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<p>Lung adenocarcinoma (LUAD), characterized by its heterogeneity and high invasiveness, remains a challenging disease despite significant advancements in immunotherapy. Our study aimed to elucidate the expression differences of immunomodulatory-related genes in LUAD tissues compared to normal tissues and to validate the predictive role of these genes in the diagnosis, immunotherapy, and prognostic assessment of LUAD. Gene expression profiles and clinical data were extracted from TCGA and GEO datasets. GO analysis, KEGG pathway analysis, and GSEA were employed to identify biological process disparities. The single-sample Gene Set Enrichment Analysis (ssGSEA) was used to assess immune cell infiltration in distinct LUAD disease subtypes and derive an immunomodulatory score (Is) for patients with LUAD. Univariate and multivariate Cox regression analyses were performed to ascertain the prognostic significance of immunomodulatory-related genes (IRGs) in LUAD. Calibration curves and decision curve analysis (DCA) was used to verify the predictive efficacy of these IRs for the prognosis of patients with LUAD. This study identified, in the TCGA dataset, 18 IRGs that were differentially expressed between the LUAD and normal groups. Differential expression analysis IRGs using a threshold of |logFC|&gt; 1 with an adjusted P-value &lt; 0.05. GO and KEGG enrichment analysis, as well as GSEA results, revealed several significantly upregulated signaling pathways, including oxidative-stress-induced cell senescence and cell response to hypoxia. Interestingly, a strong correlation was observed between IRGs and activated dendritic cells in the four LUAD disease subtypes. Cox regression analyses demonstrated that the clinical prognosis of patients with LUAD was significantly associated with several key prognostic genes and clinical variables, including T, N, and M stages. The calibration curve and DCA verify this result. In summary, IRGs are increasingly being recognized for their pivotal roles in LUAD progression. The LUAD disease subtypes and Is derived from the IRGs offer valuable tools for predicting immunotherapy prognosis and stratifying the LUAD diagnosis.</p> Graphical Abstract <p></p>

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Predictive value of immunomodulatory-related genes for the prognosis of lung adenocarcinoma based on bioinformatics analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月26日

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  • Luyu Yang,
  • Zhimin Cao,
  • Xing Yuanfang,
  • Teng Ma,
  • Huan Ye,
  • Dongchang Wang

摘要

Lung adenocarcinoma (LUAD), characterized by its heterogeneity and high invasiveness, remains a challenging disease despite significant advancements in immunotherapy. Our study aimed to elucidate the expression differences of immunomodulatory-related genes in LUAD tissues compared to normal tissues and to validate the predictive role of these genes in the diagnosis, immunotherapy, and prognostic assessment of LUAD. Gene expression profiles and clinical data were extracted from TCGA and GEO datasets. GO analysis, KEGG pathway analysis, and GSEA were employed to identify biological process disparities. The single-sample Gene Set Enrichment Analysis (ssGSEA) was used to assess immune cell infiltration in distinct LUAD disease subtypes and derive an immunomodulatory score (Is) for patients with LUAD. Univariate and multivariate Cox regression analyses were performed to ascertain the prognostic significance of immunomodulatory-related genes (IRGs) in LUAD. Calibration curves and decision curve analysis (DCA) was used to verify the predictive efficacy of these IRs for the prognosis of patients with LUAD. This study identified, in the TCGA dataset, 18 IRGs that were differentially expressed between the LUAD and normal groups. Differential expression analysis IRGs using a threshold of |logFC|> 1 with an adjusted P-value < 0.05. GO and KEGG enrichment analysis, as well as GSEA results, revealed several significantly upregulated signaling pathways, including oxidative-stress-induced cell senescence and cell response to hypoxia. Interestingly, a strong correlation was observed between IRGs and activated dendritic cells in the four LUAD disease subtypes. Cox regression analyses demonstrated that the clinical prognosis of patients with LUAD was significantly associated with several key prognostic genes and clinical variables, including T, N, and M stages. The calibration curve and DCA verify this result. In summary, IRGs are increasingly being recognized for their pivotal roles in LUAD progression. The LUAD disease subtypes and Is derived from the IRGs offer valuable tools for predicting immunotherapy prognosis and stratifying the LUAD diagnosis.

Graphical Abstract