ArticleFrontiers in oncology2022
Association of Polymorphisms in Inflammation Genes With the Prognosis of Advanced Non-Small Cell Lung Cancer Patients Receiving Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors.
Article in Frontiers in oncology, 2022. 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, 6 citations in OpenAlex.
- POU4F1 enhances lung cancer gemcitabine resistance by regulating METTL3-dependent TWF1 mRNA N6 adenosine methylation.3 Biotech · 2025Article
- Computational prediction of crucial genes involved in gonorrhea infection and neoplastic cell transformation: A multiomics approach.Microbial pathogenesis · 2024Article
- Impact of Interleukin-17 Receptor A Gene Variants on Asthma Susceptibility and Clinical Manifestations in Children and Adolescents.Children (Basel, Switzerland) · 2024Article
- Identification Of Endothelial Cell Immune-related Gene Signature for Lung Adenocarcinoma by Integrated Analysis of Single-cell and Bulk RNA Sequencing Data.Journal of Cancer · 2024Article
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9 authors at 2 institutions in 1 country.
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Abstract
Background: Inflammation is not only involved in the development and progression of cancer but also affects the response to therapy. The aim of this study was to investigate the association of single nucleotide polymorphisms (SNPs) in inflammation genes with the prognosis of advanced non-small cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). Methods: Forty-seven SNPs were genotyped in 318 advanced NSCLC patients receiving EGFR-TKIs. Of 318 patients, 182 (57.2%) patients died during follow-up period. We assessed the association of SNPs with the progression-free survival (PFS) and overall survival (OS) as well as calculated the weighted genetic risk score (GRS). We also explored the expression levels and prognostic values of inflammation genes in lung adenocarcinoma (LUAD) in Gene Expression Profiling Interactive Analysis (GEPIA) and using UCSC Xena, respectively. The relationship between the expression levels of IL15, IL17RA, AGER, MIF, and TNFRSF1A and EGFR mutation status was analyzed using UCSC Xena. Results: In single variant analyses, 3 SNPs (rs10519613, rs4819554, and rs4149570) were significantly associated with worse PFS. Five SNPs (rs10519613, rs4819554, rs2070600, rs755622, and rs4149570) were significantly with worse OS. In addition, high and intermediate GRSs (based on rs10519613, rs4819554, and rs4149570) were associated with worse PFS than those with low GRS. For OS, patients with high GRSs (based on rs10519613, rs4819554, rs2070600, rs755622, and rs4149570) had shorter survival time than those with low GRS. Furthermore, IL15, IL17RA, AGER, MIF, and TNFRSF1A were dysregulated in LUAD. There was difference in the expression level of TNFRSF1A between EGFR wildtype and EGFR-mutant LUAD. Both low AGER expression and high TNFRSF1A expression were significantly associated with worse PFS in LUAD. In addition, low IL17RA and AGER expression, high MIF and TNFRSF1A expression were significantly associated with worse OS in LUAD. Conclusion: SNPs in inflammation genes could serve as prognostic biomarkers for NSCLC patients treated with EGFR-TKIs.
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