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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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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. |
format | Online Article Text |
id | pubmed-6710267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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