A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

ABSTRACT: A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as "overexpression" and "shorter survival" is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify gene

SUBMITTER: Iwata T 

PROVIDER: S-EPMC7952695 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature