Genes From Epithelial-Mesenchymal Transition Predict Overall Survival Effectively in Breast Cancer: A Novel Risk Model Based on Initial Step of Tumor Metastasis.
[BACKGROUND] Accumulating evidence has demonstrated that epithelial-mesenchymal transition (EMT) plays a critical role in breast cancer (BRCA) initiation, invasion, metastasis, and prognosis.
- 연구 설계 cohort study
APA
Liang W, Wang ZY, et al. (2026). Genes From Epithelial-Mesenchymal Transition Predict Overall Survival Effectively in Breast Cancer: A Novel Risk Model Based on Initial Step of Tumor Metastasis.. Breast cancer : basic and clinical research, 20, 11782234261433697. https://doi.org/10.1177/11782234261433697
MLA
Liang W, et al.. "Genes From Epithelial-Mesenchymal Transition Predict Overall Survival Effectively in Breast Cancer: A Novel Risk Model Based on Initial Step of Tumor Metastasis.." Breast cancer : basic and clinical research, vol. 20, 2026, pp. 11782234261433697.
PMID
41947824
Abstract
[BACKGROUND] Accumulating evidence has demonstrated that epithelial-mesenchymal transition (EMT) plays a critical role in breast cancer (BRCA) initiation, invasion, metastasis, and prognosis.
[OBJECTIVES] To develop and validate a comprehensive EMT-related gene signature for robust prognosis prediction in BRCA.
[DESIGN] Retrospective multi-cohort study.
[METHODS] We obtained 1223 BRCA samples from The Cancer Genome Atlas (TCGA) and 1184 EMT-related genes from the dbEMT2.0 public database. Prognostic genes were selected via univariate Cox and LASSO regression analyses to construct a risk score model, which was subsequently validated in independent internal cohort (TCGA) and external cohorts (UCSC and GEO). Finally, a nomogram integrating the risk score with clinical parameters was established.
[RESULTS] A 15-gene EMT signature was identified and used to stratify patients into high- and low-risk groups. The high-risk group exhibited significantly poorer overall survival in the TCGA cohort ( < .05), a finding consistently validated across 4 independent datasets (all < .05). The risk score served as an independent prognostic factor (hazard ratio = 2.386, < .001). The integrative nomogram, incorporating the risk score, age, and N and M stages, demonstrated moderate accuracy for survival prediction (C-index = 0.711).
[CONCLUSIONS] We developed and validated a novel 15-gene EMT signature and a corresponding nomogram, which provide a potential tool for prognostic stratification in BRCA patients.
[OBJECTIVES] To develop and validate a comprehensive EMT-related gene signature for robust prognosis prediction in BRCA.
[DESIGN] Retrospective multi-cohort study.
[METHODS] We obtained 1223 BRCA samples from The Cancer Genome Atlas (TCGA) and 1184 EMT-related genes from the dbEMT2.0 public database. Prognostic genes were selected via univariate Cox and LASSO regression analyses to construct a risk score model, which was subsequently validated in independent internal cohort (TCGA) and external cohorts (UCSC and GEO). Finally, a nomogram integrating the risk score with clinical parameters was established.
[RESULTS] A 15-gene EMT signature was identified and used to stratify patients into high- and low-risk groups. The high-risk group exhibited significantly poorer overall survival in the TCGA cohort ( < .05), a finding consistently validated across 4 independent datasets (all < .05). The risk score served as an independent prognostic factor (hazard ratio = 2.386, < .001). The integrative nomogram, incorporating the risk score, age, and N and M stages, demonstrated moderate accuracy for survival prediction (C-index = 0.711).
[CONCLUSIONS] We developed and validated a novel 15-gene EMT signature and a corresponding nomogram, which provide a potential tool for prognostic stratification in BRCA patients.
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