A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients.
Haifeng LiLu LiCong XueRiqing HuangAnqi HuXin AnYanxia ShiPublished in: Biology (2021)
Breast cancer is the second leading cause of death in women, thus a reliable prognostic model for overall survival (OS) in breast cancer is needed to improve treatment and care. Ferroptosis is an iron-dependent cell death. It is already known that siramesine and lapatinib could induce ferroptosis in breast cancer cells, and some ferroptosis-related genes were closely related with the outcomes of treatments regarding breast cancer. The relationship between these genes and the prognosis of OS remains unclear. The data of gene expression and related clinical information was downloaded from public databases. Based on the TCGA-BRCA cohort, an 8-gene prediction model was established with the least absolute shrinkage and selection operator (LASSO) cox regression, and this model was validated in patients from the METABRIC cohort. Based on the median risk score obtained from the 8-gene model, patients were stratified into high- or low-risk groups. Cox regression analyses identified that the risk score was an independent predictor for OS. The findings from CIBERSORT and ssGSEA presented noticeable differences in enrichment scores for immune cells and pathways between the abovementioned two risk groups. To sum up, this prediction model has potential to be widely applied in future clinical settings.
Keyphrases
- cell death
- end stage renal disease
- gene expression
- genome wide
- newly diagnosed
- chronic kidney disease
- ejection fraction
- healthcare
- peritoneal dialysis
- prognostic factors
- breast cancer risk
- cell cycle arrest
- palliative care
- dna methylation
- young adults
- big data
- polycystic ovary syndrome
- cell proliferation
- drug induced
- weight loss
- genome wide analysis
- health insurance
- climate change
- positive breast cancer
- affordable care act
- combination therapy
- glycemic control
- metastatic breast cancer