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Updated: Aug 10, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Metabolic-immunoregulatory subtypes reveal prognostic and therapeutic insights in multiple primary lung cancer
Yuli Zhao1, Hanyu Zhao2, Hui Wu1
1School of Food & Pharmaceutical Science and Technology, Guangzhou College of Technology and Business, Guangzhou, China.
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+ Treg cells and mast cells. A metabolism-based eight-gene prognostic model was developed and validated in independent lung adenocarcinoma cohorts, effectively stratifying patient survival outcomes. High-risk patients exhibited immunosuppressive tumor microenvironment features, reduced immunotherapy response potential, and distinct drug sensitivity profiles. Functional assays confirmed that key metabolic genes, spermine oxidase (SMOX) and spermine synthase (SMS), promoted tumor proliferation and invasion, accompanied by transcriptional changes in PI3K/mTOR pathway components, highlighting their potential roles in poor prognosis and therapeutic vulnerability.
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.
Insights
Multiple primary lung cancer (MPLC) exhibits unique metabolic features and immune interactions. A new metabolism-based model predicts survival and identifies therapeutic targets for MPLC patients.
Area of Science:
- Oncology
- Immunology
- Metabolomics
Background:
- Multiple primary lung cancer (MPLC) is a distinct subtype with independent origins.
- While MPLC's immune landscape is studied, its tumor metabolism and immune interactions are largely unknown.
Purpose of the Study:
- To characterize the metabolic and immunoregulatory features of MPLC.
- To develop a prognostic model and identify therapeutic vulnerabilities in MPLC.
Main Methods:
- Single-cell RNA sequencing of MPLC and single primary lung cancer (SPLC) tumors.
- Pathway enrichment, cell-cell interaction, and deconvolution analyses.
- Construction and validation of an eight-gene prognostic model; functional assays.
Main Results:
- Identified a metabolically distinct malignant epithelial subpopulation in MPLC with upregulated amino acid metabolism.
- Developed and validated a metabolism-based prognostic model that stratifies MPLC patient survival.
- High-risk patients showed immunosuppressive microenvironments, reduced immunotherapy response, and distinct drug sensitivities. Key metabolic genes SMOX and SMS promoted tumor growth.
Conclusions:
- MPLC subpopulations display metabolic reprogramming and immunoregulatory features linked to poor prognosis.
- Metabolism-based stratification and targeting metabolic pathways offer potential therapeutic strategies for MPLC.
