Construction and validation of a novel prognostic model of neutrophil‑related genes signature of lung adenocarcinoma

Abstract

Lung adenocarcinoma (LUAD) remains an incurable disease with a poor prognosis. This study aimed to explore neutrophil‑related genes (NRGs) and develop a prognostic signature for predicting the prognosis of LUAD. NRGs were obtained by intersecting modular genes identified by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data and the marker genes of neutrophils identified from single-cell RNA-sequencing(scRNA-seq) data. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were run to construct a prognostic signature, follow by delineation of risk groups, and external validation. Analyses of ESTIMAT, immune function, Tumor Immune Dysfunction and Exclusion (TIDE) scores, Immune cell Proportion Score (IPS), and immune checkpoint genes between high- and low-risk groups were performed, and then analyses of drug sensitivity to screen for sensitive anticancer drugs in high-risk groups. A total of 45 candidate NRGs were identified, of which PLTP, EREG, CD68, CD69, PLAUR, and CYP27A1 were considered to be significantly associated with prognosis in LUAD and were used to construct a prognostic signature. Correlation analysis showed significant differences in the immune landscape between high- and low-risk groups. In addition, our prognostic signature was important for predicting drug sensitivity in the high-risk group. Our study screened for NRGs in LUAD and constructed a novel and effective signature, revealing the immune landscape and providing more appropriate guidance protocols in LUAD treatment.