Identifying prognostic signatures in the microenvironment of prostate cancer.

ABSTRACT:

Background

An increasing number of studies has indicated that the tumor microenvironment (TME), an important component of tumor tissue, has clinicopathological significance in predicting disease outcome and therapeutic efficacy. However, little evidence in prostate cancer (PCa) is available.

Methods

The cohort of TCGA-PRAD (n=477) was used in this study. Based on the proportion of 22 types of immune cells calculated by CIBERSORT, the TME was classified by K-means clustering and differentially expressed genes (DEGs) were determined. The TMEscore was calculated based on cluster signature genes, which were obtained from DEGs by the random forest method, and the samples were classified into two subtypes. Analyses of somatic mutation and copy number variation (CNVs) were further

SUBMITTER: Lu G 

PROVIDER: S-EPMC8661256 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature