Metabolic-immunoregulatory subtypes reveal prognostic and therapeutic insights in multiple primary lung cancer.

Background: Multiple primary lung cancer (MPLC) is an increasingly recognized subtype characterized by distinct lesions with independent origins. While recent studies have profiled the immune landscape of MPLC, its tumor-intrinsic metabolic features and immunoregulatory interactions remain largely unexplored. Methods: Single-cell RNA sequencing data from 11 single primary lung cancer (SPLC) tumors and 8 samples from 4 MPLC patients were analyzed using dimensionality reduction, clustering, and cell type annotation. Subtype-specific metabolic features and intercellular communication patterns were investigated through pathway enrichment and cell-cell interaction analyses. A prognostic model was constructed using Lasso-Cox regression. Immune microenvironment characteristics were assessed using deconvolution algorithms and immune-related signatures. Drug sensitivity prediction and functional assays were performed to explore potential therapeutic implications. Results: This study identified a metabolically distinct malignant epithelial subpopulation enriched in MPLC tumors, characterized by upregulation of amino acid metabolism pathways and active MHC-II-mediated interactions with immunosuppressive CD4 Conclusion: This study provides a systematic characterization of malignant subpopulations in MPLC, highlighting metabolic reprogramming and immunoregulatory features that contribute to poor prognosis. These findings provide a rationale for metabolism-based prognostic stratification and highlight potential therapeutic strategies to improve clinical outcomes.