A Circadian Rhythm-related Signature to Predict Prognosis, Immune Infiltration, and Drug Response in Breast Cancer

  • 0Department of Medical Genetics, School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.

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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.