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Sherlock L, Martin BR, Behsangar S, Mok KH. Application of novel AI-based algorithms to biobank data: uncovering of new features and linear relationships. Front Med (Lausanne) 2023; 10:1162808. [PMID: 37521348 PMCID: PMC10373878 DOI: 10.3389/fmed.2023.1162808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/16/2023] [Indexed: 08/01/2023] Open
Abstract
We independently analyzed two large public domain datasets that contain 1H-NMR spectral data from lung cancer and sex studies. The biobanks were sourced from the Karlsruhe Metabolomics and Nutrition (KarMeN) study and Bayesian Automated Metabolite Analyzer for NMR data (BATMAN) study. Our approach of applying novel artificial intelligence (AI)-based algorithms to NMR is an attempt to globalize metabolomics and demonstrate its clinical applications. The intention of this study was to analyze the resulting spectra in the biobanks via AI application to demonstrate its clinical applications. This technique enables metabolite mapping in areas of localized enrichment as a measure of true activity while also allowing for the accurate categorization of phenotypes.
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Affiliation(s)
- Lee Sherlock
- Meta-Flux Ltd., Dublin, Ireland
- Trinity Biomedical Sciences Institute (TBSI), School of Biochemistry and Immunology, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | | | | | - K. H. Mok
- Trinity Biomedical Sciences Institute (TBSI), School of Biochemistry and Immunology, Trinity College Dublin, The University of Dublin, Dublin, Ireland
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2
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Vanhove K, Derveaux E, Mesotten L, Thomeer M, Criel M, Mariën H, Adriaensens P. Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics. Int J Mol Sci 2022; 23:ijms23105602. [PMID: 35628415 PMCID: PMC9146819 DOI: 10.3390/ijms23105602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/14/2022] [Accepted: 05/15/2022] [Indexed: 11/16/2022] Open
Abstract
Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.
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Affiliation(s)
- Karolien Vanhove
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan 1-Building D, B-3590 Diepenbeek, Belgium;
- Department of Respiratory Medicine, AZ Vesalius, Hazelereik 51, B-3700 Tongeren, Belgium
- Correspondence:
| | - Elien Derveaux
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, B-3500 Hasselt, Belgium; (E.D.); (H.M.)
| | - Liesbet Mesotten
- Department of Nuclear Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, B-3600 Genk, Belgium;
| | - Michiel Thomeer
- Department of Respiratory Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, B-3600 Genk, Belgium; (M.T.); (M.C.)
| | - Maarten Criel
- Department of Respiratory Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, B-3600 Genk, Belgium; (M.T.); (M.C.)
| | - Hanne Mariën
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, B-3500 Hasselt, Belgium; (E.D.); (H.M.)
| | - Peter Adriaensens
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan 1-Building D, B-3590 Diepenbeek, Belgium;
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3
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Singh A, Prakash V, Gupta N, Kumar A, Kant R, Kumar D. Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach. ACS OMEGA 2022; 7:5510-5520. [PMID: 35187366 PMCID: PMC8851899 DOI: 10.1021/acsomega.1c06941] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/18/2022] [Indexed: 06/01/2023]
Abstract
Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics studies compare the normalized spectral features which not only provide ambiguous information but further limit the clinical translation of this information. Various such issues can be resolved by performing the concentration profiling of various metabolites with respect to formate as an internal reference using commercial software Chenomx. Continuing our efforts in this direction, the serum metabolic profiles were measured on 39 LC patients and 42 normal controls (NCs, comparable in age/sex) using high-field 800 MHz NMR spectroscopy and compared using multivariate statistical analysis tools to identify metabolic disturbances and metabolites of diagnostic potential. Partial least-squares discriminant analysis (PLS-DA) model revealed a distinct separation between LC and NC groups and resulted in excellent discriminatory ability with the area under the receiver-operating characteristic (AUROC) = 0.97 [95% CI = 0.89-1.00]. The metabolic features contributing to the differentiation of LC from NC samples were identified first using variable importance in projection (VIP) score analysis and then checked for their statistical significance (with p-value < 0.05) and diagnostic potential using the ROC curve analysis. The analysis revealed relevant metabolic disturbances associated with LC. Among various circulatory metabolites, six metabolites, including histidine, glutamine, glycine, threonine, alanine, and valine, were found to be of apposite diagnostic potential for clinical implications. These metabolic alterations indicated altered glucose metabolism, aberrant fatty acid synthesis, and augmented utilization of various amino acids including active glutaminolysis in LC.
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Affiliation(s)
- Anjana Singh
- All
India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand 249201, India
- Pulmonary
& Critical Care Medicine, King George’s
Medical University, Lucknow, Uttar Pradesh 226003, India
| | - Ved Prakash
- Pulmonary
& Critical Care Medicine, King George’s
Medical University, Lucknow, Uttar Pradesh 226003, India
| | - Nikhil Gupta
- Centre
of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh 226014, India
- Department
of Chemistry, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Ashish Kumar
- Department
of Chemistry, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Ravi Kant
- All
India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand 249201, India
| | - Dinesh Kumar
- Centre
of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh 226014, India
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4
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Callejón-Leblic B, Arias-Borrego A, Rodríguez-Moro G, Navarro Roldán F, Pereira-Vega A, Gómez-Ariza JL, García-Barrera T. Advances in lung cancer biomarkers: The role of (metal-) metabolites and selenoproteins. Adv Clin Chem 2020; 100:91-137. [PMID: 33453868 DOI: 10.1016/bs.acc.2020.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Lung cancer (LC) is the second most common cause of death in men after prostate cancer, and the third most recurrent type of tumor in women after breast and colon cancers. Unfortunately, when LC symptoms begin to appear, the disease is already in an advanced stage and the survival rate only reaches 2%. Thus, there is an urgent need for early diagnosis of LC using specific biomarkers, as well as effective therapies and strategies against LC. On the other hand, the influence of metals on more than 50% of proteins is responsible for their catalytic properties or structure, and their presence in molecules is determined in many cases by the genome. Research has shown that redox metal dysregulation could be the basis for the onset and progression of LC disease. Moreover, metals can interact between them through antagonistic, synergistic and competitive mechanisms, and for this reason metals ratios and correlations in LC should be explored. One of the most studied antagonists against the toxic action of metals is selenium, which plays key roles in medicine, especially related to selenoproteins. The study of potential biomarkers able to diagnose the disease in early stage is conditioned by the development of new analytical methodologies. In this sense, omic methodologies like metallomics, proteomics and metabolomics can greatly assist in the discovery of biomarkers for LC early diagnosis.
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Affiliation(s)
- Belén Callejón-Leblic
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain
| | - Ana Arias-Borrego
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain
| | - Gema Rodríguez-Moro
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain
| | - Francisco Navarro Roldán
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Integrated Sciences-Cell Biology, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain
| | | | - José Luis Gómez-Ariza
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain
| | - Tamara García-Barrera
- Research Center for Natural Resources, Health and the Environment (RENSMA), University of Huelva, Huelva, Spain; Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Huelva, Spain.
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5
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Hoang LT, Domingo-Sabugo C, Starren ES, Willis-Owen SAG, Morris-Rosendahl DJ, Nicholson AG, Cookson WOCM, Moffatt MF. Metabolomic, transcriptomic and genetic integrative analysis reveals important roles of adenosine diphosphate in haemostasis and platelet activation in non-small-cell lung cancer. Mol Oncol 2019; 13:2406-2421. [PMID: 31461552 PMCID: PMC6822241 DOI: 10.1002/1878-0261.12568] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 08/23/2019] [Indexed: 12/11/2022] Open
Abstract
Lung cancer is the leading cause of cancer‐related deaths in the world. The most prevalent subtype, accounting for 85% of cases, is non‐small‐cell lung cancer (NSCLC). Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the most common subtypes. Despite recent advances in treatment, the low 5‐year survival rate of NSCLC patients (approximately 13%) reflects the lack of early diagnostic biomarkers and incomplete understanding of the underlying disease mechanisms. We hypothesized that integration of metabolomic, transcriptomic and genetic profiles of tumours and matched normal tissues could help to identify important factors and potential therapeutic targets that contribute to tumorigenesis. We integrated omics profiles in tumours and matched adjacent normal tissues of patients with LUSC (N = 20) and LUAD (N = 17) using multiple system biology approaches. We confirmed the presence of previously described metabolic pathways in NSCLC, particularly those mediating the Warburg effect. In addition, through our combined omics analyses we found that metabolites and genes that contribute to haemostasis, angiogenesis, platelet activation and cell proliferation were predominant in both subtypes of NSCLC. The important roles of adenosine diphosphate in promoting cancer metastasis through platelet activation and angiogenesis suggest this metabolite could be a potential therapeutic target.
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Affiliation(s)
- Long T Hoang
- National Heart and Lung Institute, Faculty of Medicine, Imperial College London, UK
| | - Clara Domingo-Sabugo
- National Heart and Lung Institute, Faculty of Medicine, Imperial College London, UK
| | - Elizabeth S Starren
- National Heart and Lung Institute, Faculty of Medicine, Imperial College London, UK
| | | | | | - Andrew G Nicholson
- National Heart and Lung Institute, Faculty of Medicine, Imperial College London, UK.,Department of Histopathology, Royal Brompton and Harefield NHS Foundation Trust, London, UK
| | | | - Miriam F Moffatt
- National Heart and Lung Institute, Faculty of Medicine, Imperial College London, UK
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6
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Tang Y, Li Z, Lazar L, Fang Z, Tang C, Zhao J. Metabolomics workflow for lung cancer: Discovery of biomarkers. Clin Chim Acta 2019; 495:436-445. [DOI: 10.1016/j.cca.2019.05.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 05/13/2019] [Accepted: 05/13/2019] [Indexed: 12/20/2022]
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7
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Padayachee T, Khamiakova T, Louis E, Adriaensens P, Burzykowski T. The impact of the method of extracting metabolic signal from 1H-NMR data on the classification of samples: A case study of binning and BATMAN in lung cancer. PLoS One 2019; 14:e0211854. [PMID: 30726273 PMCID: PMC6364941 DOI: 10.1371/journal.pone.0211854] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 01/23/2019] [Indexed: 11/23/2022] Open
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is a principal analytical technique in metabolomics. Extracting metabolic information from NMR spectra is complex due to the fact that an immense amount of detail on the chemical composition of a biological sample is expressed through a single spectrum. The simplest approach to quantify the signal is through spectral binning which involves subdividing the spectra into regions along the chemical shift axis and integrating the peaks within each region. However, due to overlapping resonance signals, the integration values do not always correspond to the concentrations of specific metabolites. An alternate, more advanced statistical approach is spectral deconvolution. BATMAN (Bayesian AuTomated Metabolite Analyser for NMR data) performs spectral deconvolution using prior information on the spectral signatures of metabolites. In this way, BATMAN estimates relative metabolic concentrations. In this study, both spectral binning and spectral deconvolution using BATMAN were applied to 400 MHz and 900 MHz NMR spectra of blood plasma samples from lung cancer patients and control subjects. The relative concentrations estimated by BATMAN were compared with the binning integration values in terms of their ability to discriminate between lung cancer patients and controls. For the 400 MHz data, the spectral binning approach provided greater discriminatory power. However, for the 900 MHz data, the relative metabolic concentrations obtained by using BATMAN provided greater predictive power. While spectral binning is computationally advantageous and less laborious, complementary models developed using BATMAN-estimated features can add complementary information regarding the biological interpretation of the data and therefore are clinically useful.
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Affiliation(s)
| | | | - Evelyne Louis
- Faculty of Medicine and Life Sciences, Hasselt University, Diepenbeek, Belgium
| | - Peter Adriaensens
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Diepenbeek, Belgium
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8
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Moreno P, Jiménez-Jiménez C, Garrido-Rodríguez M, Calderón-Santiago M, Molina S, Lara-Chica M, Priego-Capote F, Salvatierra Á, Muñoz E, Calzado MA. Metabolomic profiling of human lung tumor tissues - nucleotide metabolism as a candidate for therapeutic interventions and biomarkers. Mol Oncol 2018; 12:1778-1796. [PMID: 30099851 PMCID: PMC6165994 DOI: 10.1002/1878-0261.12369] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 07/24/2018] [Accepted: 08/03/2018] [Indexed: 12/14/2022] Open
Abstract
Although metabolomics has attracted considerable attention in the field of lung cancer (LC) detection and management, only a very limited number of works have applied it to tissues. As such, the aim of this study was the thorough analysis of metabolic profiles of relevant LC tissues, including the most important histological subtypes (adenocarcinoma and squamous cell lung carcinoma). Mass spectrometry‐based metabolomics, along with genetic expression and histological analyses, were performed as part of this study, the widest to date, to identify metabolic alterations in tumors of the most relevant histological subtypes in lung. A total of 136 lung tissue samples were analyzed and 851 metabolites were identified through metabolomic analysis. Our data show the existence of a clear metabolic alteration not only between tumor vs. nonmalignant tissue in each patient, but also inherently intrinsic changes in both AC and SCC. Significant changes were observed in the most relevant biochemical pathways, and nucleotide metabolism showed an important number of metabolites with high predictive capability values. The present study provides a detailed analysis of the metabolomic changes taking place in relevant biochemical pathways of the most important histological subtypes of LC, which can be used as biomarkers and also to identify novel targets.
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Affiliation(s)
- Paula Moreno
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Unidad de Cirugía Torácica y Trasplante Pulmonar, Hospital Universitario Reina Sofía, Cordoba, Spain
| | - Carla Jiménez-Jiménez
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Cordoba, Spain
| | | | - Mónica Calderón-Santiago
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Química Analítica, Universidad de Córdoba, Cordoba, Spain
| | - Susana Molina
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Cordoba, Spain
| | - Maribel Lara-Chica
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Cordoba, Spain
| | - Feliciano Priego-Capote
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Química Analítica, Universidad de Córdoba, Cordoba, Spain
| | - Ángel Salvatierra
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Unidad de Cirugía Torácica y Trasplante Pulmonar, Hospital Universitario Reina Sofía, Cordoba, Spain
| | - Eduardo Muñoz
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Cordoba, Spain
| | - Marco A Calzado
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Cordoba, Spain.,Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Cordoba, Spain
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9
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Hanash SM, Ostrin EJ, Fahrmann JF. Blood based biomarkers beyond genomics for lung cancer screening. Transl Lung Cancer Res 2018; 7:327-335. [PMID: 30050770 DOI: 10.21037/tlcr.2018.05.13] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
While there is considerable interest at the present time in the development of so-called liquid biopsy approaches for cancer detection based notably on circulating tumor DNA, there are other types of potential biomarkers that show promise for lung cancer screening and early detection. Here we review approaches and some of the promising markers based on proteomics, metabolomics and the immune response to tumor antigens in the form of autoantibodies.
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Affiliation(s)
- Samir M Hanash
- Department of Clinical Cancer Prevention, MD Anderson Cancer Center, Houston, TX, USA
| | - Edwin Justin Ostrin
- Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Johannes F Fahrmann
- Department of Clinical Cancer Prevention, MD Anderson Cancer Center, Houston, TX, USA
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10
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Yu L, Li K, Zhang X. Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review. Oncotarget 2017; 8:115774-115786. [PMID: 29383200 PMCID: PMC5777812 DOI: 10.18632/oncotarget.22404] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 09/21/2017] [Indexed: 02/05/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death. Next-generation metabolomics is becoming a powerful emerging technology for studying the systems biology and chemistry of health and disease. This mini review summarized the main platforms of next-generation metabolomics and its main applications in lung cancer including early diagnosis, pathogenesis, classifications and precision medicine. The period covers between 2009 and August, 2017. The major issues and future directions of metabolomics in lung cancer research and clinical applications were also discussed.
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Affiliation(s)
- Li Yu
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China
| | - Kefeng Li
- School of Medicine, University of California San Diego, San Diego, CA, USA
| | - Xiaoye Zhang
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China
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