Proteomic Profiling of Immune Cell Infiltration Reveals Prognostic Immune Subtypes in Lung Adenocarcinoma.
4 affiliations
- 1Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
- 2Department of Medical Oncology, Central Hospital, Tianjin University/Third Central Hospital, Jintang Road 83, Hedong District, Tianjin 300170, China.
- 3Beijing Proteome Research Center, Beijing 102206, China.
- 4Department of Thoracic Surgery, Baodi Hospital, Tianjin Medical University, Tianjin 301000, China.
Abstract
Background
Lung adenocarcinoma (LUAD) shows marked heterogeneity in its immune microenvironment, which may contribute to differences in disease-free survival (DFS) and clinical outcome. Although current LUAD classifications are largely based on genomic or transcriptomic features, immune subtypes defined directly from bulk proteomic data remain poorly characterized. Here, we used an immune-cell proteomic reference matrix to investigate proteome-defined immune states in LUAD and to identify prognostically relevant immune subtypes.Methods
A quantitative human immune-cell proteomic reference matrix was integrated with LUAD tumor proteomic profiles. The reference matrix covered seven major immune lineages and 26 immune-cell states. The discovery cohort included 101 LUAD tumor proteomes with matched clinical information. After gene symbol matching and normalization, proteome-defined immune-cell state signals were estimated for each sample using non-negative constrained regression. These signals were then used for unsupervised subtype identification and DFS analysis. An independent Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD cohort was used for validation, with subtype analysis performed at the immune-cell marker protein module level.Results
The immune-cell reference matrix contained 8400 quantified proteins, and 2381 proteins were retained for modeling. Based on 26 proteome-defined immune-cell state signals, LUAD samples separated into two immune proteomic subtypes. In the discovery cohort, Subtype 2 had significantly worse DFS than Subtype 1 (log-rank p = 0.0047; HR = 2.09, 95% CI 1.24-3.54). In the Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD validation cohort, marker protein module-based analysis again identified two subtypes with distinct DFS outcomes. The high-risk Subtype 2 showed higher Granulocyte and Myeloid/DC modules, whereas the low-risk Subtype 1 showed higher B cell, T cell, and NK-cell modules. Subtype 2 was associated with shorter DFS in the validation cohort (log-rank p = 0.0061; HR = 3.45, 95% CI: 1.35-8.82), and this association remained significant after adjustment for age, sex, and stage.Conclusions
Proteomic immune profiling identified two prognostically distinct immune subtypes in LUAD. The poor-DFS subtype was characterized by increased myeloid/granulocyte-related protein modules, whereas the favorable-DFS subtype showed stronger B cell-, T cell-, and NK cell-related signals. These findings support the use of bulk tumor proteomics to characterize clinically relevant immune heterogeneity in LUAD.
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BibTeX
@article{zhang2026proteomic,
title = {{Proteomic Profiling of Immune Cell Infiltration Reveals Prognostic Immune Subtypes in Lung Adenocarcinoma.}},
author = {Ruoxian Zhang and Hongsheng Guo and Xianju Li and Hongjie Zhao and Jun Qin},
journal = {Proteomes},
year = {2026},
month = oct,
doi = {10.3390/proteomes14040052},
url = {https://europepmc.org/article/MED/42924750},
note = {CC BY},
}
RIS
TY - JOUR
TI - Proteomic Profiling of Immune Cell Infiltration Reveals Prognostic Immune Subtypes in Lung Adenocarcinoma.
AU - Ruoxian Zhang
AU - Hongsheng Guo
AU - Xianju Li
AU - Hongjie Zhao
AU - Jun Qin
PY - 2026
DA - 2026/10/02
JO - Proteomes
DO - 10.3390/proteomes14040052
UR - https://europepmc.org/article/MED/42924750
AB - Background Lung adenocarcinoma (LUAD) shows marked heterogeneity in its immune microenvironment, which may contribute to differences in disease-free survival (DFS) and clinical outcome. Although current LUAD classifications are largely based on genomic or transcriptomic features, immune subtypes defined directly from bulk proteomic data remain poorly characterized. Here, we used an immune-cell proteomic reference matrix to investigate proteome-defined immune states in LUAD and to identify prognostically relevant immune subtypes.Methods A quantitative human immune-cell proteomic reference matrix was integrated with LUAD tumor proteomic profiles. The reference matrix covered seven major immune lineages and 26 immune-cell states. The discovery cohort included 101 LUAD tumor proteomes with matched clinical information. After gene symbol matching and normalization, proteome-defined immune-cell state signals were estimated for each sample using non-negative constrained regression. These signals were then used for unsupervised subtype identification and DFS analysis. An independent Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD cohort was used for validation, with subtype analysis performed at the immune-cell marker protein module level.Results The immune-cell reference matrix contained 8400 quantified proteins, and 2381 proteins were retained for modeling. Based on 26 proteome-defined immune-cell state signals, LUAD samples separated into two immune proteomic subtypes. In the discovery cohort, Subtype 2 had significantly worse DFS than Subtype 1 (log-rank p = 0.0047; HR = 2.09, 95% CI 1.24-3.54). In the Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD validation cohort, marker protein module-based analysis again identified two subtypes with distinct DFS outcomes. The high-risk Subtype 2 showed higher Granulocyte and Myeloid/DC modules, whereas the low-risk Subtype 1 showed higher B cell, T cell, and NK-cell modules. Subtype 2 was associated with shorter DFS in the validation cohort (log-rank p = 0.0061; HR = 3.45, 95% CI: 1.35-8.82), and this association remained significant after adjustment for age, sex, and stage.Conclusions Proteomic immune profiling identified two prognostically distinct immune subtypes in LUAD. The poor-DFS subtype was characterized by increased myeloid/granulocyte-related protein modules, whereas the favorable-DFS subtype showed stronger B cell-, T cell-, and NK cell-related signals. These findings support the use of bulk tumor proteomics to characterize clinically relevant immune heterogeneity in LUAD.
SN - 2227-7382
ER -