| Literature DB >> 26857262 |
Xiangchun Li1, William K K Wu2, Rui Xing3, Sunny H Wong4, Yuexin Liu5, Xiaodong Fang6, Yanlin Zhang7, Mengyao Wang6, Jiaqian Wang6, Lin Li6, Yong Zhou6, Senwei Tang4, Shaoliang Peng8, Kunlong Qiu6, Longyun Chen6, Kexin Chen5, Huanming Yang6, Wei Zhang9, Matthew T V Chan10, Youyong Lu3, Joseph J Y Sung4, Jun Yu11.
Abstract
Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as molecular classifiers or prognostic markers of disease outcome has yet to be established. In this study, we integrated somatic mutational profiles and clinicopathologic information from 544 gastric cancer patients from previous genomic studies to identify significantly mutated genes (SMG) with prognostic relevance. Gastric cancer patients were classified into regular (86.8%) and hypermutated (13.2%) subtypes based on mutation burden. Notably, TpCpW mutations occurred significantly more frequently in regular, but not hypermutated, gastric cancers, where they were associated with APOBEC expression. In the former group, six previously unreported (XIRP2, NBEA, COL14A1, CNBD1, ITGAV, and AKAP6) and 12 recurrent mutated genes exhibited high mutation prevalence (≥3.0%) and an unexpectedly higher incidence of nonsynonymous mutations. We also identified two molecular subtypes of regular-mutated gastric cancer that were associated with distinct prognostic outcomes, independently of disease staging, as confirmed in a distinct patient cohort by targeted capture sequencing. Finally, in diffuse-type gastric cancer, CDH1 mutation was found to be associated with shortened patient survival, independently of disease staging. Overall, our work identified previously unreported SMGs and a mutation signature predictive of patient survival in newly classified subtypes of gastric cancer, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping. Cancer Res; 76(7); 1724-32. ©2016 AACR. ©2016 American Association for Cancer Research.Entities:
Mesh:
Year: 2016 PMID: 26857262 DOI: 10.1158/0008-5472.CAN-15-2443
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701