Evidence map›Paper›PMID 42164482›Full record

ArticleFrontiers in immunology2026

Integrated characterization of distinct immune subtypes linked to drug responsiveness in breast cancer.

Min Liu, Meina Yang, Bo-Shi Fu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Min LiuDepartment of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Meina YangDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.
Bo-Shi FuDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Precision medicine emphasizes accurate patient stratification. However, existing molecular frameworks often fail to fully capture the intrinsic heterogeneity of breast cancer (BRCA). This study aims to establish a novel immune-based classification system using immunological gene sets to elucidate tumor heterogeneity and identify predictive biomarkers for optimizing clinical management. Methods: Non-negative Matrix Factorization (NMF) analysis of Gene Set Variation Analysis enrichment scores, transformed from TCGA, GEO, and CCLE transcriptomic profiles, revealed distinct immune subtypes. These subtypes were comprehensively characterized for their immune, mutational, and molecular features. Therapeutic sensitivity was assessed using computational prediction algorithms and validated via Results: Three distinct immune subtypes were identified. Cluster II exhibited a survival advantage, high immune infiltration, and strong correlation with Basal-like tumors. In contrast, Cluster I aligned with Luminal subtypes and indicated poor prognosis. Therapeutic analysis revealed that Cluster II is most likely to benefit from immunotherapy. Additionally, five identified hub genes further confirmed the stability and accuracy of this immune stratification system. Conclusions: This study demonstrated that classifying identification of immune patterns for individual tumor patients could reveal the complexity of tumor immune microenvironment and further optimize precision immunotherapy.

Indexed as

Biomarkers, TumorBreast NeoplasmsAntineoplastic AgentsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyPrecision MedicinePrognosisTranscriptomeTumor MicroenvironmentAntineoplastic AgentsBiomarkers, Tumorbreast cancerimmune subtypeimmunologic gene setimmunotherapyprognosistumor immune microenvironment

Identifiers

PMID42164482
PMCPMC13183846

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.