Establishment and evaluation of novel prognostic biomarkers based on systemic coagulation-inflammation index and related genes in breast cancer

Abstract

Background Coagulation and inflammation play crucial roles in the initiation and progression of cancer, and they exhibit a synergistic effect. However, a hematological biomarker and risk model based on coagulation and inflammatory have not yet been established in breast cancer. Methods This study retrospectively analyzed 749 breast cancer patients at our institution. We established a coagulation-inflammation-related genes (CIRGs) risk model using the TCGA-BRCA dataset as the training set and GEO datasets (GSE20685, GSE21653) as the testing sets. Immunohistochemical staining was performed on tumor tissues to validate protein-level expression of key genes. Additionally, single-cell RNA sequencing (scRNA-seq) was applied to investigate the expression of the CIRGs and explore intercellular communication differences. Results All enrolled cases were stratified by median systemic coagulation-inflammation index (SCI) into high- and low-SCI groups. The low-SCI group had longer disease-free survival and overall survival than the high-SCI group, with higher SCI levels noted in triple-negative breast cancer (TNBC). SCI exhibited a linear correlation with survival outcomes and superior survival predictive performance compared to the platelet-to-lymphocyte ratio. LASSO regression selected 21 prognosis-related CIRGs to construct a prognostic model, which showed robust predictive efficacy across three datasets. Tumor microenvironment analysis indicated that the high-risk group was associated with immune suppression. Drug sensitivity analysis identified 6 potential candidate drugs for low- and high-risk groups. Four hub genes (ABCA1, IL1R1, SERPINE1, and HPN) were identified among CIRGs, showing strong correlations with tumor stage and prognosis. scRNA-seq analysis revealed high expression of the CIRGs in myeloid, endothelial, and epithelial cells, with higher AUCell scores of the CIRGs in TNBC. Significant intercellular communication differences were observed between the two risk groups, especially in fibroblast/endothelial cell-to-T/B cell signaling pathways. Conclusion This study deeply explores the roles and clinical significance of coagulation and inflammation in breast cancer. The hematological indicator SCI and the CIRGs risk model can serve as reliable biomarkers for breast cancer personalized treatment.