Gene Expression and Cancer

1. Gene Expression and Cancer Presentation: Inna Weiner

2. Cancer • Cellular level: over–proliferation of the cell • Tissue level: cells deviate from their natural place in the tissue and spread • 3 main principles: • Tumors are mono-clonal • DNA mutations (6-7 usually) • Selection (from bad to worse)

3. Cellular mechanisms in cancer • Signaling pathways damage • Tumor cells uncontrolled proliferation • Growth factors constitutive activity • Constitutive up/down regulation • DNA repair problem • Apoptosis mechanism not active • Cells acquire metastatic potential • …

4. Primary Tumor

5. Cancer – metastatic pathway

6. Articles • A molecular signature of metastasis in primary solid tumors. S. Ramaswamy et al. Nature Genetics, 2002 • Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. H. Y. Chang et al. PNAS, 2005 • An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis. A. Sweet-Cordero et al. Nature Genetics, 2004

7. A molecular signature of metastasis in primary solid tumors Sridhar Ramaswamy, Ken N. Ross, Eric S. Lander & Todd R. Golub Nature Genetics, December 2002

8. Motivation for Predicting Metastasis • Metastasis (Greek: change of the state): spread of cancer from its primary site to other places in the body (e.g., brain, liver) • Metastasis is the principal event leading to death in individuals with cancer

9. Model of Metastasis • Most primary tumor cells have low metastatic potential • Rare cells (estimated at less than 1 in 10,000,000) within large primary tumors acquire metastatic capacity through somatic mutation

10. Metastatic Phenotype • Has the ability to • migrate from the primary tumor • survive in blood or lymphatic circulation • invade distant tissues • establish distant metastatic nodules • Supported by animal models

11. Setup • 12 metastatic adenocarcinoma nodules of diverse origin (lung, breast, prostate, colorectal, uterus, ovary) • 64 primary adenocarcinomas representing the same spectrum of tumor types

12. Hypothesis: a gene-expression program of metastasis may already be present in the bulk of some primary tumors at the time of diagnosis

13. Hypothesis testing • 62 stage I/II primary lung adenocarcinomas • Hierarchical clustering in the space 128 metastases-derived genes

14. 128 pre-defined genes 17 unique genes nearest the centroids of the two lung cancer clusters all genes Clinical Outcome Prediction

15. Generality of metastatic signature

16. Upregulation: Protein translation apparatus 17-gene metastatic signature

17. Upregulation: Non-epithelial components of the tumor 17-gene metastatic signature

18. Downregulation: Antigene presenting cell 17-gene metastatic signature

19. 17-gene metastatic signature Downregulation: Tumor suppressor

20. Prevailing Model: incidence of metastasis is related to the number of cells susceptible to metastasis-promoting mutations, and hence to tumor size New Model: the propensity to metastasize reflects the predominant genetic state of a primary tumor • consequence of particular mechanisms of transformation • metastasis-potential tumor • selection process favoring the metastatic phenotype • rare metastatic phenotype Novel Model of Metastasis

21. The authors did not prove that there is a single cell with all metastatic functions Maybe a small fraction of primary tumors (the biggest?) did acquire metastatic-potential cells Critical View

22. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival H. Y. Chang, D. S. A. Nuyten, J. B. Sneddon, T. Hastie, R. Tibshirani, T. Sørlie, H. Dai, Y. D. He, L. J. van’t Veer, H. Bartelink, M. van de Rijn, P. O. Brown, and M. J. van de Vijver PNAS, March 8, 2005

23. Chang et al (2004), PLoS • Hypothesis: Molecular program of normal wound healing might play an important role in cancer metastasis • Procedure: Measured gene expression of serum response of cultured fibroblasts from 10 anatomic sites in vitro • Result: Identified a set of “core serum response” genes and their canonical expression profile in fibroblasts activated with serum

24. 512 core serum response genes were identified and were considered representative of a ‘‘wound’’ signature

25. Likely to contribute to cancer invasion and metastasis Chang et al (2004):Identified Annotations of Genes • Matrix remodeling • Cytoskeletal rearrangement • Cell–cell signaling • Angiogenesis • Cell motility

26. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival H. Y. Chang, D. S. A. Nuyten, J. B. Sneddon, T. Hastie, R. Tibshirani, T. Sørlie, H. Dai, Y. D. He, L. J. van’t Veer, H. Bartelink, M. van de Rijn, P. O. Brown, and M. J. van de Vijver PNAS, March 8, 2005

27. Performance of “wound-response” signature 295 breast cancer samples using 442 available core serum response genes

28. Chang et al (2004): Clinical Outcome Prediction

29. Scalable Prognostic Score • Problem: Hierarchical clustering provides biologically arbitrary threshold • Solution: Create the centroid of the differential expression in response to serum in cultured fibroblasts from 10 anatomic sites (Chang, 2004) • Score = corr (centroid, new example)

30. Improving Clinical Decision Making • 30% of women with early breast cancer develop metastasis • For young women chemotherapy increases 10 year survival at ~10% • Chemotherapy does not benefit for 89-93% of all breast cancer patients

31. Summary • Mechanism-driven approach to prognostic biomarker discovery on a genome scale • Uncovered the catalog of genes involved in a potentially new cellular process that defines the clinical biology of breast cancer • pathogenic mechanisms • potential targets for treatment • New findings applicable for clinical decision making

32. Cancer course, I. Ben-Neria

33. The MAP-K cascade :Protein-Protein interactions bridging the plasma membrane and the nucleus Cancer course, I. Ben-Neria

34. RAS Activation RAS is oncogenic due to constitutive activation in the GTP-bound form

35. An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis. A. Sweet-Cordero, S. Mukherjee, A Subramanian, H. You, J.J. Roix, C. Ladd-Acosta, T. R. Golub and T.Jacks Nature Genetics, December 2004

36. Why use animal models? • Initiated by single well-characterized event • Discover novel pathways obscure in human data • Endogenous activation of oncogenes in vivo is distinct from overexpression in vitro

37. Experimental Setup • Goal: build animal model for human lung adenocarcinoma • Create KrasLA mouse model: Mice with sporadically activated Kras2 through spontaneous homologous recombination • Mice develop lung adenoma • Through time acquire characteristics similar to human tumor: nuclear atypia and high mitotic index

38. Gene Set Enrichment Analysis (GSEA) Is Rank-Ordered Gene List (from human analysis) enriched in independent a priori defined Gene set (from mouse model)?

39. Gene Set Enrichment Analysis (GSEA)

40. Comparison of Gene Expression in mouse and human lung cancer • Using GSEA was found • Differentially expressed genes in KrasLA mouse model were significantly enriched in Human Lung Adenocarcinoma but not in other lung subtypes • NNK mouse model (induced by chemical mutogen) adenoma and carcinoma did not provide enriched Differentially Expressed Gene Set • Mouse tumor from KrasLA and NNK model were not distinguishable histologically

41. Oncogenic KRAS2 signature • 89 differentialy expressed genes (upregulated) in KrasLA mouse model that contributed maximally to the GSEA score in human data set

42. KRAS2 signature verification (1) • KRAS2 signature is enriched in pancreatic adenocarcinoma • KRAS2 mutation occurs in >90% of pancreatic adenocarcinomas  Link between KRAS2 signature and mutation of KRAS2

43. KRAS2 signature verification (2) • Real-time PCR analysis of expression of selected KRAS2 signature genes (in human cell lines)

44. KRAS2 signature verification (3) • Knock-down of KRAS2 in human lung cancer cell line

45. Summary • Integrative analysis of mouse model and human cancer can • Validate the animal model • Extract an evidence of oncogene-specific program • Compare several models against human cancer types • In this research were identified many potential effectors of KRAS2 • New directions for anti-Ras pathway therapeutic strategies