Title:A Circadian Rhythm-related Signature to Predict Prognosis,
Immune Infiltration, and Drug Response in Breast Cancer
Volume: 32
Issue: 3
Author(s): Mingyu Chu, Jing Huang, Qianyu Wang, Yaqun Fang, Dina Cui and Yucui Jin*
Affiliation:
- Department of Medical Genetics, School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian
Avenue, Nanjing, 211166, China
- Jiangsu Key Laboratory of Xenotransplantation, School of Basic
Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
Keywords:
CRRGs, breast cancer, prognostic signature, therapeutic response, tumor microenvironment, biomarkers.
Abstract:
Purpose: Circadian rhythm-related genes (CRRGs) play essential roles in cancer
occurrence and development. However, the prognostic significance of CRRGs in
breast cancer (BC) has not been fully elucidated. Our study aimed to develop a prognostic
gene signature based on CRRGs that can accurately and stably predict the prognosis
of BC.
Methods: The transcriptome data and clinical information for BC patients were obtained
from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.
A consensus unsupervised clustering analysis was carried out to investigate the roles
of CRRGs in BC. A CRRGs-related prognostic risk model was established by using logistic
least absolute shrinkage and selection operator (LASSO) Cox regression and univariate
Cox regression analyses. Kaplan-Meier (KM) curves analysis, time-dependent receptor
operation characteristics (ROC) curves analysis, and nomogram were plotted to
evaluate the predictive efficacy of the model. The relevance of risk score to the immune
cell infiltration, tumor burden mutation (TMB), and therapeutic response was assessed.
Results: A risk model comprising six CRRGs (SLC44A4, SLC16A6, TPRG1, FABP7,
GLYATL2, and FDCSP) was constructed and validated, demonstrating an effective predictor
for the prognosis of BC. The low-risk group displayed a higher expression of immune
checkpoint genes and a lower burden of tumor mutation. Additionally, drug sensitivity
analysis demonstrated that the prognostic signature may serve as a potential chemosensitivity
predictor.
We established a CRRGs-related risk signature, which is of great value in
predicting the prognosis of patients with BC and guiding the treatment for BC..
