Abstract
The identification of novel biomarkers in cancer patients often requires both survival and gene expression analyses. The Kaplan-Meier survival analysis is one of the most common methods to assess the fraction of subjects living for a certain amount of time.Here, we describe a method for researchers to identify potential prognostic markers across distinct tumor types. We utilize The Cancer Genome Atlas (TCGA) as this is one of the most extensive and successful cancer genomics programs to date that includes expression data and clinical follow-up information for up to 33 distinct tumor types. Nevertheless, the method described here can also be applied to any open-source dataset where the RNA expression and clinical outcome are provided.We provide detailed practical instructions and advices for investigators to be able to successfully identify prognostic markers in cancer patients.
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