PLoS ONE (Jan 2014)

Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

  • Yuichi Shiraishi,
  • Akihiro Fujimoto,
  • Mayuko Furuta,
  • Hiroko Tanaka,
  • Ken-ichi Chiba,
  • Keith A Boroevich,
  • Tetsuo Abe,
  • Yoshiiku Kawakami,
  • Masaki Ueno,
  • Kunihito Gotoh,
  • Shun-ichi Ariizumi,
  • Tetsuo Shibuya,
  • Kaoru Nakano,
  • Aya Sasaki,
  • Kazuhiro Maejima,
  • Rina Kitada,
  • Shinya Hayami,
  • Yoshinobu Shigekawa,
  • Shigeru Marubashi,
  • Terumasa Yamada,
  • Michiaki Kubo,
  • Osamu Ishikawa,
  • Hiroshi Aikata,
  • Koji Arihiro,
  • Hideki Ohdan,
  • Masakazu Yamamoto,
  • Hiroki Yamaue,
  • Kazuaki Chayama,
  • Tatsuhiko Tsunoda,
  • Satoru Miyano,
  • Hidewaki Nakagawa

DOI
https://doi.org/10.1371/journal.pone.0114263
Journal volume & issue
Vol. 9, no. 12
p. e114263

Abstract

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Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV)-related hepatocellular carcinomas (HCCs) and their matched controls. Comparison of whole genome sequence (WGS) and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3), and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.