The landscape of kinase fusions in cancer

TLDR

Human cancer genomes harbor diverse alterations that deregulate key pathways, yet gene fusions have been less extensively characterized. The study aims to develop heuristics for reliably detecting gene fusion events in RNA‑seq data and apply them to nearly 7,000 TCGA samples. The authors applied these heuristics to nearly 7,000 TCGA RNA‑seq samples to identify gene fusions. The analysis uncovered several novel and recurrent kinase fusions, many of which have immediate clinical relevance due to existing approved or experimental drugs.

Abstract

Abstract Human cancer genomes harbour a variety of alterations leading to the deregulation of key pathways in tumour cells. The genomic characterization of tumours has uncovered numerous genes recurrently mutated, deleted or amplified, but gene fusions have not been characterized as extensively. Here we develop heuristics for reliably detecting gene fusion events in RNA-seq data and apply them to nearly 7,000 samples from The Cancer Genome Atlas. We thereby are able to discover several novel and recurrent fusions involving kinases. These findings have immediate clinical implications and expand the therapeutic options for cancer patients, as approved or exploratory drugs exist for many of these kinases.