Affiliation:
1. The Second Affiliated Hospital, Department of Breast and Thyroid Surgery, Hengyang Medical School University of South China Hengyang Hunan China
2. Clinical Research Center for Breast and Thyroid Disease Prevention and Control in Hunan Province, Hengyang Medical School University of South China Hengyang Hunan China
Abstract
AbstractBackgroundThis study aimed to type breast cancer in relation to reactive oxygen species (ROS), clinical indicators, single nucleotide variant (SNV) mutations, functional differences, immune infiltration, and predictive responses to immunotherapy or chemotherapy, and constructing a prognostic model.MethodsWe used uniCox analysis, ConsensusClusterPlus, and the proportion of ambiguous clustering (PAC) to analyze The Cancer Genome Atlas (TCGA) data to determine optimal groupings and obtain differentially expressed ROS‐related genes. Clinical indicators were then combined with the classification results and the Chi‐square test was used to assess differences. We further examined SNV mutations, and functional differences using gene set enrichment analysis (GSEA) analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, immune cell infiltration, and response to immunotherapy and chemotherapy. A prognostic model for breast cancer was constructed using these differentially expressed genes, immunotherapy or chemotherapy responses, and survival curves. RT‐qPCR was used to detect the differences in the expression of LCE3D, CA1, PIRT and SMR3A in breast cancer cell lines and normal breast epithelial cell line.ResultsWe identified two distinct tumor types with significant differences in ROS‐related gene expression, clinical indicators, SNV mutations, functional pathways, and immune infiltration. The response to specific chemotherapy drugs and immunotherapy treatments also documented significant differences. The prognostic model constructed with 16 genes linked to survival could efficiently divide patients into high‐ and low‐risk groups. The high‐risk group showed a poorer prognosis, higher tumor purity, distinct immune microenvironment, and lower immunotherapy response. RT‐qPCR results showed that LCE3D, CA1, PIRT and SMR3A are highly expressed in breast cancer.ConclusionOur methodical examination presented an enhanced insight into the molecular and immunological heterogeneity of breast cancer. It can contribute to the understanding of prognosis and offer valuable insights for personalized treatment strategies. Further, the prognostic model can potentially serve as a powerful tool for risk stratification and therapeutic decision‐making in clinical settings.