ArticleBMC medical genomics2022
Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma.
Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 5 citations in OpenAlex.
- Targeting GNG4 inhibits tumor progression and restores enzalutamide sensitivity in prostate cancer by suppressing autophagy.Cell death & disease · 2026Article
- Integrating network analysis and machine learning to explore the pharmacological targets and associations of oleanolic acid in lung adenocarcinoma.Frontiers in pharmacology · 2026Article
- Neurogenic locus notch homolog protein 1 (NOTCH 1) SNP informatics coupled with intrinsically disordered regions and post-translational modifications reveals the complex structural crosstalk of Lung Adenocarcinoma (LUAD).Frontiers in bioinformatics · 2025Article
- Osimertinib resistance prognostic gene signature: STRIP2 is associated with immune infiltration and tumor progression in lung adenocarcinoma.Journal of cancer research and clinical oncology · 2023Article
- Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies.Cancers · 2023Article
- An Inflammatory Response-Related Gene Signature Can Predict the Prognosis and Impact the Immune Status of Lung Adenocarcinoma.Cancers · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough the relationship between inflammatory response and tumor has been gradually recognized, the potential implications of of inflammatory response genes in lung adenocarcinoma (LUAD) remains poorly investigated.
methodsRNA sequencing and clinical data were obtained from multiple independent datasets (GSE29013, GSE30219, GSE31210, GSE37745, GSE42127, GSE50081, GSE68465, GSE72094, TCGA and GTEx). Unsupervised clustering analysis was used to identify different tumor subtypes, and LASSO and Cox regression analysis were applied to construct a novel scoring tool. We employed multiple algorithms (ssGSEA, CIBERSORT, MCP counter, and ESTIMATE) to better characterize the LUAD tumor microenvironment (TME) and immune landscapes. GSVA and Metascape analysis were performed to investigate the biological processes and pathway activity. Furthermore, 'pRRophetic' R package was used to evaluate the half inhibitory concentration (IC50) of each sample to infer drug sensitivity.
resultsWe identified three distinct tumor subtypes, which were related to different clinical outcomes, biological pathways, and immune characteristics. A scoring tool called inflammatory response gene score (IRGS) was established and well validated in multiple independent cohorts, which could well divide patients into two subgroups with significantly different prognosis. High IRGS patients, characterized by increased genomic variants and mutation burden, presented a worse prognosis, and might show a more favorable response to immunotherapy and chemotherapy. Additionally, based on the cross-talk between TNM stage, IRGS and patients clinical outcomes, we redefined the LUAD stage, which was called 'IRGS-Stage'. The novel staging system could distinguish patients with different prognosis, with better predictive ability than the conventional TNM staging.
conclusionsInflammatory response genes present important potential value in the prognosis, immunity and drug sensitivity of LUAD. The proposed IRGS and IRGS-Stage may be promising biomarkers for estimating clinical outcomes in LUAD patients.
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