Egfr Activates a Taz-Driven Oncogenic Program in Glioblastoma

EGFR ACTIVATES A TAZ-DRIVEN ONCOGENIC PROGRAM IN GLIOBLASTOMA

by Minling Gao

A thesis submitted to Johns Hopkins University in conformity with the

requirements for the degree of Doctor of Philosophy

Baltimore, Maryland March 2020

Abstract

Hyperactivated EGFR signaling is associated with about 45% of Glioblastoma (GBM), the most aggressive and lethal primary brain tumor in humans. However, the oncogenic transcriptional events driven by EGFR are still incompletely understood. We studied the role of the transcription factor TAZ to better understand master transcriptional regulators in mediating the EGFR signaling pathway in GBM. The transcriptional coactivator with PDZ- binding motif (TAZ) and its paralog gene, the Yes-associated protein (YAP) are two transcriptional co-activators that play important roles in multiple cancer types and are regulated in a context-dependent manner by various upstream signaling pathways, e.g. the

Hippo, WNT and GPCR signaling. In GBM cells, TAZ functions as an oncogene that drives mesenchymal transition and radioresistance.

This thesis intends to broaden our understanding of EGFR signaling and TAZ regulation in

GBM. In patient-derived GBM cell models, EGF induced TAZ and its known gene targets through EGFR and downstream tyrosine kinases (ERK1/2 and STAT3). In GBM cells with

EGFRvIII, an EGF-independent and constitutively active mutation, TAZ showed EGF- independent hyperactivation when compared to EGFRvIII-negative cells. These results revealed a novel EGFR-TAZ signaling axis in GBM cells.

The second contribution of this thesis is that we performed next-generation sequencing to establish the first genome-wide map of EGF-induced TAZ target genes. To further define

EGF-induced TAZ target genes, we performed RNA-sequencing and TAZ ChIP-sequencing in EGF-treated GBM neurospheres. Using KEGG pathway analysis followed by extensive validation, we found that TAZ acts downstream of EGFR to activate multiple oncogenic signaling pathways, including key components of the RTK signaling pathway to form an

EGFR-TAZ-RTK positive feedback loop, and other oncogenic genes, which form a EGFR-

TAZ-driven network to promote GBM growth, invasion, stemness, therapeutic resistance and immune escape.

To further study the oncogenic effects of the EGF-induced TAZ hyperactivation in GBM cells, we found that enforced TAZ expression promoted GBM cell proliferation, invasion, radioresistance and tumorigenicity.

Our results and discoveries from others all suggested that TAZ is a potential drug target for

GBM therapy. Based on the EGFR-TAZ signaling axis model, we tested a set of brain- penetrating RTK inhibitors and the TAZ inhibitor Verteporfin (VP) for their abilities to inhibit

TAZ signal in GBM cells. Besides VP, Osimertinib, a third-generation EGFR inhibitor most potently inhibited TAZ and its gene targets both in vitro and in vivo. It also effectively inhibited GBM xenograft growth and extended the survival of tumor-bearing mice. In summary, our discoveries reveal a novel EGFR-TAZ signaling axis that promotes GBM malignancy, and provides preclinical evidence to justify future clinical applications of VP, OS, and other similar brain-penetrating EGFR inhibitors for targeting TAZ-associated GBM and possibly other primary or metastatic brain tumors.

Together, this thesis elucidates a novel EGFR-TAZ signaling axis in GBM and further provides a genome-wide map of downstream transcriptome that promotes key malignant features of GBM. Our results also support the clinical use of defined FDA-approved EGFR inhibitor OS and the FDA-approved drug VP for effective TAZ targeting in GBM and possibly other primary or metastatic brain tumors with TAZ hyperactivation.

Primary Reader and Advisor: John Laterra

Secondary Reader: Charles Eberhart

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Acknowledgments

Graduate school is one of the most precious periods in my life, full of challenges and excitement. It would be impossible for me to make it to the end without all the support and help I received along this process.

First, I would like to thank Dr. John Laterra for his mentorship. Your work attitude and ethic is inspiring and encouraging. And I also want to thank Dr. Mingyao Ying for the direct guidance through this project.

Second, I would like to thank my thesis committee members: Dr. Charles Eberhart, Dr.

Edward Gabrielson, Dr. Mingyao Ying, and Dr. John Laterra for their thought provoking discussions and professional guidance throughout my thesis.

I am also most grateful for all the scientific and personal help for Dr. Laterra’s group:

Bachchu, Hernando, Qingfu, Yingchao, Shuang, Chengchen, Emma, Tengjiao, Qian,

Fenghong, Yi, Dr. Li, and Dr. Xia. Special thanks to Dr. Yi Fu for all his help in animal experiments.

I would also like to thank Dr. Rodriguez, Dr. Eberhart, and Dr. Nix for introducing me to the world of neuropathology and eye pathology.

I want to thank Mrs. Margaret Lee and Mr. Al Lee for their kind support and scholarship.

Also, the supportive atmosphere of the Pathobiology department and numerous help from

Stacey and Tracy are critical for this process. And I am thankful for all the support I received from KKI 4th floor.

Last but not least, I would like to thank my parents and friends for their unconditional love and support throughout my life.

Contents

Abstract ...... ii

Acknowledgments ...... iv

Content ...... v

List of Tables ...... vii

List of Figures ...... ix

Abbreviations ...... xi

Chapter 1: Introduction ...... 1

1.1 Glioblastoma ...... 1

1.2 Receptor Tyrosine Kinase and Epidermal Growth Factor Receptor ...... 7

1.3 The Hippo Signaling Pathway and TAZ/YAP ...... 12

1.4 Rationale and Hypothesis ...... 17

Chapter 2: EGF induces TAZ transcription through EGFR and its downstream kinase pathway ...... 20

2.1 Introduction ...... 20

2.2 Materials and Methods ...... 21

2.3 Results ...... 23

2.4 Conclusion and Discussion ...... 27

Chapter 3: TAZ acts as a key mediator of EGF signaling to activate oncogenic cascades in GBM ...... 43

3.1 Introduction ...... 43

3.2 Materials and Methods ...... 44

3.3 Results ...... 47

3.4 Conclusion and Discussion ...... 50

Chapter 4: TAZ hyperactivation promotes GBM growth, invasion, and tumorigenicity

...... 63

4.1 Introduction ...... 63

4.2 Materials and Methods ...... 63

4.3 Results ...... 65

4.4 Conclusion and Discussion ...... 67

Chapter 5: The EGFR inhibitor Osimertinib and TAZ inhibitor Verteporfin potently inhibits the TAZ-driven oncogenic program in GBM cells and xenografts ...... 79

5.1 Introduction ...... 79

5.2 Materials and Methods ...... 80

5.3 Results ...... 80

5.4 Conclusion and discussion ...... 83

Chapter 6: Conclusion and Discussion ...... 92

6.1 Conclusion ...... 92

6.2 Discussion ...... 94

Chapter 7: Supplement data ...... 103

7.1 R script for KEGG analysis ...... 103

Bibliography ...... 137

Curriculum Vitae ...... 164

List of Tables

Table 1: Summary of antibodies used in Chapter 2 ...... 29

Table 2: Summary of primers used in Chapter 2 ...... 30

Table 3: Summary of RTK inhibitors and other compounds used in Chapter 2 ...... 31

Table 4: Correlation analysis between RTK genes and TAZ in the TCGA and CGGA database

...... 32

Table 5: Summary of antibodies used in Chapter 3 ...... 52

Table 6: Top 20 KEGG terms enriched in TAZ-Up genes ...... 53

Table 7: Summary of correlation analysis in the TCGA and CGGA database and mRNA validation results of TAZ-Up genes in GBM1B and A172 cells ...... 55

Table 8: Primers for pLEX-TAZ cloning ...... 69

Table 9: Summary of antibodies used in Chapter 4 ...... 70

Table 10: Summary of chemical compounds used in Chapter 5 ...... 85

Table 11: IC50 of VP, OS, and Er in GBM cells ...... 86

Table S1: Summary qRT-PCR primers used for validating RNA-Seq results in Chapter 3

...... 104

Table S2: Summary of ChIP-PCR primers used for validating ChIP-Seq results in Chapter 3

...... 105

Table S3: Differentially expressed genes in GBM1B cells after 4-hour EGF treatment ..... 106

Table S4: Differentially expressed genes in GBM1B cells after 24-hour EGF treatment ... 107

Table S5: Up-regulated genes identified by RNA-Seq after either 4-hour or 24-hour EGF treatment (FDR ≤ 0.05, log2 (fold change) ≥0.8) ...... 108

vii

Table S6: Down-regulated genes identified by RNA-Seq after either 4-hour or 24-hour EGF treatment (FDR ≤ 0.05, log2 (fold change) ≤-0.8) ...... 117

Table S7: TAZ-binding peaks identified by TAZ ChIP-Seq (FDR≤ 0.05) ...... 125

Table S8: TAZ binding motif prediction ...... 126

Table S9: TAZ-Up gene list ...... 127

Table S10: TAZ-Down gene list ...... 131

Table S11: KEGG pathway analysis results for TAZ-Up and TAZ-Down genes ...... 133

viii

List of Figures

Fig. 1: TAZ expression analysis in the TCGA-GBM, CGGA, and Rembrandt databases. .... 33

Fig. 2: TAZ expression positively correlates with the expression of RTK ligands and receptors.

...... 34

Fig. 3: EGF induces TAZ in GBM cells...... 35

Fig. 4: EGF induces the level of TAZ in the nucleus...... 37

Fig. 5: EGF activates TAZ gene targets in GBM cells...... 38

Fig. 6: EGF induces TAZ expression through EGFR...... 39

Fig. 7: EGF induces TAZ transcription through EGFR pathway downstream kinases...... 40

Fig. 8: The EGFRvIII mutation causes EGF-independent TAZ hyperactivation in GBM cells.

...... 42

Fig. 9: Outline of the genome-wide analysis...... 56

Fig. 10: RNA-sequencing reveals transcriptome changes between GBM1B cells with or without EGF treatment...... 57

Fig. 11: ChIP-Seq on GBM1B cells after 4-hour EGF treatment identifies TAZ genome-wide binding sites...... 58

Fig. 12: KEGG and IPA analysis of TAZ-Up genes...... 59

Fig. 13: KEGG Clustergram analysis ranks TAZ-Up gene in the top 20 KEGG terms...... 60

Fig. 14: TAZ mediates the activation of multiple oncogenic genes induced by EGF...... 61

Fig. 15: Generation and validation of GBM cell lines with enforced TAZ expression...... 71

Fig. 16: Enforced TAZ expression promotes malignant phenotypes of GBM cells...... 73

Fig. 17: Enforced TAZ expression leads to more aggressive GBM1B tumor xenograft formation...... 75

Fig. 18: Enforced TAZ expression induces tumorigenesis in non-tumorigenic A172 cells.

...... 77

Fig. 19: Enforced TAZ expression inhibits tumor infiltration of cytotoxic T lymphocytes. .. 78

Fig. 20: Testing of a TAZ inhibitor (VP) and BBB-crossing RTK inhibitors...... 87

Fig. 21: Systemic OS therapy inhibits TAZ expression, TAZ-Up genes and xenograft growth in GBM xenograft models...... 89

Fig. 22: Transgenic TAZ is inhibited by VP by not by OS...... 91

Fig. 23: Model of the EGFR-TAZ signaling axis in GBM cells...... 102

Fig. S1: Cluster of all 641 up-regulated genes within top 20 enriched KEGG pathways. .... 134

Fig. S2: Correlation between TAZ and TAZ-Up genes in the TCGA database...... 136

Abbreviations

APC adenomatous polyposis coli BBB Blood-Brain Barrier CAF cancer-associate fibroblasts CNS central nervous system CSC cancer stem cell CT computed tomography DNA-PK DNA-dependent protein kinase ECM extracellular matrix EGF epidermal growth factor EGFR epidermal growth factor receptor ELASA Enzyme Linked Immunosorbent Assay EMT epithelial-to-mesenchymal transition FGFR fibroblast growth factor receptor GBM Glioblastoma multiforme GPCR G protein-coupled receptors GSK glycogen synthase kinase HGF hepatocyte growth factor HIF hypoxia-inducible factor LATS Large tumor suppressor homolog MAPK mitogen-activated protein kinase MGMT O6-methylguanine-DNA methyltransferase MMP matrix metalloproteinase MRI magnetic resonance imaging MST Mammalian sterile 20-like NSCIC non-small-cell lung cancer PCNA proliferating cell nuclear antigen PDGFR platelet-derived growth factor receptor PD-L1 programmed cell death ligand 1 PKA protein kinase PTEN Phosphatase and tensin homologue deleted on chromosome ten RTK receptor tyrosine kinase SCF receptor for stem cell factor STAT signal transduction and activator of transcription TAZ Transcriptional coactivator with PDZ-binding motif TEAD TEA domain family member TERT Telomerase reverse transcriptase TKI tyrosine kinase inhibitors TNBC triple-negative breast cancer WHO World Health Organism YAP Yes-associated protein

Chapter 1: Introduction

1.1 Glioblastoma

Gliomas are the most commonly diagnosed central nervous system (CNS) neoplasms, accounting for 80% of malignant primary brain tumors [1-4]. Gliomas include astrocytic tumors (astrocytoma, anaplastic astrocytoma, and glioblastoma), oligodendrogliomas, and ependymomas [1, 2, 5, 6]. Glioma diagnosis is based on microscopic analysis and histological features (cellularity, mitotic figures, necrosis, and vascular proliferation) and genetic features (e.g. 1p/19q LOH as a molecular marker for oligodentroglioma and p53 mutation/ATRX loss as molecular markers for astrocytoma) [7-10]. The World Health

Organization (WHO) groups astrocytomas into Grade I to IV based on increasing malignancy

[11-13].

Glioblastoma Multiforme (GBM), accounts for 50% of gliomas in all age groups and more than 60% of all brain tumors in adults [14]. GBM occurs at all ages with a peak between 55 and 60 years old [15]. GBM incidence is less than 10 per 100,000 globally [16, 17]. It is a very aggressive malignancy, with median survival of 14 to 15 months after diagnosis [18, 19] and less than 6% 5-year survival [20-22]. Familial heredity has little impact on GBM (<1%)

[21, 22] and the only confirmed risk factor for GBM is prior ionizing radiation exposure [23-

25]. GBM remains incurable and for recurrent GBM patients, the median survival is only 8-9 months even with treatment.

GBM Diagnose and Symptoms

GBM is diagnosed by increased cell density, areas of necrosis (soft and yellow), hemorrhage, cellular atypia, mitotic activity, and cystic and gelatinous areas [2, 26, 27]. Cerebral hemispheres are the most common location, and 95% of GBM generate in the supratentorial

1 region, others may present in the cerebellum, brainstem and spinal cord [28]. These tumors demonstrate a pleomorphic cell population from small-undifferentiated cells to large multinucleated cells with multifocal necrosis, pseudopalisading nuclei and prevalent mitotic activity [29]. Vascular endothelial cells proliferation and glomeruloid structures are also major characteristic features of GBM [2].

As a direct effect of necrosis, GBM patients are often suffer from focal neural deficiency (40-

60%) and cognitive impairments [30]. Patients display symptoms depending on tumor location: if a tumor locates in the temporal lobe area, patient will have hearing and visual problems; if a tumor locates in frontal lobe, patient shows personality changes; and if a tumor is large and massive, patient can present with headache, imbalance, and incontinence [30].

With the increase in tumor size and edema in the surrounding region, a secondary effect of increased intracranial pressure will present, resulting in symptoms such as headaches (a hallmark in 30-50% of GBM patient), vomiting and papilledema [30]. 20-40% of GBM patients may develop seizures [30].

The gold-standard imaging technique in diagnosing GBM is magnetic resonance imaging

(MRI). T1-weighted MR scans show hypointense lesions while T2-weighted MR scans show hyperintense lesions [29]. Glioma patients show a central area of necrosis with surrounding white matter edema. For patients who cannot undergo MRI, computed tomography (CT) can also be used to visualize the hypointense area. Glioma patients usually also demonstrate a midline shift as a result of edema [30].

Molecular classification of GBM

As mentioned above, current diagnosis and grading of gliomas were based on histological features and degree of malignancy, such as the presence and degree of atypia and mitotic activity, and specific hallmarks for some subtypes such as microvascular proliferation and/or pseudopalisading necrosis in the case of GBM [31].

There are some limitations of these classification system. One problem is that the diagnosis is subjective and interobserver variability exists. Histological classification can further be complicated by insufficient or nonrepresentattive tissue sampling [32]. With the recent detailed findings on molecular alterations within gliomas, a refinement of diagnostic criteria, prognostic biomarkers, and more effective targeted therapies can be developed.

In 2008, The Cancer Genome Atlas (TCGA) group originally investigated 206 GBM tissue specimens for genomic characterization [33]. Several biomarkers of GBM have been discovered: IDH1/2, ATRX, and Histone Cluster 1 H3 Family Member A (HIST1H3A or

H3F3A) [34]. Most of them lie in three core pathways: (1) receptor tyrosine kinase (RTK)/rat sarcoma (RAS)/PI3K (88%), (2) p53 (78%), and (3) RB (87%).

(1) RTK signaling pathway

Based on 130 human cancer cell lines, profiling of tyrosine kinase activation showed that the most frequently activated tyrosine kinases were EGFR, fibroblast growth factor receptor 3

(FGFR3), protein tyrosine kinase 2 (PTK2), and SFKs including SRC, LYN, and LCK [35].

In half of GBM cases, EGFR gene is amplified, and 20-50% have EGFRvIII mutations [36-

40]. EGFRvIII is associated with a worse prognosis than wild-type EGFR expression alone

[41, 42]. Unfortunately, clinical trials with EGFR inhibitors have not yet been successful, likely due to poor BBB permeability of drugs and intratumoral molecular heterogeneity [43].

In nearly 15% glioma, PDGFRA is amplified and amplification enriched in proneural subtype

[44, 45] PDGF ligands A-D are also up-regulated in 30% of glioma surgical samples and cell lines [46-50]. In 5% glioblastomas, the c-Met RTK is amplified [33, 51]. In GBM, c-MET is coactivated with increased EGFR/EGFRvIII level [52-54]. The c-MET ligand, HGF transcriptionally activates EGFR ligands (TGF-alpha and heparin-binding EGF (HBEGF))

[55]. GMB is recently found to be composed of heterogeneous subpopulations expressing wild type EGFR/EGFRvIII [56, 57]; PDGFRA [47]; c-Met [58]; angiogenic factors [59]; and

3 adhesion molecules [60]. Angiogenesis switch is controlled by VEGF (regulated by hypoxia state via HIF1a and acting on VEGFR2/KDR) and is often deregulated in GBM [61-67].

Demonstrated by FISH analysis from a whole-brain autopsy of an untreated bilateral GBM patient, there was a striking anatomic distribution of EGFR- and PDGFRA- amplified cells suggesting the predominant pattern was mosaic amplification of a single RTK [68, 69]. In

GBM, this integrated signaling by several RTKs makes it insufficient to treat tumor by targeting one of them [52, 53, 70].

(2) P53 signaling pathway and RB signaling pathway

In the p53 pathway, 49% of mutations occur at CDKN2A and 35% mutations at TP53; while in the RB pathway, CDKN2A, CDKN2B, and RB homozygote deletion occur in 52%, 47%, and 11%, respectively [33].

The majority of GBM cases (>90%) are primary tumors that develop rapidly de novo, without clinical or histological evidence of a less malignant precursor lesion, while secondary

GBM develop through progression from low-grade diffuse astrocytoma or anaplastic astrocytoma and manifest in younger patients [71]. Hallmarks for primary GBM include

EGFR overexpression, mouse double minute 2 (MDM2) overexpression, p16 deletion, TERT promoter mutation and chromosome 10q loss of heterozygosity (LOH). While the molecular indicators of secondary GBMs include platelet-derived growth factor A (PDGFA)/ PDGFRA overexpression, IDH1/2 mutation, TP53, retinoblastoma (RB) and ATRX LOH [2, 71-75].

IDH mutation is an important molecular marker for distinguishing primary and secondary

GBM. IDH1 mutation is found in 70% of grade II-III astrocytomas and secondary GBM

(associated with TP53 and ATRX mutations), while it is presented only in 5% of primary

GBM [76-78]. IDH1 mutation (R132H as the most frequent form) correlates with a better prognosis and increased overall survival [79]. Wild type IDH1 catalyzes NADP+-dependent

4 oxidation of isocitrate; however, mutant IDH1 (at R132) catalyzes NADPH-dependent reduction of alpha-KG to 2-HG [80, 81]. 2-HG induces epigenetic changes (hypermethylation) in human gliomas [82] and activates PDGFRA, further inducing gliomagenesis [83].

GBM can be classified into classical, mesenchymal, and proneural subtypes [2, 33, 45, 84,

85]. Classical GBM tumors are identified by chromosome 7 amplification and chromosome

10 loss; of which 97% display EGFR amplification [45] and 95% show CDKN2A (Ink4a/ARF) homozygous deletion [86]. Mesenchymal subtype shows loss of NF1; upregulated markers of epithelial-to-mesenchymal transition (EMT) (CD44, MERTYK); and high expression of NF- kB pathways and TNF superfamily [26, 44, 45]. Proneural subtype presents with alteration of platelet-derived growth factor receptor alpha (PDGFRA) and point mutations in IDH1/2 genes [45, 87]. The proneural subtype has a better prognosis and longer overall survival and most secondary GBMs or GBMs that occur in younger patients are classed into the proneural subtype [44, 45].

Current treatment for GBM

The standard treatment for GBM is surgery with maximal possible resection and then followed by radiotherapy and chemotherapy to treat residual tumor cells [88, 89]. As a highly invasive tumor, GBM generally cannot be cured and relapse occurs typically within 2-3 cm of the original lesion [16, 90, 91]. The Stupp regimen has become standard care for the treatment of GBM since 2005 and has led to significant survival improvements. It combines radiotherapy and chemotherapy with temozolomide, an alkylating agent [18]. The other two

FDA approved alkylating agents used before are temozolomide (TMZ), carmustine (BCNU) and lomustine (CCNU) [16]. BCNU and CCNU are very harsh and associated with early resistance and multiple side effects [92]. O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is present in 50% of GBM and a sign for better response to

5 temozolomide and prolonged survival [37, 93, 94]. When treating patients, the invasiveness of GBM, radiation necrosis, radiation-induced permanent neuronal damage and radioresistance need to be taken into consideration [16]. Tumor-treating fields (TTF), a novel cytotoxic mechanism, adapts directional fields of low-intensity radiation of 150-200 kHz throughout the tumor, leading to disruption of mitotic spindle formation and cell death in dividing cells [95, 96].

With recent data refined our understanding of the immune environment in CNS, we now know the CNS is an immunologically distinctive site, with accessibility to lymphocytes and robust immune responses. Much progress has been achieved in GBM immunotherapy. First,

EGFRvIII, IDH1R132 and TERT have been selected as targets for monoclonal antibodies: such as ACT IV targeting EGFRvIII; NOA-16 and RESIST for IDH1R132 [97]. Second, multipeptide vaccines have also been developed. IMA-950 is a combination of 11 tumor- associated peptides and the synthetic hepatitis B virus marker peptide IMA-HBV-001. ICT-

107 consists of patient-derived DCs incubated ex vivo with six peptides from protein based on their over-representation in the gene-expression profiles of GBM cells compared with nonmalignant tissues [98]. Third, there have been CAR-T cells designed for IL-13Ra2 (often overexpressed on GBM cells) and EGFRvIII [99, 100]. For both, there was no sign of cytokine-release syndrome or neurotoxicity, suggesting the approach is safe. However, overall survival benefit of these therapies did not seem to be very promising. Last but not least, anti-PD1 and Anti-CTLA4 therapy have been tested in GBM. The median overall survival of recurrent patients treating with nivolumab is 9.8 months while with bevacizumab is 10.0 months [101, 102]. Poor results to date might be due to the fact that GBM is a solid tumor with relatively low mutational load and low T-cell infiltration comparing to other tumors.

1.2 Receptor Tyrosine Kinase and Epidermal Growth Factor Receptor

RTK signaling

RTKs are a family of cell surface receptors that mediate important signaling cascades involving in cell proliferation, differentiation, survival, and migration [103-106]

The major downstream signaling pathways are: MAPK (Raz/Raf/ERK1/2), PI3K/AKT and signal transduction and activator of transcription (STAT) pathways. The MAPK pathway is highly mutated in GBM: 86% of GBM presents at least one alteration that affects the MAPK pathway according to TCGA. This pathway regulates hundreds of proteins involved in different cellular functions [107, 108], such as MYC, JUN, FOS, ELK1, ETS1, p63 involving in cell proliferation [109]; MLC and MLCK involving in cell migration [110]; or conexin 43 regulating GAP junctions [111]. Three RAS genes (K-RAS H-RAS and N-RAS) are mutated in 20-30% of all human cancer [112]. High RAS activity in GBM is observed, although RAS mutation is rare in GBM (~2%) [33, 113].

The PI3K/AKT pathway is able to phosphorylate substrates participating in cell cycle regulation [113], apoptosis (e.g. BCL2 associated death protein (BAD) [114] and Caspase-9

[115]), protein synthesis [115, 116] and glucose metabolism [117-121]. In GBM, the most frequent mutation which affects this pathway is in the tumor suppressor PTEN, which is a key negative regulator [122]. About 20-40% of GBM patients present with PTEN mutational inactivation and about 35% have from genetic loss due to promoter methylation [123, 124].

The JAK/STAT signaling pathway represents as a link between extracellular signals and transcriptional responses and induces anti-apoptotic and cell cycle regulatory proteins [125].

The role of STAT3 in GBM tumorigenesis depends on other gene mutations [126]. Generally,

STAT3 promotes EMT [127], suppresses the antitumor response of the immune system and induces tumor stemness and angiogenesis [128-130]. Moreover, the interaction of JAK2 with

EGFR induces resistance to EGFR inhibitors; inhibition of JAK2 sensitizes U87MG cells’ response to Erlotinib [131].

RTK subfamilies

About 58 RTKs have been found in humans (e.g. EGFR, VEGFR, and PDGFR). According to activating ligands and structure, they are classified into 20 subtypes or subfamilies [132-

134]. RTKs are normally activated through ligand-induced dimerization and receptor autophosphorylation on tyrosine, which acts as an anchor and phosphorylates downstream signaling molecules [104, 135-137]. Abnormal RTKs activation in cancers is often mediated by ligand independent activation mutations, genomic amplification, and chromosomal rearrangements [138-141].

EGFR members are commonly mutated in many cancers [142]. Overexpression of HER2

(ERBB2) is found in 10-30% breast cancer patient [143], and overexpression of EGFR found in 30-50% of GBM [144, 145], 25-82% in colorectal cancer [146-149] and 5-20% of non- small-cell lung cancer [150]. Several generations of EGFR inhibitors have been developed and will be introduced later. The VEGFR family plays a key role in angiogenesis and is important for tumor vascular formation and metastasis [151-154]. VEGFR inhibitors have been developed to reduce angiogenesis and lymphangiognenesis [151]. Sorafenib (Nexavar) has been used in renal cell cancer, liver cancer, and thyroid cancer [155-157]. Sunitinib

(Sutene, SU11248) has been shown to improve overall survival in renal cell cancer and gastrointestinal stromal tumor [158, 159]. Bevacizumab (Avastin), a monoclonal antibody has been used in combined chemotherapy treating metastatic colorectal carcinoma [160]. PDGFR amplification presented in 5-10% of GBM, esophageal squamous cell carcinoma and artery intimal sarcomas [46, 49, 161-164]. Imatinib (Gleevec) has been used to target PDGFR in gastrointestinal stromal tumors KIT positive, but many patients tend to develop resistance

[165]. Amplifications, point mutations or chromosomal translocations disrupt FGFR

8 functions present in breast cancer, gastric cancer, bladder cancer, oral squamous carcinoma, ovarian cancer, prostate cancer, lung cancer, uterus cancer, brain cancer, stomach cancer, head and neck cancer, colon cancer and malignant melanoma [166-186]. Brivanib (BMS-540215), a dual inhibitor for FGFR and VEGFR has been shown to be effective in mouse model of human hepatocellular carcinoma [187]. CHIR-258 (TKI-258), a multiple-function inhibitor for VEGFR, PDGFR, FLT-3, c-Kit, and FGFR is effective in multiple myelomas [188, 189].

MET, hepatocyte growth factor (HGF) receptor, is reported to be mutated or amplified in neuroblastoma, GBM, osteosarcomas, esophageal and gastric colorectal cancers, multiple myelomas and T-cell leukemia, involving in cancer proliferation, invasion, and metastasis

[190-199]. K252a, the first generated c-MET inhibitor, and others, such as SGX523, ARQ197

(ArQule), have been tested to be effective in multiple cancer cell lines [200-203]. C-Kit

(CD117), the receptor for stem cell factor (SCF), with its major oncogenic mutated form c-

KitV560G and c-KitD816V is present in leukemia, gastrointestinal stromal tumors (GIST), testicular germ cell tumor (TGCT) and melanoma [204]. Inhibitors have been developed but have made a little impact: Imatinib, Dasatinib, and PKC412 [205-207]. Small inhibitors targeting multiple RTKs have been developed to inhibit cell proliferation and angiogenesis, such as Sunitinib, Sorafenib, Pazopanib, and Nilotinib [208-211].

EGFR and EGFRvIII

Among these subfamilies, the EGFR mutation occurs in about 40% of GBM [71, 212]. Other than amplification, the EGFRvIII mutation, an in-frame deletion of exons 2-7, is also very common in GBM (about half of the cases) and leads to a hyperactivated downstream signaling cascade [213, 214]. Point mutations, such as R108K, A289V/ D/T, G598D, are also identified in 24% of GBM patients [213]. When located on the plasma membrane, EGFR activates previously introduced downstream RTK signaling: MAPK, PI3K/AKT, and

JAK/STAT. Phosphorylation of Y845 of EGFR stimulates mitochondrial relocation of EGFR,

9 resulting in decreased cytochrome oxidase subunit II (COXII) activity and respiratory inhibition [215]. EGFR can also function as a transcription cofactor in the nucleus [216].

With STAT3/5, EGFR enhances transcription of genes such as MYC, Aurora-A kinase and others critical in cell growth and survival [216]. Nuclear EGFR can also serve as a kinase to phosphorylate DNA-dependent protein kinase (DNA-PK), proliferating cell nuclear antigen

(PCNA) and histone H4 to regulate DNA repair and replication [217, 218]. Due to the gene deletion, EGFRvIII lacks amino acids 6-273, resulting in ligand-independent constitutive activity [219-221]). Even though the kinase activity of EGFRvIII is much weaker than ligand-activated wild type EGFR, but this weak constitutive kinase activity turning on MAPK,

PI3K/AKT and, JAK/STAT is sufficient and important to confer growth advantage [221-227].

And both wild type EGFR and EGFRvIII can translocate into the nucleus and drive proliferation/ DNA damage repair [216]. EGFRvIII is not found in normal tissue, suggesting it can serve as a therapy target [228], even though a recent vaccine using EGFRvIII as a tumor-associated antigen has failed phase III clinical trial [229, 230]. EGFR need to dimerize and phosphorylate each other to activate downstream signaling, wild type EGFR can phosphorylate EGFRvIII, but EGFRvIII cannot phosphorylate wild type EGFR [231]. But wild type EGFR cannot substitute for EGFRvIII in driving invasive glioma formation [232-

234]. EGFRvIII cannot phosphorylate EGFR [231, 235], but EGFRvIII can induce expression of EGFR ligands, such as TGF-α and HB-EGF [236], and form transient dimer with EGFR and other ERBB family members [235, 237, 238] to promote tumor growth [239].

EGFRvIII also, in paracrine ways, supports the growth of wild type EGFR expressing cells via interleukin 6 (IL6) and glycoprotein 130 [57]. By epigenomic and transcriptomic analysis

[240], EGFRvIII was found to specifically activate >2000 enhancers and regulate GBM sensitivity to drugs (such as bromodomain ligand JQ1). Specifically, EGFRvIII activates

MET, which in-turn drives STAT3 [241, 242]; EGFRvIII also activates c-SRC, which

10 promotes secretion of VEGF and angiogenesis [243]; EGFRvIII can up-regulate Bcl-XL, which is a potent inhibitor of apoptosis [244]; and EGFRvIII induces invasiveness through matrix metalloproteinase (MMP)-13 [245].

There are at least three feasible ways to target EGFR: small molecule tyrosine kinase inhibitors (TKIs), neutralizing antibodies, and RNAi therapies (under pre-clinical trials).

Three generations of TKI have been developed to target the extracellular ligand-binding site of EGFR [246]. The first-generation EGFR inhibitors (such as Erlotinib (Er) and Gefitinib

(Ge), both approvded by the FDA) were designed for targeting ATP/substrate-binding pocket in the tyrosine kinase domain of EGFR and used in patients with lung cancer. The second- generation binds irreversibly to the tyrosine kinase domain. In which, Afatinib (phase I/II trial) and Dacommitnib (preclinical trial) are FDA approved [247, 248]. One of the third- generation EGFR inhibitors, AZD9291 (Osimertinib (OS)) that is discussed in our experiments later displays good blood-brain barrier (BBB) penetration and overcomes EGFR

T790M mutation in lung cancer [249, 250]. For the neutralizing antibody therapy, FAD- approved anti-EGFR monoclonal antibodies: Cetuximab (C225; Erbitux), Panitumumab

(ABX-EGF; Vectibix), and Nimotuzumab, prevent ligand binding or dimerization to inhibit signaling [251-254]. Other intradermal vaccines CDX-110 and GM-CSF specifically target

EGFRVIII, which is a tumor-associated antigen [255]; and there are also engineered bispecific T-cell engagers (BiTEs) (e.g. bscEGFRVIIIxCD3), which bind to both CD3 and

EGFRVIII and can direct T-cell to EGFRVIII expressing GBM cells [256]. In RNAi therapy, siRNA or antisense oligonucleotides are under development [257].

However, due to heterogeneity of GBM, intracellular and intercellular “transactivation” of

RTK is common, and RTK signaling also crosstalk with other signaling pathways such as

GPCR and wnt [258-261]. Targeting EGFR or any single RTK is usually not effective [53, 68,

262, 263]. Downstream effectors of RTK may be better targets for GBM therapies.

1.3 Hippo pathway and TAZ/YAP

Hippo pathway

The Hippo signaling pathway was first identified in Drosophila, where mutant Warts (wts),

Salvador (sav), Hippo (hpo), and Mob as tumor suppressor (mats) genes resulted in tissue overgrowth [264-269]. Yorkie (yki) was later discovered in a WTS-interacting protein screen as the key transcription co-activator of the Hippo pathway in organ size regulation [270].

Hippo pathway is a very important signaling pathway and highly conserved in mammals [264,

265, 267]. Mammalian sterile 20-like 1/2 (MST1/2, also called STK4/3), Salvador (SAV1),

Large tumor suppressor homolog 1/2 (LATS1/2), MOB kinase activator 1A/B (MOB1a/b), and YAP/ TAZ (also called WWTR1), are mammalian orthologs of HPO, SAV, WTS, MATS, and YKI respectively [271-273]. When the Hippo signal is on, LATS is phosphorylated by

MTS, and then phosphorylates YAP/TAZ to retain them in cytoplasmic by 14-3-3 and in turn triggers YAP/TAZ degradation through ubiquitination. When the Hippo signal is off, unphosphorylated YAP/TAZ are translocated into the nucleus, bind to their transcription partner (such as TEAD, RUNX1/2, ErbB) to activate downstream gene transcription [270,

274-295].

TAZ/YAP regulation

As the key transcriptional co-activators, TAZ and YAP are contextually regulated through many molecular mechanisms. Cell contacts (such as cell adhesion and formation of the tight junction), mechanical cues (such as cell geometry, extracellular matrix stiffness, and tissue tension) and cellular attachment/detachment to ECM have been shown to regulate TAZ/YAP activation through the Hippo pathway [273, 279, 284, 296-301]. Lysophosphatidic acid, thrombin, angiotensin II and estrogen activates TAZ/YAP through Ga12/13 or Gaq/11 coupled receptors; meanwhile, epinephrine and glucagon can repress TAZ/YAP through Gas- coupled G protein-coupled receptors (GPCRs) and protein kinase A (PKA) [284, 302-308].

TAZ/YAP can be ubiquitinated and dissembled through a complex composed by Axin, adenomatous polyposis coli (APC), and glycogen synthase kinase-3 (GSK3), which are regulated by the Wnt signaling [309-311]. The regulation of EGF and insulin on TAZ/YAP has been controversial. It is reported that EGF and insulin-regulated YAP/YKI activity through Ras/Raf/MAPK or PDK1/PI3K/AKT in cultured mammalian cells and drosophila

[312-314]. TAZ is also stabilized upon PI3K activation, which is mediated by direct phosphorylation by GSK3 [315, 316]. However, YAP activity remained normal with the treatment of PI3K/AKY inhibitors or in PDK1 null embryonic cells [300, 304]. Metabolism also affects TAZ/YAP activity. Nutrient starvation (glucose, lipid, and amino acids) depresses

TAZ/YAP through LATS and interrupts interaction between them and TEA domain family members (TEADs) [317-320]. Alternatively, oxygen deprivation activates hypoxia-inducible factor 1 (HIF1), which can direct activate TAZ transcription [321], or stabilize TAZ/YAP through the ubiquitination and degradation of LATS [321, 322].

TAZ/YAP functions in human cancers

As essential regulators of cell growth, TAZ/YAP is found to be important in various types of tumors. In Her2-positive breast cancer, triple-negative breast cancer (TNBC), non-small-cell lung cancer (NSCLC), hepatocellular carcinomas (HCCs), and cholangiocarcinoma (CCs);

TAZ/YAP expression correlates with grade and prognosis [286, 323, 324]. In spontaneous tumor models, conditional knockout of YAP in mammary gland extends tumor latency [325] and combined TAZ/YAP knockout suppresses tumor initiation in a WNT-driven, TNDC-like mammary tumor model [326]. Combined with RasG12D (gain of function) and loss of LKb1,

YAP is critical for tumor progression and metastasis in the NSCLC mouse model [327].

TAZ/YAP is required for HCC and CC in mouse models and can mediate the dedifferentiation of hepatocytes to a bipotent liver progeny state [328, 329]. TAZ/YAP nuclear expression is stronger in pancreatic ductal adenocarcinomas than benign lesions and

13 is essential for malignant transition [330, 331]. TAZ/YAP is also hyperactive and required in mouse models of squamous cell carcinomas and basal cell carcinomas [332, 333].

TAZ/YAP regulated genes are involved in many important oncogenic processes affecting cell proliferation, plasticity, drug resistance and metastasis [286]. Sustained TAZ/YAP activity promotes aberrant cell proliferation, which involves the regulation of the cell cycle, DNA duplication/repair, mitosis, glycolysis, glutamine metabolism, and nucleotide biosynthesis

[300, 334-344]. Moreover, TAZ/YAP can act in an autocrine way to form self-sustainable positive feedback loops through their target genes [345, 346]; especially other proto- oncogenic transcription factors, such as MYC, JUN and FOS-like factors [332, 344, 347-349].

TAZ/YAP overexpression can convert normal differentiated cells (such as mammary luminal cells, pancreatic acinar cells, hepatocytes, neurons, and astrocytes) into stem-like cells of the same tissue [329, 350]. TAZ/YAP also involves and can be essential for cancer stem cells

(CSCs) [351-356]. The mechanisms underlying how TAZ/YAP induce stemness are under study and may involve the EMT process [356]. These TAZ/YAP-induced CSC features involve the initiation of tumor formation, induction of chemoresistance, metastasis, and expansion of undifferentiated cell population [289, 302, 335, 353, 357-362]. Besides inducing cancer stemness, TAZ/YAP also promotes therapeutic resistance [363, 364] by activating alternative survival pathways [335, 357, 358, 365] and directly interrupts tumor microenvironment [366]. Thus, targeting TAZ/YAP will be a potential way to prevent drug resistance and tumor recurrence [326, 358, 365, 367]. TAZ/YAP participates in the regulation of metastasis through many steps [368]: 1.effects on cytoskeletal remodeling, F-actin dynamics, and Rho-GTPase activating proteins (such as ARHGAP29) [369]; 2. promotion of resistance to tumor cell anoikis in blood or lymphatic circulations [300, 301, 337, 370]; 3. induction of many genes that stimulate EMT (e.g. ZEB1/2, CYR61) [293, 371-373].

TAZ/YAP signaling also promotes an oncogenic tumor microenvironment. TAZ/YAP is central for tumor-host competition [374, 375]. This effect is well studied in drosophila: loss of the polarity factor Scribble, can deregulate Hippo pathway, activate YKI (drosophila homolog of TAZ/YAP), and inactivate contact inhibition of tumor cell and help them escape from a monolayer [376-379]. And due to this surviving advantage, tumor cells can induce death of nearby normal cells [375]. As mentioned in the earlier paragraph, extracellular matrix (ECM) stiffness is one of the key regulators of TAZ/YAP activity, and ECM rigidity may contribute partially to the tumor-suppressing mechanism of our body [297, 380, 381].

Aging, tissue damage, and inflammation can cause ECM stiffening, and disrupt TAZ/YAP regulation. During tumor progression, ECM proteins (laminin, laminin-associated proteins, and proteoglycans) are accumulated at the tumor border facilitating tissue stiffness and collagen remodeling [382, 383]. This mechanotransduction change leads to TAZ/YAP activation [297, 384, 385], and this activation further transcribes downstream TAZ/YAP targeting genes participating in ECM-modifying, F-actin remodeling and focal adhesion [369,

386-390]. TAZ/YAP is also up-regulated in cancer-associate fibroblasts (CAF) to maintain the ECM stiffness and sustain tumor proliferation [391]. Inflammation, on one hand, activates

TAZ/YAP through IL6-GP130; on the other, is enhanced by TAZ/YAP regulated inflammatory interleukins [392, 393], which in turn feedback on CAFs and epithelial cells to self-sustain YAP/TAZ activity [394]. Besides tumor cells, TAZ/YAP is also activated in epithelial cells via epithelial-microenvironment positive feedback loop to suppress immune surveillance. In mouse models of liver cancer, YAP overexpression in hepatocytes induces infiltration of tumor promoting macrophage [395-398]. The TAZ/YAP direct target, C-C motif chemokine ligand 2 (Ccl2, also known as Mcp1), facilitates this recruitment [395, 396].

This YAP-dependent macrophage recruitment was also found in pancreatic adenocarcinoma

[399]. In pancreatic and prostate cancer, TAZ/YAP was also essential for recruiting myeloid-

15 derived suppressor cells (MDSCs), which are important for inhibiting cytotoxic T cells and promoting tumor angiogenesis [399-401]. This involved the TAZ/YAP/TEAD targeted cytokines: IL6, macrophage colony- stimulating factor (CSF1), granulocyte- macrophage colony-stimulating factor (CSF2), granulocyte colony-stimulating factor (CSF3) and C–X–C motif chemokine ligand 5 (CXCL5) [399, 400]. TAZ/YAP also regulates programmed cell death ligand 1 (PD-L1) transcription in multiple cancers (melanoma, lung cancer, and mesothelioma) [106, 402, 403] to promote immune escape of cancer cells.

Small molecules that interrupt the interaction between TAZ/YAP and TEADs have been discovered. One of them is the porphyrin family, especially Verteporfin (VP). VP, a benzoporphyrin derivative, is a medication used as a photosensitizer for photodynamic therapy to eliminate the abnormal blood vessels in the eye associated with conditions such as the wet form of macular degeneration. It can inhibit the YAP-TEAD interaction and transcriptional activity in vitro. It has also been found to suppress hepatocellular carcinoma caused by YAP overexpression or NF2 deletion in mouse livers. However, VP is light- sensitive and its biodistribution in brain tumors is still unclear [404]. Another polypeptide, termed “super-TDU” is targeted to the TAZ/YAP-TEAD and VGLL4-TEAD and has been shown to suppress tumor growth in mouse models [405].

TAZ/YAP functions in GBM have also been studied by many groups, even though Hippo pathway mutations are very rare in human GBM [406]. Bhat et al. showed that TAZ and

TEAD targeted genes drive the MES differentiation of malignant glioma and plays an important role in inducing glioma resistance [407]. Liu et al. found in GBM, that amlodipine activates Ca2+ entry to cells and store-operated Ca2+ entry (SOCE), which in turn triggers

LATS phosphorylation and restrains TAZ/YAP in the cytoplasm and inhibits tumor growth

[408]. Zhang et al. found that TAZ inhibition contributes to radiation-induced senescence in

16 glioma cells [409]. TAZ/YAP was also found by others to protect tumor cells from DNA- damaging agents and RTK inhibitors [358, 410-415].

1.4 Rationale and Hypothesis

Rationale

GBM is a highly aggressive type of brain tumor. More than 80% of GBM cases present with molecular alterations affecting RTK signaling. EGFR is one of the most frequently mutated

RTKs in GBM. EGFR overexpression and EGFRvIII mutation occur in ~ 60% and ~ 30% of

GBM cases [36, 38, 52, 70]. EGFR mutation promotes differentiation, metabolism, proliferation, and survival, through its downstream signaling (PI3K/Akt, MAPK pathways and JAK/ STAT pathways) [213, 416-420]. Several generations of small inhibitors and immune therapies have been developed to target EGFR or EGFRvIII for GBM therapy.

However, little success has been achieved [53, 335, 343, 421]. This project addressed a novel downstream effector of EGFR signaling. Our founding broadens our understanding of the

EGFR signaling pathway and will likely facilitate GBM therapeutic development.

GBM are highly heterogeneous, with different pathways activated in different clones, forming a complex autocrine/paracrine network to stimulate tumor growth. Targeting single

RTKs has not been not very successful in GBM. On one hand, this can be attributed at least in part to poor BBB penetration of the inhibitors; on the other hand, it may be also due to the complexity of paracrine/autocrine RTK signaling from heterogeneous tumor cells and ECM.

Our finding also suggest a novel RTK spreading mechanism mediated by the EGFR-TAZ signaling axis.

We proposed TAZ as an EGFR effector in GBM. TAZ, and its homolog YAP, are transcriptional co-activators, controlling genes involved in cell proliferation. TAZ and YAP are very important regulators in development and currently found to participate in multiple

17 cancers, through promoting aberrant cell proliferation, overcoming apoptosis, reprogramming non-stem tumor cells into cells with full cancer stem cell (CSC) attributes, cross-talking and reconstructing tumor microenvironment [289, 337, 338, 351-354, 361, 362, 371, 372, 393,

400, 422-424]. TAZ/YAP hyper-activation in tumors is context-dependent and contextually regulated by different upstream signaling. The WNT pathway has been shown to regulate

TAZ in mammary tumor [425] and intestinal epithelium and colon tumorigenesis [310, 426].

And the G-protein coupled receptor (GPCR) pathway has been shown to regulate TAZ/YAP in melanoma [304, 427]. Bhat et al. [407] showed that TAZ expression is not regulated through the traditional Hippo pathway in GBM. It is essential to know how TAZ/YAP is regulated in GBM. Our findings identify a previously undiscovered TAZ regulation pathway in GBM and potentially in other human cancers.

Verteporfin inhibits TAZ/YAP by abrogating interaction between TAZ/YAP and TEAD [428].

However, it may not be applicable to GBM therapy due to its uncertain BBB penetrating efficiency and to-be-define pharmacodynamics in GBM; new TAZ/YAP inhibitors or inhibitors targeting their upstream activators need to be developed in the context of GBM. In addition, this study screened multiple BBB crossing RTK inhibitors; one EGFR inhibitor showed the potency of TAZ inhibition in both GBM cell and xenograft models.

Altogether, this project deepened and broadened our understanding of EGFR signaling in

GBM. We identified TAZ as a signaling hub in coordinating and amplifying RTK signaling.

Finally, our discoveries support TAZ as a potential drug target for GBM therapy.

Hypothesis

This thesis was aimed to test the hypothesis: “EGFR activates a TAZ-driven oncogenic program in GBM”. We asked five specific questions based on this hypothesis.

Q1: Can EGF induce TAZ in GBM cells?

Q2: How does EGF induce TAZ expression (the roles of ERK1/2, STAT3, and AKT)?

Q3: What is the EGF-induced TAZ-dependent oncogenic program in GBM?

Q4: What are the effects of TAZ induction on GBM malignancy?

Q5: How can we develop novel and effective TAZ targeting strategies based on our discoveries?

Chapter 2: EGF induces TAZ transcription through EGFR and its downstream kinase pathway

2.1 Introduction

GBM is the most aggressive and common primary brain tumor. Hyperactivation in RTK signaling occurs in more than 80% of GBM patients, and majority harbors mutations related to EGFR signaling [36, 38, 52, 70]. Both EGFR amplification and EGFRvIII mutation is common in GBM patients. A better understanding of EGF-driven oncogenic events is important in developing more effective therapies for GBM patients. Here, we hypothesized that EGF regulates TAZ, a transcriptional co-activator and potential oncogenic driver.

TAZ participates in multiple cancers and is known to be regulated in context-depending ways in different tumor types.examples include the WNT pathway in regulating TAZ in mammary tumor [310] and intestinal epithelium and colon tumorigenesis [425] and GPCR pathway important in regulating TAZ/YAP in melanoma [304, 426, 427].

In this chapter, we tested our hypothesis that EGF induces TAZ in GBM. We tested our hypothesis in multiple GBM cell models by measuring both TAZ protein and RNA levels after EGF treatment. We also examined well-established TAZ targets (MYC and CTGF) to verify that EGF-induced TAZ is functionally important in GBM cells. Additionally, we used specific inhibitors of EGFR, AKT, ERK, and STAT3 to investigate how EGF induces TAZ in

GBM cells. Moreover, as EGFRvIII is a common mutation in GBM, we examined

EGFRvIII–expressing GBM cell lines using a lentiviral vector and also examined GBM cells with endogenous EGFRvIII expression. We found a ligand-independent hyperactivation of

TAZ in these EGFRvIII-expressing GBM cells.

2.2 Materials and Methods

Cell culture

Human GBM neurosphere lines: GBM1A and GBM1B; were originally established by

Vescovi and colleagues [429] and further characterized by us [429-431]. The M1123 (1123) neurosphere line was established from high-grade glioma patients and kindly provided by Dr.

Nakano [432]. A172 and U87MG cells were obtained from ATCC and grown in Dulbecco's modified Eagle's medium (DMEM, Mediatech, Cat# 10-013-CV) with 10% fetal bovine serum (FBS, BenchMark, Cat# 100-106). Cells were cultured in serum-free medium (Gibco,

Cat# 32500-035) supplemented with epidermal growth factor (EGF, PeproTech EC, Cat#

100-15) and fibroblast growth factor (FGF, PeproTech EC, Cat# 100-18B) and incubated in 5%

CO2/95% air condition at 37 ℃. All cells were incubated in 5% CO2/95% air condition at

37 ℃. pLEX-EGFRvIII plasmid construction and cell line generation

Human EGFRvIII (MSCV-XZ066-EGFRvIII, Addgene, Cat# 20737) coding sequence wass cloned into the MCS of the pLEX vector (Thermo Scientific, Cat# OHS4735) by SpeI (NEB,

Cat# R0133S)/Xhol (NEB, Cat# R0146S) double digestion. This ligation product was then transformed into NEB 5-alpha competent cell (NEB, Cat# C2987H) and selected on ampicillin (50ug/mL, Sigma, Cat# A0166) plate. All constructed plasmid underwent Midi- prep (Qiagen, Cat# 12143) after verifying its sequence. pLEX-EGFRvIII plasmid we constructed was packaged using Lipofectamine 3000

(Invitrogen, Cat# 2078159) and second-generation lentivirus packaging protocol using PAX2 and PMDIG vectors (Addgene, Cat# 12260). Cells were infected by lentivirus (MOI = 5) for

24h with TransDux Virus Infection solution (System Biosciences, Cat# LV850A-1). Stable

GBM cell lines were established by puromycin selection (2μg/ml).

Protein extraction and western blot analysis

Total cellular proteins were extracted with radioimmunoprecipitation assay (RIPA) buffer

(Sigma-Aldrich, Cat# R0278) containing protease and phosphatase inhibitors (Calbiochem,

Cat# C134544). SDS-PAGE was performed with 30-50 μg total cellular proteins using 4-12% or 4-20% gradient Tris-glycine gels (Invitrogen, Cat# XP04120BOX, XP04122BOX) following manufacturer’s instructions. The primary antibodies used were listed in table 1.

The secondary antibodies were labeled by including IRDye infrared dyes (LI-COR

Biosciences, 926-32211, and 926-68020). Western blot analysis and protein levels quantification were performed using the Odyssey Infrared Imaging System (LI-COR

Biosciences).

Immunofluorescence

Cells were collected by cytospin onto glass slides and fixed with 4% paraformaldehyde

(Sigma, Cat# 158127). Cells were permeabilized by Triton X-100 (Sigma, Cat# T8787) and immunostained with anti-TAZ antibody (Table 1) and Alexa Fluor 488–labeled secondary antibody (ThermoFisher, Cat# A32731). Images were taken and analyzed using the ApoTome

System (Zeiss).

RNA extraction and Quantitative real-time PCR

Total RNA was extracted using the RNeasy Kit (Qiagen, Cat# 74004). After reverse transcription using MuLV reverse transcriptase (Applied Biosystems, Cat# 4368814) and

Random primer, quantitative real-time PCR (qRT-PCR) was performed using SYBR Green

PCR reagent (Applied Biosystems, Cat# 4309155) and IQ5 PCR system (Bio-Rad). Primer sequences are listed in Table 2. Relative expression of each gene was normalized to 18S rRNA.

With the DNA fragment from ChIP, qRT-PCR was performed and Fold enrichment was calculated using the following formula: 2 (Ct Antibody IP/Ct IgG IP). Ct is the threshold cycle.

Chromatin immunoprecipitation (ChIP)

Cells were subjected to ChIP using the MAGnify ChIP system (Invitrogen, Cat# 492024) following the manufacturer’s protocol. TAZ-associated DNA or STAT3-bound DNA was immunoprecipitated using antibodies listed in Table 1 and Dynabeads magnetic beads

(Invitrogen, Cat# 10004D). Rabbit IgG served as the control. ChIP-enriched DNA was used for ChIP-PCR.

Inhibitors treatment

Inhibitors used in this chapter are listed in Table 3. Inhibitors were all added for 16 hours with growth factor deprivation.

Statistical analysis

All results reported here represent at least three independent replications. Statistical analysis was performed using Prizm software (GraphPad) and R/Bioconductor software package

[433]. Post hoc tests included the Students t test and Tukey multiple comparison tests as appropriate. All data are represented as the mean value ± standard error of the mean (SEM).

Statistical significance in limiting dilution assay was determined by the extreme limiting dilution analysis (http:// bioinf.wehi.edu.au/software/elda/) [434].

Gene expression data for human GBM samples (TCGA database) were normalized and summarized using GlioVis [435]. The following analyses (one-way ANOVA, linear trend and linear regression) were performed using Prizm software (GraphPad). The test for linear trend is a follow-up test after one-way ANOVA and asks whether the column means increase (or decrease) systematically as the columns go from left to right.

2.3 Results

TAZ expression in clinical GBM specimens.

We analyzed the relationships between TAZ expression, glioma grades and patient outcomes in three glioma databases (TCGA, CGGA and Rembrandt) using the GlioVis data portal

[435]. TAZ is elevated in GBM specimens as compared to low-grade glioma and normal brain specimens (Fig. 1A) and positively correlated with tumor grade (Fig. 1A). TAZ-high

GBM specimens also showed poor prognosis when compared to TAZ-low specimens in both

TCGA and CGGA datasets (Fig. 1B). The potential oncogenic role of TAZ in GBM warranted elucidating upstream drivers of TAZ hyperactivation for developing effective TAZ- targeting strategies.

TAZ expression positively correlates with the expression of RTK ligands and receptors.

To identify upstream drivers of TAZ hyperactivation in GBM, we performed gene correlation assays on the TCGA and CGGA GBM database. The expression of RTKs (e.g. EGFR,

FGFR1, MET and PDGFRB) and their ligands (e.g. EGF, FGF1, FGF2, HGF, and PDGFA) showed positive correlation with TAZ expression in the TCGA dataset (Fig. 2 and Fig S2).

Results from the CGGA database are consistent with that from the TCGA database (Table 4).

These associations between TAZ and RTKs in clinical specimens led to our hypothesis that to-be-defined RTK signaling components act through TAZ to drive GBM malignancy.

EGF induces TAZ expression in GBM cells.

To explore the effects of growth factors on TAZ expression, we measured TAZ expression in response to four RTK ligands (EGF, FGF2, HGF and PDGF) associated with GBM tumorigenesis [64, 436-439]. The GBM neurosphere line GBM1B was cultured in growth factor-depleted medium overnight followed by RTK ligand stimulation. EGF most potently induced TAZ protein expression (Fig. 3A), and upregulated TAZ transcription (Fig. 3B).

We further assessed the kinetics of TAZ induction in EGF-stimulated GBM1B neurospheres.

EGF rapidly induced ERK phosphorylation within 30 minutes followed by peak TAZ induction (3.5 fold) at 4 hours (Fig. 3C). Similar kinetics of TAZ induction was found in three additional GBM cell models (GBM1A neurosphere line, and the A172 and U87MG monolayer adhesion cell lines, Fig. 3C).

TAZ and YAP are paralogous genes that are both induced by the Hippo signaling pathway

[293]. We found that EGF did not significantly induce YAP expression in GBM1B and A172 cells (Fig. 3D), contrasting with its capacity to induce TAZ. EGF also did not alter levels of phosphorylated and total LATS1, a key Hippo-signaling kinase that mediates TAZ/YAP phosphorylation and degradation (Fig. 3E). These results indicate that EGF has the potential to contextually activate TAZ but not YAP in GBM cells through Hippo-independent mechanisms.

EGF induces the nuclear TAZ level.

Since TAZ functions as a transcriptional co-activator, we measured the effect of EGF on nuclear TAZ levels. EGF treatment upregulated nuclear TAZ 2.3-fold at 4 hours (Fig. 4A).

TAZ immunostaining and quantification also showed nuclear translocation of TAZ protein in response to EGF treatment (Fig. 4B).

EGF activates TAZ gene targets in GBM cells.

To further explore the function of EGF-induced TAZ, we showed that TAZ in EGF-treated cells more actively bound to the promoters/enhancers of CTGF and MYC (Fig. 5A), two known TAZ gene targets [344, 407] and led to CTGF and MYC upregulation (Fig. 5B). These results show that EGF activates TAZ expression and its transcriptional function in GBM cells.

EGF induces TAZ expression through EGFR.

EGF binds to EGFR and signals through downstream kinases (e.g. ERK1/2, STAT3, and

AKT) to drive various human cancers [440]. To dissect the molecular mechanism underlying

EGF-induced TAZ activation in GBM cells, we first asked if EGF-induced TAZ activation is inhibited by widely used inhibitors of EGFR. GBM1B cells were pre-treated with these inhibitors followed by EGF stimulation and TAZ quantification. Two EGFR inhibitors

(Erlotinib and Gefitinib) significantly reduced TAZ induction by EGF, as examined using

25 whole cell lysates and nuclear and cytosolic fractions of GBM1B neurospheres (Fig. 6A and

6B).

EGF induces TAZ transcription through EGFR downstream kinase pathway cascade.

Next, we asked if EGF-induced TAZ activation is inhibited by widely used inhibitors of

ERK1/2, STAT3 and AKT. Again, GBM1B cells were pre-treated with these inhibitors followed by EGF stimulation and TAZ quantification. Two STAT3 inhibitors (5,15-DPP and

Stattic) potently inhibited STAT3 phosphorylation and EGF-induced TAZ induction (Fig. 7A).

Two ERK1/2 inhibitors (PD98059 and FR180204) also effectively suppressed ERK1/2 phosphorylation and TAZ induction by EGF (Fig. 7B). In contrast, the AKT inhibitor Akti-

1/2 failed to inhibit TAZ induction in EGF-stimulated cells, under conditions of effectively inhibition of AKT phosphorylation (Fig. 7C).

Certain EGFR-activated kinases (e.g. STAT3) have been shown to bind to and activate the promoters/enhancers of downstream gene targets [441]. In the promoter of TAZ, we identified two putative STAT3 binding site (-500 bp and +1138 to the TSS). We performed

ChIP-PCR using STAT3 as bait in GBM1B neurospheres cultured in EGF-containing medium. STAT3 binding to one of putative binding sites (-500bp) was identified (Fig. 7D), supporting that TAZ is transactivated by STAT3.

Overall, these results identified STAT3 and ERK1/2 as essential signaling molecules that mediate EGF-induced TAZ activation.

The constitutively active EGFRvIII mutation leads to EGF-independent TAZ hyperactivation in GBM cells.

EGFRvIII is a common mutation in GBM and leads to ligand-independent constitutive activation of EGFR signaling to drive GBM malignancy [440]. We asked if the EGFRvIII mutant causes ligand-independent TAZ hyperactivation using isogenic GBM cell lines

(GBM1B and U87MG) +/- enforced lentiviral EGFRvIII expression and an EGFRvIII+ GBM

26 neurosphere line M1123 (Fig. 8A). TAZ levels were found to be 100-150% higher in

EGFRvIII+ GBM1B and U87MG cells compared to EGFRvIII- isogenic controls (Fig. 8B).

TAZ gene targets (CTGF and MYC) were also significantly upregulated in EGFRvIII+

GBM1B cells (Fig. 8C). Regarding TAZ induction kinetics after EGF stimulation in

EGFRvIII+ cells, three EGFRvIII+ cell lines (GBM1B-EGFRvIII, U87MG-EGFRvIII and

M1123) showed weak or no obvious TAZ induction after EGF treatment (Fig. 8D), as compared to significant TAZ upregulation in EGF-treated GBM1B and U87MG cells (Fig.

4C). The phosphorylation of ERK1/2 and STAT3 was also not induced by EGF in GBM1B-

EGFRvIII cells (Fig. 8D), as compared to their strong induction in GBM1B cells (Fig. 7A and 7B), consistent with the ligand-independent feature of EGFRvIII. Taken together, these results support that the EGFRvIII mutation leads to EGF-independent TAZ hyperactivation in

GBM cells.

2.4 Conclusion and Discussion

In patient-derived GBM neurosphere cells, we found that EGF induces the up-regulation of

TAZ but not YAP. And EGF also activates known TAZ downstream targets, such as MYC and

CTGF. By using EGFR and EGFR downstream kinase inhibitors, we found that EGF induces

TAZ through EGFR and mainly through STAT3 and partially through ERK1/2. In EGFRvIII- expressing GBM cell models, TAZ showed EGF-independent hyperactivation, comparing to corresponding GBM cells without EGFRvIII. These results show that TAZ is a novel EGF target in GBM. Our results extend previous finding on TAZ/YAP regulation by RTKs in other cancers. In HER2-positive breast cancer, EphA2 receptor tyrosine kinase was reported to activate YAP and TAZ by promoting TAZ/YAP nuclear accumulation [442]. Yang et al. reported a Gas6/GDNF/FGF-TAM/RET/FGFR-MAPK/PI3K regulation of TAZ/YAP in

27 human neuroblastoma, lung adenocarcinoma, cervical adenocarcinoma, ductal breast carcinoma, and colorectal carcinoma cell lines [443].

As a transcriptional coactivator, there have been studies focusing on TAZ’s downstream targets in multiple cancers also including GBM [298, 326, 444-446]. However, the influence of EGFR signaling on TAZ-driven transcriptome has never been studied. This was a significant knowledge gap considering the contextual activity of TAZ. Here, we are interested in how EGFR activation modulates the transcriptional events of TAZ targeted genes. This knowledge will guide the therapeutic development of strategies to target EGF/EGFR-driven oncogenic signaling and likely increase our understanding of the molecular mechanisms underlying resistance to EGFR-targeted strategies. The oncogenic events activated by TAZ in response to EGF stimulation are highlighted in the next Chapter.

Table 1: Summary of antibodies used in Chapter 2.

Catalog Antibody Vendor Dilution Number Cell Signaling rabbit anti-TAZ 4883 1:1000 Technology mouse anti-Actin Sigma A1978 1:10000 Cell Signaling rabbit anti-TBP 40059 1:1000 Technology Cell Signaling rabbit anti-YAP 14074 1:1000 Technology rabbit anti-phospho- Cell Signaling 9157 1:1000 LATS1 Technology Cell Signaling rabbit anti-LATS1 9153 1:1000 Technology rabbit anti-phospho- Cell Signaling 9145 1:1000 Western Blot STAT3 Technology Cell Signaling mouse anti-STAT3 9139 1:1000 Technology rabbit anti-phospho- Cell Signaling 4370 1:1000 ERK1/2 Technology Cell Signaling mouse anti-ERK1/2 4696 1:1000 Technology rabbit anti-phospho- Cell Signaling 4060 1:1000 AKT Technology Cell Signaling mouse anti-AKT 2920 1:1000 Technology Cell Signaling rabbit anti-EGFR 4267 1:1000 Technology Immuno- rabbit anti-TAZ Sigma HPA007415 1:100 fluorescence Cell Signaling rabbit anti-TAZ 4883 1:50 Technology Cell Signaling ChIP rabbit anti-STAT3 12640 1:100 Technology Cell Signaling rabbit IgG 2729 1:500 Technology

Table 2: Summary of primers used in Chapter 2.

Targets Forward Reverse qRT-PCR TAZ GATCCTGCCGGAGTCTTTCTT CACGTCGTAGGACTGCTGG CTGF CCAATGACAACGCCTCCTG TGGTGCAGCCAGAAAGCTC MYC CCTGGTGCTCCATGAGGAGAC CAGACTCTGACCTTTTGCCAGG CAAATCGCTCCACCAACTAAGA 18s ACAGGATTGACAGATTGATAGCTC A TAZ-ChIP-PCR MYC GCTGGAAACCTTGCACCTC CCAATCGCTATGCTGGATTT CTGF TTCTGTGAGCTGGAGTGTGC GCCAATGAGCTGAATGGAGT NC GTCTGTACTCCCAGCTACTC GACAGAGCAAGACTCCATC STAT3-ChIP-PCR WWTR1- TCCTCTTCCTCCTCCTCCTC AAAGGAATGCAGATGCAGGT site 1 WWTR1- GCAGGTGGCTGGAAGTAGAG GTGGAGAGGCAACCAGAGAG site 2

Table 3: Summary of RTK inhibitors and other compounds used in Chapter 2.

Catalog Concentration Inhibitor Vendor Reference Number (μM)

Erlotinib Cell Signaling Technology 5083 10 [447]

Gefitinib Cell Signaling Technology 4765 10 [448]

5,15-DPP Santa Cruz sc-204305 100 [449]

Stattic Santa Cruz sc-202818 5 [450]

PD98059 Cell Signaling Technology 9900 20 [451]

FR180204 Sigma SML0320 50 [452]

Akti-1/2 Tocris 5773 20 [453]

Table 4: Correlation analysis between RTK genes and TAZ in the TCGA and CGGA databases.

TCGA CGGA (Pearson's r) (Pearson's r) EGF 0.313 0.54 FGF1 0.414 0.58 FGF2 0.358 0.62 HGF 0.199 0.53 PDGFA 0.397 0.55 PDGFB 0.101 0.54 EGFR 0.185 0.24 FGFR1 0.338 0.62 FGFR2 -0.028 0.04 FGFR3 0.080 0.06 FGFR4 -0.046 -0.02 MET 0.296 0.42 PDGFRA -0.194 0.06 PDGFRB 0.261 0.55

TCGA: Correlations analyzed based on 454 samples.

CGGA: Correlations analyzed based on 1016 samples.

Fig. 1: TAZ expression analysis in the TCGA-GBM, CGGA, and Rembrandt databases.

A: TAZ mRNA levels in normal brain, low-grade glioma and GBM specimens were analyzed in three glioma databases as marked (*: p < 0.01).

TAZ expression data from the TCGA database are based on histology of GBM specimens (n=489) and normal brains (n=10). TAZ expression data from the CGGA database are based on the grade of grade II glioma specimens (n=232), grade III specimens (n=194), and grade IV specimens (n=225). TAZ expression data from the Rembrandt database are based on the grade of grade I glioma specimens (n=2), grade II glioma specimens (n=98), grade III specimens (n=85), and grade IV specimens (n=130). B: Kaplan-Meier curves of GBM patients with high or low TAZ expression (Cutoff: median

TAZ expression level) from the TCGA (n=488) and CGGA (n=374) database.

Fig. 2: TAZ expression positively correlates with the expression of RTK ligands and receptors.

Correlation analysis of mRNA levels of TAZ (WWTR1) and RTK ligands and RTK receptors in GBM specimens from the TCGA database (n=454).

Fig. 3: EGF induces TAZ in GBM cells.

A: GBM1B cells were depleted of growth factors for 16 hours and treated with RTK ligands

(Con: RTK ligand untreated cells). Total cell lysates were subjected to TAZ western blotting.

B: GBM1B cells were deprived from growth factors for 16 hours and treated with EGF for 2 hours. TAZ mRNA level was quantified by qRT-PCR. C: After growth factor depletion for 16 hours, four GBM cell lines as marked were treated with EGF for the indicated times (Con: untreated cells). TAZ protein levels were quantified by western blotting. D and E: After growth factor depletion for 16 hours, GBM1B and A172 cells were treated with EGF for the indicated times (Con: untreated cells). YAP, phosphorylated and total LATS1 level were quantified by western blotting. Protein fold expression normalized to β-Actin is shown below each lane. The data represent

Mean ± SEM (*: p < 0.01).

Fig. 4: EGF induces the level of TAZ in the nucleus.

A and B: After growth factor depletion for 16 hours, GBM1B cells were treated with EGF for the indicated times (Con: untreated cells). TAZ western blotting was performed using proteins from nuclear and cytosol fractions (A). Protein fold expression normalized to β- Actin or TBP is shown below each lane. Cells with +/- EGF treatment (4 hours) were subjected to TAZ immunostaining with nuclear counterstaining by DAPI (B, Bar = 10 µM).

Fig. 5: EGF activates TAZ gene targets in GBM cells.

A and B: After growth factor depletion for 16 hours, GBM1B cells were treated with EGF for the indicated times (Con: untreated cells). These cells were subjected to ChIP-PCR using

TAZ antibody and control IgG (A, NC: negative control region randomly selected from the genome). CTGF and MYC RNA levels were also quantified in these cells (B).

The data represent Mean ± SEM (*: p < 0.01).

Fig. 6: EGF induces TAZ expression through EGFR.

A and B: GBM1B cells were first depleted of growth factors and treated with +/- Erlotinib or Gefitinib for 16 hours followed by EGF treatment for the indicated times. TAZ western blotting was performed using total protein lysates (A) or proteins from the nuclear and cytosol fractions (B). Protein fold expression normalized to β-Actin or TBP is shown below each lane.

Fig. 7: EGF induces TAZ transcription through EGFR pathway downstream kinases.

A-C: GBM1B cells were first depleted of growth factors and treated with +/- the inhibitors as indicated for 16 hours. Cells receiving 4-hour EGF treatment were subjected to western blotting using total protein lysates.

D: ChIP-PCR using STAT3 antibody and control IgG to determine the interaction between

STAT3 and putative STAT3-binding sites on the TAZ promote (-500 and +1138 bp to the TSS of TAZ).

The data represent Mean ± SEM (*: p < 0.01).

Fig. 8: The EGFRvIII mutation causes EGF-independent TAZ hyperactivation in GBM cells.

A: EGFR western blotting in various GBM cell lines and 293FT cells with +/- lentiviral

EGFRvIII expression.

B and C: GBM1B and U87MG cells with +/- EGFRvIII expression were subjected to TAZ western blotting (B) and qRT-PCR for CTGF and MYC (C).

D: After growth factor depletion for 16 hours, GBM cells as marked were treated with EGF for the indicated times (Con: untreated cells) and subjected to western blotting of TAZ and key EGFR-activated kinases.

Protein fold expression normalized to β-Actin, total ERK1/2 or STAT3 is shown below each lane. The data represent Mean ± SEM (*: p<0.01).

Chapter 3: TAZ acts as a key mediator of EGF signaling to activate oncogenic cascades in GBM

3.1 Introduction

As shown in the previous chapter, we found that EGF induces TAZ and activates multiple

TAZ targets through EGFR and downstream kinase signaling.

During development, TAZ is an important regulator in controlling organ size and also has been shown to activate multiple oncogenic events in cancer [334]. Sustained TAZ activity promotes aberrant proliferation by interrupting cell cycle, inducing DNA duplication/repair and enhancing metabolism (glycolysis, glutamine metabolism and nucleotide biosynthesis)

[335, 339-341, 343, 344, 454]. TAZ is also essential for CSCs in terms of tumor initiation and therapy resistance [351-355]. TAZ has been shown to favor tumor survival by stimulating

EMT [293, 371-373]. In GBM, TAZ has been shown to drive EMT and induce radioresistance [407, 409].

Chromatin immunoprecipitation (ChIP)-sequencing is a method used to analyze protein-DNA interactions. It is a powerful tool in studying global genome binding sites for any transcription regulator of interest; especially in studying a chromatin-associated protein’s influence on phenotype-affecting events. RNA-sequencing uses next-generation sequencing

(NGS) to quantify RNA in biological samples, which is important in analyzing cellular transcriptome.

To investigate EGF-induced TAZ target genes in GBM, we performed RNA-sequencing and

ChIP-sequencing in EGF treated GBM1B cells. TAZ bound to the promoters and transactivated 641 genes in response to EGF treatment. Through KEGG pathway analysis, these genes are shown to function in multiple oncogenic signaling pathways. We validated a

43 selection of TAZ-regulated genes, by performing ChIP-PCR, qRT-PCR, western blot and loss-of-function analysis.

3.2 Materials and Methods

Strategy for combination of RNA-sequencing and ChIP-sequencing

GBM1B cells were deprived of growth factors for 16 hours and treated with EGF for four hours or 24 hours. mRNA samples from both time points were sent for RNA-sequencing, using mRNA from EGF-untreated GBM1B cells as control. EGF 4 hours treated cells were fixed for TAZ-ChIP and used for later ChIP-sequencing (Fig. 9).

Cell culture, protein extraction and western, RNA extraction and qRT-PCR and statistic analysis

Same as described in part 3.2. Antibodies used are listed in Table 5. Primers used for qRT-

PCR are listed in Table S1. Primers used for ChIP-PCR are listed in Table S2.

ELASA

The A172 or GBM1B cell culture supernatants were collected and centrifuged to remove debris. The PDGF-BB was detected using commercially available kits (R&D Systems,

Minneapolis, USA) according to the manufacturer’s instructions. In brief, 100 μL Assay

Diluent RD1X was added to each well. Then, 100 μL of standard or sample were added to each well followed by washing with 400 μL Wash Buffer. 200 μL of Human PDGF-BB

Conjugate were added to each well, and incubated for 1.5 hours at room temperature. The wash step was repeated. 200 μL of Substrate Solution was added to each well, and incubated for 30 minutes at room temperature. 50 μL of Stop Solution were added to each well. The results were analyzed by determining the optical density using the microplate reader set to

450 nm.

TAZ knockdown

TAZ shRNA lentiviral vectors (TRCN0000019469, TRCN0000019470, Thermo Scientific, ordered from core facility, JHMI), and control shRNA (SHC004, Sigma) were packaged using Lipo 3000 and second-generation lentivirus packaging protocol using PAX2 and

PMDIG vectors. Cells were infected by lentivirus (MOI = 5) for 24h with TransDux Virus

Infection solution. Infected GBM cell was established by puromycin selection (1μg/ml) for

48 hours.

RNA-sequencing and analysis

Total RNA was extracted using the RNeasy kit (Qiagen). 4 μg of total RNA was subjected to library preparation using Illumina TrueSeq RNA Sample Preparation kit v2 (Illumina).

Indexed adapters were used to pool four cDNA libraries into one sequencing reaction.

Libraries were assessed using an Agilent Bioanalyzer (Agilent Technologies) to confirm that cDNA fragment sizes were between 200 and 500 bp in length. Sequencing was performed using an Illumina HiSeq 2500 platform (Illumina).

The raw reads were aligned to reference human genome build hg19 using HISAT2 ([428]) with default parameters. For each gene, the number of reads aligned to its exons were counted and summarized into gene-level counts by StringTie [455] based on the GENCODE hg19 annotation. Normalization between samples was carried out by R package edgeR [456,

457], which controls sequencing depth and RNA composition effects. The heat map was generated according to the count table with scaling across the samples for each gene. The log2 -fold change, log2 ((IP RMKM 1)/ (Control RPKM 1)), for each gene in each cell line was calculated. The log2 -fold change for GBM1B-EGF-treated-four hours and GBM1B-

EGF-treated-24 hours are plotted against that of GBM1B-EGF-untreated.

Chromatin immunoprecipitation (ChIP) and ChIP-sequencing

Cells were subjected to ChIP using the MAGnify ChIP system (Invitrogen) following the manufacturer’s protocol. TAZ-associated DNA was immunoprecipitated using a rabbit anti-

TAZ antibody (Cell Signaling) and Dynabeads magnetic beads (Invitrogen). Normal rabbit

IgG was used as the control. ChIP-enriched DNA was used for quantitative PCR and deep sequencing. ChIP-enriched DNA or input DNA (10 ng each) was subjected to library preparation using a ChIP-Seq DNA Sample Prep kit (Illumina) following the manufacturer’s protocol. Sequencing was performed using an Illumina HiSeq 2500 platform.

The 50-bp-long raw TAZ ChIP-Seq reads were aligned to the reference human genome build hg19 using Bowtie2 [458] allowing at most two mismatches in the first 28-bp “seed” bases.

TAZ binding sites were called using MACS [459] with default settings by comparing the two

IP samples against the two control samples. The number of reads aligned to the peak regions by each of the four ChIP samples was counted by BEDTools [455] and then normalized in R for the library size for each sample. For each peak region, its normalized counts in a given sample were further subtracted by its mean normalized counts across samples and then divided by its standard deviation, which gave the scaled binding intensity. The 150-bp-long sequences centered at the peak summits for the top-ranked peaks were extracted and fed as the input for the de novo motif discovery algorithm of CisGenome. Ten motifs of varying lengths with a mean motif length of 12 were searched simultaneously. To obtain the truly

TAZ enriched motifs, the occurrence rate of a motif in the 150-bp-long sequences centered at the peak summits for all peaks was compared with its occurrence rate in control genomic regions. The control regions were randomly chosen to match the GC content and distributional properties of ChIP-sequencing peak regions [460].

The differential gene expression detection was carried out by the R Bioconductor package edgeR ([456]; [461, 462]) with tag wise dispersion at a false discovery rate (FDR) of 5%. A matched study design was used because the four samples came from two cell lines. The list of differentially expressed transcripts was further filtered if the absolute values of log2 -fold changes for differentially expressed transcripts comparing the case versus control exceeded

0.8. TAZ target genes were defined as differentially expressed transcripts with 1 TAZ binding peaks in the 20 to 10 kb window surrounding the transcription start sites (TSSs).

Pathway analyses

Canonical pathway analysis was performed using the KEGG Pathway Analysis (EnrichR,

[463]). The significance of the association between TAZ targets and a canonical pathway was measured using the ratio between the number of KEGG targets in the pathway and the total number of molecules in the pathway database. Fisher’s exact test was performed to determine the association between TAZ targets and canonical pathways. All analysis was done based on

R (R script provided in extra supplement data).

3.3 Results

Genome-wide analysis of EGFR-TAZ-regulated gene targets.

To establish a genome-wide map of the genes regulated by the EGFR-TAZ signaling axis, we applied a high-throughput sequencing strategy (Fig. 9) combining RNA-Seq and ChIP-Seq to identify TAZ gene targets that are modulated by the EGFR-TAZ signaling axis. GBM neurosphere cells GBM1B were depleted of growth factors for 16 hours followed by EGF stimulation for 4 and 24 hours. RNA-seq was used to identify differentially-expressed (DE) genes after EGF treatment. Over 14,000 cDNA reads were generated for each of three conditions (Control, EGF-4h and EGF-24h, n=2 for each condition) and showed a >87% alignment rate to the human genome. Consistency between two RNA-Seq replicates was shown by heat map clustering (Fig. 10A). Of all 14,791 RefSeq genes (at least two samples have CPM (counts per million) >1), there are 6,765 differentially expressed genes (FDR ≤

0.05, Table S3, loaded as separated file) when comparing cells with 4-hour EGF treatment to the untreated control, and there are 7,133 differentially expressed genes (FDR ≤ 0.05, Table

S4, loaded as separated file) when comparing cells with 24-hour EGF treatment to the

47 untreated control. Together, 1,777 (12.0%) and 1,524 (10.3%) genes were up- and down- regulated by EGF, respectively (Fig. 10B; FDR ≤ 0.05, log2 (-fold change)) ≥ 0.8 or ≤

−0.8; Table S5 and S6).

TAZ ChIP-Seq (see details in Materials and Methods) was performed to define genome-wide

TAZ binding sites in GBM1B neurosphere cells after EGF treatment for 4 hours, time of peak

EGF-induced TAZ expression as shown in Fig. 3C. >90% of the ChIP-seq reads aligned to the human genome. Using Cis Genome [434], 40,225 TAZ binding peaks were called at an

FDR of 5% and mapped to 10,570 genes (Table S7, loaded as separated file). The ChIP intensities within TAZ binding peaks were consistent between both replicates as shown by the correlation assay (Fig. 11A). TAZ binding sites, but not randomly selected genomic regions, were highly enriched around the ±1kb region of TSS (Fig. 11B). We further calculated the overlapping ratio between TAZ binding peaks and peaks of histone modification marks for promoters, enhancers and suppressors sourced from the Encode database ([464], Fig. 11C). 14.4% of all TAZ binding peaks overlapped with the H3K4me3 activation mark enriched in promoters, higher than that with the H3K27ac enhancer mark

(9.7%) or the H3K27me3 suppressor mark (8.2%). The top 2000 TAZ binding peaks also overlapped more with H3K4me3 (30.8%) than either H3K27ac (14.4%) or H3K27me3

(10.7%). These results indicate that TAZ functions predominantly to activate gene transcription in EGF-stimulated cells. De novo motif discovery analysis [465] identified the consensus sequence 5’- ATGGAATGGAAT -3’ as the most enriched TAZ-binding motif (Fig.

11D). Searching the HOMER transcription factor binding site profile database [465], we found that the TAZ binding motif closely resembled the motifs of TEAD1 and TEAD3, two known TAZ-binding transcription activators (Fig. 11E and Table S8). Overall, these results support that TAZ mediates the EGF signaling by directly activating a transcription program with to-be-defined oncogenic functions.

TAZ mediates the induction of multiple oncogenes by EGF.

By merging RNA-Seq and TAZ ChIP-Seq data sets, we identified EGF-regulated TAZ gene targets that were differentially expressed after EGF treatment with at least one TAZ binding site within −20 to +10 kb of their TSSs. These TAZ gene targets were divided into those either activated or repressed by EGF stimulation (listed in TAZ-Up and TAZ-Down gene list, respectively; Table S9 and S10). These gene lists were subjected to gene function annotation and KEGG pathway enrichment analysis (Table S11, loaded as separated file) [466, 467].

Top-ranked signaling pathways enriched in TAZ-Up genes contained multiple oncogenic signaling pathways, e.g. focal adhesion, MAPK, HIF-1, RAS and PI3K-AKT signaling pathways (Fig. 12, Table 6).

TAZ-Up genes were ranked based on their enrichment in the top 20 KEGG pathways enriched in TAZ-Up genes, using Clustergram analysis (Fig. 13 and S1). 8 of the top 10 genes code for RTK ligands and receptors (EGFR, EGF, PDGFB, PDGFRA, PDGFA, VEGFA,

FGF2 and FGF1), suggesting an EGFR-TAZ-RTK positive feedback loop. This list of TAZ-

Up genes also contains other genes with oncogenic functions (e.g. HIF1A, JUN, JAK2,

CXCR4 and CD274) and known TAZ-binding partners (e.g. TEAD1) essential for its transcriptional activity.[344, 407, 468-475].

We focused on validating 16 genes either directly related to RTK signaling (EGFR, EGF,

PDGFB, PDGFRA, PDGFA, VEGFA, FGF1, FGF2, FGFR4 and ERBB3) or performed other oncogenic functions (JUN, HIF1A, JAK2, CXCR4, CD274 and TEAD1). EGF induction of these 16 genes in GBM neurosphere line GBM1B was validated by qRT-PCR (Fig. 14A, and

Table 7). EGF induction of proteins coded by nine TAZ-Up genes (EGFR, PDGFRA,

PDGFB, HIF1A, JAK2, CXCR4, JUN, TEAD1 and CD274) was validated by western blotting or ELISA in two GBM cell models, GBM1B and A172 (Fig. 14B, 14C, and 14D).

TAZ binding to the promoters/enhancers of 12 TAZ-Up genes was validated by TAZ ChIP followed by qRT-PCR (ChIP-PCR) (Fig. 14E).

To determine if the expression of these TAZ-Up genes is TAZ-dependent, we silenced TAZ expression in GBM1B neurospheres and A172 cells cultured in EGF-containing medium. The protein levels of the seven validated TAZ-Up genes were down-regulated after TAZ silencing, as measured by western blotting or ELISA (Fig. 14F and 14G). 15 out of 16 evaluated TAZ-

Up genes was significantly down-regulated at mRNA levels after TAZ silencing by at least one shRNA in GBM1B cells (Fig. 14H and Table 7) and 12 out of 16 evaluated TAZ-Up genes showed significant down-regulation after TAZ silencing by at least one shRNA in

A172 cells (Fig. 14I and Table 7).

To further determine if our discoveries are applicable to clinical GBM specimens, we found that the expression levels of 12 of 16 validated TAZ-Up genes were positively correlated with

TAZ expression in the TCGA GBM database and expression levels of 14 of 16 validated

TAZ-Up genes were positively correlated with TAZ expression in the CGGA database (Table

7 and Fig. S2).

Taken together, these validated genome-wide analyses reveal the direct activation of multiple

GBM-promoting genes by the EGFR-TAZ signaling axis.

3.4 Conclusion and Discussion

We performed ChIP-sequencing and RNA-sequencing on EGF treated/untreated GBM1B cells. Combining ChIP-sequencing and RNA-sequencing, we generated a gene list of 641

EGF-induced and TAZ-dependent genes. We then performed KEGG analysis for these 641 genes. We focused on the validation of RTK ligands and receptors and also some other important oncogenic genes.

The TAZ-Up genes we identified contain multiple key ligands and receptors belonging to the

RTK signaling network, thus indicating that TAZ may form autocrine and paracrine loops involving RTK signaling to sustain the growth of its own and surrounding cells. This feedback loop is important for RTK heterogeneity within the GBM population especially for tumors with the EGFRvIII mutation that lead to ligand-independent TAZ hyperactivation.

Our results also showed that enforced TAZ expression by EGF promoted genes such as JAK2,

CXCR4, JUN, HIF1A, TEAD1 and CD274 (PD-L1), suggesting that TAZ drives in various essential molecular pathways promoting GBM proliferation, stemness, invasion, and immune escape.

Within the top-ranked KEGG pathways, oncogenic signaling pathways of various cancer types were identified, such as small cell lung cancer, renal cell carcinoma, melanoma, and colorectal cancer. Since EGFR signaling is widely involved in human cancers, our finding suggests that EGF-induced TAZ may also have conserved and important functions across multiple human cancers. In addition to the genes involved in the RTK signaling pathway,

TAZ-Up genes also include genes involved in other oncogenic pathways, cancer metabolism, and metastasis-related pathways. All of these pathways and genes warrant further research, and we report some of them in Chapter 6.

Taken together, we found that TAZ functions as a mediator of EGF signaling by coordinating oncogenic events in GBM and may serve as a potential target in treating GBM patients. In the next chapter, we report on the oncogenic effects of TAZ overexpression and explore potential therapeutic strategies in preclinical GBM models.

Table 5: Summary of antibodies used in Chapter 3 Antibody Vendor Catalog Number Dilution Cell Signaling rabbit anti-PDGFRA 3174 1:1000 Technology Cell Signaling rabbit anti-JUN 9165 1:1000 Technology rabbit anti-CXCR4 Thermo Fisher 35-8800 2 µg/mL Cell Signaling rabbit anti-HIF1A 36169 1:1000 Technology Cell Signaling rabbit anti-JAK2 3230 1:1000 Technology Cell Signaling rabbit anti-CD274 13684 1:1000 Technology Cell Signaling rabbit anti-TEAD1 12292 1:1000 Technology

Table 6: Top 20 KEGG terms enriched in TAZ-Up genes

Term Genes Focal adhesion SHC3 LAMA2 ROCK2 PDGFB PDGFA XIAP THBS1 EGFR MYLK ACTG1 MYLK4 CDC42 FLNA TNR ITGB8 VAV3 PDGFRA JUN EGF ITGA2 PARVB VEGFA COL4A4 COL4A3 ZYX BCL2 ITGA6 TLN2 BIRC3 Regulation of actin VAV3 PDGFRA GSN ROCK2 EGF ITGA2 PDGFB PDGFA cytoskeleton CXCR4 IQGAP1 IQGAP2 FGF1 FGF2 EGFR MYLK ACTG1 MYLK4 CDC42 DIAPH2 ARHGEF4 ITGB8 MYH9 ITGA6 FGFR4 Rap1 signaling FARP2 PDGFRA RALB EGF PDGFB PDGFA ADCY1 pathway SIPA1L2 FGF1 GRIN2B FGF2 THBS1 EGFR VEGFA ACTG1 CDC42 KITLG SIPA1L1 TLN2 PLCB1 FGFR4 EPHA2 RAPGEF4 HIF-1 signaling CDKN1A CAMK2D EGLN3 PFKFB3 TFRC EGF HIF1A pathway HK2 EGFR VEGFA BCL2 TLR4 PDK1 MAPK signaling PDGFB PDGFA IL1RAP FGF1 FGF2 EGFR CDC42 pathway RPS6KA3 ERBB3 FLNA DUSP4 DUSP5 PDGFRA JUN DUSP3 MAP3K1 BDNF EGF NFATC1 DUSP9 DUSP6 VEGFA KITLG CACNB4 TRAF6 FAS FGFR4 EPHA2 Pathways in cancer CDKN1A CAMK2D RALB LAMA2 ROCK2 TCF7 PDGFB PDGFA XIAP CXCR4 ADCY1 FGF1 PLD1 HIF1A FGF2 ETS1 EGFR CDC42 CASP7 TERT PMAIP1 JAK2 PDGFRA JUN EGLN3 CDKN2B FZD5 EGF ITGA2 PLEKHG5 RUNX1 VEGFA KITLG TRAF6 COL4A4 COL4A3 BCL2 FAS ITGA6 PLCB1 FGFR4 BIRC3 Phospholipase D DGKG PDGFRA SHC3 RALB EGF SPHK1 PDGFB signaling pathway PDGFA ADCY1 PLD1 EGFR KITLG PTK2B PLCB1 DGKH RAPGEF4 Ras signaling pathway PDGFRA SHC3 RALB BDNF EGF PDGFB PLA2G3 PDGFA FGF1 PLD1 GRIN2B FGF2 ETS1 EGFR ETS2 VEGFA CDC42 KITLG REL ABL2 FGFR4 EPHA2 Small cell lung cancer CDKN1A CDKN2B LAMA2 ITGA2 COL4A4 TRAF6 COL4A3 BCL2 XIAP ITGA6 BIRC3 Arrhythmogenic right CACNB4 LAMA2 ACTN2 ITGA2 TCF7 LMNA ITGB8 ventricular ITGA6 ACTG1 cardiomyopathy (ARVC) Glutamatergic synapse GRIA2 HOMER1 HOMER2 SLC1A1 GRIK4 ADCY1 PLD1 PLCB1 GRIN2B GRIA3 SHANK2 GLS Central carbon PDGFRA SLC7A5 G6PD HIF1A HK2 EGFR GLS PDK1 metabolism in cancer

Proteoglycans in cancer CDKN1A CAMK2D FZD5 ROCK2 ITGA2 ANK2 IQGAP1 HIF1A FGF2 THBS1 EGFR VEGFA ACTG1 CDC42 ERBB3 FLNA FAS TLR4 PI3K-Akt signaling CDKN1A LAMA2 PDGFB PDGFA FGF1 FGF2 THBS1 pathway EGFR ERBB3 TNR ITGB8 JAK2 PDGFRA BDNF EGF ITGA2 PPP2R3A OSMR VEGFA KITLG COL4A4 COL4A3 BCL2 ITGA6 FGFR4 TLR4 EPHA2 Renal cell carcinoma CDC42 CDKN1A JUN EGLN3 PDGFB ETS1 HIF1A VEGFA Oxytocin signaling JUN CDKN1A CAMK2D ROCK2 NFATC1 ADCY1 RYR3 pathway EGFR ACTG1 MYLK MYLK4 CACNB4 PLCB1 KCNJ2 Melanoma PDGFRA CDKN1A EGF PDGFB PDGFA FGF1 FGF2 EGFR Choline metabolism in DGKG PDGFRA JUN EGF PDGFB PDGFA PLD1 HIF1A cancer EGFR DGKH AGE-RAGE signaling CDC42 JUN COL4A4 COL4A3 BCL2 NFATC1 JAK2 PLCB1 pathway in diabetic F3 VEGFA complications Glioma PDGFRA CDKN1A CAMK2D SHC3 EGF PDGFB PDGFA EGFR

Genes in Bold belong to the family of RTK ligands and receptors.

Table 7: Summary of correlation analysis in the TCGA and CGGA database and mRNA validation results of TAZ-Up genes in GBM1B and A172 cells Correlation with Normalized mRNA expression (control = 1.0) TAZ GBM1B A172 Genes TCGA CGGA Enforced ( Pears ( Pears shTAZ shTAZ shTAZ shTAZ EGF 4h TAZ on’s r) on’s r) 1 2 1 2 expression

EGFR 0.19 0.32 2.69 2.64 0.19 0.34 0.59 0.75 PDGFB 0.10 0.59 32.13 96.00 1.02 0.72 0.74 0.90 EGF 0.31 0.53 2.35 18.93 0.74 0.99 0.79 1.07 PDGFRA -0.19 0.08 4.46 27.68 0.21 0.59 1.91 1.70 PDGFA 0.40 0.63 3.87 7.15 0.75 1.06 0.42 0.69 VEGFA 0.38 0.56 4.96 6.30 0.82 0.68 0.52 0.74 FGF2 0.36 0.56 2.75 12.16 0.58 0.27 0.67 0.93 FGF1 0.41 0.59 5.70 2.89 0.18 0.38 0.15 0.17 FGFR4 -0.05 0.01 4.11 5.06 0.66 0.09 0.77 1.04 ERBB3 -0.32 -0.05 3.27 8.34 0.11 0.31 0.69 1.03 JUN 0.53 0.60 4.81 6.88 0.33 0.35 0.23 0.29 HIF1A 0.43 0.67 5.42 28.47 0.63 0.70 0.62 0.78 JAK2 0.21 0.62 2.19 2.83 0.52 0.73 0.53 0.66 CXCR4 0.46 0.71 10.14 3.40 0.63 0.69 1.65 1.47 CD274 0.50 0.67 34.55 18.43 0.17 0.79 0.14 0.21 TEAD1 0.32 0.53 2.64 11.68 0.20 0.46 2.31 1.79

Blue labels value with p < 0.05

Fig. 9: Outline of the genome-wide analysis.

Outline of the genome-wide analysis and summary of the gene numbers identified.

Fig. 10: RNA-sequencing reveals transcriptome changes between GBM1B cells with or without EGF treatment.

A: Heat map of expression pattern for differentially expressed genes from RNA-Seq data.

Gene expression was calculated by RPKM.

B: Volcano plot of all genes analyzed for differential expression (red and blue dots: genes with FDR≤0.05 and log2 (fold change) ≥ 0.8 or ≤ -0.8, respectively).

Fig. 11: ChIP-Seq on GBM1B cells after 4-hour EGF treatment identifies TAZ genome-wide binding sites.

A: ChIP-Seq reproducibility as determined by the scatter plot comparing peak intensities for two ChIP-Seq replicates (Pearson's correlation coefficient (R) = 0.91, p < 0.001).

B: Distribution around TSSs of TAZ binding peaks and randomly selected genomic regions.

C: Overlapping between TAZ peaks and histone marks as indicated.

D: TAZ binding motif was identified using TAZ-binding peaks.

E: TEAD1 and TEAD3 motifs are the top-ranked motifs similar to the discovered TAZ motif.

Fig. 12: KEGG and IPA analysis of TAZ-Up genes.

A: Pathways enriched in TAZ-Up genes determined by the KEGG Pathway Analysis (p<0.05). Ranking based on combined score. B: The top 20 KEGG terms C: Top 22 IPA terms (pathways are ranked based on -log (p) as calculated by the Fisher’s exact test).

Fig. 13: KEGG Clustergram analysis ranks TAZ-Up gene in the top 20 KEGG terms.

TAZ-Up genes involved in the top 20 KEGG pathway terms were ranked based on their enrichment in these pathways. The top-ranked 60 genes are shown.

Fig. 14: TAZ mediates the activation of multiple oncogenic genes induced by EGF.

A: GBM1B cells were deprived from growth factors for 16 hours and treated with +/- EGF for 4 hours. The expression of TAZ-Up genes was quantified by qRT-PCR. (Control: cells with depletion of growth factor).

B and C: GBM1B cells were deprived from growth factors for 16 hours and treated with +/-

EGF for 24 hours. TAZ-Up genes were analyzed by western blotting (B) or ELISA for

PDGFβ (C). CD274 western blotting was performed in cells cultured with IFN-gamma

(1pg/mL) to stimulate CD274 expression (B).

D: A172 cells were deprived from growth factors for 16 hours and treated with +/- EGF for 24 hours. TAZ-Up genes were analyzed by western blotting. E: GBM1B cells after growth factor depletion were treated with EGF for 4 hours, and were subjected to ChIP using TAZ antibody and control IgG. qPCR was used to validate the enrichment of TAZ binding peaks as defined by TAZ ChIP-Seq (NC: negative control primers for no TAZ-binding genomic regions).

F, G, and H: GBM1B cells after being infected by lentiviral shTAZ or control shRNA for 48 hours were treated by EGF for 24 hours. The expression of various TAZ-Up genes was measured by western blotting (F), ELISA (G) or qRT-PCR (E, dash line: gene expression level in cells with control shRNA). I: A172 cells after being infected by lentiviral shTAZ or control shRNA for 48 hours were treated by EGF for 24 hours. The expression of various TAZ-Up genes was measured by qRT-PCR. Protein fold expression normalized to β-Actin is shown below each lane. The data represent Mean ± SEM (*: p<0.01).

Chapter 4: TAZ hyperactivation promotes GBM growth, invasion, and tumorigenicity.

4.1 Introduction

We show above that EGF induces TAZ transcription through EGFR and downstream kinase pathways in GBM cells and TAZ functions as an essential signaling hub for EGF stimulated oncogenic pathways, involving: cell proliferation, aggressiveness, and immune escape. These are consistent with our knowledge of TAZ’s functions in tumor progression. The EGFR-TAZ axis in GBM cells leads to the hyperactivation of TAZ and its downstream transcriptional program including RTK signaling components and other oncogenic genes. To further define the oncogenic functions of TAZ hyperactivation by EGF in GBM cell context, we used enforced TAZ expression and examined effects on GBM growth, invasion and other malignant phenotypes in vitro and in vivo.

4.2 Materials and Methods pLEX-TAZ Plasmid construction

The human TAZ coding region was cloned with a BamHI cutting site at 5’ region and an

XhoI cutting site at 3’ region by PCR (primer listed in Table 8) and then inserted into TOPO vector (Invitrogen, Cat#450641) for amplification. This PCR-engineered DNA was inserted into pLEX MCS by BamH1 (NEB, Cat# R3136)/ XhoI double digestion. This ligation product was then transformed into Stbl3 competent cell and selected on ampicillin (50µg/mL) plate.

Cell culture, protein extraction and western, RNA extraction and qRT-PCR, virus packaging and cell line generation, and statistical analysis have been descripted in in part 2.2. Primers used for qRT-PCR are listed in Table S1. Additional antibodies used are listed in Table 9.

Cell counting

GBM1B, GBM1B-TAZ, A172 and A172-TAZ cells cultured at regular culture medium, starting from 5,000 cells at day 0 in 6-well plates. Cell number is counted at day 2, 4, and6 with Trypan blue (Corning, Cat# 25-900-CI) to stain viable cells.

Radiation resistance

Viable cells (1 × 105/condition) were treated with one dose of 3Gy radiation and then cultured in 6 well plates. After 6 days, cell numbers were counted.

Transwell assay

For transwell assay (Corning, Cat #3422), transwell was per-coated with laminin (Sigma,

Cat# L2020) for 2 hours. GBM cells were suspended at 1 × 106 cells/ml. 100 µl of cell suspension were added to the upper chamber of transwells in serum-free medium. 600 µl of medium containing 10% FCS was added to the lower chamber. After 3-hour incubation at

37°C, cells were fixed with Diff-Quick kit (Thermo Fisher Scientific). Cells on the upper side of the transwells were gently wiped off with Q-tips. Cells migrating through the filter were stained with 4'−6-Diamidino-2-phenylindole (DAPI). Migration was quantified by counting cells on six randomly selected fields per transwell in at least three independent experiments.

Scratch assay

GBM cells were grown under 10% FCS medium in 35 mm dishes until confluent. Cell proliferation was inhibited by mitomycin C (1 µg/ml) for half hour. Several scratches were created using a 10 μl pipette tip through the confluent cells. Dishes were washed with PBS for three times and cells were grown in 0.1% FCS medium for 24–48 hr. Phase contrast

64 pictures were taken at different time points to quantify cell numbers in the scratch region as described by us [476].

Tumor xenografts

4% paraformaldehyde for histopathological analysis. Tumor sizes were quantified by measuring maximum tumor volume on hematoxylin and eosin–stained brain coronal sections using computer-assisted morphometry (MCID software).

IHC and IF

The tissue frozen sections were washed five minutes with PBS. Then, sections were stained with hematoxylin (Harris) for three minutes. Next, sections were counterstained in eosin solution for one minute and then dehydrated with 95% alcohol for five minutes. Sections were dehydrated with absolute alcohol twice for five minutes each time. Last, sections were cleared with xylene for five minutes and mounted with DPX Mounting Media (Sigma-

Aldrich).

4.3 Results

Generation and validation of GBM cell lines with enforced TAZ expression.

The EGFR-TAZ axis in GBM cells leads to the hyperactivation of TAZ and its downstream transcriptional program including key RTK signaling components and other GBM-promoting genes. Here, we used enforced TAZ expression to mimic TAZ hyperactivation in EGF- stimulated and EGFRvIII+ cells and evaluated the oncogenic effects. GBM1B-TAZ, A172-

TAZ, and GL261-TAZ (GL261 is a murine glioma cell line) cells were derived from their

65 parental lines with lentiviral enforced TAZ expression (Fig. 15B, the lentiviral vector is shown in Fig. 15A).

All 16 TAZ-Up genes validated at the RNA level (see chapter 3) showed strong induction by enforced TAZ expression in GBM1B, as compared to cells transduced with control lentiviruses without the TAZ transgene (Fig. 15C). We tested eight TAZ-Up genes (EGFR,

PDGFRA, HIF1A, JAK2, CXCR4, JUN, TEAD1 and CD274) and detected protein induction in GBM1B-TAZ and A172-TAZ cells relative to controls (Fig. 15D and 15E).

Enforced TAZ expression promotes GBM cell malignancy in vitro and in vivo.

We studied cell proliferation, invasion, and radiation resistance of the GBM1B and A172 with TAZ hyperactivation. GBM1B-TAZ and A172-TAZ cells both showed enhanced proliferation in vitro, compared to control cells (Fig. 16A). GBM1B-TAZ cells also showed >100% more cell survival after one or three daily doses of 3 Gy radiation compared to isogenic control cells (Fig. 16B). Transgenic TAZ also increased cell migration and invasiveness, as determined by the transwell and scratch wound healing assay (Fig. 16C and

16D).

TAZ induction leads to more aggressive growth of GBM xenografts.

In a GBM neurosphere model, mice bearing GBM1B-TAZ xenografts showed more aggressive and invasive tumors (Fig. 17A and 18B, n=5). GBM1B-TAZ xenografts showed >2-fold increase in tumor size compared to control GBM1B xenografts (19.5 ± 3.5 vs

75.3 ± 5.1 mm3, n=5). We also detected more tumor cells invassion to the contralateral hemisphere in brains of mice bearing GBM1B-TAZ cells, compared to the control xenografts

(Fig. 17B).

Transgenic TAZ induces tumorigenesis of non-tumorigenic A172 cells.

We confirmed previous reports showing that the A172 cell line is non-tumorigenic when transplanted into the brains of immunodeficient mice [477]. Here, we found that A172-TAZ

66 cells formed tumors in mouse brains evidenced by histopathologic evaluation 76 days after transplantation (Fig. 18, n=5). Animals implanted with control A172 cells had no detectable tumors 76 days (Fig. 18) and 150 days after transplantation (data not shown). A172-TAZ tumor xenografts also showed necrosis in the tumor core, a histopathological hallmark of

GBM (Fig. 18).

TAZ induction reduces immune cell infiltration in orthotropic GL261 tumors.

To investigate the effect of TAZ hyperactivation on the host immune cell response in GBM tumors, we generated orthotropic tumors from GL261 cells with or without TAZ hyperactivation in the brains of syngeneic immunocompetent mice. H&E staining showed no obvious difference in the size of GL261 and GL261-TAZ tumors (Fig. 19A). However, CD8 staining showed significantly fewer cytotoxic T lymphocytes (CTLs) in GL261-TAZ tumors compared to GL261 tumors (the number of CD8+ CTLs: 68.5 ± 6.0 vs 24.5 ± 3.6 per mm2, n=12, Fig. 19B), suggesting that TAZ hyperactivation contributes to the immunosuppression tumor microenvironment by inhibiting CTL infiltration.

4.4 Conclusion and Discussion

Our results show that TAZ hyperactivation promotes GBM cell proliferation, radioresistance, and migration in vitro. Enforced TAZ expression led to more aggressive xenograft formation from GBM1B and induced xenograft tumor formation from non-tumorigenic A172 cells, consistent with our in vitro findings. TAZ induction reduced infiltration of cytotoxic T lymphocytes in xenograft tumors from GL261 cells, which is likely result from TAZ induction on PD-L1. These results supported that TAZ is important for tumor formation, aggressiveness, and potential immune escape; and thus TAZ can serve as a potential drug target in treating GBM patients.

To further classify xenograft tumors from A172-TAZ, Olig2 [478] or GFAP stain [479] will be applied to identify the glia content. Other histopathology features of GBM such as microvascular proliferation and molecular markers (such as EGFR, TERT, LDH, ARTX, p53, and H3K27me) [37] will also be carefully examined in follow-up experiments.

GL261-TAZ xenografts serve as a suitable model to study the effects of enforced TAZ expression on tumor immune escape. In the preliminary data we presented here, TAZ hyperactivation w reduced CD8+ T cells infiltration. In future experiment, we will first measure PD-L1 expression on GL261 +/- TAZ cell surface by flowcytometry and we will co- culture GL261 +/- TAZ will Jurkat T cells and measure Jurkat T cells survival and activation in co-culture model. Besides, we will also do CD3 staining for lymphocytes [480], and CD68 staining for macrophages [481] in GL261 +/- TAZ xenografts to further characterize immune cell filtration.

Here, we showed that enforced TAZ is sufficient to facilitate tumor formation, aggressiveness, and immune escape in vitro and in vivo. We will further study whether TAZ hyperactivation is essential for these properties. To ask these questions, we need a controllable TAZ overexpression model, in which TAZ induction and withdraw is subjected to experimental regulation. An inducible TAZ overexpression model will be established via pTRIPZ-TAZ lentivirus. pTRIPZ vector is doxycycline inducible and provides us with a tool to manipulate transgenic TAZ expression [482-484] in vitro and in vivo to study the dynamic changes of

GBM cells and xenografts in response to TAZ induction.

In next chapter, we will explore potential TAZ targeting strategies in GBM model based on our EGFR-TAZ model.

Table 8: Primers for pLEX-TAZ cloning. Forward 5'-ACCGGTGCCACCATGGACTACAAAGACCATGACG-3' Reverse 5'-ACGCGTTTACAGCCAGGTTAGAAAGGGC-3'

Table 9: Summary of antibodies used in Chapter 4

Antibody Vendor Catalog Number Dilution

Western anti-FLAG HRP Sigma A8592 1:1000 Blot

rabbit anti-TAZ Sigma HPA007415 1:100 Cell Signaling rabbit anti-EGFR 4267 1:50 Technology rabbit anti-GFAP Dako Z0334 1:200 rabbit anti-mouse Cell Signaling 98941 1:200 IHC CD8α Technolog rabbit anti-mouse Bethyl IHC-00375 1:100 Ki-67 Laboratories rabbit anti- Cleaved Cell Signaling Caspase-3 9661 1:200 Technology (Asp175)

Fig. 15: Generation and validation of GBM cell lines with enforced TAZ expression.

A: Map of the lentiviral vector pLEX-TAZ.

B: GBM1B, A172, and GL261 cells were infected with lentivirus harboring the TAZ (FLAG- tagged) cDNA or no cDNA insert as the negative control to established stable cell lines by puromycin selection. Whole cell lysates were immunoblotted against FLAG and TAZ.

C: TAZ-Up genes were analyzed by qRT-PCR in GBM1B and GBM1B-TAZ cells, and by western blotting using whole cell lysates from GBM1B and A172 cells with +/- enforced

TAZ expression.

D and E: The expressions of various TAZ-Up genes were measured by western blotting in

GBM1B and GBM1B-TAZ (D); A172 and A172-TAZ (E). CD274 was analyzed in cells cultured in medium with1pg/mL IFN-gamma (D).

Protein fold expression normalized to β-Actin is shown below each lane. The data represent

Mean ± SEM (*: p<0.01).

Fig. 16: Enforced TAZ expression promotes malignant phenotypes of GBM cells.

A: Cells within cultures were stained with trypan blue and counted on the days shown to draw cell growth curve of GBM1B and A172 cells with +/- enforced TAZ expression.

B: Clonogenic survival of GBM1B and GBM1B-TAZ cells with +/- irradiation (a single dose or 3 daily doses of 3 Gy) were quantified and normalized to untreated control cells.

C: A172 and A172-TAZ cells were subjected to scratch wound healing assay to quantify migrating cells in the scratch area marked by the red line.

D: GBM1B and GBM1B-TAZ cells were plated onto laminin-coated Transwell membranes.

Cell migration was compared after 24 h by quantifying DAPI+ cells per field.

The data represent Mean ± SEM (*: p<0.01).

Fig. 17: Forced TAZ expression leads to more aggressive GBM1B tumor xenograft formation.

A and B: 10,000 viable GBM1B and GBM1B-TAZ cells were transplanted into the brains of

SCID mice (n=5). Coronal brain sections with H&E staining were shown from animals at day

60 post implantation (Bar = 0.5 mm) with tumor volume quantification (left panel). Brain sections stained with hNu antibody showed tumor cells that had invaded the contralateral corpus callosum area (marked by black rectangles in I). The number of hNu+ cells in 5 fields as marked underneath the picture (Bar = 100 mm) were quantified.

The data represent Mean ± SEM (*: p<0.01).

Fig. 18: Forced TAZ expression induces tumorigenesis in non-tumorigenic A172 cells.

10,000 viable A172 and A172-TAZ cells were transplanted into the brains of SCID mice

(n=5). Hematoxyline and eosin stained coronal brain sections were shown from animals at post-implantation day 76 (Bar = 0.5 mm, left panel; 20 μm, right panel; Arrow head: necrotic area).).

Fig. 19: Forced TAZ expression inhibits tumor infiltration of cytotoxic T lymphocytes.

A: 20,000 viable cells were transplanted into the brains of C57BL/6 mice (n=5). H&E-stained coronal brain sections (20 μm) obtained from animals at post-implantation day 30 are shown

(Bar = 0.5mm).

B: CD8+ T cell immunohistochemical staining and quantification in sections of GL261 and

GL261-TAZ orthotropic tumor (Bar=0.05mm).

The data represent Mean ± SEM (*: p<0.01).

Chapter 5: The EGFR inhibitor Osimertinib and TAZ inhibitor

Verteporfin potently inhibits the TAZ-driven oncogenic program in GBM cells and xenografts.

5.1 Introduction

By screening the Johns Hopkins Drug Library, a collection of >3300 drugs, Verteporfin (VP) was found as a TAZ/YAP inhibitor by abrogating the interaction between TAZ/YAP and

TEAD [485]. VP is a benzoporphyrin derivative, used to treat abnormal ocular blood vessels.

VP has been shown to inhibit GBM cell proliferation in vitro [486]. However, it may not be applicable in GBM due to still unclear BBB penetration and efficacy during systemic treatment; new TAZ/YAP inhibitors or inhibitors targeting their upstream regulators need to be developed for GBM therapy.

As we discovered that the EGFR signaling pathway induces TAZ in GBM and which in turn activates more oncogenic events including the positive feedback signal to RTKs, we hypothesized that RTK inhibitors may potentially inhibit the EGFR/TAZ signaling axis and its oncogenic effects in GBM. Therefore, we screened a panel of 12 BBB-permeable RTK inhibitors in GBM cell lines with wild type EGFR or the EGFRvIII mutation. Our result identified Osimertinib as a potent TAZ inhibitor.

Osimertinib (C28H33N7O2•CH4O3S, AZD9291, OS) is a third-generation FDA-approved

EGFR inhibitor, which has been used in treatment for non-small-cell lung cancer (NSCLC), especially for patients with EGFR T790M mutation [250, 487, 488]. OS has shown good brain penetration and has been used for treating lung cancer brain metastasis [489]. OS has also been shown to efficiently inhibit the EGFR/ERK signaling in GBM cells [490].

Besides in vitro analysis, we also performed systemic OS treatment in mice bearing human

GBM xenografts. Overall, our results provided a solid foundation to support the future clinical development of OS-based GBM therapy.

5.2 Materials and Methods

RTK inhibitors

Inhibitors used in this study were listed in Table 10.

Cell viability assay

5X10^4 cells were placed inside each well on a 96-well plate black with clear bottom

(ThermoFisher, Cat#7419) and treated with different concentrations of inhibitors for 48 hours.

Cell viability was measured by the AlamarBlue kit (ThermoFisher, Cat# DAL1100), following manufacture’s protocol.

Drug treatment in GBM tumor xenografts

All animal protocols were approved by the Johns Hopkins School of Medicine Animal Care and Use Committee. For intracranial xenograft, SCID mice were transplanted with 10,000 viable cells in 2 μL DMEM medium into the right caudate/putamen. Animals were treated with Osimertinib prepared in Ora-Plus solution (Paddock, Cat# NDC 0574-0303-16) by oral gavage. We monitored drug toxicity during treatment by measuring animal body weight daily

(minimal requirement: <10% weight loss). Mice were perfused with 4% paraformaldehyde for histopathological analysis. Tumor sizes were quantified by measuring maximum tumor volume on hematoxylin and eosin–stained brain coronal sections using computer-assisted morphometry (MCID software).

5.3 Results

Evaluation of VP and BBB-penetrating RTK inhibitors.

Bhat et al. have shown that TAZ silencing by shTAZs effectively inhibited GBM neurosphere growth in vitro and in vivo [407]. We focused on establishing a pharmacological TAZ- targeted strategy for clinical translation. Based on the EGFR-TAZ signaling axis identified above, along with TAZ inhibitor Verteporfin, we screened nine EGFR inhibitors, two PDGFR inhibitors, and one FGFR inhibitor, either under clinical development or FDA-approved for cancer treatment, for their capacity to inhibit TAZ in GBM cells (Table 10). Three GBM cell lines expressing wild-type EGFR (GBM1B) or EGFRvIII (GBM1B-EGFRvIII and M1123) were treated with each compound for 16 hours followed by 4h EGF stimulation. TAZ protein levels were then quantified by western blotting (Fig. 20A). The TAZ inhibitor Verteporfin

(VP, 1 µM ) and a third-generation EGFR inhibitor Osimertinib (OS, 0.5 µM) most potently downregulated TAZ expression in all three GBM cell models, when compared to the first- generation EGFR inhibitor Erlotinib (Er) used at 10 µM and other compounds. VP and OS more effectively inhibited the EGF induction of the validated TAZ-Up genes compared to Er

(Fig. 20B). VP and OS also showed higher anti-proliferation activity in vitro than Er, as determined by the MTT assay (Fig. 20C, Table 11). Since, it remains unclear whether VP can efficiently cross the BBB during systemic delivery in GBM xenograft models, my project focused on systemic OS treatment in preclinical GBM models.

Systemic OS treatment inhibits TAZ-driven signaling in GBM xenografts.

We examined the therapeutic potency of OS treatment in immunodeficient mice bearing pre- established orthotopic xenografts from GBM neurospheres with wild-type EGFR or

EGFRvIII mutation. Mice implanted with EGFRvIII+ M1123 cells received OS treatment

(100 mg/ kg oral daily) starting from post-implantation day 5 and were sacrificed for tumor size measurement at post-implantation day 15. OS treatment inhibited tumor growth by 95%

(Fig. 21A, 0.98 ± 0.2 vs 20.76 ± 5.0 mm3, n=5). In a parallel set of similarly treated mice,

M1123 tumor specimens were microdissected to harvest tumor tissue surrounding the

81 injection needle tract for qRT-PCR analysis. OS treatment significantly inhibited TAZ expression by >90%, and down-regulated 14 of 16 previously validated TAZ-Up genes (Fig.

21C), supporting the in-vivo efficacy of TAZ targeting by OS in GBM xenografts. In mice bearing GBM1B xenografts, OS treatment (50 mg/ kg oral, every other day) from post- implantation day 20 to 82 also significantly inhibited xenograft growth by 85% (Fig. 21B,

18.5±5.7 vs 2.9±0.8 mm3, n=5). Ki67 cell proliferation index was significantly reduced by

OS treatment from 54.8% to 37.6% (Fig. 21D). Tumor cell apoptosis as marked by cleaved caspase 3 (cc3) was significantly increased by about 2-fold in response to OS treatment (Fig.

21E). Analysis of GBM1B xenografts using human nuclear antigen (hNu) immunostaining showed >80% reduction of hNu+ cells in the invading tumor edge as compared to control tumors (Fig. 21F).

The therapeutic efficacy of OS on GBM1B-TAZ cells

We showed that OS potently inhibited TAZ expression and GBM growth both in vitro and in vivo. A key question also needs to be addressed is whether the anti-GBM effects of OS rely on TAZ inhibition. Here, we used GBM1B-TAZ cells harboring a FLAG-tagged TAZ transgene driven by the CMV promotor from the lentiviral vector (Fig. 15A and 15B). This

CMV-driven TAZ expression was EGF independent (Fig. 22A). The EGFR inhibitor OS failed to inhibit EGFR-independent TAZ expression in GBM1B-TAZ cells (Fig. 22B). As a control, VP inhibited this transgenic TAZ expression (Fig. 22B), consistent with the mechanism of VP action that blocks TAZ-TEAD interaction causing the cytoplasmic retention and TAZ degradation [491]. Therefore, GBM1B-TAZ cells serves as a suitable model for testing if this EGFR-independent and OS-unresponsive TAZ expression renders

GBM cells resistance to OS treatment. OS treatment in vitro showed significantly less efficacy in GBM1B-TAZ cells as compared to GBM1B cells (Fig. 22C, IC50: 16.88 µM vs.

2.47 µM). Our laboratory is currently performing systemic OS treatment on mice bearing

82 xenografts from GBM1B-TAZ and GBM1B cells to further determine if OS treatment in vivo also is less effectively in GBM1B-TAZ xenografts when compared to GBM1B xenografts.

We anticipate providing results from both in vitro and in vivo endpoints to support that OS inhibits GBM growth by blocking the EGF/EGFR-TAZ signaling axis in vitro.

5.4 Conclusion and Discussion

Based on the EGFR-TAZ signaling axis model, we tested a set of brain-penetrating RTK inhibitors. Both the known TAZ inhibitor VP and Osimertinib, a third-generation EGFR inhibitor were found to most potently inhibited TAZ and its gene targets in vitro. Systemic

OS treatment also effectively inhibited GBM xenograft growth as evidenced by the results from animals bearing wild-type EGFR or EGFRvIII+ GBM cells, thus supporting a broad application of OS in GBM patients with or without EGFRvIII. Furthermore, our in vitro results suggest that an EGFR-independent TAZ transgene may render GBM cells response to

OS treatment, indicating that the therapeutic efficacy of OS relies on effective TAZ inhibition, and TAZ inhibition may likely be a biomarker to predict OS sensitivity. This idea warrants further studies using primary GBM cell cultures and patient-derived xenograft models. If successful, a quick assessment of OS sensitivity, relying not only on the growth inhibition of primary GBM cell cultures by OS but also TAZ downregulation as a molecular biomarker, will likely facilitate future clinical trials of OS in GBM patients.

In summary, we discovered a novel EGFR-TAZ signaling axis that promotes GBM malignancy. We also provided preclinical results to justify future clinical applications of OS and other similar brain-penetrating EGFR inhibitors for TAZ targeting in GBM and likely other primary or metastatic brain tumors.

Even though VP demonstrated good TAZ-inhibition effect, it remains unclear about its BBB crossing ability, as the current formulation of VP in clinical use is based on liposomes. More

83 studies are necessary to characterize the liposome-based VP formulation in GBM models, and also compare this formulation to other newly developed nanoparticle delivery systems that might be helpful in VP delivery [492, 493]. VP-loaded nanoparticle has been studied in ovarian cancer [494] and has been tried as an adjuvant to TMZ in GBM by intratumoral injection that is relatively hard for clinical translation [495]. Moreover, we believe that other small chemicals targeting TAZ with a good BBB crossing ability are also worthy of development to treat GBM patients.

Table 10: Summary of chemical compounds used in Chapter 5.

Catalog Concentraion Category Abbr. Name Vendor Reference Number (µM) TAZ VP Verteporfin Sigma SML0534 1 [496] inhibitor

OS Osimertinib Medkoo 206042 0.5 [497] AEE AEE788 Cayman 18416 0.05 [498] PF PF299804 Cayman 9001879 0.1 [499] EGFR Lap Lapatinib Medkoo 100490A 0.2 [500] inhibitor BPI BPI-2009 Medkoo 205847 10 [501] Laz Lazertinib Medkoo 206860 0.1 [502] Lidocaine Lid Selleckchem S4667 1000 [503] hydrochloride

FGFR JNJ JNJ-42756493 Cayman 21813 0.05 [504] inhibitor

PDGFR Sun Sunitinib Cayman 13159 1 [505] inhibitor Sor Sorafenib Cayman 10009644 1 [506]

Table 11: IC50 of VP, OS, and Er in GBM cells.

(μM) VP OS Er

GBM1B 1.959 2.477 N.A.

GBM1B-TAZ 4.111 16.88 N.A.

M1123 6.307 10.85 N.A.

N.A. means half killing was not achieved at highest treating dose.

Fig. 20: Testing of a TAZ inhibitor (VP) and BBB-crossing RTK inhibitors.

A: GBM1B, GBM1B-vIII and M1123 cells were depleted of growth factors and treated with various compounds as marked for 16 hours. Cells were then treated with EGF for 4 hours and subjected to TAZ western blotting. Protein fold expressions normalized to β-Actin were quantified and normalized to control cells without compound treatment (dash line: TAZ level in compound-untreated control cells).

B: GBM1B cell samples as prepared in A with VP, OS, and Er treatment were subjected to qRT-PCR for TAZ-Up genes targets (compound-untreated control = 1.0, dash line).

C: Alamar blue cell proliferation assay were performed in GBM1B and M1123 cells with VP,

OS, and Er treatment.

The data represent Mean ± SEM. (*: p<0.01)

Fig. 21: Systemic OS therapy inhibits TAZ expression, TAZ-Up genes and xenograft growth in GBM xenograft models.

A: H&E stained coronal brain sections were prepared for tumor volume quantification of

M1123 xenografts with +/- OS treatment (n=5, post-implantation day 15, Bar = 0.5 mm).

B: H&E stained coronal brain sections were prepared for tumor volume quantification of

GBM1B xenografts with +/- OS treatment (n=5, post-implantation day 82, Bar = 0.5 mm).

C: Tumor specimens of M1123 xenografts with +/- OS treatment were microdissected from the region marked by injection needle tract for qRT-PCR analysis of TAZ and TAZ-Up gene targets (n=2).

D-F: Ki67 immunohistochemistry staining showed less Ki67+ cells in OS-treated tumors (D,

Bar=50 µm). Cleaved caspase 3 (cc3) immunohistochemistry staining showed more apoptotic cells in OS-treated tumors (E, Bar=50 µm). hNu immunostaining detected tumor cells in the invading tumor edge (white dash line) for quantification (F, Bar = 50 µm)

The data represent Mean ± SEM. (*: p<0.01)

Fig. 22: Transgenic TAZ is inhibited by VP by not by OS.

A: GBM1B-TAZ cells were depleted from growth factors for 16 hours and treated with +/-

EGF for 4 hours. The level of Flag-tagged TAZ transgene was not altered by EGF.

B: GBM1B-TAZ cells were depleted from growth factors and treated with VP and OS for 16 hours. Cells were then treated with EGF for 4 hours and subjected to FLAG western blotting.

C: Alamar blue cell proliferation assay were performed in GBM1B and GBM1B-TAZ cells with OS treatment.

Chapter 6: Conclusion and Discussion

6.1 Conclusion

GBM is highly heterogeneous, with different oncogenic pathways activated in different clones, forming a complex autocrine/paracrine network with tumor niches to stimulate tumor growth. In the GBM context, RTK signaling is essential for tumorigenesis, progression, therapeutic resistance, and recurrence. There are multiple levels of positive feedback on RTK signaling and cross-talk between different RTK pathways [259, 507]. In EGFR-targeted therapies, one of the major mechanisms causing therapeutic resistance is by bypassing EGFR signaling activation, such as activating the PDGFR or MET signaling cascade. A better understanding of effectors downstream of the EGFR signaling would be beneficial to overcome these bypass mechanisms. Here we found that TAZ is an essential downstream mediator of the EGFR signaling and describe a novel TAZ-regulating mechanism involving the EGF-TAZ feedback loop in the GBM context.

In Chapter 2, we show that EGF is a potent regulator of TAZ through activating its transcription in GBM. In the experiments we listed above, EGF induced TAZ mRNA transcription, protein expression, nuclear TAZ levels, and expression of multiple well- established TAZ downstream targets. EGF induced TAZ through EGFR, the downstream transcriptional factor STAT3, and partially through the MAPK pathway. Besides, EGFRvIII

GBM cells display ligand-independent activation of TAZ.

In Chapter 3, based on our genome-wide study, we identify TAZ as a possible signaling hub in GBM. TAZ drives multiple oncogenic signaling pathways that are important for promoting

GBM aggressiveness. First, multiple RTK signaling ligands and receptors are downstream genes induced by TAZ. Besides the EGF-TAZ-EGF (EGFR) positive feedback loop in GBM,

TAZ also induces RTK spreading involving multiple RTK signaling pathways, such as the

PDGFR pathway (PDGFRA, PDGFB, PDGFA), FGFR pathway (FGF1, FFGF2, FGFR4), and VEGFR pathway (VEGFA). All these RTK signaling pathways form a signaling network stimulating each other either by autocrine or paracrine mechanisms in GBM [4]. TAZ adds another level of complexity into GBM heterogeneity and drug resistance to single RTK inhibitors. This feedback loop may contribute to the resistance of EGFR inhibitors in GBM.

TAZ also activated other targets important for GBM initiation, development, and maintenance; thus, TAZ is potentially a very potent target for GBM treatment.

In chapter 4, based on our novel EGFR-TAZ signaling hub model, we constructed TAZ overexpression GBM cells. We found that TAZ overexpression would enhance cell proliferation and migration both in vitro and in vivo, identifying TAZ as a potential targeting molecule using GBM cell lines and pre-clinical models.

In chapter 5, we screened BBB crossing potential TAZ inhibitors in vitro and tested them in vivo. VP is a benzoporphyrin derivative and an FDA approved drug treating central serous retinopathy [508]. VP can interrupt TAZ/YAP’s binding to TEAD, thus further inhibiting downstream targets’ transcription. However, VP has poor water solubility and can hardly across the BBB. Better TAZ targeting methods need to be developed for GBM patients.

Following our discovery that EGFR regulates TAZ in GBM cell lines, we screened a library of BBB crossing RTK inhibitors and found an EGFR inhibitor with good TAZ inhibition potential in vitro and in vivo. Osimertinib (OS), a third-generation EGFR inhibitor, is an approved drug for small cell lung cancer (SCLC), and can specifically target EGFR T790M mutation. [487, 489] It can cross the BBB and is effective in treating CNS metastasis of lung cancer [489].

We found that both VP and OS are good at TAZ-targeting and inhibiting tumor cell survival, in vitro and in vivo (OS only). To summarize, both VP and OS are worthy of further development as potential TAZ-targeting agents in GBM.

In conclusion, we proposed a model (Fig. 23), where TAZ serves as a signaling hub in GBM, starting from EGF induction to further induce RTK signaling and other oncogenic pathways.

TAZ-related signaling is important in GBM initiation, development, maintenance, and drug resistance. Thus, TAZ serves as a good target in GBM for new drug development and existing drug evaluation.

6.2 Discussion

EGF-TAZ axis turns on RTK spreading and provides positive feedback at multiple levels

RTK signaling responds to positive feedback, and this feedback serves as a form of reinforcement in multiple tumors. In ER-negative breast cancer, EGFR target, ER-α36

(transcriptionally activated) physically interacts with the EGFR/Src/Shc complex and mediates estrogen-induced phosphorylation of EGFR and Src to help retaining responsiveness to mitogenic estrogen signaling [509]. In head and neck squamous cell carcinoma, EGFR activates NF-κB through AKT/mTOR and NF-κB further activates EGFR

[510].

Here, we found that TAZ amplifies multiple RTK signaling pathways, such as the EGFR pathway (EGF, EGFR, ERBB3), PDGFR pathway (PDGFRA, PDGFB), and FGFR pathway

(FGF1, FGF2, FGFR4), which cross-talk with each other either by autocrine or paracrine mechanisms in GBM [439]. Thus, EGF induced TAZ results in RTK spreading in tumor, which adds another level of complexity on GBM heterogeneity and drug resistance to single

RTK inhibitors.

Besides RTK spreading, based on our gene analysis results, the TAZ-up genes are involved in positive feedback to the EGF-TAZ signal axis at multiple levels.

WWTR1, the gene coding for TAZ protein, is one of the TAZ-up genes, indicating that EGF induced TAZ can further activate its own transcription. Besides, TAZ transcription is also expected to increase as a result of enhanced ERK/STAT activity, either by RTK spreading discussed before, or it’s directly targeting JAK genes.

Second, TAZ-up genes also include multiple TAZ transcriptional coactivators, such as

TEAD1, RUNX, ELK [469] and JUN [344]. This upregulation of TAZ’s coactivator provides increased binding opportunities for TAZ and thus a functional enhancement on the transcription of TAZ downstream targets.

Taken together, the EGF-TAZ axis will positively feed-forward on itself and induce activation of other RTKs in autocrine or paracrine format in GBM. These will provide proliferation advantage for GBM cells especially after treatment.

EGF-TAZ axis can play important roles in other tumor types.

There have been prior reports on TAZ/EGF/RTK interactions in cancer. In HER2-positive breast cancer, EphA2 receptor tyrosine kinase was reported to activate YAP and TAZ [442].

Yang et al. reported a Gas6/GDNF/FGF-TAM/RET/FGFR-MAPK/PI3K regulation of

TAZ/YAP in RTK-driven cancer [443]. TAZ is reported to target AREG, an EGFR ligand and this plays an important role in breast tumorigenesis and metastasis [511]. AREG is also reported as a TAZ target in non-small-cell lung cancer, and this regulation plays an important role in Gefitinib sensitivity [512]. Yang et al. reported that TAZ activates EGFR in GBM

[470].

As shown in Table 6 and Table S11, EGF activates TAZ-dependent genes important in multiple cancer types, namely small cell lung cancer, renal carcinoma, melanoma, bladder cancer, prostate cancer, colorectal cancer, pancreatic cancer, gastric cancer, and breast cancer.

In most of the listed tumors, EGFR and TAZ have been found as important molecular components.

Both EGFR and TAZ are relatively rare in small cell lung cancer, while EGFR mutation occurs in over 60% of non-small cell lung cancer and TAZ is currently considered as an oncogenic marker for non-small cell lung cancer. Mutation of EGFR and TAZ usually links to drug resistance in small cell lung cancer [513, 514].

TAZ activation has been reported to sensitize renal carcinoma cells to Ferroptosis (a form of regulated cell death), regulated by cell density influenced the Hippo pathway [515]. And

EGFR mutation occurs in more than 80% cases of clear cell renal carcinoma [516], and the relationship between TAZ and EGFR is worth investigation in renal carcinoma.

EGFR itself is involved in the progression and metastasis of melanomas [517] and has been suggested as a progression marker. TAZ/YAP also is highly expressed in melanoma and promotes tumor progression [518]. In melanoma, it has been found that RAF-1/MST-2 interaction facilitates crosstalk between MAPK and Hippo signaling [519]. The core components of the Hippo pathway, which induces bladder cancer stemness acquisition, metastasis, and chemoresistance, have been emphasized [520]. The significant association of

EGFR overexpression with tumor grade, muscularis propria invasion and recurrence signifies its prognostic value; therefore EGFR can be used as a prognostic biomarker in Urothelial bladder carcinoma [521]. di Martino et al. reported on the molecular alterations occurring during urothelial malignant transformation and implicates TAZ as a possible therapeutic target in FGFR3-dependent bladder tumors [522].

EGFR is overexpressed in the majority of prostate cancer [523]. TAZ has been found to promote the EMT of prostate epithelial cells and RhoGAP protein serves as a direct TAZ target to drive prostate cancer cell motility [524]. The same group also found that MAPK

96 inhibitor U0126 treatment decreased TAZ expression, suggesting RTKs might be involved in

TAZ regulation.

Co-overexpression of TAZ and YAP increases colorectal cancer proliferation and metastasis

[525]. A GPCR receptor – ETAR has been reported to regulate TAZ/YAP in colorectal cancer and stimulates cell proliferation, migration, and tumorigenesis [526]. The TAZ target: Axl plays an important role in clonogenicity, non-adherent growth and tumor formation [527].

Cytoplasmic TIAM1 suppresses TAZ/YAP interaction with TEADs and inhibits expression of

TAZ/YAP target genes [528]. As listed above, TAZ usually is considered to be regulated through GPCR in colorectal cancer, but EGFR is also an important player in colorectal cancer initiation and progression [529]. The interaction between EGFR signaling and TAZ in colon cancer is worthy of studying.

TAZ/YAP participates in regulating pancreatic cancer immune escape, chemoresistance [530] and tumor initiation [531]. The Yap signaling network was found to correlate with poor patient outcomes in pancreatic cancer [330, 532]. TGFβ-activated kinase 1 (TAK1) was suggested to regulate TAZ/YAP in pancreatic cancer [533].

In gastric cancer, TAZ/YAP was found to regulate the MYC gene which plays an important role in gastric carcinogenesis [347]. And YAP/TAZ was found to be regulated by the traditional Hippo pathway and mechanical stress in gastric cancer [534].

More than 60% of triple-negative breast cancer showed positive nuclear TAZ staining, and 90% of metastatic breast carcinoma with EMT features were TAZ positive [535]. TAZ is important for breast CSC induction and maintenance and tumor metastasis [536]. An S-phase kinase- associated protein 2 (SKP2) was found to have an important role in mediating the neoplastic activity of TAZ in breast cancer [537]. An import transcription partner for TAZ/YAP in breast cancer tumorigenesis and drug resistance is Pin1 [538]. EGFR itself overexpressed in about

80% of triple-negative breast cancer, and TAZ can regulate the sensitivity of breast cancer cells to EGFR inhibitors [539].

TAZ and EGFR both play important roles in each of the tumors listed above. Even though the interaction between TAZ and EGFR has not been studied in most of those tumors, our pathway analysis suggests that it is worth studying their interactions in these tumors, and the therapeutic potential for the EGFR inhibitor, OS and TAZ inhibitor, VP.

EGF-TAZ axis is important for tumor invasion by regulating cancer cell interaction with

ECM and HIF1A signaling

The top-ranked KEGG term identified in our pathway analysis is focal adhesion, and regulation of actin cytoskeleton ranked the second. This suggests that TAZ regulated genes participate heavily in interacting with ECM. Additionally, ECM-receptor interaction, adherent junction, and gap junction are also up-regulated.

As described in the introduction, focal adhesion is a very important Hippo regulator in response to mechanical cues. Recently it has been discovered that TAZ/YAP can also regulate focal adhesion through YAP/TAZ-dependent myosin phosphatase regulator, NUAK2, or by inhibition of Rho-ROCK-myosin II [389]. These feedback regulations are important for the modification of cell mechanics, force development and adhesion strength, determination of cell shape, migration and differentiation and vasculogenesis. The actin cytoskeleton was reported to block Hippo signaling and allow the nuclear accumulation of TAZ/YAP [540,

541]. And YAP was reported to regulate actin depolymerization and F-actin to G-actin turnover through ARHGAP29, a RhoA suppressor [369]. CTGF acts as an important downstream effector of TAZ in regulating ECM production [542]. Cytoskeleton-associated vinculin is important in regulating ECM stiffness and TAZ/YAP nuclear localization [543].

YAP/TAZ was also proposed to integrate mechanical signals with Bone Morphogenetic

Proteins (BMP) signaling for maintaining gap/adhesion junction and integrity of angiogenic

98 vessels [544]. Altogether, TAZ/YAP serves as a communication hub between ECM and tumor cells. On one hand, TAZ/YAP senses ECM status and regulates cellular response accordingly, on the other, TAZ/YAP also turns on important ECM modifiers.

HIF-1α a signaling ranked high in our analysis and HIF-1α was validated as an EGF-TAZ axis target in our study. In breast cancer, TAZ and HIF-1α have been found to serve as reciprocal co-activators and regulate the hypoxia response (HIF-1α and TAZ serve as reciprocal co-activators in human breast cancer cells). HIF-1α is a master regulator of GBM angiogenesis. By regulating both cytoskeleton/ECM interaction and angiogenesis, the EGF-

TAZ axis serves as a key regulator for GBM invasiveness.

EGF-TAZ axis is important in the regulation of tumor metabolism

EGF-TAZ induced genes are also involved in multiple aspects of metabolism regulation: central carbon metabolism, proteoglycans, choline metabolism, glycosaminoglycan biosynthesis, and starch and sucrose metabolism.

It has been long studied that TAZ/YAP can be regulated through metabolism. Enzo et al. found that inhibition of glucose metabolism or glycolysis decrease TAZ/YAP transcription

[317]. Methylglyoxal (MG), a side-product of glycolysis, could activate TAZ/YAP [545]. O-

GlcNAcylation can activate YAP by two mechanisms, suppressing LATS-dependent phosphorylation [546] and bTrCP-dependent ubiquitination [547]. On the other hand, a high level of glucagon may inhibit the expression and activity of TAZ/YAP [303, 304]. Lipid metabolism also plays an important role in TAZ/YAP regulation. Stearoyl-CoA-desaturase 1

(SCD1) was found to promote nuclear localization and activity of TAZ/YAP in lung cancer

[548]. In β-cells, palmitate promotes TAZ/YAP transcriptional activity by an actin-dependent mechanism [549] and indirectly regulates TAZ/YAP transcription via TEAD S-palmitoylation

[550].

Hyperactivation of YAP led to increased production of the glucose transporter GLUT3, and a significant increase in glucose uptake and lactate production [319]. Another group showed that YAP elevates Hexokinase 2 (HK2), a key enzyme for glycolysis, at mRNA and protein levels [551]. YAP was also found to regulate HK2 and PFKFB3 indirectly via its targets

BCAR4 [552]. On the other hand, YAP was also found to suppress gluconeogenesis through

PGC1α [553]. TAZ/YAP also upregulates glutamine level and enhances nucleotides synthesis via glutamine synthetase [340, 554]. TAZ/YAP stimulates high-affinity amino acid transporters transcription (SLC1A5, SLC7A5, and SLC38A1) [442, 555, 556]. In lipid metabolism, TAZ/YAP has been recently demonstrated to accelerated lipid accumulation and decrease lipid deposition through uncoupling protein 1 (UCP1) [557].

As summarized above, metabolism plays an important role in TAZ/YAP regulation, however,

TAZ/YAP regulation of metabolism has only been slightly studied with greatest focus on YAP regulation. Our genomic studies provide new directions for future studies.

EGF-TAZ axis regulates tumor immune response

In lung cancer, TAZ was reported to up-regulate PD-L1 and facilitate tumor immune evasion, and MST/LATS can block PD-L1 upregulation by TAZ [473]. In our studies, we validate PD-

L1 (CD274) as an EGF-TAZ target at the RNA level in both GBM1B and A172 models and at the protein level in A172 and find strikingly reduced lymphocyte infiltration in GL261-

TAZ derived brain tumor suggesting TAZ hyperactivation plays a role in immune suppression in GBM. In our follow up studies, a more detailed analysis of immune regulations and their mechanisms will be conducted.

Potential TAZ targeting methods

Based on our novel EGF-TAZ signaling axis model, we successfully identified effective TAZ targeting strategies using GBM pre-clinical models: the first one is a TAZ/YAP inhibitor, verteporfin (VP). VP is a benzoporphyrin derivative and an FDA approved drug for treating

100 central serous retinopathy. VP can interrupt TAZ/YAP’s binding to TEAD, thereby inhibiting downstream targets’ transcriptions. Second is a third-generation EGFR inhibitor, Osimertinib

(OS). OS is an approved drug for treating small cell lung cancer (SCLC), and can specifically target EGFR T790M mutation. It can cross the BBB and is effective in treating CNS metastasis of lung cancer. We found both VP and OS are good at TAZ-targeting and inhibiting tumor cell survival, in vitro. OS was also found to inhibit TAZ signaling, tumor growth, and tumor invasiveness in vivo. To summarize, both VP and OS are worth further investment as potential TAZ-targeting in GBM.

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Fig. 23: Model of the EGFR-TAZ signaling axis in GBM cells.

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Chapter 7: Supplement data

7.1 R script for KEGG analysis

Uploaded in supplement data

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Table S1: Summary qRT-PCR primers used for validating RNA-Seq results in Chapter 3 Gene Forward Reverse EGFR AACACCCTGGTCTGGAAGTACG TCGTTGGACAGCCTTCAAGACC PDGFB GAGATGCTGAGTGACCACTCGA GTCATGTTCAGGTCCAACTCGG TGCGATGCCAAGCAGTCTGTGA GCATAGCCCAATCTGAGAACCA EGF C PDGFRA GACTTTCGCCAAAGTGGAGGAG AGCCACCGTGAGTTCAGAACGC PDGFA CAGCGACTCCTGGAGATAGACT CGATGCTTCTCTTCCTCCGAATG VEGFA TTGCCTTGCTGCTCTACCTCCA GATGGCAGTAGCTGCGCTGATA AGCGGCTGTACTGCAAAAACGG CCTTTGATAGACACAACTCCTC FGF2 TC FGF1 ATGGCACAGTGGATGGGACAAG TAAAAGCCCGTCGGTGTCCATG FGFR4 AACACCGTCAAGTTCCGCTGTC CATCACGAGACTCCAGTGCTGA CTATGAGGCGATACTTGGAACG GCACAGTTCCAAAGACACCCGA ERBB3 G CCTTGAAAGCTCAGAACTCGGA TGCTGCGTTAGCATGAGTTGGC JUN G TATGAGCCAGAAGAACTTTTAG CACCTCTTTTGGCAAGCATCCT HIF1A GC G CCAGATGGAAACTGTTCGCTCAG GAGGTTGGTACATCAGAAACAC JAK2 C CXCR4 CTCCTCTTTGTCATCACGCTTCC GGATGAGGACACTGCTGTAGAG CD274 TGCCGACTACAAGCGAATTACTG CTGCTTGTCCAGATGACTTCGG TEAD1 CCTGGCTATCTATCCACCATGTG TTCTGGTCCTCGTCTTGCCTGT

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Table S2: Summary of ChIP-PCR primers used for validating ChIP-Seq results in Chapter 3. Gene Forward Reverse EGFR TCTCTACGGCTGCATTCCTT AGGGGACTCTGTCACACACC PDGFB ACTGAATGGGCAAAAACTGG TGCAAACAGGGACAATTTGA EGF TATTGGCTGTGGGTTTGTCA ACCATGATCAAGTGGGCTTC PDGFRA CAGGTGGATTGCTTGAGGTC CTTGAGTGCAATGGCATGAT PDGFA CTGAGCCCAGAGTCAGGTTC GGAGTAGCGACTGCATGTGA VEGFA CCAACTTCTGGGCTGTTCTC CCCCTCTCCTCTTCCTTCTC FGF2 ATGATGACAATGGCGGTTTT GGATCCCAAGGCAGAAGAAT FGF1 TGCCTTTTGCCTTTGACTCT ATGGAGGAGCTGAGCTTTGA FGFR4 CCCAGAGCCAGTTCACAAAC CGAGTAAGGAGCTTGGCAGT ERBB3 GTTGGGGGTAAGGTCACAGA GAATAGAAAGGCGGGAAAGG HIF1A CATCACTGGCCATCAGAGAA TGGCTGGGTCAAATGGTATT JAK2 AAATGGTGCTGGGAAAACTG GCCATTGCTTTTGGTGTTTT CXCR4 AGTATTGGCCCCCACTCTCT AGCACCACAGAGATGCTCCT CD274 CAGCACCTGTTGTTTCCTGA GGGCGAAGGATATGAACAGA TEAD1 GTCCTGGCGTTCATTTCATT AGTCTGCAAAGTGCTTGGTG NC1 GTCTGTACTCCCAGCTACTC GACAGAGCAAGACTCCATC NC2 GACTGGTTCATTCACTGCTC CACTTCCCTACCCGAAAC

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Table S3: Differentially expressed genes in GBM1B cells after 4-hour EGF treatment Provided as separated files. Sheet 1: differentially expressed genes (FDR ≤ 0.05) Sheet 2: up-regulated genes (log2(-fold change)) ≥ 0.8, FDR ≤ 0.05) Sheet 3: down-regulated genes (log2(-fold change)) ≤ −0.8, FDR ≤ 0.05)

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Table S4: Differentially expressed genes in GBM1B cells after 24-hour EGF treatment Provided as separated files. Sheet 1: differentially expressed genes (FDR ≤ 0.05) Sheet 2: up-regulated genes (log2(-fold change)) ≥ 0.8, FDR ≤ 0.05) Sheet 3: down-regulated genes (log2(-fold change)) ≤ −0.8, FDR ≤ 0.05)

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Table S5: Up-regulated genes identified by RNA-Seq after either 4-hour or 24-hour EGF treatment (FDR ≤ 0.05, log2 (fold change) ≥0.8) A2M ACTA2 AL020996.1 ARHGDIG AARSD1 ACTBP11 AL353791.1 ARHGEF16 ABCA11P ACTG1 AL953854.2 ARHGEF4 ABCA12 ACTG1P10 ALDH1L2 ARID3A ABCA2 ACTN1 ALDOC ARID3B ABCC3 ACTN2 ALG10B ARID5B ABCC6P1 ACTR3 ALPK2 ARL13B ABCD1 ADAM11 AMIGO2 ARPC1B ABL2 ADAM12 AMMECR1 ARPC4-TTLL3 ABLIM1 ADAM19 AMPD3 ARSG AC003006.7 ADAM9 ANGPTL4 ARSI AC004158.3 ADAMTS10 ANK2 ARSJ AC005594.3 ADAMTS15 ANKHD1 ASB2 AC005789.11 ADAMTS16 ANKLE1 ASCC3 AC006014.7 ADAMTS3 ANKRD18EP ASMTL AC006486.9 ADAMTS4 ANKRD20A1 ASPHD2 AC007405.6 ADAMTS9 ANKRD20A2 ASS1P12 AC007566.10 ADCY1 ANKRD20A3 ATP10A AC010745.1 ADCY5 ANKRD27 ATP13A3 AC012512.1 ADM ANKRD33B ATP1B2 AC016735.2 ADNP ANKRD34A ATP2A3 AC016773.1 ADORA2B ANKRD36C ATP2B1 AC024580.1 ADRBK2 ANKRD42 ATP2B2 AC025165.8 ADSSL1 ANKRD45 ATP6V0A1 AC027612.4 AEBP1 ANXA1 ATR AC027612.6 AEN ANXA11 ATXN1 AC046143.3 AFF3 ANXA2 ATXN7 AC064875.2 AGAP1 AP000275.65 AUTS2 AC069287.1 AGAP2 AP001610.5 AXL AC083899.3 AGFG2 AP1S1 B3GALT5 AC092811.1 AGO2 AP1S3 B4GALNT3 AC092835.2 AGPAT9 AP3S2 B4GALT5 AC093673.5 AGT APLN BAALC AC096677.1 AHCTF1 APOL4 BACE2 AC124309.1 AHNAK APOL6 BACH2 AC137932.1 AHNAK2 AQP1 BAI1 AC137932.5 AHR AQP3 BAIAP2 AC147651.4 AIM1 ARAP3 BAIAP2-AS1 ACAD11 AK4 ARC BAK1P1 ACAT2 AK4P1 ARF6 BATF3 ACER2 AK4P3 ARHGAP11A BCL2 ACHE AK7 ARHGAP18 BCL3 ACO1 AKAP12 ARHGAP25 BDNF ACOX2 AKAP2 ARHGAP26 BDP1 ACSBG1 AKAP5 ARHGAP29 BEGAIN ACSS2 AKAP6 ARHGAP31 BEND3P3 ACSS3 AKR7A3 ARHGAP32 BEND4

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BICC1 CAMK2D CEP170B COL1A1 BIRC3 CAMKK1 CEP290 COL26A1 BIRC6 CAPN2 CEP85L COL27A1 BLZF1 CAPN5 CFH COL4A1 BMP8B CAPRIN2 CGN COL4A3 BNC2 CARD10 CH25H COL4A4 BNIP3 CARS CHD9 COL6A1 BRINP2 CASP7 CHGB COLGALT1 BSN CBL CHI3L1 CORO1A BST1 CBLN1 CHMP2B CORO2A BTAF1 CCDC102B CHPF CORO2B BTBD19 CCDC113 CHPF2 CORO6 BZW1P2 CCDC144B CHRD COTL1 C10orf12 CCDC144CP CHRM3-AS2 CPA2 C10orf67 CCDC19 CHRNA3 CPA4 C11orf82 CCDC64 CHRNA9 CPEB2 C12orf5 CCDC65 CHST11 CPEB4 C12orf68 CCDC74A CHST2 CPLX2 C12orf75 CCDC74B CHST6 CPNE2 C12orf79 CCDC88A CHST7 CPNE4 C15orf52 CCDC88B CHST8 CPNE5 C18orf25 CCL2 CHSY1 CPNE8 C1orf132 CCL8 CICP22 CRABP2 C1orf220 CCND1 CIITA CREB3L1 C1QL1 CCR1 CILP2 CRLF1 C1QL4 CCRN4L CISH CRYBB1 C1RL CCT6B CKMT1A CSDC2 C21orf62 CD109 CLCF1 CSGALNACT1 C2CD4A CD248 CLCN5 CSNK1G1 C2orf72 CD274 CLDN4 CSPG4 C2orf80 CD302 CLIC1P1 CSPG4P11 C3orf52 CD44 CLIP1 CSPG4P13 C4orf19 CD6 CLIP2 CSRNP1 C6orf118 CD63 CLIP4 CTA-445C9.15 C6orf223 CD74 CLMN CTBS C8orf46 CD82 CLMP CTC-273B12.8 C8orf56 CD9 CLRN1 CTC-479C5.12 C8orf58 CD97 CMKLR1 CTC-786C10.1 C9orf89 CD99P1 CMTM7 CTD-2047H16.4 CA12 CDC42 CMTM8 CTD-2135D7.2 CA13 CDC42EP1 CNIH3 CTD- CA2 CDC42EP2 CNN2 2207O23.10 CA9 CDC42EP3 CNN3 CTD-2350C19.1 CABIN1 CDH6 CNNM1 CTD-2561J22.2 CACNA1I CDHR2 CNTF CTD-2574D22.4 CACNB4 CDK6 CNTNAP3 CTD- CACNG5 CDKL5 CNTNAP3B 2583A14.10 CACNG8 CDKN1A COBL CTD-2622I13.3 CAMK2A CDKN2B COBLL1 CTD-2636A23.2 CAMK2B CELSR1 COL14A1 CTGF

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CUBN DNM1 EMILIN2 FAM131B CX3CL1 DNMBP EMILIN3 FAM135A CXCL11 DOCK4 EML2 FAM150B CXCL9 DOCK6 EML4 FAM157A CXCR4 DOK4 EMP1 FAM157C CXorf38 DOK6 EMP3 FAM162A CYB561 DOK7 ENDOD1 FAM178A CYB5D1 DOT1L ENG FAM181A CYFIP2 DPF3 ENO2 FAM181A-AS1 CYGB DPP8 ENTPD7 FAM184A CYP1B1 DRAM1 EOGT FAM184B CYP2E1 DSCAM EP300 FAM196A CYP4F11 DTX1 EP400NL FAM198A CYP51A1 DUSP3 EPB41L1 FAM19A5 CYR61 DUSP4 EPB41L2 FAM208B CYTL1 DUSP5 EPB41L4B FAM227A DAGLA DUSP6 EPHA1 FAM46A DCBLD2 DUSP8 EPHA2 FAM49A DCLK1 DUSP9 EPHB2 FAM65B DCST1 DYNC2H1 EPPK1 FAM72A DDB2 DYX1C1- EPS8L2 FAM72B DDHD1 CCPG1 ERBB3 FAM81A DDR2 E2F7 ERC1 FAM83F DDX21 EDA2R ERN1 FAM83G DDX59 EDEM1 ERRFI1 FAM84A DEGS1 EEA1 ERVK13-1 FAM84B DGCR5 EEPD1 ERVW-1 FARP2 DGCR9 EFCAB4B ESYT3 FAS DGKA EFCC1 ETNK2 FAT1 DGKE EFHC1 ETS1 FAT3 DGKG EFHC2 ETS2 FBLIM1 DGKH EFNA3 ETV4 FBN1 DGKI EGF ETV5 FBN2 DGKZ EGFEM1P EVA1C FBXO36 DHCR24 EGFL7 EVC FCGR2C DHCR7 EGFR EXOC6 FCHSD1 DHPS EGFR-AS1 F12 FCRLA DIAPH2 EGLN3 F2RL1 FDFT1 DIAPH3 EGR1 F3 FEM1C DIRAS2 EGR2 FABP5 FERMT2 DLC1 EGR3 FABP5P7 FGF1 DLEU1 EHBP1L1 FABP7 FGF2 DLG4 EHD2 FADS3 FGFBP3 DLK2 EHD4 FAH FGFR1 DLST EIF5A2 FAHD2CP FGFR4 DMTN ELF4 FAM101B FHL2 DMXL2 ELFN1 FAM102B FHOD1 DNAH1 ELK3 FAM129A FILIP1L DNAJB1 ELK4 FAM129B FKBP11 DNAJC22 EMILIN1 FAM131A FKBP14

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FKBP1A GFOD1 HIPK1 IL1RAP FKBP9L GFPT2 HIPK2 IL27RA FLNA GGN HIPK3 IL32 FLNB GIPC3 HIVEP2 IL4R FLNC GJB1 HIVEP3 IL6R FMN1 GJB2 HK2 ILDR2 FMNL1 GK5 HMGA2 INHA FMNL3 GLCE HMGCR INHBE FNDC3B GLIPR1 HMGCS1 INPP1 FNTB GLIS2 HNF4G INPP4B FOSB GLIS3 HOMER1 INPP5D FOSL1 GLS HOMER2 INPP5F FOSL2 GNG12 HPCAL4 INSIG1 FRAS1 GNG7 HPSE IPCEF1 FREM1 GNL1 HR IPPK FREM2 GNL3LP1 HRASLS IQCD FRMD4B GOLIM4 HRCT1 IQCH FRMD8 GPD2 HRH1 IQGAP1 FRRS1L GPR12 HS3ST3A1 IQGAP2 FRY GPR124 HS3ST3B1 IQSEC2 FRYL GPR135 HSD17B12 IRAK2 FSCN2 GPR139 HSD17B3 IRF1 FSIP1 GPR153 HSD17B7 IRS1 FST GPR155 HSPA4L ISPD FUT1 GPR157 HSPA6 ISYNA1 FZD5 GPR158 HSPA7 ITGA2 FZD6 GPR180 HSPB3 ITGA3 FZD9 GPR3 HSPG2 ITGA6 G6PD GPR62 HVCN1 ITGA7 GAD1 GPR75 HYAL3 ITGAV GADD45A GRIA2 ICAM1 ITGB1BP2 GAL GRIA3 ICAM5 ITGB8 GALNT12 GRIK3 ICOSLG ITK GALNT18 GRIK4 IDH3A ITPKC GAP43 GRIN2B IDI1 ITPR1 GAPDHP14 GRIN2D IDO1 ITPRIPL2 GAREM GSN IDS JAG1 GARNL3 GTF2H4 IFITM10 JAG2 GBAS GXYLT2 IFNB1 JAK2 GBE1 GYLTL1B IFNGR2 JPH1 GBP1 H19 IFNL1 JPH3 GBP2 HAP1 IFNL2 JPH4 GBP5 HAPLN4 IGFBP1 JUN GCH1 HAS2 IGFBP7-AS1 KAZALD1 GCK HBEGF IGLON5 KB-1732A1.1 GCLM HBQ1 IGSF5 KBTBD8 GDF15 HCFC2 IGSF9B KCNA2 GDNF HCN2 IL11 KCNC3 GEM HERC3 IL15RA KCNC4 GFAP HIF1A IL18BP KCND3

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KCNF1 LAMA4 LOXL1-AS1 MAPRE2 KCNH4 LAMC1 LOXL2 MCC KCNIP1 LARP1B LOXL4 MCHR1 KCNJ2 LAT2 LPCAT2 MCM8 KCNJ4 LATS2 LPCAT4 MDGA1 KCNJ5 LBH LPHN2 ME1 KCNK10 LCA5 LPL MED12L KCNK13 LCTL LPP MED29 KCNK15 LDHA LPPR3 MEF2B KCNK5 LDHAP4 LRP8 MEF2C KCNK7 LDLR LRRC10B METRNL KCNN2 LEMD1 LRRC4 METTL7B KCNN3 LEPREL1 LRRC48 MFSD2A KCNN4 LGALS3 LRRC53 MFSD6 KCNQ5 LGI1 LRRC73 MFSD7 KCTD9 LGI2 LRRC8C MGRN1 KDELR3 LGI3 LRRK1 MIAT KIAA0040 LGR6 LSM10 MICALL2 KIAA0226L LHFPL2 LSM12P1 MIR210HG KIAA0513 LHX4 LSP1 MIR22HG KIAA0754 LIF LTBP1 MIR24-2 KIAA0947 LIMK1 LUCAT1 MIR4292 KIAA1199 LIMS1 LURAP1 MIR4435-1HG KIAA1211L LIN7A LY96 MIR503HG KIAA1467 LINC00106 LYAR MKI67 KIAA1522 LINC00152 LYNX1 MKL2 KIAA1549L LINC00189 LYPD1 MKLN1 KIAA1671 LINC00326 LYST MLK4 KIAA1755 LINC00391 LZTS1 MMP16 KIAA2022 LINC00473 MAATS1 MMP17 KIF14 LINC00630 MAEL MMP25 KIF17 LINC00641 MAFF MOCOS KIF20B LINC00707 MALT1 MPC1 KIF21B LINC00941 MAML2 MPV17L KIFC3 LINC00961 MAMLD1 MPZL1 KIRREL2 LINC00963 MAN1A1 MRAP2 KITLG LINC00984 MAN1C1 MREG KLF5 LINC01021 MAOA MRPS17 KLHL29 LIPA MAOB MRPS31P5 KLHL32 LIPG MAP1B MSANTD4 KLHL42 LL0XNC01- MAP2K1 MSMO1 KMT2A 237H1.2 MAP2K3 MT3 KMT2D LL0XNC01- MAP3K1 MTHFD1L KPNA1 7P3.1 MAP3K14 MTX3 KRR1 LMBR1 MAP3K6 MUC20 KRT17 LMNA MAP3K7CL MYADM KRT7 LMTK3 MAP3K9 MYBPC2 KRT80 LNX1 MAP6D1 MYD88 L1CAM LONRF2 MAPK11 MYH9 LAMA2 LONRF3 MAPKAPK3 MYL12A

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MYLK NOTUM PARVB PIEZO1 MYLK4 NPAS1 PCDH1 PIK3CD MYO16 NPAS2 PCDH10 PIM2 MYO1E NPR1 PCDH12 PIPOX MYO5A NPR2 PCDH19 PIR MYO5B NPTX1 PCDH7 PITPNM2 MYO7A NQO1 PCDH9 PITPNM3 MYOF NQO2 PCDHGA6 PKDCC MYPN NR4A3 PCDHGA9 PLA2G3 MYRF NRCAM PCDHGB1 PLAT N4BP1 NRF1 PCDHGB4 PLAU N4BP3 NRGN PCDHGC3 PLBD1 NAA15 NRIP3 PCDHGC4 PLCB1 NAA25 NRP2 PCDHGC5 PLCD3 NACC2 NRROS PCNX PLCE1 NAP1L3 NSDHL PCNXL2 PLCXD2 NAV1 NSFP1 PCYT2 PLD1 NAV2 NSUN7 PDCL3P5 PLEKHG1 NBEAL1 NUDT16L1 PDE2A PLEKHG2 NBEAL2 NUFIP2 PDE3A PLEKHG5 NCEH1 NUMBL PDE4A PLEKHH2 NCOA7 NUTM2D PDE8B PLEKHS1 NCR3LG1 NXPE3 PDE9A PLK3 NDRG1 NXPH3 PDGFA PLOD2 NEB NXPH4 PDGFB PLXND1 NEDD4 OBSCN PDGFRA PMAIP1 NEDD9 OCIAD2 PDK1 PMM2 NEK3 ODF2 PDLIM3 PMP22 NEK6 OGDHL PDLIM4 PNMA2 NES OGFRL1 PDLIM7 PODNL1 NEURL OLFM2 PDP1 POLQ NFAT5 ONECUT2 PDZD4 POLR3G NFATC1 OPN1SW PDZD7 POM121B NFATC2 OSBP2 PEG10 POMK NFIL3 OSBPL3 PER1 PPAP2C NGEF OSGIN1 PER2 PPARGC1B NGFR OSMR PFKFB3 PPFIA4 NHLRC2 OTUD4 PFKFB4 PPL NID1 OVGP1 PFKP PPM1E NID2 OXCT2 PFN1P7 PPM1J NIPA1 OXCT2P1 PGAM1P7 PPME1 NIPAL2 OXTR PGM2L1 PPP1R14C NKAIN3 P2RX5 PHEX PPP1R15A NKD2 P4HA2 PHLDA1 PPP1R3B NKPD1 PALLD PHLDA2 PPP1R3G NKTR PALM2 PHLDA3 PPP2R3A NLGN3 PALM2-AKAP2 PHLDB1 PREX1 NLGN4Y PALM3 PHLPP2 PRIMA1 NMNAT2 PANK3 PHTF2 PRKAA2 NOS2 PANX2 PHYHIP PRKAR1B

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PRKCD RAPH1 RP11-1277A3.2 RP1-151F17.2 PRKDC RARG RP11-12J10.3 RP11-536C5.7 PRKXP1 RASAL1 RP11-134G8.8 RP11-551L14.1 PROS1 RASIP1 RP11-149I9.2 RP11-554I8.2 PRPS2 RASL12 RP11-158M2.4 RP11-571M6.8 PRR18 RASSF5 RP11-15J10.1 RP11-572C15.6 PRR24 RASSF8 RP11-175P13.3 RP11-61A14.2 PRR5 RASSF8-AS1 RP11-192H23.4 RP11-644F5.10 PRRC2C RBM15 RP11-20I23.8 RP11-660L16.2 PRRX2 RBM20 RP11-219G17.4 RP11-706J10.3 PRSS23 RBM3 RP1-122K4.2 RP11-711M9.1 PRUNE2 RBM33 RP11-235E17.6 RP11-713M15.2 PRX RBM47 RP11-23P13.6 RP11-71N10.1 PSMD12 RCOR1 RP11-23P13.7 RP11-732M18.3 PSME4 RDH10 RP11-277P12.20 RP11-75C10.7 PSORS1C1 RDH5 RP11-284F21.10 RP11-766F14.2 PSTPIP2 REEP6 RP11-284F21.9 RP11-77K12.4 PTCD2 REL RP11-286N22.8 RP11-82L18.4 PTCHD1 RELT RP11-292B8.1 RP11-849H4.4 PTCHD4 RFFL RP11-2E17.1 RP11-867G23.8 PTER RGS14 RP11-304L19.1 RP11-88H9.2 PTGIS RGS17 RP11-318M2.2 RP11-894P9.1 PTHLH RGS20 RP11-326C3.2 RP11-93L9.1 PTK2B RGS6 RP11-329B9.4 RP1-249H1.4 PTP4A3 RHBDF1 RP11-338I21.1 RP13-608F4.5 PTPDC1 RHBDF2 RP11-342M1.3 RP1-59D14.5 PTPN14 RHBDL1 RP11-358D14.2 RP1-74M1.3 PTPRE RHOC RP11-367G6.3 RP1L1 PTPRG RHOJ RP11-37B2.1 RP3-402G11.25 PTPRH RHOQP2 RP11-386G11.5 RP3-428L16.2 PTPRN RIC3 RP11-390F4.6 RP3-510D11.2 PTPRO RIMBP2 RP11-390P2.4 RP4-607J23.2 PTPRU RIMS2 RP11-395G23.3 RP4-639F20.1 PTPRZ1 RIN1 RP11-395L14.17 RP4-724E16.2 PTRF RINL RP11-395P17.3 RP4-782G3.1 PVR RIPPLY3 RP11-399D6.2 RP5-1024G6.8 PVRL1 RN7SKP275 RP11-415J8.3 RP5-1142A6.9 PXN RNF150 RP11-443P15.2 RP5-884M6.1 RAB20 RNF180 RP11-447L10.1 RPAP3 RAB23 RNF19A RP11-452F19.3 RPE65 RAB26 RNF207 RP11-461A8.4 RPL23AP4 RAB27B RNMT RP11-469M7.1 RPL23AP53 RAB39A ROCK2 RP11-46D6.1 RPP14 RAB3A RP1-102K2.8 RP11-496I9.1 RPRML RAB43 RP11-1008C21.2 RP11-497H17.1 RPS11P5 RAB43P1 RP11-100E13.1 RP11-500C11.3 RPS6KA1 RALB RP11-108K14.4 RP11-506K6.4 RPS6KA3 RALGAPB RP11-111G23.1 RP11-512M8.3 RPS6KB1 RAPGEF3 RP11-124N14.3 RP11-517B11.7 RRAD RAPGEF4 RP11-1277A3.1 RP1-151F17.1 RRBP1

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RRM2B SGTB SLC41A2 SPRED2 RTN4RL1 SH2B3 SLC45A3 SPRED3 RTTN SH2D3C SLC4A11 SPRY1 RUNX1 SH2D5 SLC4A3 SPRY2 RUNX2 SH3BP1 SLC4A7 SPRY4 RUNX3 SH3BP5 SLC5A3 SPSB1 RYR3 SH3D21 SLC6A6 SPTSSB S100A10 SH3RF1 SLC7A1 SRCRB4D S100A11 SH3RF3 SLC7A11 SRPX2 S100A13 SH3RF3-AS1 SLC7A5 SRRM5 S100A16 SH3TC1 SLC9A5 SRSF12 S100A2 SHANK2 SLC9A7 SRXN1 S100A3 SHB SLCO4A1 SSC5D S100A4 SHC1 SLFN12L SSH1 S100A6 SHC3 SLFNL1 SSR1 S100B SHC4 SLIT1 SSTR3 S1PR2 SHISA3 SMAP2 ST3GAL1 S1PR5 SHISA7 SMC5 ST6GAL1 SAMD9L SHISA8 SMCO4 ST6GALNAC4 SAT1 SHROOM2 SMOX ST8SIA3 SBF2 SHROOM3 SMTNL1 STAC2 SCARF2 SIPA1 SNAI1 STARD8 SCFD2 SIPA1L1 SNCB STARD9 SCG2 SIPA1L2 SNED1 STC2 SCML1 SKA1 SNORA77 STEAP3 SDC3 SLC13A5 SNRPA STK10 SDC4 SLC16A14 SNRPA1 STK17A SDCBP2 SLC16A3 SNTA1 STK32B SDK2 SLC16A4 SNTB1 STK4 SEC24A SLC18A1 SNX10 STK40 SEC24D SLC19A3 SOCS2 STOM SELM SLC1A1 SOCS2-AS1 SUDS3P1 SEMA3A SLC22A18 SOCS3 SVIL SEMA4A SLC22A4 SOCS4 SYBU SEMA4G SLC25A15 SOCS6 SYDE2 SEMA7A SLC25A30 SORL1 SYN3 SENP8 SLC25A37 SOX15 SYNE3 Sep9 SLC26A6 SOX18 SYNGR1 SERPINB1 SLC27A1 SOX7 SYNGR3 SERPINB8 SLC29A4 SP140L SYNJ2 SERPINE1 SLC2A14 SPAG1 SYNM SERPINI1 SLC2A3 SPAG4 SYNPO SERTAD1 SLC2A4RG SPATA2L SYNPR SEZ6 SLC30A1 SPATA6 SYT12 SEZ6L SLC30A3 SPEG SYT7 SFXN3 SLC35A3 SPHK1 SYTL5 SGK223 SLC35D3 SPICE1 TACC1 SGK494 SLC35E4 SPOCD1 TACC2 SGMS2 SLC38A6 SPOCK1 TAGLN SGPP2 SLC39A4 SPRED1 TANC2

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TATDN2P2 TNFRSF12A TUBA8 WTIP TBC1D8B TNFRSF18 TUBB3 WWC2 TBX21 TNFRSF1A TUBB4A WWTR1 TCF19 TNFRSF1B TUBB6 XIAP TCF7 TNFRSF4 TUBE1 XIRP1 TDG TNFRSF8 TWF1P1 XXbac- TEAD1 TNFSF13B U47924.30 B461K10.4 TEAD3 TNIK UBASH3B XXbac- TERT TNR UBE2J1 B562F10.11 TFAP2E TNS1 UBE2QL1 XYLB TFB1M TNS3 UBE3C ZBED6 TFEB TOMM6 UBR3 ZBP1 TFPI2 TPBGL UBTD1 ZBTB38 TFR2 TPH1 UCN2 ZC3HAV1 TFRC TPM4 UHMK1 ZC3HAV1L TGFBR3L TPPP ULBP3 ZCCHC12 TGM2 TPST2 ULK4 ZDHHC23 TH TRAC UNC13A ZFHX3 THBS1 TRAF1 UNC5A ZFP36 THSD1 TRAF3IP2 UNC80 ZFPM1 THY1 TRAF6 UPP1 ZFYVE28 TIAM2 TRAM2 VAC14-AS1 ZIC4 TIMP1 TREH VARS ZMAT3 TIMP3 TRIB2 VASH2 ZNF141 TLCD2 TRIB3 VAV3 ZNF154 TLN2 TRIM17 VCAN ZNF221 TLR4 TRIM44 VCL ZNF26 TM4SF1 TRIM7 VDR ZNF281 TMBIM1 TRIM71 VEGFA ZNF317 TMC6 TRIM9 VGF ZNF365 TMCC3 TRIO VGLL2 ZNF382 TMEM132E TRNP1 VIPR1 ZNF398 TMEM154 TRPM3 VMO1 ZNF460 TMEM158 TRPM4 VPS13A ZNF467 TMEM170B TRPM8 VRK2 ZNF469 TMEM173 TSN VSTM2L ZNF483 TMEM178A TSPAN12 VWA1 ZNF530 TMEM189 TSPAN17 VWA5B2 ZNF583 TMEM217 TSPAN9 WARS ZNF597 TMEM231 TSPY26P WASH5P ZNF600 TMEM249 TTC13 WDFY2 ZNF625 TMEM52 TTC24 WDR1 ZNF660 TMEM53 TTC26 WDR27 ZNF699 TMEM67 TTC39B WDR43 ZNF778 TMEM87B TTC9 WHAMMP2 ZNF800 TMPPE TTLL10 WI2-2998D17.2 ZNF805 TMTC1 TTLL11 WIPF1 ZNF827 TNC TTYH3 WNT7B ZSCAN5A TNFRSF10B TUBA4A WT1 ZYX

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Table S6: Down-regulated genes identified by RNA-Seq after either 4-hour or 24-hour EGF treatment (FDR ≤ 0.05, log2 (fold change) ≤-0.8) AASDHPPT AC093627.9 AMPH ATCAY ABCA1 AC093642.5 ANGEL1 ATF6B ABCC6 AC096772.6 ANGPTL1 ATG9B ABCD2 AC104698.1 ANGPTL6 ATOH8 ABHD17AP6 AC108479.2 ANKAR ATP1A2 ABHD8 AC113189.5 ANKDD1B ATP2B3 ABLIM2 AC114730.3 ANKFN1 ATP6AP1L ABTB1 AC116366.6 ANKRA2 ATP6V0E2-AS1 AC002398.9 AC117395.1 ANKRD12 ATXN7L1 AC004453.8 AC135048.13 ANKRD24 B3GALT2 AC004540.4 AC139100.2 ANKRD65 BAG1 AC004840.9 AC140481.1 ANO9 BAZ2B AC005003.1 AC142528.1 ANXA2R BBC3 AC005609.1 AC144530.1 ANXA9 BBOX1 AC005943.5 ACBD4 AP000473.5 BBS2 AC007092.1 ACRC AP000473.8 BBS9 AC007292.6 ACSS1 AP001258.4 BCAN AC009501.4 ACTA2 AP5Z1 BCL2L11 AC009506.1 ACTC1 APC2 BCL7A AC009948.5 ACVR2A APCDD1 BCMO1 AC009950.2 ACVR2B-AS1 APOBEC3D BCOR AC010335.1 ACYP2 APOBEC3F BDH1 AC010536.1 ADAM8 APOBEC3G BEST3 AC010642.1 ADAMTS13 APOL2 BEX1 AC016700.5 ADAMTS6 APOL3 BEX4 AC016747.3 ADAMTSL1 APOL6 BHLHE22 AC017076.5 ADCK3 ARFGAP1 BIRC2 AC017099.3 ADCYAP1R1 ARHGAP24 BMF AC018730.1 ADI1 ARHGAP27 BMP7 AC018730.3 ADPRHL1 ARHGAP9 BMPER AC018737.1 AF127936.7 ARHGEF10L BMPR1B AC018755.1 AGAP4 ARHGEF19 BMS1P10 AC018755.16 AKAP1 ARHGEF28 BOLA1 AC021188.4 AKAP3 ARHGEF9 BRD3 AC022007.5 AKNAD1 ARID3A BRD8 AC022182.3 AL161915.1 ARIH2OS BRWD1-IT2 AC025171.1 AL513327.1 ARMC12 BTBD17 AC034220.3 AL591479.1 ARMCX1 BTG1 AC040173.1 ALDH4A1 ARMCX6 BTG2 AC073283.4 ALDH6A1 ARSD BTN3A1 AC074212.5 ALDH7A1 ART3 BTN3A2 AC074212.6 ALPK3 ARTN BTN3A3 AC074289.1 AMACR ARVCF BX936347.1 AC083799.1 AMDHD2 ARX BZRAP1 AC087393.1 AMH ASB16 C10orf25 AC090945.1 AMIGO1 ASCL1 C10orf32 AC091729.9 AMOTL2 ASXL3 C11orf68

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C11orf71 CASC14 CICP13 CTB-36H16.2 C11orf96 CASC15 CICP16 CTB-58E17.5 C12orf23 CASZ1 CIR1 CTC-359D24.3 C12orf55 CBFA2T2 CITED2 CTC-444N24.8 C14orf159 CBLN3 CITF22-92A6.1 CTC-467M3.3 C14orf23 CBX4 CKB CTD-2031P19.4 C14orf93 CBX7 CKS2 CTD-2037K23.2 C15orf38-AP3S2 CCDC101 CLCN4 CTD-2186M15.3 C16orf71 CCDC121 CLCN7 CTD-2192J16.20 C16orf86 CCDC146 CLDN15 CTD-2256P15.2 C17orf103 CCDC151 CLDN5 CTD-2260A17.2 C17orf82 CCDC154 CLEC18B CTD-2287O16.5 C19orf38 CCDC157 CLEC4F CTD-2349P21.9 C19orf57 CCDC162P CLHC1 CTD-2510F5.4 C19orf66 CCDC163P CLIP3 CTD-2514K5.2 C1orf173 CCDC173 CLU CTD-2521M24.4 C1orf228 CCDC177 CMC1 CTD-2521M24.5 C1orf56 CCDC28A CMPK2 CTD-2521M24.6 C1orf95 CCL5 CNGA2 CTD-2521M24.9 C1QTNF1 CCNB2 CNGA3 CTD-2574D22.2 C1QTNF5 CCNB3 CNKSR1 CTD-2589H19.6 C20orf112 CCNG2 CNNM2 CTD-2619J13.19 C21orf58 CCT6P3 CNTFR CTD-2630F21.1 C21orf67 CD200 COL1A2 CTD-3065J16.9 C3 CD247 COL5A2 CTD-3088G3.8 C3orf18 CD24P4 COL7A1 CTD-3199J23.4 C5orf54 CD5 COL9A1 CTD-3203P2.1 C5orf55 CDC20P1 COLQ CTGLF10P C5orf56 CDC25B CPA5 CTSF C6orf3 CDC25C CPLX2 CXCL2 C7orf61 CDC42EP4 CRB1 CXorf24 C9orf156 CDC42SE2 CRB2 CXXC11 C9orf172 CDK19 CREB3L4 CXXC4 C9orf3 CDK5R2 CRELD1 CYB5R1 C9orf47 CDKN1C CRHR1-IT1 DAG1 C9orf9 CDKN2C CRIPT DAPK2 CA14 CDO1 CRISPLD2 DAZAP2 CA8 CDON CROCC DBP CABLES1 CEBPA-AS1 CRYM DCP2 CABP7 CECR6 CSAG1 DCT CACNA1G CEL CSAG2 DCTN4 CACNG4 CELF3 CSAG3 DCX CADM2 CENPF CSPG4P10 DDIT4 CADM3 CENPQ CSPG4P9 DDX11L2 CAHM CEP68 CSPG5 DDX58 CALCOCO1 CH25H CTA-29F11.1 DDX60L CAMSAP3 CHAC1 CTAGE5 DEDD2 CAPN3 CHKB-CPT1B CTB-175P5.4 DEPTOR CAPN6 CHMP1B CTB-31O20.2 DGAT2 CAPS CHRNA1 CTB-33G10.1 DGCR6

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DGKB ESAM FIBIN GPCPD1 DHRS13 ETV7 FIZ1 GPD1L DHRS2 EXOC3L1 FLJ27365 GPER1 DHRS3 EXOG FLVCR2 GPM6A DHX58 EXTL2 FN1 GPR173 DICER1-AS1 EXTL3 FOXA3 GPR179 DLL1 EZH1 FOXD3 GPR35 DLL3 FAM110B FOXD4 GPR37L1 DLX1 FAM111A FOXD4L1 GPR62 DLX2 FAM117A FOXF1 GPR88 DMAP1 FAM122C FOXG1 GPRASP1 DMRTA2 FAM127A FOXJ1 GPRASP2 DNAJB4 FAM134A FOXN3-AS1 GPSM2 DNAJC12 FAM13C FOXO3 GRAMD3 DNAJC28 FAM161B FOXO4 GRASP DNAJC30 FAM171A2 FOXO6 GRIA4 DNASE1L2 FAM173B FOXP2 GRINA DNER FAM189B FRAT1 GRN DOK3 FAM213B FRAT2 GS1-184P14.2 DRD4 FAM21A FRZB GS1-257G1.1 DTX3L FAM21D FUCA1 GS1-393G12.12 DUSP10 FAM222A FUT2 GTF2IRD2B DUSP26 FAM27E3 FUZ H1F0 DYRK1B FAM27E4 FZD2 H1FX-AS1 DYX1C1 FAM43B GADD45G H2AFJ E2F2 FAM53B GATA2 HAS3 EAPP FAM63A GATM HBP1 EBF3 FAM65C GATS HCN3 ECE2 FAM66B GBGT1 HDHD3 ECSIT FAM69A GBP1P1 HELT EDNRB FAM69C GBP4 HEPACAM EEF1A1P11 FAM83H GCA HERC2P2 EFNA1 FAM89B GCLC HERC2P3 EHHADH FANCE GDPD1 HERC5 ELAVL4 FAXDC2 GDPD2 HERC6 ELF1 FBLL1 GEMIN8 HES4 ELF3 FBXL19-AS1 GGT1 HES5 EME1 FBXL20 GIMAP2 HES6 EMX2 FBXL8 GJC2 HES7 ENC1 FBXO10 GKAP1 HEY1 ENTHD2 FBXO2 GLCCI1 HEYL ENTPD3-AS1 FBXO25 GLRB HGFAC EPAS1 FBXO32 GLTPD2 HHIPL1 EPB41L4A-AS1 FBXO39 GLYCTK HILPDA EPHB1 FBXO6 GLYCTK-AS1 HILS1 EPOR FCGBP GNAL HIRIP3 EPS8L1 FCGRT GNAO1 HIST1H1C EPSTI1 FER GNG13 HIST1H2AC ERBB2 FGD3 GOLPH3L HIST1H2AG ERMAP FGFR3 GPC4 HIST1H2BD

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HIST1H4C IFT20 KLF4 LUC7L2 HIST2H2AA3 IGDCC3 KLHDC9 LYPD6 HIST2H2AA4 IGFBP6 KLHL21 LYRM7 HIST2H2BC IGSF11 KLHL24 MACROD2 HIST2H2BD IGSF9 KLHL32 MADCAM1 HIST2H2BE IL4I1 KLHL35 MAGIX HIST2H3A ILF3-AS1 KLHL7 MALAT1 HIST2H3C ING4 KMT2E-AS1 MANBA HIST2H4A INPP5D KRBOX1 MAP2K5 HIST2H4B INPP5K LAMA3 MAP2K6 HIST3H2A INSM2 LAMP5 MAP3K8 HLA-E IQCH-AS1 LANCL2 MAP4K1 HMGCL IRF7 LAT MAP6 HMGN2P5 IRX1 LDB1 MAPK8IP1 HMMR IRX6 LETMD1 MAPK8IP2 HNRNPCP1 ISG15 LFNG Mar8 HOGA1 ISG20 LGALS9 MARCKS HOXD4 ITGB5 LGR5 MAST1 HRASLS2 JAKMIP2 LIAS MAT2B HRH3 JAZF1 LIMCH1 MB21D2 HRK JMY LIMS2 MBOAT1 HRSP12 JOSD2 LIN52 MCF2L-AS1 HS1BP3 JPH3 LINC00174 MDFI hsa-mir-8072 JUP LINC00461 MED30 HSCB KANK4 LINC00472 MEF2BNB- HSD11B2 KAT6B LINC00478 MEF2B HSD17B11 KATNAL2 LINC00537 MEGF10 HSD17B14 KB-1460A1.5 LINC00634 MEIS1 HSD17B6 KBTBD7 LINC00638 MESP1 HSFX2 KCNIP3 LINC00639 MEST HTR3E KCNJ10 LINC00680 METTL12 HTRA2 KCNJ9 LINC00886 METTL25 HTRA3 KCNK3 LINC00896 METTL7A HUNK KCNN1 LINC00899 MFAP4 ICOSLG KCNN2 LINC00925 MFNG ID2 KCNN3 LINC01003 MIEF2 ID3 KCTD12 LIPT2 MIMT1 IFI35 KCTD21 LIX1L MIR17HG IFI44 KCTD21-AS1 LL22NC03-2H8.5 MIR3615 IFI6 KDM8 LMO1 MIR3648 IFIH1 KIAA1614 LMO4 MIR3687 IFIT1 KIAA1984-AS1 LMTK3 MIS18BP1 IFIT2 KIF19 LOH12CR2 MITF IFIT3 KIF20A LRRC17 MKRN3 IFIT5 KIF5A LRRC27 MKS1 IFITM1 KLC4 LRRC37A17P MLLT3 IFNAR1 KLF11 LRRN1 MLLT4-AS1 IFNB1 KLF13 LRRN2 MMP11 IFNL1 KLF15 LRRTM3 MMP15 IFT172 KLF2 LTB4R2 MN1

120

MND1 NEU4 OPTN PIK3AP1 MNT NEURL2 OR7E38P PIK3C2B MOB2 NEURL3 OR7E7P PIK3IP1 MPPED2 NFIA ORAOV1 PINK1 MPRIPP1 NFIB OSER1-AS1 PKNOX2 MPST NFKBIA OSR2 PLA2G4C MRPL49 NFKBIZ OTOF PLA2G6 MRPS35 NHLH1 OTP PLCH1 MSH6 NKAIN4 OTUB1 PLCL2 MST1 NKD1 OTUD1 PLD5 MST1L NLRC5 OTX1 PLEKHA4 MST1P2 NMB OTX2 PLEKHA7 MT1E NMI P2RX7 PLEKHF2 MT1F NMNAT1 P2RY2 PLIN4 MT1M NMNAT3 PAIP2 PLIN5 MT2A NOD2 PARD6A PLK1S1 MTND1P23 NOP14-AS1 PARP10 PLK2 MTND4P12 NOVA2 PARP12 PLP1 MTSS1 NOXO1 PATL2 PLSCR1 MT-TD NPC2 PAX6 PLVAP MT-TI NPTX1 PBK PLXNA2 MT-TT NR1D2 PBX3 PLXNC1 MT-TV NR2F1 PBXIP1 PMEPA1 MTUS1 NR4A2 PCBD2 PMF1-BGLAP MUC20 NRARP PCBP4 PML MUM1 NRG2 PCCA PNCK MUT NRSN1 PCDH18 PNMAL2 MUTYH NTN3 PCDH8 PNPLA7 MX1 NTRK2 PCDHA13 PNRC1 MX2 NTSR1 PCDHA3 POC1A MXD3 NUAK2 PCMTD1 POLE4 MXD4 NUF2 PCOLCE POLR3GL MXI1 NUMA1 PCSK2 POMZP3 MYCL NUPR1 PCSK4 POU2F1 MYD88 NUTM2A PDCD4 POU3F3 MYO5BP2 NUTM2E PDCD4-AS1 POU3F4 MYOG NXF1 PDE3A PPAPDC2 MYT1 NYAP1 PDGFRL PPFIBP2 N4BP2L1 OAS1 PDK2 PPIC NADK2 OAS2 PDPK1 PPM1H NAIP OASL PDZD2 PPP1R3E NAPA ODF3B PDZRN3 PPP1R9A NBR1 OGFR PEX11B PROCA1 NCALD OIP5 PGBD3 PRODH NCOA5 OLIG1 PGM5 PRR19 NDC80 OLIG2 PHC1P1 PRRT2 NDP OMA1 PIF1 PRUNE NEAT1 OMG PIGB PSMB10 NEDD4L OPHN1 PIGV PSMB9 NELL1 OPRL1 PIH1D2 PTCH1

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PTCHD2 RNF112 RP1-130H16.16 RP11-54O7.17 PTGDS RNF122 RP11-311C24.1 RP11-552F3.12 PTGES RNF146 RP11-313P13.3 RP11-572O17.1 PTGES3L- RNF19B RP11-317P15.4 RP11-57A19.2 AARSD1 RNF208 RP11-317P15.5 RP11-5C23.1 PTPN3 RP11-1017G21.5 RP11-337C18.9 RP11-600F24.7 PXDNL RP11-101E13.5 RP11-339F13.2 RP11-611D20.2 QRICH2 RP11-102N12.3 RP11-340F14.5 RP11-61J19.4 RAB11B-AS1 RP11-1055B8.3 RP11-347C12.10 RP11-627K11.1 RAB33A RP11-1055B8.4 RP11-351D16.3 RP11-634H22.1 RAB3C RP11-10K16.1 RP11-351J23.1 RP11-635N19.1 RAB3IL1 RP11-111F5.4 RP11-351J23.2 RP11-644F5.11 RABEP2 RP11-118F19.1 RP11-353N14.2 RP11-66N24.4 RABGAP1L RP11-119F7.5 RP11-356J5.12 RP11-686D22.8 RAD51AP1 RP11-120J1.1 RP11-363E6.3 RP11-690G19.3 RALGDS RP11-120K24.3 RP11-373L24.1 RP11-693J15.5 RANBP3L RP11-1246C19.1 RP11-378A13.1 RP11-706J10.2 RARRES3 RP11-1275H24.3 RP11-380L11.4 RP11-707O23.5 RASD1 RP11-1299A16.3 RP11-390E23.6 RP11-708J19.1 RASD2 RP11-134L10.1 RP11-395A13.2 RP11-715J22.2 RASGRP3 RP11-137L10.6 RP11-398C13.6 RP11-715J22.6 RASL11B RP11-158M2.3 RP11-401P9.4 RP11-71H17.9 RASSF10 RP11-158M2.4 RP11-407N17.6 RP11-723O4.9 RASSF4 RP11-15H20.5 RP11-412D9.4 RP11-757G1.6 RBM43 RP11-15H20.6 RP11-420L9.5 RP11-75C9.1 RCBTB2 RP11-161M6.2 RP11-430C7.5 RP11-767N6.7 RCOR2 RP11-163N6.2 RP11-435O5.5 RP11-774O3.3 RDM1 RP11-166D19.1 RP11-436K8.1 RP11-793H13.10 RECQL5 RP11-169K16.9 RP11-439E19.10 RP11-796E2.4 RELB RP11-16N11.2 RP11-439E19.3 RP11-817O13.8 RENBP RP11-182L21.6 RP11-456K23.1 RP11-83A24.2 REP15 RP11-196G18.22 RP11-458F8.4 RP11-83N9.5 RFTN2 RP11-196G18.23 RP11-458N5.1 RP11-849F2.8 RFX4 RP11-206L10.9 RP11-469H8.6 RP11-849I19.1 RGAG1 RP11-211N8.2 RP11-46C24.7 RP11-85O21.2 RGAG4 RP11-211N8.3 RP11-480I12.5 RP11-872J21.3 RGMA RP11-215G15.5 RP11-483C6.1 RP11-90L20.2 RGR RP11-226L15.5 RP11-486G15.2 RP1-191J18.66 RGS16 RP11-248G5.8 RP11-488C13.5 RP11-91J19.4 RGS3 RP11-252A24.7 RP11-500G22.2 RP11-923I11.6 RHBDL3 RP11-254F7.2 RP11-504P24.8 RP11-923I11.7 RHOQ RP11-255C15.4 RP11-509E16.1 RP11-93B14.5 RIBC1 RP11-258C19.7 RP11-50E11.3 RP1-193H18.2 RIMBP3C RP11-271K21.11 RP11-512F24.1 RP11-973H7.3 RMI2 RP11-288L9.4 RP11-512H23.2 RP11-977G19.5 RN7SK RP11-295D4.1 RP11-512M8.3 RP11-97C16.1 RNASEK- RP11-2E11.9 RP11-521B24.3 RP11-98D18.3 C17orf49 RP11-304L19.11 RP11-529K1.2 RP11-98D18.9 RND1 RP11-308D16.4 RP11-545I5.3 RP11-999E24.3 RND3 RP11-309L24.9 RP11-54O7.1 RP1-212P9.2

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RP1-212P9.3 RXRA SMAD9 SUV420H2 RP1-228H13.5 RXRB SMARCA5-AS1 SYF2 RP1-241P17.4 RXRG SMIM14 SYNE1 RP1-266L20.2 SAMD13 SMOC1 SYT3 RP1-27O5.3 SAMD9 SMTNL1 TAPBPL RP1-283E3.4 SAMD9L SNAP23 TAPT1-AS1 RP1-302G2.5 SAMHD1 SNCAIP TARS2 RP13-516M14.1 SBSPON SNHG5 TAS1R3 RP1-39G22.7 SCARNA12 SNHG7 TBC1D17 RP3-326L13.3 SCHIP1 SNORA76 TBC1D2 RP3-388N13.3 SCN3A SNORD104 TBC1D5 RP3-395M20.12 SCRT2 SNORD3A TBX1 RP3-428L16.2 SDAD1P1 SORBS3 TBX6 RP3-508I15.21 SDCCAG8 SOX15 TCF7L1 RP3-522D1.1 SEC22A SOX4 TCF7L2 RP4-545K15.3 SEC61A1 SOX8 TCP11L2 RP4-657D16.3 SEMA4B SP100 TCTA RP4-717I23.3 SEMA6C SP110 TEKT2 RP4-740C4.6 Sep1 SP5 TEN1 RP4-758J24.5 SEPP1 SP8 TESK2 RP4-792G4.2 SFR1 SP9 TEX264 RP4-798P15.3 SFRP2 SPAG9 TF RP4-813F11.4 SH3BP5L SPARCL1 TFAP2A-AS1 RP5-1065J22.8 SH3GL1P3 SPDYE2B TFAP4 RP5-1068E13.7 SHD SPECC1L TGFB2 RP5-1074L1.4 SHF SPHK2 THAP2 RP5-1092A3.4 SHOX2 SPIB THAP7-AS1 RP5-1142A6.2 SIM2 SPOCK2 THAP8 RP5-1180C10.2 SIX2 SPSB3 THEMIS2 RP5-837J1.2 SIX3 SPSB4 THRA RP5-894A10.2 SIX5 SPTBN5 THTPA RP5-943J3.2 SKOR1 SRGAP3 TIGD2 RP5-991G20.4 SLC15A3 SRRM3 TIGD3 RP6-109B7.3 SLC24A3 SRSF6 TLE2 RPL13AP25 SLC24A5 SSBP3 TLE3 RPL17-C18orf32 SLC25A42 ST18 TLE6 RPL24P2 SLC25A45 ST20-MTHFS TLL2 RPL32P29 SLC29A3 ST3GAL5 TLR3 RPP25L SLC2A12 ST3GAL6 TMCC1 RPPH1 SLC2A4 ST6GAL1 TMCC1-AS1 RPS10P3 SLC43A1 ST6GALNAC2 TMEFF1 RPSAP54 SLC47A2 ST7-AS1 TMEM102 RRAD SLC4A4 STARD10 TMEM106C RRAGC SLC5A3 STAT2 TMEM108 RSAD1 SLC6A12 STON1 TMEM143 RSAD2 SLC6A8 STOX1 TMEM161B-AS1 RSG1 SLC7A10 STOX2 TMEM187 RTN4RL1 SLC8A2 STX10 TMEM229B RTP4 SLC9A4 SULT1C4 TMEM249 RUFY4 SLX1B-SULT1A4 SUPT3H TMEM255A

123

TMEM33 ULK1 ZDHHC22 TMEM35 UNC13D ZFP14

TMEM42 UNC79 ZFP69B TMEM44-AS1 UNC93B1 ZFYVE1 TMEM62 UPF3B ZFYVE28

TMEM86A UPRT ZGLP1 TMSB4XP8 USP18 ZHX2 TNFAIP2 USP2 ZMYND15

TNFAIP3 USP20 ZNF184 TNFRSF13C USP2-AS1 ZNF235 TNFRSF14 USP41 ZNF239

TNFRSF6B USP6 ZNF253 TNFSF10 VAPB ZNF33B TNK2 VASN ZNF345

TNR VCAM1 ZNF358 TNRC18P3 VEPH1 ZNF385C TOB1-AS1 VIPAS39 ZNF396

TOLLIP-AS1 VMAC ZNF425 TOM1 VPS37D ZNF438 TOP2A VPS9D1 ZNF491

TOR4A VSTM4 ZNF518A TOX3 WASH6P ZNF524 TPP1 WDR25 ZNF527

TPPP3 WDR45 ZNF546 TRADD WDR49 ZNF572 TRANK1 WDR81 ZNF575

TREX1 WDSUB1 ZNF579 TRIL WHSC1 ZNF581 TRIM21 WIPI1 ZNF610

TRIM22 WNT10A ZNF688 TRIM34 WNT7A ZNF703 TRIM45 XAF1 ZNF737

TRIM68 XRRA1 ZNF747 TRIM74 XXbac- ZNF775 TRIT1 BPGBPG55C20.2 ZNF788

TSC22D3 YPEL1 ZNF8 TSNARE1 YPEL3 ZNF844 TSNAXIP1 YPEL5 ZRANB3

TTC34 YTHDF3 ZSCAN2 TTK Z97634.3 ZSCAN31 TTPA ZBED5-AS1

TUB ZBP1

U73166.2 ZBTB11-AS1 UAP1L1 ZBTB12

UBA7 ZBTB18

UBALD2 ZBTB49 UBE2H ZCCHC18

UBE2L6 ZCWPW1

UCN ZDHHC11 UCP3 ZDHHC12

124

Table S7: TAZ-binding peaks identified by TAZ ChIP-Seq (FDR≤ 0.05) Provided as separated files. Sheet 1: raw data from ChIP-sequencing Sheet 2: genes called in ChIP-sequencing

125

Table S8: TAZ binding motif prediction Provided as separated files (html format).

126

Table S9: TAZ-Up gene list

ABCA12 ATXN1 CLIP2 DOK6 ABCC6P1 AUTS2 CLIP4 DOT1L ABL2 AXL CLRN1 DPF3 ABLIM1 B4GALNT3 CMKLR1 DSCAM ACAD11 BACH2 CMTM7 DUSP3 ACER2 BATF3 CMTM8 DUSP4 ACHE BCL2 CNN3 DUSP5 ACO1 BDNF CNTNAP3 DUSP6 ACOX2 BIRC3 COBL DUSP9 ACSS3 BLZF1 COL14A1 DYNC2H1 ACTG1 BNC2 COL26A1 E2F7 ACTN2 BRINP2 COL4A3 EDA2R ADAMTS3 C12orf75 COL4A4 EEA1 ADAMTS9 C2orf80 COLGALT1 EFHC1 ADCY1 C4orf19 CORO1A EFHC2 AFF3 C6orf118 CORO2B EGF AGAP1 C8orf58 COTL1 EGFEM1P AGFG2 CABIN1 CPA2 EGFR AGO2 CACNB4 CPA4 EGFR-AS1 AKAP2 CAMK2D CPEB2 EGLN3 AKAP6 CASP7 CPNE4 EGR2 ALG10B CBLN1 CPNE5 EGR3 AMIGO2 CCDC102B CPNE8 EHD2 AMMECR1 CCDC113 CRABP2 EIF5A2 AMPD3 CCDC88A CSGALNACT1 ELF4 ANK2 CCR1 CSNK1G1 ELK3 ANKHD1 CCT6B CSPG4 EMILIN2 ANKRD20A1 CD274 CTGF EML2 ANKRD20A2 CD82 CUBN ENTPD7 ANKRD20A3 CDC42 CXCR4 EPB41L2 ANKRD36C CDC42EP2 CYB561 EPHA2 ANXA2 CDC42EP3 CYGB ERBB3 AP3S2 CDH6 CYP1B1 ERC1 APLN CDKL5 CYP2E1 ETS1 APOL6 CDKN1A CYR61 ETS2 ARC CDKN2B DAGLA ETV5 ARHGAP18 CELSR1 DCBLD2 EVA1C ARHGAP32 CH25H DCLK1 EVC ARHGEF4 CHD9 DDHD1 F12 ARID3A CHRNA3 DGKG F3 ARSJ CHST11 DGKH FABP5 ASCC3 CHST2 DIAPH2 FABP7 ASMTL CHST7 DIRAS2 FAM102B ASPHD2 CHSY1 DLC1 FAM157A ATP2B2 CILP2 DMXL2 FAM157C ATP6V0A1 CLCN5 DNMBP FAM184B ATR CLIP1 DOCK6 FAM196A

127

FAM198A GPR158 KCNN2 MAP1B FAM49A GPR180 KCNQ5 MAP3K1 FAM72A GRIA2 KCTD9 MAP6D1 FAM72B GRIA3 KIAA0040 MAPRE2 FAM83F GRIK4 KIAA0754 MCC FAM83G GRIN2B KIAA1211L MCHR1 FAM84A GSN KIAA1549L ME1 FARP2 HAS2 KIAA1671 MED12L FAS HCFC2 KIF14 MIR210HG FAT1 HIF1A KIF20B MMP16 FAT3 HIPK3 KIFC3 MPZL1 FBN2 HIVEP3 KITLG MRPS31P5 FEM1C HK2 KLF5 MYBPC2 FERMT2 HMGCR KLHL29 MYH9 FGF1 HMGCS1 KLHL42 MYLK FGF2 HNF4G KRR1 MYLK4 FGFR4 HOMER1 KRT80 MYO16 FILIP1L HOMER2 LAMA2 N4BP1 FKBP11 HRASLS LARP1B N4BP3 FLNA HRH1 LATS2 NACC2 FMN1 HSD17B12 LBH NAP1L3 FMNL3 HSD17B7 LCA5 NAV2 FRAS1 HSPA4L LCTL NCEH1 FREM1 HSPA7 LDLR NCOA7 FRMD4B HSPB3 LEMD1 NCR3LG1 FRMD8 IDH3A LGI1 NEB FRYL IDS LGR6 NEDD4 FST IGSF5 LHFPL2 NEDD9 FZD5 IL1RAP LINC00326 NFATC1 G6PD ILDR2 LINC00630 NFIL3 GAL INPP4B LINC00641 NHLRC2 GAP43 INPP5F LINC00707 NID1 GBE1 INSIG1 LINC00941 NID2 GBP2 IPCEF1 LINC00963 NIPAL2 GCH1 IPPK LIPG NKAIN3 GCLM IQGAP1 LMBR1 NLGN4Y GDNF IQGAP2 LMNA NPAS1 GFAP IRF1 LNX1 NPTX1 GFPT2 ISPD LOXL2 NR4A3 GJB1 ITGA2 LOXL4 NRCAM GK5 ITGA6 LPL NRGN GLIS2 ITGB8 LPP NRP2 GLIS3 JAK2 LRP8 NSFP1 GLS JPH1 LTBP1 NSUN7 GOLIM4 JUN LUCAT1 NUMBL GPD2 KBTBD8 MAML2 NXPE3 GPR12 KCND3 MAMLD1 OBSCN GPR135 KCNF1 MAN1A1 OCIAD2 GPR139 KCNJ2 MAN1C1 ODF2 GPR153 KCNK13 MAOA OGFRL1

128

OLFM2 PRPS2 SBF2 SOX18 OSBP2 PRR18 SCFD2 SOX7 OSBPL3 PRSS23 SCG2 SP140L OSMR PRUNE2 SCML1 SPATA6 OTUD4 PRX SDCBP2 SPHK1 PALM2 PSME4 SEC24D SPICE1 PANK3 PSTPIP2 SEMA3A SPOCK1 PANX2 PTCHD1 SENP8 SPRED2 PARVB PTCHD4 Sep9 SPRY1 PCDH10 PTHLH SERPINB8 SPRY2 PCDH19 PTK2B SERPINI1 SPSB1 PCDH7 PTPDC1 SFXN3 SRXN1 PCDHGC5 PTPN14 SGMS2 ST3GAL1 PDGFA PTPRG SH2B3 ST8SIA3 PDGFB PTPRO SH3BP5 STAC2 PDGFRA PTPRZ1 SH3D21 STARD8 PDK1 RAB39A SH3RF1 STK10 PDP1 RALB SH3RF3 STK17A PDZD4 RALGAPB SHANK2 STK32B PER2 RAPGEF4 SHC3 STOM PFKFB3 RAPH1 SHISA7 SYBU PGM2L1 RBM20 SHROOM2 SYDE2 PHEX RCOR1 SHROOM3 SYN3 PHLDA1 RDH10 SIPA1L1 SYNJ2 PHLDA3 RDH5 SIPA1L2 SYNM PHLDB1 REEP6 SKA1 SYNPR PIEZO1 REL SLC19A3 SYT12 PITPNM2 RGS17 SLC1A1 TACC2 PITPNM3 RGS20 SLC25A37 TANC2 PKDCC RGS6 SLC2A4RG TBC1D8B PLA2G3 RHBDF1 SLC35A3 TCF7 PLCB1 RHOJ SLC35E4 TDG PLD1 RIC3 SLC41A2 TEAD1 PLEKHG1 RIMBP2 SLC45A3 TERT PLEKHG5 RIMS2 SLC4A11 TFEB PLK3 RNF150 SLC4A3 TFRC PLOD2 RNF180 SLC4A7 TGM2 PLXND1 RNMT SLC7A1 THBS1 PMAIP1 ROCK2 SLC7A5 THY1 POLQ RPAP3 SLC9A7 TLN2 PPARGC1B RPE65 SLFNL1 TLR4 PPM1E RPS6KA3 SMAP2 TMEM170B PPME1 RTTN SMCO4 TMEM178A PPP1R3B RUNX1 SMOX TMEM217 PPP1R3G RUNX2 SNAI1 TMTC1 PPP2R3A RYR3 SNRPA1 TNFRSF12A PREX1 S100A10 SNTB1 TNFRSF18 PRKDC S100A16 SNX10 TNFSF13B PRKXP1 S100A2 SOCS3 TNIK PROS1 S100A6 SORL1 TNR

129

TOMM6 TTC26 VGLL2 ZCCHC12 TPPP TTC39B VPS13A ZFHX3 TRAF3IP2 TTLL11 VRK2 ZIC4 TRAF6 TTYH3 WASH5P ZNF317 TRAM2 UBE3C WDFY2 ZNF365 TREH UBR3 WDR27 ZNF398 TRIB2 UBTD1 WHAMMP2 ZNF778 TRIB3 UHMK1 WT1 ZNF800 TRIM44 ULK4 WWC2 ZNF827 TRIM9 UNC13A WWTR1 ZSCAN5A TRPM3 UNC80 XIAP ZYX TSN VAV3 XYLB TSPAN9 VCAN ZBTB38 TSPY26P VEGFA ZC3HAV1

130

Table S10: TAZ-Down gene list ABCC6 CBX4 EPB41L4A-AS1 HIST2H3A ACVR2A CCDC146 EPHB1 HIST2H3C ACYP2 CCDC162P EPSTI1 HIST2H4A ADAMTS6 CCNB3 EXTL3 HLA-E ADAMTSL1 CCNG2 FAM110B HRASLS2 ADPRHL1 CCT6P3 FAM122C HSD17B6 AGAP4 CD247 FAM13C HUNK AMOTL2 CD5 FAM171A2 IFITM1 ANGPTL1 CDC25C FAM69A IFNAR1 ANKDD1B CDC42EP4 FBLL1 IGSF11 ANKFN1 CDC42SE2 FBXL20 IQCH-AS1 ANKRD12 CELF3 FBXO25 IRX1 APCDD1 CENPF FCGBP JAKMIP2 APOBEC3F CH25H FER JMY APOL6 CHAC1 FGD3 KATNAL2 ARHGAP24 CKS2 FGFR3 KBTBD7 ARHGAP27 CLCN4 FIBIN KCNN2 ARHGEF10L CLHC1 FLVCR2 KCTD12 ARHGEF28 CLU FOXD4 KDM8 ARID3A CMC1 FOXD4L1 KIAA1614 ARMCX1 CNGA3 FOXO3 KLF15 ARMCX6 CNTFR FOXP2 KLF4 ARSD COL5A2 FRZB KLHL21 ARX COL9A1 FUCA1 KLHL24 ASXL3 CRB1 GBP1P1 KLHL35 ATP6AP1L CXXC4 GCA KMT2E-AS1 BAZ2B DAG1 GCLC KRBOX1 BBOX1 DAZAP2 GDPD2 LANCL2 BBS9 DCP2 GEMIN8 LDB1 BCL7A DCT GKAP1 LFNG BCOR DCTN4 GLRB LGR5 BEX1 DCX GNAL LIAS BIRC2 DDX11L2 GPC4 LIMCH1 BMPER DDX58 GPD1L LINC00537 BMPR1B DDX60L GPM6A LINC00638 BRD3 DEDD2 GRASP LINC00639 C10orf25 DGKB GRIA4 LINC01003 C11orf68 DHRS2 GTF2IRD2B LIPT2 C17orf82 DMAP1 H1F0 LMO1 C19orf66 DMRTA2 HELT LMO4 C1orf56 DNER HERC2P2 LRRC17 C9orf47 DRD4 HERC2P3 LRRN1 CA8 DUSP26 HERC6 LRRN2 CADM2 EAPP HES4 LRRTM3 CAHM EDNRB HES7 LUC7L2 CAPN6 EFNA1 HEY1 LYPD6 CASC15 ELAVL4 HIST2H2AA3 MACROD2 CASZ1 ELF1 HIST2H2AA4 MALAT1 CBFA2T2 EPAS1 HIST2H2BC MANBA 131

MAP2K5 OTUB1 RND3 TLE6 MAP3K8 OTUD1 RNF146 TLR3 MAP6 PARP10 RNF19B TMEFF1 MAPK8IP2 PARP12 RRAGC TMEM108 Mar8 PAX6 RXRA TMEM161B-AS1 MAT2B PBX3 SAMD13 TNFSF10 MB21D2 PCDH18 SAMD9 TNK2 MBOAT1 PCDHA13 SAMHD1 TNR MED30 PCMTD1 SCN3A TOP2A MEGF10 PCSK2 SFRP2 TOX3 MEIS1 PDCD4-AS1 SH3BP5L TRIL MFNG PDZRN3 SHOX2 TRIM21 MIR17HG PIGV SIX2 TRIM45 MIS18BP1 PIH1D2 SKOR1 TRIM68 MKRN3 PIK3AP1 SLC24A3 TSNARE1 MLLT3 PLCL2 SLC4A4 TTC34 MN1 PLD5 SMIM14 TTK MNT PLEKHA4 SNCAIP UCP3 MPPED2 PLEKHA7 SNHG5 UNC79 MST1P2 PLK2 SNHG7 UNC93B1 MTSS1 PLXNC1 SORBS3 UPF3B MUM1 PMF1-BGLAP SP110 UPRT MUT PNPLA7 SPARCL1 USP6 MXI1 POLE4 SPDYE2B VAPB NADK2 POLR3GL SPECC1L VPS9D1 NAPA POMZP3 SPOCK2 WDR45 NCALD POU3F4 SPSB4 WDR49 NCOA5 PPM1H SRRM3 WDSUB1 NELL1 PPP1R9A SRSF6 WIPI1 NEU4 PRODH SSBP3 WNT7A NEURL3 PTCH1 ST3GAL6 XRRA1 NFIB PTGES STON1 YPEL1 NMNAT1 PTGES3L- STOX2 YPEL5 NMNAT3 AARSD1 SYF2 ZBED5-AS1 NPTX1 PXDNL TAPT1-AS1 ZBTB12 NR4A2 RAB11B-AS1 TARS2 ZDHHC11 NRARP RAB3C TBC1D2 ZHX2 NRG2 RABGAP1L TBC1D5 ZNF184 NRSN1 RANBP3L TCF7L2 ZNF239 NTRK2 RARRES3 TCP11L2 ZNF396 NUAK2 RASL11B TCTA ZNF425 NUTM2A RELB TEX264 ZNF438 OASL RFTN2 TF ZNF518A OIP5 RFX4 TFAP2A-AS1 ZNF581 OMA1 RGMA THAP7-AS1 ZNF737 OPHN1 RGS3 THEMIS2 ZNF747 OTP RIMBP3C TIGD2 ZRANB3

132

Table S11: KEGG pathway analysis results for TAZ-Up and TAZ-Down genes Provided as separated files Sheet 1: KEGG analysis on TAZ-Up genes Sheet 2: KEGG analysis on TAZ-Down genes

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Fig. S1: Cluster of all 641 up-regulated genes within top 20 enriched KEGG pathways.

134

Left: all 641 genes plotting in the 65 enriched pathways Right: genes which participated in at least one enriched pathways

135

Fig. S2: Correlation between TAZ and TAZ-Up genes in in the TCGA database

Correlation analysis of mRNA levels of TAZ (WWTR1) and interested oncogenes in GBM specimens from the TCGA database (n=454).

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Curriculum Vitae

Personal Information:

Name: Minling GAO

Mailing Address: 321E University Parkway, Baltimore, Maryland, USA

Telephone: +1-4436768309

E-mail: [email protected]

Education Background

08/2014 – present: Johns Hopkins School of Medicine, USA

PhD in Pathobiology, to be obtained in May 2020

08/2010 – 07/2014: Nanyang Technological University, Singapore

Bachelor in Science, Major in Biological Science, Minor in Computing

Academic Experiences

08/2015 – present: Thesis Project in Prof. John Laterra’s lab, Johns Hopkins School of

Medicine

Description: My thesis targeted at elucidating a novel EGFR-TAZ signaling axis in GBM and further provided a genome-wide map of downstream transcriptome that promotes key malignant features of GBM. Our results also support the clinical use of defined FDA-

164 approved EGFR inhibitor OS and the FDA-approved drug VP for effective TAZ targeting in

GBM and likely other primary or metastatic brain tumors with TAZ hyperactivation.

10/2013 – 07/2014: Final Year Project in Prof. Mark Featherstone’s lab, Nanyang

Technological University

Description: Structure-function studies of the PBX1 homeoprotein involving the mutation of these cysteine residues in an attempt to generate functional PBX derivatives that are amenable to structural studies. Techniques to be learned include overlap extension PCR, tissue culture, transfection, bacterial expression and protein purification.

Meetings and Publications

Minling Gao, Yi Fu, Laterra John, Mingyao Ying. EGF signaling activates a TAZ-driven oncogenic program in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia

(PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2608.

Chang YT, Hernandez D, Alonso S, Gao M, Su M, Ghiaur G, Levis MJ, Jones RJ. Role of

CYP3A4 in bone marrow microenvironment-mediated protection of FLT3/ITD AML from tyrosine kinase inhibitors. Blood Adv. 2019 Mar 26;3(6):908-916. doi:

10.1182/bloodadvances.2018022921. PMID: 30898762; PMCID: PMC6436013.

Scholarships

08/2014 – present: Margaret Lee scholarship

08/2010 – 07/2014: SM2 scholarship, Singapore

165