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Sci Rep. 2019 Jul 16;9(1):10319. doi: 10.1038/s41598-019-46643-5.

Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer.

Author information

1
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, 02114, USA.
2
Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, 02114, USA.
3
Division of X-Ray Imaging and Computed Tomography, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
4
Department of Urology, CCM, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany.
5
Department of Environmental Health, Harvard T.H. Chan School of Public Health and Department of Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts, 02115, USA.
6
Department of Haematology and Oncology, CCM, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany.
7
Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, 97080, Würzburg, Germany.
8
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, 02115, USA.
9
Department of Environmental Health, Harvard T.H. Chan School of Public Health and Department of Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts, 02115, USA. dchris@hsph.harvard.edu.
10
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, 02114, USA. cheng@nmr.mgh.harvard.edu.
11
Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, 02114, USA. cheng@nmr.mgh.harvard.edu.

Abstract

Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.

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