Identification of driver genes contributes to the understanding of cancer etiology and is imperative for the development of individualized therapies. Gene amplification is a major event in oncogenesis. Driver genes with tumor-specific amplification-dependent overexpression can be therapeutic targets. In this study, we aimed to identify amplification-dependent driver genes in 1,454 solid tumors, across more than 15 cancer types, by integrative analysis of gene expression and copy number. Amplification-dependent overexpression of 64 known driver oncogenes were found in 587 tumors (40%); genes frequently observed were MYC (25%) and MET (18%) in colorectal cancer; SKP2 (21%) in lung squamous cell carcinoma; HIST1H3B (19%) and MYCN (13%) in liver cancer; KIT (57%) in gastrointestinal stromal tumors; and FOXL2 (12%) in squamous cell carcinoma across tissues. Genomic aberrations in 138 known cancer driver genes and 491 established fusion genes were found in 1,127 tumors (78%). Further analyses of 820 cancer-related genes revealed 16 as potential driver genes, with amplification-dependent overexpression restricted to the remaining 22% of samples (327 tumors) initially undetermined genetic drivers. Among them, AXL, which encodes a receptor tyrosine kinase, was recurrently overexpressed and amplified in sarcomas. Our studies of amplification-dependent overexpression identified potential drug targets in individual tumors.
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Next-generation DNA sequencing (NGS) of the genomes of cancer cells is contributing to new discoveries that illuminate the mechanisms of tumorigenesis. To this end, the International Cancer Genome Consortium and The Cancer Genome Atlas are investigating novel alterations of genes that will define the pathways and mechanisms of the development and growth of cancers. These efforts contribute to the development of innovative pharmaceuticals as well as to the introduction of genome sequencing as a component of personalized medicine. In particular, chromosomal translocations that fuse coding sequences serve as important pharmaceutical targets and diagnostic markers given their association with tumorigenesis. Although increasing numbers of fusion genes are being discovered using NGS, the methodology used to identify such fusion genes is complicated, expensive, and requires relatively large samples. Here, to address these problems, we describe the design and development of a panel of 491 fusion genes that performed well in the analysis of cultured human cancer cell lines and 600 clinical tumor specimens.
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