Objective:This 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.Methods:Expression 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 factor (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).Results:In 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: TNFRSF18, TNFSF4, LGALS9, FAS, LAG3,
CD86, CD80, and FOXP3. The TFs-DEGs-miRNA network analysis pinpointed TNFSF4 as a
key gene, potentially regulated by 7 transcription factors and interacting with 9 miRNAs. GSEA
analysis suggested that TNFSF4 may influence NSCLC’s pathological processes through involvement
in pathways involved in chemokine, JAK/STAT, NOD-like receptor, T cell receptor,
toll-like receptor, and PPAR signaling. qRT-PCR detection displayed significantly lower expression
of TNFSF4 in the peripheral blood of the patients in the resistant group relative to the
non-resistant group (p < 0.0001). Logistic regression analysis showed that low TNFSF4 levels
were independently linked to a raised risk of resistance to bevacizumab combined with
pemetrexed therapy in lung adenocarcinoma patients.Conclusion:The 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.