Development and Validation of a Risk Prediction Model for Breast Cancer Prognosis Based on Depression-Related Genes.

ABSTRACT:

Background

Depression plays a significant role in mediating breast cancer recurrence and metastasis. However, a precise risk model is lacking to evaluate the potential impact of depression on breast cancer prognosis. In this study, we established a depression-related gene (DRG) signature that can predict overall survival (OS) and elucidate its correlation with pathological parameters and sensitivity to therapy in breast cancer.

Methods

The model training and validation assays were based on the analyses of 1,096 patients from The Cancer Genome Atlas (TCGA) database and 2,969 patients from GSE96058. A risk signature was established through univariate and multivariate Cox regression analyses.

Results

Ten DRGs were determined to construct the risk signature. Multivariate

SUBMITTER: Wang X 

PROVIDER: S-EPMC9128552 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature