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Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer

Background: Tumor dormancy is an important way to develop drug resistance. This study aimed to identify the characteristics of colorectal cancer (CRC) cell dormancy. Methods: Based on the CRC cohorts, a total of 1,044 CRC patients were included in this study, and divided into a dormant subgroup and...

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Autores principales: Xie, Lang, Huang, Renli, Huang, Hongyun, Liu, Xiaoxia, Yu, Jinlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024109/
https://www.ncbi.nlm.nih.gov/pubmed/35462906
http://dx.doi.org/10.3389/fphar.2022.879751
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author Xie, Lang
Huang, Renli
Huang, Hongyun
Liu, Xiaoxia
Yu, Jinlong
author_facet Xie, Lang
Huang, Renli
Huang, Hongyun
Liu, Xiaoxia
Yu, Jinlong
author_sort Xie, Lang
collection PubMed
description Background: Tumor dormancy is an important way to develop drug resistance. This study aimed to identify the characteristics of colorectal cancer (CRC) cell dormancy. Methods: Based on the CRC cohorts, a total of 1,044 CRC patients were included in this study, and divided into a dormant subgroup and proliferous subgroup. Non-negative matrix factorization (NMF) was used to distinguish the dormant subgroup of CRC via transcriptome data of cancer tissues. Gene Set Enrichment Analysis (GSEA) was used to explore the characteristics of dormant CRC. The characteristics were verified in the cell model, which was used to predict key factors driving CRC dormancy. Potential treatments for CRC dormancy were also examined. Results: The dormant subgroup had a poor prognosis and was more likely to relapse. GSEA analysis showed two defining characteristics of the dormant subgroup, a difference in energy metabolism and synergistic effects of cancer-associated fibroblasts (CAFs), which were verified in a dormant cell model. Transcriptome and clinical data identified LMOD1, MAB21L2, and ASPN as important factors associated with cell dormancy and verified that erlotinib, and CB-839 were potential treatment options. Conclusion: Dormant CRC is associated with high glutamine metabolism and synergizes with CAFs in 5-FU resistance, and the key effectors are LMOD1, MAB21L2, and ASPN. Austocystin D, erlotinib, and CB-839 may be useful for dormant CRC.
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spelling pubmed-90241092022-04-23 Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer Xie, Lang Huang, Renli Huang, Hongyun Liu, Xiaoxia Yu, Jinlong Front Pharmacol Pharmacology Background: Tumor dormancy is an important way to develop drug resistance. This study aimed to identify the characteristics of colorectal cancer (CRC) cell dormancy. Methods: Based on the CRC cohorts, a total of 1,044 CRC patients were included in this study, and divided into a dormant subgroup and proliferous subgroup. Non-negative matrix factorization (NMF) was used to distinguish the dormant subgroup of CRC via transcriptome data of cancer tissues. Gene Set Enrichment Analysis (GSEA) was used to explore the characteristics of dormant CRC. The characteristics were verified in the cell model, which was used to predict key factors driving CRC dormancy. Potential treatments for CRC dormancy were also examined. Results: The dormant subgroup had a poor prognosis and was more likely to relapse. GSEA analysis showed two defining characteristics of the dormant subgroup, a difference in energy metabolism and synergistic effects of cancer-associated fibroblasts (CAFs), which were verified in a dormant cell model. Transcriptome and clinical data identified LMOD1, MAB21L2, and ASPN as important factors associated with cell dormancy and verified that erlotinib, and CB-839 were potential treatment options. Conclusion: Dormant CRC is associated with high glutamine metabolism and synergizes with CAFs in 5-FU resistance, and the key effectors are LMOD1, MAB21L2, and ASPN. Austocystin D, erlotinib, and CB-839 may be useful for dormant CRC. Frontiers Media S.A. 2022-04-08 /pmc/articles/PMC9024109/ /pubmed/35462906 http://dx.doi.org/10.3389/fphar.2022.879751 Text en Copyright © 2022 Xie, Huang, Huang, Liu and Yu. 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 Pharmacology
Xie, Lang
Huang, Renli
Huang, Hongyun
Liu, Xiaoxia
Yu, Jinlong
Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title_full Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title_fullStr Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title_full_unstemmed Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title_short Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer
title_sort transcriptomics and metabolomics identify drug resistance of dormant cell in colorectal cancer
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024109/
https://www.ncbi.nlm.nih.gov/pubmed/35462906
http://dx.doi.org/10.3389/fphar.2022.879751
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