Abstract A207: Whole transcriptome profiling in upper aerodigestive tract cancers

Abstract

Abstract Background: RNA-seq is a powerful technology that allows to obtain sequence and expression information simultaneously. We applied this technology to 4 upper aerodigestive tract cancers. Methods: RNA from four upper aerodigestive tract tumor specimens was extracted and sequencing libraries constructed. Samples were analyzed using an Illumina Genome Analyzer with a paired end module (36 or 54 base read length). Raw data was processed with a proprietary data pipeline. Potential mutations were filtered using both in house and external bioinformatic solutions, involving previously established databases of mutations (COSMIC) and SNPs (dbSNP), and removal of ancestral alleles identified from multiple sequence alignments. These SNPs were then parsed via in house scripts to determine whether the SNPs were present in coding regions, 3′UTR, 5′UTR, or in splice acceptor/donor sites. The coding SNPs were further parsed to determine which SNPs result in non-synonymous changes. RNA-Seq expression data was analyzed using Partek Genomics Suite and compared to microarray based expression data. Pathway analysis was performed using GeneGO Metacore and DAVID. Results: 500Mb to 2GB of data were obtained per sample. Between 700 and 2000 nsSNPs were identified, as well as a large number of alteration in the 3′ and 5′ untranslated regions. Genetic alterations in several commonly mutated genes were identified including TP53, ErbB2, H-RAS, and Cyclin D1. SNPs were enriched in pathways commonly involved in upper aerodigestive tract tumors including cell cycle control, cytoskeleton, and receptor tyrosine kinases. Furthermore we screened for viral sequences identifying one sample that was HPV16 positive. RNA-seq based and microarray based expression data generally correlated, but significant differences were also observed, that were at least partly due to the limited number of RNA-seq reads. Conclusion: Cancer transcriptome sequencing is a promising and cost effective approach for identifying mutations and obtaining expression analysis simultaneously. Transcriptome sequencing holds promise as a readily available platform for assessing potential treatment targets in a specific tumor. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A207.