Objective To excavate differentially expressed genes (DEGs) and signaling pathways associated with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection, construct mol. interaction networks, and analyze the functions of key genes based on gene expression profile chip data and comprehensive bioinformatics methods. Methods The NCBI-GEO database was used to screen the expression profile dataset related to SARS-CoV-2 infection. GEO2R tool was used to analyze and screen the DEGs. DAVID was used to enrich and analyze the related signaling pathways, STRING database was used to construct and analyze the information and function of mol. interaction network, and key subnetworks were screened for functional annotation of hub genes. The GEPIA2 database was used to evaluate the potential clin. value of related genes in cancer patients prone to SARS-CoV-2 infection. Results After the anal. of GSE156544 dataset, a total of 59 DEGs significantly related to SARS-CoV-2 infection were screened and enriched. Function enrichment and signal pathway anal. were carried out, and the mol. interaction network was successfully constructed, and 1 key subnetwork and 21 hub genes were obtained (including NOP58, NOL6, CIRH1A, HEATR1, PDCD11, BMS1, NOP56, NHP2L1, WDR36, TBL3, BOP1, DCAF13, DKC1, UTP18, BYSL, IMP4, NOP14, FBL, KRR1, RRP9, MPHOSPH10). Conclusion Extracellular matrix receptor interaction and ribosome biosynthesis are significantly correlated with SARS-CoV-2 infection. In addition, NOP56, NHP2L1 and FBL may be potential gene targets for cancer patients susceptible to SARS-CoV-2 infection.