. All my love to Maria and Leticia, and your families and friends, for giving me a home to run away to across the ocean.

And last but not least to Malia and Andrew – couldn’t have done it without you. You know why.

xvi

CHAPTER 1:

INTRODUCTION

1.1 mTORC1 is a major regulator of cell growth and metabolism

1.1.1 Overview

As the agents of communication responsible for controlling and coordinating cellular functions, signaling networks and their component molecules are dysregulated in cancer and many other diseases.

The development of precision therapies relies in part on targeting differences in mutational status or dependence on a single driver in a signaling pathway between the disease milieu and normal tissue. One network of interest is the mTORC1 signaling network, as it is located at a key node between several major upstream growth pathways and downstream anabolic processes. The mechanistic target of rapamycin (mTOR) is an evolutionarily conserved serine/threonine protein kinase that is found in two functionally distinct complexes, mTOR complex 1 (mTORC1) and 2 (mTORC2)1. Both complexes contain the catalytic mTOR subunit and mLST8 (mammalian lethal with Sec13 protein 8, also known as

GßL), along with complex-specific core components: Raptor in mTORC1 and Rictor, Protor1/2 and mSIN1 in mTORC2. mLST8 associates with the kinase domain of mTOR, stimulating its kinase activity, perhaps through stabilizing its kinase activation loop2,3. Raptor (regulatory protein associated with mTOR) plays a dual role in mTORC1 signaling: by recruiting substrates with a TOR signaling (TOS) motif for phosphorylation by mTOR4,5, and through recruitment of mTORC1 to the lysosome, where it enacts its signaling program6,7. In mTORC2, Rictor (rapamycin insensitive companion of mTOR) likely serves an analogous function to Raptor, although it is structurally unrelated8,9. mSIN1 (mammalian stress- activated protein kinase-interacting protein 1) and Protor1/2 (protein observed with Rictor-1 and -2) are also necessary components of mTORC210-15; mSIN1 is required for mTORC2 recruitment to the plasma membrane16. Both complexes can be bound by the negative regulator DEPTOR (DEP domain-containing mTOR-interacting protein)17. mTORC1 also contains the negative regulatory subunit PRAS40 (proline- rich Akt/PKB substrate 40 kDa)15,18-20.

Upon activation, mTORC1 phosphorylates a growing number of downstream targets, including its canonical effectors ribosomal S6 kinases (S6K1 and S6K2), and eukaryotic translation initiation factor

4E (eIF4E) binding proteins (4E-BP1 and 4E-BP2)1. Through its downstream effectors, mTORC1 promotes anabolic cell growth while inhibiting autophagy21,22. Alternatively, mTORC2 promotes cell survival, proliferation, and changes to the actin cytoskeleton through its phosphorylation of Akt, SGK

(serum/glucocorticoid regulated kinases), some isoforms of protein kinase C (PKC), and likely other targets23.

The two complexes have differential susceptibility to the mTOR inhibitor rapamycin and its many analogs (rapalogs), which interact with FKBP12 to promote its binding to an allosteric site N- terminal to the mTOR kinase domain24-26. This rapamycin-FKBP12 complex is only capable of inhibiting mTOR in complex 1, although prolonged exposure to rapamycin can also block mTORC2, likely through decreased availability of the mTOR kinase for incorporation into complex 227,28. Furthermore, these rapalogs are only partial inhibitors of mTORC1, influenced by the differential quality of the mTORC1 phosphorylation sequence on a given substrate29. As a result, the phosphorylation of some effectors, such as S6K, is strongly inhibited by rapamycin treatment, while other effectors, such as 4E-BP1, are only modestly inhibited30. Second generation mTOR inhibitors that target the catalytic domain of the kinase have been developed in recent years, and are capable of fully inhibiting both mTOR complexes.

1.1.2 Upstream regulation of mTORC1

As a key regulator of cell growth and metabolism, mTORC1 is situated downstream of several major pathways involved in the sensing of growth factors, cellular energy levels, and nutrient availability

(Figure 1.1). These pathways converge on the TSC protein complex, a major upstream regulator of mTORC131. The TSC complex is a three-subunit complex comprised of the tuberous sclerosis complex tumor suppressors TSC1 and TSC2, and a third regulatory subunit TBC1D7 (Tre2-Bub2-Cdc16 (TBC) 1 domain family, member 7)32,33. The TSC complex acts as a GTPase-activating protein (GAP) toward the essential upstream activator of mTORC1, Rheb (RAS homolog enriched in the brain), a RAS-related small G protein34. The full mechanism for how Rheb activates mTORC1 remains uncharacterized.

Figure 1.1. Regulation of mTORC1 by a variety of upstream inputs.

The PI3K-Akt pathway, stimulated by insulin and IGF, and the RAS-ERK pathway, stimulated by EGF, are two major pathways that converge on the TSC complex to stimulate mTORC1 activity. mTORC1 can also be activated by the Wnt signaling pathway via its inhibition of GSK3. Through REDD1/2 and

AMPK, mTORC1 is sensitive to systemic and local energy and oxygen availability. These signals either activate or inhibit the TSC complex to act as a GAP for Rheb, thereby inhibiting or activating mTORC1, respectively. mTORC1 can be allosterically inhibited by rapamycin via FKBP12, which directly binds mTORC1. Many of the proteins upstream of mTORC1 are oncogenes (green) and tumor suppressors (red) that are frequently mutated in cancer and tumor syndromes.

The TSC complex integrates upstream signals from several key growth pathways, including the

PI3K-Akt and RAS-ERK pathways, which phosphorylate and inactivate the complex in order to activate mTORC1 (Figure 1.1)1. The PI3K-Akt pathway can be stimulated by the binding of growth promoting molecules such as insulin or insulin-like growth factor-1 (IGF-1) to receptor tyrosine kinases (RTK) at the cell surface, which stimulates PI3K (phosphoinositide 3-kinase) activity35. PI3K is a lipid kinase, and class I PI3Ks predominantly phosphorylate phosphatidylinositol-4,5-bisphosphate (PI4,5P2) to produce phosphatidylinositol-3,4,5-triphosphate (PIP3). PIP3 recruits Akt to the plasma membrane, where it is activated by phosphoinositide-dependent kinase-1 (PDK1)36. Akt subsequently activates many cellular processes through its phosphorylation of proteins containing a consensus RXXS/T motif37. Akt phosphorylates the TSC complex on multiple residues, leading to its inhibition and subsequent activation

38,39 of mTORC1 . Conversely, the pathway can be repressed by the conversion of PIP3 back to PI4,5P2 by phosphatase and tensin homolog (PTEN), a commonly disrupted tumor suppressor40.

Growth factor signals such as epidermal growth factor/EGF also regulate mTORC1 signaling through RTK binding and activation of ERK-MAPK (mitogen-activated protein kinase) signaling (Figure

1.1). Growth factor binding activates RTK autophosphorylation and subsequent recruitment and simulation of the RAS GTPase41. RAS then recruits RAF to the plasma membrane, where it can be activated and subsequently phosphorylate its own effector MEK, which activates ERK (extracellular signal-related kinase)42. When activated, this pathway targets many protein substrates that regulate cell cycle progression and growth. Like the PI3K-Akt pathway, the RAS-ERK pathway converges on the TSC complex; TSC2 is inactivated upon phosphorylation by both ERK and its downstream target RSK (p90 ribosomal S6 kinase), leading to mTORC1 activation43,44.

Beyond PI3K-Akt and RAS-ERK, mTORC1 activation is effected by several other upstream growth pathways (Figure 1.1). The Wnt signaling cascade is a major growth control and proliferation pathway important in development and stem cell maintenance in adult cells, and through its inhibition of

GSK-3 it can stimulate mTORC145,46. The proinflammatory cytokine TNFα (tumor necrosis factor alpha), can also inhibit TSC2 through its effector IKKβ47.

The biosynthetic programs stimulated by mTORC1 are heavily energy dependent, and therefore the pathway has evolved to be sensitive to energy requirements in the cell in addition to its sensitivity to growth factors and cytokines. AMPK (AMP-activated protein kinase) is the major sensor of energy stress in the cell, as it is activated by high cellular AMP levels48. AMPK can inhibit mTORC1 through both the

TSC complex and direct inhibition of mTORC1 via phosphorylation of Raptor, thus ensuring that mTORC1 can be turned off in energy-stressed conditions49,50. It is similarly important that the cell regulate anabolic processes in low-oxygen situations, which is achieved through the hypoxia-inducible

REDD proteins (REDD1 and 2), which can inactivate the TSC complex51,52.

The anabolic programs downstream of mTORC1 are also dependent on nutrient availability.

Amino acids regulate mTORC1 activity independently of growth factors and the TSC complex through the heterodimeric RAS-related GTP binding protein (Rag) GTPases (Figure 1.2)6,53. The Rags are obligate heterodimers comprised of either RagA or RagB with RagC or RagD, and are tethered to the lysosomal membrane by the Ragulator complex (MP1, p14, p18, HBXIP, and C7ORF59), which has guanine- nucleotide exchange factor (GEF) activity toward RagA/B7,54. In the presence of amino acids, the Rags are converted to their active state and able to recruit mTORC1 to the lysosomal surface, which is necessary for mTORC1 activation. Once at the lysosome, mTORC1 is sensitive to both intra-lysosomal and cytosolic amino acid levels through distinct mechanisms. Intra-lysosomal levels of amino acids can be sensed through a mechanism dependent on the V-ATPase, which interacts with the Ragulator-Rag complex to promote RagA/B activation55. The Rags can also be inhibited by the upstream protein complex GATOR1 (comprised of DEPDC5, Nprl2, and Nprl3), which is tethered to the lysosomal membrane by the KICSTOR complex (comprised of Kaptin, ITFG2, C12orf66, and SZT2)56-58. GATOR1 is itself inhibited by the mTORC1-activating upstream complex GATOR2 (comprised of Mios, WDR24,

WDR59, Seh1L, and Sec13), which is sensitive to both cytosolic leucine and arginine levels through

Sestrin2 and CASTOR1, respectively, which inhibit GATOR2 in the absence of their particular amino acid binding partner56,59-64. There are likely several as-yet uncharacterized mechanisms through which these and other amino acids regulate mTORC1. Another recent addition to the pathway was the

Figure 1.2. Amino acid sensing and mTORC1 activation at the lysosome.

Activation of mTORC1 requires recruitment to the lysosome and stimulation by both the Rheb and Rag

GTPases. Phosphorylation of the TSC complex stimulates its dissociation from the lysosome, allowing

GTP-bound Rheb to stimulate mTORC1. Amino acids stimulate mTORC1 in the cytosol via the Rags and an upstream amino acid sensing pathway involving GATOR1 and 2, Sestrin, and CASTOR1. mTORC1 is also sensitive to intra-lysosomal amino acids via the V-ATPase, which interacts with the Ragulator complex to stimulate its GEF activity toward RagA/B.

7 identification of the Folliculin-FNIP2 complex as a GAP for RagC/D, placing it as another amino acid- sensitive activator upstream of mTORC165,66.

Recent work has found that the TSC complex also localizes to the lysosome, where it interacts with Rheb to inhibit the Rheb-mediated activation of mTORC167. Rheb itself localizes to the lysosome through a C-terminal faresylation event68. Upon stimulation by growth factors, the TSC complex dissociates from the lysosomal surface, enabling GTP-loaded Rheb to stimulate mTORC1 activity. Thus, full activation of mTORC1 requires signal integration of both amino acids and growth factors at the lysosomal surface requiring stimulation by both the Rag and Rheb GTPases (Figure 1.2). mTORC1 must first be recruited to the lysosome in the presence of high cytosolic amino acid concentrations, and then subsequently requires inhibition and dissociation of the TSC complex via input from growth factor signaling upstream.

While mTORC1 has historically been characterized as a driver of protein synthesis through its canonical effectors S6K and 4E-BP1, thus providing a rationale for its sensing of amino acid levels, a growing body of literature has placed mTORC1 upstream of other anabolic processes, including lipid and nucleotide synthesis69. Interestingly, evidence has also been emerging that mTORC1 may sense cellular lipid and nucleotide levels in addition to amino acids. The mTOR FK506-binding protein–12-rapamycin- binding (FRB) domain can bind phosphatidic acid (PA), and suppression of PA synthesis may result in mTORC1 repression70,71. Furthermore, mTORC1 may be sensitive to cellular purine nucleotide levels independent of energy stress pathways (e.g., AMPK), placing a third class of nutrients upstream of mTORC1 signaling72.

1.1.3 Downstream processes regulated by mTORC1

Due to its position at an integration point between growth signals and nutrient availability, mTORC1 is uniquely positioned to decide whether a cell should grow. Under pro-growth conditions, mTORC1 activates a downstream program that is broadly anabolic while also inhibiting catabolic processes such as autophagy. The earliest identified role for mTORC1 in anabolic metabolism is its

Figure 1.3. mTORC1 stimulates anabolic pathways to support cell growth and proliferation. mTORC1 activates HIF1α to stimulate aerobic glycolysis. It drives de novo lipid synthesis through its stimulation of SREBP processing and subsequent transcriptional activity. Via the enzyme CAD mTORC1 drives de novo pyrimidine synthesis. It also drives de novo purine synthesis via the mitochondrial tetrahydrofolate cycle enzyme MTHFD2, which is transcriptionally activated downstream of mTORC1 via the transcription factor ATF4. Cap-dependent protein synthesis is enhanced via S6K and 4E-BP1. mTORC1 also inhibits autophagy via ULK1, and it can repress lysosomal biogenesis through its phosphorylation of TFEB, which causes it to be sequestered in the cytosol.

9 stimulation of protein synthesis through its major effectors, S6K and 4E-BP (Figure 1.3). Once activated,

S6K stimulates mRNA translation initiation through its phosphorylation of ribosomal protein S6, a component of the 40S ribosomal subunit. S6K also stimulates translation through phosphorylation and recruitment of eIF4B, a binding partner of the eIF4A RNA helicase, and through phosphorylation of the inhibitory protein programmed cell death 4 (PDCD4), which targets it for degradation73-75. S6K further enhances mRNA elongation through its inhibitory phosphorylation of eEF2K (eukaryotic elongation factor 2 (eEF2) kinase), which inhibits the mRNA translocation protein eEF276. S6K also enhances the translation efficiency of spliced mRNAs77,78. mTORC1 further enhances mRNA translation through inhibition of 4E-BP and its subsequent release from its inhibitory binding to eIF4E at the 5’-cap of mRNAs, with a particularly pronounced effect on mRNAs containing 5’TOP (terminal oligopyrimidine) and TOP-like sequences, a subset of transcripts that includes most protein synthesis genes79-82. Together, these effects enable mTORC1 to enact broad control over protein synthesis.

Long-term activation of mTORC1 and its protein synthesis program increases the demand for amino acids, and mTORC1 has been shown to mediate this potential stressor in several ways. mTORC1 increases the expression of proteasomal subunits in order to increase the efficiency of protein turnover in the cell83. This increase is mediated by a global regulator of proteasome gene expression, the transcription factor NRF1 (nuclear factor erythroid-derived 2-related factor 1; also known as NFE2L1 or TCF11)84,85.

NRF1 transcription is induced by mTORC1 signaling via its stimulation of another transcription factor,

SREBP (sterol regulatory element-binding protein), which then targets the NRF1 promoter (Figure

1.3)86,87. Recent work has further shown that mTORC1 increases the expression of other genes involved in amino acid homeostasis through a mechanism requiring activating transcription factor 4 (ATF4)88. mTORC1 increases ATF4 translation via 4E-BP, which allows ATF4 to stimulate the transcription of

ATF4 target genes, including amino acid transporters and tRNA aminoacyl transferases. These downstream processes enable the cell to balance the increased protein synthesis downstream of mTORC1 with an increased supply of amino acids.

In growing and proliferating cells, there is also an increased need for nucleotides to be used in

DNA replication and ribosome biogenesis, and recent studies have shown that mTORC1 activity stimulates de novo nucleotide synthesis to cope with this demand. Through S6K, mTORC1 increases the basal activity of CAD (carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase), the rate-limiting enzyme in de novo pyrimidine synthesis89,90. mTORC1 can also stimulate de novo purine synthesis through ATF4 and its transcriptional target MTHFD2 (methylene tetrahydrofolate dehydrogenase 2), an enzyme in the mitochondrial tetrahydrofolate (THF) cycle that provides one-carbon units for purine synthesis91. mTORC1 activity can also increase Myc translation via

S6K, which induces the expression of multiple nucleotide biosynthesis genes92-94. Collectively, these and other metabolic pathways influenced by mTORC1 activity coordinate to ensure a sufficient pool of nucleotides for the downstream anabolic processes necessary for cell growth and proliferation.

Growing and proliferating cells also require lipids for a variety of processes, including incorporation into the plasma membrane and subcellular organelles95. Many of the enzymes necessary for both de novo sterol and fatty acid synthesis are controlled by the transcription factors SREBP1 and 296. mTORC1 stimulates the processing and subsequent transcriptional activation of these transcription factors through at least two mechanisms, one involving an S6K-dependent mechanism97, and another involving mTORC1-mediated inhibition of Lipin1, an inhibitor of SREBP98. Other downstream targets of mTORC1 may affect SREBP processing and activity, perhaps in a cell-dependent manner99. While the mechanism for SREBP activation by mTORC1 is not yet fully understood, the induction of de novo lipid synthesis downstream of mTORC1 has been established in a variety of settings, indicating that this third important macromolecule, along with proteins and nucleotides, is regulated by mTORC1.

mTORC1 also facilitates a shift from oxidative phosphorylation to aerobic glycolysis, a hallmark of cancer cells known as the Warburg effect. The transcription factor HIF1α (hypoxia inducible factor 1- alpha) induces expression of nearly all enzymes involved in glycolysis, and its cap-dependent translation can be enhanced by mTORC1 via 4E-BP. This shift toward glycolysis allows the cell to generate

11 metabolic intermediates which can be used in side branches of glycolysis to generate nucleotides, non- essential amino acids, and lipids in support of the production of biomass for cell proliferation100.

To concentrate cellular activity on anabolic processes, mTORC1 also inhibits a number of catabolic processes when it is activated, including autophagy and lysosomal biogenesis. When active, autophagy recycles cellular components such as organelles and proteins into their constitutive parts through engulfment by the autophagosome prior to its fusion with the lysosome, where the degradation of these components occurs101. The protein ULK1 (Unc51-like kinase 1) is a key regulator of autophagy induction, along with a complex comprising ATG13, ATG101, and FIP200. ULK1 is inhibited by mTORC1 phosphorylation, thus inhibiting autophagosome formation102. Recent work has also implicated mTORC1 in control of later-stage autophagosome and endosome maturation via inhibition of UVRAG

(UV radiation resistance-associated gene product)103. Evidence is also mounting for the relationship between mTORC1 and lysosomal function beyond autophagy: the recent findings that mTORC1 signals at the lysosome, described above, implicate mTORC1 sensitivity to lysosomal function as well. mTORC1 inhibition is sufficient to induce a transcriptional program that promotes lysosomal biogenesis and other genes, including components of the V-ATPase, through transcription factor EB (TFEB) and its related transcription factors MITF and TFE3104-106. When active, mTORC1 phosphorylates TFEB, causing it to be sequestered in the cytosol; repression of mTORC1 signaling conversely allows TFEB to translocate into the nucleus where it activates its gene transcription program. This reciprocal coordination of lysosomal health with signaling networks exemplifies another mTORC1-mediated mode of adaptation to fluctuations in nutrient availability within the cell.

1.1.4 mTORC1 control of coding and non-coding RNA expression

To regulate its many downstream anabolic and catabolic processes, mTORC1 controls a vast network of transcriptional programming through a variety of mechanisms (Figure 1.4)107. Of the transcription factors discussed above, mTORC1-mediated control is achieved through post-translational modifications (e.g., TFEB); increased translation (e.g., HIF1α, ATF4); and increased transcription (e.g.,

Figure 1.4. mTORC1 controls a vast transcriptional program to regulate anabolic processes and stimulate cell growth. mTORC1 activation of STAT3 stimulates its transcription of genes involved in immunity and cell growth processes. Through HIF1α it activates genes involved in aerobic glycolysis. mTORC1 drives lipid synthesis through SREBP and PPARγ. ATF4 and Myc activation allow mTORC1 to control a variety of processes, including nucleotide synthesis. Through an undefined mechanism involving activation of

PGC1α, possibly involving YY1, mTORC1 can control mitochondrial biogenesis. Protein turnover via the proteasome is increased by chronic mTORC1 activation via NRF1, which is upregulated downstream of mTORC1 via SREBP transcriptional activity. To balance this anabolic program, mTORC1 also represses several transcription factors involved in lysosomal biogenesis: MIFT, TFE3, and TFEB.

Through S6K2 interaction with nCoR1, mTORC1 inhibits PPARα, thus attenuating its program of genes involved in fatty acid oxidation.

NRF1). In the case of its activation of SREBP, the mechanism is less poorly understood. After its synthesis, SREBP resides in the endoplasmic reticulum (ER), where it can be retained under conditions of abundant sterols through its interaction with the sterol-sensing SCAP (SREBP cleavage activating protein) and the Insig proteins99. In conditions with scarce sterols, SREBP-SCAP are released from Insig and transported to the golgi apparatus, where SREBP undergoes processing, releasing its N-terminal region. This region contains the DNA-binding and -transactivating domains, and once cleaved it enters the nucleus to activate genes containing sterol regulatory elements (SREs) in their promoters. mTORC1 promotes SREBP processing (through S6K) and the entrance of the mature fragment into the nucleus

(through Lipin1) via unknown mechanisms. Together, these transcription factors regulate a staggering variety of transcripts, including but not limited to genes for lysosome and autophagosome biogenesis; lipid synthesis; aerobic glycolysis and glucose transport; and nucleotide synthesis. However, these targets only represent a subset of the full landscape of mTORC1-mediated gene expression changes.

The anabolic processes stimulated by mTORC1 activity generate a huge demand for energy. mTORC1 has been shown to regulate mitochondrial biogenesis and function, and its activation increases the expression of genes that regulate mitochondrial metabolism108,109. This may be through a mechanism involving the transcriptional activity of PGC1α (peroxisome proliferator-activated receptor gamma

(PPARγ) coactivator-1) and mTORC1-mediated effects on its interaction with another transcription factor, YY1 (yin-yang 1), although the mechanism for this effect, and its tissue specificity, is not yet fully understood108.

In adipose tissue, inhibition of mTORC1 signaling has profound effects on adipogenesis and adipose cell maintenance through its regulation of the expression and activity of PPARγ110-112. While the mechanism for mTORC1-mediated alteration of PPARγ activity has not yet been elucidated, it may involve translational control via 4E-BP113. It is also possible that mTORC1 stimulation of SREBP transcriptional activity promotes PPARγ through the production of undefined endogenous ligands114.

Alterations in the expression and activity of PPARγ affect its downstream targets, including genes involved in fatty acid synthesis and uptake115. In the liver, mTORC1 activity inhibits PPARα, a nuclear

14 receptor that controls genes involved in ketone body formation and fatty acid oxidation116,117. mTORC1 phosphorylation of S6K2 enables its interaction with and nuclear accumulation of nCoR1 (nuclear receptor corepressor 1), a negative regulator of PPARα118.

mTORC1 directly phosphorylates and activates STAT3 (signal transducer and activator of transcription 3) at S727, and rapamycin treatment reduces STAT3 transcriptional activity119,120. When active, STAT3 activates the expression of genes involved in a variety of processes including survival

(e.g., anti-apoptotic proteins BCL-XL and MCL-1); proliferation (e.g., Myc and cyclin D1/D2); angiogenesis (e.g., vascular endothelial growth factor (VEGF)); and metastasis (e.g., matrix metalloproteinases (MMPs))121.

Beyond its regulation of transcription factors and the subsequent impact on genes mostly transcribed by RNA polymerase (Pol) II, mTORC1 also effects gene transcription through RNA Pol I and

III, and their transcription of genes involved in ribosome biogenesis and RNA maturation69,107. RNA pol

III can be inhibited in the nucleus by Maf1, which is sequestered in the cytosol upon direct phosphorylation by mTORC1122-124. mTORC1 effects RNA Pol I through S6K-mediated activation of the regulatory unit TIF1A (transcription initiation factor -1A, also called RRN3), which subsequently interacts with and activates RNA Pol I125. These effectors enable mTORC1 to further enhance additional aspects of ribosome biogenesis, and thus protein synthesis, beyond its well-characterized induction of mRNA translation.

Gene expression can also be influenced through transcript targeting by microRNAs (miRs or miRNAs). miRNAs are a class of short, non-coding RNAs that are 18-22 nucleotides long and regulate the expression of genes via complementary sequences in the 3’ untranslated region (3’UTR) of target genes126. miRNA is initially transcribed as a primary miRNA, and then processed to precursor miRNA in the nucleus by Drosha and its partner DGCR8 before a second processing step from precursor to mature miRNA by Dicer in the cytoplasm127. There is increasing evidence of miRNA alterations downstream of mTORC1 signaling (Figure 1.5). Long-term rapamycin treatment causes profound reprogramming of miRNA expression, including upregulation of oncogenic miRNAs (oncomiRs) (e.g., miR-17 and miR-

Figure 1.5. microRNA regulation downstream of mTORC1. mTORC1 can affect global miRNA biogenesis through increasing the expression of the E3 ubiquitin ligase MDM2, which targets the miRNA processing enzyme DROSHA for degradation, resulting in decreased expression of miRNAs. Several miRNAs have been characterized as inhibited by mTORC1, perhaps through this inhibition of DROSHA. Not all miRNAs are inhibited downstream of mTORC1, as miR-1 has been shown to be stimulated by mTORC1 activity via MyoD.

19b) and down-regulation of tumor suppressor miRNAs (e.g., miR-22 and miR-29)128. Other studies investigating rapamycin-induced miRNAs have also found many of the same targets altered, including the miR-21, an oncomiR, and miR-143, which targets the glycolytic enzyme hexokinase 2 (HK2)128-130.

Recently, mTORC1 has further been shown to globally downregulate miRNA biogenesis through increased expression of the E3 ubiquitin ligase Mdm2, which targets Drosha for degradation131. These findings may provide a mechanism for miRs repressed downstream of mTORC1. Other studies also show a role for mTORC1 promotion of miRNA expression through activation of specific transcription factors.

For example, miR-1 is increased downstream of mTORC1 in muscle cells, possibly via the transcription factor MyoD132. The relative contributions of MDM2-mediated downregulation of miRNA biogenesis versus mTORC1-driven transcriptional effects on miRNA upregulation remain to be fully determined, although it seems likely that there are uncharacterized miRNAs upregulated by mTORC1 via its network of transcriptional activation.

1.1.5 mTORC1 signaling in disease

In normal conditions, the upstream regulatory pathways of mTORC1 coordinate in poorly understood ways to tightly control its activity. However, some of the most commonly mutated oncogenes

(PI3K, Akt, RAS, and RAF) and tumor suppressors (PTEN, NF1) lie upstream of mTORC1 (Figure 1.1), resulting in constitutive activation of mTORC1 in at least 50% of tumor settings across nearly all lineages133. Loss of function mutations in PTEN, the TSC genes, NF1 (neurofibromin 1), and other upstream effectors also occur frequently in familial tumor syndromes (e.g., Cowden’s syndrome, tuberous sclerosis complex (TSC) and lymphangioleiomyomatosis (LAM), or neurofibromatosis) and are characterized by uncontrolled mTORC1 activation. Many other diseases, including metabolic disease and neurologic disorders (e.g., autism spectrum disorders, fragile X syndrome, and Alzheimer’s disease) are characterized by dysregulated mTORC1 signaling1,134. Interestingly, unlike in cancer, which is typically characterized by constitutive activation of mTORC1, both chronic activation and inhibition of mTORC1 can cause deleterious effects, e.g. in the liver, chronic activation can lead to insulin resistance while

17 chronic repression can cause hepatic steatosis. The common theme of mTORC1 dysregulation in such a diverse array of conditions highlights the importance of this complex as a major regulator of cell growth and proliferation.

The frequent dysregulation of mTORC1 in disease has led to intense interest in targeting it with small molecules. The partial inhibitor rapamycin was first clinically approved and is still widely used as an immunosuppressant due to its ability to block lymphocyte proliferation135. There has also been ongoing interest in using mTORC1 inhibitors to treat a wide variety of cancers136. To date, rapamycin/rapalogs have been tested in nearly 1000 clinical cancer trials, across most cancer lineages and genetic tumor syndromes (http://clinicaltrials.gov). However, despite its promise as a therapeutic target, the majority of these trials fail to achieve tumor regression, indicating that single-agent rapalog therapy is insufficient.

Even in TSC and LAM, where rapamycin treatment can shrink tumors by as much as 50%, improving clinical outcomes, the cessation of rapamycin treatment causes rapid tumor regrowth in most patients137,138. The poor efficacy of rapamycin alone may be partly a result of the fact that it is a partial inhibitor of mTORC1, and as a result many current clinical trials are investigating the efficacy of mTOR kinase inhibitors and dual PI3K/mTOR inhibitors139. Another contributing factor is likely the cytostatic effect of rapamycin, which arrests or delays cells in the G1 phase of the cell cycle140. The complexity of the signaling network both up and downstream of mTORC1 also complicates responses to its inhibition: mTORC1 is a shared downstream effector of many pathways described above, but these pathways also have their own highly branched signaling pathways, of which mTORC1 is a single node. Furthermore, repression of mTORC1 is known to relieve several distinct feedback mechanisms that attenuate upstream signaling through RTKs, PI3K, mTORC2, and likely other uncharacterized pathways that promote cell- survival141-145. A full understanding of the wiring of the network, particularly as concerns cell survival pathways, may be necessary for the design of future targeted therapies.

1.2 The PIM kinase family in signaling and disease

1.2.1 Overview

The PIM kinases are a family of three proto-oncogenic serine/threonine kinases (PIM1, 2, and 3) that contribute to tumorigenesis through a variety of downstream effectors. They were originally identified as a common site for Moloney murine leukemia virus (MuLV) integration in early T-cell lymphomas, thus explaining their name (proviral integration site MuLV)146. A decade after the discovery of PIM1, PIM2 was identified as a closely related gene due to its compensatory role in Pim1-/- mice147, with the identification of PIM3 following a few years later due to its sequence similarity to PIM1148.

There are two isoforms of PIM1 encoded by alternative start sites, and three isoforms of PIM2, with a single isoform of PIM3147,149. The main isoform of all three kinases is 33-34 kDa, and none of the kinases contains regulatory domains150. These kinases are highly conserved, and unique in that they share very little sequence similarity with other kinases151. They are, however, highly similar to each other and believed to be largely redundant, although some recent studies have suggested distinct roles for PIM1 and

PIM2 in some settings152. In normal settings, the PIM kinases are ubiquitously expressed153. Consistent with their identification in a hematological setting, the PIM kinases have been shown to play a role in hematopoietic malignancies, although they are increasingly being characterized as important drivers of tumorigenesis in solid tumors as well. In cancer, PIM1 is expressed more highly in hematopoietic cells, gastric, head and neck, and prostate cancer; PIM2 is more highly expressed in brain and lymphoid tissues; and PIM3 is more highly expressed in the kidney, brain, and breast tissues154. While the full extent of their downstream signaling networks have not yet been characterized, they are emerging as important drivers of survival, growth, and proliferation.

1.2.2 Upstream regulation of PIM kinases

The PIM kinases are constitutively active, and have no known regulatory domains or post- translational modifications151,152. As such, they are regulated primarily at the transcriptional, translational,

Figure 1.6. A wide network of transcription factors regulates the expression of the PIM kinases.

The PIM kinases are primarily regulated at the transcriptional level by several upstream pathways, including the Jak-STAT and NFκB pathways, and they can be activated by a wide range of growth factors and cytokines via these transcription factors.

20 and degradational levels. PIM transcript levels can be increased by a variety of upstream transcription factors (Figure 1.6). The expression of all three PIM kinases can be activated by the STAT family of transcription factors and nuclear factor- κB (NF-κB)155-160. Kruppel-like factor 5 (KLF5) induces PIM1 expression by binding to SP-1 sites in its promoter upon DNA damage, indicating that the PIM kinases may play a pro-survival role under DNA damage conditions161. PIM1 has also been shown to be activated by homeobox protein HOXA9, which acts in hematopoiesis and enhances proliferation of primitive blood cells, and can play a role in myeloid leukemia162. Interestingly, PIM1 has been shown in several studies to be induced in hypoxic conditions independently of HIF1α163,164. The mechanism by which this occurs has not been fully elucidated. Fewer studies have been performed to describe PIM2- and PIM3-specific transcriptional activation. PIM2 may be activated by Paired box gene 5 (Pax-5) in B-cell lymphomas165, and PIM3 is transcriptionally activated by Myc166. PIM3 has further been shown to be a target of Ets-1, first in NIH 3T3 cells that had been malignantly transformed with the EWS/Ets-1 fusion gene, and later in pancreatic cancer cells with wild-type Ets-1167,168. Ets-1 can itself be activated downstream of MAPK signaling in some settings169,170.

In addition to their regulation by transcription factors, the PIM mRNA transcripts are extensively regulated via their 3’UTRs. Their transcripts have short half-lives due to multiple copies of the destabilizing AUUU(A) sequence in the 3’UTR171. More recently, the PIM transcripts have been shown to be targeted by a growing number of miRNAs, which also contribute to their regulation (Table 1.1).

PIM1 has been characterized as a target of several microRNAs including miR-1 and miR-33172-183. PIM3 transcripts can also be targeted by several of the same miRNAs as PIM1, including miR-33184,185, in addition to being targeted by a distinct set of miRNAs185,186. The PIM2 3’UTR differs more significantly from the sequences of PIM1 and 3, and shares no overlap in its predicted or characterized miRNA targets.

PIM2 transcript levels can be inhibited by miR-135187, and may also be a target of miR-24 in familial colorectal cancer188. At the translational level, the PIM transcripts are translated via a cap-dependent translational mechanism due to the GC-rich region in their 5’UTR, in a manner dependent on eIF-

4E189,190.

Table 1.1. Published miRNA that target the PIM kinases.

Kinase microRNA References

miR-1, miR-16, miR-33, miR-124, miR-144, miR-195, PIM1 miR-206, miR-214, 172 - 183 miR-328, miR-370, miR-486, miR-542, miR-638

PIM2 miR-24, miR-135 187, 188

miR-15, miR-33, PIM3 184 - 186 miR-377, miR-506

Once translated, the PIM kinases are constitutively active, although an autophosphorylation site on PIM1 may have some functional requirements151,191. While they are constitutively active, at least one phosphorylation site, on Y218 of PIM1, may enhance its kinase activity192. A recent study also described

SUMOylation of PIM1 at two sites that interestingly increase its kinase activity and also target it for degradation by the SUMO-targeted ubiquitin ligase RNF4193. PIM kinases are tightly regulated via their protein stability, having a very short protein half-life194. The heat shock protein 90β (HSP90) binds and stabilizes PIM1, and inhibition of HSP90 causes rapid degradation of PIM1195. PIM1 and PIM3 are also regulated by protein phosphatase 2A (PP2A), which dephosphorylates both kinases, resulting in decreased kinase activity and degradation via the proteasome196,197.

1.2.3 Downstream targets of PIM kinases

The PIM kinases activate a downstream network with targets involved in apoptosis, cell cycle progression, and metabolism (Figure 1.7). A peptide library screen identified their optimal phosphorylation site sequence as ARKRRRHPSGPPTA191, which was in line with an earlier study that had identified a preference for substrates with K/RXRHXS/TX motifs198. Interestingly, this consensus sequence is highly similar to those of the AGC group of kinases such as Akt and S6K, although the PIM kinases are only distantly related37. Indeed, many of the substrates phosphorylated by the PIM kinases are shared with AGC kinases199. The PIM kinases control translation through a variety of effectors, including activation of eIF4B200 and eIF4E201. In addition to direct activation of translation, they also target the upstream mTORC1 signaling network, which acts to increase translation as well. PIM1 has been shown to activate mTORC1 through phosphorylation of PRAS40 at T246, a shared site also phosphorylated by

Akt202, and PIM2 has been characterized as a direct upstream inhibitor of the mTORC1 negative regulator

TSC2203.

The PIMs may also affect mTORC1 through their effect on cellular energy status. While the role played by the PIMs in control of metabolism and mitochondrial health has not yet been fully elucidated,

Figure 1.7. The PIM kinases promote cell survival through a variety of pathways.

Through inhibition of BAD, ASK1, and caspase 3 and 9, the PIM kinases inhibit apoptosis. They promote cell growth through enhancing translation via eIF4E, and eIF4B, and through their activation of mTORC1 via inhibition of TSC2 and PRAS40. Their effects on cellular ATP levels result in activation of AMPK upon PIM inhibition or knockout. They further effect metabolism through phosphorylation of ABCA1 and PKM2, and through increasing the expression of Myc and PGC1α. The PIM kinases also drive cell cycle progression at both the G1/S and G2/M phase transitions, via their activation or inhibition of several effectors.

24 several studies point to an important role for these kinases. In PIM triple knockout (TKO) mouse embryonic fibroblasts (MEFs), a high AMP:ATP ratio is observed, resulting in activation of AMPK and subsequent inhibition of the mTORC1 signaling axis, among other effects204. PIM3 addback in these cells was sufficient to inhibit AMPK via restoration of energy levels through upregulation of c-Myc and

PGC1α and their subsequent transcription of targets involved in glycolysis and mitochondrial biogenesis.

Other studies have also pointed to a role for the PIMs in cellular energy maintenance205. PIM TKO mice exhibit premature aging in the heart, characterized by abnormal mitochondrial morphology and decreased levels of ATP206, and in cisplatin-treated cells, overexpression of PIM1 was sufficient to maintain mitochondrial transmembrane potential164. Knockdown of PIM1 in hepatocellular carcinoma (HCC) cells caused tumors to take up less glucose under hypoxic conditions207, and PIM2 was shown to promote glycolysis through direct phosphorylation of the glycolytic enzyme pyruvate kinase M2 (PKM2)208, indicating that the activity of these kinases may control glycolysis. While the exact mechanism of these effects on cellular energy production are currently poorly defined, they indicate that the PIMs may play a significant role in maintaining energy homeostasis in the cell.

Beyond energy production, the PIMs may have a broader role in metabolic control. The ATP- binding cassette transporter A1 (ABCA1), a major regulator of cholesterol efflux and phospholipid homeostasis, is a direct target of PIM1 phosphorylation209. PIM1 phosphorylation of ABCA1 facilitates its binding to and stabilization by the liver X receptor β at the cell surface, which protects it from lysosome-mediated degradation. In 3T3-L1 adipocytes treated with the pan-PIM inhibitor SGI-1776, lipid droplet accumulation was inhibited during differentiation from preadipocytes into adipocytes, and a concurrent downregulation of the expression or phosphorylation of the enzyme fatty acid synthase (FAS) and of the transcription factors C/EBP-α (CCAAT/enhancer-binding protein-α), PPAR-γ, and STAT3, was observed210. Conversely, transgenic mice expressing human PIM3 in the liver exhibited increased lipid droplet accumulation when challenged with a carcinogen211. Overall, these studies point to a role for the PIM kinases in lipid metabolism, although the extent of that role, and its mechanism of action, has yet to be fully elucidated.

The PIMs also control several effectors involved in the cell cycle, which results in accelerated cell cycle progression in settings with PIM kinase overexpression211-213. PIM1 and 2 have been shown to phosphorylate an inhibitory site on CHK1, a master regulator of cell cycle progression, thus allowing cells to bypass etoposide-induced G2/M arrest214. The PIMs can further act as positive regulators of the

G2/M transition through direct activation of Cdc25C, and through inactivation of Cdc25 C-associated kinase 1 (C-TAK1), an inhibitor of Cdc25C215,216. The PIMs also drive cell cycle progression at the G1/S transition through their targeting of p21Cip1/WAF1 (also known as cyclin dependent kinase inhibitor 1

(CDKN1A))217, p27KIP1 (also known as CDKN1B)218, and CDC25A (cell division cycle 25 homolog A)219.

As a complement to their promotion of cell cycle progression, the PIM kinases are also well characterized for their pro-survival role via their regulation of apoptotic proteins, specifically Bcl-2 family members. PIM phosphorylation of the pro-apoptotic protein BAD at S112 results in disruption of its association with anti-apoptotic protein Bcl-2 and its sequestration by 14-3-3 in the cytosol, freeing

Bcl-2 to promote its anti-apoptotic activity220,221. The PIM kinases are also capable of inhibiting the activation of caspase 3 and 9164. This blockage of caspase 3 activation may be at least partly due to PIM1 inhibitory phosphorylation of apoptosis signaling kinase 1 (ASK1), an upstream activator of caspase 3 through JNK (c-Jun N-terminal kinase) and p38 MAP kinase222.

1.2.4 PIM kinases in cancer

The PIM kinases were originally identified as oncogenes due to their synergism with Myc in a variety of tumor settings223, and work over the last several decades has described a number of pathways through which this is achieved (Figure 1.8). Myc translation is increased by PIM activation of cap- dependent translation, even in a rapamycin-insensitive manner, indicating that this is independent of its upstream effects on mTORC1 signaling152,201. Furthermore, this effect of the PIMs on translation has been shown to act as a resistance mechanism to rapamycin treatment by sustaining protein synthesis in acute myeloid leukemia (AML)224. Once Myc protein has been translated, PIM2 kinase may increase its stability via phosphorylation at S329, although further work is needed to fully verify this finding225.

Figure 1.8. The PIM kinases stimulate Myc expression and transcription at multiple steps.

(A) Through enhancement of translation via eIF4E and eIF4B, the PIM kinases increase Myc protein translation. (B) Phosphorylation of Myc at S329 and S62 by PIM2 and PIM1, respectively, results in stabilization of the Myc protein. (C) PIM1 interaction with the Myc-Max complex at enhancer E box sequences stimulates the transcription of Myc target genes226-228. PIM1 phosphorylation of histone H3S10 at the enhancer allows binding of 14-3-3, which recruits the histone acetyltransferase MOF, resulting in acetylation of H4 at K16. Acetylated H4K16 is bound by BRD4 (bromodomain-containing protein 4), which recruits P-TEFb (positive transcription elongation factor b), which can subsequently phosphorylate several effectors at the transcription start site, including the C-terminal domain of RNA Pol II, resulting in transcriptional elongation.

Figure 1.8. (Continued).

The two isoforms of PIM1 have been shown to have different subcellular localization229. The longer, 44 kDa isoform, localizes to the plasma membrane, while the shorter, 33 kDa isoform is found in the cytosol and nucleus. The nuclear form of PIM1 can interact with Myc and its partner MAX (Myc- associated factor X), which results in PIM1 recruitment to the E boxes of Myc targeted genes227. Once at the E box, PIM1 phosphorylates S10 on histone H3. Phosphorylated histone H3S10 leads to a cascade of events culminating in release of paused RNA Pol II at Myc-targeted genes (Figure 1.8)228,230. This interaction between Myc and PIM1 at the E box enables PIM1 to contribute to the regulation of nearly

20% of Myc-regulated genes227. In a variety of cell culture, xenograft, and mouse models, tumors characterized by high Myc expression show a requirement for PIM kinase activity to sustain proliferation, including in B cell lymphomas166, prostate231,232, and triple negative breast cancer (TNBC)233,234.

Beyond their synergy with Myc, overexpression of the PIM kinases is observed in many hematological and epithelial malignancies, including AML, mantle cell lymphoma and B cell lymphomas; and prostate adenocarcinoma, pancreatic ductal carcinoma, squamous cell carcinomas of the head and neck, colon carcinoma, and hepatocellular carcinomas150,154. The kinases are infrequently mutated or duplicated, and their overexpression is believed to be a result of aberrant activation of upstream transcriptional and translational pathways.

Due to their overexpression in such a wide array of malignant diseases, the PIM kinases have been explored as therapeutic targets. Structurally, they are characterized by a hinge region in the kinase domain that distinguishes them from other kinases, making them promising targets for highly selective inhibition151,191. Also, the Pim triple knockout mouse is viable, with some impairment of hematopoietic response to growth factors, indicating that pan-PIM inhibition may be well tolerated as a therapy235. Pan-

PIM inhibitors that are both ATP-competitive and ATP-mimetic have been developed by several groups.

Several clinical trials have begun exploring the efficacy of these inhibitors in the clinic, both as single agent therapies and in combination with other inhibitors (www.clinicaltrials.gov). Future studies to determine the full regulatory network influenced by the PIM kinases will continue to inform the design of

29 targeted therapies, particularly combination therapies, for tumors characterized by overexpression of the

PIMs.

1.3 Specific Aims and Overview of the Dissertation

Cancer cells take advantage of exquisitely designed cell signaling networks in their quest for immortalization, using parallel pathways and feedback loops that in normal cells exist to maintain a homeostatic balance. The complexity of these networks has thus far made it difficult to gain a complete picture of cell signaling, although a great deal of work in the last few decades has begun to fill in many of the blanks. Further work remains to be done in order to define the most efficacious downstream therapeutic targets of mTORC1 in the many diseases characterized by its dysregulation. In this dissertation, I characterize the pro-survival kinase PIM3 as induced by mTORC1 inhibition via a newly characterized mTORC1-regulated miRNA, miR-33.

In chapter 2, I establish miR-33 and PIM3 as regulated downstream of mTORC1. Although an increasing number of miRNAs have been identified as regulating the network upstream of mTORC1, less is known about specific miRNAs affected downstream of its activity. I demonstrate that the SREBP- intronic miR-33 is expressed at higher levels in MEFs with constitutive mTORC1 activation, with subsequent decrease in miR-33 expression upon mTORC1 inhibition with rapamycin. Furthermore, I find that the proto-oncogenic kinase PIM3 is activated upon rapamycin treatment via a mechanism that requires SREBP and miR-33. Inhibition of SREBP processing and transcriptional activity by treatment with 25-hydroxycholesterol resulted in an mTORC1-independent increase in PIM3 expression.

Importantly, miR-33 targets PIM3 expression, and in cells treated with a miR-33 mimic, rapamycin failed to induce PIM3 expression. These results confirm that miR-33 is positively regulated by mTORC1 signaling, and that one effect of this regulation is the targeting of the pro-survival kinase PIM3, which is

30 activated upon mTORC1 inhibition, with potential consequences for the treatment of diseases driven by activated mTORC1 signaling.

In Chapter 3, I explore the physiological consequences of miR-33 and PIM3 regulation downstream of mTORC1. I identify several miR-33 targets activated by rapamycin treatment downstream of mTORC1, including the pro-survival proteins PIM1 and IRS-2. The induction of two of the three PIM kinases by mTORC1 inhibition indicates that these two pathways might have promise for combination therapies. I therefore investigated dual inhibition of mTORC1 and the PIM kinases with rapamycin and pan-PIM inhibitors, finding an additive effect on slowing proliferation and increasing apoptosis in Tsc2-/- mouse embryonic fibroblasts. Finally, to explore the metabolic effect of the PIM kinases downstream of mTORC1, I performed a steady-state metabolic flux experiment. Interestingly, many metabolites in the kynurenine pathway, which synthesizes NAD+ from tryptophan, were downregulated upon PIM inhibition, which could define a new role for the PIM kinases in control of cellular energy levels.

My work highlights a survival pathway activated upon mTORC1 inhibition, with implications for cancer treatment. The activation of miR-33 by mTORC1 also points to a class of uncharacterized molecules that may be regulated by mTORC1 activity. I finish by discussing the implications of these findings, placing them in the broader context of the mTORC1 signaling network.

1.4 References

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CHAPTER 2:

mTORC1 SUPPRESSES PIM3 EXPRESSION VIA miR-33 ENCODED BY THE SREBP LOCI

This chapter is adapted from: Kelsey I., Zbinden M., Byles V., Torrence M., Manning B.D. mTORC1 suppresses PIM3 expression via miR-33 encoded by the SREBP loci. In submission. 2.1 Abstract

The mechanistic target of rapamycin complex 1 (mTORC1) is a central regulator of cell growth that is often aberrantly activated in cancer. However, mTORC1 inhibitors, such as rapamycin, have limited effectiveness as single agent cancer therapies, with feedback mechanisms inherent to the signaling network thought to diminish the anti-tumor effects of mTORC1 inhibition. Here, we identify the protein kinase and proto-oncogene PIM3 as being repressed downstream of mTORC1 signaling. PIM3 expression is suppressed in cells with loss of the tuberous sclerosis complex (TSC) tumor suppressors, which exhibit growth factor-independent activation of mTORC1, and in the mouse liver upon feeding-induced activation of mTORC1. Inhibition of mTORC1 with rapamycin induces PIM3 transcript and protein levels in a variety of settings. Suppression of PIM3 involves the sterol regulatory element-binding

(SREBP) transcription factors SREBP1 and 2, whose processing and mRNA expression are stimulated by mTORC1 signaling. We find that PIM3 repression is mediated by miR-33, an intronic microRNA encoded within the SREBP loci, the expression of which is decreased with rapamycin. These results demonstrate that PIM3 is induced upon mTORC1 inhibition, with potential implications for the effects of mTORC1 inhibitors in TSC, cancers, and the many other disease settings influenced by aberrant mTORC1 signaling.

2.2 Introduction

Due to its positioning at a critical nexus between upstream growth signals and downstream anabolic processes, the conserved serine/threonine protein kinase complex mechanistic target of rapamycin complex 1 (mTORC1) is a key driver of cell growth, including the uncontrolled growth of tumor cells. mTORC1 is frequently activated in human cancers, across nearly all lineages, and would seem to be a prime target for precision therapies1. With few exceptions, however, mTOR-targeted therapies alone have proven insufficient to cause tumor regression, in part due to the complexity of the

51 mTORC1 signaling network, among other reasons2,3. While upstream inputs into mTORC1 signaling and mTORC1-mediated control of anabolic processes downstream have been extensively characterized4,5, less is understood about effectors whose activity is repressed by mTORC1 signaling, and the role these effectors might play in the response to pharmacological inhibition of mTORC1.

As a key regulator of cell growth and metabolism, mTORC1 is situated downstream of several major pathways involved in the sensing of growth factors, cellular energy levels, and nutrient availability, including the PI3K-Akt, RAS-ERK, and AMPK pathways4. Aberrant activation of mTORC1 signaling in cancer is primarily due to the frequent misregulation of these upstream signaling pathways, which converge to regulate the TSC protein complex (TSC1-TSC2-TBC1D7), a key negative regulator of mTORC12. Inactivating mutations in the TSC complex or direct inhibitory phosphorylation from upstream oncogenic pathways cause constitutive activation of mTORC16-11. This activation enables mTORC1 to promote its downstream processes, including protein, nucleotide, and lipid synthesis12-18.

While there have been extensive studies to characterize the upstream regulation of mTORC119, we are only beginning to fully understand the scope of the downstream consequences of mTORC1 activation.

A variety of omics approaches have been employed to define the downstream functional repertoire of mTORC1 signaling, including transcriptional profiling, ribosomal profiling, phosphoproteomics, and metabolomics13,15-18,20-22. Genetic settings with loss of the TSC tumor suppressors, leading to constitutively active mTORC1 signaling, together with the use of mTORC1 inhibitors such as rapamycin, have been particularly powerful in expanding our knowledge of mTORC1 functions and crosstalk regulation with other cellular pathways and processes. Here, we use such an approach to identify the proto-oncogene PIM3 as a downstream target inhibited by mTORC1 signaling. Using TSC-deficient mouse embryonic fibroblasts (MEFs), we show that PIM3 inhibition is coupled to mTORC1 signaling via the transcription factors SREBP1 and 2 (sterol regulatory element-binding proteins 1 and 2). SREBP transcriptional activity is induced by mTORC1 via its stimulation of SREBP processing from an endoplasmic reticulum-bound inactive form to a mature nuclear form18,23-26. The mTORC1-mediated increase in SREBP transcriptional activity induces the transcript levels of its own gene products Srebf1

52 and Srebf218, and we find that this regulation causes a concomitant increase in the levels of its intronic microRNA, miR-3327. We demonstrate that induction of miR-33 downstream of mTORC1 suppresses

PIM3 expression. These findings highlight a previously unappreciated mechanism of gene repression downstream of mTORC1, and demonstrate an unexpected outcome of treatment with mTORC1 inhibitors in the induction of the PIM3 proto-oncogene.

2.3 Materials and Methods

Cell culture and RNAi

The immortalized litter-mate derived pair of Tsc2+/+ and Tsc2-/- (both p53-/-) MEFs were provided by Dr. D.J. Kwiatkowski (Brigham and Women’s Hospital), and maintained in Dulbecco’s Modified

Eagle Medium (DMEM; VWR, Radnor, PA, USA) with 4.5 g/L glucose containing 10% fetal bovine serum (FBS)28,29. MDA-MB-453 and MDA-MB-468 cells were obtained from the American Type Culture

Collection (ATCC, Manassas, VA, USA) and maintained in RPMI-1640 with 10% FBS at 37°C and 5%

-/- CO2. TSC2 ELT3 cells (Eker Rat uterine leiomyoma/myosarcoma tumor-derived) were provided by Dr.

C. Walker (Texas A&M University), and maintained in DF8 medium (50% DMEM, 50% F-12, 1.2 g/ml

NaHCO3, 1.6 muM FeSO4, 50 nM sodium selenite, 25 mug/ml insulin, 200 nM hydrocortisone, 10 mg/ml transferrin, 1 nM triiodothyronine, 10 muU/ml vasopressin, 10 nM cholesterol, 10 ng/ml epidermal growth factor) containing 15% FBS30,31. U87MG-iPTEN cells were maintained in the presence of geneticin (G418, 0.4 mg/mL, Sigma-Aldrich, St. Louis, MO, USA) in DMEM with 4.5 g/L glucose containing 10% FBS and were developed in the laboratory of M.M. Georgescu (MD Anderson Cancer

Center)32. JHH-4, JHH-6, and HepG2 cells were obtained from Novartis Institutes for BioMedical

Research (Cambridge, MA), and maintained in DMEM with 4.5 g/L glucose containing 10% FBS. All siRNA-mediated knockdown experiments were carried out with ON-TARGET-plus SMARTpool siRNAs

(30 nM, GE Dharmacon, Lafayette, CO, USA). Cells were transfected using Lipofectamine RNAiMax

(Invitrogen, Carlsbad, CA, USA), according to the manufacturer’s protocol for reverse transfection.

Rapamycin (553210, Calbiochem, San Diego, CA, USA), and Torin1 (4247, R&D Systems, Minneapolis,

MN, USA) were used to inhibit mTOR; 25-hydroxycholesterol (H1015, Sigma-Aldrich) was used to inhibit SREBP.

Immunoblotting

Cells were lysed in ice-cold NP-40 lysis buffer (40 nM HEPES [pH 7.4], 400 nM NaCl, 1 mM

EDTA [pH 8.0], 1% NP-40 [CA-630, Sigma-Aldrich], 5% glycerol, 10 mM pyrophosphate, 10 mM β- glycerophosphate, 50 mM NaF, 0.5 mM orthovanadate) containing protease inhibitor cocktail (P8340,

Sigma-Aldrich) and 1 µM microcystin-LR (ALX-350-012-C500, Enzo Life Sciences, Farmingdale, NY,

USA). Lysates were clarified by centrifugation (20,000 x g for 15 min at 4°C) and protein concentrations were determined with Bradford assay (Bio-Rad) prior to normalization. The following antibodies were used for detection of proteins transferred to immobilon-P PVDF membranes after SDS-PAGE: β-actin

(A5316, Sigma-Aldrich), tubulin (T5168, Sigma-Aldrich), TFEB (A303-673A, Bethyl, Montgomery, TX,

USA), HIF1-α (10006421, Cayman Chemical, Ann Arbor, MI, USA), SREBP1 (for human samples; sc-

8984, Santa Cruz), SREBP1 (for mouse samples; 557036, BD Biosciences). All other antibodies were obtained from Cell Signaling Technologies (Danvers, MA, USA): PIM3 (4165), SCD (2438), P-S6K1-

T389 (9234), Total-S6K1 (2708), ATF4 (11815), and c-Myc (13987). mRNA and miRNA expression analysis

Microarray data were obtained and analyzed as previously described18. RNA was isolated using the RNeasy Mini Kit (Qiagen, Valencia, CA, USA). Complementary DNA was synthesized using the

Superscript III First Strand Synthesis System (Invitrogen) and after dilution 1: in nuclease-free water was quantified using SYBR-Green for quantitative reverse transcription polymerase chain reaction (Bio-Rad

CFX Connect Real-Time System). Each condition was run in triplicate and normalized to RPLP0

(m36b4), or Actin. Primer sequences for mouse mRNAs were as follows: Pim3 (F 5’-

CGACATCAAGGACGAGAACC-3’, R 5’-CTCCTCATCCTGCTCAAAGG-3’); Srebf1 (F 5’-

TAGATGGTGGCTGCTGAGTG-3’, R 5’-GATCAAAGAGGAGCCAGTGC-3’); Srebf2 (F 5’-

GGATCCTCCCAAAGAAGGAG-3’, R 5’-TTCCTCAGAACGCCAGACTT-3’); Scd (F 5’-

CTGACCTGAAAGCCGAGAAG-3’, R 5’-GCGTTGAGCACCAGAGTGTA-3’). Primer sequences for human mRNAs were as follows: PIM3 (F 5’-AAGCTCATCGACTTCGGTTC-3’, R 5’-

AGGATCTCCTCGTCCTGCTC-3’); SREBF1 (F 5’-GCGGAGCCATGGATTGCAC-3’, R 5’-

CTCTCCCTTGATACCAGGCCC-3’); SREBF2 (F 5’-TGGCTTCTCTCCCTACTCCA-3’, R 5’-

GAGAGGCACAGGAAGGTGAG-3’).

Small RNAs for miRNA measurement were isolated using the miRNeasy Mini Kit (Qiagen).

Complementary DNA was synthesized using the miScript II RT Kit (Qiagen) and quantified using

SYBR-Green for qRT-PCR (Bio-Rad CFX Connect Real-Time System). Each condition was run in triplicate and normalized to RNU6. Primer assays were purchased from Qiagen (hsa-miR-33_1

[MS00003304], hsa-miR-33b_2 [MS00007819], hsa-RNU6-2_11 [MS00033740]). miRNA inhibitors and mimics

For miR-33a inhibition, miRCURY LNA power microRNA inhibitors were purchased from

Exiqon (Vedbaek, Denmark): inhibitor control A (199006-002) and hsa-miR-33a-5p (4102039-102).

Cells were transfected at a final concentration of 10 nM inhibitor with RNAiMax Lipofectamine for 24,

48, or 72 hours and starved for the final 16 hours before lysis. For miR-33a mimics, mirVana miRNA

Mimics were purchased from Thermo Fisher Scientific (Waltham, MA, USA): control mimic #1

(4464058) and miR-33a-5p mimic (MC12410). Cells were reverse transfected following the manufacturer’s protocol at a final concentration of 30 nM with RNAiMax Lipofectamine for 24 hours, and either starved (MEFs) or left in full serum (U87MG) for the final 16 hours, plus vehicle or rapamycin

(20 nM).

Mouse fasting and refeeding experiment

Twelve C57BL/6J male mice (aged 8 weeks) were fasted for 8-10 hours during the light cycle and either euthanized (n=4) or administered either vehicle (5% Tween-80, 5% PEG-400 in 1x PBS; n=4)

55 or rapamycin (10 mg/kg; n=4) via intraperitoneal injection 30 minutes prior to refeeding normal chow for

4 hours during the dark cycle, followed by euthanization. Liver lysates were prepared in RIPA buffer (150 mM Sodium Chloride, 1% IGEPAL, 0.5% sodium deoxycholate, 0.1% SDS and 50 mM Tris [pH 8]). mRNA was processed with the RNeasy Mini Kit (Qiagen), and complementary DNA was synthesized with the iScript cDNA Kit (Bio-Rad, Hercules, CA, USA). mRNA transcript levels were quantified by qRT-PCR as described above.

Statistical Analysis

All qRT-PCR data were analyzed with GraphPad Prism (La Jolla, CA, USA). P-values were calculated by an unpaired two-tailed Student’s t-test, where appropriate.

2.4 Results

2.4.1 PIM3 expression is repressed downstream of mTORC1 and induced by mTOR inhibitors

Through analysis of gene expression array data from Tsc1-/- and Tsc2-/- mouse embryonic fibroblasts (MEFs), which have constitutive mTORC1 activation, Pim3 transcript levels were found to be repressed relative to untreated wild-type MEFs and induced in a time-dependent manner over 24 hours of treatment with the mTORC1 inhibitor rapamycin (Fig. 2.1A). We confirmed that both PIM3 mRNA and protein levels were decreased in Tsc2-/- MEFs and found that mTORC1 inhibition with either rapamycin or the mTOR kinase domain inhibitor Torin1 induced PIM3 expression (Fig. 2.1B, C). The ability of rapamycin to induce PIM3 mRNA and protein levels was also observed in ELT3 cells, a cellular model of

TSC derived from a TSC2-/- uterine leiomyoma arising in the Eker rat (Fig. 2.1D, E)30.

In vivo, mTORC1 signaling is highly sensitive to feeding status, especially in the liver, being repressed during fasting and acutely activated upon feeding. Thus, to determine whether physiological control of mTORC1 signaling influenced PIM3 expression, PIM3 mRNA and protein levels were

Figure 2.1. PIM3 is repressed downstream of mTORC1.

(A) Microarray data for Pim3 expression levels in Tsc1-/- or Tsc2-/- mouse embryonic fibroblasts (MEFs), normalized to wild-type MEFs and treated with a 24-hour time-course of rapamycin (20 nM). (B) mRNA and (C) protein levels of PIM3 in mTORC1-activated (Tsc2-/-) MEFs compared with Tsc2-wild-type

MEFs. Cells were starved and treated overnight with vehicle, rapamycin (Rap, 20 nM) or torin (250 nM).

N=4 for qPCR; data are shown as mean ± s.e.m. (D) mRNA and (E) protein levels of PIM3 in TSC2-/- rat

ELT3 cells. Cells were starved and treated overnight with vehicle or rapamycin (Rap, 20 nM). N=3 for qPCR; data are shown as mean ± s.e.m. (F) mRNA and (G) protein levels of PIM3 in mouse liver samples fasted during the day and then treated with vehicle or rapamycin (Rap, 10 mg/kg) for 30 minutes before refeeding. N=4 for qPCR; data are shown as mean ± s.e.m. *statistical significance determined by a two-tailed t-test.

Figure 2.1. (Continued).

Figure 2.2. PIM3 repression by mTORC1 is observed in a variety of human cancer settings.

(A) mRNA levels of PIM3 in U87MG glioblastoma cells. Cells were starved and treated overnight with vehicle or rapamycin (Rap, 20 nM). N=3 for qPCR; data are shown as mean ± s.e.m. (B) PIM3 protein levels in U87MG cells with doxycycline-inducible PTEN (U87MG-iPTEN). Cells were starved and treated overnight with vehicle, rapamycin (Rap, 20 nM), or doxycycline (Dox, 1 µg/mL). (C-E) PIM3 protein levels in hepatocellular carcinoma cell lines JHH-4, HepG2, and JHH-6. Cells were treated overnight with vehicle or rapamycin (Rap, 20 nM) in full serum. (F-G), PIM3 protein levels in breast cancer cells lines MDA-MB-453 and MDA-MB-468. Cells were starved and treated overnight with vehicle or rapamycin (Rap, 20 nM). *statistical significance determined by a two-tailed t-test.

59 measured in liver samples from mice that had been fasted or fed with or without rapamycin pretreatment.

PIM3 transcript and protein levels were highest in the fasted state and were strongly suppressed upon feeding, coincident with activation of mTORC1 signaling, indicated by phosphorylation of its direct downstream target S6K1 (Fig. 2.1F, G). Importantly, the feeding-induced suppression of PIM3 was largely dependent on mTORC1 activation, as PIM3 mRNA and protein levels remained elevated in liver samples from mice treated with rapamycin just prior to feeding.

To ascertain the broader applicability of these findings, we determined the effects of rapamycin on PIM3 in a variety of human cancer cell lines that exhibit constitutive mTORC1 activation (Fig. 2.2). In human glioblastoma cells (U87MG) with activated mTORC1 signaling downstream of PTEN loss, PIM3 expression was increased upon mTORC1 inhibition (Fig. 2.2A). In U87MG cells expressing a doxycycline-inducible PTEN (U87MG-iPTEN), repression of mTORC1 signaling either with rapamycin or PTEN re-expression via doxycycline treatment led to elevated PIM3 (Fig. 2.2B). PIM3 levels were also increased to varying degrees by rapamycin treatment in the hepatocellular carcinoma (HCC) lines JHH-4,

Hep-G2 and JHH-6 (Fig. 2.2C-E), and the breast cancer cell lines MDA-MB-453 and MDA-MB-468

(Fig. 2.2F-G). Therefore, mTORC1 signaling suppresses PIM3 expression in a variety of mammalian settings, resulting in PIM3 induction by rapamycin.

2.4.2 A survey of mTORC1-regulated transcription factors identifies SREBP1 and 2 as upstream of

PIM3

Due to the nature of our original transcriptional profiling experiment and the timescale over which PIM3 is induced by rapamycin, we hypothesized that a transcription factor downstream of mTORC1 influences PIM3 expression. We therefore tested siRNAs targeting a panel of transcription factors established to be downstream of mTORC1 for effects on PIM3 levels in Tsc2-/- MEFs, including hypoxia-inducible factor 1 alpha (HIF1α), c-myc, activating transcription factor 4 (ATF4), transcription factor EB (TFEB), and sterol regulatory element-binding proteins 1 and 2 (SREBP1/2) (Fig. 2.3). None of these knockdowns affected mTORC1 signaling. Interestingly, only siRNA-mediated knockdown of

Figure 2.3. Identification of the mTORC1 effectors SREBP1 and 2 as being upstream of PIM3 regulation.

PIM3 protein levels upon transient siRNA knockdown of a panel of transcription factors downstream of mTORC1: (A) hypoxia-inducible factor 1 alpha (HIF1α); (B) c-myc; (C) activating transcription factor 4

(ATF4); (D) transcription factor EB (TFEB); or (E) sterol regulatory element-binding proteins 1 and 2

(SREBP1/2). Full-length precursor (P) form of SREBP1 is shown. Cells were transfected for 72 hours and starved overnight for the final 16 hours before lysis.

SREBP1 and 2 resulted in an increase in PIM3 levels (Fig. 2.3E), similar to that observed with rapamycin treatment.

Full-length SREBP is retained as an inactive precursor form on the membrane of the endoplasmic reticulum (ER), and mTORC1 signaling promotes its proteolytic processing at the Golgi and subsequent nuclear localization of its mature form, which binds to sterol regulatory elements (SREs) in the promoters of the genes that it induces (Fig. 2.4A)23. Therefore, in Tsc2-/- MEFs, mature SREBP protein levels are elevated, resulting in increased transcription of numerous SREBP target genes18 including its canonical target SCD1 (Fig. 2.4B). Treatment with rapamycin decreased both the precursor and mature forms of

SREBP1 and lowered expression of SCD1 to levels similar to wild-type MEFs. siRNA-mediated knockdown of SREBP1 and 2 increased PIM3 transcript levels, concurrent with a decrease in the mRNA levels of SREBP1, SREBP2, and SCD1 (Fig. 2.4C). Independent of mTORC1 signaling, SREBP processing and activation is sensitive to intracellular sterol levels33. Interestingly, treatment of Tsc2-/- cells with 25-hydroxycholesterol (25-HC), which, like rapamycin, strongly inhibits SREBP processing and expression of SCD1, resulted in increased PIM3 mRNA and protein levels despite sustained mTORC1 activity (Fig. 2.4D, E). Thus, inhibition of SREBP with either siRNAs or sterols overrides the mTORC1- mediated suppression of PIM3 expression.

2.4.3 miR-33, an intronic microRNA within the SREBP loci, targets PIM3 downstream of mTORC1

SREBP1 and 2 are primarily characterized as activators of gene transcription, although a handful of repressive binding events have been described34,35. However, there are no discernible SREs in the

PIM3 promoter, indicating that SREBP1 and 2 are likely to repress PIM3 expression via other mechanisms. Interestingly, the SREBP1 and 2 loci (gene names SREBF1 and 2) contain intronic microRNAs that are expressed upon transcription of SREBP (Fig. 2.5A)27. These microRNAs encoded by the SREBP1 and 2 loci, miR-33b and miR-33a, differ by just two nucleotides and thus widely target the same set of transcripts36. It should be noted that while humans express both miR-33 forms, mice only

Figure 2.4. PIM3 is induced upon inhibition of SREBP1 and 2.

(A) Schematic of SREBP stimulation by mTORC1 and its subsequent induction of transcription from sterol response elements (SREs) in target genes. (B) Protein levels of full-length precursor SREBP1

(SRE1 (P)), mature SREBP1 (SRE1 (M)), and its target SCD1 in Tsc2 wild-type or Tsc2-/- MEFs treated with vehicle or rapamycin (Rap, 20 nM). Cells were starved and treated overnight for 16 hours. (C) mRNA expression levels of PIM3, SREBP1, SREBP2, and SCD1 upon SREBP1/2 double knockdown with siRNA. Cells were transfected for 72 hours and starved overnight for the final 16 hours. N=3 for qPCR; data are shown as mean ± s.e.m., *p < 0.5, **p < 0.01, ***p < 0.005. (D) PIM3 mRNA and (E) protein levels in Tsc2-/- MEFs starved and treated for 16 hours with vehicle, rapamycin (Rap, 20 nM) or

25-hydroxycholesterol (25-HC, 1 μg/mL). N=3 for qPCR; data are shown as mean ± s.e.m. *statistical significance determined by a two-tailed t-test.

Figure 2.5. An SREBP-intronic microRNA, miR-33, targets PIM3 expression downstream of mTORC1.

(A) SREBP1 and SREBP2 contain intronic sequences for miR-33b and miR-33a, respectively37. (B) The

PIM3 3’UTR contains a conserved miR-33 target sequence (Targetscan)38. (C) SREBP1 and SREBP2 mRNA transcript levels in Tsc2-/- MEFs starved and treated overnight (16 hr) with vehicle or rapamycin

(Rap, 20 nM). N=3, data are shown as mean ± s.e.m. (D) miR-33a levels in Tsc2-/- MEFs starved and treated overnight (16 hrs) with vehicle or rapamycin (Rap, 20 nM). N=3, data are shown as mean ± s.e.m.

Figure 2.5. (Continued).

(E) PIM3 protein levels in Tsc2-/- MEFs over a time-course of treatment with a miR-33a inhibitor. Cells were transfected for 24, 48, or 72 hours with the final 16 hours starved overnight with vehicle or rapamycin treatment (Rap, 20 nM). (F) PIM3 protein levels in Tsc2-/- MEFs upon treatment with a miR-

33a mimic. Cells were reverse transfected for 24 hours and starved overnight with vehicle or rapamycin treatment (Rap, 20 nM) for the final 16 hours. (G) Proposed model of the results. *statistical significance determined by a two-tailed t-test for qPCR data.

65 possess miR-33a27. Importantly, the PIM3 3’UTR contains a consensus target sequence for miR-33 that is conserved throughout mammals, including in mouse, rat, and human (Fig. 2.5B), all species where rapamycin induces PIM3 expression (Fig. 2.1, 2.2)38. Furthermore, a recent study found that miR-33 does indeed target the PIM3 transcript39. While mTORC1 signaling promotes the processing of SREBP1 and 2, it also induces transcription of the SREBP loci due to autoregulation from SREs present in both the

SREBP1 and 2 promoters18,23,40,41. We confirmed that the transcription of SREBP1 and 2 is sensitive to rapamycin (Fig. 2.5C). Importantly, this decrease in SREBP transcript levels resulted in corresponding decreases in miR-33a levels upon rapamycin treatment (Fig. 2.5D).

To determine whether mTORC1 signaling suppresses PIM3 expression through the induction of miR-33, we tested the effects of both an anti-miR inhibiting miR-33a and a miR-33a mimic in Tsc2-/-

MEFs. Introduction of the anti-miR to miR-33a induced a time-dependent increase in PIM3 expression, similar to the de-repression observed with rapamycin treatment (Fig. 2.5E). Conversely, a mimic of miR-

33a decreased PIM3 levels and blocked the ability of rapamycin to induce PIM3 (Fig. 2.5F). Collectively, these data demonstrate that mTORC1 signaling suppresses PIM3 through the induction of SREBP transcription and a corresponding increase in miR-33, which attenuates PIM3 expression (Fig. 2.5G).

2.5 Discussion

mTORC1 is aberrantly activated in the majority of human cancers, and increasing evidence has highlighted the vital role of sustained mTORC1 signaling in resistance to targeted therapies of upstream pathways42,43. While a number of studies have indicated that mTORC1 inhibition is necessary for therapeutic response to oncogene-targeted therapies, it is also recognized that mTORC1 inhibition alone is generally not sufficient for a robust anti-tumor response in most settings2. mTORC1 inhibitors induce autophagy, which can have pro-survival effects on tumor cells44, and also relieve feedback inhibition of receptor tyrosine kinase signaling leading to enhanced activation of the pro-survival kinase Akt45,46,

66 suggesting cell-survival mechanisms are promoted by mTORC1 inhibition. A more thorough understanding of signal wiring and rewiring upon mTORC1 activation and inhibition could help explain the cytostatic effect of mTORC1 inhibitors and suggest promising candidates for the design of combination therapies. In this study, we demonstrate that a proto-oncogenic kinase, PIM3, is repressed downstream of mTORC1, and that its expression is induced upon treatment with the mTORC1 inhibitor rapamycin. Importantly, this induction of PIM3 expression is also observed under physiological control of mTORC1 in the liver with fasting and feeding. Furthermore, induction of PIM3 by rapamycin was also observed in a variety of human cancer cell lines. Our data suggest an additional mechanism limiting the effectiveness of mTORC1 inhibitors as single agent cancer therapies.

There has been increasing interest in the PIM kinases in cancer due to their role as pro-survival kinases. Indeed, they phosphorylate a consensus sequence highly similar to that preferred by AGC family kinases such as Akt and S6K, and PIM kinases have overlapping substrates with these kinases that contribute to their pro-survival and pro-growth role in cells45,47,48. The PIM kinases are unique in that they are constitutively active and have a short half-life, such that their levels are proportional to their cellular activity49. While PIM levels are regulated primarily at the transcriptional and protein stability levels50-53, there are also reports implicating miRNAs as key regulators of PIM expression39,54,55. Consistent with these reports, we find evidence that PIM3 expression is repressed downstream of mTORC1 via its induction of SREBP1 and 2 transcriptional activity and a subsequent increase in miR-33 levels.

Several recent studies have found that mTORC1 inhibitors can cause pronounced changes in cellular miRNAs56,57. This is partly due to mTORC1-mediated repression of the microRNA processing enzyme DROSHA58, which leads to a general increase in miRNA expression upon mTORC1 inhibition; however, a subset of microRNAs were found to be decreased upon rapamycin treatment. The ability of mTORC1 to modulate the expression of miRNAs provides new insights into the full molecular effects of mTORC1 inhibitors, and alterations in the expression of miR-33 may play a key role in the response to these inhibitors in some settings. A recent study suggested that miR-33a inhibition might decrease sensitivity to cisplatin treatment in HCC59. Perhaps this effect is partly due to increased levels of PIM3 in

67 this setting, and other uncharacterized miR-33 targets might contribute to the pro-survival effect of miR-

33 inhibition. However, other studies have suggested that high levels of miR-33 might be detrimental to cancer therapy60,61. These conflicting findings highlight that the role of miR-33 in cancer and therapeutic responses remains to be fully elucidated.

Consistent with their expression requiring transcriptional induction of the SREBP1/2 loci, the majority of miR-33 targets that have been characterized to date are involved in fatty acid and cholesterol metabolism27,36,62. Given that the PIM kinases are believed to have a high degree of functional redundancy, it is interesting to note that PIM1 appears to stabilize the cholesterol transporter ABCA1, which is also a canonical miR-33 target, providing a rationale for PIM targeting by miR-3363. While many canonical PIM targets are involved in cell survival, recent work has also implicated them in various metabolic pathways, including glycolysis and mitochondrial biogenesis64-67. Furthermore, transgenic mice with human PIM3 expression in the liver exhibited increased lipid droplet accumulation when challenged with a carcinogen68, indicating that the PIM kinases may have as-yet undefined roles in lipid regulation, and providing further rationale for their regulation downstream of SREBP and miR-33. The metabolic consequences of decreased miR-33 and subsequent increase in PIM3, therefore, might also influence the cellular and systemic responses to mTOR inhibitors in cancer and other disease settings. Interestingly, chronic and complete inhibition of mTORC1 in the liver has been found to enhance carcinogen-induced hepatocellular carcinoma69, an effect also observed with liver-specific overexpression of PIM368.

Our data here expand the functional consequences of mTORC1 activation and inhibition, demonstrating that its regulation of the SREBP transcription factors, thereby affecting levels of the intron- encoded miR33, influences cellular proteins and processes beyond the program of lipid synthesis directly regulated by SREBP. In future studies, it will be important to identify additional targets of miR33 that are induced by mTORC1 inhibitors and their contribution to the response of cells, tissues, and systems to these inhibitors, in both physiological and pathological settings.

2.6 Acknowledgements

This work was supported by NIH/NCI grants F31-CA186295 (I.K.), P01-CA120964 (B.D.M.) and R35-CA197459 (B.D.M.).

2.7 Author Contributions

Initial observations were made by M.Z., and figure 2.1E. Mouse-work was performed by V.B. and M.T. (Figure 2.1F, G). All other experiments were performed by I.K. I.K. and B.D.M. analyzed all data and wrote the manuscript.

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CHAPTER 3:

BIOLOGICAL SIGNIFICANCE OF miR-33 INDUCTION AND PIM REPRESSION BY mTORC1 3.1 Abstract

The full downstream consequences of mTORC1 signaling have not yet been fully elucidated.

Here, we begin to define the physiological consequences of mTORC1-mediated control of miR-33, which is induced upon mTORC1-mediated stimulation of SREBP processing and transcriptional activity. We identify the pro-survival molecules PIM1 and IRS-2, which are both targeted by miR-33, as induced upon rapamycin treatment. Knockdown of SREBP by siRNA interference or inhibition of SREBP with cholesterol results in upregulation of the PIM1 transcript. Inhibition of the PIM kinases in combination with rapamycin treatment in Tsc2-/- mouse embryonic fibroblasts (MEFs) slows proliferation and increases cell death compared to either treatment alone. Finally, steady-state flux analysis of PIM inhibition compared to a rapamycin-induced setting finds decreased intermediates in the kynurenine pathway, with a subsequent decrease in steady-state NAD levels. Collectively, these data demonstrate that miR-33 targets, including PIM3 and PIM1, may play an important role in maintenance of cell survival and metabolic homeostasis upon mTORC1 inhibition.

3.2 Introduction

The mechanistic target of rapamycin complex 1 (mTORC1) is a central regulator of cell growth and metabolism that is situated downstream of several major pathways involved in the sensing of growth factors, cellular energy levels, and nutrient availability, including the PI3K-Akt, RAS-ERK, and AMPK pathways1. These pathways, through mTORC1 and other effectors, activate a wide array of metabolic and growth processes necessary for unregulated growth and as such are often mutated in cancer, leading to the frequent, constitutive, activation of mTORC1 across nearly all lineages2. While mTORC1 itself is infrequently mutated, its position at the convergence of several upstream signaling networks would seem to make it a prime target for precision therapies; however, with few exceptions, mTOR-targeted therapies alone are not sufficient to induce tumor regression3. While there are several reasons for these mostly

76 cytostatic effects4, one is that the complexity of the mTORC1 signaling network allows for intrinsic and mutational rewiring to survive mTORC1-targeted therapies. With few exceptions5-7, however, the downstream signaling events that lead to this maintenance of cell survival continue to be poorly characterized, which in turn limits the development of targeted strategies to treat tumors characterized by activated mTORC1.

Increasingly, altered expression of microRNAs has been implicated as a method of chemoresistance in a wide variety of cancer settings8-12. While less is understood about mTORC1- regulated microRNAs, several recent studies have begun to characterize an mTORC1-regulated non- coding RNA network, finding that changes in microRNA expression downstream of mTORC1 are characterized by known pro-survival and tumor suppressive microRNAs, and may contribute to resistance to the mTORC1 inhibitor rapamycin in some settings13,14. Our own work has placed miR-33 downstream of mTORC1, as it is induced via the transcription factors SREBP1 and 2, whose processing and mRNA expression are stimulated by mTORC1 signaling15,16. The implications of this finding remain to be fully elucidated; while several pro-survival proteins have been characterized as targets of miR-33, including

PIM1, PIM3, and IRS-217-19, the role of mTORC1 signaling upstream of these targets, and the functional implications of this miR-33-regulated network, have not yet been fully characterized.

The PIM kinases are a family of three kinases, PIM1, 2, and 3, that play a role in tumorigenesis due to their phosphorylation of a variety of pro-survival targets, including BAD and Ask120-22. They also have been shown to activate mTORC1 signaling through phosphorylation and inactivation of TSC2 and

PRAS40, both negative regulators of mTORC123-28. Due to their pro-survival effect, these kinases are promising targets in cancer therapy. In hematological malignancies, pan-PIM inhibition has been shown to inhibit proliferation and increase cell death29,30; combinations of PIM inhibitors with both traditional chemotherapies and targeted therapies have shown efficacy in solid and hematological settings31-34.

However, their efficacy in combination with mTOR inhibitors has yet to be explored. In this chapter, I investigate cell proliferation and death in cells treated with a combination of the mTORC1 inhibitor rapamycin and pan-PIM inhibitors. I also characterize pro-survival and metabolic targets of miR-33

77 downstream of mTORC1 signaling, to identify other potential targets for combination therapies. Finally, to determine why the PIM kinases are regulated by a primarily metabolic microRNA, I characterize metabolic changes upon PIM inhibition in mouse embryonic fibroblasts (MEFs).

3.3 Materials and Methods

Cell culture and RNAi

The immortalized litter-mate derived pair of Tsc2+/+ and Tsc2-/- (both p53-/-) mouse embryonic fibroblasts (MEFs) were provided by Dr. D.J. Kwiatkowski (Brigham and Women’s Hospital), and maintained in Dulbecco’s Modified Eagle Medium (DMEM; VWR, Radnor, PA, USA) with 4.5 g/L glucose containing 10% fetal bovine serum (FBS)35,36. U87MG-iPTEN cells were maintained in the presence of geneticin (G418, 0.4 mg/mL, Sigma-Aldrich, St. Louis, MO, USA) in DMEM with 4.5 g/L glucose containing 10% FBS and were developed in the laboratory of M.M. Georgescu (MD Anderson

Cancer Center)37. All siRNA-mediated knockdown experiments were carried out with ON-TARGET-plus

SMARTpool siRNAs (30 nM, GE Dharmacon, Lafayette, CO, USA). Cells were transfected using

Lipofectamine RNAiMax (Invitrogen, Carlsbad, CA, USA), according to the manufacturer’s protocol for reverse transfection. Rapamycin (553210, Calbiochem, San Diego, CA, USA) was used to inhibit mTORC1; 25-hydroxycholesterol (H1015, Sigma-Aldrich) was used to inhibit SREBP; simvastatin

(S6196-5MG, Sigma-Aldrich) was used to activate SREBP; SGI-1776 (S2198, Selleck Chemicals,

Houston, TX, USA) and AZD1208 (S7104, Selleck Chemicals) were used to inhibit the PIM kinases. mRNA expression analysis

RNA was isolated using the RNeasy Mini Kit (Qiagen, Valencia, CA, USA). Complementary

DNA was synthesized using the Superscript III First Strand Synthesis System (Invitrogen) and after dilution 1:20 in nuclease-free water was quantified using SYBR-Green for quantitative reverse transcription polymerase chain reaction (Bio-Rad CFX Connect Real-Time System). Each condition was

78 run in triplicate and normalized to RPLP0 (m36b4), or Actin. Primer sequences for mouse mRNAs were as follows: Pim1 (F 5’-CGACATCAAGGACGAGAACA-3’, R 5’-GTAGCGATGGTAGCGAATCC-

3’); Abca1 (F 5’-GGCAGTGTCCAACATCTGAAAA-3’, R 5’-CAGGGTTGGAGCCTGCTATTC-3’);

Irs-2 (F 5’-GAGCCTTCAGTAGCCACAGG-3’, R 5’-TCAGGGGTCTATCCATGCTC-3’).

Proliferation and cell death assays

For cell proliferation, cell number was measured in solution following trypsinization using a Z2

Coulter Counter (Beckman Coulter, Brea, CA, USA). Cells were transiently transfected with siRNA targeting PIM3 24 hours prior to treatment with rapamycin, and lysed at 24, 48, or 72 hours after rapamycin treatment.

For the crystal violet assay, cells were washed once with phosphate-buffered saline (PBS) supplemented with 1 mM CaCl2 and 1 Mm MgCl2, and then fixed with paraformaldehyde (PFA, 4% in

PBS [1mM CaCl2, 1 Mm MgCl2]) for fifteen minutes. After washing with PBS, cells were stained with

0.1% crystal violet in 10% ethanol for twenty minutes. Cells were washed three times in PBS prior to dye extraction with 10% acetic acid on the rocker for twenty minutes. Final suspension was diluted 1:4 and absorbance at 590 nm was read on a EnSpire Multimode plate reader (PerkinElmer, Waltham, MA,

USA).

Cell death was analyzed using the Dead Cell Apoptosis Kit with Annexin V Alexa Fluor® 488 and Propidium Iodide (PI) (Invitrogen) according to the manufacturer’s protocol. Briefly, adherent and nonadherent cells were combined, washed in PBS and resuspended in 1x Annexin V buffer (50 mM

HEPES, 700 mM NaCl, 12.5 mM CaCl2, pH 7.4) before incubation with Annexin-V Alexa Fluor® 488

(5 µL per 100 µL) and PI (1 ng/µL) for fifteen minutes. Each sample was then resuspended in Annexin buffer before analysis by flow cytometry (FACSCalibur, Bectin Dickinson, Franklin Lake, NJ, USA).

Metabolite profiling for steady state analysis (metabolomics)

To determine relative levels of intracellular metabolites, extracts were prepared in quadruplicate from 10-cm plates that had been serum-starved and treated with either rapamycin or rapamycin plus SGI-

1776 for 16 hours. Metabolites were extracted on dry ice with 4-mL 80% methanol (-80°C), and analyzed using a 5500 QTRAP triple quadrupole mass spectrometer (AB/SCIEX) coupled to a Prominence UFLC

HPLC system (Shimadzu) via selected reaction monitoring (SRM) of a total of 254 endogenous water- soluble metabolites for steady-state analyses of samples, as described previously38,39. Peak areas of metabolites detected by mass spectrometry were normalized to median and then normalized to protein concentrations.

Statistical analyses

All qRT-PCR data were analyzed with GraphPad Prism (La Jolla, CA, USA). P-values were calculated by an unpaired two-tailed Student’s t-test, where appropriate. For steady-state metabolomics,

MetaboAnalyst was used to assist data analyses (http://www.metaboanalyst.ca). For heat map, normalized peak areas were sorted based on their Marker selection using GENE-E software from the Broad Institute

(http://www.broadinstitute.org/cancer/software/GENE-E/). Marker selection identifies entities (e.g., metabolites) that are present at different levels between experimental conditions, and the software estimates the significance (p-value) of the differences, correcting for multiple hypotheses testing by calculating the false discovery rate and family-wise error rate. P-values were calculated by an unpaired two-tailed Student’s t-test for all pair-wise comparisons (N=4). The distributions of the variables of interest are normal.

3.4 Results

3.4.1 miR-33-targeted transcripts are changing downstream of mTORC1

In Tsc2-/- MEFs, which are characterized by constitutive mTORC1 activation, we investigated the transcript levels of several known miR-33 targets. Upon mTORC1 inhibition with rapamycin, the canonical miR-33 target ABCA1, a cholesterol efflux transporter, was induced (Figure 3.1A).

Figure 3.1. miR-33 targets are induced by rapamycin.

(A) mRNA expression levels of Abca1, Pim1, and Irs-2 in Tsc2-/- MEFs. Cells were starved and treated overnight for 16 hours with vehicle or rapamycin (20 nM). N=3; data are shown as mean ± s.e.m. (B)

Pim1 mRNA expression levels upon transient siRNA knockdown of SREBP1 and 2 in Tsc2-/- MEFs.

Cells were transfected for 72 hours and starved overnight for the final 16 hours before lysis. N=3; data are shown as mean ± s.e.m. (C) Pim1 mRNA expression levels in Tsc2-/- MEFs starved and treated for 16 hours with vehicle, rapamycin (Rap, 20 nM) or 25-hydroxycholesterol (25-HC, 1 μg/mL). N=3; data are shown as mean ± s.e.m. (D) Pim1 mRNA expression levels in Tsc2-wildtype MEFs treated overnight with simvastatin (5 µM). N=2; data are shown as mean ± s.e.m. *statistical significance determined by a two- tailed t-test.

Interestingly, two pro-survival molecules, the protein kinase PIM1 and insulin receptor substrate 2

(IRS2), were also induced upon rapamycin treatment in this setting (Figure 3.1A). As SREBP1 and 2 transcriptional activity is necessary for sustained levels of miR-33 in the cell, we tested the effect of loss of SREBP1 and 2 on PIM1 levels (Figure 3.1B). Transient siRNA knockdown of SREBP1 and 2 in Tsc2-/-

MEFs resulted in an increase in PIM1 mRNA expression levels. Full-length SREBP is retained in the endoplasmic reticulum (ER), and its proteolytic processing and subsequent nuclear localization of its mature form can be stimulated by mTORC1 activity15. As a major regulator of lipid synthesis, SREBP is also sensitive to intracellular sterol levels, and can be activated by low levels of intracellular sterols independently of mTORC1 activity40. Treatment of Tsc2-/- cells with 25-hydroxycholesterol (25-HC), which strongly inhibits SREBP processing and activity, resulted in increased PIM1 expression levels

(Figure 3.1C), while activation of SREBP processing via treatment with simvastatin in Tsc2-wildtype

MEFs resulted in decreased levels of PIM1 (Figure 3.1D).

3.4.2 Additive effects of combination of mTORC1 and PIM kinase inhibitors in Tsc2-/- MEFs

Since the PIM kinases have shown efficacy as therapeutic targets in cancer, we performed a transient siRNA knockdown of PIM3 in Tsc2-/- MEFs, either alone or in combination with rapamycin

(Figure 3.2A). Loss of PIM3 combined with mTORC1 inhibition had an additive effect on cell proliferation. Interestingly, two structurally distinct pan-PIM inhibitors, SGI-1776 and AZD1208, also showed an additive effect on slowing proliferation by crystal violet assay when combined with even a low dose of rapamycin treatment (Figure 3.2B), and the dual inhibitor combination also increased cell death in an Annexin V/PI assay (Figure 3.2C). Combining rapamycin with these inhibitors in the human glioblastoma line U87MG, which also has constitutive mTORC1 activity downstream of PTEN loss, did not have an increased ability to slow proliferation compared to rapamycin alone (Figure 3.2D).

Figure 3.2. Combined inhibition of PIM3 and mTORC1 has an additive effect in MEFs.

(A) Proliferation of Tsc2-/- MEFs upon transient siRNA knockdown of PIM3 either alone or combined with rapamycin treatment (20 nM) over a 96-hour time-course. (B) Crystal violet assay for proliferation of Tsc2-/- MEFs upon treatment with vehicle, rapamycin (Rap, 1 nM), or the pan-PIM inhibitors SGI-1776

(300 nM) or AZD1208 (3 µM), either singly or in combination for 72 hours. N=2; error bars are shown as mean ± s.e.m. *All column comparisons are statistically significant (p < 0.05) as calculated by two-tailed t-test.

Figure 3.2. (Continued).

(C) Cell death assessed by annexin V/propidium iodide (PI) staining in Tsc2-/- MEFs upon starvation and treatment with vehicle, rapamycin (20 nM), or SGI-1776 (300 nM), either singly or in combination for 24 hours. (D) Crystal violet assay for proliferation of U87MG cells upon treatment with vehicle, rapamycin

(Rap, 20 nM), or the pan-PIM inhibitors SGI-1776 (300 nM) or AZD1208 (3 µM), either singly or in combination for 72 hours. N=2; error bars are shown as mean ± s.e.m. *All column comparisons are statistically significant (p < 0.05) as calculated by two-tailed t-test.

3.4.3 Implications for PIM effects on metabolism, particularly cellular NAD+ levels

While the PIM kinases are most well characterized as activators of pro-survival pathways, their placement downstream of mTORC1, SREBP, and miR-33 highlights a potentially unexplored role for these kinases in metabolism. To determine if the PIM kinases are playing a role in metabolism, we performed a steady-state metabolomics experiment using Tsc2-/- MEFs treated with either rapamycin, to induce PIM1 and 3, or with rapamycin plus SGI-1776, with high PIM expression but blocked activity.

From an initial screen of 224 metabolites identified through liquid chromatography (LC) tandem mass spectrometry (MS/MS), 49 were significantly changed (p < 0.05) between the high (rapamycin-treated) and low (rapamycin + SGI-1776) PIM3 settings, of which 22 were downregulated upon PIM inhibition, and 27 were upregulated (Figure 3.3A). Metabolite changes observed in control conditions are represented in Figure 3.4. These metabolites are involved in a variety of metabolic pathways important for energy production in the cell, including glycolysis. Interestingly, several metabolites in the kynurenine pathway, which synthesizes nicotinamide adenine dinucleotide (NAD) from tryptophan, were down- regulated upon PIM inhibition (Figure 3.3B, C). Nicotinamide mononucleotide, a precursor of NAD+ from the salvage pathway, was also decreased in this setting. Collectively, these data demonstrate that the

PIM kinases may play a role in maintaining cellular energy levels, particularly in settings characterized by their upregulation.

3.5 Discussion

Since the discovery in 2002 of two microRNA clusters, miR-15 and miR-16, in a frequently deleted region of chromosome 13q14 in chronic lymphocytic leukemia41, a variety of studies have implicated microRNA dysregulation as a frequent hallmark of cancer, with potential for therapeutic intervention and use of microRNA signatures in defining tumor type, prognosis and response42. While less is known about microRNA dysregulation in mTORC1-driven tumor settings, a handful of recent

Figure 3.3. Metabolomic profiling in high/low PIM3 settings reveals changes in NAD+ levels and synthesis upon PIM inhibition.

(A) Steady-state metabolite profiles from Tsc2-/- MEFs serum starved and treated for 16 hours with rapamycin (20 nM) or rapamycin plus SGI-1776 (300 nM). Intracellular metabolites from four independent samples per condition were profiled by means of liquid chromatography (LC)MS/MS.

Metabolites shown were significantly changed between the two conditions (p < 0.05, student’s t-test), and are ranked from most significantly decreased metabolites to most significantly increased. (B) Schematic of the tryptophan biosynthesis pathway for de novo NAD+ synthesis; also shown is the salvage pathway metabolite nicotinamide mononucleotide, which can also be used to make NAD+. (C) The effects of PIM inhibition on the steady-state levels of indole, tryptophan, kynurenic acid, xanthurenic acid, NAD+, and nicotinamide mononucleotide, measured via LC/MS/MS in Tsc2-/- MEFs after starvation and treatment for 16 hours with rapamycin (20 nM) or rapamycin plus SGI-1776 (300 nM). N=4; error bars are shown as mean ± s.e.m. *All column comparisons are statistically significant (p < 0.05) as calculated by two- tailed t-test.

Figure 3.3. (Continued).

Figure 3.4. Supporting metabolomics data for Figure 3.3.

Steady-state metabolite profiles from Tsc2-/- MEFs serum starved and treated for 16 hours with rapamycin

(20 nM) or rapamycin plus SGI-1776 (300 nM). Intracellular metabolites from four independent samples per condition were profiled by means of liquid chromatography (LC)MS/MS. Metabolites shown were significantly changed between the two conditions (p < 0.05, student’s t-test), and are ranked from most significantly decreased metabolites to most significantly increased. Conditions were compared between vehicle- and rapamycin-treated cells (A), vehicle- and SGI-1776-treated cells (B), and rapamycin- versus

SGI-1776-treated cells (C).

Figure 3.4. (Continued).

91 studies have characterized the microRNA network downstream of mTORC1, finding upregulation of oncogenic microRNA clusters and downregulation of tumor suppressing clusters upon long-term rapamycin treatment13,14. My previous work has placed another microRNA, miR-33, downstream of mTORC1 activity. miR-33 has been primarily characterized as a metabolic microRNA, with targets in the cholesterol and fatty acid biosynthesis pathways, but a handful of pro-survival molecules have been characterized as miR-33 targets as well, indicating that this microRNA may have effects on pathways outside of its role in metabolism17-19,43-45. In this study, I have found that several of these pro-survival targets of miR-33, specifically IRS-2 and PIM1, are induced by rapamycin treatment, which, in addition to my earlier findings placing PIM3 downstream of mTORC1, highlight several feedback pathways that may be acting to diminish the efficacy of mTORC1-targeted therapies in cancer by restoring pro-survival signaling. These data highlight the likelihood that dozens of as-yet uncharacterized targets of miR-33 repression may be altered upon mTORC1 inhibition, with unknown physiological consequences. Indeed, in a survey of gene transcript changes downstream of mTORC1 upon inhibition with rapamycin, we found 18 significantly up- or down-regulated genes that are predicted targets of miR-33 (from Targetscan)

(Table 3.1)46,47. Importantly, the majority of these targets (fourteen) were inhibited in high mTORC1 settings and induced upon rapamycin treatment. Collectively, these findings demonstrate that miR-33 is likely targeting transcripts in a diverse array of cellular processes. Future studies to define the effect of this miR-33-regulated program and other microRNAs regulated by mTORC1 will be necessary to completely define the downstream signaling landscape.

Despite the activation of mTORC1 across nearly all lineages2, mTORC1-targeted inhibitors alone have proven mostly ineffective in the clinic3. As a result, several recent studies have begun probing the efficacy of mTORC1 inhibitors in combination with other therapies48-50. While some of these studies combined mTOR inhibition with traditional chemotherapies49, more recent studies have sought to combine targeted therapies informed by knowledge of the signaling network itself, finding that these therapies are capable of synergizing to increase tumor regression48,50. In the mTORC1-activated Tsc2-/-

MEFs, the combination of either PIM3 siRNA-mediated knockdown with rapamycin or treatment with

Table 3.1. Predicted miR-33 target genes regulated downstream of mTORC147.

Genes with a p value < 0.01 were classified as mTORC1-regulated transcripts in the original study; this table represents the dataset with a cutoff of p < 0.05. PKA/C = protein kinase A or C; HDAC = Histone deacetylase; ER = endoplasmic reticulum; ALL = acute lymphoblastic leukemia; TNF = tumor necrosis factor.

Table 3.1. (Continued).

Induced by p Gene Name Rapamycin value Functions Proto-oncogene; survival Pim3 proviral integration site 3 Yes < 0.01 kinase PKA signaling; binds actin Akap2 A kinase (PRKA) anchor protein 2 Yes < 0.01 cytoskeleton Probable ATP-dependent Ddx5 DEAD (Asp-Glu-Ala-Asp) box polypeptide 5 Yes < 0.01 RNA helicase runt-related transcription factor 1; translocated Tumor suppressor; Runx1t1 Yes < 0.01 transcription repression via to, 1 (cyclin D-related) HDAC recruitment Reduction of oxidized Msrb3 methionine sulfoxide reductase B3 Yes < 0.01 methionine on proteins at ER or mitochondria SET domain containing (lysine Lysine methyltransferase; Setd7 Yes < 0.05 role in metabolic disease methyltransferase) 7 and cancer progression Transcriptional coactivator; role in pediatric ALL, Arid5b AT rich interactive domain 5B (Mrf1 like) Yes < 0.05 adipogenesis and liver development Drosophila homolog Pcnx pecanex homolog (Drosophila) Yes < 0.05 involved in Notch signaling Binds membrane cytoskeleton and Add1 adducin 1 (alpha) Yes < 0.05 Ca2+/calmodulin complex; substrate of PKC/PKA E3 ubiquitin ligase involved Pja2 praja 2, RING-H2 motif containing Yes < 0.05 in PKA and pro-survival signaling Transcription factor involved in cell-cycle Tfdp2 transcription factor Dp 2 Yes < 0.05 regulation and DNA replication Tsc22d2 TSC22 domain family 2 Yes < 0.05 Putative tumor suppressor May be involved in Ttc28 tetratricopeptide repeat domain 28 Yes < 0.05 formation of midbody during mitosis Regulates TNF receptor Traf3 Tnf receptor-associated factor 3 Yes < 0.05 activation, particularly in immune response activation phosphatidylinositol 3 kinase, regulatory Activates cell survival Pik3r3 No < 0.01 subunit, polypeptide 3 (p55) pathways Beta-tubulin Ttll7 tubulin tyrosine ligase-like family, member 7 No < 0.01 polyglutamylase required for neurite growth methylenetetrahydrofolate dehydrogenase One-carbon folate Mthfd2 No < 0.01 metabolism; frequently (NAD+ dependent) overexpressed in cancer subunit of the oligosaccharyltransferase Stt3b No < 0.01 Involved in N-glycosylation complex, homolog B (S. cerevisiae)

94 the pan-PIM inhibitors SGI-1776 and AZD1208 with rapamycin had an additive effect on slowing proliferation, with an increase in cell death as seen by the annexin V/PI positive staining. However, we did not find a similar additive effect of the dual inhibitor combination in the glioblastoma U87MG line, which has activated mTORC1 downstream of PTEN loss. The PIM kinases have been shown to be upregulated in hematological malignancies51,52, and they have been found to play a role in hepatocellular carcinoma and pancreatic cancers53-57, so it is possible that the dual combination of PIM and mTORC1 inhibition would be more efficacious in these settings. Indeed, a handful of recent studies have shown efficacy of combined PIM and mTOR inhibitors, including in acute myeloid leukemia58. Furthermore,

PIM1 and PIM3 are not the only pro-survival molecules upregulated downstream of mTORC1, as IRS-2 and possibly other miR-33 targets are induced upon rapamycin treatment as well. Future studies designing targeted inhibitor combinations in cancer should investigate miR-33 activation in combination with mTORC1 inhibitors, in order to block the induction of its full downstream program. It may be necessary to block all the miR-33 pro-survival targets upon mTORC1 inhibition, rather than only one or two at a time.

The repression of PIM1 and PIM3 downstream of mTORC1 defines a new negative feedback loop in the greater mTORC1 signaling network, as the PIMs have been described as upstream activators of mTORC123,24. However, their placement downstream of SREBP and miR-33, both primarily involved in cellular metabolism, indicates that the PIM kinases may also play a role in control of metabolic functions. Indeed, there is increasing evidence for this hypothesis, as PIM1 has been shown to affect glycolysis and PIM3 to affect lipid droplet accumulation, both in hepatocellular carcinoma53,59.

Furthermore, loss of the PIM kinases effects mitochondrial health, glycolysis, the pentose phosphate pathway, and mitochondrial oxidative phosphorylation60-62. Generally, the metabolic effects of PIM kinase loss or overexpression seem to influence cellular energy levels. Consistent with these reports, our metabolomics results find alterations in glycolytic pathway intermediates such as fructose-6-phosphate and D-glyceraldehyde-3-phosphate, which are reduced upon PIM inhibition in Tsc2-/- MEFs.

Interestingly, several intermediates of the kynurenin pathway, which synthesizes NAD from tryptophan,

95 are all decreased upon pan-PIM inhibition as well. Collectively, these data indicate that the PIM kinases may have a role in maintaining cellular energy homeostasis. Future studies to determine which downstream targets are responsible for mediating these effects will be needed to determine how the PIM kinases are involved in cellular metabolism. Furthermore, the potential effect of PIM3 on lipid accumulation points to the potential for a lipidomics study, to investigate if this kinase affects any specific lipid species, which would in turn shed light on the full downstream consequences of alterations in the expression and activity of the PIM kinases.

Collectively, these data begin to investigate the full physiological consequences of miR-33 activation, and PIM1 and PIM3 repression, in response to changes in mTORC1 activity. In future studies, it will be important to continue characterizing additional targets of miR-33 induced by mTORC1 inhibitors, and to more fully characterize the consequences of PIM activation and inhibition on cellular metabolic processes, with implications for the many diseases characterized by dysregulation in the mTOR and PIM signaling networks.

3.6 Acknowledgements

We thank Issam Ben-Sahra and Gerta Hoxhaj for technical advice and stimulating discussions.

This work was supported by NIH/NCI grants F31-CA186295 (I.K.), P01-CA120964 (B.D.M.) and R35-

CA197459 (B.D.M.).

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60 Song, J. H. et al. Deletion of Pim kinases elevates the cellular levels of reactive oxygen species and sensitizes to K-RAS-induced cell killing. Oncogene 34, 3728-3736 (2015).

61 Din, S. et al. Pim-1 preserves mitochondrial morphology by inhibiting dynamin-related protein 1 translocation. Proceedings of the National Academy of Sciences 110, 5969-5974 (2013).

62 Din, S. et al. Metabolic Dysfunction Consistent With Premature Aging Results From Deletion of Pim Kinases. Circulation Research 115, 376-387 (2014).

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CHAPTER 4:

CONCLUSIONS

Sections 4.2.1 and 4.2.4 of this chapter are adapted from: Kelsey, I. & Manning, B. D. mTORC1 status dictates tumor response to targeted therapeutics. Science Signaling 6, (2013). 4.1 Overview

In this dissertation, I investigated the control of PIM3 expression by mTORC1 (Figure 4.1). I found that PIM3 is repressed by mTORC1 and induced by rapamycin treatment in mouse, rat, and human cells, and in a variety of cancer cell settings. I further found that this repression is mediated via the transcription factor SREBP and its intronic miRNA, miR-33, which targets the PIM3 transcript. Next, I demonstrated that a handful of other miR-33 targets are induced by rapamycin, raising the possibility that several targets of miR-33 may contribute to pro-survival effects upon mTORC1 inhibition. I also showed that rapamycin in combination with pan-PIM inhibitors shows promise as a dual-combination therapy, although the effects may be cell type specific. Furthermore, I show that the PIM kinases may play a role in regulating cellular energy levels, specifically the generation of NAD+ from tryptophan. While more experiments will be required in order to fully map the complex network downstream of mTORC1, my data characterize a previously unappreciated survival pathway induced by mTORC1 inhibition, with implications for effects on Cell Metabolism, energy, and survival.

4.2 Challenges of targeting the mTORC1 signaling axis in disease

4.2.1 Overview

The notion that single oncogenic events can render cancer cells addicted to specific molecular pathways has led to a movement toward genotype-based personalized approaches to cancer treatment using targeted therapeutics. Drugs that target the most common oncogenic signaling pathways, such as the

PI3K-Akt and RAS-RAF-MEK-ERK pathways, are at the forefront of this revolution. Clinical trials using tumor genetics to stratify patients for these treatments will surely increase response rates, an idea supported by early clinical data from such trials (e.g., refs1,2). However, it is also evident that there will be some non-responders and that resistance can develop in initial responders. Therefore, while

103

Figure 4.1. Graphical summary of the dissertation.

104 genetic analyses of tumor tissue to determine the primary molecular drivers of the cancer will be important for dictating first-line therapies, there will continue to be tumors that resist these precision treatments. As such, there is a need for defining resistance mechanisms to targeted therapies and for identifying biomarkers to predict and monitor tumor response. As our understanding of cell signaling networks improves, it becomes evident that a major mechanism of resistance to pathway inhibitors will be the activation of alternative signaling events converging on a few common downstream targets that are critical for cancer progression.

4.2.2 Crosstalk and feedback pathways contribute to rewiring of the signaling network in response to specific inhibitors

Despite ongoing interest in targeting the PI3K-Akt-mTOR pathway in cancer, single agent activity of PI3K and mTOR inhibitors has been mostly characterized by a lack of durable responses in the clinic3. Initial clinical trials targeting mTORC1 have investigated the efficacy of rapamycin and its analogs (rapalogs) in a wide variety of cancers, but the majority of these trials failed to achieve tumor regression. While a variety of factors likely contribute to this observed effect of rapalogs, including the fact that rapamycin is a partial inhibitor of mTORC1 and that it arrests or delays cells in the G1 phase of the cell cycle4,5, a growing body of work has increasingly shown that intrinsic properties of the signaling network also contribute to sustained survival upon mTORC1 inhibition (Figure 4.2). In normal cells, the complex wiring of cellular signaling networks ensures that the cell can maintain homeostasis when faced with challenges such as fluctuations in the environment. However, we are only beginning to understand the full extent of the feedback and crosstalk mechanisms that exist to ensure this stability, particularly within the greater mTORC1 signaling network, and the implications of these pathways in disease and therapeutics.

When active, mTORC1 inhibits its upstream activation via Akt through its phosphorylation of

S6K, which inhibits mTORC2 via phosphorylation of its subunits Rictor (T1135) and Sin1 (T86, T398)6-8.

This blocks mTORC2-mediated activation of Akt at S473, leading to decreased Akt activity upstream of

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Figure 4.2. Feedback pathways in the mTORC1 signaling network.

There are many feedback pathways that reactivate signaling in the PI3K-Akt-mTORC1 and RAS-ERK signaling networks. Inhibition of single nodes in the network often result in reactivation of signaling through a variety of mechanisms: upregulation of receptor tyrosine kinases (RTKs), de-repression of adaptor proteins, and reactivation of upstream kinases.

106 mTORC19. Conversely, inhibition of mTORC1 relieves this repression of mTORC2, restoring signaling through Akt. My own findings highlight a previously uncharacterized negative feedback loop involving mTORC1 and the PIM kinases. PIM1 and PIM3, through transcript targeting by miR-33, are repressed by mTORC1 activity and induced by mTORC1 repression, leading to restored activity of these kinases.

Among the characterized effectors of the PIM kinases are TSC2 and PRAS4010,11, which would then be capable of reactivating mTORC1 signaling. Interestingly, several studies have identified the PIMs as upregulated in resistance models of Akt or PI3K inhibition12,13. In a recent study to identify genes upregulated in breast cancer cells resistant to the PI3K inhibitor BYL719, PIM1 kinase was identified as upregulated13. The authors further showed that all three PIM kinases were capable of sustaining cell proliferation through upregulation and sustained phosphorylation of targets including PRAS40 and ribosomal protein S6. This indicates that the activity of these kinases, perhaps in part through their activation of mTORC1, may play an important role in feedback and resistance mechanisms in cancers characterized by activated mTORC1 signaling. It remains to be seen whether inhibitors of PI3K are capable of inducing PIM transcript levels via mTORC1-mediated control of miR-33, or if the upregulation of PIM1 in this setting was via an independent mechanism. It will also be interesting to determine if other upstream inhibitors targeting Akt, RTKs, or molecules in the RAS-RAF-MEK-ERK pathway are also characterized by upregulation of PIM kinases in resistant models, and if the mechanism of activation involves changes in miR-33 levels downstream of altered mTORC1 activation.

mTORC1 also negatively regulates upstream signaling via its inhibition of insulin receptor substrate 1 (IRS-1), a cytoplasmic adaptor that links activated cell surface receptors including insulin (IR) and insulin-like growth factor 1 (IGF-1R) to PI3K-Akt activation. mTORC1 promotes the degradation of

IRS-1 through both direct phosphorylation and phosphorylation by S6K114-16. Furthermore, reactivation of IRS-1 via mTORC1 inhibition also results in increased signaling through IRS-1/PI3K to the RAS-

MAPK signaling pathway17. The Harrington et. al. study also identified control of IRS-2 by mTORC1, although unlike IRS-1, no phosphorylation sites were identified. Interestingly, IRS-2 has been characterized as a target of miR-3318, and I have shown that its transcript levels are induced upon

107 rapamycin treatment, which is consistent with the hypothesis that miR-33 is regulated by mTORC1

(Figure 3.1). A third mechanism by which mTORC1 represses the IRS proteins is through another adaptor protein, growth factor receptor bound protein 10 (GRB10), which is stabilized by mTORC1-mediated phosphorylation, allowing it to repress signaling activity of the IRS proteins19,20. Interestingly, Yu et. al. also found that loss of GRB10 expression was negatively correlated with loss of the tumor suppressor

PTEN, indicating that this protein might be a tumor suppressor that would be down-regulated upon mTORC1 inhibition and highlighting the potential importance of this molecule in cell growth pathways.

Independently of the PI3K-Akt pathway, ERK can also inhibit signaling from RTKs via its repression of the adaptor proteins GRB2-associated binder 1 and 2 (GAB1/2), which can activate both PI3K and

RAS21,22.

The PI3K-Akt and RAS-RAF-MEK-ERK pathways, both independently and through their convergence on mTORC1, also regulate the expression and activity of upstream receptor tyrosine kinases

(RTKs), many of which are inhibited by the activity of these pathways. The PI3K-Akt pathway can be activated by the platelet-derived growth factor (PDGF) receptor (PDGFR), which has two cognates,

PDGFRα and PDGFRβ, which when bound by ligands such as PDGF undergo homo- or heterodimerization followed by autophosphorylation23,24. This then allows promotion of intracellular signaling cascades. The constitutive activation of mTORC1 by Tsc2 loss or activation of Akt results in downregulation of PDGFRα and PDGFRβ, and treatment with rapamycin restores expression of PDGFR and signaling through Akt in an S6K dependent manner6,24. Independently of mTORC1, Akt inhibits the transcription factor FOXO, which targets a variety of RTK genes including IR; IGF-1R; vascular endothelial growth factor (VEGF) receptor; estrogen receptor α (ERα); and members of the EGF Receptor family (EGFR, ERBB2, 3, and 4 [also known as Her2, 3, and 4])25-29. Inhibition of Akt or mTOR causes marked induction of the expression, phosphorylation, and activation of these RTKs, restoring growth factor-mediated activation30,31. Furthermore, MEK inhibition can also result in increased activation of

ERBB3 and EGFR due to loss of inhibitory ERK-mediated threonine phosphorylation32. The increased activation of ERBB3 signaling in a variety of epithelial cancer settings was able to bypass MEK

108 inhibitory effects on cell growth by activation of PI3K-Akt signaling. This reinduction of RTK signaling upon treatment with inhibitors targeting various nodes in the network contributes to resistance in a variety of settings, including in ovarian, breast, colorectal, and non-small cell lung cancer.

The transcription factor Myc can repress the transcription of a variety of RTKs, including

ERBB2, ERBB3, PDGFR, EGFR, and VEGFR33,34. ERK stabilizes Myc protein levels by phosphorylation at S6235. Once phosphorylated at S62, Myc can be subsequently phosphorylated at T58 by GSK3β, which targets it for degradation36. Myc protein accumulation is further enhanced by PI3K-Akt signaling via Akt-mediated inhibitory phosphorylation of GSK3β37. Finally, mTORC1 itself drives Myc protein accumulation through S6K-mediated enhancement of its cap-dependent translation38. Inhibition of the PI3K-Akt-mTORC1 or RAS-RAF-MEK-ERK-RSK-mTORC1 pathways results in lower levels of

Myc protein and subsequent upregulation of these RTKs. Conversely, the induction of PIM kinase expression and activity downstream of mTORC1 inhibition would instead promote Myc translation and stability. It is possible that PIM kinase-mediated stabilization of Myc via S62 phosphorylation is abrogated by subsequent T58 phosphorylation by activated GSK3 in these conditions. However, a recent study has implicated PIM1 as capable of phosphorylating and inhibiting GSK3 in prostate cancer cells, indicating that further studies are needed to determine the relative contribution of these kinases in control of GSK3 activity and Myc expression, and whether these effects have any tissue specificity.

4.2.3 Redundancies in the greater mTORC1 network enable sustained signaling

As evidenced by their convergence on Myc and the TSC complex, ERK, RSK, Akt, and the PIM kinases often converge on the same substrates when activated (Figure 4.3A). FOXO, which is inhibited by Akt signaling, can also be inhibited by ERK, albeit via a distinct mechanism: Akt phosphorylation of

FOXO1 and FOXO3 increases their interaction with 14-3-3 and sequestration in the cytosol27, while ERK

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Figure 4.3. Convergent targets downstream of the PI3K-Akt, RAS-ERK, and PIM signaling pathways.

Convergent targets downstream of the AGC kinases Akt, S6K, and RSK, and the evolutionarily unrelated

PIM kinases allow for broad redundancy in the network. Convergent targets include proteins involved in mRNA translation (yellow and orange), apoptosis (teal), and cell cycle progression (lime green).

Convergence on GSK3 and FOXO influences targets involved in survival, proliferation, growth, and metabolism.

110

Figure 4.3. (Continued).

111 phosphorylation of FOXO3 at distinct sites targets it for proteasome-mediated degradation via increased interaction with the E3 ubiquitin ligase MDM239.

Many of the proteins in the PI3K-Akt-mTORC1 and RAS-ERK pathways have convergent targets because they are members of the AGC kinase family (i.e., RSK, Akt, and S6K). The AGC kinase family consists of 60 proteins that are characterized by a conserved catalytic domain and activated by phosphorylation of two highly conserved regulatory motifs: an activation segment in the catalytic domain targeted by PDK1, and a hydrophobic motif40. The hydrophobic motifs of these proteins are activated by different mechanisms: S6K is phosphorylated by mTORC1; Akt by mTORC2; and RSK can autophosphorylate itself. These kinases in turn regulate a consensus motif of RXRXXS/T, leading them to often, but not always, phosphorylate the same regulatory sites on shared substrates41. Interestingly, we have only recently begun to appreciate the convergent role played by the PIM kinases in this network, as they are evolutionarily unrelated to the AGC kinase family. However, the PIM consensus motif

(K/RXRHXS/T) is highly similar to the ACG kinase consensus motif, leading them to share many targets with the ACG kinase family proteins as well42-44.

Protein synthesis can be augmented by the activity of RSK, Akt, S6K, and the PIM kinases via regulation of unique targets and through shared effectors. Akt, RSK, and PIM2 all converge on TSC2, leading to its inactivation by phosphorylation at several residues (Figure 4.3B)10,45. Although not an AGC kinase, ERK also inactivates TSC through phosphorylation of distinct regulatory motifs45. Inactivation of

TSC2 leads to activation of mTORC1, which can then drive protein synthesis through S6K and 4E-BP1. mTORC1 can be further activated by dissociation of PRAS40, a non-essential member of mTORC1, via its phosphorylation by Akt at T24646,47. PIM1 has also been shown to activate mTORC1 through inhibitory targeting of PRAS40, also at T24611. ERK and RSK further affect this pathway through phosphorylation of the mTORC1 component Raptor at distinct regulatory sites48-50.

Activated mTORC1 drives cap-dependent protein synthesis through S6K- and 4E-BP-dependent mechanisms. S6K stimulates mRNA translation via eIF4B phosphorylation and recruitment to its binding partner eIF4A RNA helicase51,52. Independently of mTORC1 and S6K, eIF4B can be activated by Rsk,

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Akt and the PIM kinases at S422 and/or S40653-55. Rsk and S6K further promote cap-dependent translation through phosphorylation of ribosomal protein S6 (rpS6) at S235/236, and S6K additionally at

S240/24456,57. PDCD4, an inhibitor of the translation initiation complex, is targeted for degradation by phosphorylation by both S6K and Akt51,58. After translation initiation, AGC kinases can further enhance mRNA elongation through inhibitory phosphorylation of eEF2K, which causes derepression of the mRNA translocation protein eEF259. eEF2K is targeted by both S6K and Rsk activity at S36659. The promiscuity of these proteins ensures that the cell can regulate protein translation in mTORC1-dependent and -independent manners.

Beyond protein synthesis, the AGC kinases and PIMs co-regulate proteins involved in PI3K- mTOR- and ERK-mediated cell survival, proliferation, and metabolism. Akt, RSK, S6K, and PIM1 can all phosphorylate GSK3 at S9/S21, resulting in its inhibition and subsequent repression of its control of cell survival, proliferation, and metabolism through a variety of downstream effectors37,60-62. Cell survival is further regulated by AGC kinases via BAD, a pro-apoptotic BCL2 family member that when not phosphorylated can interact with the pro-survival BCL2 family members, freeing BAX and BAK to induce apoptosis at the mitochondria63. There are two major RXRXXS/T consensus motifs on BAD, at

S112 and S136; RSK, Akt, and the PIM kinases phosphorylate S112, while Akt and S6K phosphorylate

BAD at S13664-67. The phosphorylation of these sites results in recognition and sequestration in the cytosol by 14-3-3, freeing the pro-survival BCL2 family members at the mitochondria. Akt and the PIMs further inhibit apoptosis through inhibition of the pro-apoptotic Ask1 at S83, which can trigger apoptosis through a variety of mechanisms68,69.

Cell cycle progression at the G1/S transition can be inhibited by p27Kip1, which binds to cyclin E or cyclin D to prevent their activation. Akt and Rsk can phosphorylate p27Kip1 at T198, resulting in its sequestration by 14-3-3 in the cytosol70,71. Similarly, the PIM kinases can repress the activity of this protein by phosphorylation at the same site72. Cell cycle progression can be further enhanced through inhibitory phosphorylation of p21Cip1/Waf1 at T145 by both Akt and PIM1, and S146 by PIM173,74.

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4.2.4 Resistance to targeted therapies is intrinsic to the wiring of the network

The many feedback loops, crosstalk mechanisms, and pathway convergences of the PI3K-Akt and

RAS-RAF-ERK-RSK signaling networks result in decreased efficacy of single-agent therapies targeting these pathways in disease. Interestingly, many of the feedback loops and crosstalk mechanisms result in restored signaling, through these or other pathways, to mTORC1. Interestingly, recent work from several groups has found that the status of mTORC1 activation may serve as a biomarker for resistance to inhibitors targeting upstream effectors, providing a rationale for specific combination therapies in distinct cancer lineages. In a panel of twenty breast cancer cell lines with mutations in the gene PIK3CA, which encodes the p110α subunit of PI3K, the response to p110α-selective PI3K inhibitor BYL719 was investigated75. Whether sensitive to this compound or not, all of the cell lines showed strong inhibition of

Akt. However, both initially resistant cell lines and cells selected for acquired resistance displayed sustained mTORC1 signaling in the presence of the PI3K inhibitor. Furthermore, acquired resistance in patients that initially responded and later progressed was characterized by restoration of mTORC1 signaling, assessed by phospho-S6 levels, in tumor samples. Treatment with RAD001 (everolimus), an mTORC1-specific inhibitor derived from rapamycin (sirolimus), restored sensitivity to BYL719 in resistant cell lines and xenograft tumors. Later studies of resistance to BYL719 in squamous cell carcinomas of the head and neck bearing PIK3CA mutations found similar results, with sustained mTORC1 signaling characterizing resistance76. In addition to supporting mTORC1 activation as a major resistance mechanism, these findings indicate that the addition of an mTORC1 inhibitor to anti-PI3K or -

Akt therapy could enhance or prolong the clinical response of PI3K-driven cancers.

Similarly, in BRAF-mutant melanoma treated with either the RAF inhibitor vemurafenib or the selective MEK inhibitor selumetinib, the activation status of ERK following treatment of a panel of

BRAF-mutant melanoma cell lines with these drugs did not predict sensitivity. Melanoma cell lines that were sensitive to either vemurafenib or selumetinib displayed inhibition of mTORC1 signaling after treatment, whereas resistant cell lines were all characterized by sustained mTORC1 signaling77. In a

114 separate study using mouse models of BRAF-mutant melanoma, the authors found that mutations in the

NF1 tumor suppressor promoted resistance to B-RAF inhibitors, but that this resistance could be overcome by mTOR inhibitors78.

The reactivation of RTKs upstream of both the PI3K-Akt and RAS-ERK pathways upon inhibition of single nodes in either pathway can also contribute to intrinsic resistance in cancer. In BRAF- mutant colon cancer, vemurafenib alone caused a rapid activation of EGFR, which was able to restore pro-growth signaling79. The efficacy of vemurafenib treatment was synergistically enhanced by the addition of an EGFR inhibitor. Similarly, one study found that resistance to rapamycin in hepatocellular carcinoma (HCC) is characterized by upregulation of PDGFRβ and restoration of signaling through the

PI3K-Akt and RAS-ERK pathways80. Addition of sorafenib, a multi-kinase inhibitor that targets both

PDGFR and RAF, provided greater anti-tumor efficacy in combination with rapamycin in this setting.

This result was extended in a separate study that found enhanced anti-proliferative effects in HCC cells when targeted with a combination of pan-AKT and mTOR inhibitors81. Several other studies in a variety of cancer lineages have also shown the importance of targeting multiple nodes in this network to achieve greater efficacy, including combined inhibition of IGF1R/IR with MEK inhibition in colorectal cancer82,83; either combined MEK and Akt inhibition, MEK and IGF1R/IR inhibition, or MEK and EGFR inhibition in non-small cell lung cancer84-86; and combination of MEK inhibition with a dual PI3K/mTOR inhibitor in NRAS-mutant melanoma87.

Importantly, a few recent studies have also shown the efficacy of combining PIM inhibition with

PI3K-Akt pathway inhibition. In prostate cancers driven by PI3K-Akt hyperactivation, the efficacy of Akt inhibitors is limited by upregulation of RTKs. The PIM kinases have been shown to control the upregulation of RTKs in this setting via enhanced cap-independent translation, and combination of PIM and AKT inhibitors had a synergistic effect on prostate cell lines and xenograft tumor growth88. More recently, combination of PIM inhibition with the PI3K-p110α inhibitor BYL719 in glioblastoma cells was shown to have a greater anti-growth effect than either inhibitor alone89. The results from these and other studies advance an approach to cancer therapy that entails not only genetic diagnosis of the major tumor-

115 promoting events to choose an initial targeted therapeutic, but also of early monitoring of biomarkers for activated feedback pathways that are predictive of therapeutic response. As our knowledge of the feedback loops, crosstalk, and redundant targets in this network increases, so too does our ability to design combinatorial therapies that maximize the inhibition of multiple arms of the network in order to enhance treatment outcomes.

4.3 Future Directions

Much of the interest in the PI3K-Akt-mTORC1 and RAS-ERK pathways has focused on their importance in driving cancer proliferation and growth. In recent years, this has extended to defining the crosstalk and feedback mechanisms innate to the network that contribute to resistance to targeted therapeutics. My work has added an important new branch to this network with the finding that PIM1 and

PIM3 are induced by rapamycin treatment, which would enable them to restore upstream signaling. The finding that this occurs through mTORC1-mediated activation of miR-33 also adds a new facet to our understanding of the complex network downstream of mTORC1.

The extent of the effect of PIM1 and PIM3 upregulation by mTORC1 remains to be fully elucidated. My finding that dual inhibition of the PIM kinases and mTORC1 results in decreased levels of

NAD+ may imply that the PIM kinases, in addition to their role in signaling upstream of mTORC1, may contribute to cellular energy status. Other studies have highlighted a role for these kinases in glycolysis and mitochondrial maintenance as well. However, the exact mechanism of PIM kinase effects on cellular energy status is poorly understood. Future studies are required to improve our understanding of the downstream effectors of these kinases, in order to understand the physiological implications of their control downstream of mTORC1.

While the PIM kinases have been historically treated as completely redundant, recent findings have implicated some divergence in targets between PIM1 and PIM2, and the targets of PIM3 are poorly

116 characterized. My results show that both PIM1 and PIM3 as repressed by mTORC1 activity via miR-33; however, PIM2 is not regulated in the same manner. It seems likely that divergent effectors may account for the difference in regulation between PIM1/3 and PIM2. Future studies will be needed to determine the extent of overlap and divergence in the targets of PIM1, 2, and 3, and what the functional implications of their convergent and divergent targets are in different settings.

Additionally, the finding that miR-33 is activated by mTORC1 highlights the need for further studies defining specific miRNA targets influenced by the greater mTORC1 signaling network. Changes in single miRNAs or classes of miRNAs upon targeted inhibitor treatment may be having unexpected effects on various transcriptional targets, as shown by the alteration in PIM3 and PIM1 expression upon rapamycin treatment. It is possible that inhibition or activation of specific miRNAs in combination with mTOR inhibitors may increase the efficacy of mTOR-targeted therapies by effecting the entire class of miR-targeted genes with a single intervention. Whether this type of combinatorial treatment would be effective remains to be seen.

My results in MEFs showed that combined pan-PIM inhibitors plus rapamycin treatment increased cell death and slowed proliferation, while there was no additive affect in U87MG glioblastoma cells. However, the efficacy of combined PIM and mTOR inhibitors shown by other groups indicates that there may be some promise in pursuing this combination, perhaps with the more potent mTOR-kinase inhibitors. Future studies using 3D culture and mouse models, which will more faithfully recapitulate the tumor environment, will be required to determine the true efficacy of PIM inhibitors in combination with mTOR inhibitors.

This dissertation has established that the proto-oncogenes PIM3 and PIM1 are induced by rapamycin treatment in mTORC1-driven settings, and that this is mediated by miR-33 activation downstream of mTORC1 and SREBP. This improves our understanding of intrinsic survival mechanisms in the mTORC1 signaling network, with the hope that these findings and the future studies proposed herein will lead to the development of more effective therapies to treat cancer and the many other diseases characterized by dysregulation of the mTORC1 signaling network.

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