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ArticleRecent patents on anti-cancer drug discovery2025

Bioinformatics Analysis of Key Genes Associated with Resistance to the Combination of Bevacizumab and Pemetrexed Chemotherapy in Non-small Cell Lung Cancer.

Chenling Hu, Shenjie Xu, Siwen Chen, Qian Sun, Xudong Pan

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Article in Recent patents on anti-cancer drug discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Chenling HuDepartment of General Medicine, the First Affiliated Hospital of Soochow University, Suzhou, 215031, China.
Shenjie XuDepartment of General Medicine, the First Affiliated Hospital of Soochow University, Suzhou, 215031, China.
Siwen ChenDepartment of General Medicine, the First Affiliated Hospital of Soochow University, Suzhou, 215031, China.
Qian SunDepartment of Medical Oncology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Xudong PanDepartment of General Medicine, the First Affiliated Hospital of Soochow University, Suzhou, 215031, China.

Funding

Suzhou key medical support discipline SZFCXK202111
6 · The paper itself

Abstract

objectivesThis study aimed to identify key genes linked to resistance to a combination treatment regimen of bevacizumab and pemetrexed in non-small cell lung cancer (NSCLC) through bioinformatics analysis and analysis of their associated pathways.

methodsExpression data from the Gene Expression Omnibus (GEO) database (GSE154286) were analyzed. The differentially expressed genes (DEGs) between tissues sensitive and resistant to combined bevacizumab and pemetrexed treatment in NSCLC were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was investigated, and protein-protein interaction (PPI) networks, as well as transcription factors (TFs)- DEGs-miRNA networks, were created using the STRING tool. Key genes were identified with the help of the MCODE plugin. Additionally, gene set enrichment analysis (GSEA) was utilized to identify pathways linked to the key genes. A retrospective analysis was conducted on clinical data from 80 NSCLC patients. Patients were categorized into drug-resistant and non-resistant groups based on RECIST1.1 criteria. The expression of the key gene TNFSF4 was analyzed using quantitative real-time PCR (qRT-PCR).

resultsIn the GSE154286 dataset, 35 downregulated DEGs were discovered. KEGG pathway enrichment analysis revealed that these DEGs were primarily associated with immunity and inflammation-related pathways. The PPI network construction highlighted a significant module and led to the identification of 8 candidate genes:

conclusionThe identification of key genes, such as TNFSF4, and resistance-related signaling pathways through bioinformatics analysis offers valuable insights into potential mechanisms of chemotherapy resistance in NSCLC when treated with the combination of bevacizumab and pemetrexed. These findings provide a theoretical foundation for advancing clinical research on diagnosis and treatment.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, Non-Small-Cell LungDrug Resistance, NeoplasmLung NeoplasmsBevacizumabComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPemetrexedProtein Interaction MapsRetrospective StudiesBevacizumabPemetrexedbevacizumabbioinformaticsNon-small cell lung cancerpemetrexedresistanceTNFSF4.

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