Prognostic signature of ovarian cancer based on 14 tumor microenvironment-related genes.

ABSTRACT:

Background

Ovarian cancer is one of the lethal gynecological diseases in women. However, using tumor microenvironment related genes to identify prognostic signature of ovarian cancer has not been discussed in detail.

Methods

The mRNA profiles of 386 ovarian cancer patients were retrieved from The Cancer Genome Atlas. Univariate Cox regression and LASSO Cox regression analyses were performed and 14 optimized prognostic genes related to tumor microenvironment were identified.

Results

The multivariate Cox hazards regression showed risk score was an independent prognostic signature for ovarian cancer. Nomogram model could reliably predict the patients' survival. Furthermore, M1 macrophages, M2 macrophages, and follicular helper T cells, differentially expressed between th

SUBMITTER: Nie X 

PROVIDER: S-EPMC8284754 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature