Correlation between Ferroptosis-Related Gene Signature and Immune Landscape, Prognosis in Breast Cancer.
Jiahao ZhuQingqing ChenKe GuYou MengShengjun JiYutian ZhaoBo YangPublished in: Journal of immunology research (2022)
Breast cancer (BC) is the most commonly diagnosed cancer and second leading cause of cancer-related death in women worldwide. Ferroptosis, an iron-dependent newly discovered mode of cell death, can be induced by lenaltinib and plays an important role in the biological behaviors of BC. Therefore, the prognostic value of ferroptosis-related genes (FRGs) in BC warrants further investigation. FRG expression profiles and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO). Immune-related pathways were found in the functional analysis. Significant differences in enrichment scores for immune cells were observed. Some patients from TCGA-BRCA were included as the training cohort. A six-gene prediction signature was constructed with the least absolute shrinkage and selection operator Cox regression. This model was validated in the rest of the TCGA-BRCA and GEO cohort. The expressions of the six FRGs were verified with real-time quantitative polymerase chain reaction and immunohistochemistry in the Human Protein Atlas. Relapse or metastasis was more likely in the high-risk group. Risk score was an independent predictor of disease-free survival. Collectively, the ferroptosis-related risk model established in this study may serve as an effective tool to predict the prognosis in BC.
Keyphrases
- cell death
- free survival
- gene expression
- breast cancer risk
- papillary thyroid
- single cell
- genome wide
- cell cycle arrest
- end stage renal disease
- dna methylation
- squamous cell
- endothelial cells
- copy number
- newly diagnosed
- ejection fraction
- chronic kidney disease
- squamous cell carcinoma
- type diabetes
- high resolution
- metabolic syndrome
- wastewater treatment
- prognostic factors
- cell proliferation
- big data
- pregnant women
- patient reported outcomes
- skeletal muscle
- young adults
- lymph node metastasis
- small molecule
- deep learning
- induced pluripotent stem cells
- genome wide identification
- artificial intelligence