Identify cancer survival related mutation genes from integrated TCGA datasets

Abstract

Several large-scale human cancer genomics projects such as TCGA offered huge genomic and clinical data for researchers to obtain meaningful genomics alterations which intervene in the development and metastasis of tumors. The object of this study was to identify associations of mutation genes and survival time by linking these genomic features to clinical outcome. Based on the TCGA dataset, this study developed a website called TCGA4U which provides a visualization solution to illustrate the relationship of these genomics alternations with clinical data. Through integrating somatic mutation data and follow up data of three cancer types in TCGA, this study identified several somatic mutations which impact patient survival with statistical significance. These identified mutation genes have the potential to be used as new cancer biomarkers in clinical to predict the survival of patients.