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Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics

Accurate prediction of chemo- or targeted therapy responses for patients with similar driver oncogenes through a simple and least-invasive assay represents an unmet need in the clinical diagnosis of non-small cell lung cancer. Using a single-cell on-chip metabolic cytometry and fluorescent metabolic...

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Autores principales: Li, Ziming, Wang, Zhuo, Tang, Yin, Lu, Xiang, Chen, Jie, Dong, Yu, Wu, Baojun, Wang, Chunying, Yang, Liu, Guo, Zhili, Xue, Min, Lu, Shun, Wei, Wei, Shi, Qihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710267/
https://www.ncbi.nlm.nih.gov/pubmed/31451693
http://dx.doi.org/10.1038/s41467-019-11808-3
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author Li, Ziming
Wang, Zhuo
Tang, Yin
Lu, Xiang
Chen, Jie
Dong, Yu
Wu, Baojun
Wang, Chunying
Yang, Liu
Guo, Zhili
Xue, Min
Lu, Shun
Wei, Wei
Shi, Qihui
author_facet Li, Ziming
Wang, Zhuo
Tang, Yin
Lu, Xiang
Chen, Jie
Dong, Yu
Wu, Baojun
Wang, Chunying
Yang, Liu
Guo, Zhili
Xue, Min
Lu, Shun
Wei, Wei
Shi, Qihui
author_sort Li, Ziming
collection PubMed
description Accurate prediction of chemo- or targeted therapy responses for patients with similar driver oncogenes through a simple and least-invasive assay represents an unmet need in the clinical diagnosis of non-small cell lung cancer. Using a single-cell on-chip metabolic cytometry and fluorescent metabolic probes, we show metabolic phenotyping on the rare disseminated tumor cells in pleural effusions across a panel of 32 lung adenocarcinoma patients. Our results reveal extensive metabolic heterogeneity of tumor cells that differentially engage in glycolysis and mitochondrial oxidation. The cell number ratio of the two metabolic phenotypes is found to be predictive for patient therapy response, physiological performance, and survival. Transcriptome analysis reveals that the glycolytic phenotype is associated with mesenchymal-like cell state with elevated expression of the resistant-leading receptor tyrosine kinase AXL and immune checkpoint ligands. Drug targeting AXL induces a significant cell killing in the glycolytic cells without affecting the cells with active mitochondrial oxidation.
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spelling pubmed-67102672019-08-28 Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics Li, Ziming Wang, Zhuo Tang, Yin Lu, Xiang Chen, Jie Dong, Yu Wu, Baojun Wang, Chunying Yang, Liu Guo, Zhili Xue, Min Lu, Shun Wei, Wei Shi, Qihui Nat Commun Article Accurate prediction of chemo- or targeted therapy responses for patients with similar driver oncogenes through a simple and least-invasive assay represents an unmet need in the clinical diagnosis of non-small cell lung cancer. Using a single-cell on-chip metabolic cytometry and fluorescent metabolic probes, we show metabolic phenotyping on the rare disseminated tumor cells in pleural effusions across a panel of 32 lung adenocarcinoma patients. Our results reveal extensive metabolic heterogeneity of tumor cells that differentially engage in glycolysis and mitochondrial oxidation. The cell number ratio of the two metabolic phenotypes is found to be predictive for patient therapy response, physiological performance, and survival. Transcriptome analysis reveals that the glycolytic phenotype is associated with mesenchymal-like cell state with elevated expression of the resistant-leading receptor tyrosine kinase AXL and immune checkpoint ligands. Drug targeting AXL induces a significant cell killing in the glycolytic cells without affecting the cells with active mitochondrial oxidation. Nature Publishing Group UK 2019-08-26 /pmc/articles/PMC6710267/ /pubmed/31451693 http://dx.doi.org/10.1038/s41467-019-11808-3 Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Li, Ziming
Wang, Zhuo
Tang, Yin
Lu, Xiang
Chen, Jie
Dong, Yu
Wu, Baojun
Wang, Chunying
Yang, Liu
Guo, Zhili
Xue, Min
Lu, Shun
Wei, Wei
Shi, Qihui
Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title_full Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title_fullStr Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title_full_unstemmed Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title_short Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
title_sort liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710267/
https://www.ncbi.nlm.nih.gov/pubmed/31451693
http://dx.doi.org/10.1038/s41467-019-11808-3
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