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Nat Commun. 2019 Aug 26;10(1):3856. doi: 10.1038/s41467-019-11808-3.

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

Li Z1, Wang Z2, Tang Y3,4, Lu X5, Chen J3, Dong Y3, Wu B3, Wang C3, Yang L6, Guo Z7, Xue M7, Lu S8, Wei W9,10,11, Shi Q12,13,14.

Author information

1
Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, 200030, Shanghai, China.
2
Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, 200032, Shanghai, China.
3
Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 200240, Shanghai, China.
4
Institute for Systems Biology, Seattle, WA, 98109, USA.
5
Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
6
Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University, 200008, Shanghai, China.
7
Department of Chemistry, University of California, Riverside, CA, 92521, USA.
8
Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, 200030, Shanghai, China. shunlu@sjtu.edu.cn.
9
Institute for Systems Biology, Seattle, WA, 98109, USA. wwei@systemsbiology.org.
10
Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. wwei@systemsbiology.org.
11
Jonnson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. wwei@systemsbiology.org.
12
Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, 200032, Shanghai, China. qihuishi@fudan.edu.cn.
13
Minhang Branch, Zhongshan Hospital, Fudan University, 201199, Shanghai, China. qihuishi@fudan.edu.cn.
14
Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, 201199, Shanghai, China. qihuishi@fudan.edu.cn.

Abstract

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.

PMID:
31451693
PMCID:
PMC6710267
DOI:
10.1038/s41467-019-11808-3
[Indexed for MEDLINE]
Free PMC Article

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