PLoS ONE (Jan 2014)

Genetic mutation analysis of human gastric adenocarcinomas using ion torrent sequencing platform.

  • Zhi Xu,
  • Xinying Huo,
  • Hua Ye,
  • Chuanning Tang,
  • Vijayalakshmi Nandakumar,
  • Feng Lou,
  • Dandan Zhang,
  • Haichao Dong,
  • Hong Sun,
  • Shouwen Jiang,
  • Guangchun Zhang,
  • Zhiyuan Liu,
  • Zhishou Dong,
  • Baishuai Guo,
  • Yan He,
  • Chaowei Yan,
  • Lu Wang,
  • Ziyi Su,
  • Yangyang Li,
  • Dongying Gu,
  • Xiaojing Zhang,
  • Xiaomin Wu,
  • Xiaowei Wei,
  • Lingzhi Hong,
  • Yangmei Zhang,
  • Jinsong Yang,
  • Yonglin Gong,
  • Cuiju Tang,
  • Lindsey Jones,
  • Xue F Huang,
  • Si-Yi Chen,
  • Jinfei Chen

DOI
https://doi.org/10.1371/journal.pone.0100442
Journal volume & issue
Vol. 9, no. 7
p. e100442

Abstract

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Gastric cancer is the one of the major causes of cancer-related death, especially in Asia. Gastric adenocarcinoma, the most common type of gastric cancer, is heterogeneous and its incidence and cause varies widely with geographical regions, gender, ethnicity, and diet. Since unique mutations have been observed in individual human cancer samples, identification and characterization of the molecular alterations underlying individual gastric adenocarcinomas is a critical step for developing more effective, personalized therapies. Until recently, identifying genetic mutations on an individual basis by DNA sequencing remained a daunting task. Recent advances in new next-generation DNA sequencing technologies, such as the semiconductor-based Ion Torrent sequencing platform, makes DNA sequencing cheaper, faster, and more reliable. In this study, we aim to identify genetic mutations in the genes which are targeted by drugs in clinical use or are under development in individual human gastric adenocarcinoma samples using Ion Torrent sequencing. We sequenced 737 loci from 45 cancer-related genes in 238 human gastric adenocarcinoma samples using the Ion Torrent Ampliseq Cancer Panel. The sequencing analysis revealed a high occurrence of mutations along the TP53 locus (9.7%) in our sample set. Thus, this study indicates the utility of a cost and time efficient tool such as Ion Torrent sequencing to screen cancer mutations for the development of personalized cancer therapy.