Gene Expression and Cancer Presentation: Inna Weiner

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)

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 …

Primary Tumor

Cancer – metastatic pathway דה-אדהיז'ן - הפסקת התאחיזה בין התאים ברקמה (ירידה בביטוי גנים של תאחיזה בין תאית) פלישה - רכישת כושר פולשנות . יצירת אנזימים שיכולים לעכל את הקרום הבסיסי. תנועה - רכישת כושר תנועתיות – חריגה מהנישה הטבעית שלהם. חדירה לכלי הדם או הלימפה (Intravasation). הפיזור של התאים בכל הגוף הוא מיידי. מאפשר פיזור נרחב של גרורות [אין ספציפיות לגידול, אולם יש העדפות מסוימות. הכיצד?] החלצות מכלי הדם (Extravasation) ברקמת המטרה. יצירת מושבה של גרורות.

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

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

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 Cancer cells can break away from a primary tumor, penetrate into lymphatic and blood vessels, circulate through the bloodstream, and grow in a distant focus (metastasize) in normal tissues elsewhere in the body.

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

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 The successful metastatic cancer cell must leave the primary tumor, enter the lymphatic and blood circulation, survive within the circulation, overcome host defenses, extravasate and grow as a vascularized of tumor cells, but less than 0.01% of these cells develop into metastasis.

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

Hypothesis: a gene-expression program of metastasis may already be present in the bulk of some primary tumors at the time of diagnosis The arrow - these tumors being misclassified as metastases (see Web Note A and Web Table A). This observation suggested the hypothesis that a gene-expression program of metastasis may already be present in the bulk of some primary tumors at the time of diagnosis.

Hypothesis testing 62 stage I/II primary lung adenocarcinomas Hierarchical clustering in the space 128 metastases-derived genes a, Hierarchical clustering of 62 primary lung adenocarcinomas using 128 metastases-derived genes defined two predominant primary-tumor groups in the resulting dendrogram. Colorgram depicts high (red) and low (blue) relative levels of gene expression. Vertical bar (left) indicates genes that were originally expressed in primary tumors (black) or metastases (red). Horizontal bar (top) indicates samples from individuals whose cancer was observed to be non-recurrent (black) or recurrent (red).

Clinical Outcome Prediction 128 pre-defined genes all genes 17 unique genes nearest the centroids of the two lung cancer clusters Kaplan–Meier analyses

Generality of metastatic signature Kaplan–Meier analyses of cluster- defined primary-tumor subsets 60 medulloblastomas large B-cell lymphoma10 (P = 0.497; Fig. 3d), consistent with the idea that hematopoietic tumors have specialized mechanisms for navigating the hematologic and lymphoid compartments.

17-gene metastatic signature Upregulation: Protein translation apparatus Notably, the large stromal component of the signature would have been missed had only malignant epithelial cells been isolated (for example, by laser capture microdissection) before expression profiling.

17-gene metastatic signature Upregulation: Non-epithelial components of the tumor Notably, the large stromal component of the signature would have been missed had only malignant epithelial cells been isolated (for example, by laser capture microdissection) before expression profiling.

17-gene metastatic signature Notably, the large stromal component of the signature would have been missed had only malignant epithelial cells been isolated (for example, by laser capture microdissection) before expression profiling. Downregulation: Antigene presenting cell

17-gene metastatic signature Notably, the large stromal component of the signature would have been missed had only malignant epithelial cells been isolated (for example, by laser capture microdissection) before expression profiling. Downregulation: Tumor suppressor

Novel Model of Metastasis 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 A metastatic tumor may be more efficient at producing metastasis because it has a higher proportion of the rare metastatic cell or because the average tumor cell in the colony has a stronger metastatic fitness. selection process favoring the metastatic phenotype rare metastatic phenotype consequence of particular mechanisms of transformation metastasis-potential tumor

Critical View 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 -- some individuals harboring metastasis can survive many years despite a large metastatic burden, whereas others will succumb rapidly to aggressive metastatic disease -- host/stromal cells

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

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 Blood plasma is the liquid component of blood, in which the blood cells are suspended. Serum is the same as blood plasma except that clotting factors (such as fibrin) have been removed (Wikipedia)

of a ‘‘wound’’ signature 512 core serum response genes were identified and were considered representative of a ‘‘wound’’ signature (A) The fibroblast common serum response.Genes with expression changes that demonstrate coordinate induction or repression by serum in fibroblasts from ten anatomic sites are shown. Representative genes with probable function in cell cycle progression (orange), matrix remodeling (blue), cytoskeletal rearrangement (red), and cell–cell signaling (black) are highlighted by colored text on the right. Three fetal lung fibroblast samples, cultured in low serum, which showed the most divergent expression patterns among these samples (in part due to altered regulation of lipid biosynthetic genes, are indicated by blue branches. (B) Identification of cell cycle-regulated genes in the common serum response signature. The expression pattern of each of the genes in (A) during HeLa cell cycle over 46 h after synchronization by double thymidine block is shown.

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

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

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

Chang et al (2004): Clinical Outcome Prediction

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)

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 NIH - five molecular subtypes, SG - discovered by directly fitting to survival data, and one based on an in vitro model of a wound response 185 patients did not receive chemotherapy 10% undertreated 30% overtreated

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

Cancer course, I. Ben-Neria

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

RAS Activation Small G proteins are monomeric G proteins with molecular weight of 20-40 kDa. Like heterotrimeric G proteins, their activity depends on the binding of GTP. Cycling of the Ras protein between active and inactive states.  Like other G proteins, Ras can switch between GTP-bound and GDP-bound states.  Transition from the GDP-bound to the GTP-bound state is catalyzed by guanine nucleotide exchange factor (GEF) which induces exchange between the bound GDP and the cellular GTP.  The reverse transition is catalyzed by a GTPase-activating protein (GAP) which induces hydrolysis of the bound GTP. RAS is oncogenic due to constitutive activation in the GTP-bound form

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 Official Symbol: KRAS and Name: v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog  Summary: This gene, a Kirsten ras oncogene homolog from the mammalian ras gene family, encodes a protein that is a member of the small GTPase superfamily. A single amino acid substitution is responsible for an activating mutation. The transforming protein that results is implicated in various malignancies, including lung adenocarcinoma, mucinous adenoma, ductal carcinoma of the pancreas and colorectal carcinoma. Alternative splicing leads to variants encoding two isoforms that differ in the C-terminal region.

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 Validation by Gene Expression Profile

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

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

Gene Set Enrichment Analysis (GSEA)

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 Conclusion: the found genes were NOT merely cancer/proliferation signature. Conclusion: mouse models that seem similar may differ on gene expression level.

Oncogenic KRAS2 signature 89 differentialy expressed genes (upregulated) in KrasLA mouse model that contributed maximally to the GSEA score in human data set Boston: 185 tumor, 17 normal. Ann Arbor: 85 adenocarcinoma, 10 normal Each gene is only moderately changed in human. As a collection the entire set achieves statistical significance at p < 0.05.

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  Link between signature and mutation of KRAS2

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

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

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