Found programs: Joint Special Project for Regional High-Incidence Diseases Research , Natural Science Founda- tion of Guangxi ( No . 2023GXNSFAA026338) ; National Natural Science Foundation of China ( Nos . 81803564 , 82160448 , 82160482 ) ; National College Student Innovation and Entrepreneurship Training Project (Nos . 202210598040 , 202210598038 , 202210598033 , 202110598029)
Authors:Wei Handong1 , Chen Shuxing2 , Liu Linting2 , Jing Zihan3 , Yang Yiting1 , Song Qiong1 , Wang Wenchu1 , Zou Chunlin1 , Wang Lihui 1
Keywords:non small cell lung cancer; lung adenocarcinoma; bioinformatics analysis; differentially expressed genes; molecular markers; chemoresistance;
DOI:10.19405/j.cnki.issn1000-1492.2025.10.006
〔Abstract〕 Objective To discover molecular markers associated with lung adenocarcinoma diagnosis/prognosis and drug resistance through screening of differentially expressed genes based on published chip data in gene expression databases using bioinformatics methods. Methods Comprehensive analysis was performed in available mRNA microarray datasets including lung adenocarcinoma tissues dataset GSE32863 and lung adenocarcinoma taxane-platin resistance dataset GSE77209 from the gene expression omnibus(GEO) database. Gene ontology enrichment analysis, gene pathway enrichment analysis and protein interaction network analysis were performed based on significantly correlated genes. The expression level of genes was validated in the cancer genome atlas(TCGA) dataset. Survival differences were assessed by the log-rank test in TCGA lung adenocarcinoma dataset. Based on the publications genomics of drug sensitivity in cancer(GDSC) database in CellMiner cross database(CellMiner CDB), Pearson correlation analysis was used to analyze the correlation between differentially expressed genes and the half-maximal inhibitory concentration(IC50) of anticancer drugs. Results There were a total of 77 genes which had a different expression in resistance lung adenocarcinoma cells and lung adenocarcinoma cancer tissues. The functional enrichment analysis showed that these co-different expression genes were mainly enriched in microtubule, extracellular exosome, cell cycle and signaling by nuclear receptors. Protein-protein interactions(PPI) network screened 6 most connected genes as molecular complex(MCODE). Among the MCODE, overexpressed ubiquitin conjugating enzyme E2 T(UBE2T), kinesin family member 20A(KIF20A), PCNA clamp associated factor(KIAA0101), pituitary tumor-transforming gene 1(PTTG1) and NIMA related kinase 2(NEK2) were associated with poor outcomes. Survival analysis results showed that these five genes were upregulated in lung adenocarcinoma tissues and drug-resistant cells and were significantly associated with poor prognosis in lung adenocarcinoma patients. Drug sensitivity analysis results suggested that high expression of PTTG1 and UBE2T was significantly associated with sensitivity to multiple anticancer drugs, including paclitaxel and docetaxel. RT-PCR validation showed that PTTG1 andUBE2T were highly expressed in docetaxel-resistant cells A549-TXR and H358-TXR.Conclusion PTTG1 andUBE2T holds the potential to be chemoresistance markers in lung adenocarcinoma.