Abstract / Summary
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.