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Master Regulators of Tumor Subtype and Associated Driver Mutations

Interrogating High-Grade Glioma Regulatory Networks to Identify :. Master Regulators of Tumor Subtype and Associated Driver Mutations. Systems Biology. Genomics. Cancer . Drugs & Biomarkers. Prevention Diagnosis Treatment. Transcriptomics. Cell Regulatory Logic. Epigenomics.

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Master Regulators of Tumor Subtype and Associated Driver Mutations

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  1. Interrogating High-Grade Glioma Regulatory Networks to Identify : Master Regulators of Tumor Subtype and Associated Driver Mutations

  2. Systems Biology Genomics Cancer Drugs & Biomarkers Prevention Diagnosis Treatment Transcriptomics Cell RegulatoryLogic Epigenomics Protein DNA Protein Protein Protein Membrane Other Omics: Metabolomics Proteomics Glycomics … Clinical Trials

  3. Developmental Transcriptional Interactions POST-TRANSCRIPTIONAL INTERACTIONS Zhao X et al. (2009) Dev Cell. 17(2):210-21. Mani KM et al. (2008) Mol Syst Biol. 4:169 Palomero T et al., Proc NatlAcadSci U S A 103, 18261 (Nov 28, 2006). Margolin AA et al., Nature Protocols; 1(2): 662-671 (2006) Margolin AA et al., BMC Bioinformatics 7 Suppl 1, S7 (2006). Basso K et al. (2005), Nat Genet.;37(4):382-90. (Apr. 2005) Basso et al. Immunity. 2009 May;30(5):744-52 Klein et al, Cancer Cell, 2010 Jan 19;17(1):28-40. Sumazin et al. 2011, in press Master regulators and mechanism of action Post-translational Interactions Wang K, Saito M, et al. (2009) Nat Biotechnol. 27(9):829-39 Zhao X et al. (2009) Dev Cell. 17(2):210-21. Wang K et al. (2009) Pac SympBiocomput. 2009:264-75. Mani KM et al. (2008) Mol Syst Biol. 4:169 Wang K et al. (2006) RECOMB The CTD2 Network (2010), Nat Biotechnol. 2010 Sep;28(9):904-906. Floratos A et al. Bioinformatics. 2010 Jul 15;26(14):1779-80 Lefebvre C. et al (2010), Mol Syst. Biol, 2010 Jun 8;6:377 Carro MS et al. (2010) Nature 2010 Jan 21;463(7279):318-25 Mani K et al, (2008) Molecular Systems Biology, 4:169

  4. MINDy: Reverse Engineering of Post Translational Modulators of Transcriptional Regulation Mary Joe TERT MYC GSK3 Tony Signal GSK3 Degradation MYC TERT

  5. Post-Translational Network Validation (MINDy) STK38 (serine-threonine kinase 38, NDR1) 1) Protein-Protein interaction with MYC 2) STK38 silencing in ST486 decreases MYC stability 3) MYC mRNA is not affected 3) MYC targets are consistently affected ~400 Gene Expression Profiles for Normal and Tumor Related Human B Cells 1 3 2 Wang K, Saito M, et al. (2009) Nat. Biotechnol. 27(9):829-39

  6. Available Transcriptional Interactomes: • Cancer • B Cell interactome (BCi) • Breast Cancer Cell interactome (BCCi) • T-ALL interactome (TALLi) • AML • Prostate Cancer interactome (Pci mouse/human) • Glioblastoma Multiforme interactome (GBMi) • Ovarian • Non-small-cell Lung Cancer • Colon Cancer • Hepatocellular Carcinoma • Neuroblastoma • NET • Stem Cells • Mouse EpiSC and ESC • Human ESC • Germ Cell Tumors (Pluripotency, Lineage Differentiation) • Neurodegenerative Disease • Human and Mouse Motor Neuron (ALS) • Human and Mouse whole brain (Alzheimer’s) Interactomes are generated from primary tissue profiles and thus reflect cell regulation in vivo, in the presence of all relevant paracrine, endocrine, and contact signals

  7. Interrogating the Assembly Manual of the Cell Disease Initiation & Progression Biomarkers Pluripotency and Lineage Differentiation Therapeutic Targets Cell Regulatory Logic Small-molecule Modulators Mechanism of Action Drug MoA and Resistance

  8. MARINa: Master Regulator Inference algorithm A Master Regulator is a gene that is necessary and/or sufficient to induce a specific cellular transformation or differentiation event. Phenotype 1 (Normal) Phenotype 2 (Neoplastic) MRx? TF1: Repressed: 5/7 Activated: 5/7 Coverage: 10/18 (55%) TF2: Repressed: 1/5 Activated: 1/6 Coverage: 2/18 (11%) Under-expressed in Tumor Over-expressed in Tumor Tumor Signature • Carro, M. et al. (2010). "The transcriptional network for mesenchymal transformation of brain tumours." Nature463(7279): 318-325 • Lefebvre C. et al. (2009). "A Human B Cell Interactome Identifies MYB and FOXM1 as Regulators of Germinal Centers." Mol SystBiol, in press • Lim, W. et al. (2009). "Master Regulators Used As Breast Cancer Metastasis Classifier." Pac SympBiocomp14: 492-503

  9. Mesenchymal Subtype of High-Grade Gliomas Unsupervised clustering of 176 high grade tumors by expression of 108 genes that are positively or negatively associated with survival reveals 3 tumors classes (Proneural (PN), Mesenchymal (Mes) and Proliferative (Prolif). Phillips et al., Cancer Cell, 2006 PNGES MGES PROGES Malignant gliomas belonging to the mesenchymal sub-class express genes linked to the most aggressive properties of glioblastoma (migration, invasion and angiogenesis).

  10. Mes signature genes Activator Repressor Identification of a mesenchymal regulatory module Master Regulators control >75% of the Mesenchymal Signature of High-Grade Glioma Biochemical Validation of ARACNe Inferred Targets of Stat3, C/EBPb, FosL2, and bHLH-B2 Hierarchical Regulatory Module

  11. In Vitro Validation

  12. In Vivo Validation Mouse Survival Data Control Vector Stat3- C/EBPb- Stat3-/C/EBPb- Human Survival Data Mouse immunohistochemistry Carro, M. et al. (2010). Nature 463(7279): 318-325

  13. TCGA dataset on different networks E 1 2 3 Sun (3) 6 5 4 22 10 1.9x10-7 • 1Cancer Genome Atlas Research Network, Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008 Oct 23;455(7216):1061-8 • 2Phillips, H.S., et al., Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell, 2006. 9(3): p. 157-73. • 3Sun, L., et al., Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell, 2006. 9(4): p. 287-300` 10 8 Phillips (2) TCGA (1) Distinct Programs with significant overlap across distinct datasets

  14. The Bottleneck Hypothesis • Glioblastoma: • Carro MS et al. The transcriptional network for mesenchymal transformation of brain tumours. Nature. 2010 Jan 21;463(7279):318-25. • Master Regulators: C/EBP + Stat3 • Diffuse Large B Cell Lymphoma: • Compagno M et al. Mutations of multiple genes cause deregulation of NF-kappaB in diffuse large B-cell lymphoma. Nature. 2009 Jun 4;459(7247):717-21 • Master Regulator: Nf-kB pathway • GC-Resistance in T-ALL: • Real PJ et al. Gamma-secretase inhibitors reverse glucocorticoid resistance in T cell acute lymphoblastic leukemia. Nat Med. 2009 Jan;15(1):50-8. • Master Regulator: NOTCH1 pathway G1 G2 G3 G4 G5 G6 G7 G8 Therapeutic Targets G9 G10 G11 G12 Patient X G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 = EGFR = PDGFRA = p16 = p53 = PTEN = MDM2 = MDM4 = MYC = NF1 = ERBB2 = RB1 = CDK4 X W Y Z Master Regulator Module(s) V Molecular Phenotype Disease Stratification Biomarkers … E.g. GBM subtypes

  15. Inhibitors of C/EBP Activity (c) MINDy Analysis (a) Protein Binding Assays M2 M1 Mn M2 M1 Mn C/EBP Comp1 Comp1 STAT3 Compn MGES Compn (b) High Throughput Screening Collaboration with: S. Schreiber (a) B. Stockwell (b) A. Iavarone and A. Lasorella (a, b, c)

  16. MINDy Modulators of miRNA activity mature miRNA Mod miR target Sumazin et al. Cell, 2011 Oct 14;147(2):370-81.

  17. Novel miR-program mediated regulatory network • Analysis of TCGA data for GBM and Ovarian Cancer • including matched gene and miRNA expression profiles for 422 and 587 samples • Modulation of miRNA activity on targets • 7,000Sponge modulators, participating in248,000 miR-mediated mRNA-mRNA interactions • 148 Non-sponge modulators affecting more than 100 miRs (using only experimentally validated miRs targets) • 17/430 are RNA-binding proteins or a component of the spliceosome

  18. 13 miR-mediated regulators of PTEN G14 – G 563 G1 G2 G3 G13 PTEN 564 node, 111 core sub-graph G4 G11 G5 G10 G9 G6 G8 G7 p < 5 x 10-23 p < 2 x 10-10

  19. 13 miR-mediated regulators of PTEN

  20. A B PTEN over expression and silencing effects on SNB19 cell growth rate Silencing PTEN mPR regulators affects SNB19 cell growth rate Proliferation fold change Proliferation fold change Days Days C D PTEN over expression and silencing effects on SF188 cell growth rate Silencing PTEN mPR regulators affects SF188 cell growth rate Proliferation fold change Proliferation fold change Days Days

  21. Targeted Drug Development Hit compound Molecular Target(s) CTD2 Network Biomarkers: Response/Efficacy Clinical Trials Compound Mechanism of Action

  22. Conclusions and Reflections • Current emphasis on genes harboring genetic and epigenetic alterations may not be sufficient • We should also focus on Master Regulator and Master Integrator genes • Current approach to biomarker discovery should be re-evaluated in a molecular interaction network context. • It is not the genes/proteins that change the most but rather those that change most consistently. (mRNA is not informative) • From GWAS (Genome-Wide Association Studies) to NBAS (Network-Based Association Studies) • Califano A, Butte A, Friend S, Ideker T, and Schadt EE, Integrative Network-based Association Studies: Leveraging cell regulatory models in the post-GWAS era, Nat. Genetics, in press. Accessible in Nature Preceedings: http://precedings.nature.com/documents/5732/version/1 • One disease – One target – One drug Multi-target combinations • Optimal combination of drugs selected from a repertoire of safe, target-specific compounds using predictive tools. • Identification of genetic dependencies (addictions) from Ex Vivo Models • Identification of candidate therapeutic agents from In Vitro mechanistic models.

  23. Acknowledgements • Califano Lab (Computational) • MukeshBansal, Ph.D. • ArchanaIyer, Ph.D. • Celine Lefebvre, Ph.D. • YishaiShimoni, Ph.D. • Maria Rodriguez-Martinez, Ph.D. • AntoninaMitrofanova, Ph.D. • Jose’ Morales, Ph.D. • Paola Nicoletti, Ph.D. • PavelSumazin, Ph.D. • Gonzalo Lopez, Ph.D. • James Chen, (GRA) • Hua-Sheng Chu (GRA) • Wei-Jen Chung (GRA) • In Sock Jang (GRA) • William Shin (GRA) • Jiyang Yu (GRA) • Wei-Jen Chung (GRA) • Alex Lachman (GRA) • PradeepBandaruM.A. • ManjunathKustagi (Programmer) • Software Development • ArisFloratos, Ph.D. (Exec. Director) • Ken Smith, Ph.D. • Min Yu, (Programmer) • Califano Lab Experimental • Gabrielle Rieckhof, Ph.D. (Exec Director) • Mariano Alvarez, Ph.D. • BrygidaBisikirska, Ph.D. • Xuerui Yang, Ph.D. • Yao Shen, Ph.D. • PreshaRajbhandari, M.A. (Sr. Res. Worker) • JoridaCoku, M.A. (Staff Associate) • HesedKim, (Staff Associate) • Sergey Pampou, Ph.D. • A. Iavarone & A. Lasorella (CU) • Maria Stella Carro • K. Aldape (MD Anderson) • R. DallaFavera(CUMC) • Katia Basso • Ulf Klein • R. Chaganti (MSKCC) • M. White & J. Minna(UTSW) • J. Silva (CU) • C. Abate-Shen & M. Shen (CU) • D. Felsher (Stanford) Funding Sources: NCI, NIAID, NIH Roadmap

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