多组学和孟德尔随机化鉴定 S1PR5 为肺腺癌中的因果保护基因和 NK 细胞介导的预后生物标志物

Lung adenocarcinoma (LUAD) sustains an immunosuppressive tumor microenvironment (TME) via stromal-immune interactions. Efferocytosis regulates immune suppression and tissue homeostasis, yet biomarkers stratifying its TME states are lacking in LUAD, hindering precision therapy. This study aimed to investigate efferocytosis-associated immune regulation with both causal and prognostic relevance in LUAD, and to identify key biomarkers with potential implications for tumor stratification and therapeutic guidance.

Gene expression profiles from The Cancer Genome Atlas (TCGA) LUAD cohort and Genotype-Tissue Expression (GTEx) underwent differential expression analysis. Efferocytosis-related genes (ERGs) from GeneCards were intersected to identify LUAD-associated candidates. Mendelian randomization (MR) and colocalization evaluated causal ERG-LUAD relationships. Risk-related ERGs were systematically analyzed for expression, biological functions, prognosis, and immune interactions. Single-cell RNA sequencing (scRNA-seq) mapped cellular expression specificity of core ERGs. Machine learning prognostic models ( S1PR5 -enriched NK cell-related prognostic signature, SENRPS) were developed and validated across independent cohorts.

S1PR5 expression was significantly lower in tumor tissues from LUAD patients compared to healthy lung tissue, at both the transcript and protein levels. We identified S1PR5 as a dual biomarker serving both as a protective factor against LUAD pathogenesis and a prognostic marker for survival outcomes, linked to favorable prognosis and enhanced therapy sensitivity. ScRNA-seq localized S1PR5 to natural killer (NK) cells, enhancing the anti-tumor activity of CD16 + NK cells and mediating interactions with antigen-presenting CEACAM8 + macrophages. The SENRPS model integrates molecular and cellular features for risk stratification and clinical decision-making.

S1PR5 serves as a causal protective gene and prognostic biomarker governing cytotoxic immunity. SENRPS bridges TME dynamics to clinical risk prediction and therapeutic optimization, advancing LUAD precision oncology.