Exploration of the cancers association based on somatic data in TCGA
As the widely development of Next-generation sequencing (NGS), many studies conducted the somatic data analysis of cancers, which provides the valuable information for understanding cancer incidence and progression. In this paper, we conducted a somatic data analysis for eight cancers, they are: Glioblastoma Multiforme, Head and Neck squamous cell carcinoma, Kidney renal clear cell carcinoma (Kirc), Lung Adenocarcinoma (Luad), Lung squamous cell carcinoma (Lusc), Ovarian Cancer (Ov), Skin Cutaneous Melanoma (Skcm) and Thyroid carcinoma (Thca). We explored the potential association between these cancers based on the somatic signatures identification and the association rules analysis. We found that TTN, TP53, CSMD3, MUC16 and PCDHGC5 were genes haboring the highest mutations ratio for eight cancers. Furthermore, we found the potential association among Hnsc, Skcm and Luad using association rules method. Some evidences have approved the common risk factors and molecular abnormalities in cell-cycle regulation and signal transduction predominate among these three cancers. Our analysis might help shed light on the links between different cancers as a whole.
Somatic Data Cancers Association TCGA
Hong Xia Lin Hua WeiYing Zheng Ping Zhou
School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China;Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China
国际会议
重庆
英文
465-473
2015-12-18（万方平台首次上网日期，不代表论文的发表时间）