Prognostic and therapeutic implications of lipid metabolism-related lncRNAs in lung adenocarcinoma: a comprehensive analysis integrating transcriptomics, Mendelian randomization, and immunotherapy sensitivity

Abstract

Background and Aim

Lipid metabolism plays a crucial role in cancer progression, and long non-coding RNAs (lncRNAs) are emerging as key regulators in tumor biology. However, the prognostic and therapeutic implications of lipid metabolism-related lncRNAs in lung adenocarcinoma (LUAD) remain unclear. This study aimed to identify lipid metabolism-associated lncRNAs, construct a prognostic model, and explore their clinical relevance in LUAD.

Methods

Transcriptomic and clinical data from LUAD patients were obtained from The Cancer Genome Atlas (TCGA). Co-expression networks, functional enrichment (GO/KEGG), and survival analyses (univariate/multivariate Cox regression, LASSO) were used to identify prognostic lncRNAs. A risk prediction model was developed and validated using tumor mutation burden (TMB), immune microenvironment analysis, and drug sensitivity profiling. Mendelian randomization (MR) and Bayesian weighting were employed to assess causal relationships between lipid metabolism pathways and LUAD.

Results

Three lipid metabolism-related lncRNAs—LINC00862 and AC125807.2 (risk factors) and LINC01447 (protective factor)—were significantly associated with LUAD prognosis. The risk model stratified patients into high- and low-risk groups with distinct sur-vival outcomes (p < 0.001). High-risk patients exhibited elevated TMB and immune dysfunction but greater sensitivity to chemotherapy (e.g., cisplatin, gemcitabine), while low-risk patients showed potential responsiveness to targeted therapies (e.g., PAK1/GSK-3 inhibitors). MR analysis confirmed that normal lipid metabolism pathways (linoleic acid/fatty acid metabolism) reduce LUAD risk (IVW p < 0.05).

Conclusion

This study identifies lipid metabolism-related lncRNAs as novel prognostic biomarkers in LUAD, with implications for risk stratification and personalized therapy. The findings highlight the interplay between lipid metabolism, immune regulation, and therapeutic response, offering a foundation for future clinical validation and targeted interventions.

Keywords

TCGA / NSCLC / Lipid metabolism / Long non-coding RNA / Immunotherapy / Mendelian randomization analysis

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