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Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer

BACKGROUND: Colorectal cancer (CRC) is a common gastrointestinal tumor with subtle, often undetectable early symptoms, which means that upon diagnosis, patients often present in the middle or late stages of disease. Therefore, the need for an effective biomarker for the early diagnosis and developme...

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Autores principales: Ni, Juan, Chen, Yang, Li, Ningning, Sun, Diandian, Ju, Haixing, Chen, Zhongjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797830/
https://www.ncbi.nlm.nih.gov/pubmed/35116504
http://dx.doi.org/10.21037/tcr-20-3406
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author Ni, Juan
Chen, Yang
Li, Ningning
Sun, Diandian
Ju, Haixing
Chen, Zhongjian
author_facet Ni, Juan
Chen, Yang
Li, Ningning
Sun, Diandian
Ju, Haixing
Chen, Zhongjian
author_sort Ni, Juan
collection PubMed
description BACKGROUND: Colorectal cancer (CRC) is a common gastrointestinal tumor with subtle, often undetectable early symptoms, which means that upon diagnosis, patients often present in the middle or late stages of disease. Therefore, the need for an effective biomarker for the early diagnosis and development of novel therapeutic targets is urgent to prolong patient survival time and reduce mortality. METHODS: Twenty mice were randomly divided into patient-derived xenograft (PDX) model (transplantation of fresh CRC tumor samples) and control groups (10 mice in each group). All the animals were euthanized using isoflurane at the end of the experiment. Gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling was performed to investigate the differential metabolites in the serum, and publicly available gene expression data (GSE106582) were analyzed to determine dysregulated metabolic pathways. Joint pathway analysis was used to identify potential metabolic targets. Immunohistochemistry analysis was performed to confirm the presence of the identified targets at the protein level. RESULTS: A total of 96 differential circulating metabolites were identified, which were predominantly involved in amino acid metabolism. In particular, the serum levels of amino acids such as phenylalanine and aspartic acid were significantly downregulated in the PDX group, suggesting an increased consumption of amino acids in CRC. Moreover, both the mRNA and protein levels of the amino acid transporters, SLC7A5 and SLC1A5, were found to be upregulated in CRC. CONCLUSIONS: By combining GC-MS-based metabolomics profiling with a PDX model of CRC our study successfully identified potential diagnostic circulating metabolites. Dysregulated amino acid metabolism was found to be a significant feature of CRC. The amino acid transporters, SLC7A5 and SLC1A5, were identified as potential metabolic therapeutic targets. This study furthers the understanding of the metabolic processes involved in CRC.
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spelling pubmed-87978302022-02-02 Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer Ni, Juan Chen, Yang Li, Ningning Sun, Diandian Ju, Haixing Chen, Zhongjian Transl Cancer Res Original Article BACKGROUND: Colorectal cancer (CRC) is a common gastrointestinal tumor with subtle, often undetectable early symptoms, which means that upon diagnosis, patients often present in the middle or late stages of disease. Therefore, the need for an effective biomarker for the early diagnosis and development of novel therapeutic targets is urgent to prolong patient survival time and reduce mortality. METHODS: Twenty mice were randomly divided into patient-derived xenograft (PDX) model (transplantation of fresh CRC tumor samples) and control groups (10 mice in each group). All the animals were euthanized using isoflurane at the end of the experiment. Gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling was performed to investigate the differential metabolites in the serum, and publicly available gene expression data (GSE106582) were analyzed to determine dysregulated metabolic pathways. Joint pathway analysis was used to identify potential metabolic targets. Immunohistochemistry analysis was performed to confirm the presence of the identified targets at the protein level. RESULTS: A total of 96 differential circulating metabolites were identified, which were predominantly involved in amino acid metabolism. In particular, the serum levels of amino acids such as phenylalanine and aspartic acid were significantly downregulated in the PDX group, suggesting an increased consumption of amino acids in CRC. Moreover, both the mRNA and protein levels of the amino acid transporters, SLC7A5 and SLC1A5, were found to be upregulated in CRC. CONCLUSIONS: By combining GC-MS-based metabolomics profiling with a PDX model of CRC our study successfully identified potential diagnostic circulating metabolites. Dysregulated amino acid metabolism was found to be a significant feature of CRC. The amino acid transporters, SLC7A5 and SLC1A5, were identified as potential metabolic therapeutic targets. This study furthers the understanding of the metabolic processes involved in CRC. AME Publishing Company 2021-04 /pmc/articles/PMC8797830/ /pubmed/35116504 http://dx.doi.org/10.21037/tcr-20-3406 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Ni, Juan
Chen, Yang
Li, Ningning
Sun, Diandian
Ju, Haixing
Chen, Zhongjian
Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title_full Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title_fullStr Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title_full_unstemmed Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title_short Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
title_sort combination of gc-ms based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797830/
https://www.ncbi.nlm.nih.gov/pubmed/35116504
http://dx.doi.org/10.21037/tcr-20-3406
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