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Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis
Amino acid metabolism is closely related to the occurrence and development of colon adenocarcinoma (COAD). Studies on the relationship between COAD and the expression of amino acid metabolism are still rare. Based on in silico analysis, we used 358 amino acid metabolism-related genes (AAMRGs) to det...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630836/ https://www.ncbi.nlm.nih.gov/pubmed/36341436 http://dx.doi.org/10.3389/fimmu.2022.1018334 |
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author | Xie, Yile Chen, Huimin Fang, Jing-Yuan |
author_facet | Xie, Yile Chen, Huimin Fang, Jing-Yuan |
author_sort | Xie, Yile |
collection | PubMed |
description | Amino acid metabolism is closely related to the occurrence and development of colon adenocarcinoma (COAD). Studies on the relationship between COAD and the expression of amino acid metabolism are still rare. Based on in silico analysis, we used 358 amino acid metabolism-related genes (AAMRGs) to determine the amino acid metabolism characteristics and then classified COAD into two distinct subtypes, namely AA1 and AA2. Then we analyzed the clinical characteristics, somatic mutation landscape, transcriptome profile, metabolism signatures, immune infiltration, and therapy sensitivity of these two subtypes. The AA1 subtype had inferior overall survival and was characterized by lower amino acid metabolic activity, higher tumor mutation burden, and higher immune cell infiltration, while AA2 displayed higher metabolic activity and relatively better survival. Furthermore, the AA1 subtype was likely to benefit from irinotecan in chemotherapy and immune checkpoint blockade therapy including programmed cell death protein-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) immune checkpoint inhibitor but was resistant to targeted therapy cetuximab. The AA2 subtype showed higher sensitivity to 5-fluorouracil and oxaliplatin. To provide perspectives on cell-specific metabolism for further investigation, we explored metabolic activity in different cell types including lymphocytes, mast cells, myeloid cells stromal cells, and epithelial cells via colorectal cancer single-cell data. Additionally, to assist in clinical decision-making and prognosis prediction, a 60-AAMRG-based classifier was generated and validated in an independent cohort. |
format | Online Article Text |
id | pubmed-9630836 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96308362022-11-04 Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis Xie, Yile Chen, Huimin Fang, Jing-Yuan Front Immunol Immunology Amino acid metabolism is closely related to the occurrence and development of colon adenocarcinoma (COAD). Studies on the relationship between COAD and the expression of amino acid metabolism are still rare. Based on in silico analysis, we used 358 amino acid metabolism-related genes (AAMRGs) to determine the amino acid metabolism characteristics and then classified COAD into two distinct subtypes, namely AA1 and AA2. Then we analyzed the clinical characteristics, somatic mutation landscape, transcriptome profile, metabolism signatures, immune infiltration, and therapy sensitivity of these two subtypes. The AA1 subtype had inferior overall survival and was characterized by lower amino acid metabolic activity, higher tumor mutation burden, and higher immune cell infiltration, while AA2 displayed higher metabolic activity and relatively better survival. Furthermore, the AA1 subtype was likely to benefit from irinotecan in chemotherapy and immune checkpoint blockade therapy including programmed cell death protein-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) immune checkpoint inhibitor but was resistant to targeted therapy cetuximab. The AA2 subtype showed higher sensitivity to 5-fluorouracil and oxaliplatin. To provide perspectives on cell-specific metabolism for further investigation, we explored metabolic activity in different cell types including lymphocytes, mast cells, myeloid cells stromal cells, and epithelial cells via colorectal cancer single-cell data. Additionally, to assist in clinical decision-making and prognosis prediction, a 60-AAMRG-based classifier was generated and validated in an independent cohort. Frontiers Media S.A. 2022-10-20 /pmc/articles/PMC9630836/ /pubmed/36341436 http://dx.doi.org/10.3389/fimmu.2022.1018334 Text en Copyright © 2022 Xie, Chen and Fang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Xie, Yile Chen, Huimin Fang, Jing-Yuan Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title | Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title_full | Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title_fullStr | Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title_full_unstemmed | Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title_short | Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
title_sort | amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630836/ https://www.ncbi.nlm.nih.gov/pubmed/36341436 http://dx.doi.org/10.3389/fimmu.2022.1018334 |
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