Prognostic value of a circadian rhythm-related gene signature in breast cancer patients: A retrospective cohort study
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a prognostic signature using circadian rhythm-related genes (CRRGs) to predict breast cancer (BRCA) survival. A 9-gene subset demonstrated superior accuracy in identifying high-risk patients for improved clinical management.
Area Of Science
- Oncology
- Genetics
- Chronobiology
Background
- Breast cancer (BRCA) is the most prevalent cancer globally, posing significant morbidity and mortality challenges.
- Circadian rhythm disruption is increasingly recognized for its role in cancer progression and patient outcomes.
Purpose Of The Study
- To develop and validate a prognostic signature based on circadian rhythm-related genes (CRRGs) for predicting BRCA patient survival.
- To identify key CRRGs that can serve as novel biomarkers for risk stratification in breast cancer.
Main Methods
- Utilized gene expression and clinical data from GEO, TCGA, and MSigDB databases.
- Constructed a multigene prognostic signature using LASSO-penalized Cox regression and validated it with ROC curves and Kaplan-Meier analysis.
- Assessed pathway activity using gene set variation analysis (GSVA).
Main Results
- A 20-CRRG prognostic signature effectively stratified BRCA patients into high- and low-risk groups (K-M P < .05) with high predictive accuracy (AUC > 0.7).
- A refined 9-gene subset (ADRB1, BHLHE41, BTG1, EGR3, NONO, NR1H3, NTRK3, OPN4, PIGF) showed superior 5-year survival prediction (AUC 0.82).
- Enrichment analysis linked CRRGs to circadian regulation, nuclear components, and DNA binding.
Conclusions
- The CRRG-based prognostic signature, especially the 9-gene subset, robustly predicts BRCA patient survival.
- This signature offers potential clinical utility for long-term prognosis and risk stratification in breast cancer patients.
- Highlights the significant role of circadian rhythms in BRCA progression and identifies novel biomarkers.
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