Abstract
Abstract Many evidences report that alternative splicing, the mechanism producing mRNAs and proteins with different structures and functions from the same gene, is altered in cancer cells. Thus, the identification and characterization of cancer-specific splice variants may give large impulse to the discovery of novel diagnostic and prognostic tumor biomarkers, as well as of new targets for more selective and effective therapies. We developed novel and effective computational tools for performing a genome-wide analysis of the alternative splicing pattern of human genes using both exon array and RNA-Seq data. Notably, we sought to identify “cassette exon” generated by exon skipping differentially expressed in the tumor and normal conditions. To this aim we analyzed data obtained by exon array hybridization from clear cell renal carcinoma (ccRC) and colorectal cancer (CRC) samples as well as from the corresponding normal controls. Furthermore, high-throughput transcriptome sequencing from CRC and control samples were also analyzed. By using our computational strategy we identified several cassette exons differentially expressed in the tumoral and normal conditions. In order to test the effectiveness of our computational strategy, we experimentally verified the occurrence of tumor- and normal-specific cassette exons by RT-qPCR assay. Remarkably, we were able to confirm “in vivo” the differential expression of these predicted cassette exons in patients affected by CRC and ccRC. This study presents a novel computational methodology for the identification of tumor-associated transcript variants to be used as cancer molecular biomarkers, provides its experimental validation, and reports specific candidate biomarkers for CRC and ccRC. Citation Format: Alessio Valletti, Orazio Palumbo, Mattia D'Antonio, Tiziana Castrignano, Margherita Gigante, Massimo Carella, Ernesto Picardi, Anna Maria D'Erchia, Elena Ranieri, Graziano Pesole. Identification of tumor-associated cassette exons in human cancer through exon-array and RNA-Seq data analysis. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA06.
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