Novel Biological Insights and Therapeutic Approaches in High-Risk Acute Myeloid Leukemia

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Houda Alachkar, PharmD

Graduate Program in Integrated Biomedical Sciences

The Ohio State University

2012

Dissertation Committee:

Guido Marcucci, MD Advisor

Michael Caligiuri, MD

Danillo Perrotti, PhD

Lai-Chu Wu, PhD

Houda Alachkar

2012

Abstract

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy characterized by clonal proliferation of myeloid progenitors with a reduced ability to differentiate into more mature functional blood cells. Consequently, an accumulation of leukemic cells (blasts) in bone marrow and blood occurs and leads to hematopoietic failure. Even with recent progress in understanding the biologic and genetic changes that underlie the disease, most patients with AML fail to achieve long-term survival. This highlights the need for novel therapeutic strategies that would improve outcome.

Cytogenetic aberrations have long been shown to be the most important risk factor for predicting outcome in AML and have therefore been used to guide treatment. However, each cytogenetic risk group presents with molecular heterogeneity, which may explain different outcome among patients with similar chromosome aberrations. Cytogenetically normal AML (CN-AML) is the largest cytogenetic group (45% of AML) and the best molecularly characterized among both younger and older AML patients. Frequent genetic mutations with prognostic significance have been identified in CN-AML. Patients with FLT3 internal tandem duplication (ITD) or IDH2-R172 have been shown to have worse outcome, while patients with CEBPA or NPM1 mutations are commonly reported to have more favorable prognosis. The cytogenetic and molecular aberrations associated with AML influence the expression of downstream target genes that encode proteins involved in complex biologic networks supporting leukemogenesis. Therefore, microarray genome-wide gene-expression profiling and microRNA-expression profiling assays provide molecular insight into the underlying biology of the different disease ii subsets, offer diagnostic and prognostic information, and potentially reveal novel therapeutic targets.

The research we are presenting in the following chapters has two major aims. Aim 1: identify novel therapeutic targets and prognostic markers employing genome-wide analyses of gene expression signatures in high risk AML patients. Aim 2: investigate novel therapeutic approaches directed toward previously identified molecular targets in high risk disease. In chapter #2 we identified SPARC as a novel molecular and therapeutic target in AML. We demonstrated a functional, mechanistic and clinical implication of SPARC in AML, revealing that high SPARC expression promoted growth advantage in vitro, aggressive disease in vivo, and worse outcome in CN-AML patients.

SPARC acts likely via activation of ILK/AKT/-catenin pathways. We also identified

RUNX1 and IDH2-R172 mutations as an upstream upregulators of SPARC expression likely via NFκb/SP1 complex mediating mechanisms. In chapter #3 we investigated the preclinical and pharmacological activity of the natural initiation of translation inhibitor, silvestrol in FLT3-ITD positive AML denoting a large proportion of high risk AML patients.

We demonstrated that silvestrol had a potent in vitro and in vivo anti-leukemia activity in

FLT3-ITD and FLT3 overexpressing AML cells. Silvestrol inhibited FLT3 mRNA translation resulting in FLT3 protein down-regulation and in turn inhibition of aberrant tyrosine kinase activity.

In conclusion, we identified an original molecular target with novel biological insights, and investigated innovative therapeutic approaches suitable for high risk subsets of

AML. This research will significantly advance understanding of AML and open new avenues of treatment strategies, which will result in optimized patient care, and improved clinical outcome.

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This thesis is dedicated to

The great people of Syria who are dying for their freedom, you were my inspiration

My loving Mother who devoted her life for our education, you were always in my heart

My amazing family father sisters and brothers Bassem, Wafa, Hana, Nada, Amal, Malack, Mustafa, and Murhaf You were always with me

My beloved husband Irshad You were my best friend and companion

Acknowledgments

I am above all deeply grateful to my advisor, Dr. Guido Marcucci, for his support, mentorship, guidance, patience, and encouragement. It is because of his instructions and guidance that I have been able to complete this work.

I would like to thank my committee members, Drs. Michael Caligiuri, Danillo Perrotti and

Lai-Chu Wu, for offering insightful comments and kind advice regarding my research and my progress. I would like to acknowledge Dr. Bloomfield for her overall support for this project, as without her help and support much of this work would not have been possible. I would like to thank Dr. Wolfgang Sadee for offering me a research opportunity in his lab. It was his directions and advices that guided me through setting up my professional goals to further my career as a research scientist.

I would like to acknowledge the current and former members of Dr. Marcucci‘s lab, specifically, John Curfman for trying his best maintaining all aspects of the lab and keeping everyone happy. I thank Chris Hickey for being a good listener and for his great help with the ChIP experiments. I greatly appreciate Ramasamy Santhanam for his assistance with in vivo experiments and Yue-Zhong Wu for his technical help with cloning and for very interesting political discussions.

I also like to thank all my friends for their help and support particularly Sana and Barraha for being always with me.

Vita

2001 ...... B.S. Pharmacy, Aleppo University, Syria

2005 ...... M.S. Pharmacology&Toxicology, Wright

State University, OH, US

2011 ...... PharmD. Ohio Northern University, OH, US

2008 to present ...... Graduate Research Associate, Integrated

Biomedical Graduate Program, The Ohio

State University, OH, US

Publications

1- Hickey CJ, Schwind S, Radomska HS, Dorrance AM, Santhanam R, Mishra A,

Wu YZ, Alachkar H, Maharry K, Nicolet D, Mrózek K, Walker A, Eiring AM, Whitman

SP, Becker H, Perrotti D, Wu LC, Zhao X, Fehniger TA, Vij R, Byrd JC, Blum W, Lee LJ,

Caligiuri MA, Bloomfield CD, Garzon R, Marcucci G. Lenalidomide-mediated enhanced translation of C/EBPα-p30 protein upregulates expression of the anti-leukemic microRNA-181a in acute myeloid leukemia. Blood. 2012 Oct 25. PMID:23100311

2- Alachkar H, Xie Z, Marcucci G, Chan KK. Determination of cellular uptake and intracellular levels of Cenersen (Aezea(®), EL625), a p53 antisense oligonucleotide in acute myeloid leukemia cells. J Pharm Biomed Anal. 2012 Dec;71:228-32. doi:

10.1016/j.jpba.2012.08.011. Epub 2012 Aug 19.PMID:22944355

3- Smith RM, Alachkar H, Papp AC, Wang D, Mash DC, Wang JC, Bierut LJ,

Sadee W. Nicotinic α5 receptor subunit mRNA expression is associated with distant 5' upstream polymorphisms. Eur J Hum Genet. 2011 Jan;19(1):76-83. Epub 2010 Aug

11.PMID:20700147

4- Alachkar H, Kataki M, Scharre DW, Papp A, Sadee W. Allelic mRNA expression of sortilin-1 (SORL1) mRNA in Alzheimer's autopsy brain 4-tissues. Neurosci Lett. 2008

Dec 19;448(1):120-4. Epub 2008 Oct 15.PMID:18938222

5- Frasch HF, Barbero AM, Alachkar H, McDougal JN. Skin penetration and lag times of neat and aqueous diethyl phthalate, 1,2-dichloroethane and naphthalene. Cutan

Ocul Toxicol. 2007;26(2):147-60. PMID:17612981

Fields of Study

Major Field: Integrated Biomedical Science Program

Area of Research Emphasis: Molecular Pharmacology, Pharmacogenomics and

Therapeutics

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Table of Contents

Chapter 1 : Background ...... 1

1.1 Definition, etiology, diagnosis and classification ...... 1

1.2 Clinical Presentation ...... 5

1.3 Risk Stratification and prognosis ...... 5

1.2 AML Treatment ...... 10

1.4 Molecular signatures in AML ...... 12

Chapter 2 : SPARC Contributes to Leukemia Growth and Aggressive Disease in Acute

Myeloid Leukemia ...... 15

2.1 Introduction ...... 15

2.1.1 SPARC gene and expression ...... 15

2.1.2 SPARC protein structure and functions ...... 15

2.1.3 SPARC signaling pathways ...... 18

2.1.4 SPARC and Cancer ...... 20

2.2 Experimental procedure ...... 22

2.3 Results ...... 28

2.3.1 SPARC is expressed in hematopoietic stem cells (HSCs) ...... 28

2.3.2 SPARC promotes leukemia growth ...... 30

2.3.3 SPARC overexpression negatively impacts clinical outcome in CN-AML ...37 viii

2.3.4 SPARC overexpression is associated with distinct gene and microRNA

expression signatures in CN-AML ...... 41

2.3.5 SPARC activates ILK/AKT/-catenin signaling pathways ...... 46

2.3.6 Distinct mutations in IDH2 and RUNX1 genes induce SPARC expression

likely via activation of NF-B/SP1 complex in CN-AML ...... 61

2.3.7 SPARC is a novel therapeutic target in AML ...... 70

2.4 Discussion ...... 73

Chapter 3 : Pharmacological Activity of Silvestrol in High-Risk Acute Myeloid Leukemia

...... 77

3.1 Introduction ...... 77

3.2 Materials and Methods ...... 80

3.3 Results ...... 85

3.3.1 Silvestrol antileukemia activity in FLT3-ITD and FLT3-wt expressing AML

cells…...... 85

3.3.2 Silvestrol downregulates FLT3 expression through inhibition of FLT3

translation initiation ...... 88

3.3.3 Silvestrol downregulates miR-155 expression in FLT3-ITD positive AML ...94

3.3.4 Activity of silvestrol in FLT3-ITD positive leukemia grafts ...... 98

3.4 Discussion ...... 101

Chapter 4 : Summary and Future Directions ...... 104

References ...... 114

List of Tables

Table 1.1 FAB classification of Acute Myeloid Leukemia ...... 4

Table 1.2 WHO classification of Acute Myeloid Leukemia ...... 4

Table 1.3 European LeukemiaNet Classification System for Correlation of Cytogenetic and Molecular Genetic Data in AML with Clinical Data ...... 8

Table 1.4 Recurrent Molecular Genetic Abnormalities in Adult AML and their Clinical

Significance ...... 9

Table 1.5 New agents directed at molecular and other specific targets in AML ...... 11

Table 2.1 Comparison of clinical and molecular characteristics of Low vs. High SPARC all patients ...... 38

Table 2.2 miR expression profile associated with SPARC expression in older patients .44

Table 2.3 miR expression profile associated with SPARC expression in younger patients

...... 45

Table 2.4 List of patient samples used in in vitro experiments ...... 60

Table 3.1 Calculated IC50 values for AML primary cells and cell lines ...... 88

List of Figures

Figure 1.1 The molecular heterogeneity of cytogenetically normal AML (modified from

(21) ...... 6

Figure 2.1 A schematic of SPARC protein structure and its multi-functional domains

(88) ...... 17

Figure 2.2 SPARC is expressed in hematopoitic stem cells/progenitors...... 29

Figure 2.3 SPARC promotes growth advantage in AML cell lines...... 31

Figure 2.4 SPARC promotes growth advantage in primary blasts...... 33

Figure 2.5 SPARC promotes aggressive disease in vivo...... 35

Figure 2.6 SPARC promotes aggressive disease in vivo...... 36

Figure 2.7 SPARC overexpression negatively impacts clinical outcome in younger CN-

AML patients...... 40

Figure 2.8 SPARC overexpression is associated with distinct gene expression signature in CN-AML...... 42

Figure 2.9 SPARC overexpression is associated with distinct microRNA expression signature in CN-AML...... 43

Figure 2.10 SPARC activates ILK/AKT/-catenin signaling pathways in THP-1 cells. ....48

Figure 2.11 SPARC enhances β-catenin nuclear translocation...... 50

Figure 2.12 SPARC activates TCF/LEF transcriptional activity and increase the expression of β-catenin target genes...... 52

Figure 2.13 SPARC activates ILK/AKT/-catenin signaling pathways in MV4-11 cells. ..53

Figure 2.14 SPARC promotes growth advantage via ILK activation...... 55 xi

Figure 2.15 SPARC activates ILK/AKT/-catenin signaling pathways in primary blasts. 57

Figure 2.16 SPARC knock-down decreases β-catenin protein level in primary blasts. ...58

Figure 2.17 SPARC increases P--catenin(Ser675) in primary blasts...... 59

Figure 2.18 SPARC expression in CN-AML patients according to their IDH1 and IDH2 mutational status...... 62

Figure 2.19 SPARC expression in CN-AML patients according to their RUNX1 mutational status...... 64

Figure 2.20 Mutations in IDH2 and RUNX1 genes induce SPARC expression...... 65

Figure 2.21 SPARC expression is regulated by NF-B, SP1, and RUNX1 transcription factors...... 67

Figure 2.22 IDH2-R172 and RUNX1 contribute individually to SPARC overexpression through NF-κB and SP1 mediating mechanisms...... 69

Figure 2.23 Bortezomib inhibits SPARC expression...... 72

Figure 3.1 Antileukemic activity of silvestrol in vitro...... 86

Figure 3.2 Silvestrol induces apoptosis in primary blasts in vitro...... 87

Figure 3.3 Silvestrol down-regulates FLT3 protein expression...... 91

Figure 3.4 Silvestrol affects FLT3 mRNA expression differently in FLT3-wt and FLT3-ITD

AML cells...... 92

Figure 3.5 Silvestrol down-regulates FLT3 mRNA expression in THP-1 cells in the presence of FLT3 ligand...... 93

Figure 3.6 Silvestrol down-regulates miR-155 and upregulates miR-155 target PU1. ....96

Figure 3.7 In vivo antileukemic activity of silvestrol in FLT3-ITD positive MV4-11 xenograft leukemia mouse model...... 100

xii

Figure 4.1 SPARC upregulates c-Myc and CyclinD1 mRNA expression in CD34+ cells isolated from cord blood cells...... 108

Figure 4.2 In vitro and In vivo antileukemic activity of silvestrol in KIT mutant AML. .... 112

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Chapter 1 : Background

Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is one of the most common and deadly form of acute leukemia among adults in the United States (1). According to Surveillance

Epidemiology and End Results (SEER), based on cases between 2005 and 2009 the age-adjusted incidence rate and the age-adjusted death rate were 3.6 and 2.8 per

100,000 men and women per year, respectively (2). It is estimated that approximately

13,780 new case of AML will be diagnosed, and 10,200 patients will die of the disease in

2012 (3). The incidence of AML is rising as the population ages. The median age at diagnosis is 67 years, with 54% of patients diagnosed at 65 years or older and at least

33% at 75 years of age (1).

1.1 Definition, etiology, diagnosis and classification

AML is a heterogeneous hematologic malignancy characterized by clonal proliferation and block of differentiation of myeloid precursors, the so-called blasts.

Consequently, an accumulation of leukemic cells (blasts) in bone marrow (BM) and

1 blood occurs and leads to hematopoietic failure (4). If left untreated, patients with AML die of infection, bleeding and organ failure within few weeks.

Although the etiology of AML is still mostly unknown, the risks for developing the disease have been attributed to several environmental and hereditary factors.

Prolonged exposure to petrochemicals; solvents such as benzene, petroleum, pesticides, herbicides and tobacco smoking were found to increase risk for developing

AML(5, 6). Ionizing radiation from warfare, occupational, or therapeutic exposure was also found to increase disease incidence (1, 7). Additionally, up to 10% of patients receiving cytotoxic therapy for solid tumors or hematologic malignancies such as alkylating agents and topoisomerase II inhibitors develop AML within one to six years after exposure. Recent studies suggest that therapy-related AML may account for 5% to

20% of patients with AML (8-10). Heredity related risk factors for developing AML include constitutional chromosome aneuploidies such as +21 in Down and XXY in

Klinefelter syndromes, and inherited diseases with excessive chromatin fragility, e.g.,

Bloom syndrome, ataxia telangiectasia neurofibromatosis and Schwachman-Diamond syndrome, Faconi anemia and Kostmann syndrome (11). Additional hereditary risk factors are germline mutations of the CEBPA and RUNX1 genes (12).

According to the World Health Organization (WHO) classification, the term

―myeloid‖ includes cells of granulocytic (neutrophil, eosinophil, basophil), monocytic/macrophage, erythroid, megakaryocytic and mast cell lineages (13). In this system, a myeloid neoplasm with 20% or more blasts in the PB or BM is considered to be AML (13). However, in some cases associated with specific cytogenetic aberrations include t(8;21)(q22;q22); inv(16) (p13;1q22) or t(16;16)(p13.1;q22); and t(15;17)

(q22;q12) [APL subtype], the diagnosis of AML may be made regardless of the 20% cut off blast count in the PB or BM. Therefore, the 20% blast threshold is not required to treat the patient as having AML (13).

Historically, AML was classified according to the French-American-British (FAB) system based on morphologic and cytochemical criteria (Table 1.1) (14). More recently, the WHO system based more on cytogenetic and molecular markers with biological and clinical impact has been adopted (Table 1.2). Previously, abnormalities included in the classification were mainly chromosomal translocations involving transcription factors and associated with characteristic clinical, morphologic and immunophenotypic features.

However, experimental evidences leading to advance understanding of leukemogenesis suggest that myeloid differentiation resulting from chromosomal rearrangements involving transcription factors require a second genetic abnormality to promote proliferation of the leukemic clone (15). Incorporating this rationale, at least two classes of mutations in AML pathogenesis are recognized. Class I mutations involve mutations that encode proteins that activate signal transduction pathways to promote proliferation and/or survival advantage. Class II mutations involve mutations that impair hematopoietic differentiation and subsequent apoptosis (15). Since the WHO system has been frequently revised to include the most recent discoveries and updates in the field; it provides more meaningful prognostic information than the FAB system and therefore is considered the more clinically useful classification system (16).

Table 1.1 FAB classification of Acute Myeloid Leukemia

FAB Name % of adult AML subtype patients M0 Undifferentiated acute myeloblastic leukemia 5% M1 Acute myeloblastic leukemia with minimal 15% maturation M2 Acute myeloblastic leukemia with maturation 25% M3 Acute promyelocytic leukemia (APL) 10% M4 Acute myelomonocytic leukemia 20% M4 eos Acute myelomonocytic leukemia with 5% eosinophilia M5 Acute monocytic leukemia 10% M6 Acute erythroid leukemia 5% M7 Acute megakaryoblastic leukemia 5%

Table 1.2 WHO classification of Acute Myeloid Leukemia

Acute myeloid leukemia and related neoplasms Acute myeloid leukemia with recurrent genetic abnormalities AML with t(8;21)(q22;q22); RUNX1-RUNX1T1 AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 APL with t(15;17)(q22;q12); PML-RARA AML with t(9;11)(p22;q23); MLLT3-MLL AML with t(6;9)(p23;q34); DEK-NUP214 AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1 AML (megakaryoblastic) with t(1;22)(p13;q13); RBM15-MKL1 Provisional entity: AML with mutated NPM1 Provisional entity: AML with mutated CEBPA Acute myeloid leukemia with myelodysplasia-related changes Therapy-related myeloid neoplasms Acute myeloid leukemia, not otherwise specified AML with minimal differentiation AML without maturation AML with maturation Acute myelomonocytic leukemia Acute monoblastic/monocytic leukemia Acute erythroid leukemia Pure erythroid leukemia Erythroleukemia, erythroid/myeloid Acute megakaryoblastic leukemia Acute basophilic leukemia Acute panmyelosis with myelofibrosis

1.2 Clinical Presentation

Nearly 50% of patients report fatigue, weakness, anorexia and weight loss at the time of diagnosis. Other signs and symptoms at diagnosis include: fever with or without an identifiable infection, and abnormal hemostasis (bleeding and bruising) due to neutopenia and thrombocytopenia, respectively. Occasionally, patients complain of bone pain, cough, headache and diaphoresis. Symptomatic mass lesions in soft tissues, cranial or spinal dura may rarely be present at the time of diagnosis (1, 7).

1.3 Risk Stratification and prognosis

Cytogenetic aberrations have long been the most important prognostic factor for predicting remission rates, relapse risks, and overall survival (OS) outcomes (1). AML associated with t(8;21), t(15;17) or inv(16) predicted a relatively favorable outcome (5- year survival rates are 55-65%). Whereas in patients lacking these favorable changes, the presence of a complex karyotype, -5, del(5q), -7, or abnormalities of 3q defined a group with relatively poor prognosis (5-year survival rates are 5-14%). The remaining group of patients including those with 11q23 abnormalities, +8, +21, +11, del(9q), del(7q) or other miscellaneous structural or numerical defects not included in the favorable or adverse risk groups were found to have an intermediate prognosis (5-year survival rates are 24-41%) (17) .

The intermediate-risk cytogenetic category is the most heterogeneous group in

AML, because it includes both normal karyotype without cytogenetic abnormalities and those with cytogenetic abnormalities that are considered neither poor-risk nor favorable.

Cytogenetically normal AML (CN-AML) is the largest cytogenetic group (45% of AML) and the best molecularly characterized among both younger and older AML patients (18)

(19, 20). However this group is also very molecularly and clinically heterogeneous

(Figure1.1) [modified from (21), recently discovered mutations in AML are not included].

Figure 1.1 The molecular heterogeneity of cytogenetically normal AML (modified from (21)

Frequent mutations in genes have been identified to possess important prognostic values in AML (22). Mutations in FLT3 encoding a receptor tyrosine kinase involved in hematopoiesis such as FLT3-ITD are found in approximately 30% to 40% of

CN-AML cases, and are associated with a poor outcome. Survival rate for this subset is

20% to 25% at 4 years when only the FLT3-ITD status is considered (22-26).

NPM1, encoding a shuttling protein in the nucleolus, is found to be mutated in

50% to 60% of CN-AML cases, and when only the NPM1 mutation status is considered, it is reported to be associated with better outcome, approximately 50% survival at 4 years (18, 27-29). Mutations of CEBPA gene encodes for CCAAT/enhancer binding protein alpha (C/EBPα), a transcription factor are found in approximately 15% of CN-

AML cases and these patients also have favorable outcome with approximately 60% 4- year survival rate (30, 31). The prognostic impacts of mutations in the IDH1 (8%-16% of

CN-AML patients) and IDH2 (19% of CN-AML) encoding the isocitrate dehydrogenase 1 and 2 have been inconsistent (32-38). Mutations of DNMT3A, which encode for DNA methyltransferase 3A have been reported in 29% to 34% in CN-AML, with R882 is the most commonly mutated residue. Data concerning the prognostic significance of

DNMT3A mutations have also been conflicting (39-42).

From the 2008 revision of the WHO classification of myeloid neoplasms and acute leukemia, an international expert panel working on behalf of the European

LeukemiaNet (ELN) constructed a new stratification system for reporting cytogenetic and selected molecular abnormalities in studies correlating genetic findings with treatment outcome in AML. The novel aspect of the ELN classification is that it divides patients

7 with CN-AML into genetic groups according to molecular alterations recognized in the

WHO classification, specifically NPM1, CEBPA, and FLT3 mutations (Table 1.3).

Table 1.3 European LeukemiaNet Classification System for Correlation of Cytogenetic and Molecular Genetic Data in AML with Clinical Data

Genetic Group Subsets Favorable t(8;21)(q22;q22); RUNX1-RUNX1T1 inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 Mutated NPM1 without FLT3-ITD (normal karyotype) Mutated CEBPA (normal karyotype) Intermediate-I Mutated NPM1 and FLT3-ITD (normal karyotype) Wild-type NPM1 and FLT3-ITD (normal karyotype) Wild-type NPM1 without FLT3- ITD (normal karyotype) Intermediate-II t(9;11)(p22;q23); MLLT3-MLL Cytogenetic abnormalities not classified as favorable or adverse Adverse inv(3)(q21q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1 t(6;9)(p23;q34); DEK-NUP214 t(v;11)(v;q23); MLL rearranged –5 or del(5q) –7 abnl(17p) Complex karyotype

In addition to structural genetic aberrations, changes in expression of specific genes seem to impact prognosis of molecular subsets of patients with AML. Higher

BAALC (brain and acute leukemia, cytoplasmic) gene expression levels predicted lower

CR rates as well as inferior disease-free and overall survival (OS). MN1 (meningioma 1) overexpression is also associated with poor response to induction chemotherapy and higher relapse rate and worse OS in AML. ERG (v-ets erythroblastosis virus E26 oncogene homolog, avian) overexpression was observed in AML with complex aberrant karyotypes and the adverse prognostic significance of high blood ERG levels was established in CN-AML.

Recently, microRNA, short RNAs that bind to their complementary sequences on

8 target mRNA resulting in their translation inhibition or mRNA degradation, expression was also found to affect clinical outcome in AML. Low expression levels of let7b and miR-9 were detected in patients classified in the favorable-risk group, while higher expression levels of these microRNAs were found in patients with adverse- or intermediate-risk cytogenetic groups. Also, high level of miR-181a was correlated with favorable outcome in CN-AML. A list of molecular genetic abnormalities that impact clinical outcome are presented in Table 1.4.

Table 1.4 Recurrent Molecular Genetic Abnormalities in Adult AML and their Clinical Significance

Mutation Prognostic relevance KIT Unfavorable FLT3-ITD Unfavorable FLT3-TKD Controversial CEBPA Favorable NPM1 Favorable MLL-PTD Unfavorable RAS Controversial WT1 Controversial RUNX1 Unfavorable IDH1/IDH2 Unfavorable DNMT3A Unfavorable ASXL Unfavorable TET2 Unfavorable TP53 Unfavorable JAK2 Unfavorable

Gene Overexpression Prognostic relevance BAALC Unfavorable ERG Unfavorable MN1 Unfavorable EVI1 Unfavorable miRs Overexpression Prognostic relevance miR-181a Favorable

1.2 AML Treatment

Treatment of AML includes induction chemotherapy and post-remission (or consolidation) therapy. The induction therapy aims to achieve complete remission (CR), by reducing the leukemic burden and restoring the normal hematopoiesis. It is decided after considering individual patient characteristics such as age, co-morbidities, performance status, and preexisting myelodysplasia and likely initiated before karyotype and molecular markers information become available (1). Standard induction regimens are based on a backbone of cytarabine and an anthracycline. These regimens are appropriate for patients younger than age 60 years and for older patients with intact functional status, minimal co-morbidity, and favorable cytogenetic or molecular mutations. Another option for older patients who are medically fit is the purine nucleoside analogue clofarabine, epigenetic agents, including hypomethylating drugs such as 5- azacytadine and decitabine, alone or in combination with histone deacetylase inhibitors

(1).

Consolidation therapy aims to maintain CR, prolong survival and achieve complete cure. Most patients who do not receive post-remission therapy will experience relapse, usually within 6 to 9 months. A bone marrow aspirate and biopsy should be performed 7 to 10 days after completion of induction therapy to determine the efficacy of the induction therapy. Additional therapy with standard-dose cytarabine and anthracycline or escalation to high-dose cytarabine with or without an anthracycline is the most common consolidation treatment (1). Patients who fail the induction therapy

10 and additional high-dose cytarabine or patients with high risk AML (such as FLT3-ITD) should be considered for allogeneic HSCT with matched donor, a clinical trial, or best supportive care (1).

Recent progress made in understanding the pathophysiology of AML has helped advancing targeted therapy developments, a summary of some of these therapeutic strategies are listed in (Table1.5) (4, 43).

Table 1.5 New agents directed at molecular and other specific targets in AML

New agents Targets Farnesyltransferase inhibitor Farnesylation of lamin A and HJJ-2 FLT3 tyrosine kinase Internal tandem duplications of inhibitors: FLT3 PKC-412, MLN518, CEP701. MDR modulators: P-glycoprotein and other cyclosporine, PSC833, multidrug resistance proteins zosuquidar Histone deacetylase Histone deacetylase inhibitors: phenylbutyrate, depsipeptide Proteosome inhibitor Bortezomib DNA demethylating agents DNMTs 5-Azacytidine, Decitabine Clofarabine Ribonucleotide reductase BCL-2 antisense BCL-2 protein deoxynucleotide Antiangiogenic agents Vascular endothelial growth factor

1.4 Molecular signatures in AML

The cytogenetic and molecular aberrations associated with AML influence the expression of downstream target genes that encode proteins involved in complex biologic networks supporting leukemogenesis. Therefore, microarray genome-wide gene-expression profiling and microRNA-expression profiling assays may provide molecular insight into the underlying biology of the different disease subsets, offer diagnostic and prognostic information, and potentially reveal novel therapeutic targets.

Indeed, several gene and microRNA expression profiles have been reported in AML, and some of which have resulted in revealing new molecular targets in AML (44).

Gene expression signature associated with CEBPA mutations in a high-risk molecular group of CN-AML, (patients with wild-type NPM1 genes with or without FLT3-

ITD or those with NPM1 mutation and FLT3–ITD) showed upregulation of genes involved in erythroid differentiation (e.g. GATA1, ZFPM1) (44). In contrast, genes involved in myeloid differentiation (e.g. RUNX1, SPI1, ID1) and genes belong to the homeobox family were downregulated in patients with CEBPA mutations (45).

MicroRNA expression signatures have also been associated with distinct molecular aberrations in AML. For example microRNA expression signature associated with FLT3 -ITD revealed the upregulation of miR-155 (46-48). Sustained expression of miR-155 was shown to cause granulocyte/monocyte expansion and result in pathological features of myeloid neoplasia in a mouse model (49). Gene and microRNA expression signatures associated with NPM1 mutations include the upregulation of the

HOX genes and miRs that reside in the genomic cluster of HOX genes such as miR-10a, miR-10b and miR-196a (48, 50). In addition, among the downregulated microRNAs in

12 the NPM1- associated microRNA signature, were miR-204 and miR-128, which are also predicted to target HOX genes (48).

Thus far, it became clear that AML is very heterogeneous disease, and responses of AML patients to chemotherapy range from days to cure. This heterogeneity in patients clinical outcomes is mere manifestation of the underneath diversity of the molecular and cytogenetic aberrations. Unfortunately, and despite our expanded understanding of the clinical and biological heterogeneity of this disease in the last decade, the treatment remained the same and one for all. This suggests that further research is highly needed to understand the molecular and biological pathways involved in leukemogenesis in order to improve the dismal outcome of high risk subset of AML patients.

The research we are presenting in the following chapters is divided into two major aims, our first aim is to identify novel therapeutic targets and prognostic markers employing previously identified genome-wide analyses of gene expression signatures in high risk

AML patients. Our second aim is to investigate novel therapeutic approaches directed toward previously identified molecular targets in high risk disease.

In chapter #2 we identified SPARC as a novel molecular and therapeutic target in AML.

We demonstrated a functional, mechanistic and clinical implication of SPARC in AML, revealing that high SPARC expression promoted growth advantage in vitro, aggressive disease in vivo, and worse outcome in CN-AML patients. SPARC acts likely via activation of ILK/AKT/-catenin pathways.

In chapter #3 we investigated the preclinical and pharmacological activity of the natural initiation of translation inhibitor, silvestrol in FLT3-ITD positive AML representing

13 a large proportion of high risk AML patients. We demonstrated that silvestrol had a potent in vitro and in vivo anti-leukemia activity in FLT3-ITD and FLT3 overexpressing

AML cells. Silvestrol inhibited FLT3 mRNA translation resulting in FLT3 protein downregulation and in turn inhibition of aberrant tyrosine kinase activity.

Chapter 2 : SPARC Contributes to Leukemia Growth and Aggressive Disease in

Acute Myeloid Leukemia

2.1 Introduction

2.1.1 SPARC gene and expression

The Secreted Protein Acidic and Rich in Cysteine (SPARC) gene is highly conserved in vertebrates, localizes on human chromosome 5q31–q33 (51) and lacks the canonical CAAT and TATA box sequences in its promoter region. The SPARC gene encodes a 32 kDa secreted matricellular calcium binding glycoprotein also known as osteonectin or BM-40 (52-54). SPARC expression is elevated during development and tissue differentiation and declines following maturation (55). Post-development the expression of SPARC is limited to tissues with high extracellular matrix (ECM) turnover, such as bone and gut epithelia (55). SPARC is also induced during wound-healing, angiogenesis, and by the stromal cells during tumorigenesis (56-59)

2.1.2 SPARC protein structure and functions

Human SPARC protein consists of 303 amino acids (54), 17 amino acids that makes a signal peptide is removed during processing leaving a mature protein of

SPARC that consists of three individual structural domains (60) (Figure 2.1). the three 15 domains are: 1- An N-terminal domain, which consists of 52 amino acids (Ala1-Glu52), is highly acidic, binds calcium with low affinity, inhibits cell spreading, enhances plasminogen activator inhibitor-1(PAI-1) and decreases fibronectin (FN) and thrombospondin-1 (TSP-1). 2- FS-like domain which is 85 amino acids (Asn53-Pro137) located between the N-terminus domain sequence and EC-binding domain, and contains

10 cysteine residues and several internal disulfide bonds. This domain promotes angiogenesis and proliferation and block focal adhesions (53). Cationic region 1 (Amino acids 54–73) of this domain has been shown to inhibit the proliferation of endothelial cells, while cationic region 2 (amino acids 113–130) stimulates DNA synthesis. 3- EC- binding domain (extracellular calcium-binding domain) which comprises 149 amino acid residues (Cys138-Ile286), and consists of two EF-hand motifs that bind to calcium with high affinity. This domain induces matrix metalloproteinases (MMPs), regulates the interactions between cells and matrix, and inhibits cell spreading, proliferation, and adhesion (61, 62). SPARC is post-translationally modified by N-linked glycosylation.

Phosphorylation modification has been also reported in bone osteonectin, however the role of this modification in the function of SPARC is unclear (63).

Figure 2.1 A schematic of SPARC protein structure and its multi-functional domains (88)

Matrix metalloproteinases (MMP-2, -3, -7 and -13, plasmin and trypsin) cleave

SPARC producing KGHK-containing fragment that can stimulate angiogenesis (64). The presence of truncated form of SPARC protein has been recently reported in hepatocellular carcinoma (HCC) samples and esophageal carcinoma (65, 66).

The phenotype of SPARC-null mice shows characteristics of ECM disruption, including early cataract formation, accelerated dermal wound-healing, osteopenia and a

17 curly tail (55, 67-69). SPARC-null mice also show deficiencies in connective tissue, such as decreased levels of collagen I in skin, adipose, heart and bone (70-72).

2.1.3 SPARC signaling pathways

Although cell surface receptors have not been identified for SPARC yet.; several reports have suggested that stabilin-1 and integrins may mediate the intracellular effects of SPARC. Stabilin-1 was found using a phage display as a cellular receptor interacts with SPARC through the extracellular epidermal growth factor (EGF)-like domain resulting in internalization and delivery of SPARC to the endocytic pathway and its targeting to lysosomes. SiRNA knock-down of Stabilin-1 reduces SPARC expression, while elevated SPARC level is observed in stabilin-1 over-expressing cells (73).

Integrins connect cells to the ECM, signal in response to ECM (―outside-in‖ signaling) and regulate the interactions of the ECM in response to intracellular cues

(‗inside-out‘ signaling) (74). Integrins contribute to tumor growth and metastasis via interacting and clustering directly with growth factor receptor to control cell survival, proliferation, adhesion and migration. In addition, integrin activation and signaling are required for proper cell response to cytokine (75-79).

Several studies reported that SPARC binds integrins β1, β3, αv, and β5 and regulates integrin interaction with the ECM. In addition, many studies suggest that

SPARC influences downstream components of integrin signaling, specifically the activation of integrin linked kinase (ILK) (80). SPARC was recently found to bind integrin

β1 with its copper-binding domain; thereby, directly enhancing integrin/ILK signaling (81,

82). SPARC also promotes cell survival of lens epithelial cells following serum starvation by enhancing ILK activation (82). SPARC-intergin/ILK interaction is also observed in several cancer cell lines. SPARC increased survival and induced an invasive phenotype in human glioma cells (83-85). In addition, targeting SPARC with short-hairpin RNA decreased the activity of ILK, focal adhesion kinase (FAK) and protein kinase B (Akt) resulting in decrease of cell survival and invasion (85). Forced SPARC expression resulted in increase ILK expression in glioma cells (86). In human ovarian cancer cells,

SPARC reduced the surface localization and/or clustering of αv, β1, β3 and β5 integrins resulting in inhibition of adhesion, invasion and proliferation (87).

SPARC protein regulates cell–matrix interactions and tissue remodeling through binding directly to collagen and other ECM proteins, and activating MMPs (88). It also interacts with and regulates several growth factors such as transforming growth factor β

(TGFβ), fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF) (89-92).

SPARC does not bind bFGF directly, but it inhibits bFGF-induced migration of endothelial cells (90, 92-95). SPARC binds PDGF and results in dose-dependent inhibition of ligand binding and activation of PDGF receptors on human dermal fibroblasts (92). Similarly, SPARC binds VEGF directly and inhibits VEGFR1 activation and VEGF- induced proliferation of microvascular endothelial cells (90, 96). On the other hand, VEGF induces the expression of SPARC in human vascular endothelial cells (97).

SPARC is also implicated in the regulation of TGFβ (89, 95). TGFβ is a master regulator of wound-healing and fibrosis by inducing the synthesis of several ECM proteins including collagen and fibronectin (98). Several studies demonstrate that TGFβ induces

SPARC expression (99-102). SPARC was also reported to regulate the expression and

19 activity of TGFβ (103) suggesting that there is a reciprocal regulatory feedback loop between SPARC and TGFβ.

The interaction of SPARC with several signaling pathways and different growth factors that have a dichotomous effect in cancer progression such as TGFβ (104) influences and explains the apparently paradoxical role of SPARC in cancer.

2.1.4 SPARC and Cancer

The functions of SPARC in regulating ECM deposition, cell-ECM interaction and growth factor signaling suggested to researchers a possible contribution of this protein in several hallmarks of cancer including angiogenesis, migration, proliferation and survival

(52, 58, 105). In line with this observation, altered SPARC expression was reported in several malignancies. However, inconsistency and often contradiction, even among the same tumor types were reported.

Conflicting reports have classified SPARC as either a tumor suppressor or an oncogene. The difficulty of assigning a specific role to SPARC may be related to the diversified roles that this protein plays in the tumor and microenvironment cells of distinct types of cancer (58). Low expression levels of SPARC have been found in ovarian cancer (106), colorectal (107, 108) , pancreatic (109); while high expression levels have been reported in breast cancer (110, 111) melanoma (112-114), and glioblastomas

(115). The association of SPARC expression levels with clinical outcome is also controversial. While stromal SPARC expression has been significantly associated with poor prognosis in non-small cell lung cancer (116) and with recurrence of ductal carcinoma in situ (117), absence of stromal SPARC independently predicted poor

20 prognosis in colon cancer (118). This controversial role of SPARC in cancer is likely related to the diversified functions of the protein in the microenvironment of distinct types of cancer. Suggesting that SPARC activity to promote or inhibit tumor progression is dependent on the initiating cell-type, the tumor stage, and the context of the tumor microenvironment.

In hematological malignancies, SPARC was found to be downregulated at diagnosis in patients with del(5) MDS and became upregulated post-treatment with lenalidomide (119-121). SPARC was also found downregulated in AML with MLL rearrangements and upregulated in t(8;21) and inv(16) acute myeloid leukemia (AML)

(122), although no correlation with outcome was reported in these molecular and cytogenetic subsets. Finally In chronic myelogenous leukemia (CML), the accumulation of intracellular SPARC was found to contribute to imatinib resistance (123).

Recently, we have observed that upregulated SPARC was comprised in gene expression profiles (GEPs) associated with distinct gene mutations [i.e., IDH2-R172

((34)] or aberrantly overexpressed genes [BAALC and ERG levels (124)] predicting poor outcome in cytogenetically normal (CN)-AML). In contrast, SPARC was found among the most downregulated genes in the GEP associated with NPM1 mutations, which predict favorable outcome in CN-AML (50). Therefore, we hypothesized that SPARC deregulation contributes to the level of disease aggressiveness and, when overexpressed, is associated with unfavorable prognosis in AML.

2.2 Experimental procedure

2.2.1 Cell lines and primary blasts

THP-1, MV4-11 and Kasumi-1 cells (ATCC, Manassas, VA) were cultured in

RPMI 1640 medium supplemented with 10-20% calf serum. HEK 293T cells (ATCC,

Manassas) were grown in DMEM medium supplemented with 10% calf serum. Patient

AML blasts were maintained in RPMI 1640 medium supplemented with 30% fetal bovine serum, 1% HEPES Buffer, and 1x StemSpan CC100 (Stemcell Technologies,

Vancouver, Canada) containing IL-3, IL-6, FLT3 ligand and SCF. All cells were incubated at 37ºC with 5% CO2. The AML blasts utilized in the experiments were obtained from apheresis blood samples collected from patients treated at the Ohio State

University (OSU) and stored in the OSU Leukemia Tissue Bank. Informed consent to use the tissue for investigational studies was obtained from each patient according to

OSU institutional guidelines.

2.2.2 Transient transfection, RNA interference and viral induction

THP-1, MV4-11 and Kasumi-1 cells and patient AML blasts were transfected with

1-2μg of pLenti-SPARC and pLenti-EV, pLenti-IDH1-wt, pLenti-IDH1-R132, pLenti-IDH2- wt, pLenti-IDH2-R172 or pCMV-RUNX1, pCMV-EV, pCMV-P65, pSuper-SP1 and pSuper-EV;. For RNA interference, cells were transfected with 1.0 nmol (10µl) of

SPARC–siRNA, ILK-siRNA, RUNX1-siRNA, t(8,21)-siRNA, SP1-siRNA, P65-siRNA or off target-siRNA control (Dharmacon Inc., Lafayette, CO). Transient transfection was done utilizing the Nucleofector Kit (Amaxa Inc, Walkersville, MD) according to the

6 manufacturer‘s instructions. For viral inductions, approximately 2X10 cells were infected 22 with lentivirus containing the following vectors pLenti6.2/V5-DEST vectors: Empty vector,

SPARC, IDH1-WT, IDH2-WT, IDH1-R132 and IDH2-R172. After 48 hours, antibiotic selection with blasticidin was started for 10 days.

2.2.3 RNA extraction and Real-Time RT-PCR

Total RNA was extracted using Trizol reagent (Invitrogen). cDNA was synthesized using SuperScript III reagents (Invitrogen) and the TaqMan MicroRNA

Reverse Transcription Kit (Applied Biosystems, Foster City, CA) according to the manufacturer‘s instructions. Quantitative Real-Time RT-PCR for SPARC, c-MYC,

CyclinD1, IDH1, IDH2, P65, SP1, RUNX1, and 18S, expression was performed using commercially available TaqMan Gene Expression Assay primers and probes (Applied

Biosystems) and the 7900HT Fast Real-Time PCR System (Applied Biosystems). The comparative cycle threshold (CT) method was used to determine the expression levels normalized by the internal control 18S for gene expression.

2.2.4 Immunoprecipitation, Western Blot Analysis, Chromatin

Immunoprecipitation and Antibodies

Immunoprecipitation and western blot were performed as previously described

(125) utilizing the following antibodies: Actin (I-19) sc-1616 (Santa Cruz Biotechnology,

Santa Cruz, CA); SPARC-ab89218 (abcam, Cambridge, MA) and (Cell Signaling

Technology, Danvers, MA), GSK3, AKT, P-GSK3, P-AKT, p--catenin (Cell signaling), c-MYC (santa cruz), IDH1-3997S (Cell Signaling), IDH2-ab55271 (abcam), SP1 (Santa cruz), P65 (upstate), and RUNX1(Calbiochem, San Diego, CA). ChIP assays were performed using the EZ ChIP Assay Kit (Millipore) according to the manufacturer‘s

23 standard protocol. DNA was quantified using qRT-PCR with SYBR green incorporation

(Applied Biosystems). The antibodies used were: anti-RUNX1(abcam), SP1 and NF-

κB(p65) (Millipore, Billerica, MA). The primers specific for SPARC gene promoter are:

(F1: CGCAAAAAGAGGAGGAAAGA, R1: GAGACAGGCAACAGGAAACC, F2:

GGCTATGGGAGAAGGAGGAG, R2: GGGGGTCACACATACCTCAG, F3:

TGCCTTTGTGGCAAATACAA, R3: TTGTTCAGAGGGCAAGTGAG)

2.2.5 Immunofluorescent Staining, Cell Sorting, Flow Cytometry and

Confocal Microscopy

Cells were washed and stained with CD34, CD38, CD45RA and CD123 antibodies

(eBioscience), and sorted into the following populations: hematopoietic stem cells and multipotent progenitors (HSC&MPP) or CD34+/CD38-, common-myeloid progenitors

(CMP) or CD34+/CD45RA‐/CD123low and granulocyte/monocyte progenitors (GMP) or

CD34+/CD45RA+/CD123low. Analysis was performed using a BD Aria II cell sorter

Version 6.1.2 (BD Biosciences).

For intracellular flow and confocal microscopy analysis; cells (1×106) were washed twice with cold PBS, and then fixed in Cytofix/cytoperm buffer (500ul per 1 million of cells) (BD

Biosciences, Billerica, MA), by incubation for 20min on ice. Cells were then washed twice with 1ml of Perm/Wash buffer and blocked in 10% goat serum (diluted in PBS pH7.4) on shaker for 2hr. After washing twice with PBS, cells were resuspend in 100ul of

Perm/Wash buffer (1X) with the 1ul of β-catenin antibody (cell signaling) and c-MYC antibody (Santa-Cruz) and incubated overnight on shaker at 4C. After washing, the samples were incubated with fluorochrome conjugated secondary antibody for 2 hour at room temperature. Samples were analyzed by flow cytometry on a FACSCalibur 24 instrument. Nuclei were stained with 1ul of Drag5. 10ul of stained cells were pipetted to a slide, air-dried for 3min and coversliped. Samples were analyzed by confocal microscope (The Ohio State University Image facility).

2.2.5 Clonogenic, Viability and Growth Inhibition Analysis

3 Methylcellulose clonogenic assays were carried out by plating 1X10 of the different cell lines, 1-2X104 cells from primary blasts in 0.9% MethoCult (Stem Cell

Technologies). Colonies from cell lines and primary cells were scored 10 and 14 days later, respectively. For cells viability and growth inhibition, we utilized MTS assay Briefly,

5.0×104 cells were incubated in triplicate in a 96-well plate in the presence or absence of the indicated test samples in a final volume of 100 µl for 24, 48 and 72 hours at 37°C.

Thereafter, 20 μl MTS solution (Promega, Madison WI) was added to each well. After 4 hours incubation at 37°C, plates were shaken and the optical density at 490 nm was measured. Percent cell viability was calculated as cell viability of the experimental samples/cell viability of the control samples × 100. At least three independent experiments were performed.

2.2.6 Leukemogenesis in NOD/SCID gamma mice

Four to six-week-old NOD/SCID gamma (NSG) (The Jackson Laboratory, Bar

Harbor, ME) were intravenously injected through the tail vein with 1-5X106 cells of THP-1 or MV4-11 infected with pLenti-EV or pLenti-SPARC. Six to eight weeks after engraftment, cell-injected mice (n = 6) were euthanized, and spleens, livers, kidneys and sternum were isolated. Parts of the spleens were grounded, and the red blood cells were lysed to attain single MNCs utilized for immunoblotting and qRT-PCR assays. For

25 pathological examination, tissue sections from liver and spleen were fixed on formalin, embedded in paraffin blocks, and H&E stained. All animal studies were performed in accordance with OSU institutional guidelines for animal care and under approved protocols by the OSU Institutional Animal Care and Use Committee.

2.2.7 Patients

We studied pretreatment bone marrow and blood samples with ≥ 20% blasts from 363 patients (age 19 to 83 years) with de novo CN-AML. Cytogenetic analyses at diagnosis were confirmed by central karyotype review. To establish CN-AML, ≥ 20 metaphase cells from diagnostic bone marrow had to be analyzed and the karyotype had to be normal, Institutional review board–approved informed consent for participation in the studies was obtained from all patients. Younger patients (age < 60 years; n = 153) were treated on CALGB 9621 and 19808 protocols and older patients (age ≥ 60 years; n

= 210) were enrolled on protocols 8525, 8923, 9420 9720, or 10201. No patient included in our analysis received allogeneic transplantation in first complete remission (CR). The median follow-up for younger and older patients alive and included in this analysis was

7.0 and 3.8 years, respectively.

2.2.8 Cytogenetic and Mutational Analyses

The diagnosis of CN-AML was based on the analysis of 20 metaphases in bone marrow specimens subjected to short-term cultures and confirmed by central karyotype review. Patients were also characterized centrally for FLT3 internal tandem duplication

(ITD)(126), FLT3 tyrosine kinase domain mutations (24), MLL partial tandem duplication

(127) NPM1 (28, 50), WT1 (128), CEBPA (45), IDH1, IDH2 (34) TET2, (129) ASXL1

(130) and DNMT3A (40) mutations as previously reported.

2.2.9 Genome-Wide Expression Analyses

Gene- and microRNA-expression profiling were conducted using the NanoString nCounter System (NanoString Technologies, Seattle, WA ) and the Affymetrix U133 Plus

2.0 array (Affymetrix, Santa Clara, CA) and the Ohio State University custom microRNA array (OSU_CCC version 4.0), respectively, as reported previously (131).

2.2.10 Statistical Analysis

Statistical analyses relative to microarray gene and microRNA expression data were performed by the CALGB Statistical Center. Definitions of clinical end points—CR, disease-free survival (DFS), and OS—are as reported previously (34). The differences among patients in baseline clinical and molecular features according to their SPARC expression levels were tested using the Fisher's exact and Wilcoxon rank sum tests for categoric and continuous variables, respectively. Estimated probabilities of DFS and OS were calculated using the Kaplan-Meier method, and the log-rank test evaluated differences between survival distributions.

2.3 Results

2.3.1 SPARC is expressed in hematopoietic stem cells (HSCs)

SPARC has been linked to tissue remodeling, development and stem cells (55,

132); but its role in hematopoesis has not been fully investigated yet. To understand the role of SPARC in leukemogenesis, we initially characterized its expression in normal bone marrow (NBM) cells obtained from normal donors by sorting four different NBM samples into CD34+ and CD34- populations using magnetic beads. SPARC mRNA level measured by qRT-PCR was found to be significantly higher in the CD34+ cells compared to that in the CD34- cells (Figure 2.2a). This prompted us to examine SPARC expression in the following sorted stem cells/ progenitor populations: hematopoietic stem cells and multipotent progenitors (HSC&MPP) or CD34+/CD38-, common-myeloid progenitors (CMP) or CD34+/CD45RA‐/CD123low and granulocyte/monocyte progenitors (GMP) or CD34+/CD45RA+/CD123low of NBM (n=2). We found SPARC protein expression to be the highest in HSC-MPP and this expression has significantly

(70-97%) decreased when cells transitioned into CMP (Figure 2.2b,c). This suggests a possible implication of SPARC in hematopoiesis.

b NBM #3 NBM #4

SPARC a P < 0.0001 Actin

1 HSC- CMP GMP HSC-CMP GMP MPP MPP 0.1

P= 0.0001 0.01 P= 0.0004 0.001 c

1.2 normalized to 18S normalized

SPARC mRNA expression mRNA SPARC 0.0001 1 CD34- NBM CD34+ NBM 0.8

0.6

0.4

0.2

SPARC protein expression (Fold Change) (Fold expression protein SPARC 0 HSC/MPP CMP GMP

Figure 2.2 SPARC is expressed in hematopoitic stem cells/progenitors.

SPARC mRNA level measured in CD34+ and CD34- cells of NBM samples (n=4) (a). SPARC protein expression measured by western blot in sorted stem cells/progenitors populations of NBM samples (b,c)

2.3.2 SPARC promotes leukemia growth

To investigate the impact of SPARC on leukemia growth, gain and loss of function experiments were initially performed. THP-1 cells expressing low level of SPARC were stably infected with pLenti-SPARC (THP-1/SPARC) or a control empty vector pLenti-EV

(THP-1/EV); SPARC ectopic expression was confirmed by western blotting (Figure

2.3a). Colony forming assays were then performed and scored 10-14 days later. A significant increase in the ability of colony formation was observed in THP-1/SPARC compared to the THP-1/EV (164 vs 63; P=0.03) (Figure 2.3b). When we knocked-down

SPARC in Kasumi-1 cells expressing high endogenous levels of this gene (Figure 2.3c), we observed a decrease in the colony forming ability in SPARC siRNA transfected cells compared with the off-target siRNA transfected controls (84 vs 46; P=0.03) (Figure

2.3d).

a c KASUMI-1 THP-1

SPARC SPARC

Actin Actin pLenti- pLenti- EV SPARC Cont SPARC siRNA siRNA

b d 120 200 180 100 160 140 80 120 60 100 80 40 60 40 20

20 Numbercoloniesof per well number ofnumbercolonies perwell 0 0 THP-1 plenti THP-1 plenti KAS-CONT - KAS-SPARC - EV SPARC siRNA siRNA

Figure 2.3 SPARC promotes growth advantage in AML cell lines.

SPARC ectopic expression in THP-1 cells was confirmed by western blotting (a) resulted in increase in colony formation (b), SPARC knock-down in Kasumi-1 cells confirmed by western blot (c) resulted in decrease colony formation (d).

These results were then confirmed in AML primary blasts from four different patients (Table 2.4). Blasts were infected with either pLenti-SPARC or pLenti-EV vectors; ectopic SPARC expression was confirmed by western blot (Figure 2.4a).

Significant increase in colony forming ability was observed in SPARC infected blasts (16 vs 7; P=0.005; 125 vs 77; P=0.013; 22 vs 16; P=0.05 and 357 vs 170; P=0.062) compared to their respective controls (Figure 2.4b) for each patients.

a Pt #1 Pt #2 Pt #3 Pt #4

SPARC

Actin

pLenti-EV + - + - + - + - pLenti- SPARC - + - + - + - +

pLenti-EV P = 0.06 b pLenti-SPARC 400 P = 0.05 300 200 P = 0.01 100 P= 0.005

25 20 15 10 5

Number of colonies per well colonies of Number 0 U-09-0395Pt #1 U-11-0673Pt #2 U-12-0045Pt #3 U-12-1414Pt #4 Primary samples

Figure 2.4 SPARC promotes growth advantage in primary blasts.

SPARC ectopic expressions in primary blasts from 4 different AML patients were confirmed by western blotting (a) and resulted in increase in colony formation (b).

To examine the activity of SPARC in vivo, NSG mice were injected with THP-

1/SPARC cells or THP-1/EV controls via tail vein. We hypothesized that both mice group developed an AML- disease, albeit those transplanted with THP-1/SPARC cells had a more aggressive phenotype. In fact, 8 weeks later the mice injected with THP-1/SPARC cells had significantly larger spleens (P=0.008) (Figure 2.5a,b) and livers (P=0.02)

(Figure 2.5c,d) than THP-1/EV cells injected mice. The livers in THP-1/SPARC mice showed increase tumor nodularity with respect to THP-1/EV controls. Similar results were obtained when we used MV4-11/SPARC xenografts (Figure 2.6). Pathology analysis showed that the THP-1/SPARC cells formed coalescing masses that obliterated large expanses of the liver parenchyma. In contrast, THP-1/EV cells occurred as individual or small clusters of tumor cells within some hepatic sinusoids without effacing the hepatic cords (Figure 2.5e). The THP-1/SPARC had a monomorphic phenotype and high proliferative capacity relative to the pleomorphic character (i.e., variable cell appearance) and elevated apoptotic tendency of the THP-1/EV cells. The pattern and degree of tumor infiltration in the bone marrow (from sternum), heart, and kidney were similar for THP-1/SPARC and THP-1/EV cells injected mice (data not shown).

Importantly, THP-1/SPARC-injected mice (n=6) had a significantly shorter survival than

THP-1/EV-injected mice (n=7) (P=0.006; Figure 2.5f). These data support increase aggressiveness of leukemia cells overexpressing SPARC.

a b P=0.008 Spleen 160 e 140 THP-1 EV 120 100 80 THP-1 EV THP-1 SPARC 60 THP-1 SPARC 40 20

Spleen Weight (mg) WeightSpleen 0 c THP-1 EV THP-1 SPARC Liver d P=0.02

40 1 EV 1 - 35 LIVER 30 THP 25 20 15 10 Liver Size(mm) Liver 5

1 SPARC 1 0

- THP-1 EV THP-1 SPARC THP

f SPARC survival curve 150 THP-1 EV THP-1 SPARC

100

50 Percent Percent survival

0 0 20 40 60 P<0.01 Days after engraftment

Figure 2.5 SPARC promotes aggressive disease in vivo.

NSG mice were engrafted with THP-1 cells infected with plenti-EV or plenti-SPARC vecrtors; spleens (a,b), and livers (c,d) collected 8 weeks following engraftment. Histopathology of liver from the THP-1/EV and THP-1/SPARC (e) Survival analysis of THP-1/EV mice (N=7) compared to THP-1/SPARC (N=6) (f).

a b MV4-11 MV4-11 spleen cell

SPARC SPARC

Actin Actin pLenti- pLenti- pLenti- pLenti- EV SPARC EV SPARC

Spleen Spleen

EV EV

SPARC * SPARC

200 80 70 150 60 50 100 40 30 50 20

10 Spleen weight (mg) weight Spleen

Spleen weight (mg) Spleenweight 0 0 pLenti pLenti- EV SPARC pLenti EV pLenti- SPARC

Figure 2.6 SPARC promotes aggressive disease in vivo.

NSG mice were engrafted with MV4-11 from a previously engrafted NSG mouse (a) with parental MV4-11 cells (b) before injection, cells were infected with pLenti-EV or pLenti- SPARC vectors. Spleens collected 4-8 weeks following engraftment.

2.3.3 SPARC overexpression negatively impacts clinical outcome in CN-AML

Since we found that SPARC contributes to an aggressive leukemia phenotype in preclinical models, next we tested whether increased SPARC expression also associates with aggressive human disease. We analyzed 362 adult patients with primary

CN-AML, enrolled and treated on Cancer and Leukemia Group B (CALGB) upfront protocols with cytarabine-daunorubicin-based regimens for SPARC expression by nCounter assays (nanostring). At diagnosis, higher SPARC expressers harbor more frequently RUNX1 mutations (P < .0001) and ASXL1 mutations (P < .0001), and higher

BAALC, ERG and MN1 expression (P<.001, each) and less frequently NPM1 mutations

(P<.0001) and FLT3-TKD (P=.02) compared with lower expressers, but we found no increase frequency of extramedullary disease (Table 2.1). Higher SPARC expressers had lower chances for achieving CR (P<.001; OR .75) and shorter DFS (P<.001; HR

1.17) and OS (P<.001; HR 1.16), once adjusted for age. In a multivariable analyses, higher SPARC expression independently predicted worse odds for achieving CR

(P<.001), once adjusting for RUNX1 mutation (P=.01), WBC (P<.001) and age group

(P=.01) and was associated with a trend for shorter DFS (P=.07) once adjusting for

FLT3-ITD (P<.001), RUNX1 mutation (P=.03), WBC (P=.005), age group (P<.001), and with significantly shorter OS (P<.001), once adjusting for FLT3-ITD (P<.001), WT1

(P=.003) and ASXL1 (P=.04) mutations and age group (P<.001). Although we used

SPARC as a continuous variable, for display purpose only, we dichotomized younger patients into higher and lower expresser groups using the median SPARC expression value and present the DFS and OS Kaplan-Maier curves in (Figure 2.7a,b).

Table 2.1 Comparison of clinical and molecular characteristics of Low vs. High SPARC all patients n=363 Low SPARC High SPARC P P (n=182) (n=181) (Median cut) (Continuous) Protocol, no. (%) .28 .10 8525 13 (7) 10 (5) 8923 13 (7) 4 (2) 9420 1 (1) 4 (2) 9621 38 (21) 37 (20) 9720 46 (25) 49 (27) 10201 32 (18) 38 (21) 19808 39 (21) 39 (22) Age (years) .23 .005 Median 62 63 Range (18, 81) (20, 83) Age group no. (%) 1.00 .04 <60 77 (42) 76 (42) ≥60 105 (58) 105 (58) Sex, no. (%) .14 .17 Male 85 (47) 99 (55) Female 97 (53) 82 (45) Race, no. (%) 2 unknown 1 unknown .86 .96 White 163 (91) 161 (89) Non-White 17 (9) 19 (11) Hemoglobin (g/dL) 4 unknown 4 unknown .003 .002 Median 9.5 9.2 Range (4.8, 15.0) (4.6, 13.4) Platelet count (x109/L) 2 unknown .13 .01 Median 60 69 Range (4, 507) (8, 850) WBC count (x109/L) 2 unknown .007 .002 Median 35.9 24.9 Range (1.0, 450.0) (1.0, 434.1) %Blood Blasts 2 unknown 2 unknown .009 <.001 Median 65 51 Range (0, 97) (0. 99) %Bone Marrow Blasts .002 .002 Median 73 64 Range (4, 97) (6, 97) FAB, no. (%) 45 unknown 53 unknown .19 .18 M0 1 (1) 5 (4) M1 36 (26) 31 (24) M2 36 (26) 41 (32) M4 32 (23) 33 (26) M5 30 (22) 16 (13) M6 2 (1) 2 (2) M7 0 (0) 0 (0) Extramedullary Involvement, no. (%) 56 (32) 38 (21) .03 .02 CNS 0 (0) 2 (1) .50 .67 Hepatomegaly 9 (5) 7 (4) .62 .66 Splenomegaly 12 (7) 9 (5) .51 .90 Lymphadenopathy 15 (8) 13 (7) .84 .12 Skin Infiltrates 13 (7) 11 (6) .83 .84 Gum Hypertrophy 26 (14) 12 (7) .02 .04 Mediastinal Mass 1 (1) 1 (1) 1.00 .34 Induction Treatment, no. (%) .32 .65 AD 46 (25) 35 (19) ADE 93 (51) 93 (51) ADEP 32 (18) 36 (20) DNR-CTX-E-PRED 1 (1) 0 (0) G3139 10 (5) 17 (9)

Continued 38

Table 2.1 continued n=363 Low† SPARC High† SPARC P§ P£ (n=182) (n=181) (Median cut) (Continuous) NPM1, no. (%) 3 unknown 4 unknown <.001 <.001 Mutated 153 (85) 73 (41) Wild-Type 26 (15) 104 (59) FLT3-ITD, no. (%) 3 unknown 3 unknown .83 .76 ITD positive 66 (37) 68 (38) No ITD 113 (63) 110 (62) CEBPA, no. (%) 3 unknown 4 unknown .02 .37 Mutated 20 (11) 35 (20) Single mutated 6 20 Double mutated 14 15 Wild-Type 159 (89) 142 (80) ELN Risk Group*, no. (%) 4 unknown 4 unknown <.001 <.001 Favorable 110 (62) 64 (36) Intermediate-I 68 (38) 113 (64) FLT3-TKD, no. (%) 3 unknown 4 unknown .002 .02 TKD positive 28 (16) 9 (5) No TKD 151 (84) 168 (95) WT1, no. (%) 3 unknown 4 unknown .28 .34 Mutated 14 (8) 20 (11) Wild-Type 165 (92) 157 (89) TET2, no. (%) 5 unknown 7 unknown .18 .80 Mutated 50 (28) 38 (22) Wild-Type 127 (72) 136 (78) MLL-PTD, no. (%) 22 unknown 23 unknown .12 .09 Present 7 (4) 14 (9) Absent 153 (96) 144 (91) IDH1, no. (%) 6 unknown 5 unknown .13 .16 R132 14 (8) 22 (13) V71i 2 (1) 0 (0) Wild-Type 160 (91) 154 (87) IDH2, no. (%) 6 unknown 5 unknown .68 .19 IDH2 31 (18) 35 (20) R140 31 25 R172 0 10 Wild-Type 145 (82) 141 (80) RUNX1, no. (%) 19 unknown 17 unknown <.001 <.001 Mutated 6 (4) 36 (22) Wild-Type 157 (96) 128 (78) ASXL1, no. (%) 7 unknown 6 unknown <.001 <.001 Mutated 4 (2) 30 (17) Wild-Type 171 (98) 145 (83) DNMT3A 12 unknown 9 unknown .11 .12 Mutated 67 (39) 53 (31) R882 39 41 Non-R882 28 12 Wild-Type 103 (61) 119 (69) ERG expression group <.001 <.001 Median -3.34 -2.64 Range (-6.10, -0.79) (-5.68, -0.02) BAALC expression group <.001 <.001 Median -2.78 -0.29 Range (-7.65, 5.12) (-5.66, 7.59) MN1 expression group (median cut), no. (%) 74 unknown 74 unknown <.001 <.001 High 36 (33) 75 (70) Low 72 (67) 32 (30)

SPARC Disease-free Survival for Younger Patients

1.0 High SPARC (n=58) Low SPARC (n=69)

0.8

0.6

0.4

free Survival free -

0.2 Disease

P =.009 0.0

0 1 2 3 4 5 6 7 8 9 10 Years

b SPARC Overall Survival for Younger Patients

1.0 High SPARC (n=76) Low SPARC (n=77)

0.8

0.6

0.4

Overall Survival Overall 0.2

P =.001 0.0

0 1 2 3 4 5 6 7 8 9 10

Years

Figure 2.7 SPARC overexpression negatively impacts clinical outcome in younger CN-

AML patients.

Younger CN-AML patients were dichotomized into higher and lower expresser groups using the median SPARC expression value and present the DFS and OS Kaplan-Maier curves.

2.3.4 SPARC overexpression is associated with distinct gene and microRNA expression signatures in CN-AML

To gain a biologic insight into SPARC leukemia activity, we derived genome-wide microarray gene and microRNA expression signatures associated with SPARC overexpression in CN-AML patients. We found 650 genes to be significant at P<0.001

(Figure 2.8). Among the most upregulated genes (≥ 2 fold increase) were the two human hematopoietic stem cell markers: CD34 (3.1 folds, P < 1e-07), and PROM1 (CD133) (5.2 folds, P < 1e-07); other genes that have been associated with negative prognosis in

AML were also upregulated such as: BAALC (2.8 folds, P < 1e-07) and MN1 (2.4 folds,

P < 1e-07). Among the most downregulated genes in the signature were members of

HOXA and HOXB clusters and the HOX cofactor, MEIS1. In addition, we were able to derive a microRNA expression signature associated with SPARC expression (Figure

2.9) (Table 2.2 and 2.3). The hematopoietic stem cell-specific miR-126 and miR-130a were upregulated in both older and younger patients. miRs previously reported to be upregulated in the favorable molecular group of NPM1 mutated AML patients were among the most downregulated miRs in high SPARC expressers signature including miR-10a, miR-10b, miR100 and miR-196b in older and miR10a and let7b in younger patients.

HOXB4 HOXB5 HOXB6

HOXA3 HOXA4

APP

CD34

BAALC MN1

Figure 2.8 SPARC overexpression is associated with distinct gene expression signature in CN-AML.

miR expression profile associated with SPARC expression in older patients

High SPARC Low SPARC

miR expression profile associated with SPARC expression in younger patients

High SPARC Low SPARC

Figure 2.9 SPARC overexpression is associated with distinct microRNA expression signature in CN-AML.

Table 2.2 miR expression profile associated with SPARC expression in older patients

Correlation Parametric FDR UniqueID coefficient p-value

1 0.369 1.6e-06 0.000143 hsa_miR_126

2 0.352 5.1e-06 0.000379 hsa_miR_126

3 0.273 0.0004676 0.0209 hsa_miR_130a

4 -0.268 0.0005936 0.0241 hsa_let_7c

5 -0.309 6.75e-05 0.00335 hsa_miR_196b

6 -0.31 6.46e-05 0.00335 hsa_miR_135a

7 -0.33 2.04e-05 0.0013 hsa_let_7b

8 -0.383 6e-07 6.69e-05 hsa_miR_100

9 -0.44 <1e-07 <1e-07 hsa_miR_10a

10 -0.512 <1e-07 <1e-07 hsa_miR_10a

11 -0.52 <1e-07 <1e-07 hsa_miR_10b

Table 2.3 miR expression profile associated with SPARC expression in younger patients

Correlation Parametric FDR UniqueID coefficient p-value

1 0.392 1.5e-06 0.000524 hsa_miR_130a

2 0.378 3.5e-06 0.000611 hsa_miR_126

3 0.338 3.77e-05 0.00329 hsa_miR_126

4 0.285 0.0005687 0.0397 hsa_miR_130b

5 -0.273 0.0009624 0.053 hsa_let_7b

6 -0.351 1.85e-05 0.00215 hsa_miR_1

2.3.5 SPARC activates ILK/AKT/-catenin signaling pathways

Having demonstrated that AML cells overexpressing SPARC supported a more aggressive disease phenotype, next we sought to determine the molecular mechanisms of SPARC in leukemogenesis. We started with the notion that secreted SPARC interact with several cell surface receptors including integrins, such as α5β1, αvβ5, and αvβ3 (133,

134). Integrin β1 was found to interact with SPARC and in turn activate Integrin Linked

Kinase (ILK), a multifunctional cytoplasmic serine/threonine kinase (80, 82), shown to activate PI3K/AKT phosphorylation and inactivates glycogen synthase kinase 3β

(GSK3β) thereby resulting in enhanced β-catenin signaling pathway that support cell survival (84, 135, 136). Thus, we hypothesized that these mechanisms become aberrantly operative in SPARC overexpressing cells and contribute to leukemia growth.

In the media collected from THP-1/SPARC cell culture, we found a significantly higher levels of SPARC protein when compared to that obtained from THP-1/EV cells

(Figure 2.10a). Co-immunoprecipitation assay with SPARC and integrin antibodies showed higher binding of the protein to integrins α5, αv, β1, β3, in THP-1/SPARC cells compared with THP-1/EV cells thereby supporting a potential SPARC autocrine integrin- binding mechanism in leukemia cells overexpressing SPARC (Figure 2.10b).

To determine whether the SPARC binding to integrins enhanced ILK activity, we then performed kinase activity assays. Lysates from THP-1/SPARC cells and THP-1/EV cells were immunoprecipitated with anti-ILK antibody and subjected to assays utilizing

GSK3 fusion protein as an ILK substrate. THP-1/SPARC cells showed increased P-

GSK3αβ(Ser21/9) reflecting higher ILK activity than THP-1/EV cells (Figure 2.7c).

Furthermore, we showed increase in P-AKT(Ser-473) and P-GSK3αβ(Ser9) in THP-

1/SPARC cells compared to THP-1/EV (Figure 2.7d). Knocking down ILK or blocking integrin receptors with αv, β1, β3, antibodies abolished the AKT and GSK3β phosphorylation in THP-1/SPARC cells, thereby supporting the SPARC signaling through this pathway (Figure 2.10d, e).

a b IP:SPARC d THP-1 c THP-1 THP-1 EV SPARC IP: ILK P-AKT

EV SPARC (S473)

EV EV SPARC SPARC

Integrin αv Heavy AKT Chain P-GSK3β BSA (S9) Integrin β3 P-GSK3αβ (Ser 21/9) SPARC GSK3β

Integrin α5

ILK

Integrin β1 SPARC e Actin P-GSK3β(ser9)

pLenti-EV + - + - Actin pLenti-SPARC - + - + Cont siRNA + + - - pLenti-EV + - + - ILK siRNA - - + + pLenti-SPARC - + - +

Integrin Antibodies - - + +

Figure 2.10 SPARC activates ILK/AKT/-catenin signaling pathways in THP-1 cells.

THP-1 cells were infected/transfected with pLenti-EV or pLenti-SPARC vectors, secreted SPARC protein levels were measure by western blot in media collected from cell culture (a). Co-immunoprecipitation assay with SPARC showed binding of SPARC to integrins α5, αv, β1, β3 (b). Lysates from THP-1/SPARC cells and THP-1/EV cells were immunoprecipitated with anti-ILK antibody and subjected to assays utilizing GSK3 fusion protein as an ILK substrate (c). P-AKT(Ser-473) and P-GSK3αβ(Ser9) levels in THP- 1/SPARC cells compared to THP-1/EV following ILK Knock-down (d) or blocking integrin receptors with αv, β1, β3, antibodies (e).

GSK3β promotes β-catenin degradation, and when phosphorylated, this activity is suppressed, and β-catenin stabilization and nuclear translocation are enhanced (137).

Similarly P-AKT(Ser473) induces β-catenin stabilization and nuclear translocation through phosphorylation of β-catenin (Ser552) residue (138). Both GSK3β and AKT are 48 downstream targets of ILK. Indeed we observed higher levels of p-β-catenin(Ser552) in

THP-1/SPARC cells compared to THP-1/EV controls (Figure 2.12c). By confocal microscopy, we also showed an increase nuclear translocation of β-catenin in THP-

1/SPARC compared to THP-1/EV cells (Figure 2.11).

Draq5 B-catenin Merged

EV -

pLenti 1 1 -

THP

SPARC -

pLenti

1 1

- THP

Figure 2.11 SPARC enhances β-catenin nuclear translocation.

THP-1 cells were transfected with pLenti-EV or pLenti-SPARC vectors. Cells were stained with β-catenin antibody and Draq5 antibody (nuclear staining). Immunofluoresence confocal images showing β-catenin and cell nuclei as green and blue respectively.

Once in the nucleus, β-catenin interacts with TCF/LEF transcription factors and promotes expression of genes supporting cell growth and proliferation. Ectopic SPARC expression resulted in >4 fold increase of TCF/LEF reporter activity measured by luciferase assay in 293T cells transfected with SPARC compared with EV-controls

(P<.001; Figure 2.12a). The SPARC-induced TCF/LEF activity was decreased by siRNA knock-down of ILK (Figure 2.12b). The SPARC-induced β-catenin-TCF/LEF activity was also supported by increased expression of the target genes c-MYC in THP-1 cells

(P=0.04) (Figure 2.12c,d). Consistent with these results, we observed significant increase in target genes c-MYC and cyclin D1 expression in MV4-11 cells transfected with pLenti-SPARC compared to pLenti-EV transfected MV4-11 cells; also 1.8 fold increase in c-MYC expression in spleens from mice xenografted with MV4-11/SPARC compared to those xenografted with MV4-11/EV (P=0.002) (Figure 2.13).

a TCF/LEF Luciferase Reporter Activity c THP-1 ***

*** EV

5 SPARC

4 C-Myc

3 P-β- catenin(Ser552) 2 P-GSK3β

1 (Ser9) TCF/LEF TCF/LEF luciferasereporter activity 0 SPARC Ranilla +pLenti Ranilla +pLenti Ranilla +pLenti Ranilla +pLenti EV pfuBAR EV pBAR SPARC pfuBAR SPARC pBAR Actin b TCF/LEF Luciferase Reporter Activity *** d c-MYC mRNA expression in *** 30 THP-1 cells 25 P=0.04 20 2 1.8 15 1.6 10 1.4 1.2 5 1

0 0.8 mRNA relativemRNA expression TCF/LEF TCF/LEF luciferase reporter activity 0.6 pLenti-EV + - + -

MYC 0.4 - Plenti-SPARC - + - + c 0.2 cont-siRNA + + - - 0 ILK-siRNA - - + + EV SPARC

Figure 2.12 SPARC activates TCF/LEF transcriptional activity and increase the expression of β-catenin target genes.

Luciferase activity were measured in 293T cells 24 hours following co-transfection with pBAR (TCF/LEF reporter vector) or pfuBAR (TCF/LEF reporter vector with mutated site) and pLenti-EV or pLenti-SPARC (a) and off-target siRNA or ILK siRNA (b). P-β-catenin (ser552) and c-MYC protein (c) and c-MYC mRNA (d) expression in THP-1 cells transfected with pLenti-EV and pLenti-SPARC.

MV4-11 P=0.01 b c P-AKT a (S473) 3 2.5 P-GSK3b 2 MV4-11 (S9) 1.5 EV SPARC ILK 1

mRNA expressionmRNA 0.5 P-β- SPARC 0 catenin MV4-11 EV MV4-11 SPARC

(Ser552) CyclinD1 Actin P-GSK3β (Ser9) pLenti-EV + - + - pLenti-SPARC - + - + Cont siRNA + + - - C-MYC mRNA expression in spleens Actin ILK siRNA - - + + from MV4-11 mice d P=0.002

2 C-MYC 1.8 1.6 1.4 1.2 SPARC 1 0.8

0.6 mRNA relative mRNA relative expression 0.4 Actin

MYC MYC 0.2 - C 0 EV SPARC

Figure 2.13 SPARC activates ILK/AKT/-catenin signaling pathways in MV4-11 cells.

MV4-11 cells were transfected with pLenti-EV or pLenti-SPARC vectors, P-AKT(Ser- 473), P-GSK3αβ(Ser9), P-β-catenin (ser552) and c-MYC protein levels were measured (a) and (b) and cyclinD1 mRNA expression (c).c-MYC mRNA expression levels were measured in spleen tissues collected from MV4-11/EV and MV4-11/SPARC mice (d).

In order to confirm that SPARC activity in leukemia was mediated by ILK activation, THP-1/EV and THP-1/SPARC cells were treated with 1, 2 and 10 M of T315, an ILK inhibitor, and MTS assays were performed and scored on days 1, 2, 4 and 7. We observed 30% SPARC-induced growth advantage on day 7 in the vehicle-treated cells but no significant growth advantage in T315-treated cells (P= 0.04; Figure 2.14).

Growth advantage ratio of THP-1 SPARC/THP-1 EV

folloing treatment with ILK inhibitor 1 1 EV - P=0.02

1.6

1.4

1 SPARC/THP 1 - 1.2

0.8

0.6

0.4

0.2

Growth advantage advantage Growth ratio of THP 0 untreated 2uM T315

Figure 2.14 SPARC promotes growth advantage via ILK activation.

THP-1/EV and THP-1/SPARC cells were treated with 2 M of T315, an ILK inhibitor, and MTS assays were performed and scored on day 7. Cells viability values on day 7 were normalized to that on day 1 and the growth advantage of SPARC was determined by calculating the cell growth ratio of THP-1/SPARC to that of THP-1/EV.

Finally, we validated our findings in primary blasts from AML patients (Table 2.4).

Forced expression of SPARC in primary blasts resulted in increase of P-GSK3β(Ser9),

P-β-catenin(Ser552) and P-AKT(Ser473) (Figure 2.15.a,b) and increase of c-MYC level measured by intracellular flow (Figure 2.15.d). In addition SPARC knock-out by siRNA decreased total β-catenin, as appeared by confocal microscopy (Figure 2.16) and decreased P-GSK3β(Ser9) and P-β-catenin(Ser552) protein levels (Figure 2.15.c), and c-MYC mRNA expression (Figure 2.15.e). SPARC overexpression and knockdown also resulted in significant increase and decrease of P-β-catenin(Ser675) respectively (Figure

2.17.a,b), a PKA mediated phosphorylation known to stabilize β-catenin (139).

a Pt #5 b c Pt #6 Pt #6 Off-Target siRNA + - EV SPARC EV SPARC SPARC siRNA - + P-β-catenin P-AKT (Ser 552) P-β-catenin (Ser473) (Ser 552) P-GSK3β (Ser 9) SPARC P-GSK3β Actin (Ser 9)

Actin SPARC SPARC

Actin Actin e d c-MYC mRNA expression in ectopically SPARC Pt #7 expressing primary blasts P=0.01 12

8 P=0.01 6 P=0.04

MYC mRNA expression relative mRNA MYC EV SPARC EV SPARC EV SPARC - Green: SPARC infected blasts c Red: EV infected blasts Pt #3 Pt #6 Pt #8

Figure 2.15 SPARC activates ILK/AKT/-catenin signaling pathways in primary blasts.

Primary blasts were infected/transfected with pLenti-EV or pLenti-SPARC, off target siRNA or SPARC siRNA; immunoblot analysis were performed on P-GSK3αβ(Ser9) (a,c), P-AKT(Ser-473) (b), P-β-catenin (ser552) (a,c) and intracellular flow cytometry were performed to measure c-MYC protein levels (d) and qRT-PCR was used to measure c-MYC mRNA expression (e).

Draq5 β-catenin Merged

siRNA

target

Pt #9 #9 Off Pt

siRNA

- Pt #9 #9 SPARC Pt

Figure 2.16 SPARC knock-down decreases β-catenin protein level in primary blasts. primary blasts were transfected with pLenti-EV or pLenti-SPARC. Cells were stained with β-catenin antibody and Draq5 antibody (nuclear staining). Immunofluoresence confocal images showing β-catenin and cell nuclei as green and blue respectively.

a b Pt #1 Pt #5 Pt #4 Pt #10

P-β-catenin P-β-catenin (ser675) (Ser 675)

SPARC SPARC

Actin Actin Off SPARC Target pLenti-EV + - + - + - siRNA siRNA pLenti- SPARC - + - + - +

Figure 2.17 SPARC increases P--catenin(Ser675) in primary blasts.

Primary blasts were infected/transfected with pLenti-EV or pLenti-SPARC, off target siRNA or SPARC siRNA; immunoblot analyses were performed on P-β-catenin (Ser675).

Table 2.4 List of patient samples used in in vitro experiments

Sample Cytogenetics Mutation analyses

Pt #1 Inv(16)

Pt #2 Normal FLT3-ITD/ NPM1-mut

Pt #3 Normal FLT3-ITD

Pt #4 Normal FLT3-ITD/ NPM1-mut

Pt #5 Normal NPM1-mut

Pt #6 Nomal FLT3-ITD

Pt #7 Normal FLT3-ITD/ NPM1-mut

Pt #8 Inv(16)

Pt #9 NA NA

Pt #10 Inv(16)

Pt #11 Normal NPM1-mut

2.3.6 Distinct mutations in IDH2 and RUNX1 genes induce SPARC expression likely via activation of NF-B/SP1 complex in CN-AML

Having dissected the downstream mechanisms that potentially mediate the contribution of SPARC to aggressive AML, next we asked the question of how SPARC expression becomes deregulated in AML. We previously reported that SPARC was among the most upregulated genes in the GEP associated with IDH2-R172 mutation that predicted unfavorable outcome in CN-AML patients (34). Here we showed that

SPARC upregulation was indeed specifically associated with IDH2-R172 mutants

(P<0.001) and not with other IDH1 or IDH2 mutations (Figure 2.18).

Figure 2.18 SPARC expression in CN-AML patients according to their IDH1 and IDH2 mutational status.

In order to validate the association between IDH2-R172 and SPARC overexpression, we tested the expression of SPARC in THP-1 cells infected with IDH2-

R172. A significant increase in SPARC mRNA (3 fold increase) and protein levels were detected in THP-1 infected with IDH2-R172 compared with empty vector or IDH2-wt infected cells (Figure 2.20.a,b). We also verified SPARC upregulation in Kasumi-1 and

MV4-11 cells and primary blasts from AML patient (Figure 2.20c,d,e) transiently transfected with IDH2-R172 and found a significant increase in SPARC expression in

IDH2-R172-cells compared to IDH2-wt-cells. THP-1 and Kasumi-1 cells transfected with

IDH1-R132 and MV4-11 cells transfected with IDH2-R140Q mutation constructs did not show significant increase in SPARC expression compared to their respective controls

(Figure 2.20a,b,c,f).

Higher SPARC expression was also observed in the unfavorable RUNX1- mutated CN-AML subset compared with the RUNX1-wt subsets (Figure 2.19).

Interestingly, SPARC was reported to be overexpressed in patients with t(8,21) and inv(16) AML (122). Because of the heterogeneity of RUNX1 mutations, we utilized a loss of function approach to examine the effect of RUNX1 on SPARC expression. Knock- down of RUNX1-RUNX1T1 translocation by siRNAs in Kasumi-1 cells resulted in significant decrease in SPARC expression (Figure 2.20g); while knock-down of

RUNX1wt in MV4-11 cells resulted in SPARC overexpression (Figure 2.20h).

Figure 2.19 SPARC expression in CN-AML patients according to their RUNX1 mutational status.

a THP-1 c KASUMI-1 d MV4-11 IDH1- IDH1- IDH2- IDH2- THP-1 IDH1- IDH1- IDH2- IDH2- WT R132 WT R172 EV IDH2- IDH2- WT R132 WT R172 E V WT R172 SPARC SPARC SPAR C IDH1 Actin Actin

Actin f MV4-11 e Pt #2 IDH2- DH2 - EV R140Q IDH2 IDH2- IDH2- WT WT R172 IDH2 Actin SPARC SPARC b Actin Actin

1000 MV4-11 g Kasumi-1 h Runx1 Cont AML-ETO Cont siRNA siRNA 100 siRNA siRNA

AML-ETO RUNX1 10 24h

Actin Actin

1 SPARC mRNA expression (Log) expression mRNA SPARC

0.1 SPARC SPARC THP-1 IDH1-WT IDH1-R132 IDH2-WT IDH2-R172 72h

Actin Actin

Figure 2.20 Mutations in IDH2 and RUNX1 genes induce SPARC expression.

SPARC protein levels in THP-1 (a) and Kasumi-1 (c) cells and mRNA levels in THP-1 cells (b) were measured in infected/transfected cells with pLenti-EV, pLenti-IDH1-WT, pLenti-IDH1-R132, pLenti-IDH2-WT pLenti-IDH2-R172 by immunoblot and qRT-PCR respectively. SPARC protein levels were measured in Primary blasts infected with pLenti-IDH2-WT and pLenti-IDH2-R172 (e), and in MV4-11 cells transfected with pLenti- EV, pLenti-IDH2-WT, pLenti-IDH2-R172 (d) pLenti-IDH2-R140Q (f). Kasumi-1 cells transfected with AML-ETO siRNA and SPARC protein level was measured 72 hours after (g), MV4-11 cells were transfected with RUNX1 siRNA and SPARC protein expression was measured 48hours after.

To understand how IDH2-R172 and RUNX1 mutations induce SPARC expression, we searched SPARC promoter for transcription factors that might be involved. Utilizing TFSEARCH program, SPARC promoter sequence revealed several binding sites for SP1, RUNX1 and NF-κB among other transcription factors. To examine the effect of these transcription factors on SPARC promoter activity, we cloned SPARC promoter region in PGL4.11 luciferase vector and used it along with expressing vectors of each of the different transcription factor (SP1, RUNX1 and P65 (NF-κB subunit)) to co-transfect 293T cells. Luciferase activities measured 24 hours later, showed significant increase (P<.001, each) in SPARC promoter activity in cells transfected with SP1 or P65 respectively (Figure 2.21). Furthermore, a significant decrease in SPARC promoter activity was observed when cells were transfected with RUNX1 expression vector (80%,

P<.001) or SP1 siRNA (50%, P<.001) (Figure 2.21a). In addition, ectopic expression of

SP1 and P65 resulted in significant increase in SPARC protein level compared to empty vector transfected MV4-11 and THP-1 cells (Figure 2.21b,e), while SP1 and P65 knock- down by siRNAs resulted in significant decrease in SPARC protein level in Kasumi-1 cells (Figure 2.21c,d).

a 2.5 *** ***

*** 1.5 ***

0.5

SPARC Promoter luciferase activity luciferase Promoter SPARC 0 EV Runx1 EV P65 EV SP1 cont-siRNA SP1-siRNA

b e THP-1 d EV P65 Kasumi-1 c SPARC cont- P65- MV4-11 Kasumi-1 siRNA siRNA EV SP1 cont- SP1- Actin siRNA siRNA P65 SP1 SP1 P65 SPARC SPARC SPARC

Actin Actin Actin Actin

Figure 2.21 SPARC expression is regulated by NF-B, SP1, and RUNX1 transcription factors.

293T cells were co-transfect with PGL4.11 luciferase vector contain the SPARC promoter region (PGL4.11/SPARC-promoter) and expressing vectors of each of the different transcription factor (SP1, RUNX1 and P65 (NF-κB subunit)), Luciferase activities measured 24 hours later, and normalized to that in 293T cells co-transfect with PGL4.11/SPARC-promoter and EV vector (a). SPARC protein expression levels were measure following SP1 ectopic expression in MV4-11 cells (b), SP1 or P65 knock-down in Kasumi-1 cells (c,d), and p65 expressing vector in THP-1 cells (e).

IDH2-R172 mutation was found to result in accumulation of 2- Hydroxyglutarate

(2HG) in both glioblastoma and AML (140). This accumulation resulted in inhibition of 2- oxoglutarate dependent oxygeneases including the Jmjc lysine demethylases such as

FBXL11 (140, 141). FBXL11 was found to negatively regulate transcriptional NF-κB activity through lysine demethylation (142). On the other hand, RUNX1 inhibits NF-κB signaling through interaction with IκB kinase complex in the cytoplasm (143). RUNX1 mutants lacked the ability to inhibit NF-κB signaling; importantly patients with RUNX1- related leukemia exhibits distinctly activated NF-κB signaling (143). These reports led us to speculate that IDH2-R172 and RUNX1 mutations contribute individually to SPARC overexpression through NF-κB activating mechanisms.

To test this possibility we utilized NF-κB luciferase reporter assay and examined the effect of IDH2-R172 and RUNX1 ectopic expression on NF-κB activity. 293T cells cotransfected with IDH2-R172 and NF-κB luciferase vectors exhibit higher luciferase activity when compared with IDH2-wt transfected cells (Figure 2.22a), on the other hand

RUNX1 ectopic expression in 293T cells resulted in significant decrease of NF-κB luciferase reporter activity compared to the empty vector transfected cells (Figure 2.22a).

Importantly, 293T cells cotransfected with SPARC promoter luciferase vector and IDH2-

R172 showed also increase of luciferase promoter activity (Figure 2.22b). Furthermore, chromatin immunoprecipitation (ChIP) showed P65 enrichment on SPARC promoter in

IDH2-R172 transfected THP-1 cells compared with IDH2-wt transfected cells (Figure

2.22d). Although no significant change in P65 enrichment in RUNX1 transfected cells was observed, we found significant decrease in SP1 enrichment on SPARC promoter in

RUNX1 transfected cells compared to EV-transfected cells (Figure 2.22e). These results 68 suggest that IDH2-R172 and RUNX1 contribute individually to SPARC overexpression through NF-κB/SP1 activating mechanisms.

a b ***

*** 2.50 2.5

2.00 2 ***

1.50 1.5

1.00 1 kb luciferaseactivitykb

- 0.50 0.5 NF

0.00 0

IDH2-wt IDH2-R172 CMV-EV CMV-Runx1 SPARC Promoter luciferase activity IDH2-wt IDH2-R172 c d e 1.4 4.5 3 1.2 4 2.5 3.5 1

3 2 0.8 2.5 1.5 0.6 2

1 1.5 0.4 1 0.5 promoter SPARC onenrichment P65 0.2

0.5 promoterSPARC onenrichment SP1 P65 enrichment on SPARC promoter SPARC onenrichment P65 0 0 0 EV Runx1-CMV EV-pCMV P65-pCMV pLenti-IDH2wt pLenti-IDH2-R172

Figure 2.22 IDH2-R172 and RUNX1 contribute individually to SPARC overexpression through NF-κB and SP1 mediating mechanisms.

293T cells cotransfected with pLenti-IDH2-R172 or pCMV-RUNX1 and NF-κB luciferase vectors (a). 293T cells cotransfected with pLenti-IDH2-R172 and PGL4.11/SPARC- promoter vectors (b) and luciferase activities were measured 24hours later, values were normalized to that in respective controls. chromatin immunoprecipitation (CHIP) showed P65 enrichment on SPARC promoter in IDH2-R172 transfected THP-1 cells compared with IDH2-wt transfected cells (c). Decrease in SP1 enrichment on SPARC promoter in RUNX1 transfected cells compared to EV-transfected cells (d).

2.3.7 SPARC is a novel therapeutic target in AML

Thus far, we demonstrated that SPARC overexpression resulted in more aggressive AML in vitro and in vivo, correlated with worse outcome in CN-AML patients and resulted in activation of signaling pathways associated with tumor progression.

Therefore, SPARC may represent a novel therapeutic target in AML patients exhibiting high expression level of this gene. We found SPARC to be upregulated though mechanisms that activate NF-B/SP1 complex. In addition, SPARC was previously found to be a target for miR-29a and miR-29c (144) and SPARC 3‘UTR region was predicted to have binding sites for miR-29b (145, 146). To confirm these reports we cloned SPARC 3‘UTR region in luciferase reporer vector (pGL3) and used the generated vector to co-transfect 293T cells with the following synthetic miRNA (miR-29b, miR-203, and miR-9*) or scramble oligos. We found 60% decrease of SPARC 3‘UTR-luciferase activity in the presence of miR-29b compared to that in the presence of the scramble or the other miRs (P<0.0001) (Figure 2.20a).

Additionally we have previously identified SP1 as a direct target for miR-29b

(147). In sum, these observations suggest that modulating NF-B/SP1 and/or miR-29b may provide a therapeutic advantage for AML characterized by SPARC upregulation.

Bortezomib, a proteasome inhibitor with antitumor activity was found to exhibit antileukemic activity through miR-29b-dependent SP1 downregulation (125). Therefore we hypothesized that bortezomib, may provide a promising therapeutic approach to disrupt SPARC expression and efficiently override aberrant SPARC activity in AML.

Thus, Kasumi-1 cells were treated with 0, 20, 60 and 100 nM of Bortezomib; immunoblot analysis at 24 hours after Bortezomib treatment showed significant dose dependent increase of miR-29b (Figure 2.23a) decrease in SPARC RNA and protein levels (Figure 2.23 b,c). Consistent with these results, we found SPARC levels to be decreased on day 26 in samples of patients treated on a phase 1 dose escalation trial of decitabine in combination with bortezomib (Figure 2.23e).

a b c SP1 and SPARC mRNA Expression in 3`UTR SPARC Luciferase Activity miR 29b Expression in Kasumi-1 Kasumi-1 cells 24 Hours After in cells 24 Hours After Treatment Treatment with Bortezomib 1.2 3 with Bortezomib 1.4 1 2.5 1.2 SP1 SPARC 0.8 2 1 0.8 0.6 *** 1.5 0.6 1 0.4 miR 29b Expression29b miR 0.4 0.5

0.2 0.2 Relative mRNA expressionRelative mRNA 0 3`UTR SPARC LuciferaseActivity SPARC 3`UTR 0 0 0 20 60 100 scrabmle miR-29b miR-203 miR-9* 0 20 60 100 Bortezomib Concentration (ηM) Bortezomib Concentration (ηM)

d e SPARC expression in BM of BTZ&DEC treated Control 20ȠM 60ȠM 100ȠM patients 10 9 SPARC 8 7

SP1 6 5 4 3 c-MYC 2 1

Actin SPARCmRNA relative expression 0 Pre Day5 Day26

Figure 2.23 Bortezomib inhibits SPARC expression.

SPARC 3‘UTR-luciferase activity in the presence of miR-29b was measured by co- transfecting 293T cells with SPARC-3‘UTR reporter and a synthetic miRNA, values were normalized to that of cells transfected with scramble(a). Kasumi-1 cells were treated with 20, 60, and 100 nM of Bortezomib; miR-29b (b) and mRNA levels of SPARC and SP1 (c) were measure 24 hours later by qRT-PCR. SPARC, SP1 and c-MYC protein levels were measured by western blot (d). SPARC mRNA levels in bone marrow samples from patients treated on phase 1 dose escalation trial of decitabine in combination with bortezomib (e).

2.4 Discussion

We demonstrated here the functional, mechanistic and clinical implication of

SPARC in AML. Our study reveals that high SPARC expression in AML cells promoted growth advantage in vitro and aggressive disease in vivo, likely via activation of

ILK/AKT/-catenin pathways. Furthermore, SPARC overexpression independently associated with worse outcome in CN-AML patients.

Several studies have reported elevated SPARC expression in invasive malignant tumors (115, 148). High SPARC was associated with malignant melanomas progression

(112, 113, 149) and meningiomas and gliomas invasiveness (86, 115, 150-152). On the contrary, in other types of cancer (colon cancer, ovarian cancer), SPARC has also been found to be associated with tumor suppression (153, 154). In MDS, 5q deletion results in the loss of one copy of SPARC among other genes and significant downregulation of

SPARC expression in the progenitor compartment (119, 120). The involvement of

SPARC in MDS was supported by the dramatic upregulation of SPARC in response to lenalidomide, a drug approved for treatment of MDS patients (119). Although this suggested a possible tumor suppressor role of SPARC in del(5q) MDS, no biological evidence was found to support this notion. Indeed SPARC was found to be dispensable for murine hematopoiesis suggesting that SPARC deficiency does not alter the hematopoietic potential of normal bone marrow (155). Tripodo and colleagues have later reported that increased SPARC expression in the bone marrow stroma contributes to the detrimental fibrotic changes associated with myeloproliferation, while loss of SPARC expression induces a defective stromal niche that supports myeloid expansion (156).

Being expressed by both stromal and hematopoietic cells, with different functions 73 depending on the cellular source, SPARC contributions to myeloid neoplasms seem at least controversial and remain to be fully elucidated.

Here we investigated SPARC overexpression in AML by functional approaches in both mouse models and human AML. We demonstrated that SPARC promotes aggressive leukemia growth, thereby implicating SPARC as a potential oncogene. This seems in disagreement with a previous report by DiMartino et al, where exogenous

SPARC protein was found to induce growth inhibition in AML with MLL rearrangements

(122). The discrepancy between the two studies may be related to difference in experimental conditions. In fact, while we forced ectopic SPARC expression in leukemia cells, Di Martino et al. exposed the leukemia cells directly to recombinant exogeneous

SPARC protein. This raises the question of, whether post-translational modifications occur in the endogenously produced protein and may be required for the leukemogenesis. Furthermore, while we showed a likely autocrine SPARC function that allows for interaction of SPARC with membrane proteins such as the integrins, it cannot be excluded the involvement of SPARC in intracellular signaling pathways different from those activated by the extracellular protein. Indeed, the intracellular retention of SPARC was seemingly required for its protective effect in imatinib resistant CML (123). In support of the negative impact of SPARC in human AML, we showed that expression of this gene predicted a lower CR rate and shorter DFS and OS in younger and older patients with primary CN-AML and treated similarly with cytrabine-anthracyline regimens on CALGB upfront protocols. Indeed, SPARC expression was found higher in patients with concurrent unfavorable prognostic mutations (i.e., IDH2-R172 and RUNX1) or aberrantly upregulated genes (ie., BAALC and MN1) and lower in patients with

74 concurrent favorable prognostic mutations (NPM1). It should be underscored, however, that multivariable analyses in our study demonstrated that SPARC levels are prognostically independent from the aforementioned mutations, suggesting that while

IDH2-R172 and RUNX1 mutants may activate pathways leading to SPARC overexpression, these mechanisms are not private of these mutations. Indeed, analysis of the SPARC promoter revealed several binding sites for NF-κB and SP1 in addition to

RUNX1. These transcription factors have been found to participating in transactivating complexes leading to upregulation of target genes in AML cells (157).

Our initial observation supports the notion that SPARC overexpression enhanced

-catenin signaling pathway, known to be required for leukemia growth and stemness

(158, 159). Indeed, in GEP and MEP associated with high SPARC expression, we observed upregulation of hematopoietic stem cell gene and microRNA markers such as

CD34, CD133, TGF genes and miR-126 and miR130a that have been associated with leukemia stemness. The SPARC-dependent activation of -catenin, resulted from upstream binding of SPARC with integrin and activation of ILK, which indeed was found activated in leukemic cells (160). ILK a kinase that links the cell adhesion receptors, integrins, and growth factors to the downstream signaling pathways that involve AKT and GSK3β resulting in the nuclear localization of β-catenin and activated transcription, cell cycle progression, and cell proliferation (161). ILK inhibitors in combination with

FLT3 inhibitors were found to result in selective targeting of AML rather than normal hematopoietic progenitors (160, 162). While SPARC/ILK/AKT signal transduction pathways were found involved in glioma cell invasion and survival (85), to our knowledge this mechanism has not been previously reported in AML.

In conclusion, high SPARC expression contributes to aggressive AML growth via

-catenin activation-mediated mechanisms. SPARC overexpression independently predicted worse outcome in CN-AML patients. Furthermore, given the involvement of

SPARC in leukemia growth and aggressive disease, mapping out the SPARC-related leukemogenic pathways may open new avenues for therapeutic intervention. Indeed, it is equitable to speculate that SPARC may represent a novel therapeutic target in AML for compounds inhibiting NF-κB activity or directly interfering with -catenin transactivation.

Chapter 3 : Pharmacological Activity of Silvestrol in High-Risk Acute Myeloid

Leukemia

3.1 Introduction

The outcome for high-risk patients who are treated with allogeneic stem cell transplantation in first complete remission are encouraging, but lack of suitable donors, presence of co-morbidities and treatment-related toxicity and mortality has often limited the application of this approach. Therefore, novel therapeutic strategies that improve the currently poor outcome in AML patients while demonstrating an optimal toxicity index are highly needed.

As we have shown in chapter 1, recurrent cytogenetics and molecular aberrations are known to impact the prognosis of AML. Importantly, several of these genomic aberrations may also comprise novel therapeutic targets. Gain-of-function mutations of the tyrosine kinase (TK) receptor encoding gene FLT3 occur in approximately 30% of AML patients, and result in constitutive TK activity and, in turn, increasing growth and survival of leukemia blasts. Of the FLT3 mutations, the internal tandem duplication (FLT3-ITD) is associated with poorer outcome (23, 163-167). In addition, overexpression of the FLT3-wt receptor and its ligand (FL) occur in a high 77 percentage of AML and the subsequent autocrine stimulatory loop may contribute to the pathogenesis and aggressiveness of the disease (168, 169). Therefore, investigating compounds that can inhibit both mutant and overexpressed wild type FLT3 in AML leukemia is warranted.

Smith et al. demonstrated that FLT3-ITD likely constitutes a driver mutation in

AML and therefore it may represent not only as a prognosticator but also a potential therapeutic target (170). Emerging small molecule inhibitor compounds have been shown to interfere with the aberrant FLT3 TK activity and lead to arrest of leukemia growth (165). Unfortunately the clinical impact of these compounds as single agents or in combination with chemotherapy has not yet fulfilled the promise, likely because of their relatively low potency, lack of specificity and the early onset of mechanisms of resistance (171-173). This underscores the need for additional strategies that effectively target aberrant FLT3 activity in AML blasts and improve the currently poor survival rate in high-risk patients with FLT3-driven AML.

In addition to the activation of FLT3 kinase activity, another hallmark of FLT3-ITD positive AML is the upregulation of miR-155 (46-48). Importantly, studies have shown that sustained expression of miR-155 caused granulocyte/monocyte expansion and resulted in pathological features of myeloid neoplasia in a mouse model (49). Also, miR-

155 has a known oncogenic activity in hematologic malignancies and may serve as clinical biomarker for disease progression, and therefore a novel therapeutic target (174,

175).

Silvestrol is a cyclopenta[b]benzofuran rocaglate with a unique dioxanyl ring- containing side chain (176, 177). It was isolated from the Indonesian plant Aglaia foveolata, structurally characterized, and tested for anti-tumor efficacy (176). Silvestrol

78 showed activity against several solid tumor cell lines (178-181) as well as primary chronic lymphocytic leukemia cells at nanomolar concentrations, and prolonged survival in a murine model of B cell acute lymphoblastic leukemia (182). More recently, silvestrol was reported to have synergistic activity against AML cell lines when combined with chemotherapy (183). Pelletier et al, have demonstrated that silvestrol interferes with assembly of the eIF4F translation complex by promoting an aberrant interaction between capped mRNA and eIF4A, thus blocking protein synthesis at the initiation step (181,

184). This inhibition of protein synthesis results in a preferential depletion of proteins with short half-lives, such as MCL1, to which leukemia and cancer cells may be addicted and thrive on (182, 184). Therefore, we hypothesize that silvestrol could also inhibit translation of FLT3 mRNA and in turn downregulate the expression of FLT3 and decrease aberrant tyrosine kinase in FLT3-driven AML. Thus, we sought to examine the in vitro and in vivo anti-leukemic and biological activity of silvestrol in FLT3-ITD or FLT3- wt overexpressing AML cell lines and primary blasts.

3.2 Materials and Methods

3.2.1 Reagents

Silvestrol was kindly provided by Dr. A. Douglas Kinghorn. PKC412 was purchased from LC Laboratories (Woburn, MA, USA). Human FLT3 ligand (FL) was purchased from PeproTech (Rocky Hill, NJ, USA)

3.2.2 Cell lines and primary blasts

MV4-11 and THP-1 cells (ATCC, Manassas, VA) were cultured in RPMI 1640 medium supplemented with 10% calf serum. Blasts from AML patients were maintained in RPMI 1640 medium supplemented with 30% fetal bovine serum, 1% HEPES buffer, and 1x StemSpan CC100 (StemCell Technologies, Vancouver, BC, Canada) containing

IL-3, IL-6, FLT3 ligand and SCF. All cells were incubated at 37ºC with 5% CO2. Patient

AML blasts were obtained from apheresis blood samples collected from patients treated at the Ohio State University (OSU) and stored in the OSU Leukemia Tissue Bank.

Informed consent to use cells for investigational studies was obtained from each patient under an OSU Institutional Review Board-approved protocol, according to the

Declaration of Helsinki. Authenticating tests of these cell lines was done using monoclonal antibodies and FLT3 mutational analysis.

3.2.3 Immunoblot analyses

Cells were suspended 30 min in 1x lysis buffer (20 mM Hepes,150 mM NaCl,

0.1% NP40) containing protease inhibitor cocktail III (Calbiochem, Darmstadt, Germany) and lysate was recovered by centrifugation. Lysates were separated using 4-20% SDS-

PAGE and transferred to PVDF membrane (GE Healthcare, Piscataway, NJ). 80

Membranes were blocked using 5% milk or BSA in 1x TBS with 0.1% Tween 20 (1xTBS-

T) for 1 hour at room temperature with shaking, then incubated overnight at 4ºC in the following primary antibodies diluted in 1xTBS-T with 5% milk or BSA: actin (Santa Cruz

Biotechnology, Santa Cruz CA), FLT3 (Cell Signaling, Danvers, MA), phosphorylated and total STAT5 (Cell Signaling), P65 antibody (Billerica, MA). Membranes were washed using 1xTBS-T, incubated with HRP-conjugated secondary antibodies diluted in 1xTBS-

T with 5% milk or BSA, washed, and developed using ECL Western Blotting Detection reagents (GE Heathcare).

3.2.4 RNA immunoprecipitation (RIP), RNA extraction, Real-Time RT-PCR

MV4-11 cells were treated with 50 nM silvestrol for 3 hour, lysed (5 min) in 100 mM KCl, 5 mM MgCl2, 10 mM HEPES [pH 7.0], 0.5% NP-40, 1 mM dithiothreitol (DTT),

100 units/ml RNase OUT (Invitrogen), 400 mM vanadyl-ribonucleoside complex and protease inhibitors (Roche, Mannheim. Germany). Extracts were clarified and stored at -

80°C. Anti-eIF4E antibody (cell signaling) and goat IgG (Sigma, St. Louis, MO) were incubated with protein sepharose A/agarose G-coupled beads overnight. Beads were subsequently washed four times with 50 mM TRIS/HCl, pH 7.0, 150 mM NaCl, 1 mM

MgCl2, and 0.05% NP-40, and twice after addition of 1M urea. Precipitates were digested with proteinase K (55°C), and eIF4E-associated mRNAs were isolated using

Trizol reagent (Invitrogen, Grand Island, NY). cDNA was synthesized using SuperScript

III reagents (Invitrogen) and the TaqMan MicroRNA Reverse Transcription Kit (Applied

Biosystems, Foster City, CA) according to the manufacturer‘s instructions. Quantitative

Real-Time RT-PCR for FLT3 and PU1 genes and miR-155 and miR-34a expression was performed using commercially available TaqMan Gene Expression Assay primers and

81 probes and the 7900HT Fast Real-Time PCR System (Applied Biosystems). The comparative cycle threshold (CT) method was used to determine the expression levels normalized by the internal control 18S for gene expression.

3.2.5 Clonogenic and Viability Analysis

Methylcellulose clonogenic assays were carried out by plating 2X104 primary blasts in 0.9% MethoCult (Stem Cell Technologies). Colonies (>100 mm) from cell lines and primary cells were scored 14 days later.

3.2.6 Flow cytometry

For FLT3 detection, cells (5×105) were washed with phosphate-buffered saline

(PBS) and resuspended in 50 μl binding buffer containing 5 μL FLT3 antibody (BD

Biosciences, Billerica, MA). After 15 min incubation, cells were washed with PBS, resuspended in 400 μL flow buffer and analyzed on a FACSCalibur cytometer (BD

Biosciences). To assess apoptosis, AML cells were incubated with 10, 30 and 50 nM silvestrol for 24 hours. Cells (5×105) were then washed with PBS and resuspended in 50

μl binding buffer containing 2 μL of annexin V-FITC stock (BioWhittaker, Inc,

Walkersville, MD) and 5 μL propidium iodide (PI) (BD Biosciences). After 20 min incubation, fluorescence was quantified by flow cytometry on a FACSCalibur instrument.

3.2.7 MV4-11 xenograft murine model

This model was developed recently in our laboratory. Briefly, 4~6 week-old non- obese diabetic severe combined immunodeficient gamma (NSG) mice (NOD.Cg-

Prkdcscid Il2rgtm1Wjl/SzJ, The Jackson Laboratory, Bar Harbor, ME) were

82 intravenously (i.v) injected via tail vein with 2x107 MV4-11 cells. Two months later, the spleen mononuclear cells (MNCs) were isolated from MV4-11 cells injected mice (1st- adapted MV4-11 cells in NSG mice). The adapted spleen MNCs were injected into the new NSG mice via tail vein. The loading dose of cells was reduced to 50% in second and third transplantation and only 1X107 cells/mouse were used for second injection.

About a month later, the spleen MNC were isolated from 2nd-adapted MV4-11 cells in

NSG mice. The 3rd transplantation was performed using 0.5 x107 cells/mouse spleen

MNC from 2nd adapted NSG mice. For the subsequent transplantation model, 0.5X106 spleen MNC cells were used. The complete blood count and FACS analysis of CD45 and FLT3 expression and cytospin were examined weekly to monitor the progression of disease. Generally, these mice develop AML-like disease in two weeks after the injection of spleen MNC from 3rd adapted MV4-11 cells of NSG mice and their lifespan is around

3~4 weeks. All the experiments were conducted in accordance with the institutional guidelines for animal care and use.

Spleen cells (0.5x106) from MV4-11 transplanted NSG mice were intravenously (iv) injected into NSG mice via tail vein, and divided into groups for vehicle (hydroxypropyl beta-cyclodextrin in 30% sterile water; N=6) or silvestrol (1.5 mg/kg in vehicle; N=10) treatment. One control mouse (no leukemia/no treatment) was also included. Two to three weeks after engraftment, white blood count (WBC) and FLT3 expression by flow cytometry were assessed to confirm transplantation. Treatments with silvestrol or vehicle were initiated 21 days after engraftment (based on disease signs documented by WBC count and FLT3 expression). Administration was by intraperitoneal injection every 48 hours for up to three weeks or until euthanasia criteria were met. Expected median survival of untreated animals in this model is 28 days. Mice were weighed daily and

83 checked for signs of dehydration, discomfort or toxicity. On day of administration, doses were recalculated for each animal after weighing to maintain 1.5 mg/kg. For the pharmacodynamic study, 6 mice were used (3 per group, vehicle and silvestrol). These mice were given 3 doses of either vehicle or silvestrol; and 48 hours following the third dose, spleens were isolated and mononuclear cells obtained for immunoblotting assay.

For pathological examination, tissue sections from the liver and spleen were fixed on formalin, embedded in paraffin blocks, and H&E stained.

3.2.8 Wright-Giemsa staining

Morphological signs of apoptosis were detected by Wright-Giemsa staining.

Smears of control and treated cells were stained with Wright-Giemsa solution for 25 min, rinsed with distilled water and air dried. Cell morphology was studied by light microscopy.

3.2.9 MTS assay for growth inhibition

Briefly, 5.0×104 cells were incubated in triplicate in a 96-well plate in the presence or absence of the indicated test samples in a final volume of 100 µl for 24, 48 and 72 hours at 37°C. Thereafter, 20 μl MTS solution (Promega, Madison WI) was added to each well. After 4 hours incubation at 37°C, plates were shaken and the optical density at 490 nm was measured. Percent cell viability was calculated as cell viability of the experimental samples/cell viability of the control samples × 100. At least three independent experiments were performed.

3.3 Results

3.3.1 Silvestrol antileukemia activity in FLT3-ITD and FLT3-wt expressing AML cells

We first examined the antileukemia activity of silvestrol in AML cell lines. MV4-11 cells are FLT3-ITD positive, whereas THP-1 cells are negative for FLT3-ITD but express robust levels of FLT3-wt. measured by MTS assay we found that leukemia growth decreased in a dose- (5 to 160 nM) and time-dependent manner following silvestrol treatment (Figure 3.1a). At 48 hours, ICs50 (concentration required to inhibit growth to

50% of control) were 2.6 and 3.8 nM in MV4-11 and THP-1, respectively (Figure 3.1b and Table 3.1). Primary blasts from three AML patients with FLT3-ITD and two AML patients with FLT3-wt were treated with 5 to 320 nM silvestrol. A dose-dependent decrease in proliferation was observed, with ICs50 values at 48 hours of 4.0, 6.4 and 3.6 nM for the blasts from the FLT3-ITD patients and 6.6 and 16.9 nM for the blasts from the

FLT3-wt patients (Figure 3.1c and Table 3.1). We also performed a colony forming assay of silvestrol in primary samples from three different patients including two FLT3-

ITD positive cases. We observed no colony formation for any of the tested samples when blasts were treated with 25 nM of silvestrol (Figure 3.1d).

To determine whether the antileukemic activity of silvestrol was mediated by enhanced apoptosis, we utilized annexin and PI staining of cells treated with 10-50 nM silvestrol for 48 hours. A dose-dependent increase in apoptosis was observed in silvestrol treated compared to vehicle-treated primary blasts from FLT3-ITD (n=3) as well as FLT3-wt (n=2) AML patients (Figure 3.2). In AML primary cells, silvestrol induced 1 to

7.5 fold increase in apoptosis in both FLT3-wt and FLT3-ITD blasts (P=0.0001 for every

85 tested case) treated with 10, 30 and 50 nM of silvestrol compared with vehicle treated controls.

a b Silvestrol antiproliferative activity in AML 1.2 Silvestrol antiproliferative activity in MV4-11 1.2 cell lines 1 24h 1

0.8 48h 0.8 MV4-11

72h 0.6 0.6 THP-1 0.4 0.4 0.2

0.2 RelativeGrowthInhibition

RelativeGrowthInhibition 0 0 0 5 10 20 40 80 160 0 5 10 20 40 80 160 Silvestrol concentration (nM) Silvestrol concentration (nM)

c d Colony forming assay of Silvestrol antiproliferative activity in AML primary cells Silvestrol in AML primary blasts 1.2 30 Pat#1 (FLT3-wt) 1 Pat#2 (FLT3-wt)) 25 Pat#3 (FLT3-ITD) 20 0.8 Pat#4 (FLT3-ITD) 15 Pat#5 (FLT3-ITD) 0.6 10 5 0.4 0

RelativeGrowthInhibition 0.2 number of colonies per wellper colonies of number 0 0 5 10 20 40 80 160 320 Pat#2 Silvestrol concentration (nM) Pat#3 Pat#4 Samples

Figure 3.1 Antileukemic activity of silvestrol in vitro.

(a) MV4-11 cells were incubated with 5 to 160 nM silvestrol. Cell viability was evaluated by a MTS assay at 24, 48 and 72 hours. (b) AML cell lines were incubated with 5 to 160 nM silvestrol, and viability was evaluated by a MTS assay 48 hours later. (c) AML primary cells unmutated FLT3 or with FLT3-ITD were incubated with 5 to 320 nM silvestrol. Cell viability was evaluated by MTS assay 48 hours following treatment. (d) Colony forming ability in primary blasts from FLT3-ITD positive and negative AML patients treated with 25nM of silvestrol and scored 14 days later.

Silvestrol apoptotic activity in AML primary cells

vehicle 10 nM silv. 30 nM silv. 50 nM silv.

2.5% 10% 3% 17% 5% 33% 5% 32%

wt) -

5.5% 11% 14% 14% Pat#2 (FLT3 Pat#2

3% 1% 10% 11% 22% 16% 15% 23%

ITD) -

4% 11%

14% 20%

Pat#5 (FLT3 Pat#5 Iodide → Iodide

28% 26%

3.5% 4.5% 8% 50% 6.5% 58%

Propidium

ITD -

5% 5% 8% 10% Pat#3 (FLT3 Pat#3

Annexin-FITC →

Figure 3.2 Silvestrol induces apoptosis in primary blasts in vitro.

Primary blasts from FLT3-ITD positive and negative AML patients treated with 10, 30 and 50 nM of silvestrol for 48 hours and analyzed by annexin/PI flow cytometry.

Table 3.1 Calculated IC50 values for AML primary cells and cell lines

* Cell line FLT3 Status IC50 (95% Confidence Intervals)

MV4-11 FLT3-ITD 2.65 nM (1.49 to 4.72)

THP-1 FLT3-wt 3.81 nM (2.46 to 5.09)

Primary cells

Pt #1 FLT3-wt 16.9 nM (13.6 to 21.1)

Pt #2 FLT3-wt 6.61 nM (5.67 to 7.70)

Pt #3 FLT3-ITD 3.65 nM (2.21 to 6.04)

Pt #4 FLT3-ITD 4.89 nM (3.90 to 6.12)

3.3.2 Silvestrol downregulates FLT3 expression through inhibition of FLT3 translation initiation

Silvestrol interferes with assembly of the eIF4F translation complex by promoting an aberrant interaction between capped mRNA and eIF4A, thus inhibiting mRNA translation at the initiation step and therefore blocking protein synthesis (181, 184). This inhibition of protein synthesis results in a preferential depletion of proteins with short half-lives to which leukemia and cancer cells may be addicted (182, 184). While several proteins have been shown to be targeted by silvestrol, whether this compound also inhibits FLT3 initiation of translation resulting in inhibition of FLT3 protein synthesis has

88 not been reported. Thus, using an RNA immunoprecipitation assay, we tested this possibility.

Because of the difficulty immunoprecipitating eIF4A protein for the RNA immunoprecipitation assay using commercially available antibodies, we utilized an antibody against eIF4E, a subunit of the initiation of translation complex that binds the mRNA cap structure. Cells were exposed to silvestrol at concentrations that were higher than the calculated in vitro IC50 but that were also achievable in vivo, and harvested at 24 hours or earlier time points, to avoid interfering with cell death observed with more prolonged drug exposure but still ensure adequate pharmacologic activity (185). MV4-11 cells were treated with 50 nM silvestrol for 3 hours and eIF4E was immunoprecipitated in three different experiments. Associated RNA was then assessed for depletion of FLT3

RNA by quantitative RT-PCR. While no change in FLT3 mRNA levels was observed in total RNA from MV4-11 cells treated with silvestrol compared to vehicle-treated cells, a five-fold depletion of FLT3 mRNA was detected in eIF4E immunoprecipitates from silvestrol-treated cells compared to vehicle-treated cells at 3 hours (Figure 3.3a). This resulted in 54% and 46% reduction in FLT3 receptor expression (by flow cytometry)

(Figure 3.3b) and 92% and 84% reduction in FLT3-ITD or FLT3-wt protein levels (by western blot) respectively in MV4-11 and THP-1 cells, exposed to 50 nM silvestrol for 24 hours, compared to vehicle-treated controls (Figure 3.3c). Since total FLT3 protein levels were almost undetected following silvestrol treatment, we expected phosphorylated FLT3 to be depleted as well. Therefore, the effect of silvestrol on FLT3 kinase activity was determined by measuring phosphorylation of the FLT3 target protein

STAT5. We found a significant decrease in P-STAT5 in MV4-11 cells 24 hours following silvestrol treatment (50nM) (Figure 3.3d). Similarly, we confirmed the effect of silvestrol

89 on FLT3 expression in primary blasts from FLT3-wt and FLT3-ITD patients. We also found down-regulation of FLT3 protein in silvestrol-treated primary blasts regardless of their mutational status (Figure 3.3e). On the mRNA level, and consistent with a sole effect on mRNA translation, silvestrol treatment resulted in increase in FLT3 mRNA levels in FLT3-wt AML cell line and primary blasts (Figure 3.4). However we observed a significant decrease in FLT3 mRNA expression in FLT3-ITD positive cell lines and primary cells and FLT3-wt cell lines treated with 25ng/ml of FLT3 ligand (FL), suggesting that once the receptors are activated by gain-of-function mutations or ligand binding,

FLT3 downregulation may interfere with an autoregulation mechanisms of gene expression (Figure 3.5) (157).

P=0.05 a 1.2 d 1 P-STAT5 0.8 0.6 STAT5

0.4 expression

0.2 Actin Relative FLT3mRNA 0 Untreated Unteated Untreated Silvestrol Silvestrol Silvestrol _ _ input IgG eIF4E input IgG eIF4E 50nM Silvestrol (6h) + + b MV4-11 THP-1 50nM PKC412 (6h) _ _ + +

e Pat#1(FLT3-wt) →

FLT3 Cell count Cell

Actin

FLT3-FITC → Silvestrol 0 10 30 50 Silvestrol: DMSO: conc. (nM) Pat#5(FLT3-ITD) MV4-11 (FLT3-ITD) THP-1 (FLT3-wt) c FLT3 FLT3

GAPDH Actin Silvestrol - + - + - + - + (50nM ) Silvestrol 12h 24h 24h 48h conc. (nM) 0 10 30 50

Figure 3.3 Silvestrol down-regulates FLT3 protein expression.

(a) FLT3 mRNA expression in eIF4E immunoprecipitates from 50 nM silvestrol treated MV4-11 cells compared to that from untreated cells. (b) Expression of FLT3 examined by flow cytometry in MV4-11 and THP-1 cells after 24 hours exposure to 50 nM silvestrol. Blue = silvestrol-treated samples; Red = vehicle-treated control. (c) AML cells treated with 50 nM silvestrol and examined for FLT3 expression by immunoblotting. (d) Primary AML cells incubated with increasing concentrations of silvestrol for 24 hours, and assessed for FLT3 protein expression was by immunoblot. (e) MV4-11 cells treated with silvestrol or PKC-412 (50 nM each) for 6 hours, and assessed for STAT5 phosphorylation by immunoblot.

FLT3 mRNA expression in THP-1 cells FLT3 expression in MV4-11 treated withFig.S2 treated with 50nM silvestrol 50nM Silvestrol for 24h

3 1.2

2.5 1

2 0.8

1.5 0.6

1 0.4

0.5 0.2 0

Relative FLT3 mRNA expression mRNA FLT3 Relative 0 Untreated Silvestrol expression mRNA FLT3 Relative Untreated Silvestrol

FLT3 mRNA expression in FLT3-wt FLT3 mRNA expression in FLT3-ITD primary cells treated with 50nM of primary cells treated with 50nM of silvestrol for 24h * silvestrol for 24h 4 1.2 3.5 1 3 2.5 0.8 * 2 0.6 1.5 0.4 1 0.5 0.2

0 0

Relative FLT3 mRNA expression expression mRNA FLT3 Relative Relative FLT3 mRNA expression expression mRNA FLT3 Relative Untreated Silvestrol Untreated Silvestrol

Figure 3.4 Silvestrol affects FLT3 mRNA expression differently in FLT3-wt and FLT3-ITD AML cells.

THP-1 and MV4-11 cells and FLT3-wt and FLT3-ITD primary blasts were treated with 50nM of silvestrol for 24 hours, and FLT3 mRNA expression was measured thereafter, mRNA expression is normalized to 18S.

FLT3 expression in THP-1 cells treated with silvestrol and FL 0.000025

6h 0.00002 12h

0.000015

0.00001

0.000005

Relative FLT3 mRNA expression mRNA FLT3 Relative 0

Silvestrol - + - + FLT3 Ligand - - + +

Figure 3.5 Silvestrol down-regulates FLT3 mRNA expression in THP-1 cells in the presence of FLT3 ligand.

THP-1 cells treated stimulated with 25ng/ml FL ligand and treated with 50nM of silvestrol for 24 hours, then FLT3 mRNA expression was measure thereafter.

3.3.3 Silvestrol downregulates miR-155 expression in FLT3-ITD positive AML

We reported that miR-155 is up-regulated in FLT3-ITD positive AML compared to

FLT3-wt AML although whether this microRNA directly contributes to the leukemogeneic activity of FLT3-ITD is unknown (46). Having shown that silvestrol downregulated FLT3-

ITD protein, next we tested whether silvestrol also altered the expression of miR-155 that appears co-regulated with FLT3. Thus, miR-155 expression was measured in MV4-

11 cells treated with 50 nM of silvestrol for up to 24 by qRT-PCR. We found approximately a 40-60% decrease in miR-155 expression in silvestrol treated compared to untreated cells as early as 6 hours following the treatment (P=0.05), while no significant change was observed in the expression of an unrelated miRs (i.e., miR-34)

(Figure 3.6a, b and c). We also examined the effect of silvestrol on miR-155 function, we treated MV4-11 cells with 50nM silvestrol and assessed the mRNA expression of the miR-155 target gene PU1 (186). Twenty-four hours following treatment with silvestrol, we observed more than 2 folds increase of PU1 mRNA expression level in treated compared to untreated MV4-11 (P = 0.04) (Figure 3.6d). Similar results were obtained in

FLT3-ITD positive primary blasts; these cells exhibited 80% decrease in miR-155 expression (P = 0.058) and a 2-fold increase in PU1 expression (P= 0.005), 24 hours following treatment with 50 nM of silvestrol compared with untreated cells (Figure 3.6e and 3.6f).

Although, the mechanisms through which constitutively activated FLT3 associates with increased miR-155 expression are unknown. miR-155 has been reported to be regulated by NF-κB, which is also potentially activated in AML blasts with constitutively activated FLT3 (187, 188). Importantly, silvestrol belongs to the rocaglate

94 derivatives, which have been reported to inhibit the activity of NF-κB (178, 189).

Therefore we speculated that silvestrol may influence NF-κB activity and/or protein level.

When we treated MV4-11 and THP-1 cells with 50 nM of silvestrol for 24 hours, we observed decrease in NF-κB (P65) protein expression in silvestrol-treated cells compared with vehicle-treated cells (Figure 3.6g). This suggests that the effect of silvestrol on miR-155 may be independent or only partially dependent of the silvestrol mediated FLT3 inhibition. Nevertheless, the compound effectively targets both the microRNA and the mutant protein that may concurrently contribute to the aggressiveness of FLT3-ITD AML.

a c miR-34a expression in MV4-11 cells 1.2 treated with 50nM silvestrol for 24h

0.8 * * 1.2 * 1

0.6 0.8

155 expression 155 -

34a expression 34a 0.6 0.4 - 0.4 0.2 0.2 0 0

Relative miR Relative untreted Silvestrol

0 6h 12h 24h Relative miR Relative Time of Treatment (hours)

b d PU1 mRNA expression in MV4-11cells miR-155 expression in MV4-11 cells treated with 50nM of silvestrol for 24h treated with 50nM of silvestrol for 24h 1.2 2.5 1 * 2 0.8 * 1.5

155 expression 155 0.6 -

0.4 1

0.2 0.5 Relative miR Relative 0 0 Untreated Silvestrol expression mRNA PU1 Relative Untreated Silvestrol Continued

Figure 3.6 Silvestrol down-regulates miR-155 and upregulates miR-155 target PU1.

(a) MV4-11 cells were treated with 50nM of silvestrol and miR-155 expression was measured and normalized to U44 expression at 6, 12 and 24 hours following silvestrol treatment. (b, c) MV4-11 cells were treated with 50nM of silvestrol for 24 hours, and miR-155 (b) and miR-34a (c) expression was measured thereafter. (d) MV4-11 cells were treated with 50 nM of silvestrol for 24 hours, and PU1 expression was measured thereafter. (e) FLT3-ITD positive primary cells were treated with 50nM of silvestrol for 24 hours, and miR-155 expression was measured thereafter. (f) FLT3-ITD positive primary cells were treated with 50nM of silvestrol for 24 hours, and PU1 expression was measured thereafter. (g) MV4-11 and THP-1 cells were treated with 50nM of silvestrol for 24 hours and assessed for P65 protein expression by immunoblot.

Figure 3.7 Continued

e miR-155 expression in FLT3-ITD primary f PU1 mRNA expression in FLT3-ITD primary cells treated with 50nM of silvestrol for 24h cells treated with 50nM of silvestrol for 24h 1.6 2 * 1.4 1.8 1.2 1.6 1.4 1

1.2 155 expression 155 - 0.8 1 * 0.6 0.8 0.6 0.4 * 0.4 0.2 0.2 Relative miR Relative 0 0 Untreated Silvestrol expression mRNA PU1 Relative Untreated Silvestrol

MV4-11 (FLT3-ITD) THP-1 (FLT3-wt) 1 0.59 1 0.43

P65

Actin

50nM Silvestrol (24h) - + - +

3.3.4 Activity of silvestrol in FLT3-ITD positive leukemia grafts

To investigate the in vivo efficacy of silvestrol in AML we employed MV4-11 leukemia graft murine model. NSG mice were subjected to secondary transplant with

MV4-11 cells harvested from the spleen of previous MV4-11 engrafted mice that developed an aggressive AML-like disease. Twenty-one days post-engraftment, mice were treated intraperitoneally with vehicle (Group 1) or 1.5 mg/kg silvestrol (Group 2) every other day for 3 weeks. The silvestrol dose and schedule used here were previously reported for lymphoid leukemia models (182, 190). Forty-eight hours following the first two doses, blood samples with circulating MV4-11 cells were taken from 3 mice from each group, and FLT3 expression was assessed by flow cytometry. A two- and three-fold increase in FLT3 expression was observed in vehicle-treated mice

48 hours after the first (P=0.07) and second (P=0.024) treatment doses compared with pretreatment baseline, while no significant change was found in the silvestrol treatment group (Figure 3.7a). After 3 doses (day 6 of treatment), spleens from three mice from each group were examined. Spleens from silvestrol treated mice were 60% smaller

(P=0.016) and showed an 80% reduction in FLT3 protein (P=0.002) compared to vehicle-treated controls (Figure 3.7b, c). Cytospins of bone marrow cells and histopathology of bone marrow (sternum), spleen, and liver sections from MV4-11- engrafted mice treated with vehicle showed extensive infiltration of blast cells. In contrast, cytospins from silvestrol-treated leukemic mice were similar to those of the age-matched control mice with some differentiated blasts (Figure 3.7d, e). Silvestrol- treated leukemic mice (n=10) survived significantly longer than the vehicle-treated controls (n=6) (median survival: 63 days from engraftment vs. 29 days, respectively;

P<0.0001). All mice in the vehicle group died by day 31 from engraftment (day 11 from 98 treatment start), while 50% of silvestrol-treated mice were still alive on day 74 from engraftment (day 54 from treatment start) (Figure 3.7f). Of the silvestrol-treated mice,

30% were still alive at 6 months from experiment start day. When sacrificed, these survived mice showed no signs of leukemia.

P= 0.02 d a pre-dose 2.5 CONTROL 2 48h (after 1 dose) 1.5 1 48h (after 2 doses ) 0.5

0 P= 0.016 (fluorescence)

FLT3 expression expression FLT3 Vehicle Silvestrol VEHICLE b 250 200 150 VEHICLE 100 * 50 SILVESTROL

0 Spleen weight (mg) SILVESTROL c FLT3 e CONTROL UNTREATED SILVESTROL Actin

Neg BONE MARROW vehicle Silvestrol f control STERNUM 110 100 Vehicle 90 Silvestrol LIVER 80 P =<0.0001 70 60 50 Silvestrol (n=10) 40 30 Percent Percent survival 20 Vehicle (n= 6) SPLEEN 10 0 0 25 50 75 100 125 150 175 200 Days

Figure 3.8 In vivo antileukemic activity of silvestrol in FLT3-ITD positive MV4-11 xenograft leukemia mouse model.

NSG mice were engrafted with MV4-11 cells from a previously engrafted NSG mouse. (a) FLT3 expression by flow cytometry evaluated 48 hours after 1st and 2nd doses. (b) spleens size after 3 silvestrol doses (day 6 of treatment) (c) Immunoblot of FLT3 protein expression in spleens from silvestrol-treated mice and vehicle-treated controls. (d) Cytospins of bone marrow cells and (e) histopathology of bone marrow (sternum), spleen, and liver from the silvestrol-treated leukemic mice and age-matched (non- leukemic) control mice. (f) Survival analysis of silvestrol-treated leukemic mice (N=10) compared to the vehicle-treated controls (N=6).

100

3.4 Discussion

The natural product silvestrol has been shown to inhibit translation initiation by modulating the interaction of capped mRNA with the RNA helicase eIF4A (184). Proto- oncogenes such as CCND1, MCL1, and MYC tend to encode proteins with short half- lives, and are therefore more dependent on active translation to maintain protein levels that support malignant cell growth and survival. Such factors and in turn cancer cells addicted to them, are thus expected to be more sensitive to translation inhibition by silvestrol, as was recently reported (181-183, 190). To our knowledge, the effect of silvestrol on FLT3 expression has not been previously reported. Here we report that silvestrol also inhibits FLT3 mRNA translation thereby causing depletion of the encoded oncoprotein, inhibition of the protein‘s aberrant tyrosine kinase activity. Silvestrol caused growth arrest and apoptosis in AML cell lines and primary blasts treated at nanomolar concentrations. These results therefore extend the list of the oncoproteins targeted by silvestrol and support the antileukemia activity of this compound.

It is expected that interference with translational initiation complex would results in depletion of target proteins, without substantial changes in the encoding mRNAs.

Indeed, we noted this in THP-1 cells. In contrast, in MV4-11, THP-1 stimulated with FL and primary blast expressiong FLT3-ITD, we noted a significant decrease in FLT3 mRNA following silvestrol treatment. This suggested that activated FLT3 autoregulates its transcription in these cells. The mechanism of this phenomenon is not completely understood. However, STAT and /or NFκB proteins may contribute to this mechanism,

101 both proteins are constitutively active in FLT3-ITD cells, and their ectopic expression have been reported to upregulate FLT3 mRNA (191) (192)(Onai 2006) (blum 2012).

Most importantly, we showed a remarkable in vivo activity of silvestrol in a FLT3-

ITD leukemia engraftment model. Mice engrafted with adapted MV4-11 cells developed leukemia and had a median survival of only 4 weeks. Treatment with silvestrol had no obvious toxicity and lowered the FLT3 expression to undetectable levels after administration of only three doses. Silvestrol treatment significantly prolonged survival and even cured approximately 30% of the animals, further reinforcing the concept that pursuing suppression of the FLT3-ITD protein expression may be a valid therapeutic approach in FLT3-driven AML. Recently, there has been an increased interest in utilizing small molecule kinase inhibitors to target aberrant TK activity of FLT3 mutants that contribute to leukemia growth and poor outcome in AML patients (193).

Unfortunately, the lack of selectivity, inadequate pharmacokinetics, and early onset of resistance resulted in relatively disappointing outcomes with these agents (194, 195).

Nevertheless, FLT3 down-regulation via siRNA has been shown to result in growth inhibition and apoptosis in FLT3-ITD-positive AML cells (187, 196). This implicates that interfering not only with aberrant activity of this kinase but also with FLT3 expression might be a useful therapeutic strategy in AML. Thus drugs, like silvestrol, that have the ability to decrease the expression of FLT3 may be clinically useful in this distinct subset of AML addicted to the FLT3 aberrant TK activity.

Although activity of silvestrol on the FLT3 expression was impressive, it is likely that silvestrol as a natural product and an inhibitor of eIF4A has the ability to alter the

102 expression and activity of several other targets that may contribute to the impairment of leukemia growth. Nevertheless, the antileukemia activity of this natural product may result specific for those FLT3-driven molecular subsets of AML that are resistant to chemotherapy and/or enzymatic kinase inhibitors. To this end, we not only showed silvestrol-related FLT3 suppression, but also downregulation of miR-155, an oncomiR whose expression is likely regulated by NFκB often found constitutively activated in

FLT3-driven AML (197, 198). This microRNA has been shown to be upregulated in

FLT3-ITD positive AML, and is thought to contribute to leukemia growth and aggressiveness in these molecular subsets of AML (23, 48). Thus the dual activity of silvestrol on FLT3 and miR-155 expression in FLT3-ITD positive cells suggests that this compound may represent a potentially valuable therapeutic approach to this high-risk

AML.

In conclusion, we showed that silvestrol is a compound with a potent antileukemia activity in FLT3-driven AML. These results thereby provide a novel therapeutic strategy in FLT3-driven AML by a novel mechanism that is not based on the disruption of the aberrant tyrosine kinase activity through enzymatic TK inhibition, but rather it is effective via translation inhibition of FLT3 mRNA. Given these and other previously published findings (182, 190), silvestrol is now under preclinical development in the

National Cancer Institute‘s NExT Program for a rapid translation into the clinic.

103

Chapter 4 : Summary and Future Directions

AML is the most common and deadly type of leukemia in adults. The lifetime risk of this disease is 1 in 254 (men and women)(2) and only 10-50% of AML patients achieve long-term survival (4). AML is a heterogeneous clonal disorder characterized by the aberrant proliferation and block of differentiation and maturation of leukemic progenitors and precursor cells called blast (199). Accumulation of somatically acquired genetic alterations in hematopoietic progenitor and stem cells transform these cells into leukemia initiating cells with hallmark properties that define their malignant status such as: self-renewal, limitless proliferation potential and block of differentiation and apoptosis

(200, 201). In recent years, identification of gene mutations and deregulated expression of genes and noncoding RNAs (ie, microRNAs) provided enormous insights into the mechanisms of leukemogenesis and unraveled the molecular genetic heterogeneity within distinct cytogenetically defined subsets of AML, in particular the large group of cytogenetically normal (CN) AML (202). Several signaling pathways have been also identified in AML and found implicated not only in the pathophysiology of the disease, but also in the prognosis and response to treatment.

Despite this progress, AML research has gone through in the last decade, this progress was not correlated with rewarding corresponding improvement with regard to patient‗s outcome. In fact, the major progress made in AML therapeutic have not been

104 due to the introduction of new therapeutic agents but rather the more optimal use of previously used chemotherapy (e.g., high-dose cytarabine therapy) as well as to better supportive therapy (control of bacterial and fungal infections and hemorrhagic events)

The improvement of survival rates related to allogeneic and autologous transplantation has also accounted for the improvement of overall survival of AML patients (203). This lack of direct cause-effect relationship between the progress in basic research and the improvement of patient‘s outcome observed in AML is likely due to several disease characteristics.

AML is very heterogeneous disease with regard to clinical and morphological features, and cytogenetic abnormalities and gene mutations and expression. Therefore, it is projected that patients respond differently to treatment and thus have extremely variable survival rates, ranging from several days to complete recovery. Furthermore, representing a medical emergency in most cases, requiring immediate medical intervention; is a critical challenge that faces introducing new individualized therapy based on genetic or molecular findings at diagnosis. Therefore, the application of molecularly or cytogenetic analysis at induction is currently considered to address post- remission therapy only, specifically to identify patients with need for allogeneic stem cell transplantation (1).

An ideal targeted therapy as a replacement of the induction therapy is expected to inhibit key pathways of leukemogenesis, eradicate the leukemic clone and restore normal hematopoiesis (203). However, the large number of different cytogenetic, genetic, and molecular abnormalities makes the individualized treatment of AML a

105 challenging objective. In addition, genetic aberrations associated with AML are not mutually exclusive and often coexist in the leukemic cells of the single patient. More importantly, we are still far from identifying and distinguishing the somatic alterations imperative in tumor initiation and progression from passenger mutations resulting from genomic instability of leukemic cell. Therefore, it may not be a realistic on the short term to aim for identifying a new single agent that ultimately eliminates the leukemic clone and efficiently restores the normal hematopoiesis. Instead a combination of several new drugs or conventional chemotherapy could represent a more effective and potentially curative strategy.

The work we presented here focused on two objectives, first: identification of novel molecular targets (i.e. SPARC) in AML (chapter 2). Second: investigating novel approaches (i.e. Silvestrol) to target previously identified molecular targets (i.e. FLT3) in

AML (chapter 3).

In summary of the first objective, we utilized recently published GEP data to identify new molecular targets that have not been studied in AML before. We found

SPARC to be upregulated in several GEPs associated with worse outcome in CN-AML patients. SPARC was among the most upregulated genes associated with IDH2-R172 mutation and among the most downregulated genes associated with NPM1 mutations.

These observations indicated a previously unidentified proleukemic contribution of

SPARC in AML. Altered SPARC expression has been reported in different types of cancer, but its role in AML remained unknown. In chapter 2 we showed that SPARC promoted AML growth in vitro, aggressive disease in vivo, and worse outcome in CN-

106

AML patients. SPARC activity was mediated by activation of ILK-AKT-GSK3 pathways and in turn, -catenin, a protein required for leukemia stemness. Consistently, SPARC overexpression was associated with gene and microRNA profiles comprising upregulated stem cell markers. Analyzing the function of RUNX1 and IDH2-R172 mutations associated with SPARC overexpression and poor outcome in AML, revealed

NF-κB/SP1 transactivation as the likely mechanism for SPARC upregulation. These data suggest that SPARC is a novel prognosticator and a potential therapeutic target in AML.

We expect this work to have significant diagnostic, prognostic, and therapeutic implications in AML. SPARC upregulation identifies a novel subset of CN-AML that are more likely to harbor IDH2-R172, RUNX1, or deregulation of the NF-κB/SP1 and miR-

29b molecular network. Furthermore, SPARC association with negative clinical outcome makes measuring this protein levels at diagnosis prognostically informative. Being a secreted protein permits feasible and fast quantification techniques (i.e, ELISA based assays) to be utilized for SPARC levels assessments at diagnosis. Further research will be needed in order to obtain meaningful guidelines for serum SPARC levels.

Additionally, we demonstrated that SPARC links the upstream NF-κB/SP1/miR-

29b deregulation with its downstream targets: ILK/AKT/β-catenin. Therefore several therapeutic approaches can be investigated in patients with high SPARC expression.

Some of these approaches include: 1- Intervention with SPARC upstream network utilizing pharmacological disruption of NF-κB/SP1 with Bortizomib or synthetic miR-29b.

2- Direct interference with SPARC expression and/or activity via SPARC antibodies based treatment, or proteases based therapy that results in SPARC digestion and therefore inhibition of its activity. 3- Intervention with SPARC downstream targets utilizing integrins antibodies, ILK inhibitors, AKT or β-catenin inhibitors. 107

Supported by in vitro and in vivo experimental evidence, we demonstrated that

SPARC promoted growth advantage and aggressive disease in AML cells and AML mouse model respectively. This work revealed SPARC as a novel molecular contributor to AML aggressiveness and progression. Although, ectopic SPARC expression in normal CD34+ cells resulted in c-Myc and CyclinD1 mRNA upregulation (Figure 4.1), it was not sufficient to transform these cells; suggesting that SPARC requires other hits or activated pathways in order to enhance the leukemogenic potential of AML cells. Further research will be needed to identify the different molecular targets that interact with

SPARC and account for its role in AML. Introducing mutations such as RAS, FLT3-ITD or KIT along with ectopic expression of SPARC will be an initial approach to answer some of these questions.

P=0.03 P=0.002

2.5 2.5

2 2

1.5 1.5

mRNA expressionmRNA 1

mRNA mRNA expression

MYC -

CyclinD1 0.5 C 0.5

0 0 CBC plenti-EV CBC plenti-SPARC CBC plenti-EV CBC plenti-SPARC

Figure 4.1 SPARC upregulates c-Myc and CyclinD1 mRNA expression in CD34+ cells isolated from cord blood cells.

108

In addition, we demonstrated that SPARC upregulation in AML results from activation of NF-κB and SP1 complex and acts through activating ILK, AKT and β- catenin signaling pathways. As a result SPARC represent a cross-link between the NF-

κB and AKT/β-catenin pathways, both are crucial for leukemic stem cell survival and self-renewal. In melanoma, ILK also altered the activity and subcellular localization of nuclear NF-κB subunit p65; whether similar effect occurs in AML is still unknown (204).

However, it is possible that SPARC is key protein in the regulatory loop of NF-κB/ILK found to be activated in several cancer types, and therefore disruption of this loop can be achieved by targeting SPARC expression or activity.

We speculate that several other matricellular protein might play similar role to the one we reported for SPARC. Osteopontin (OPN) is also a matricellular protein found to be upregulated in AML patients compared to healthy donors and also associated with worse outcome in AML patients (205). Therefore expanding this work to other matricellular protein may provide better understanding to this new class of proto- oncogenes and their clinical and biological impacts.

While the first objective of our work focused on identification of previously unknown prognostic markers and molecular targets in AML, the second objective was directed toward investigating novel therapeutic approaches that target previously known ones. As we mentioned in previous chapter, overexpression and/or activating mutations

[i.e., ITD] of the FLT3 are among cytogenetic and molecular aberrations that have an unfavorable prognostic significance for both younger and older AML patients treated with conventional chemotherapy. This substantiates the need for novel therapeutic approaches in this molecular subset of patients. However, the use of emerging small

109 molecule inhibitors of the enzymatic kinase activity of the FLT3 protein, albeit promising, is limited by early onset of mechanisms of resistance. We showed in chapter 3 that silvestrol, a natural product from Aglaia foveolata had a potent anti-leukemia activity in

AML cells including those with FLT3-ITD and FLT3 overexpression. Silvestrol induced down-regulation of the FLT3 gene expression and in turn inhibition of tyrosine kinase activity. FLT3 protein downregulation occurred via inhibition of mRNA translation, a mechanism that has also been reported to mediate downregulation of other proteins that contribute to malignant growth and survival (i.e., MYC and MCL1). Remarkably, silvestrol significantly prolonged survival and even cured approximately 30% of mice engrafted with FLT3-ITD positive compared to vehicle-treated controls.

Because of the remarkable antileukemic activity of silvestrol in FLT3-ITD positive

AML, we asked whether this activity is valid in other mutant or upregulated RTKs in

AML. Similar to FLT3, KIT is frequently mutated and/or upregulated in AML. To examine the activity of silvestrol in KIT mutant AML, we tested silvestrol cytotoxicity in Kasumi-1 cells (KIT mutant AML cells) by MTS assay. We showed that silvestrol reduced the viability of Kasumi-1 cells in a time and dose dependent manner with IC50 of 7.53 nM at

48 hours. A dose dependent increase in Annexin staining in the treated Kasumi-1 cells when cells were treated with 0, 10, 30, and 50 nM silvestrol for 48 hours was observed suggesting an apoptosis mediated cytotoxicity of silvestrol (Figure 4.2a). To determine whether KIT expression is affected by silvestrol treatment, we treated Kasumi-1 cells with 50nM of silvestrol for 24 hours; KIT protein level then was evaluated by western blot. We found a significant decrease in KIT expression in Kasumi-1 cells (46%) in silvestrol treated cells when compared to the untreated (Figure 4.2b).

110

To evaluate the in vivo efficacy of silvestrol in KIT mutant AML, KIT mut FCD-

P1(D816V) xenograft mouse model was selected to evaluate the in vivo efficacy of silvestrol in AML with KIT mutation. NOD-SCID Gamma (NSG) mice were engrafted with

KIT mut FCD-P1(D816V). Twenty-one days post-engraftment, mice were also treated intraperitoneally with vehicle or silvestrol (1.5 mg/kg every 48 hr for 3 weeks). After 3 doses (day 6 of treatment), spleens were obtained from three mice from each group.

Spleens from silvestrol treated mice were 53% decreased in size (P=0.02) (Figure 4.2c).

Interestingly, cytospins of bone marrow cells from silvestrol treated mice looked similar to cells from NSG-control mice and showed signs of differentiation compared to bone marrow cells obtained from vehicle treated mice (Figure 4.2d). Silvestrol treated leukemic mice (n=8) survived significantly longer than vehicle treated control (n=6)

(median survival: 35.5 vs. 29 days from engraftment day respectively; P=0.002). All vehicle-treated mice died by day 31 from engraftment (day 11 from treatment start), while 50% of silvestrol-treated mice are still alive on day 35 from engraftment (day 15 from treatment start) (Figure 4.2e).

111

KASUMI-1

a vehicle 10 nM silv. 30 nM silv. 50 nM silv.

Iodide → Iodide Propidium Annexin-FITC →

d NSG-CONTROL VEHICLE SILVESTROL b KASUMI-1

KIT

Actin

Silvestrol - + (50nM 24hr) c e

160 VEHICLE 140 120 100 * 80 60 SILVESTROL 40

Spleen weight (mg) weight Spleen 20 Log-rank (Mantel-Cox) Test 0 Vehicle N=6 P = 0.0027 Silvestrol N=8

Figure 4.2 In vitro and In vivo antileukemic activity of silvestrol in KIT mutant AML.

Kasumi-1 cells treated with 10, 30 and 50 nM of silvestrol for 48 hours and analyzed by annexin/PI flow cytometry (a). Kasumi-1 cells treated with 50 nM silvestrol and examined for KIT protein expression by immunoblotting (b), NSG mice were engrafted with KIT mut FCD-P1(D816V) cells from a previously engrafted NSG mouse. Spleens size after 3 silvestrol doses (day 6 of treatment) (c) Cytospins of bone marrow cells and (d) Survival analysis of silvestrol-treated leukemic mice (N=8) compared to the vehicle-treated controls (N=6) (e).

112

We conclude that silvestrol has a potent in vitro and in vivo antileukemic activity in AML through downregulation of the expression and activity of FLT3 and other TKs driving leukemia. Given the excellent antileukemic activity of silvestrol via a novel mechanism of TK inhibition that is potentially complementary to that of TKIs (i.e., silvestrol-induced suppression of TK protein expression vs. TKI-induced protein enzymatic inhibition), a rapid translation of this natural product to the clinic as a single agent or in combination with other TKIs ± chemotherapy seems warranted.

To sum up, we identified an original molecular target with novel biological insights, and investigated innovative therapeutic approaches suitable for high risk subsets of AML. This research will significantly advance understanding of AML and open new avenues of treatment strategies, which will result in optimized patient care, and improved clinical outcome for high risk patients.

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References

1. O'Donnell MR, Abboud CN, Altman J, Appelbaum FR, Arber DA, Attar E, et al. Acute myeloid leukemia. Journal of the National Comprehensive Cancer Network : JNCCN. 2012;10(8):984-1021. 2. SEER Stat Fact Sheets: Acute Myeloid Leukemia. http://seer.cancer.gov/statfacts/html/amyl.html: National Cancer Institute; [cited 2012 October 16]. 3. Siegel R, DeSantis C, Virgo K, Stein K, Mariotto A, Smith T, et al. Cancer treatment and survivorship statistics, 2012. CA: a cancer journal for clinicians. 2012;62(4):220-41. 4. Estey E, Dohner H. Acute myeloid leukaemia. Lancet. 2006;368(9550):1894-907. Epub 2006/11/28. 5. Travis LB, Li CY, Zhang ZN, Li DG, Yin SN, Chow WH, et al. Hematopoietic malignancies and related disorders among benzene-exposed workers in China. Leukemia & lymphoma. 1994;14(1-2):91-102. 6. Kane EV, Roman E, Cartwright R, Parker J, Morgan G. Tobacco and the risk of acute leukaemia in adults. British journal of cancer. 1999;81(7):1228-33. 7. Smith M, Barnett M, Bassan R, Gatta G, Tondini C, Kern W. Adult acute myeloid leukaemia. Critical reviews in oncology/hematology. 2004;50(3):197-222. 8. Leone G, Pagano L, Ben-Yehuda D, Voso MT. Therapy-related leukemia and myelodysplasia: susceptibility and incidence. Haematologica. 2007;92(10):1389-98. 9. Pagana L, Pulsoni A, Tosti ME, Avvisati G, Mele L, Mele M, et al. Clinical and biological features of acute myeloid leukaemia occurring as second malignancy: GIMEMA archive of adult acute leukaemia. British journal of haematology. 2001;112(1):109-17. 10. Pulsoni A, Pagano L, Lo Coco F, Avvisati G, Mele L, Di Bona E, et al. Clinicobiological features and outcome of acute promyelocytic leukemia occurring as a second tumor: the GIMEMA experience. Blood. 2002;100(6):1972-6. 11. Sandler DP, Ross JA. Epidemiology of acute leukemia in children and adults. Seminars in oncology. 1997;24(1):3-16. 12. Owen C, Barnett M, Fitzgibbon J. Familial myelodysplasia and acute myeloid leukaemia--a review. British journal of haematology. 2008;140(2):123-32. 13. Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114(5):937-51. 14. Bennett JM, Catovsky D, Daniel MT, Flandrin G, Galton DA, Gralnick HR, et al. Proposals for the classification of the acute leukaemias. French-American-British (FAB) co-operative group. British journal of haematology. 1976;33(4):451-8. 15. Kelly LM, Gilliland DG. Genetics of myeloid leukemias. Annual review of genomics and human genetics. 2002;3:179-98. 16. Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100(7):2292-302. 17. Grimwade D, Walker H, Oliver F, Wheatley K, Harrison C, Harrison G, et al. The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients

114 entered into the MRC AML 10 trial. The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood. 1998;92(7):2322-33. 18. Mrozek K, Marcucci G, Paschka P, Whitman SP, Bloomfield CD. Clinical relevance of mutations and gene-expression changes in adult acute myeloid leukemia with normal cytogenetics: are we ready for a prognostically prioritized molecular classification? Blood. 2007;109(2):431-48. 19. Gaidzik V, Dohner K. Prognostic implications of gene mutations in acute myeloid leukemia with normal cytogenetics. Seminars in oncology. 2008;35(4):346-55. 20. Mrozek K, Heerema NA, Bloomfield CD. Cytogenetics in acute leukemia. Blood reviews. 2004;18(2):115-36. 21. Dohner H, Estey EH, Amadori S, Appelbaum FR, Buchner T, Burnett AK, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood. 2010;115(3):453-74. Epub 2009/11/03. 22. Schlenk RF, Dohner K, Krauter J, Frohling S, Corbacioglu A, Bullinger L, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. The New England journal of medicine. 2008;358(18):1909-18. 23. Whitman SP, Maharry K, Radmacher MD, Becker H, Mrozek K, Margeson D, et al. FLT3 internal tandem duplication associates with adverse outcome and gene- and microRNA-expression signatures in patients 60 years of age or older with primary cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. Blood. 2010;116(18):3622-6. Epub 2010/07/27. 24. Whitman SP, Ruppert AS, Radmacher MD, Mrozek K, Paschka P, Langer C, et al. FLT3 D835/I836 mutations are associated with poor disease-free survival and a distinct gene-expression signature among younger adults with de novo cytogenetically normal acute myeloid leukemia lacking FLT3 internal tandem duplications. Blood. 2008;111(3):1552-9. 25. Santos FP, Jones D, Qiao W, Cortes JE, Ravandi F, Estey EE, et al. Prognostic value of FLT3 mutations among different cytogenetic subgroups in acute myeloid leukemia. Cancer. 2011;117(10):2145-55. 26. Bacher U, Haferlach C, Kern W, Haferlach T, Schnittger S. Prognostic relevance of FLT3-TKD mutations in AML: the combination matters--an analysis of 3082 patients. Blood. 2008;111(5):2527-37. 27. Falini B, Mecucci C, Tiacci E, Alcalay M, Rosati R, Pasqualucci L, et al. Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. The New England journal of medicine. 2005;352(3):254-66. 28. Dohner K, Schlenk RF, Habdank M, Scholl C, Rucker FG, Corbacioglu A, et al. Mutant nucleophosmin (NPM1) predicts favorable prognosis in younger adults with acute myeloid leukemia and normal cytogenetics: interaction with other gene mutations. Blood. 2005;106(12):3740-6. 29. Falini B, Nicoletti I, Martelli MF, Mecucci C. Acute myeloid leukemia carrying cytoplasmic/mutated nucleophosmin (NPMc+ AML): biologic and clinical features. Blood. 2007;109(3):874-85. 30. Frohling S, Schlenk RF, Stolze I, Bihlmayr J, Benner A, Kreitmeier S, et al. CEBPA mutations in younger adults with acute myeloid leukemia and normal cytogenetics: prognostic relevance and analysis of cooperating mutations. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2004;22(4):624-33. 115

31. Pabst T, Mueller BU, Zhang P, Radomska HS, Narravula S, Schnittger S, et al. Dominant-negative mutations of CEBPA, encoding CCAAT/enhancer binding protein- alpha (C/EBPalpha), in acute myeloid leukemia. Nature genetics. 2001;27(3):263-70. 32. Abbas S, Lugthart S, Kavelaars FG, Schelen A, Koenders JE, Zeilemaker A, et al. Acquired mutations in the genes encoding IDH1 and IDH2 both are recurrent aberrations in acute myeloid leukemia: prevalence and prognostic value. Blood. 2010;116(12):2122-6. 33. Chotirat S, Thongnoppakhun W, Promsuwicha O, Boonthimat C, Auewarakul CU. Molecular alterations of isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) metabolic genes and additional genetic mutations in newly diagnosed acute myeloid leukemia patients. Journal of hematology & oncology. 2012;5:5. 34. Marcucci G, Maharry K, Wu YZ, Radmacher MD, Mrozek K, Margeson D, et al. IDH1 and IDH2 gene mutations identify novel molecular subsets within de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2010;28(14):2348-55. 35. Paschka P, Schlenk RF, Gaidzik VI, Habdank M, Kronke J, Bullinger L, et al. IDH1 and IDH2 mutations are frequent genetic alterations in acute myeloid leukemia and confer adverse prognosis in cytogenetically normal acute myeloid leukemia with NPM1 mutation without FLT3 internal tandem duplication. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2010;28(22):3636-43. 36. Chou WC, Hou HA, Chen CY, Tang JL, Yao M, Tsay W, et al. Distinct clinical and biologic characteristics in adult acute myeloid leukemia bearing the isocitrate dehydrogenase 1 mutation. Blood. 2010;115(14):2749-54. 37. Chou WC, Lei WC, Ko BS, Hou HA, Chen CY, Tang JL, et al. The prognostic impact and stability of Isocitrate dehydrogenase 2 mutation in adult patients with acute myeloid leukemia. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK. 2011;25(2):246-53. 38. Mardis ER, Ding L, Dooling DJ, Larson DE, McLellan MD, Chen K, et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. The New England journal of medicine. 2009;361(11):1058-66. 39. Ley TJ, Ding L, Walter MJ, McLellan MD, Lamprecht T, Larson DE, et al. DNMT3A mutations in acute myeloid leukemia. The New England journal of medicine. 2010;363(25):2424-33. 40. Marcucci G, Metzeler KH, Schwind S, Becker H, Maharry K, Mrozek K, et al. Age-related prognostic impact of different types of DNMT3A mutations in adults with primary cytogenetically normal acute myeloid leukemia. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2012;30(7):742-50. 41. Markova J, Michkova P, Burckova K, Brezinova J, Michalova K, Dohnalova A, et al. Prognostic impact of DNMT3A mutations in patients with intermediate cytogenetic risk profile acute myeloid leukemia. European journal of haematology. 2012;88(2):128-35. 42. Renneville A, Boissel N, Nibourel O, Berthon C, Helevaut N, Gardin C, et al. Prognostic significance of DNA methyltransferase 3A mutations in cytogenetically normal acute myeloid leukemia: a study by the Acute Leukemia French Association. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK. 2012;26(6):1247-54. 43. Shipley JL, Butera JN. Acute myelogenous leukemia. Experimental hematology. 2009;37(6):649-58. Epub 2009/05/26. 116

44. Mrozek K, Radmacher MD, Bloomfield CD, Marcucci G. Molecular signatures in acute myeloid leukemia. Current opinion in hematology. 2009;16(2):64-9. 45. Marcucci G, Maharry K, Radmacher MD, Mrozek K, Vukosavljevic T, Paschka P, et al. Prognostic significance of, and gene and microRNA expression signatures associated with, CEBPA mutations in cytogenetically normal acute myeloid leukemia with high-risk molecular features: a Cancer and Leukemia Group B Study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2008;26(31):5078-87. 46. Garzon R, Volinia S, Liu CG, Fernandez-Cymering C, Palumbo T, Pichiorri F, et al. MicroRNA signatures associated with cytogenetics and prognosis in acute myeloid leukemia. Blood. 2008;111(6):3183-9. 47. Jongen-Lavrencic M, Sun SM, Dijkstra MK, Valk PJ, Lowenberg B. MicroRNA expression profiling in relation to the genetic heterogeneity of acute myeloid leukemia. Blood. 2008;111(10):5078-85. 48. Garzon R, Garofalo M, Martelli MP, Briesewitz R, Wang L, Fernandez-Cymering C, et al. Distinctive microRNA signature of acute myeloid leukemia bearing cytoplasmic mutated nucleophosmin. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(10):3945-50. 49. O'Connell RM, Rao DS, Chaudhuri AA, Boldin MP, Taganov KD, Nicoll J, et al. Sustained expression of microRNA-155 in hematopoietic stem cells causes a myeloproliferative disorder. The Journal of experimental medicine. 2008;205(3):585-94. 50. Becker H, Marcucci G, Maharry K, Radmacher MD, Mrozek K, Margeson D, et al. Favorable prognostic impact of NPM1 mutations in older patients with cytogenetically normal de novo acute myeloid leukemia and associated gene- and microRNA- expression signatures: a Cancer and Leukemia Group B study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2010;28(4):596- 604. 51. Swaroop A, Hogan BL, Francke U. Molecular analysis of the cDNA for human SPARC/osteonectin/BM-40: sequence, expression, and localization of the gene to chromosome 5q31-q33. Genomics. 1988;2(1):37-47. 52. Framson PE, Sage EH. SPARC and tumor growth: where the seed meets the soil? Journal of cellular biochemistry. 2004;92(4):679-90. 53. Lane TF, Sage EH. The biology of SPARC, a protein that modulates cell-matrix interactions. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 1994;8(2):163-73. 54. Motamed K. SPARC (osteonectin/BM-40). The international journal of biochemistry & cell biology. 1999;31(12):1363-6. 55. Bradshaw AD, Sage EH. SPARC, a matricellular protein that functions in cellular differentiation and tissue response to injury. The Journal of clinical investigation. 2001;107(9):1049-54. 56. Bornstein P, Sage EH. Matricellular proteins: extracellular modulators of cell function. Current opinion in cell biology. 2002;14(5):608-16. 57. Mendis DB, Ivy GO, Brown IR. SPARC/osteonectin mRNA is induced in blood vessels following injury to the adult rat cerebral cortex. Neurochemical research. 1998;23(8):1117-23. 58. Podhajcer OL, Benedetti LG, Girotti MR, Prada F, Salvatierra E, Llera AS. The role of the matricellular protein SPARC in the dynamic interaction between the tumor and the host. Cancer metastasis reviews. 2008;27(4):691-705. 117

59. Reed MJ, Puolakkainen P, Lane TF, Dickerson D, Bornstein P, Sage EH. Differential expression of SPARC and thrombospondin 1 in wound repair: immunolocalization and in situ hybridization. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society. 1993;41(10):1467-77. 60. Maurer P, Hohenadl C, Hohenester E, Gohring W, Timpl R, Engel J. The C- terminal portion of BM-40 (SPARC/osteonectin) is an autonomously folding and crystallisable domain that binds calcium and collagen IV. Journal of molecular biology. 1995;253(2):347-57. 61. Sage H, Johnson C, Bornstein P. Characterization of a novel serum albumin- binding glycoprotein secreted by endothelial cells in culture. The Journal of biological chemistry. 1984;259(6):3993-4007. 62. Yan Q, Sage EH. SPARC, a matricellular glycoprotein with important biological functions. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society. 1999;47(12):1495-506. 63. Nagaraju GP, Sharma D. Anti-cancer role of SPARC, an inhibitor of adipogenesis. Cancer treatment reviews. 2011;37(7):559-66. 64. Sage EH, Reed M, Funk SE, Truong T, Steadele M, Puolakkainen P, et al. Cleavage of the matricellular protein SPARC by matrix metalloproteinase 3 produces polypeptides that influence angiogenesis. The Journal of biological chemistry. 2003;278(39):37849-57. 65. Lau CP, Poon RT, Cheung ST, Yu WC, Fan ST. SPARC and Hevin expression correlate with tumour angiogenesis in hepatocellular carcinoma. The Journal of pathology. 2006;210(4):459-68. 66. Yamashita K, Upadhay S, Mimori K, Inoue H, Mori M. Clinical significance of secreted protein acidic and rich in cystein in esophageal carcinoma and its relation to carcinoma progression. Cancer. 2003;97(10):2412-9. 67. Gilmour DT, Lyon GJ, Carlton MB, Sanes JR, Cunningham JM, Anderson JR, et al. Mice deficient for the secreted glycoprotein SPARC/osteonectin/BM40 develop normally but show severe age-onset cataract formation and disruption of the lens. The EMBO journal. 1998;17(7):1860-70. 68. Norose K, Clark JI, Syed NA, Basu A, Heber-Katz E, Sage EH, et al. SPARC deficiency leads to early-onset cataractogenesis. Investigative ophthalmology & visual science. 1998;39(13):2674-80. 69. Yan Q, Clark JI, Wight TN, Sage EH. Alterations in the lens capsule contribute to cataractogenesis in SPARC-null mice. Journal of cell science. 2002;115(Pt 13):2747-56. 70. Bradshaw AD, Puolakkainen P, Dasgupta J, Davidson JM, Wight TN, Helene Sage E. SPARC-null mice display abnormalities in the dermis characterized by decreased collagen fibril diameter and reduced tensile strength. The Journal of investigative dermatology. 2003;120(6):949-55. 71. Bradshaw AD, Graves DC, Motamed K, Sage EH. SPARC-null mice exhibit increased adiposity without significant differences in overall body weight. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(10):6045- 50. 72. Delany AM, Kalajzic I, Bradshaw AD, Sage EH, Canalis E. Osteonectin-null mutation compromises osteoblast formation, maturation, and survival. Endocrinology. 2003;144(6):2588-96.

118

73. Kzhyshkowska J, Workman G, Cardo-Vila M, Arap W, Pasqualini R, Gratchev A, et al. Novel function of alternatively activated macrophages: stabilin-1-mediated clearance of SPARC. Journal of immunology. 2006;176(10):5825-32. 74. Moser M, Legate KR, Zent R, Fassler R. The tail of integrins, talin, and kindlins. Science. 2009;324(5929):895-9. 75. Eliceiri BP. Integrin and growth factor receptor crosstalk. Circulation research. 2001;89(12):1104-10. 76. Porter JC, Hogg N. Integrins take partners: cross-talk between integrins and other membrane receptors. Trends in cell biology. 1998;8(10):390-6. 77. Somanath PR, Malinin NL, Byzova TV. Cooperation between integrin alphavbeta3 and VEGFR2 in angiogenesis. Angiogenesis. 2009;12(2):177-85. 78. Somanath PR, Ciocea A, Byzova TV. Integrin and growth factor receptor alliance in angiogenesis. Cell biochemistry and biophysics. 2009;53(2):53-64. 79. Akhtar N, Marlow R, Lambert E, Schatzmann F, Lowe ET, Cheung J, et al. Molecular dissection of integrin signalling proteins in the control of mammary epithelial development and differentiation. Development. 2009;136(6):1019-27. 80. Barker TH, Baneyx G, Cardo-Vila M, Workman GA, Weaver M, Menon PM, et al. SPARC regulates extracellular matrix organization through its modulation of integrin- linked kinase activity. The Journal of biological chemistry. 2005;280(43):36483-93. 81. Nie J, Chang B, Traktuev DO, Sun J, March K, Chan L, et al. IFATS collection: Combinatorial peptides identify alpha5beta1 integrin as a receptor for the matricellular protein SPARC on adipose stromal cells. Stem cells. 2008;26(10):2735-45. 82. Weaver MS, Workman G, Sage EH. The copper binding domain of SPARC mediates cell survival in vitro via interaction with integrin beta1 and activation of integrin- linked kinase. The Journal of biological chemistry. 2008;283(33):22826-37. 83. Schultz CR, Golembieski WA, King DA, Brown SL, Brodie C, Rempel SA. Inhibition of HSP27 alone or in combination with pAKT inhibition as therapeutic approaches to target SPARC-induced glioma cell survival. Molecular cancer. 2012;11:20. 84. Shi Q, Bao S, Maxwell JA, Reese ED, Friedman HS, Bigner DD, et al. Secreted protein acidic, rich in cysteine (SPARC), mediates cellular survival of gliomas through AKT activation. The Journal of biological chemistry. 2004;279(50):52200-9. 85. Shi Q, Bao S, Song L, Wu Q, Bigner DD, Hjelmeland AB, et al. Targeting SPARC expression decreases glioma cellular survival and invasion associated with reduced activities of FAK and ILK kinases. Oncogene. 2007;26(28):4084-94. 86. Golembieski WA, Thomas SL, Schultz CR, Yunker CK, McClung HM, Lemke N, et al. HSP27 mediates SPARC-induced changes in glioma morphology, migration, and invasion. Glia. 2008;56(10):1061-75. 87. Said N, Najwer I, Motamed K. Secreted protein acidic and rich in cysteine (SPARC) inhibits integrin-mediated adhesion and growth factor-dependent survival signaling in ovarian cancer. The American journal of pathology. 2007;170(3):1054-63. 88. Brekken RA, Sage EH. SPARC, a matricellular protein: at the crossroads of cell- matrix communication. Matrix biology : journal of the International Society for Matrix Biology. 2001;19(8):816-27. 89. Francki A, McClure TD, Brekken RA, Motamed K, Murri C, Wang T, et al. SPARC regulates TGF-beta1-dependent signaling in primary glomerular mesangial cells. Journal of cellular biochemistry. 2004;91(5):915-25.

119

90. Kupprion C, Motamed K, Sage EH. SPARC (BM-40, osteonectin) inhibits the mitogenic effect of vascular endothelial growth factor on microvascular endothelial cells. The Journal of biological chemistry. 1998;273(45):29635-40. 91. Motamed K, Blake DJ, Angello JC, Allen BL, Rapraeger AC, Hauschka SD, et al. Fibroblast growth factor receptor-1 mediates the inhibition of endothelial cell proliferation and the promotion of skeletal myoblast differentiation by SPARC: a role for protein kinase A. Journal of cellular biochemistry. 2003;90(2):408-23. 92. Raines EW, Lane TF, Iruela-Arispe ML, Ross R, Sage EH. The extracellular glycoprotein SPARC interacts with platelet-derived growth factor (PDGF)-AB and -BB and inhibits the binding of PDGF to its receptors. Proceedings of the National Academy of Sciences of the United States of America. 1992;89(4):1281-5. 93. Hasselaar P, Sage EH. SPARC antagonizes the effect of basic fibroblast growth factor on the migration of bovine aortic endothelial cells. Journal of cellular biochemistry. 1992;49(3):272-83. 94. Phan E, Ahluwalia A, Tarnawski AS. Role of SPARC--matricellular protein in pathophysiology and tissue injury healing. Implications for gastritis and gastric ulcers. Medical science monitor : international medical journal of experimental and clinical research. 2007;13(2):RA25-30. 95. Schiemann BJ, Neil JR, Schiemann WP. SPARC inhibits epithelial cell proliferation in part through stimulation of the transforming growth factor-beta-signaling system. Molecular biology of the cell. 2003;14(10):3977-88. 96. Nozaki M, Sakurai E, Raisler BJ, Baffi JZ, Witta J, Ogura Y, et al. Loss of SPARC-mediated VEGFR-1 suppression after injury reveals a novel antiangiogenic activity of VEGF-A. The Journal of clinical investigation. 2006;116(2):422-9. 97. Kato Y, Lewalle JM, Baba Y, Tsukuda M, Sakai N, Baba M, et al. Induction of SPARC by VEGF in human vascular endothelial cells. Biochemical and biophysical research communications. 2001;287(2):422-6. 98. Verrecchia F, Mauviel A. TGF-beta and TNF-alpha: antagonistic cytokines controlling type I collagen gene expression. Cellular signalling. 2004;16(8):873-80. 99. Ford R, Wang G, Jannati P, Adler D, Racanelli P, Higgins PJ, et al. Modulation of SPARC expression during butyrate-induced terminal differentiation of cultured human keratinocytes: regulation via a TGF-beta-dependent pathway. Experimental cell research. 1993;206(2):261-75. 100. Pavasant P, Yongchaitrakul T, Pattamapun K, Arksornnukit M. The synergistic effect of TGF-beta and 1,25-dihydroxyvitamin D3 on SPARC synthesis and alkaline phosphatase activity in human pulp fibroblasts. Archives of oral biology. 2003;48(10):717-22. 101. Reed MJ, Vernon RB, Abrass IB, Sage EH. TGF-beta 1 induces the expression of type I collagen and SPARC, and enhances contraction of collagen gels, by fibroblasts from young and aged donors. Journal of cellular physiology. 1994;158(1):169-79. 102. Wrana JL, Overall CM, Sodek J. Regulation of the expression of a secreted acidic protein rich in cysteine (SPARC) in human fibroblasts by transforming growth factor beta. Comparison of transcriptional and post-transcriptional control with fibronectin and type I collagen. European journal of biochemistry / FEBS. 1991;197(2):519-28. 103. Bassuk JA, Pichler R, Rothmier JD, Pippen J, Gordon K, Meek RL, et al. Induction of TGF-beta1 by the matricellular protein SPARC in a rat model of glomerulonephritis. Kidney international. 2000;57(1):117-28.

120

104. Tian M, Schiemann WP. The TGF-beta paradox in human cancer: an update. Future oncology. 2009;5(2):259-71. 105. Clark CJ, Sage EH. A prototypic matricellular protein in the tumor microenvironment--where there's SPARC, there's fire. Journal of cellular biochemistry. 2008;104(3):721-32. 106. Mok SC, Chan WY, Wong KK, Muto MG, Berkowitz RS. SPARC, an extracellular matrix protein with tumor-suppressing activity in human ovarian epithelial cells. Oncogene. 1996;12(9):1895-901. 107. Cheetham S, Tang MJ, Mesak F, Kennecke H, Owen D, Tai IT. SPARC promoter hypermethylation in colorectal cancers can be reversed by 5-Aza-2'deoxycytidine to increase SPARC expression and improve therapy response. British journal of cancer. 2008;98(11):1810-9. 108. Yang E, Kang HJ, Koh KH, Rhee H, Kim NK, Kim H. Frequent inactivation of SPARC by promoter hypermethylation in colon cancers. International journal of cancer Journal international du cancer. 2007;121(3):567-75. 109. Sato N, Fukushima N, Maehara N, Matsubayashi H, Koopmann J, Su GH, et al. SPARC/osteonectin is a frequent target for aberrant methylation in pancreatic adenocarcinoma and a mediator of tumor-stromal interactions. Oncogene. 2003;22(32):5021-30. 110. Watkins G, Douglas-Jones A, Bryce R, Mansel RE, Jiang WG. Increased levels of SPARC (osteonectin) in human breast cancer tissues and its association with clinical outcomes. Prostaglandins, leukotrienes, and essential fatty acids. 2005;72(4):267-72. 111. Gilles C, Bassuk JA, Pulyaeva H, Sage EH, Foidart JM, Thompson EW. SPARC/osteonectin induces matrix metalloproteinase 2 activation in human breast cancer cell lines. Cancer research. 1998;58(23):5529-36. 112. Ledda MF, Adris S, Bover L, Bravo AL, Mordoh J, Podhajcer OL. [The role of SPARC gene in tumorigenic capacity of human melanoma cells]. Medicina. 1996;56(1):51-4. Rol del gen SPARC en la capacidad tumorigenica de celulas de melanoma humano. 113. Ledda F, Bravo AI, Adris S, Bover L, Mordoh J, Podhajcer OL. The expression of the secreted protein acidic and rich in cysteine (SPARC) is associated with the neoplastic progression of human melanoma. The Journal of investigative dermatology. 1997;108(2):210-4. 114. Kato Y, Frankenne F, Noel A, Sakai N, Nagashima Y, Koshika S, et al. High production of SPARC/osteonectin/BM-40 in mouse metastatic B16 melanoma cell lines. Pathology oncology research : POR. 2000;6(1):24-6. 115. Golembieski WA, Ge S, Nelson K, Mikkelsen T, Rempel SA. Increased SPARC expression promotes U87 glioblastoma invasion in vitro. International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience. 1999;17(5-6):463-72. 116. Koukourakis MI, Giatromanolaki A, Brekken RA, Sivridis E, Gatter KC, Harris AL, et al. Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients. Cancer research. 2003;63(17):5376-80. 117. Witkiewicz AK, Freydin B, Chervoneva I, Potoczek M, Rizzo W, Rui H, et al. Stromal CD10 and SPARC expression in ductal carcinoma in situ (DCIS) patients predicts disease recurrence. Cancer biology & therapy. 2010;10(4):391-6.

121

118. Liang JF, Wang HK, Xiao H, Li N, Cheng CX, Zhao YZ, et al. Relationship and prognostic significance of SPARC and VEGF protein expression in colon cancer. Journal of experimental & clinical cancer research : CR. 2010;29:71. 119. Pellagatti A, Jadersten M, Forsblom AM, Cattan H, Christensson B, Emanuelsson EK, et al. Lenalidomide inhibits the malignant clone and up-regulates the SPARC gene mapping to the commonly deleted region in 5q- syndrome patients. Proceedings of the National Academy of Sciences of the United States of America. 2007;104(27):11406-11. 120. Lehmann S, O'Kelly J, Raynaud S, Funk SE, Sage EH, Koeffler HP. Common deleted genes in the 5q- syndrome: thrombocytopenia and reduced erythroid colony formation in SPARC null mice. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK. 2007;21(9):1931-6. 121. Fidler C, Strickson A, Boultwood J, Waincoat JS. Mutation analysis of the SPARC gene in the 5q-syndrome. American journal of hematology. 2000;64(4):324. 122. DiMartino JF, Lacayo NJ, Varadi M, Li L, Saraiya C, Ravindranath Y, et al. Low or absent SPARC expression in acute myeloid leukemia with MLL rearrangements is associated with sensitivity to growth inhibition by exogenous SPARC protein. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK. 2006;20(3):426-32. 123. Fenouille N, Puissant A, Dufies M, Robert G, Jacquel A, Ohanna M, et al. Persistent activation of the Fyn/ERK kinase signaling axis mediates imatinib resistance in chronic myelogenous leukemia cells through upregulation of intracellular SPARC. Cancer research. 2010;70(23):9659-70. 124. Schwind S, Marcucci G, Maharry K, Radmacher MD, Mrozek K, Holland KB, et al. BAALC and ERG expression levels are associated with outcome and distinct gene and microRNA expression profiles in older patients with de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. Blood. 2010;116(25):5660-9. 125. Liu S, Liu Z, Xie Z, Pang J, Yu J, Lehmann E, et al. Bortezomib induces DNA hypomethylation and silenced gene transcription by interfering with Sp1/NF-kappaB- dependent DNA methyltransferase activity in acute myeloid leukemia. Blood. 2008;111(4):2364-73. 126. Thiede C, Steudel C, Mohr B, Schaich M, Schakel U, Platzbecker U, et al. Analysis of FLT3-activating mutations in 979 patients with acute myelogenous leukemia: association with FAB subtypes and identification of subgroups with poor prognosis. Blood. 2002;99(12):4326-35. 127. Whitman SP, Ruppert AS, Marcucci G, Mrozek K, Paschka P, Langer C, et al. Long-term disease-free survivors with cytogenetically normal acute myeloid leukemia and MLL partial tandem duplication: a Cancer and Leukemia Group B study. Blood. 2007;109(12):5164-7. 128. Becker H, Marcucci G, Maharry K, Radmacher MD, Mrozek K, Margeson D, et al. Mutations of the Wilms tumor 1 gene (WT1) in older patients with primary cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. Blood. 2010;116(5):788-92. 129. Metzeler KH, Maharry K, Radmacher MD, Mrozek K, Margeson D, Becker H, et al. TET2 mutations improve the new European LeukemiaNet risk classification of acute myeloid leukemia: a Cancer and Leukemia Group B study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2011;29(10):1373-81. 122

130. Metzeler KH, Becker H, Maharry K, Radmacher MD, Kohlschmidt J, Mrozek K, et al. ASXL1 mutations identify a high-risk subgroup of older patients with primary cytogenetically normal AML within the ELN Favorable genetic category. Blood. 2011;118(26):6920-9. 131. Radmacher MD, Marcucci G, Ruppert AS, Mrozek K, Whitman SP, Vardiman JW, et al. Independent confirmation of a prognostic gene-expression signature in adult acute myeloid leukemia with a normal karyotype: a Cancer and Leukemia Group B study. Blood. 2006;108(5):1677-83. 132. Silva WA, Jr., Covas DT, Panepucci RA, Proto-Siqueira R, Siufi JL, Zanette DL, et al. The profile of gene expression of human marrow mesenchymal stem cells. Stem cells. 2003;21(6):661-9. 133. Sturm RA, Satyamoorthy K, Meier F, Gardiner BB, Smit DJ, Vaidya B, et al. Osteonectin/SPARC induction by ectopic beta(3) integrin in human radial growth phase primary melanoma cells. Cancer research. 2002;62(1):226-32. 134. Pavasant P, Yongchaitrakul T. Secreted protein acidic, rich in cysteine induces pulp cell migration via alphavbeta3 integrin and extracellular signal-regulated kinase. Oral diseases. 2008;14(4):335-40. 135. Nie J, Sage EH. SPARC inhibits adipogenesis by its enhancement of beta- catenin signaling. The Journal of biological chemistry. 2009;284(2):1279-90. 136. Chang W, Wei K, Jacobs SS, Upadhyay D, Weill D, Rosen GD. SPARC suppresses apoptosis of idiopathic pulmonary fibrosis fibroblasts through constitutive activation of beta-catenin. The Journal of biological chemistry. 2010;285(11):8196-206. 137. Novak A, Dedhar S. Signaling through beta-catenin and Lef/Tcf. Cellular and molecular life sciences : CMLS. 1999;56(5-6):523-37. 138. He XC, Yin T, Grindley JC, Tian Q, Sato T, Tao WA, et al. PTEN-deficient intestinal stem cells initiate intestinal polyposis. Nature genetics. 2007;39(2):189-98. 139. Hino S, Tanji C, Nakayama KI, Kikuchi A. Phosphorylation of beta-catenin by cyclic AMP-dependent protein kinase stabilizes beta-catenin through inhibition of its ubiquitination. Molecular and cellular biology. 2005;25(20):9063-72. 140. Chowdhury R, Yeoh KK, Tian YM, Hillringhaus L, Bagg EA, Rose NR, et al. The oncometabolite 2-hydroxyglutarate inhibits histone lysine demethylases. EMBO reports. 2011;12(5):463-9. 141. Varier RA, Timmers HT. Histone lysine methylation and demethylation pathways in cancer. Biochimica et biophysica acta. 2011;1815(1):75-89. 142. Lu T, Jackson MW, Wang B, Yang M, Chance MR, Miyagi M, et al. Regulation of NF-kappaB by NSD1/FBXL11-dependent reversible lysine methylation of p65. Proceedings of the National Academy of Sciences of the United States of America. 2010;107(1):46-51. 143. Nakagawa M, Shimabe M, Watanabe-Okochi N, Arai S, Yoshimi A, Shinohara A, et al. AML1/RUNX1 functions as a cytoplasmic attenuator of NF-kappaB signaling in the repression of myeloid tumors. Blood. 2011;118(25):6626-37. Epub 2011/10/25. 144. Zhu XC, Dong QZ, Zhang XF, Deng B, Jia HL, Ye QH, et al. microRNA-29a suppresses cell proliferation by targeting SPARC in hepatocellular carcinoma. International journal of molecular medicine. 2012. 145. Luna C, Li G, Qiu J, Epstein DL, Gonzalez P. Role of miR-29b on the regulation of the extracellular matrix in human trabecular meshwork cells under chronic oxidative stress. Molecular vision. 2009;15:2488-97.

123

146. Kapinas K, Kessler CB, Delany AM. miR-29 suppression of osteonectin in osteoblasts: regulation during differentiation and by canonical Wnt signaling. Journal of cellular biochemistry. 2009;108(1):216-24. 147. Garzon R, Liu S, Fabbri M, Liu Z, Heaphy CE, Callegari E, et al. MicroRNA-29b induces global DNA hypomethylation and tumor suppressor gene reexpression in acute myeloid leukemia by targeting directly DNMT3A and 3B and indirectly DNMT1. Blood. 2009;113(25):6411-8. 148. Porter PL, Sage EH, Lane TF, Funk SE, Gown AM. Distribution of SPARC in normal and neoplastic human tissue. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society. 1995;43(8):791-800. 149. Massi D, Franchi A, Borgognoni L, Reali UM, Santucci M. Osteonectin expression correlates with clinical outcome in thin cutaneous malignant melanomas. Human pathology. 1999;30(3):339-44. 150. McClung HM, Golembieski WA, Schultz CR, Jankowski M, Schultz LR, Rempel SA. Deletion of the SPARC acidic domain or EGF-like module reduces SPARC-induced migration and signaling through p38 MAPK/HSP27 in glioma. Carcinogenesis. 2012;33(2):275-84. 151. Yunker CK, Golembieski W, Lemke N, Schultz CR, Cazacu S, Brodie C, et al. SPARC-induced increase in glioma matrix and decrease in vascularity are associated with reduced VEGF expression and secretion. International journal of cancer Journal international du cancer. 2008;122(12):2735-43. 152. Ledda MF, Adris S, Bravo AI, Kairiyama C, Bover L, Chernajovsky Y, et al. Suppression of SPARC expression by antisense RNA abrogates the tumorigenicity of human melanoma cells. Nature medicine. 1997;3(2):171-6. 153. Yiu GK, Chan WY, Ng SW, Chan PS, Cheung KK, Berkowitz RS, et al. SPARC (secreted protein acidic and rich in cysteine) induces apoptosis in ovarian cancer cells. The American journal of pathology. 2001;159(2):609-22. 154. Aoi W, Naito Y, Takagi T, Tanimura Y, Takanami Y, Kawai Y, et al. A novel myokine, secreted protein acidic and rich in cysteine (SPARC), suppresses colon tumorigenesis via regular exercise. Gut. 2012. 155. Siva K, Jaako P, Miharada K, Rorby E, Ehinger M, Karlsson G, et al. SPARC is dispensable for murine hematopoiesis, despite its suspected pathophysiological role in 5q- myelodysplastic syndrome. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK. 2012. 156. Tripodo C, Sangaletti S, Guarnotta C, Piccaluga PP, Cacciatore M, Giuliano M, et al. Stromal SPARC contributes to the detrimental fibrotic changes associated with myeloproliferation while its deficiency favors myeloid cell expansion. Blood. 2012. 157. Liu S, Wu LC, Pang J, Santhanam R, Schwind S, Wu YZ, et al. Sp1/NFkappaB/HDAC/miR-29b regulatory network in KIT-driven myeloid leukemia. Cancer cell. 2010;17(4):333-47. Epub 2010/04/14. 158. Siapati EK, Papadaki M, Kozaou Z, Rouka E, Michali E, Savvidou I, et al. Proliferation and bone marrow engraftment of AML blasts is dependent on beta-catenin signalling. British journal of haematology. 2011;152(2):164-74. 159. Wang Y, Krivtsov AV, Sinha AU, North TE, Goessling W, Feng Z, et al. The Wnt/beta-catenin pathway is required for the development of leukemia stem cells in AML. Science. 2010;327(5973):1650-3.

124

160. Tabe Y, Jin L, Tsutsumi-Ishii Y, Xu Y, McQueen T, Priebe W, et al. Activation of integrin-linked kinase is a critical prosurvival pathway induced in leukemic cells by bone marrow-derived stromal cells. Cancer research. 2007;67(2):684-94. 161. Hannigan G, Troussard AA, Dedhar S. Integrin-linked kinase: a cancer therapeutic target unique among its ILK. Nature reviews Cancer. 2005;5(1):51-63. 162. Muranyi AL, Dedhar S, Hogge DE. Combined inhibition of integrin linked kinase and FMS-like tyrosine kinase 3 is cytotoxic to acute myeloid leukemia progenitor cells. Experimental hematology. 2009;37(4):450-60. 163. Meshinchi S, Appelbaum FR. Structural and functional alterations of FLT3 in acute myeloid leukemia. Clinical cancer research : an official journal of the American Association for Cancer Research. 2009;15(13):4263-9. Epub 2009/06/25. 164. Beran M, Luthra R, Kantarjian H, Estey E. FLT3 mutation and response to intensive chemotherapy in young adult and elderly patients with normal karyotype. Leukemia research. 2004;28(6):547-50. Epub 2004/05/04. 165. Krause DS, Van Etten RA. Tyrosine kinases as targets for cancer therapy. The New England journal of medicine. 2005;353(2):172-87. Epub 2005/07/15. 166. Weisberg E, Sattler M, Ray A, Griffin JD. Drug resistance in mutant FLT3- positive AML. Oncogene. 2010;29(37):5120-34. Epub 2010/07/14. 167. Bang SM, Ahn JY, Park J, Park SH, Cho EK, Shin DB, et al. Low frequency and variability of FLT3 mutations in Korean patients with acute myeloid leukemia. Journal of Korean medical science. 2008;23(5):833-7. Epub 2008/10/29. 168. Ozeki K, Kiyoi H, Hirose Y, Iwai M, Ninomiya M, Kodera Y, et al. Biologic and clinical significance of the FLT3 transcript level in acute myeloid leukemia. Blood. 2004;103(5):1901-8. Epub 2003/11/08. 169. Zheng R, Levis M, Piloto O, Brown P, Baldwin BR, Gorin NC, et al. FLT3 ligand causes autocrine signaling in acute myeloid leukemia cells. Blood. 2004;103(1):267-74. Epub 2003/09/13. 170. Smith CC, Wang Q, Chin CS, Salerno S, Damon LE, Levis MJ, et al. Validation of ITD mutations in FLT3 as a therapeutic target in human acute myeloid leukaemia. Nature. 2012;485(7397):260-3. Epub 2012/04/17. 171. Kindler T, Lipka DB, Fischer T. FLT3 as a therapeutic target in AML: still challenging after all these years. Blood. 2010;116(24):5089-102. Epub 2010/08/14. 172. Pratz KW, Sato T, Murphy KM, Stine A, Rajkhowa T, Levis M. FLT3-mutant allelic burden and clinical status are predictive of response to FLT3 inhibitors in AML. Blood. 2010;115(7):1425-32. Epub 2009/12/17. 173. Pratz KW, Cortes J, Roboz GJ, Rao N, Arowojolu O, Stine A, et al. A pharmacodynamic study of the FLT3 inhibitor KW-2449 yields insight into the basis for clinical response. Blood. 2009;113(17):3938-46. Epub 2008/11/26. 174. Garzon R, Croce CM. MicroRNAs in normal and malignant hematopoiesis. Current opinion in hematology. 2008;15(4):352-8. Epub 2008/06/10. 175. Lee DW, Futami M, Carroll M, Feng Y, Wang Z, Fernandez M, et al. Loss of SHIP-1 protein expression in high-risk myelodysplastic syndromes is associated with miR-210 and miR-155. Oncogene. 2012. Epub 2012/01/18. 176. Hwang BY, Su BN, Chai H, Mi Q, Kardono LB, Afriastini JJ, et al. Silvestrol and episilvestrol, potential anticancer rocaglate derivatives from Aglaia silvestris. The Journal of organic chemistry. 2004;69(10):3350-8. Epub 2004/05/11.

125

177. Kinghorn AD, Pan L, Fletcher JN, Chai H. The relevance of higher plants in lead compound discovery programs. Journal of natural products. 2011;74(6):1539-55. Epub 2011/06/10. 178. Kim S, Hwang BY, Su BN, Chai H, Mi Q, Kinghorn AD, et al. Silvestrol, a potential anticancer rocaglate derivative from Aglaia foveolata, induces apoptosis in LNCaP cells through the mitochondrial/apoptosome pathway without activation of executioner caspase-3 or -7. Anticancer research. 2007;27(4B):2175-83. Epub 2007/08/19. 179. Mi Q, Kim S, Hwang BY, Su BN, Chai H, Arbieva ZH, et al. Silvestrol regulates G2/M checkpoint genes independent of p53 activity. Anticancer research. 2006;26(5A):3349-56. Epub 2006/11/11. 180. Gerard B, Cencic R, Pelletier J, Porco JA, Jr. Enantioselective synthesis of the complex rocaglate (-)-silvestrol. Angew Chem Int Ed Engl. 2007;46(41):7831-4. Epub 2007/09/07. 181. Bordeleau ME, Robert F, Gerard B, Lindqvist L, Chen SM, Wendel HG, et al. Therapeutic suppression of translation initiation modulates chemosensitivity in a mouse lymphoma model. The Journal of clinical investigation. 2008;118(7):2651-60. Epub 2008/06/14. 182. Lucas DM, Edwards RB, Lozanski G, West DA, Shin JD, Vargo MA, et al. The novel plant-derived agent silvestrol has B-cell selective activity in chronic lymphocytic leukemia and acute lymphoblastic leukemia in vitro and in vivo. Blood. 2009;113(19):4656-66. Epub 2009/02/05. 183. Cencic R, Carrier M, Trnkus A, Porco JA, Jr., Minden M, Pelletier J. Synergistic effect of inhibiting translation initiation in combination with cytotoxic agents in acute myelogenous leukemia cells. Leukemia research. 2010;34(4):535-41. Epub 2009/09/04. 184. Cencic R, Carrier M, Galicia-Vazquez G, Bordeleau ME, Sukarieh R, Bourdeau A, et al. Antitumor activity and mechanism of action of the cyclopenta[b]benzofuran, silvestrol. PloS one. 2009;4(4):e5223. Epub 2009/04/30. 185. Saradhi UV, Gupta SV, Chiu M, Wang J, Ling Y, Liu Z, et al. Characterization of silvestrol pharmacokinetics in mice using liquid chromatography-tandem mass spectrometry. The AAPS journal. 2011;13(3):347-56. Epub 2011/04/19. 186. Vigorito E, Perks KL, Abreu-Goodger C, Bunting S, Xiang Z, Kohlhaas S, et al. microRNA-155 regulates the generation of immunoglobulin class-switched plasma cells. Immunity. 2007;27(6):847-59. Epub 2007/12/07. 187. Grosjean-Raillard J, Ades L, Boehrer S, Tailler M, Fabre C, Braun T, et al. Flt3 receptor inhibition reduces constitutive NFkappaB activation in high-risk myelodysplastic syndrome and acute myeloid leukemia. Apoptosis : an international journal on programmed cell death. 2008;13(9):1148-61. Epub 2008/08/02. 188. Takahashi S, Harigae H, Ishii KK, Inomata M, Fujiwara T, Yokoyama H, et al. Over-expression of Flt3 induces NF-kappaB pathway and increases the expression of IL-6. Leukemia research. 2005;29(8):893-9. Epub 2005/06/28. 189. Baumann B, Bohnenstengel F, Siegmund D, Wajant H, Weber C, Herr I, et al. Rocaglamide derivatives are potent inhibitors of NF-kappa B activation in T-cells. The Journal of biological chemistry. 2002;277(47):44791-800. Epub 2002/09/19. 190. Alinari L, Prince CJ, Edwards RB, Towns WH, Mani R, Lehman A, et al. Dual Targeting of the Cyclin/Rb/E2F and Mitochondrial Pathways in Mantle Cell Lymphoma with the Translation Inhibitor Silvestrol. Clinical cancer research : an official journal of the American Association for Cancer Research. 2012;18(17):4600-11. Epub 2012/07/14. 126

191. Onai N, Obata-Onai A, Tussiwand R, Lanzavecchia A, Manz MG. Activation of the Flt3 signal transduction cascade rescues and enhances type I interferon-producing and dendritic cell development. The Journal of experimental medicine. 2006;203(1):227- 38. Epub 2006/01/19. 192. Blum W, Schwind S, Tarighat SS, Geyer S, Eisfeld AK, Whitman S, et al. Clinical and pharmacodynamic activity of bortezomib and decitabine in acute myeloid leukemia. Blood. 2012;119(25):6025-31. Epub 2012/05/09. 193. Kottaridis PD, Gale RE, Frew ME, Harrison G, Langabeer SE, Belton AA, et al. The presence of a FLT3 internal tandem duplication in patients with acute myeloid leukemia (AML) adds important prognostic information to cytogenetic risk group and response to the first cycle of chemotherapy: analysis of 854 patients from the United Kingdom Medical Research Council AML 10 and 12 trials. Blood. 2001;98(6):1752-9. Epub 2001/09/06. 194. Pratz KW, Levis MJ. Bench to bedside targeting of FLT3 in acute leukemia. Current drug targets. 2010;11(7):781-9. Epub 2010/04/08. 195. Weisberg E, Barrett R, Liu Q, Stone R, Gray N, Griffin JD. FLT3 inhibition and mechanisms of drug resistance in mutant FLT3-positive AML. Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy. 2009;12(3):81-9. Epub 2009/05/27. 196. Walters DK, Stoffregen EP, Heinrich MC, Deininger MW, Druker BJ. RNAi- induced down-regulation of FLT3 expression in AML cell lines increases sensitivity to MLN518. Blood. 2005;105(7):2952-4. Epub 2004/12/09. 197. Thompson RC, Herscovitch M, Zhao I, Ford TJ, Gilmore TD. NF-kappaB down- regulates expression of the B-lymphoma marker CD10 through a miR-155/PU.1 pathway. The Journal of biological chemistry. 2011;286(3):1675-82. Epub 2010/10/16. 198. Guzman ML, Neering SJ, Upchurch D, Grimes B, Howard DS, Rizzieri DA, et al. Nuclear factor-kappaB is constitutively activated in primitive human acute myelogenous leukemia cells. Blood. 2001;98(8):2301-7. Epub 2001/10/06. 199. Cornell RF, Palmer J. Adult acute leukemia. Disease-a-month : DM. 2012;58(4):219-38. 200. Frohling S, Scholl C, Gilliland DG, Levine RL. Genetics of myeloid malignancies: pathogenetic and clinical implications. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2005;23(26):6285-95. 201. Moore MA. Converging pathways in leukemogenesis and stem cell self-renewal. Experimental hematology. 2005;33(7):719-37. 202. Marcucci G, Haferlach T, Dohner H. Molecular genetics of adult acute myeloid leukemia: prognostic and therapeutic implications. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2011;29(5):475-86. 203. Ferrara F. New agents for acute myeloid leukemia: is it time for targeted therapies? Expert opinion on investigational drugs. 2012;21(2):179-89. 204. Wani AA, Jafarnejad SM, Zhou J, Li G. Integrin-linked kinase regulates melanoma angiogenesis by activating NF-kappaB/interleukin-6 signaling pathway. Oncogene. 2011;30(24):2778-88. 205. Powell JA, Thomas D, Barry EF, Kok CH, McClure BJ, Tsykin A, et al. Expression profiling of a hemopoietic cell survival transcriptome implicates osteopontin as a functional prognostic factor in AML. Blood. 2009;114(23):4859-70.

127