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A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive carcinoma located in pleural cavity. Due to lack of effective diagnostic biomarkers and therapeutic targets in MPM, the prognosis is extremely poor. Because of difficulties in sample extraction, and the high rate of misdiagnos...

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Autores principales: Chen, Zhongjian, Yang, Chenxi, Guo, Zhenying, Song, Siyu, Gao, Yun, Wang, Ding, Mao, Weimin, Liu, Junping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600931/
https://www.ncbi.nlm.nih.gov/pubmed/34789172
http://dx.doi.org/10.1186/s12885-021-08980-5
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author Chen, Zhongjian
Yang, Chenxi
Guo, Zhenying
Song, Siyu
Gao, Yun
Wang, Ding
Mao, Weimin
Liu, Junping
author_facet Chen, Zhongjian
Yang, Chenxi
Guo, Zhenying
Song, Siyu
Gao, Yun
Wang, Ding
Mao, Weimin
Liu, Junping
author_sort Chen, Zhongjian
collection PubMed
description BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive carcinoma located in pleural cavity. Due to lack of effective diagnostic biomarkers and therapeutic targets in MPM, the prognosis is extremely poor. Because of difficulties in sample extraction, and the high rate of misdiagnosis, MPM is rarely studied. Therefore, novel modeling methodology is crucially needed to facilitate MPM research. METHODS: A novel patient-derived xenograft (PDX) modeling strategy was designed, which included preliminary screening of patients with pleural thickening using computerized tomography (CT) scan, further reviewing history of disease and imaging by a senior sonographer as well as histopathological analysis by a senior pathologist, and PDX model construction using ultrasound-guided pleural biopsy from MPM patients. Gas chromatography-mass spectrometry-based metabolomics was further utilized for investigating circulating metabolic features of the PDX models. Univariate and multivariate analysis, and pathway analysis were performed to explore the differential metabolites, enriched metabolism pathways and potential metabolic targets. RESULTS: After screening using our strategy, 5 out of 116 patients were confirmed to be MPM, and their specimens were used for modeling. Two PDX models were established successfully. Metabolomics analysis revealed significant metabolic shifts in PDX models, such as dysregulations in amino acid metabolism, TCA cycle and glycolysis, and nucleotide metabolism. CONCLUSIONS: To sum up, we suggested a novel modeling strategy that may facilitate specimen availability for MM research, and by applying metabolomics in this model, several metabolic features were identified, whereas future studies with large sample size are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08980-5.
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spelling pubmed-86009312021-11-19 A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma Chen, Zhongjian Yang, Chenxi Guo, Zhenying Song, Siyu Gao, Yun Wang, Ding Mao, Weimin Liu, Junping BMC Cancer Research BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive carcinoma located in pleural cavity. Due to lack of effective diagnostic biomarkers and therapeutic targets in MPM, the prognosis is extremely poor. Because of difficulties in sample extraction, and the high rate of misdiagnosis, MPM is rarely studied. Therefore, novel modeling methodology is crucially needed to facilitate MPM research. METHODS: A novel patient-derived xenograft (PDX) modeling strategy was designed, which included preliminary screening of patients with pleural thickening using computerized tomography (CT) scan, further reviewing history of disease and imaging by a senior sonographer as well as histopathological analysis by a senior pathologist, and PDX model construction using ultrasound-guided pleural biopsy from MPM patients. Gas chromatography-mass spectrometry-based metabolomics was further utilized for investigating circulating metabolic features of the PDX models. Univariate and multivariate analysis, and pathway analysis were performed to explore the differential metabolites, enriched metabolism pathways and potential metabolic targets. RESULTS: After screening using our strategy, 5 out of 116 patients were confirmed to be MPM, and their specimens were used for modeling. Two PDX models were established successfully. Metabolomics analysis revealed significant metabolic shifts in PDX models, such as dysregulations in amino acid metabolism, TCA cycle and glycolysis, and nucleotide metabolism. CONCLUSIONS: To sum up, we suggested a novel modeling strategy that may facilitate specimen availability for MM research, and by applying metabolomics in this model, several metabolic features were identified, whereas future studies with large sample size are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08980-5. BioMed Central 2021-11-17 /pmc/articles/PMC8600931/ /pubmed/34789172 http://dx.doi.org/10.1186/s12885-021-08980-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Zhongjian
Yang, Chenxi
Guo, Zhenying
Song, Siyu
Gao, Yun
Wang, Ding
Mao, Weimin
Liu, Junping
A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title_full A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title_fullStr A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title_full_unstemmed A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title_short A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
title_sort novel pdx modeling strategy and its application in metabolomics study for malignant pleural mesothelioma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600931/
https://www.ncbi.nlm.nih.gov/pubmed/34789172
http://dx.doi.org/10.1186/s12885-021-08980-5
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