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Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8898926/ https://www.ncbi.nlm.nih.gov/pubmed/35340619 http://dx.doi.org/10.1515/med-2022-0433 |
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author | Zhang, Tongyi Zhu, Liyong Cai, Jianhua He, Jiaqi |
author_facet | Zhang, Tongyi Zhu, Liyong Cai, Jianhua He, Jiaqi |
author_sort | Zhang, Tongyi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8898926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-88989262022-03-25 Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation Zhang, Tongyi Zhu, Liyong Cai, Jianhua He, Jiaqi Open Med (Wars) Research Article 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. De Gruyter 2022-03-04 /pmc/articles/PMC8898926/ /pubmed/35340619 http://dx.doi.org/10.1515/med-2022-0433 Text en © 2022 Tongyi Zhang et al., published by De Gruyter https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. |
spellingShingle | Research Article Zhang, Tongyi Zhu, Liyong Cai, Jianhua He, Jiaqi Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title | Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title_full | Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title_fullStr | Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title_full_unstemmed | Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title_short | Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
title_sort | four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8898926/ https://www.ncbi.nlm.nih.gov/pubmed/35340619 http://dx.doi.org/10.1515/med-2022-0433 |
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