An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer

Academic Article

Abstract

  • Cancer genomes contain many aberrant gene fusionsa few that drive disease and many more that are nonspecific passengers. We developed an algorithm (the concept signature or 'ConSig' score) that nominates biologically important fusions from high-throughput data by assessing their association with 'molecular concepts' characteristic of cancer genes, including molecular interactions, pathways and functional annotations. Copy number data supported candidate fusions and suggested a breakpoint principle for intragenic copy number aberrations in fusion partners. By analyzing lung cancer transcriptome sequencing and genomic data, we identified a novel R3HDM2-NFE2 fusion in the H1792 cell line. Lung tissue microarrays revealed 2 of 76 lung cancer patients with genomic rearrangement at the NFE2 locus, suggesting recurrence. Knockdown of NFE2 decreased proliferation and invasion of H1792 cells. Together, these results present a systematic analysis of gene fusions in cancer and describe key characteristics that assist in new fusion discovery.
  • Published In

    Digital Object Identifier (doi)

    Author List

  • Wang XS; Prensner JR; Chen G; Cao Q; Han B; Dhanasekaran SM; Ponnala R; Cao X; Varambally S; Thomas DG
  • Start Page

  • 1005
  • End Page

  • 1011
  • Volume

  • 27
  • Issue

  • 11