A Circadian Rhythm-related Signature to Predict Prognosis, Immune Infiltration, and Drug Response in Breast Cancer
- Mingyu Chu 1, Jing Huang 1, Qianyu Wang 1, Yaqun Fang 1, Dina Cui 1, Yucui Jin 1,2
- Mingyu Chu 1, Jing Huang 1, Qianyu Wang 1
- 1Department of Medical Genetics, School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.
- 2Jiangsu Key Laboratory of Xenotransplantation, School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.
- 0Department of Medical Genetics, School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a six-gene signature based on circadian rhythm-related genes (CRRGs) to predict breast cancer (BC) prognosis. The signature accurately forecasts patient outcomes and may guide treatment strategies.
Area Of Science
- Oncology
- Genetics
- Chronobiology
Background
- Circadian rhythm-related genes (CRRGs) are implicated in cancer development.
- The prognostic value of CRRGs in breast cancer (BC) requires further investigation.
Purpose Of The Study
- To develop and validate a prognostic gene signature using CRRGs for breast cancer.
- To assess the signature's predictive accuracy and stability in BC prognosis.
Main Methods
- Utilized The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets for BC transcriptome and clinical data.
- Employed consensus unsupervised clustering and LASSO Cox regression to build a CRRGs-related risk model.
- Validated the model using Kaplan-Meier curves, ROC analysis, and nomograms; assessed correlations with immune infiltration, tumor mutation burden (TMB), and drug sensitivity.
Main Results
- A robust six-gene signature (SLC44A4, SLC16A6, TPRG1, FABP7, GLYATL2, FDCSP) was constructed and validated for BC prognosis.
- The low-risk group showed higher immune checkpoint gene expression and lower TMB.
- The signature demonstrated potential as a chemosensitivity predictor.
Conclusions
- A novel CRRGs-based risk signature effectively predicts breast cancer prognosis.
- This signature holds significant value for guiding clinical treatment decisions in BC patients.
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