Classical Monocyte Marker Gene Signatures (CMMGS) Identified by Analysis of Single-Cell and Bulk-RNA Sequencing to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma

Abstract

Abstract Background Classical monocytes, pivotal in the innate immune response, wield considerable influence over cancer prognosis and response to immunotherapy. Our aim was to construct lung adenocarcinoma (LUAD) prognostic signature associated with Classical monocytes.Methods This study encompassed 1,822 samples drawn from diverse public datasets. Initially, we conducted an comprehensive analysis of lung adenocarcinoma (LUAD) single-cell RNA sequencing data obtained from the Gene Expression Omnibus (GEO), identifying 145 marker genes specific to classical monocyte. Univariate Cox regression and Least Absolute Shrinkage Operator (LASSO) analyses were performed on the TCGA training cohort to construct a signature for classical monocyte marker genes.Result Patients in the TCGA LUAD cohort were categorized into high- and low-risk groups based on polygenic prognostic signature derived from these marker genes. The predictive capacity of this signature was robustly validated across distinct clinical subgroups and GEO cohorts. Notably, this signature emerged as an independent prognostic indicator via multivariate analysis. Low-risk patients exhibited heightened immune cell infiltration, correlating inversely with inflammatory activity and risk score. Conversely, the low-risk group demonstrated amplified abundance and diversity in T-cell receptor (TCR) repertoires, higher Immunophenotype scores (IPS), and lower Tumor Immune Dysfunction and Exclusion (TIDE) scores. Significantly, an assessment across three GEO immunotherapy cohorts showcased superior immunotherapeutic response and prognosis among low-risk patients compared to their high-risk counterparts.Conclusion In summary, our study introduces a novel signature rooted in monocyte marker genes that proficiently prognosticates and predicts immunotherapeutic response in LUAD patients.Supplementary Information: Supplementary information is uploaded in the attached document.