Abstract B177: The use of Oncotest molecular database to identify amplified and overexpressed drug target genes.

Abstract

Abstract Background: Carcinogenesis is characterized by complex genomic rearrangements including gene copy number variations, gene fusions or somatic mutations and may contribute to tumor progression. Increased gene copy number is one of the mechanisms shown to cause over-expression and over-activation of genes and signaling pathways involved in tumor progression. Such alterations offer a rationale to develop drugs specifically blocking these over-expressed genes. Recently, we characterized more than 250 patient-derived tumor xenografts in nude mice on DNA, RNA and protein levels using high throughput technologies. In the present study, we used this database to identify putative target genes that are amplified and over-expressed in our tumor models. Method: A total of 176 patient-derived tumor models representing 26 tumor types have been investigated. DNA was analyzed using Affymetrix genome wide SNP6.0 arrays and RNA transcripts by Affymetrix HGU-133 plus 2.0 arrays. Analysis was done using R-based statistical tools and Pathway Studio. Gene variations were considered relevant when having an increased gene copy number equal to 4 and log of signal intensity from microarray higher than 12. Result: The DNA analysis of the 176 tumor models allowed identification of a total of 2003 different genomic regions with a copy number gain equal to 4. The median number of genomic regions with copy number gains is 15 per tumor model but was shown to greatly vary between tumor types (colon tumors having the lowest median number ∼ 5). The genomic region gains were observed frequently for chromosomes 3, 5, 8, 17 and 18. The size of the 2003 regions with increase copy number gain varied from 100kb to 89mb and included a total of 16.558 protein coding sequences coding. Transcript analysis using Affymetrix data revealed that among these 16.558 coding sequences, 1609 (10%) have a log2 intensity signal above 12 and were considered over-expressed. The pathway studio analysis revealed genes coding for proteins with trans-membrane domain, receptors, kinases and oncogenes. As expected, we identified tumor models with amplified regions containing overexpressed growth factors or receptors such as AREG, EGFR, HER2, c-Met and FGFR1. The analysis also showed new amplified and over-expressed genes associated with cellular growth. These may be putative drug targets. Conclusion: In the present study, we showed that our patient-derived tumor xenograft panel contains representative tumor models with well know amplified and over-expressed genes. The analysis also revealed tumor models with new drug targets genes. The strategies of blocking them at RNA or protein level in appropriate tumor models could contribute to identification of new drugs. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B177.