Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis.

ABSTRACT:

Background

Previous studies have found that the microenvironment of cervical cancer (CESC) affects the progression and treatment of this disease. Thus, we constructed a multigene model to assess the survival of patients with cervical cancer.

Methods

We scored 307 CESC samples from The Cancer Genome Atlas (TCGA) and divided them into high and low matrix and immune scores using the ESTIMATE algorithm for differential gene analysis. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The multigene signature prognostic model was constructed by Cox analyses. Multivariate Cox analysis was applied to evaluate the significance of the multigene signature for cervical cancer prognosis. Prognosis was assessed by Kaplan-Meier curves co

SUBMITTER: Chen Q 

PROVIDER: S-EPMC7992856 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature