Subtype-Stratified Consensus Gene Signatures: Bridging Tumor Cell Biology, Immune Microenvironment, and Clinical Prognosis in Breast Cancer

Breast cancer is characterized by profound molecular heterogeneity, which severely limits the clinical utility of universal prognostic tools. To address this gap, we systematically explored transcriptomic profiles in three independent breast cancer cohorts (TCGA, METABRIC, and SCAN-B) via unsupervised clustering. We identified both pan-cancer and PAM50 subtype-specific consensus prognostic gene signatures through log-rank tests and cross-cohort intersection. Single-sample Gene Set Enrichment Analysis (ssGSEA)-derived prognostic scores strongly stratified overall survival across all cohorts, with superior performance over established features (assessed via C-index, time-dependent AUC, NRI, and IDI). Functional enrichment analysis uncovered subtype-specific biological mechanisms: immune-related pathways dominated good-prognostic gene sets in HER2-enriched and Basal-like tumors, while oncogenic pathways characterized poor-prognostic gene sets. Correlation analysis with CIBERSORT-deconvolved immune cell proportions revealed that good-prognostic scores positively correlated with anti-tumor immune cells (CD8+ T cells, M1 macrophages) and negatively with pro-tumor cells (M2 macrophages, Tregs). Independent validation in the Lancet2005 ER+ cohort confirmed that Luminal prognostic gene sets robustly stratified distant relapse-free survival. Collectively, these subtype-specific consensus signatures integrate tumor cell biology and tumor immune microenvironment features, offering robust prognostic tools with potential for future clinical translation.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2026-03-31
DOI
https://doi.org/10.3390/ijms27073162
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Subtype-Stratified Consensus Gene Signatures: Bridging Tumor Cell Biology, Immune Microenvironment, and Clinical Prognosis in Breast Cancer

Shang Cai
International Journal of Molecular Sciences
Cancer Immunotherapy and Biomarkers
article

Subtype-Stratified Consensus Gene Signatures: Bridging Tumor Cell Biology, Immune Microenvironment, and Clinical Prognosis in Breast Cancer

Shang Cai
article en

Abstract

Breast cancer is characterized by profound molecular heterogeneity, which severely limits the clinical utility of universal prognostic tools. To address this gap, we systematically explored transcriptomic profiles in three independent breast cancer cohorts (TCGA, METABRIC, and SCAN-B) via unsupervised clustering. We identified both pan-cancer and PAM50 subtype-specific consensus prognostic gene signatures through log-rank tests and cross-cohort intersection. Single-sample Gene Set Enrichment Analysis (ssGSEA)-derived prognostic scores strongly stratified overall survival across all cohorts, with superior performance over established features (assessed via C-index, time-dependent AUC, NRI, and IDI). Functional enrichment analysis uncovered subtype-specific biological mechanisms: immune-related pathways dominated good-prognostic gene sets in HER2-enriched and Basal-like tumors, while oncogenic pathways characterized poor-prognostic gene sets. Correlation analysis with CIBERSORT-deconvolved immune cell proportions revealed that good-prognostic scores positively correlated with anti-tumor immune cells (CD8+ T cells, M1 macrophages) and negatively with pro-tumor cells (M2 macrophages, Tregs). Independent validation in the Lancet2005 ER+ cohort confirmed that Luminal prognostic gene sets robustly stratified distant relapse-free survival. Collectively, these subtype-specific consensus signatures integrate tumor cell biology and tumor immune microenvironment features, offering robust prognostic tools with potential for future clinical translation.

International Journal of Molecular SciencesVol. 27(7)
Westlake University (CN), Zhejiang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
No poverty
Openalex Percentile: Top 33%
Cancer Immunotherapy and Biomarkers
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.