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Breaking the heterogeneity barrier: a robust prognostic signature for survival stratification and immune profiling in triple-negative breast cancer

Haixing Shen, Qing Zheng, Zhenyu Wang, Daitian Zheng, Zhenqi Gong, Huaiming Wang, Tianmiao Sun, Jie Pan, Yukai Jin, Xiaohong Zheng, Jingzhi Wang, Jiongjiong Zhang

2025Frontiers in Immunology5 citationsDOIOpen Access PDF

Abstract

Background: Triple-negative breast cancer (TNBC), a highly heterogeneous breast cancer subtype, poses significant challenges to human health. Intra-tumor heterogeneity (ITH) limits the reliability of conventional prognostic models. Methods: Using multi-region RNA-seq, we quantified TNBC transcriptomic heterogeneity through an integrative heterogeneity score (IHS). After evaluating inter-patient heterogeneity (IPH) and ITH, prognostic and low-heterogeneity genes were identified and used to build a prognostic risk model with a random survival forest (RSF) algorithm. This model was combined with TNM staging into a nomogram for clinical applicability. We further revealed the distinct immune microenvironment features, somatic mutations, and chemotherapy responses between risk subgroups. Gene expression was validated via RT-qPCR. Results: Spatial characterization uncovered substantial ITH, evidenced by sharp shifts in PAM50 subtypes and immune infiltration. Two low-heterogeneity biomarkers, CYP4B1 and GBP1, were identified to develop a robust prognostic signature with consistent predictive performance across 3- to 9-year survival endpoints (AUC > 0.6). The high-risk subgroup exhibited reduced immune infiltration, reduced immune checkpoint molecule expression, and poor immunotherapy response rates. Integration of the risk signature with TNM staging created a clinically practical nomogram with superior predictive accuracy (C-index >0.67). Therapeutic vulnerability profiling identified six targeted agents showing increased efficacy in high-risk patients. Dysregulation of signature genes was demonstrated in two TNBC cell lines. Conclusions: This study established a transcriptomic heterogeneity-resilient prognostic model for TNBC, enabling precise survival stratification and immune microenvironment assessment. The integrative nomogram and risk-guided therapeutic predictions address clinical challenges in TNBC management, advancing personalized treatment strategies.

Topics & Concepts

Breast cancerNomogramMedicineImmune systemRisk stratificationProfiling (computer programming)TranscriptomeOncologyTumor microenvironmentPersonalized medicineComputational biologySurvival analysisOverall survivalStratification (seeds)ImmunotherapyBioinformaticsGene expression profilingInternal medicinePopulation stratificationPrecision medicinePrognostic modelBiologyGene signatureImmune escapeProportional hazards modelCancer researchTumour heterogeneityImmune checkpointImmunologyBreast Cancer Treatment StudiesFerroptosis and cancer prognosisCancer Immunotherapy and Biomarkers
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