biostudies-literatureUnknown11Lei C<h4>Objective</h4>Breast cancer is highly heterogeneous, presenting challenges in prognostic assessment. Developing a universally applicable prognostic model could simplify clinical decision-making. This study aims to develop and validate a novel breast cancer prognosis model using coagulation-related genes with broad clinical applicability.<h4>Methods</h4>A total of 203 genes related to coagulation were obtained from the KEGG database, and the mRNA data of 1,099 tumor tissue samples and 572 samples of normal tissue were retrieved from the TCGA-BRCA cohort and GTEx databases. The R package "limma" was utilized to detect variations in gene expression related to coagulation between the malignancies and normal tissue. A model was constructed in the TCGA cohort through a multivariable Cox regrFrontiers in molecular biosciences1394585https://www.ebi.ac.uk/biostudies/studies/S-EPMC11094261biostudies-literatureUnraveling breast cancer prognosis: a novel model based on coagulation-related genes.PMC11094261Yang HWang NLi YZhang KLu WLei CXuan LfalseUnraveling breast cancer prognosis: a novel model based on coagulation-related genes.<h4>Objective</h4>Breast cancer is highly heterogeneous, presenting challenges in prognostic assessment. Developing a universally applicable prognostic model could simplify clinical decision-making. This study aims to develop and validate a novel breast cancer prognosis model using coagulation-related genes with broad clinical applicability.<h4>Methods</h4>A total of 203 genes related to coagulation were obtained from the KEGG database, and the mRNA data of 1,099 tumor tissue samples and 572 samples of normal tissue were retrieved from the TCGA-BRCA cohort and GTEx databases. The R package "limma" was utilized to detect variations in gene expression related to coagulation between the malignancies and normal tissue. A model was constructed in the TCGA cohort through a multivariable Cox regr2024-01-01T00:00:00Z20242026-07-14T18:08:35.408Z2026-06-22T03:08:08.351ZS-EPMC110942613875144510.3389/fmolb.2024.1394585