Construction of a circadian rhythm-related gene signature for predicting the prognosis and immune infiltration of breast cancer.

ABSTRACT:

Objectives

In this study, we constructed a model based on circadian rhythm associated genes (CRRGs) to predict prognosis and immune infiltration in patients with breast cancer (BC).

Materials and methods

By using TCGA and CGDB databases, we conducted a comprehensive analysis of circadian rhythm gene expression and clinicopathological data. Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. On this basis, a circadian gene prediction model about BC prognosis was constructed and validated. We also evaluated the association of the model's risk score with immune cells and immune checkpoint genes, and analyzed prognostic genes and drug sensitivity in this model.

Results

We screened 62 DEGs, in

SUBMITTER: Ni L 

PROVIDER: S-EPMC11839441 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature