Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer.

ABSTRACT:

Background

DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods

The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic mark

SUBMITTER: Tu J 

PROVIDER: S-EPMC9249661 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature