We aimed to screen the drug metabolism-related subgroups of pancreatic adenocarcinoma (PAAD) and to study the prognosis, clinical features, immune infiltration, and gene mutation differences of different subtypes in PAAD patients. All 181 cases of PAAD samples and clinical characteristics data were downloaded from The Cancer Genome Atlas (TCGA). After matching the drug metabolism-related genes downloaded from PMID 33202946 with the TCGA dataset, the drug metabolism-related genes were initially obtained. Besides, univariate Cox regression analysis was used to screen the drug metabolism genes related to the prognosis of PAAD. Moreover, the construction of the protein-protein interaction (PPI) network and gene ontology were performed. The four subgroups of PAAD obtained from unsupervised clustering analysis were systematically analyzed, including prognostic, GSVA, immune infiltration, and gene mutation analysis. A total of 83 drug metabolism genes related to the prognosis of PAAD were obtained and enriched in 16 pathways. The PPI network was composed of 248 relationship pairs. Four subgroups that can identify different subtypes of PPAD were obtained, and there were significant differences in survival and clinical characteristics, mutation types, and immune infiltration abundance between subgroups. A total of 17 different pathways among the four subgroups involved in cell cycle, response to stimulants such as drugs, and transmembrane transport. In this study, the four subgroups related to the drug metabolism of PAAD were comprehensively analyzed, and the important role of drug metabolism-related genes in the immune infiltration and prognosis of PAAD were emphasized.
Keywords: drug metabolism genes; immune infiltration; pancreatic adenocarcinoma; prognosis; unsupervised clustering analysis.
© 2022 Tongyi Zhang et al., published by De Gruyter.