Tumor microenvironment characterization in cervical cancer identifies prognostic relevant gene signatures.

ABSTRACT:

Objective

The aim of this study is to systematically analyze the transcriptional sequencing data of cervical cancer (CC) to find an Tumor microenvironment (TME) prognostic marker to predict the survival of CC patients.

Methods

The expression profiles and clinical follow-up information of CC were downloaded from the TCGA and GEO. The RNA-seq data of TCGA-CESC samples were used for CIBERSORT analysis to evaluate the penetration pattern of TME in 285 patients, and construct TMEscore. Other data sets were used to validate and evaluate TMEscore model. Further, survival analysis of TMEscore related DEGs was done to select prognosis genes. Functional enrichment and PPI networks analysis were performed on prognosis genes.

Results

The TMEscore model has relatively good results

SUBMITTER: Peng L 

PROVIDER: S-EPMC8075229 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature