ArticleJournal of the Egyptian National Cancer Institute2024
Identification of an immune-related genes signature in lung adenocarcinoma to predict survival and response to immune checkpoint inhibitors.
Article in Journal of the Egyptian National Cancer Institute, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- miR-4513 promotes the proliferation and metastasis of non-small cell lung cancer cells by targeting VIPR1.Hereditas · 2026Article
- Multiple roles of S100P in pan carcinoma: Biological functions and mechanisms (Review).Oncology reports · 2025Review
- The mechanism of RNA methylation writing protein-related prognostic genes in lung adenocarcinoma based on bioinformatics.Frontiers in genetics · 2025Article
- Bioinformatics-based prognostic value andFrontiers in oncology · 2025Article
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Abstract
backgroundAlthough advances in immune checkpoint inhibitor (ICI) research have provided a new treatment approach for lung adenocarcinoma (LUAD) patients, their survival is still unsatisfactory, and there are issues in the era of response prediction to immunotherapy.
methodsUsing bioinformatics methods, a prognostic signature was constructed, and its predictive ability was validated both in the internal and external datasets (GSE68465). We also explored the tumor-infiltrating immune cells, mutation profiles, and immunophenoscore (IPS) in the low-and high-risk groups.
resultsAs far as we are aware, this is the first study which introduces a novel prognostic signature model using BIRC5, CBLC, S100P, SHC3, ANOS1, VIPR1, LGR4, PGC, and IGKV4.1. According to multivariate analysis, the 9-immune-related genes (IRGs) signature provided an independent prognostic factor for the overall survival (OS). The low-risk group had better OS, and the tumor mutation burden (TMB) was significantly lower in this group. Moreover, the risk scores were negatively associated with the tumor-infiltrating immune cells, like CD8
conclusionThe combination of these 9-IRGs not only could efficiently predict overall survival of LUAD patients but also show a powerful association with the expression of immune checkpoints and response to ICIs based on IPS; hoping this model paves the way for better stratification and management of patients in clinical practice.
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