1. EMT ☤ MET CRC MET overexpression as a hallmark of the epithelial-mesenchymal transition (EMT) phenotype in colorectal cancer K. Raghav, W. Wang, G.C. Manyam, B.M. Broom, C. Eng, M.J. Overman, S. Kopetz The University of Texas M D Anderson Cancer Center, Houston TX

2. Disclosures No relevant relationships to disclose.

3. Learning Objectives Recognize epithelial-mesenchymal transition (EMT) as a principal molecular subtype in colorectal cancers. Identify MET protein overexpression as a key clinical biomarker of EMT physiology in colorectal cancers.

4. Overview Introduction Epithelial-mesenchymal transition (EMT) Challenges & Research question MET/HGF Axis Study Objective Methodology Results Conclusions Future

5. Overview Introduction Epithelial-mesenchymal transition (EMT) Challenges & Research question MET/HGF Axis Study Objective Methodology Results Conclusions Future

6. EMT & Normal cells Epithelial phenotype ► Mesenchymal phenotype Embryogenesis & Development Weinberg RA et al. J Clin Invest. Jun 2009

7. EMT & Tumors EMT ‘mesenchymal’ phenotype: Migratory capacity: Invasion & Metastasis Linked to chemo-resistance (oxaliplatin and 5FU) Thiery JP. Nature Reviews Cancer. Jun 2002 ; Yang AD et al. Clin Cancer Res. Jul 2006

8. Gene Signatures identify EMT Gene signatures: EMT ‘mesenchymal’ subtype Distinct biology Cheng WY et al. PLoS One. Apr 2012 ; Loboda A et al. Med Genomics. Jan 2011

9. EMT foretells Poor prognosis EMT molecular classification is prognostic EMT or mesenchymal-subtype: Worse Prognosis Epithelial-Subtype: Better Prognosis Figure 1Figure 2 Shioiri M et al. Br J Cancer. Jun 2006 ; Loboda A et al. Med Genomics. Jan 2011 High EMT Score Low EMT Score EMT + EMT -

10. Challenges in Defining EMT Phenotype in Clinic EMT Gene Signature: Extensive ongoing efforts Hard to implement in clinic Limited availability Protein Biomarker: More practical Readily available ABC Epigenetic Modulation Tumor ABC Genes Proteins Post Translational Modification Weigelt B et al. Ann Oncol. Sep 2012 Protein Processing

11. Research Question Possibility of using a clinical biomarker, to reflect EMT biology to recognize EMT “mesenchymal” subtype as identified by EMT gene signatures ? Possible marker: MET MET is motogenic: + Cell mobility & invasiveness First EMT cell lines transformed using MET activation. Common signaling pathways with EMT Optimized assays & integrated as a biomarker Thiery JP. Nature Reviews Cancer. Jun 2002

12. MET/HGF Axis MET/HGF Axis: Receptor: MET Ligand: HGF/SF Regulates Gene expression Cytoskeleton Aberrancy: Tumor Proliferation, Survival, Invasion, Migration Raghav K & Eng C. Colorectal Cancer Aug 2012

13. Overview Introduction Epithelial-mesenchymal transition (EMT) Challenges & Research question MET/HGF Axis Study Objective Methodology Results Conclusions Future

14. Study Objective To identify association between MET protein expression and gene/protein expression of EMT markers and EMT gene signatures in human colorectal cancers.

15. Study Methodology Data collection: The Cancer Genome Atlas (TCGA) Data The cBio Cancer Genomics Portal Data type (Untreated primary): Gene expression: mRNA Expression RNA Sequencing Protein levels (MET, SLUG, ERCC1): Reverse phase protein array RPPA

16. Study Methodology Tumors classified as per MET protein levels: MET High/Overexpressed: Protein in top quartile MET Low: Protein level < 3 rd Quartile 58 genes associated with EMT phenotypes evaluated: Unsupervised: ≥ 2 EMT signatures (N = 41) Loboda, Taube, Salazar & Cheng EMT profiles Nominated: Common EMT markers (N = 17) Salazar R et al. J Clin Oncol. Jan 2011 ; Cheng WY et al. PLoS One. Apr 2012 ; Taube JH et al. Proc Natl Acad Sci U S A. Aug 2010

17. Study Methodology Statistical methods: Non-parametric Spearman rank correlation Mann-Whitney unpaired two-sample U test Regression tree method Kaplan-Meier estimates P < 0.05: Statistically significant All tests were two-sided

18. Baseline Characteristics Protein & Gene expression data (N = 139) Median age at diagnosis: 71 yrs. (35-90 yrs.) Stage Distribution: Anatomy:

19. MET overexpression: A Distinct Subset Study Sample (N = 139) Right Skewed MET protein expression is r ight skewed Top quartile represents distinct subset Poor correlation with MET gene expression (r = 0.16) Protein (Z-score)

20. High MET portends poor survival

21. Hazard Ratio: 2.92 (P = 0.003) MET High MET Low MET-High MET-Low

22. Clinicopathological Associations MET protein expression: Not associated with any clinical-pathological variables including stage Colon > Rectum P < 0.0001 P = 0.008

23. Protein-Protein Associations

24. MET & SLUG Protein SLUG encoded by SLUG/SNAI2 gene Zinc finger protein transcription factor Represses E-cadherin transcription  EMT r = 0.63 P < 0.0001

25. MET & ERCC1 Protein DNA nucleotide excision repair protein Negative predictive marker for platinum therapy SNAIL upregulates ERCC1 expression P < 0.001 ERCC1 protein correlates with MET expression (r = 0.6) Higher ERCC1 in MET overexpressed (P < 0.001)

26. Protein-Gene Associations

27. Results : EMT Markers GeneP P AEBP0.034 GREM1 0.033 AXL0.005 LUM 0.035 CDH110.006 MGP 0.003 CDH20.029 MMP11 0.038 COPZ20.008 PRXX1 0.002 CTGF0.035 SERPINF1 0.004 DCN 0.006 SPOCK1 0.003 ECM2 0.016 TAGLN 0.033 FAP 0.020 TCF4 0.046 FBLN5 0.017 TGFB1I1 0.012 FGF1 0.008 THBS2 0.022 FGF7 0.045 VIM 0.011 FSTL1 0.032 ZEB1 0.010 Upregulated EMT markers ZEB2 0.005 AXL P = 0.005 ZEB1 P = 0.010 ZEB2 P = 0.005 VIM P = 0.011 MET-LowMET-High

28. EMT signatures correlate well EMT gene signature scores: Cheng vs. Salazar (r = 0.8) Salazar vs. Taube (r = 0.6) Taube vs. Cheng (r = 0.7) P < 0.001 Salazar R et al. J Clin Oncol. Jan 2011 ; Cheng WY et al. PLoS One. Apr 2012 ; Taube JH et al. Proc Natl Acad Sci U S A. Aug 2010 P < 0.001

29. EMT gene scores & MET EMT meta gene score: MET overexpression group vs. MET normal group Cheng (P = 0.016) Taube (P = 0.029)Salazar (P = 0.017)

30. Conclusions MET protein expression Highest quartile represents a distinct subset Not correlate with MET mRNA expression Higher in colon than in rectal cancers Higher expression of SLUG transcription factor Higher ERCC1 protein levels Increased gene expression of EMT markers Higher EMT gene signature scores

31. Take Home Message MET protein expression can potentially be used as a clinical biomarker representative of the EMT “mesenchymal” phenotype in CRC.

32. Overview Introduction Epithelial-mesenchymal transition (EMT) Problem at hand & Research question MET/HGF Axis Study Objective Methodology Results Conclusions Future

33. Validation of these results on an independent dataset is currently being performed. Evaluation of IHC in assessing MET protein expression is underway. MET can be used as a clinical bio-marker for patient selection for trials targeting EMT. Unique approach for biomarker search

34. Proposed Paradigm for Pursuit of Biomarkers Genomic Profiling Biomarker Proposed Strategy TrialDrugBiomarker Conventional Strategy Tumor Biology Trial B C A Target based biomarkers Taxonomy based biomarkers Drug

35. Acknowledgement K OPETZ L AB T EAM Dr. Ali Kazmi, M.D. Dr. Arvind Dasari, M.D. Maria Pia Morelli, M.D., Ph.D. Shweta Aggarwal, M.D. Feng Tian, Ph.D. Zhi-Qin Jiang, M.D., Ph.D. NCI TCGA initiative Collaborators C O -I NVESTIGATORS Wenting Wang, Ph.D. Ganiraju C Manyam, Ph.D. Bradley M Broom, Ph.D. Cathy Eng, M.D., FACP Michael J. Overman, M.D. Scott Kopetz, M.D., Ph.D., FACP C OLLABORATORS Dr. Amin Hesham, M.D., M.Sc. Dr. David S. Hong, M.D.