Cancer Genomics

The complexity of the transcriptome has been appreciated in recent years in light of the Encyclopedia of DNA Elements (ENCODE) project. While less than 3% of the genome is annotated with protein-coding genes, 62% of the genome is long RNA molecules (>200 nucleotides). With an increasing sequencing throughput and a decreasing cost, RNA sequencing (RNA-seq) is becoming a frequently used technology in transcriptome research. This chapter summarizes the advantages of RNA-seq compared to hybridization-based microarrays, the RNA-seq experiment workflow and reviews current applications of RNA-seq in the field of cancer research. With advantages in expression analysis of non-coding genes, fusion genes, investigation of expressed allelic imbalance, pseudogenes, viral integrated genes, and post-transcriptional regulation analysis including splicing, polyadenylation as well as RNA editing, RNA-seq technology has a tremendous potential to elucidate the complexity of the transcriptome and its working mechanisms in the initiation and development of cancer. Along with expression and pathway analysis, RNA-seq data can clarify the functional consequences of any potential genomic (DNA) variances and thus help to distinguish “driver” from “passenger” genomic events. In summary, RNA-seq allows a genome-wide interrogation of complex transcriptomes and will help elucidate important biological mechanisms linked to cancer phenotypes. In addition, the non-protein-coding transcriptome has the potential to provide novel biomarkers for early detection, diagnostics, prognostics and targets for therapy.