Objective To identify genes associated with resistance to programmed cell death protein 1 (PD-1) inhibitors in colorectal cancer (CRC) 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 differential genes (HDGs) and differentially expressed genes (DEGs). The CRC gene expression data from The Cancer Genome Atlas (TCGA) were analyzed using Pearson correlation analysis to identify PD-1-related genes. The key PD-1-related genes were further selected via STRING database analysis (minimum interaction score > 0.7) and Cytoscape visualization. The GEPIA 2 and Kaplan-Meier Plotter databases were employed to assess the relation between the key PD-1-related genes and the prognosis of the patietns with CRC. The relation between the Aurora kinase A (AURKA) and prognosis in the PD-1 inhibitor-treated patients across pan-cancer was analyzed using Kaplan-Meier Plotter and ROC Plotter databases. The differential expression of AURKA in the CRC tissues versus adjacent normal tissues was assessed by real-time fluorescent reverse transcription quantitative polymerase chain reaction (qRT-PCR) in 20 the patients with CRC. The test level was set at α=0.05. Results A total of 651 HDGs and 329 DEGs were identified, yielding 37 HDGs at their intersection for subsequent analysis. The pearson correlation analysis identified 25 PD-1 key genes. The protein-protein interaction networks constructed via MCC and MCODE algorithms further prioritized 10 and 14 PD-1 key genes, respectively. The survival analysis revealed that the CRC patients with low AURKA expression exhibited significantly poorer prognosis compared to those with high AURKA expression (P=0.005). The Kaplan-Meier Plotter and ROC Plotter analyses demonstrated that the low AURKA expression correlated with inferior response to PD-1 inhibitor therapy, whereas high AURKA expression was associated with better prognosis in the patients receiving PD-1 inhibitors. The GEO database analysis showed that AURKA expression was significantly downregulated in the CRC hypoxic cell lines (P<0.001), while qRT-PCR results indicated elevated AURKA expression in the CRC tissues compared to adjacent normal tissues (P=0.008). Conclusion The results of this bioinformatics analysis suggest that hypoxia down-regulated AURKA expression, and low AURKA expression is associated with worse prognosis in CRC patients, and worse reactivity and prognosis in patients treated with PD-1 inhibitors.

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