Abstract 2017: Key pathways that are altered at both gene copy number and transcript levels in ovarian cancer: An integrated analysis of TCGA data

Abstract

Abstract Background One of the three cancer types that have been systematically examined at genomic and epigenomic levels by The Cancer Genome Atlas (TCGA) program is ovarian cancer, which represents a major health issue for women world-wide. Currently, a major challenge is to interrogate the vast amount of raw data to reveal fundamental knowledge regarding the etiology of these cancers. One of our goals is to identify genes and pathways that are jointly altered in terms of both gene copy number and transcript levels. We hypothesize that these genes and pathways represent the critical genomic and transcriptomic events that are important for cancer maintenance. Method Paired array Comparative Genomic Hybridization (aCGH) and transcriptome data from 345 ovarian cancer samples were obtained from TCGA. The majority of these tumors (263) are grade 3 serous adenocarcinoma. Both expression and aCGH data were lowess normalized and aCGH data further subjected to the circular binary segmentation (CBS) algorithm. Spearman's rank correlation (Rho) was computed on 15,553 genes detected for both aCGH and expression array to investigate the association between copy number and expression in the 345 ovarian tumor samples. The genes were then ranked based on Rho and significantly enriched pathways were indentified with highly ranked genes using gene set enrichment analysis (GSEA) algorithm in 380 pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta databases. Result Among the 15,553 genes, 5,486 genes in the cytobands of 19p13.11-p13.2, 8q24.3, 4p16.3, 16p13.3, 15q22.31, 12q24.31 and 10q24.32 exhibited high gene dosage-expression correlations (FDR < 0.1%, Rho > 0.4). Among the 5,486 dosage sensitive genes, 142 were pre-defined as cancer genes in Cancer Gene Census database. These genes include BRCA2 (Correlation P< 5.65E-18), PIK3CA (P<5.44E-37), PTEN (P<1.30E-24), AKT1 (P<1.33E-33), AKT2 (P<6.78E-17), MSH6 (P<1.18E-16), STK11 (P<6.47E-18), MLH1 (P<1.23E-24), MSH2 (P<2.63E-20), KRAS (P < 8.33E-39), and NF1 (P<2.56E-19). Further GSEA pathway analysis revealed a number of cancer related pathways that were highly enriched with dosage sensitive genes. These pathways included PI3K/Akt/mTOR pathway, Wnt-signal pathway, MAPK pathway, VEGF pathway, RAS pathway, and insulin signaling pathway. Conclusion Our integrated analysis of gene copy number and transcriptome data of ovarian cancer data in TCGA revealed key pathways that may be critical for ovarian cancer development and maintenance. Further analyses incorporating other information, including clinical data, will shed further light on the genetic and molecular basis of ovarian cancer pathophysiology and help identify the key targets for therapeutic intervention. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2017.