Wei Runmin, De Vivo Immaculata, Huang Sijia, Zhu Xun, Risch Harvey, Moore Jason H, Yu Herbert, Garmire Lana X
Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa, Honolulu, HI, USA.
Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
Oncotarget. 2016 Aug 23;7(34):55249-55263. doi: 10.18632/oncotarget.10509.
Endometrial Cancer (EC) is one of the most common female cancers. Genome-wide association studies (GWAS) have been investigated to identify genetic polymorphisms that are predictive of EC risks. Here we utilized a meta-dimensional integrative approach to seek genetically susceptible pathways that may be associated with tumorigenesis and progression of EC. We analyzed GWAS data obtained from Connecticut Endometrial Cancer Study (CECS) and identified the top 20 EC susceptible pathways. To further verify the significance of top 20 EC susceptible pathways, we conducted pathway-level multi-omics analyses using EC exome-Seq, RNA-Seq and survival data, all based on The Cancer Genome Atlas (TCGA) samples. We measured the overall consistent rankings of these pathways in all four data types. Some well-studied pathways, such as p53 signaling and cell cycle pathways, show consistently high rankings across different analyses. Additionally, other cell signaling pathways (e.g. IGF-1/mTOR, rac-1 and IL-5 pathway), genetic information processing pathway (e.g. homologous recombination) and metabolism pathway (e.g. sphingolipid metabolism) are also highly associated with EC risks, diagnosis and prognosis. In conclusion, the meta-dimensional integration of EC cohorts has suggested some common pathways that may be associated from predisposition, tumorigenesis to progression.
子宫内膜癌（EC）是最常见的女性癌症之一。全基因组关联研究（GWAS）已被用于识别可预测EC风险的基因多态性。在此，我们采用元维度整合方法来寻找可能与EC发生和进展相关的遗传易感性通路。我们分析了从康涅狄格州子宫内膜癌研究（CECS）获得的GWAS数据，并确定了前20条EC易感通路。为了进一步验证前20条EC易感通路的重要性，我们使用基于癌症基因组图谱（TCGA）样本的EC外显子组测序、RNA测序和生存数据进行了通路水平的多组学分析。我们测量了所有四种数据类型中这些通路的总体一致排名。一些经过充分研究的通路，如p53信号通路和细胞周期通路，在不同分析中显示出始终较高的排名。此外，其他细胞信号通路（如IGF-1/mTOR、rac-1和IL-5通路）、遗传信息处理通路（如同源重组）和代谢通路（如鞘脂代谢）也与EC风险、诊断和预后高度相关。总之，EC队列的元维度整合揭示了一些可能与从易感性、肿瘤发生到进展相关的共同通路。
