Identification of a Six-Gene Signature for Predicting the Overall Survival of Cervical Cancer Patients.

ABSTRACT:

Background

Although the incidence of cervical cancer has decreased in recent decades with the development of human papillomavirus vaccines and cancer screening, cervical cancer remains one of the leading causes of cancer-related death worldwide. Identifying potential biomarkers for cervical cancer treatment and prognosis prediction is necessary.

Methods

Samples with mRNA sequencing, copy number variant, single nucleotide polymorphism and clinical follow-up data were downloaded from The Cancer Genome Atlas database and randomly divided into a training dataset (N=146) and a test dataset (N=147). We selected and identified a prognostic gene set and mutated gene set and then integrated the two gene sets with the random survival forest algorithm and constructed a prognostic signa

SUBMITTER: Huo X 

PROVIDER: S-EPMC7873033 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature