ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Deciphering Immune Heterogeneity in Lung Adenocarcinoma via Machine Learning-based Differential Phenotype Immune Score (DPIS): TPX2 as a Key Biomarker for Immunotherapy Resistance
Xu Zhang 1
Siyi Sun 1
Xin Hong 1
Yi Dong 1
Xin Wang 1
Yifan Ma 2
Kaisheng Yuan 3
Man Dou 1
Ying Cao 1
Xufeng Zhang 1
Ying Xing 1
1. Harbin Medical University Cancer Hospital, Harbin, China
2. Harbin Medical University, Harbin, China
3. Washington State University College of Pharmacy and Pharmaceutical Sciences, Spokane, United States
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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 tumours 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 tumours 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 unfavourable immunotherapy responses. Functional experiments further demonstrated that TPX2 promotes tumour 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.
Summary
Keywords
immune heterogeneity, Immunotherapy response, Lung Adenocarcinoma, Single-cell transcriptomics, Tpx2
Received
27 January 2026
Accepted
17 February 2026
Copyright
© 2026 Zhang, Sun, Hong, Dong, Wang, Ma, Yuan, Dou, Cao, Zhang and Xing. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Xu Zhang; Xufeng Zhang; Ying Xing
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