Evidence map›Paper›PMID 41836411›Full record

ArticleFrontiers in immunology2026

Deciphering immune heterogeneity in lung adenocarcinoma via machine learning-based Differential Phenotype Immune Score: TPX2 as a key biomarker for immunotherapy resistance.

Xu Zhang, Siyi Sun, Xin Hong, Yi Dong, Xin Wang, Yifan Ma, Kaisheng Yuan, Man Dou, Ying Cao, Xufeng Zhang and 1 more

Abstract read
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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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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Xu Zhang *The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Siyi Sun *The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Xin Hong *The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Yi DongThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Xin WangThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Yifan MaDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, China.
Kaisheng YuanDepartment of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, United States.
Man DouThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Ying CaoThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Xufeng ZhangThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Ying XingThe Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune heterogeneity is a major determinant of clinical outcome and immunotherapy responsiveness in lung adenocarcinoma (LUAD). However, the tumor-intrinsic transcriptional programs that drive immune divergence across patients remain insufficiently characterized. Methods: We constructed an integrated immune landscape of LUAD by combining bulk transcriptomic data, multi-omics profiling, and a large-scale single-cell atlas of non-small cell lung cancer. Immune subtypes were identified through integrative clustering approaches. A machine learning-derived Differential Phenotype Immune Score (DPIS) was developed to quantify immune-related phenotypic variation. Single-cell mapping, regulatory network inference, pan-cancer analyses, protein-level validation, and functional assays were conducted to interrogate key molecular drivers. Results: Three recurrent immune states were identified, including the Wound Healing, IFN-γ Dominant, and Inflammatory subtypes, each exhibiting distinct immune compositions, metabolic features, signalling activities, and clinical trajectories. Although tumors classified as IFN-γ Dominant or Inflammatory showed comparable sensitivity to immune checkpoint blockade, their baseline prognoses differed substantially, suggesting that immune activation alone does not fully explain outcome heterogeneity. DPIS consistently stratified overall survival across six independent cohorts and was predominantly localized to highly proliferative malignant cells at single-cell resolution. Regulatory network analysis revealed that DPIS-high tumors were governed by cell cycle-associated transcriptional programs. Among the DPIS components, TPX2 emerged as a central regulator linking proliferative signalling to immune suppression, characterized by impaired antigen presentation, reduced immune cell infiltration, and unfavorable immunotherapy responses. Functional experiments further demonstrated that TPX2 promotes tumor cell proliferation, migration, and resistance to apoptosis. Conclusion: This study identifies a proliferation-driven immune suppression program in LUAD, establishes DPIS as a robust and clinically applicable framework for immune stratification, and highlights TPX2 as a potential therapeutic target for overcoming immune resistance.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorCell Cycle ProteinsDrug Resistance, NeoplasmLung NeoplasmsMachine LearningMicrotubule-Associated ProteinsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyPhenotypeBiomarkers, TumorCell Cycle ProteinsMicrotubule-Associated ProteinsTPX2 protein, humanimmune heterogeneityimmunotherapy responselung adenocarcinomasingle-cell transcriptomicsTPX2

Identifiers

PMID41836411
PMCPMC12982036

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