Objective To identify genes associated with resistance to programmed cell death protein 1 (PD-1) inhibitors in colorectal cancer and elucidate their underlying mechanisms using bioinformatics approaches. Methods Genes expression datasets were downloaded from the Gene Expression Omnibus (GEO) database to screen hypoxia-related genes (HRGs) and differentially expressed genes (DEGs). The intersection of HRGs and DEGs was defined as hypoxia-related differentially expressed genes (HDGs). The gene expression data of patients with colorectal cancer from The Cancer Genome Atlas (TCGA) were analyzed using Pearson correlation to identify the PD-1-related genes, further the STRING analysis (minimum interaction score was greater than 0.7) and Cytoscape were subsequently employed to screen the key PD-1-related genes. The relation between the screened key PD-1-related genes and the prognosis of colorectal cancer patients was analyzed to screen out the target genes. The real-time fluorescence reverse transcription quantitative polymerase chain reaction was used to analyze the expression of the target genes in the cancer tissues and their corresponding adjacent tissues of 20 patients with colorectal cancer. The Kaplan-Meier Plotter database and the ROC Plotter database were used to analyze the relation between the high and low expression of the target genes and the prognosis in different patients. The significance level was set as α=0.05. Results A total of 651 HRGs and 329 DEGs were screened out. By taking the intersection of these two sets, 37 HDGs were obtained for subsequent analysis. Through Pearson correlation analysis, 25 key PD-1-related genes were screened out and 10 and 14 key PD-1-related genes were screened out by the MCC algorithm and the MCODE algorithm respectively. By taking the intersection of these three sets, 3 key PD-1-related genes were obtained, then survival analysis, the Aurora kinase A (AURKA) gene was finally screened out as the target gene. The expression level of the AURKA gene in the pan-cancer patients who responded to PD-1 inhibitor treatment was significantly higher than that in non-responders (P＜0.001), and was significantly lower in the six colorectal cancer cells treated with hypoxia than in six colorectal cancer cells treated with normoxia (P＜0.001). The AURKA expression in the colorectal cancer tissues was significantly higher than that in the corresponding adjacent colorectal tissues (P=0.008). The overall survival of pan-cancer patients with high AURKA expression was better than that of those with low AURKA expression [HR (95%CI)=0.67 (0.49, 0.93), P=0.015]. Among the colorectal cancer patients with MMR deficiency, the patients with low AURKA gene expression had worse overall survival [HR (95%CI)=2.596 (1.028, 6.332), P=0.043] and recurrence-free survival [HR (95%CI)=4.201 (1.092, 16.150), P=0.037] as compared with those with high AURKA gene expression. The low AURKA expression was associated with significantly worse overall survivals in the colorectal cancer patients harboring wild-type or mutant TP53, BRAF, and KRAS as compared with high AURKA expression (P＜0.05), while no statistically significant difference was found in the overall survival of the normal MMR patients between with high AURKA expression and low AURKA expression (P=0.307). Conclusion The results of this bioinformatics analysis suggest that hypoxia down-regulated AURKA expression, and low AURKA expression is associated with worse prognosis in colorectal cancer patients, and worse reactivity and prognosis in patients treated with PD-1 inhibitors.

Citation： WANG Hongpeng, LIU Tao, JIANG Lei. Hypoxia-induced down-regulation of aurora kinase A inhibits colorectal cancer response to programmed death protein-1 inhibitors: a bioinformatic analysis. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2025, 32(5): 609-616. doi: 10.7507/1007-9424.202410035 Copy

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