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López-López Á, López-Gonzálvez Á, Barbas C. Metabolomics for searching validated biomarkers in cancer studies: a decade in review. Expert Rev Mol Diagn 2024:1-26. [PMID: 38904089 DOI: 10.1080/14737159.2024.2368603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 06/12/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways. AREAS COVERED This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types. EXPERT OPINION Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.
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Affiliation(s)
- Ángeles López-López
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
| | - Ángeles López-Gonzálvez
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
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Wang C, Gamage PL, Jiang W, Mudalige T. Excipient-related impurities in liposome drug products. Int J Pharm 2024; 657:124164. [PMID: 38688429 DOI: 10.1016/j.ijpharm.2024.124164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/02/2024]
Abstract
Liposomes are widely used in the pharmaceutical industry as drug delivery systems to increase the efficacy and reduce the off-target toxicity of active pharmaceutical ingredients (APIs). The liposomes are more complex drug delivery systems than the traditional dosage forms, and phospholipids and cholesterol are the major structural excipients. These two excipients undergo hydrolysis and/or oxidation during liposome preparation and storage, resulting in lipids hydrolyzed products (LHPs) and cholesterol oxidation products (COPs) in the final liposomal formulations. These excipient-related impurities at elevated concentrations may affect liposome stability and exert biological functions. This review focuses on LHPs and COPs, two major categories of excipient-related impurities in the liposomal formulations, and discusses factors affecting their formation, and analytical methods to determine these excipient-related impurities.
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Affiliation(s)
- Changguang Wang
- Arkansas Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Prabhath L Gamage
- Arkansas Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenlei Jiang
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, 20993, USA.
| | - Thilak Mudalige
- Arkansas Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
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3
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Shi W, Cheng Y, Zhu H, Zhao L. Metabolomics and lipidomics in non-small cell lung cancer. Clin Chim Acta 2024; 555:117823. [PMID: 38325713 DOI: 10.1016/j.cca.2024.117823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/09/2024]
Abstract
Due to its insidious nature, lung cancer remains a leading cause of cancer-related deaths worldwide. Therefore, there is an urgent need to identify sensitive/specific biomarkers for early diagnosis and monitoring. The current study was designed to provide a current metabolic profile of non-small cell lung cancer (NSCLC) by systematically reviewing and summarizing various metabolomic/ lipidomic studies based on NSCLC blood samples, attempting to find biomarkers in human blood that can predict or diagnose NSCLC, and investigating the involvement of key metabolites in the pathogenesis of NSCLC. We searched all articles on lung cancer published in Elsevier, PubMed, Web of Science and the Cochrane Library between January 2012 and December 2022. After critical selection, a total of 31 studies (including 2768 NSCLC patients and 9873 healthy individuals) met the inclusion criteria, and 22 were classified as "high quality". Forty-six metabolites related to NSCLC were repeatedly identified, involving glucose metabolism, amino acid metabolism, lipid metabolism and nucleotide metabolism. Pyruvic acid, carnitine, phenylalanine, isoleucine, kynurenine and 3-hydroxybutyrate showed upward trends in all studies, citric acid, glycine, threonine, cystine, alanine, histidine, inosine, betaine and arachidic acid showed downward trends in all studies. This review summarizes the existing metabolomic/lipidomic studies related to the identification of blood biomarkers in NSCLC, examines the role of key metabolites in the pathogenesis of NSCLC, and provides an important reference for the clinical diagnosis and treatment of NSCLC. Due to the limited size and design heterogeneity of the existing studies, there is an urgent need for standardization of future studies, while validating existing findings with more studies.
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Affiliation(s)
- Wei Shi
- Shenyang Pharmaceutical University, 103 Wenhua Road Shenhe District, 110016 Shenyang, Liaoning Province, PR China
| | - Yizhen Cheng
- Shenyang Pharmaceutical University, 103 Wenhua Road Shenhe District, 110016 Shenyang, Liaoning Province, PR China
| | - Haihua Zhu
- Betta Pharmaceuticals Co., Ltd, 24 Wuzhou Road Yuhang Economic and Technological Development Area, Hangzhou, Zhejiang Province, PR China
| | - Longshan Zhao
- Shenyang Pharmaceutical University, 103 Wenhua Road Shenhe District, 110016 Shenyang, Liaoning Province, PR China.
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Pautova AK. Metabolic Profiling of Aromatic Compounds. Metabolites 2024; 14:107. [PMID: 38392999 PMCID: PMC10890443 DOI: 10.3390/metabo14020107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 02/02/2024] [Indexed: 02/25/2024] Open
Abstract
Metabolic profiling is a powerful modern tool in searching for novel biomarkers and indicators of normal or pathological processes in the body [...].
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Affiliation(s)
- Alisa K Pautova
- Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, 25-2 Petrovka Str., 107031 Moscow, Russia
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Almalki AH. Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer. Metabolites 2023; 13:1037. [PMID: 37887362 PMCID: PMC10609104 DOI: 10.3390/metabo13101037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 09/10/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.
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Affiliation(s)
- Atiah H. Almalki
- Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
- Addiction and Neuroscience Research Unit, Health Science Campus, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
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Kannampuzha S, Mukherjee AG, Wanjari UR, Gopalakrishnan AV, Murali R, Namachivayam A, Renu K, Dey A, Vellingiri B, Madhyastha H, Ganesan R. A Systematic Role of Metabolomics, Metabolic Pathways, and Chemical Metabolism in Lung Cancer. Vaccines (Basel) 2023; 11:vaccines11020381. [PMID: 36851259 PMCID: PMC9960365 DOI: 10.3390/vaccines11020381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
Lung cancer (LC) is considered as one of the leading causes of cancer-associated mortalities. Cancer cells' reprogrammed metabolism results in changes in metabolite concentrations, which can be utilized to identify a distinct metabolic pattern or fingerprint for cancer detection or diagnosis. By detecting different metabolic variations in the expression levels of LC patients, this will help and enhance early diagnosis methods as well as new treatment strategies. The majority of patients are identified at advanced stages after undergoing a number of surgical procedures or diagnostic testing, including the invasive procedures. This could be overcome by understanding the mechanism and function of differently regulated metabolites. Significant variations in the metabolites present in the different samples can be analyzed and used as early biomarkers. They could also be used to analyze the specific progression and type as well as stages of cancer type making it easier for the treatment process. The main aim of this review article is to focus on rewired metabolic pathways and the associated metabolite alterations that can be used as diagnostic and therapeutic targets in lung cancer diagnosis as well as treatment strategies.
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Affiliation(s)
- Sandra Kannampuzha
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Anirban Goutam Mukherjee
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Uddesh Ramesh Wanjari
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Abilash Valsala Gopalakrishnan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
- Correspondence: (A.V.G.); (R.G.)
| | - Reshma Murali
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Arunraj Namachivayam
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Kaviyarasi Renu
- Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College & Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, India
| | - Abhijit Dey
- Department of Life Sciences, Presidency University, Kolkata 700073, India
| | - Balachandar Vellingiri
- Stem Cell and Regenerative Medicine/Translational Research, Department of Zoology, School of Basic Sciences, Central University of Punjab (CUPB), Bathinda 151401, India
| | - Harishkumar Madhyastha
- Department of Cardiovascular Physiology, Faculty of Medicine, University of Miyazaki, Miyazaki 889-1692, Japan
| | - Raja Ganesan
- Institute for Liver and Digestive Diseases, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea
- Correspondence: (A.V.G.); (R.G.)
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Loots DT, Adeniji AA, Van Reenen M, Ozturk M, Brombacher F, Parihar SP. The metabolomics of a protein kinase C delta (PKCδ) knock-out mouse model. Metabolomics 2022; 18:92. [PMID: 36371785 PMCID: PMC9660189 DOI: 10.1007/s11306-022-01949-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 10/29/2022] [Indexed: 11/15/2022]
Abstract
INTRODUCTION PKCδ is ubiquitously expressed in mammalian cells and its dysregulation plays a key role in the onset of several incurable diseases and metabolic disorders. However, much remains unknown about the metabolic pathways and disturbances induced by PKC deficiency, as well as the metabolic mechanisms involved. OBJECTIVES This study aims to use metabolomics to further characterize the function of PKC from a metabolomics standpoint, by comparing the full serum metabolic profiles of PKC deficient mice to those of wild-type mice. METHODS The serum metabolomes of PKCδ knock-out mice were compared to that of a wild-type strain using a GCxGC-TOFMS metabolomics research approach and various univariate and multivariate statistical analyses. RESULTS Thirty-seven serum metabolite markers best describing the difference between PKCδ knock-out and wild-type mice were identified based on a PCA power value > 0.9, a t-test p-value < 0.05, or an effect size > 1. XERp prediction was also done to accurately select the metabolite markers within the 2 sample groups. Of the metabolite markers identified, 78.4% (29/37) were elevated and 48.65% of these markers were fatty acids (18/37). It is clear that a total loss of PKCδ functionality results in an inhibition of glycolysis, the TCA cycle, and steroid synthesis, accompanied by upregulation of the pentose phosphate pathway, fatty acids oxidation, cholesterol transport/storage, single carbon and sulphur-containing amino acid synthesis, branched-chain amino acids (BCAA), ketogenesis, and an increased cell signalling via N-acetylglucosamine. CONCLUSION The charaterization of the dysregulated serum metabolites in this study, may represent an additional tool for the early detection and screening of PKCδ-deficiencies or abnormalities.
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Affiliation(s)
- Du Toit Loots
- Human Metabolomics, North-West University, Hoffman Street, 2531, Potchefstroom, South Africa.
| | | | - Mari Van Reenen
- Human Metabolomics, North-West University, Hoffman Street, 2531, Potchefstroom, South Africa
| | - Mumin Ozturk
- Human Metabolomics, North-West University, Hoffman Street, 2531, Potchefstroom, South Africa
- International Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town-Component, Cape Town, South Africa
| | - Frank Brombacher
- Human Metabolomics, North-West University, Hoffman Street, 2531, Potchefstroom, South Africa
- International Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town-Component, Cape Town, South Africa
- Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology and South African Medical Research Council (SAMRC) Immunology of Infectious Diseases, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Wellcome Center for Infectious Disease Research in Africa (CIDRI-Africa), Institute of Infectious Diseases and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Suraj P Parihar
- Human Metabolomics, North-West University, Hoffman Street, 2531, Potchefstroom, South Africa.
- International Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town-Component, Cape Town, South Africa.
- Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology and South African Medical Research Council (SAMRC) Immunology of Infectious Diseases, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
- Wellcome Center for Infectious Disease Research in Africa (CIDRI-Africa), Institute of Infectious Diseases and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
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Kim JO, Balshaw R, Trevena C, Banerji S, Murphy L, Dawe D, Tan L, Srinathan S, Buduhan G, Kidane B, Qing G, Domaratzki M, Aliani M. Data-driven identification of plasma metabolite clusters and metabolites of interest for potential detection of early-stage non-small cell lung cancer cases versus cancer-free controls. Cancer Metab 2022; 10:16. [PMID: 36224630 PMCID: PMC9559833 DOI: 10.1186/s40170-022-00294-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 09/22/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development. METHODS Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates. RESULTS A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol. CONCLUSIONS Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.
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Affiliation(s)
- Julian O Kim
- Section of Radiation Oncology, Department of Radiology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada. .,CancerCare Manitoba Research Institute, Winnipeg, Manitoba, Canada.
| | - Robert Balshaw
- George and Fay Yee Center for Healthcare Innovation, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Connel Trevena
- Department of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Shantanu Banerji
- CancerCare Manitoba Research Institute, Winnipeg, Manitoba, Canada.,Section of Medical Oncology, Department of Internal Medicine, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Leigh Murphy
- CancerCare Manitoba Research Institute, Winnipeg, Manitoba, Canada.,Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba, Canada
| | - David Dawe
- CancerCare Manitoba Research Institute, Winnipeg, Manitoba, Canada.,Section of Medical Oncology, Department of Internal Medicine, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Lawrence Tan
- Section of Thoracic Surgery, Department of Surgery, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Sadeesh Srinathan
- Section of Thoracic Surgery, Department of Surgery, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Gordon Buduhan
- Section of Thoracic Surgery, Department of Surgery, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Biniam Kidane
- Section of Thoracic Surgery, Department of Surgery, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Gefei Qing
- Department of Human Pathology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Michael Domaratzki
- Department of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Michel Aliani
- Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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Introduction to Mass Spectrometry for Bimolecular Analysis in a Clinical Laboratory. Methods Mol Biol 2022; 2546:1-12. [PMID: 36127573 DOI: 10.1007/978-1-0716-2565-1_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Mass spectrometry is a technique that identifies analytes based on mass-to-charge (m/z) ratio and structural fragments. Although this technique has been used in research and specialized clinical laboratories for decades, only in recent years has mass spectrometry become popular in routine clinical laboratories. Mass spectrometry, especially when coupled with gas chromatography or liquid chromatography, provides very specific and often sensitive analysis of many analytes. Other advantages of mass spectrometry include simultaneous analysis of multiple analytes (>100) and generally limited requirement for specialized reagents. Commonly measured analytes by mass spectrometry include metabolites, drugs, hormones, and proteins.
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10
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Zang X, Zhang J, Jiao P, Xue X, Lv Z. Non-Small Cell Lung Cancer Detection and Subtyping by UPLC-HRMS-Based Tissue Metabolomics. J Proteome Res 2022; 21:2011-2022. [PMID: 35856400 DOI: 10.1021/acs.jproteome.2c00316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Non-small cell lung cancer (NSCLC) is the prevalent histological subtype of lung cancer. In this study, we performed ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based metabolic profiling of 227 tissue samples from 79 lung cancer patients with adenocarcinoma (AC) or squamous cell carcinoma (SCC). Orthogonal partial least squares-discriminant analysis (oPLS-DA) analyses showed that AC, SCC, and NSCLC tumors were discriminated from adjacent noncancerous tissue (ANT) and distant noncancerous tissue (DNT) samples with good accuracies (91.3, 100, and 88.3%), sensitivities (85.7, 100, and 83.9%), and specificities (94.3, 100, and 90.7%), using 12, 4, and 7 discriminant metabolites, respectively. The discriminant panel for AC detection included valine, sphingosine, glutamic acid γ-methyl ester, and lysophosphatidylcholine (LPC) (16:0), levels of which in tumor tissues were significantly altered. Valine, sphingosine, LPC (18:1), and leucine derivatives were used for SCC detection. The discrimination between AC and SCC had 96.8% accuracy, 98.2% sensitivity, and 85.7% specificity using a five-metabolite panel, of which valine and creatine had significant differences. The classification models were further verified with external validation sets, showing a promising prospect for NSCLC tissue detection and subtyping.
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Affiliation(s)
- Xiaoling Zang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Jie Zhang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Peng Jiao
- Department of Thoracic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P. R. China
| | - Xuyan Xue
- College of Physics, Qingdao University, Qingdao, Shandong 266071, P. R. China
| | - Zhihua Lv
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
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Panebianco C, Villani A, Pisati F, Orsenigo F, Ulaszewska M, Latiano TP, Potenza A, Andolfo A, Terracciano F, Tripodo C, Perri F, Pazienza V. Butyrate, a postbiotic of intestinal bacteria, affects pancreatic cancer and gemcitabine response in in vitro and in vivo models. Biomed Pharmacother 2022; 151:113163. [PMID: 35617803 DOI: 10.1016/j.biopha.2022.113163] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/16/2022] [Accepted: 05/16/2022] [Indexed: 11/02/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer. The characteristic excessive stromatogenesis accompanying the growth of this tumor is believed to contribute to chemoresistance which, together with drug toxicity, results in poor clinical outcome. An increasing number of studies are showing that gut microbiota and their metabolites are implicated in cancer pathogenesis, progression and response to therapies. In this study we tested butyrate, a product of dietary fibers' bacterial fermentation, whose anticancer and anti-inflammatory functions are known. We provided in vitro evidence that, beside slowing proliferation, butyrate enhanced gemcitabine effectiveness against two human pancreatic cancer cell lines, mainly inducing apoptosis. In addition, we observed that, when administered to a PDAC mouse model, alone or combined with gemcitabine treatment, butyrate markedly reduced the cancer-associated stromatogenesis, preserved intestinal mucosa integrity and affected fecal microbiota composition by increasing short chain fatty acids producing bacteria and decreasing some pro-inflammatory microorganisms. Furthermore, a biochemical serum analysis showed butyrate to ameliorate some markers of kidney and liver damage, whereas a metabolomics approach revealed a deep modification of lipid metabolism, which may affect tumor progression or response to therapy. Such results support that butyrate supplementation, in addition to conventional therapies, can interfere with pancreatic cancer biology and response to treatment and can alleviate some damages associated to cancer itself or to chemotherapy.
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Affiliation(s)
- Concetta Panebianco
- Division of Gastroenterology, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Annacandida Villani
- Division of Gastroenterology, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Federica Pisati
- Histopathology Unit, Cogentech S.C.a.R.L, Via Adamello, 16, 20139 Milan, MI, Italy
| | | | - Marynka Ulaszewska
- Proteomics and Metabolomics Facility (ProMeFa), IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132 Milan, Italy
| | - Tiziana Pia Latiano
- Oncology Unit, Fondazione IRCCS "Casa Sollievo della Sofferenza Hospital, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Adele Potenza
- Dietetic and Clinical Nutrition Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Annapaola Andolfo
- Proteomics and Metabolomics Facility (ProMeFa), IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132 Milan, Italy
| | - Fulvia Terracciano
- Division of Gastroenterology, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Claudio Tripodo
- Histopathology Unit, Cogentech S.C.a.R.L, Via Adamello, 16, 20139 Milan, MI, Italy; Tumor Immunology Unit, Department of Health Sciences, University of Palermo, Via del Vespro 129, 90127 Palermo, Italy
| | - Francesco Perri
- Division of Gastroenterology, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy
| | - Valerio Pazienza
- Division of Gastroenterology, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 1, 71013 San Giovanni Rotondo, FG, Italy.
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12
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Yang Z, Li W, Huang H, Ren S, Men Y, Li F, Yu X, Luo Q. Detection of serum phospholipids by microchannel-integrated black phosphorus-assisted laser desorption/ionization mass spectrometry. Talanta 2022; 237:122978. [PMID: 34736700 DOI: 10.1016/j.talanta.2021.122978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 10/14/2021] [Accepted: 10/16/2021] [Indexed: 10/20/2022]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has been widely applied in the analysis of phospholipids in biological samples. However, it remains a challenge to improve the sensitivity and reproducibility and to control the background noise of matrices. In this study, black phosphorus nanomaterial was used as the matrix of MALDI-MS, and microchannel technique was combined. This microchannel-integrated black phosphorus-assisted laser desorption/ionization (BPALDI) MS approach can effectively detect a variety of lipids with a small amount of sample, and has high sensitivity for phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) with a detection limit of 0.2 μg/mL. Compared with traditional matrices, BPALDI-MS has the advantages of high sensitivity, good reproducibility, and high salt tolerance. This method was successfully applied in the detection of serum PC/LPC ratios in children patients with asthma or bronchopneumonia. This work provides a novel application of black phosphorus matrix and microchannel technique, and gives new insights into method development of rapid screening and identification of disease indicators in biological fluids.
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Affiliation(s)
- Zhiyi Yang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Wenbo Li
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Hao Huang
- Shenzhen Engineering Laboratory of Single-molecule Detection and Instrument Development, Shenzhen, 518055, China
| | - Songlei Ren
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yongfan Men
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Fang Li
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Shenzhen Engineering Laboratory of Single-molecule Detection and Instrument Development, Shenzhen, 518055, China
| | - Xuefeng Yu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Qian Luo
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Shenzhen Engineering Laboratory of Single-molecule Detection and Instrument Development, Shenzhen, 518055, China.
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Chen J, Chen S, Chen J, Shen B, Jiang Z, Xu Y. Study on the Molecular Basis of Huanglian Jiedu Decoction Against Atopic Dermatitis Integrating Chemistry, Biochemistry, and Metabolomics Strategies. Front Pharmacol 2022; 12:770524. [PMID: 34970141 PMCID: PMC8712871 DOI: 10.3389/fphar.2021.770524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 11/24/2021] [Indexed: 11/27/2022] Open
Abstract
Atopic dermatitis (AD) is a common chronic relapsing skin inflammation, which severely affect the quality of life of patients. Inhibiting itching and enhancing immunity to mitigate scratching are key elements in the fight against AD. Huanglian Jiedu decoction (HLJDD) has multiple pharmacological effects in the treatment of AD. However, the effective ingredients and underlying molecular mechanisms have not yet been fully explored. Thus, this study integrates chemistry, biochemistry, and metabolomics strategies to evaluate the active substance basis of HLJDD against AD. First, HLJDD was split to five fractions (CPF, 40AEF, 90AEF, PEF and WEF) and 72 chemical components were identified. NSD (Non-similarity degree) among the different fractions showed significant chemical differences (>81%). Interleukin IL-13, IL-17A, IL-3, IL-31, IL-33, IL4, IL-5, TSLP, IgE, and histamine in the serum, and IL-4Rα, JAK1, and HRH4 levels in skin, participating in inhibiting itching and regulating immunity signaling, were found to be restored to varying degrees in AD treating with HLJDD and its fractions, especially 40AEF and CPF. Untargeted metabolomics analysis demonstrated that forty metabolites were differential metabolites in plasma between the HLJDD-treated group and the AD group, involving in histidine metabolism, arginine biosynthesis, pyrimidine metabolism, and so on. Further, targeted metabolomics analysis revealed that eleven differential metabolites, associating with physiological and biochemical indices, were significant improved in the HLJDD and its fractions groups. In conclusion, HLJDD exhibited anti-AD effects by inhibiting itching and enhancing immunity, which in turn regulating the levels of relative metabolites, and CPF and 40AEF were considered the most important components of HLJDD.
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Affiliation(s)
- Jing Chen
- Department of Pharmacy, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Lin Hai, China
| | - Saizhen Chen
- Department of Pharmacy, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Jinguang Chen
- Department of Dermatology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Bixin Shen
- Department of Pharmaceutics, School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China
| | - Zhengli Jiang
- Department of Pharmacy, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Lin Hai, China
| | - Yubin Xu
- Department of Pharmacy, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
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André R, Guedes R, López J, Serralheiro ML. Untargeted metabolomic study of HepG2 cells under the effect of Fucus vesiculosus aqueous extract. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2021; 35:e9197. [PMID: 34515383 DOI: 10.1002/rcm.9197] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 06/28/2021] [Accepted: 09/09/2021] [Indexed: 06/13/2023]
Abstract
RATIONALE Fucus vesiculosus has been described with potential to develop functional foods containing bioactive compounds against various diseases. However, more studies are needed to better understand its functioning and its previously reported bioactivities, mainly at the molecular level. METHODS An untargeted metabolomic study was performed to analyse HepG2 cells exposed to F. vesiculosus aqueous extract, rich in phlorotannins and peptides, during 24 h. This study was carried out using liquid chromatography combined with high-resolution tandem mass spectrometry. RESULTS This metabolomic study showed significant changes in HepG2 metabolites in the presence of the extract, standing out being the increased intensity of various fatty acid amides (oleamide, (Z)-eicos-11-enamide, linoleamide, palmitamide, dodecanamide and stearamide). This group of metabolites is reported in the literature with anticancer and hypocholesterolemic activity, bioactivities also described for F. vesiculosus. The extract induced, likewise, the expression of glutathione indicating its antioxidant effect. CONCLUSIONS This study demonstrated the potential of the compounds present in the F. vesiculosus aqueous extract for the development of natural drugs, nutraceuticals or dietary supplements, justified at the molecular level by changes in cell metabolites related to anticancer and hypocholesterolemic activity. The results here described, using an untargeted metabolomic approach, may contribute to a better understanding of algal behaviour, when used as food, in health-promoting effects.
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Affiliation(s)
- Rebeca André
- Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, University of Lisbon, Campo Grande, Lisbon, Portugal
| | - Rita Guedes
- Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, University of Lisbon, Campo Grande, Lisbon, Portugal
| | - Javier López
- Parque Empresarial Rivas Futura, Bruker Española SA, Rivas Vaciamadrid, Madrid, Spain
| | - Maria Luísa Serralheiro
- Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, University of Lisbon, Campo Grande, Lisbon, Portugal
- Faculty of Sciences, Departamento de Química e Bioquímica, University of Lisbon, Campo Grande, Lisbon, Portugal
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15
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Yu M, Sun R, Zhao Y, Shao F, Zhu W, Aa J. Detection and verification of coexisting diagnostic markers in plasma and serum of patients with non-small-cell lung cancer. Future Oncol 2021; 17:4355-4369. [PMID: 34674559 DOI: 10.2217/fon-2021-0025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Aim: To screen and identify the potential biomarkers co-existing in plasma and serum of patients with non-small-cell lung cancer (NSCLC), and establish appropriate diagnostic models. Methods: A cohort of 195 plasma samples and 180 serum samples were obtained from healthy controls (HCs), adenocarcinoma (AdC) and squamous cell carcinoma (SqCC) patients enrolled from the First Affiliated Hospital of Nanjing Medical University. Metabolites in plasma and serum were analyzed by GC-MS. Results: Hypoxanthine was found to have good performance in the differential diagnosis of NSCLC (including AdC and SqCC) and HC (area under the receiver operating characteristic [AUROC] ≥0.85). Combinations of metabolites could be used for differential diagnosis of NSCLC and HC (AUROC >0.93), AdC and HC (AUROC >0.91), SqCC and HC (AUROC >0.95), AdC and SqCC (AUROC >0.72). Conclusions: Metabolomics based on GC-MS can screen and identify the differential metabolites coexisting in plasma and serum of patients with NSCLC, and prediction models established by this method can be used for the differential diagnosis of patients with NSCLC.
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Affiliation(s)
- Mengjie Yu
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
| | - Runbin Sun
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
| | - Yuqing Zhao
- Phase I Clinical Trial Unit, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Feng Shao
- Phase I Clinical Trial Unit, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Wei Zhu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Jiye Aa
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
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16
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Fu H, He M, Wu J, Zhou Y, Ke S, Chen Z, Liu Q, Liu M, Jiang H, Huang L, Chen C. Deep Investigating the Changes of Gut Microbiome and Its Correlation With the Shifts of Host Serum Metabolome Around Parturition in Sows. Front Microbiol 2021; 12:729039. [PMID: 34603257 PMCID: PMC8484970 DOI: 10.3389/fmicb.2021.729039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 08/30/2021] [Indexed: 01/14/2023] Open
Abstract
Parturition is a crucial event in the sow reproduction cycle, which accompanies by a series of physiological changes, including sex hormones, metabolism, and immunity. More and more studies have indicated the changes of the gut microbiota from pregnancy to parturition. However, what bacterial species and functional capacities of the gut microbiome are changed around parturition has been largely unknown, and the correlations between the changes of gut bacterial species and host metabolome were also uncovered. In this study, by combining 16S rRNA gene and shotgun metagenomic sequencing data, and the profiles of serum metabolome and fecal short-chain fatty acids (SCFAs), we investigated the changes of gut microbiome, serum metabolite features and fecal SCFAs from late pregnancy (LP) to postpartum (PO) stage. We found the significant changes of gut microbiota from LP to PO stage in both 16S rRNA gene sequencing and metagenomic sequencing analyses. The bacterial species from Lactobacillus, Streptococcus, and Clostridium were enriched at the LP stage, while the species from Bacteroides, Escherichia, and Campylobacter had higher abundances at the PO stage. Functional capacities of the gut microbiome were also significantly changed and associated with the shifts of gut bacteria. Untargeted metabolomic analyses revealed that the metabolite features related to taurine and hypotaurine metabolism, and arginine biosynthesis and metabolism were enriched at the LP stage, and positively associated with those bacterial species enriched at the LP stage, while the metabolite features associated with vitamin B6 and glycerophospholipid metabolism had higher abundances at the PO stage and were positively correlated with the bacteria enriched at the PO stage. Six kinds of SCFAs were measured in feces samples and showed higher concentrations at the LP stage. These results suggested that the changes of gut microbiome from LP to PO stage lead to the shifts of host lipid, amino acids and vitamin metabolism and SCFA production. The results from this study provided new insights for the changes of sow gut microbiome and host metabolism around parturition, and gave new knowledge for guiding the feeding and maternal care of sows from late pregnancy to lactation in the pig industry.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Lusheng Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Congying Chen
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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17
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Qi SA, Wu Q, Chen Z, Zhang W, Zhou Y, Mao K, Li J, Li Y, Chen J, Huang Y, Huang Y. High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis. Sci Rep 2021; 11:11805. [PMID: 34083687 PMCID: PMC8175557 DOI: 10.1038/s41598-021-91276-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 05/19/2021] [Indexed: 12/19/2022] Open
Abstract
Lung cancer is the leading cause of human cancer mortality due to the lack of early diagnosis technology. The low-dose computed tomography scan (LDCT) is one of the main techniques to screen cancers. However, LDCT still has a risk of radiation exposure and it is not suitable for the general public. In this study, plasma metabolic profiles of lung cancer were performed using a comprehensive metabolomic method with different liquid chromatography methods coupled with a Q-Exactive high-resolution mass spectrometer. Metabolites with different polarities (amino acids, fatty acids, and acylcarnitines) can be detected and identified as differential metabolites of lung cancer in small volumes of plasma. Logistic regression models were further developed to identify cancer stages and types using those significant biomarkers. Using the Variable Importance in Projection (VIP) and the area under the curve (AUC) scores, we have successfully identified the top 5, 10, and 20 metabolites that can be used to differentiate lung cancer stages and types. The discrimination accuracy and AUC score can be as high as 0.829 and 0.869 using the five most significant metabolites. This study demonstrated that using 5 + metabolites (Palmitic acid, Heptadecanoic acid, 4-Oxoproline, Tridecanoic acid, Ornithine, and etc.) has the potential for early lung cancer screening. This finding is useful for transferring the diagnostic technology onto a point-of-care device for lung cancer diagnosis and prognosis.
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Affiliation(s)
- Shi-Ang Qi
- Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China
| | - Qian Wu
- Shanghai Center for Bioinformation Technology and Shanghai Engineering Research Center of Pharmaceutical Translation, Shanghai Industrial Technology Institute, Shanghai, 201203, China
- Shanghai Fenglin Clinical Laboratory Co., Ltd, Shanghai, 200231, China
| | - Zhenpu Chen
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China
| | - Wei Zhang
- Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
| | - Yongchun Zhou
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China
| | - Kaining Mao
- Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
| | - Jia Li
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China
| | - Yuanyuan Li
- Shanghai Center for Bioinformation Technology and Shanghai Engineering Research Center of Pharmaceutical Translation, Shanghai Industrial Technology Institute, Shanghai, 201203, China
| | - Jie Chen
- Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
| | - Youguang Huang
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China.
| | - Yunchao Huang
- Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, 650118, Yunnan, China.
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Wan L, Liu Q, Liang D, Guo Y, Liu G, Ren J, He Y, Shan B. Circulating Tumor Cell and Metabolites as Novel Biomarkers for Early-Stage Lung Cancer Diagnosis. Front Oncol 2021; 11:630672. [PMID: 34136379 PMCID: PMC8202280 DOI: 10.3389/fonc.2021.630672] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 04/09/2021] [Indexed: 12/12/2022] Open
Abstract
Background Lung cancer is a malignant tumor that has the highest morbidity and mortality rate among all cancers. Early diagnosis of lung cancer is a key factor in reducing mortality and improving prognosis. Methods In this study, we performed CTC next-generation sequencing (NGS) in early-stage lung cancer patients to identify lung cancer-related gene mutations. Meanwhile, a serum liquid chromatography-tandem mass spectrometry (LC-MS) untargeted metabolomics analysis was performed in the CTC-positive patients. To screen potential diagnostic markers for early lung cancer. Results 62.5% (30/48) of lung cancer patients had ≥1 CTC. By CTC NGS, we found that > 50% of patients had 4 commonly mutated genes, namely, NOTCH1, IGF2, EGFR, and PTCH1. 47.37% (9/19) patients had ARIDH1 mutations. Additionally, 30 CTC-positive patients and 30 healthy volunteers were subjected to LC-MS untargeted metabolomics analysis. We found 100 different metabolites, and 10 different metabolites were identified through analysis, which may have potential clinical application value in the diagnosis of CTC-positive early-stage lung cancer (AUC >0.9). Conclusions Our results indicate that NGS of CTC and metabolomics may provide new tumor markers for the early diagnosis of lung cancer.
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Affiliation(s)
- Lingling Wan
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Qingyi Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Di Liang
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Yongdong Guo
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Guangjie Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Jinxia Ren
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Yutong He
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Baoen Shan
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
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19
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Tian R, Liu H, Feng S, Wang H, Wang Y, Wang Y, Liang L, Xu H, Xing H, Zhang S. Gut microbiota dysbiosis in stable coronary artery disease combined with type 2 diabetes mellitus influences cardiovascular prognosis. Nutr Metab Cardiovasc Dis 2021; 31:1454-1466. [PMID: 33810955 DOI: 10.1016/j.numecd.2021.01.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/29/2020] [Accepted: 01/11/2021] [Indexed: 01/06/2023]
Abstract
BACKGROUND AND AIMS Host-microbiota interactions involving metabolic pathways have been linked to the pathogenesis of atherosclerotic disease and type 2 diabetes. As stable coronary artery disease (SCAD) patients combined with type 2 diabetes have significantly increased risk for cardiac event, we focused on elucidating the role of microbiota affecting cardiometabolic disease development. METHODS AND RESULTS We used multi-omics analyses (metagenomics and metabolomics) of fecal and serum samples from a prospective cohort including stable coronary artery disease combined with diabetes mellitus (SCAD + T2DM, n = 38), SCAD (n = 71), and healthy control (HC, n = 55). We linked microbiome features to disease severity in a three-pronged association analysis and identified prognostic bacterial biomarkers. We identified that bacterial and metabolic signatures varied significantly between SCAD and SCAD + T2DM groups. SCAD + T2DM individuals were characterized by increased levels of aromatic amino acids and carbohydrates, which correlate with a gut microbiome with enriched biosynthetic potential. Our study also addressed how metformin may confound gut dysbiosis and increase the potential for nitrogen metabolism. In addition, we found that specific bacterial taxa Ruminococcus torques [HR: 2.363 (08-4.56), P = 0.03] was predictive of cardiac survival outcomes. CONCLUSION Overall, our study identified relationships between features of the gut microbiota (GM) and circulating metabolites, providing a new direction for future studies aiming to understand the host-GM interplay in atherosclerotic cardiovascular pathogenesis.
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Affiliation(s)
- Ran Tian
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Honghong Liu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Siqin Feng
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Hui Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Yifei Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China; Department of Medicine, Tsinghua University, Haidian district, Beijing, China.
| | - Yiyang Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China; Department of Medicine, Tsinghua University, Haidian district, Beijing, China.
| | - Lifeng Liang
- Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.
| | - Haopeng Xu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Haiping Xing
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Shuyang Zhang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
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20
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Yu J, Du F, Yang L, Chen L, He Y, Geng R, Wu L, Xie B. Identification of potential serum biomarkers for simultaneously classifying lung adenocarcinoma, squamous cell carcinoma and small cell carcinoma. Cancer Biomark 2021; 30:331-342. [PMID: 33361584 DOI: 10.3233/cbm-201440] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Histological subtypes of lung cancer are crucial for making treatment decisions. However, multi-subtype classifications including adenocarcinoma (AC), squamous cell carcinoma (SqCC) and small cell carcinoma (SCLC) were rare in the previous studies. This study aimed at identifying and screening potential serum biomarkers for the simultaneous classification of AC, SqCC and SCLC. PATIENTS AND METHODS A total of 143 serum samples of AC, SqCC and SCLC were analyzed by 1HNMR and UPLC-MS/MS. The stepwise discriminant analysis (DA) and multilayer perceptron (MLP) were employed to screen the most efficient combinations of markers for classification. RESULTS The results of non-targeted metabolomics analysis showed that the changes of metabolites of choline, lipid or amino acid might contribute to the classification of lung cancer subtypes. 17 metabolites in those pathways were further quantified by UPLC-MS/MS. DA screened out that serum xanthine, S-adenosyl methionine (SAM), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE) and squamous cell carcinoma antigen (SCC) contributed significantly to the classification of AC, SqCC and SCLC. The average accuracy of 92.3% and the area under the receiver operating characteristic curve of 0.97 would be achieved by MLP model when a combination of those five variables as input parameters. CONCLUSION Our findings suggested that metabolomics was helpful in screening potential serum markers for lung cancer classification. The MLP model established can be used for the simultaneous diagnosis of AC, SqCC and SCLC with high accuracy, which is worthy of further study.
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Affiliation(s)
- Jiangqing Yu
- Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, Zhejiang, China.,Department of Respiratory and Critical Care Medicine, Huadu District People's Hospital of Guangzhou, Southern Medical University, Guangzhou, Guangdong, China
| | - Fen Du
- Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, Zhejiang, China.,School of Pharmaceutical Science, Nanchang University, Nanchang, Jiangxi, China
| | - Liping Yang
- Medical Oncology, People's Hospital of Gansu Province, Lanzhou, Gansu, China
| | - Ling Chen
- School of Pharmaceutical Science, Nanchang University, Nanchang, Jiangxi, China
| | - Yuanxiang He
- Thoracic Surgery, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Ruijin Geng
- School of Pharmaceutical Science, Nanchang University, Nanchang, Jiangxi, China
| | - Le Wu
- Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, Zhejiang, China.,School of Pharmaceutical Science, Nanchang University, Nanchang, Jiangxi, China
| | - Baogang Xie
- Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, Zhejiang, China.,School of Pharmaceutical Science, Nanchang University, Nanchang, Jiangxi, China
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21
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Zhao H, Xi C, Tian M, Lu X, Cai TJ, Li S, Tian XL, Gao L, Liu HX, Liu KH, Liu QJ. Identification of Potential Radiation Responsive Metabolic Biomarkers in Plasma of Rats Exposed to Different Doses of Cobalt-60 Gamma Rays. Dose Response 2021; 18:1559325820979570. [PMID: 33402881 PMCID: PMC7745571 DOI: 10.1177/1559325820979570] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 10/27/2020] [Accepted: 11/16/2020] [Indexed: 11/21/2022] Open
Abstract
Metabolomics has great potential to process accessible biofluids through high-throughput and quantitative analysis for radiation biomarker screening. This study focused on the potential radiation responsive metabolites in rat plasma and the dose-response relationships. In the discovery stage, 20 male Sprague–Dawley rats were exposed to 0, 1, 3 and 5 Gy of cobalt-60 gamma rays at a dose rate of 1 Gy/min. Plasma samples were collected at 72 h after exposure and analyzed using liquid chromatography mass spectrometry based on non-targeted metabolomics. In the verification stage, 50 additional rats were exposed to 0, 1, 2, 3, 5 and 8 Gy of gamma rays. The concentrations of candidate metabolites were then analyzed using targeted metabolomics methods. Fifteen candidate radiation responsive metabolites were identified as potential radiation metabolite biomarkers. Metabolic pathways, such as linoleic acid metabolism and glycerophospholipid metabolism pathways, were changed after irradiation. Six radiation responsive metabolites, including LysoPC(20:2), LysoPC(20:3), PC(18:0/22:5), L-palmitoylcarnitine, N-acetylornithine and butyrylcarnitine, had good dose-response relationships (R2 > 0.80). The area under the curve of the panel of the 6 radiation responsive metabolites was 0.923. The radiation exposure metabolomics biomarkers and dose-response curves may have potential for rapid dose assessment and triage in nuclear and radiation accidents.
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Affiliation(s)
- Hua Zhao
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Cong Xi
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Mei Tian
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Xue Lu
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Tian-Jing Cai
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Shuang Li
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Xue-Lei Tian
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Ling Gao
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hai-Xiang Liu
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Ke-Hui Liu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, People's Republic of China.,Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, People's Republic of China.,University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Qing-Jie Liu
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
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22
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Patel SK, George B, Rai V. Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology. Front Pharmacol 2020; 11:1177. [PMID: 32903628 PMCID: PMC7438594 DOI: 10.3389/fphar.2020.01177] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 07/20/2020] [Indexed: 12/13/2022] Open
Abstract
The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.
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Affiliation(s)
- Sandip Kumar Patel
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
- Buck Institute for Research on Aging, Novato, CA, United States
| | - Bhawana George
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vineeta Rai
- Department of Entomology & Plant Pathology, North Carolina State University, Raleigh, NC, United States
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23
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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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24
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Ruiying C, Zeyun L, Yongliang Y, Zijia Z, Ji Z, Xin T, Xiaojian Z. A comprehensive analysis of metabolomics and transcriptomics in non-small cell lung cancer. PLoS One 2020; 15:e0232272. [PMID: 32374740 PMCID: PMC7202610 DOI: 10.1371/journal.pone.0232272] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 04/10/2020] [Indexed: 12/20/2022] Open
Abstract
Non-small cell lung cancer (NSCLC) remains a leading cause of cancer death globally. More accurate and reliable diagnostic methods/biomarkers are urgently needed. Joint application of metabolomics and transcriptomics technologies possesses the high efficiency of identifying key metabolic pathways and functional genes in lung cancer patients. In this study, we performed an untargeted metabolomics analysis of 142 NSCLC patients and 159 healthy controls; 35 identified metabolites were significantly different between NSCLC patients and healthy controls, of which 6 metabolites (hypoxanthine, inosine, L-tryptophan, indoleacrylic acid, acyl-carnitine C10:1, and lysoPC(18:2)) were chosen as combinational potential biomarkers for NSCLC. The area under the curve (AUC) value, sensitivity (SE), and specificity (SP) of these six biomarkers were 0.99, 0.98, and 0.99, respectively. Potential diagnostic implications of the metabolic characteristics in NSCLC was studied. The metabolomics results were further verified by transcriptomics analysis of 1027 NSCLC patients and 108 adjacent peritumoral tissues from TCGA database. This analysis identified 2202 genes with significantly different expressions in cancer cells compared to normal controls, which in turn defined pathways implicated in the metabolism of the compounds revealed by metabolomics analysis. We built a fully connected network of metabolites and genes, which shows a good correspondence between the transcriptome analysis and the metabolites selected for diagnosis. In conclusion, this work provides evidence that the metabolic biomarkers identified may be used for NSCLC diagnosis and screening. Comprehensive analysis of metabolomics and transcriptomics data offered a validated and comprehensive understanding of metabolism in NSCLC.
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Affiliation(s)
- Chen Ruiying
- Department of Respiratory Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
| | - Li Zeyun
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
| | - Yuan Yongliang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
| | - Zhu Zijia
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
| | - Zhang Ji
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
| | - Tian Xin
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
- * E-mail: (TX); (ZX)
| | - Zhang Xiaojian
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, china
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, china
- * E-mail: (TX); (ZX)
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25
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Wang D, Ma X, Guo S, Wang Y, Li T, Zou D, Song H, Yang W, Ge Y. Effect of Huangqin Tang on Urine Metabolic Profile in Rats with Ulcerative Colitis Based on UPLC-Q-Exactive Orbitrap MS. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2020; 2020:1874065. [PMID: 32382278 PMCID: PMC7193274 DOI: 10.1155/2020/1874065] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 02/12/2020] [Accepted: 02/13/2020] [Indexed: 01/29/2023]
Abstract
As a classic prescription, Huangqin Tang (HQT) has been widely applied to treat ulcerative colitis (UC), although its pharmacological mechanisms are not clear. In this study, urine metabolomics was first analysed to explore the therapeutic mechanisms of HQT in UC rats induced by TNBS. We identified 28 potential biomarkers affected by HQT that might cause changes in urine metabolism in UC rats, mapped the network of metabolic pathways, and revealed how HQT affects metabolism of UC rats. The results showed that UC affects amino acid metabolism and biosynthesis of unsaturated fatty acids and impairs the tricarboxylic acid cycle (TCA cycle). UC induced inflammatory and gastrointestinal reactions by inhibiting the transport of fatty acids and disrupting amino acid metabolism. HQT plays key roles via regulating the level of biomarkers in the metabolism of amino acids, lipids, and so on, normalizing metabolic disorders. In addition, histopathology and other bioinformatics analysis further confirm that HQT altered UC rat physiology and pathology, ultimately affecting metabolic function of UC rats.
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Affiliation(s)
- Dunfang Wang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Xuran Ma
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Shanshan Guo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yanli Wang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Tao Li
- The Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Dixin Zou
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Hongxin Song
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Weipeng Yang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yongxiang Ge
- Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China
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26
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Zhang L, Zheng J, Ahmed R, Huang G, Reid J, Mandal R, Maksymuik A, Sitar DS, Tappia PS, Ramjiawan B, Joubert P, Russo A, Rolfo CD, Wishart DS. A High-Performing Plasma Metabolite Panel for Early-Stage Lung Cancer Detection. Cancers (Basel) 2020; 12:cancers12030622. [PMID: 32156060 PMCID: PMC7139410 DOI: 10.3390/cancers12030622] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 03/02/2020] [Accepted: 03/05/2020] [Indexed: 12/19/2022] Open
Abstract
The objective of this research is to use metabolomic techniques to discover and validate plasma metabolite biomarkers for the diagnosis of early-stage non-small cell lung cancer (NSCLC). The study included plasma samples from 156 patients with biopsy-confirmed NSCLC along with age and gender-matched plasma samples from 60 healthy controls. A fully quantitative targeted mass spectrometry (MS) analysis (targeting 138 metabolites) was performed on all samples. The sample set was split into a discovery set and validation set. Metabolite concentration data, clinical data, and smoking history were used to determine optimal sets of biomarkers and optimal regression models for identifying different stages of NSCLC using the discovery sets. The same biomarkers and regression models were used and assessed on the validation models. Univariate and multivariate statistical analysis identified β-hydroxybutyric acid, LysoPC 20:3, PC ae C40:6, citric acid, and fumaric acid as being significantly different between healthy controls and stage I/II NSCLC. Robust predictive models with areas under the curve (AUC) > 0.9 were developed and validated using these metabolites and other, easily measured clinical data for detecting different stages of NSCLC. This study successfully identified and validated a simple, high-performing, metabolite-based test for detecting early stage (I/II) NSCLC patients in plasma. While promising, further validation on larger and more diverse cohorts is still required.
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Affiliation(s)
- Lun Zhang
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada; (L.Z.); (J.Z.); (J.R.); (R.M.)
| | - Jiamin Zheng
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada; (L.Z.); (J.Z.); (J.R.); (R.M.)
| | - Rashid Ahmed
- BioMark Diagnostics Inc., Richmond, BC V6X 2W8, Canada; (R.A.); (G.H.)
| | - Guoyu Huang
- BioMark Diagnostics Inc., Richmond, BC V6X 2W8, Canada; (R.A.); (G.H.)
| | - Jennifer Reid
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada; (L.Z.); (J.Z.); (J.R.); (R.M.)
| | - Rupasri Mandal
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada; (L.Z.); (J.Z.); (J.R.); (R.M.)
| | - Andrew Maksymuik
- Cancer Care Manitoba, Winnipeg, MB R3E 0V9, Canada;
- Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3A 1R9, Canada;
| | - Daniel S. Sitar
- Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3A 1R9, Canada;
- Department of Pharmacology & Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0T5, Canada
| | - Paramjit S. Tappia
- Asper Clinical Research Institute & Office of Clinical Research, St. Boniface Hospital, Winnipeg, MB R2H 2A6, Canada; (P.S.T.); (B.R.)
| | - Bram Ramjiawan
- Asper Clinical Research Institute & Office of Clinical Research, St. Boniface Hospital, Winnipeg, MB R2H 2A6, Canada; (P.S.T.); (B.R.)
| | - Philippe Joubert
- Department of Pathology, University of Laval, Quebec, QC G1V 4G5, Canada;
| | - Alessandro Russo
- Medical Oncology Unit A.O. Papardo & Department of Human Pathology, University of Messina, 98158 Messina, Italy;
- Thoracic Medical Oncology Program Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland, Baltimore, MD 21201, USA;
| | - Christian D. Rolfo
- Thoracic Medical Oncology Program Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland, Baltimore, MD 21201, USA;
| | - David S. Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada; (L.Z.); (J.Z.); (J.R.); (R.M.)
- Correspondence:
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27
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Serum lipidomic biomarkers for non-small cell lung cancer in nonsmoking female patients. J Pharm Biomed Anal 2020; 185:113220. [PMID: 32145537 DOI: 10.1016/j.jpba.2020.113220] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 02/26/2020] [Accepted: 02/28/2020] [Indexed: 02/06/2023]
Abstract
Lung cancer (Lca) is one of the malignant tumors with the fastest morbidity and mortality increase and the greatest threat to human health and life. The incidence of non-small cell lung cancer (NSCLC) in the nonsmoking female has increased recently. However, its pathogenesis is still unclear, and there is an urgent need for clinical diagnostic biomarkers, especially for early diagnosis. A nontargeted lipidomic approach based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS), as well as two machine learning approaches (genetic algorithm and binary logistic regression) was used to screen candidate discriminating lipids and define a combinational lipid biomarker in serum samples to distinguish female patients with NSCLC from healthy controls. Moreover, the candidate biomarkers were verified by using an external validation sample set. Our result revealed that fatty acid (FA) (20:4), FA (22:0) and LPE (20:4) can serve as a combinational biomarker for distinguishing female patients with NSCLC from healthy control with good sensitivity and specificity. Furthermore, this combinational biomarker also showed good performance in distinguishing early-stage NSCLC female patients from a healthy control. We observed that levels of unsaturated fatty acids clearly decreased, while saturated fatty acids and lysophosphatidylethanolamines pronouncedly increased in Lca patients, compared with the healthy controls, which revealed significant disturbance of lipid metabolism in NSCLC females. Our results not only provide hints to the pathological mechanism of NSCLC in nonsmoking female but also supply a combinational lipid biomarker to aid the diagnosis of NSCLC at early-stage.
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28
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Yang Z, Song Z, Chen Z, Guo Z, Jin H, Ding C, Hong Y, Cai Z. Metabolic and lipidomic characterization of malignant pleural effusion in human lung cancer. J Pharm Biomed Anal 2019; 180:113069. [PMID: 31884394 DOI: 10.1016/j.jpba.2019.113069] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/27/2019] [Accepted: 12/21/2019] [Indexed: 12/31/2022]
Abstract
Malignant pleural effusion (MPE) is an important hallmark for late-stage lung cancer with metastasis. Current clinical diagnosis methods require tedious work to distinguish MPE from benign pleural effusion (BPE). The objective of this study was to characterize the metabolic signatures in MPE of lung cancer, and identify potential metabolite biomarkers for diagnosis of MPE. MPE from lung cancer (n = 46) and BPE from tuberculosis patients (n = 32) were investigated by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based global metabolomic and lipidomic profiling. Multivariate partial least-square discriminative analysis models exhibited distinct metabolic profiles between MPE and BPE. A total of 25 ether lipids, including phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and phosphatidylethanolamines (PE), were observed to be significantly downregulated in MPE with excellent diagnostic potential. Plasmalogen PC(40:3p) showed highest AUC value of 0.953 in receiver operating characteristic (ROC) model. Oxidized polyunsaturated fatty acids (PUFA) were upregulated in MPE. The obtained results implied a high oxidative stress and peroxisome disorder in lung cancer patients. Combined metabolomic and lipidomic profiling have discovered potential biomarkers in MPE with excellent clinical diagnostic capability. Dysregulated ether lipids and oxidized PUFAs have implied an aberrant redox metabolism, which provides novel insights into the pathology of MPE in lung cancer.
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Affiliation(s)
- Zhiyi Yang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Zhengbo Song
- Department of Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Zhongjian Chen
- Department of Cancer Research, Zhejiang Cancer Hospital, Hangzhou, China
| | - Zhenyu Guo
- HKBU Institute for Research and Continuing Education, Shenzhen, China
| | - Hangbiao Jin
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Cheng Ding
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Yanjun Hong
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China; HKBU Institute for Research and Continuing Education, Shenzhen, China.
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
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29
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Noreldeen HAA, Liu X, Xu G. Metabolomics of lung cancer: Analytical platforms and their applications. J Sep Sci 2019; 43:120-133. [DOI: 10.1002/jssc.201900736] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 11/05/2019] [Accepted: 11/15/2019] [Indexed: 12/24/2022]
Affiliation(s)
- Hamada A. A. Noreldeen
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences Dalian P. R. China
- University of Chinese Academy of Sciences Beijing P. R. China
- Marine Chemistry LabMarine Environment DivisionNational Institute of Oceanography and Fisheries Hurghada Egypt
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences Dalian P. R. China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences Dalian P. R. China
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30
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Wolrab D, Jirásko R, Chocholoušková M, Peterka O, Holčapek M. Oncolipidomics: Mass spectrometric quantitation of lipids in cancer research. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.04.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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31
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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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32
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Ren H, Chen W, Wang H, Kang Y, Zhu X, Li J, Wu T, Du Y. Quantitative analysis of free fatty acids in gout by disposable paper-array plate based MALDI MS. Anal Biochem 2019; 579:38-43. [DOI: 10.1016/j.ab.2019.05.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 05/19/2019] [Accepted: 05/20/2019] [Indexed: 12/27/2022]
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33
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Liquid Biopsy in Lung Cancer Screening: The Contribution of Metabolomics. Results of A Pilot Study. Cancers (Basel) 2019; 11:cancers11081069. [PMID: 31362354 PMCID: PMC6721278 DOI: 10.3390/cancers11081069] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 07/26/2019] [Accepted: 07/26/2019] [Indexed: 02/07/2023] Open
Abstract
Background: Lung cancer is the most common cause of cancer-related deaths worldwide. Early diagnosis is crucial to increase the curability chance of the patients. Low dose CT screening can reduce lung cancer mortality, but it is associated with several limitations. Metabolomics is a promising technique for cancer diagnosis due to its ability to provide chemical phenotyping data. The intent of our study was to explore metabolomic effects and profiles of lung cancer patients to determine if metabolic perturbations in the SSAT-1/polyamine pathway can distinguish between healthy participants and lung cancer patients as a diagnostic and treatment monitoring tool. Patients and Methods: Plasma samples were collected as part of the SSAT1 Amantadine Cancer Study. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify and quantify metabolite concentrations in lung cancer patient and control samples. Standard statistical analyses were performed to determine whether metabolite concentrations could differentiate between healthy subjects and lung cancer patients, as well as risk prediction modeling applied to determine whether metabolic profiles could provide an indication of cancer progression in later stage patients. Results: A panel consisting of 14 metabolites, which included 6 metabolites in the polyamine pathway, was identified that correctly discriminated lung cancer patients from controls with an area under the curve of 0.97 (95% CI: 0.875-1.0). Conclusion: When used in conjunction with the SSAT-1/polyamine pathway, these metabolites may provide the specificity required for diagnosing lung cancer from other cancer types and could be used as a diagnostic and treatment monitoring tool.
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34
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Lee GB, Lee JC, Moon MH. Plasma lipid profile comparison of five different cancers by nanoflow ultrahigh performance liquid chromatography-tandem mass spectrometry. Anal Chim Acta 2019; 1063:117-126. [DOI: 10.1016/j.aca.2019.02.021] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Revised: 01/22/2019] [Accepted: 02/04/2019] [Indexed: 12/12/2022]
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35
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Serum lipidome screening in patients with stage I non-small cell lung cancer. Clin Exp Med 2019; 19:505-513. [PMID: 31264112 PMCID: PMC6797644 DOI: 10.1007/s10238-019-00566-7] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 06/18/2019] [Indexed: 12/24/2022]
Abstract
The ability of early lung cancer diagnosis is an unmet need in clinical practice. Lung cancer metabolomic analyses conducted so far have demonstrated several abnormalities in cancer lipid profile providing a rationale for further study of blood lipidome of the patients. In the present research, we performed a targeted lipidome screening to select molecules that show promise for early lung cancer detection. The study was conducted on serum samples collected from newly diagnosed, stage I non-small cell lung cancer (NSCLC) patients and non-cancer controls. A high-throughput mass spectrometry-based platform with confirmed interlaboratory reproducibility was used. The analyzed profile consisted of acylcarnitines, sphingomyelins, phosphatidylcholines and lysophosphatidylcholines. Among the assayed lipid species, the significant differences between NSCLC and non-cancer subjects were observed in the group of phosphatidylcholines (PC) and lysophosphatidylcholines (lysoPC), especially in the levels of lysoPC a C26:0; lysoPC a C26:1; PC aa C42:4; and PC aa C34:4. The metabolites mentioned above were used to create a multivariate classification model, which reliability was proved by permutation tests as well as external validation. Our study indicated choline-containing phospholipids as potential lung cancer markers. Further investigations of phospholipidome are crucial to better describe the shifts in metabolite composition occurring in lung cancer patients.
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Liu H, Chen X, Hu X, Niu H, Tian R, Wang H, Pang H, Jiang L, Qiu B, Chen X, Zhang Y, Ma Y, Tang S, Li H, Feng S, Zhang S, Zhang C. Alterations in the gut microbiome and metabolism with coronary artery disease severity. MICROBIOME 2019; 7:68. [PMID: 31027508 PMCID: PMC6486680 DOI: 10.1186/s40168-019-0683-9] [Citation(s) in RCA: 178] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 04/09/2019] [Indexed: 05/07/2023]
Abstract
BACKGROUND Coronary artery disease (CAD) is associated with gut microbiota alterations in different populations. Gut microbe-derived metabolites have been proposed as markers of major adverse cardiac events. However, the relationship between the gut microbiome and the different stages of CAD pathophysiology remains to be established by a systematic study. RESULTS Based on multi-omic analyses (sequencing of the V3-V4 regions of the 16S rRNA gene and metabolomics) of 161 CAD patients and 40 healthy controls, we found that the composition of both the gut microbiota and metabolites changed significantly with CAD severity. We identified 29 metabolite modules that were separately classified as being positively or negatively correlated with CAD phenotypes, and the bacterial co-abundance group (CAG) with characteristic changes at different stages of CAD was represented by Roseburia, Klebsiella, Clostridium IV and Ruminococcaceae. The result revealed that certain bacteria might affect atherosclerosis by modulating the metabolic pathways of the host, such as taurine, sphingolipid and ceramide, and benzene metabolism. Moreover, a disease classifier based on differential levels of microbes and metabolites was constructed to discriminate cases from controls and was even able to distinguish stable coronary artery disease from acute coronary syndrome accurately. CONCLUSION Overall, the composition and functions of the gut microbial community differed from healthy controls to diverse coronary artery disease subtypes. Our study identified the relationships between the features of the gut microbiota and circulating metabolites, providing a new direction for future studies aiming to understand the host-gut microbiota interplay in atherosclerotic pathogenesis.
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Affiliation(s)
- Honghong Liu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Xi Chen
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaomin Hu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Haitao Niu
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Ran Tian
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Hui Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Haiyu Pang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Lingjuan Jiang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Bintao Qiu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Xiuting Chen
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Yang Zhang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Yiyangzi Ma
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Si Tang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Hanyu Li
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Siqin Feng
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Shuyang Zhang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
| | - Chenhong Zhang
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- Joint International Research Laboratory of Metabolic & Developmental Science, Shanghai Jiao Tong University, Shanghai, China
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Gaugain M, Mompelat S, Fourmond MP, Manceau J, Rolland JG, Laurentie M, Verdon E, Bellanger L, Hurtaud-Pessel D. A non-targeted LC-HRMS approach for detecting exposure to illegal veterinary treatments: The case of cephalosporins in commercial laying Hens. J Chromatogr A 2019; 1599:161-171. [PMID: 31014576 DOI: 10.1016/j.chroma.2019.04.022] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 12/19/2022]
Abstract
Cephalosporins are of particular importance in human medicine and should be reserved for second-line curative treatment in the veterinary field to avoid any emerging antimicrobial resistance. Due to misuse of ceftiofur in the poultry sector in France, it is now recommended to completely stop using cephalosporins in this sector. Methods currently used for the control of veterinary practices are mostly based on liquid chromatography coupled to mass spectrometry in a targeted mode, including parent compounds and any major metabolites. The aim of the present study was to evaluate the relevance of untargeted metabolomic approaches to highlight a possible exposure of laying hens to cephalosporins using a predictive model including selected treatment biomarkers. An experimentation carried out on living animals involved the administration of cefquinome and ceftiofur. Three biological matrices-droppings, eggs and liver-were investigated. Metabolites were extracted and analysed by liquid chromatography coupled to high resolution mass spectrometry in a full scan mode. Metabolites impacted by the treatment were selected by using univariate and multivariate statistical analyses. Predictive models built from the potential biomarkers selected in the "droppings" matrix were validated and able to classify "treated" and "control" hens. PLS-DA and logistic regression models were compared and both models gave satisfactory results in terms of prediction. Results were of less interest for other matrices in which only biomarkers of exposure to cefquinome were detected.
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Affiliation(s)
- Murielle Gaugain
- Residues and Contaminants Analysis Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France.
| | - Sophie Mompelat
- Residues and Contaminants Analysis Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Marie-Pierre Fourmond
- Residues and Contaminants Analysis Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Jacqueline Manceau
- Analysis of Data, Modeling and Experiment Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Jean-Guy Rolland
- Analysis of Data, Modeling and Experiment Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Michel Laurentie
- Analysis of Data, Modeling and Experiment Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Eric Verdon
- EU Reference Laboratory for Antimicrobial and Dye Residues in Food, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
| | - Lise Bellanger
- Université de Nantes, Département de Mathématiques, Laboratoire Jean Leray UMR CNRS 6629, 2, Rue de la Houssinière BP 92208, F-44322 Nantes Cedex 03, France
| | - Dominique Hurtaud-Pessel
- Residues and Contaminants Analysis Unit, Fougères Laboratory, ANSES (French National Agency for Food, Environment and Occupational Health & Safety), 10 B, rue Claude Bourgelat - Javené, CS 40608, 35306, Fougères Cedex, France
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Metabolomic study of serum, urine and bronchoalveolar lavage fluid based on gas chromatography mass spectrometry to delve into the pathology of lung cancer. J Pharm Biomed Anal 2019; 163:122-129. [DOI: 10.1016/j.jpba.2018.09.055] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 09/26/2018] [Accepted: 09/27/2018] [Indexed: 12/15/2022]
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Larrouy-Maumus G. Lipids as Biomarkers of Cancer and Bacterial Infections. Curr Med Chem 2019; 26:1924-1932. [PMID: 30182838 DOI: 10.2174/0929867325666180904120029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 07/09/2018] [Accepted: 07/18/2018] [Indexed: 02/06/2023]
Abstract
Lipids are ubiquitous molecules, known to play important roles in various cellular processes. Alterations to the lipidome can therefore be used as a read-out of the signs of disease, highlighting the importance to consider lipids as biomarkers in addition of nucleic acid and proteins. Lipids are among the primary structural and functional constituents of biological tissues, especially cell membranes. Along with membrane formation, lipids play also a crucial role in cell signalling, inflammation and energy storage. It was shown recently that lipid metabolism disorders play an important role in carcinogenesis and development. As well, the role of lipids in disease is particularly relevant for bacterial infections, during which several lipid bacterial virulence factors are recognized by the human innate immune response, such as lipopolysaccharide in Gram-negative bacteria, lipoteichoic acid in Gram-positive bacteria, and lipoglycans in mycobacteria. Compared to nucleic acids and proteins, a complete analysis of the lipidome, which is the comprehensive characterization of different lipid families, is usually very challenging due to the heterogeneity of lipid classes and their intrinsic physicoproperties caused by variations in the constituents of each class. Understanding the chemical diversity of lipids is therefore crucial to understanding their biological relevance and, as a consequence, their use as potential biomarkers for non-infectious and infectious diseases. This mini-review exposes the current knowledge and limitations of the use of lipids as biomarkers of the top global killers which are cancer and bacterial infections.
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Affiliation(s)
- Gerald Larrouy-Maumus
- Department of Life Sciences, MRC Centre for Molecular Bacteriology and Infection, Faculty of Natural Sciences, Imperial College London, London, United Kingdom
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40
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Callejón-Leblic B, Pereira-Vega A, Vázquez-Gandullo E, Sánchez-Ramos JL, Gómez-Ariza JL, García-Barrera T. Study of the metabolomic relationship between lung cancer and chronic obstructive pulmonary disease based on direct infusion mass spectrometry. Biochimie 2018; 157:111-122. [PMID: 30439409 DOI: 10.1016/j.biochi.2018.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 11/07/2018] [Indexed: 12/19/2022]
Abstract
The high prevalence of lung cancer (LC) has triggered the search of biomarkers for early diagnosis of this disease. For this purpose the study of metabolic changes related to the development of lung cancer could provide interesting information about its early diagnosis. In this sense, chronic obstructive pulmonary disease (COPD), a disease associated with tumor development, is a comorbidity that increases the risk of onset and progression of lung neoplasia and has also to be considered in the study of pathology related to lung cancer. This work develop a metabolomic approach based on direct infusion mass spectrometry using a hybrid triple quadrupole-time of flight mass spectrometer (DI-ESI-QqQ-TOF-MS) in order to identify altered metabolites from serum of LC and COPD patients and evaluate its relationship and implication in the progression of LC. This methodology has been applied to 30 serum samples from LC, 30 healthy patients used as controls (HC) and 30 serum samples from COPD to found altered metabolites from both LC and COPD diseases. In addition, some metabolic differences and similarities were found in Pulmonary Emphysema and Chronic Bronchitis patients. On the other hand, altered metabolites were studied in different stages of LC (II, III and IV) to evaluate the perturbation of them throughout the progression of disease. The sample treatment consisted of the extraction of polar and non-polar metabolites from serum that was later infused into the mass spectrometer using an electrospray ionization source in positive and negative mode. Partial least squares discriminant analysis (PLS-DA) allowed a classification between LC, HC and COPD groups in all acquisition modes. A total of 35 altered and common metabolites between LC and COPD, including amino acids, fatty acids, lysophospholipids, phospholipids and triacylglycerides were identified, being alanine, aspartate and glutamate metabolism the most altered. Finally, ROC curves were applied to the dataset and metabolites with AUC value higher than 0.70 were considered as relevant in the progression of LC.
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Affiliation(s)
- B Callejón-Leblic
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain
| | - A Pereira-Vega
- Pneumonology Area of Juan Ramón Jiménez Hospital, Huelva, Spain.
| | | | | | - J L Gómez-Ariza
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain
| | - T García-Barrera
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain.
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41
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Seok AE, Lee J, Lee YR, Lee YJ, Kim HJ, Ihm C, Sung HJ, Hyun SH, Kang HG. Estimation of Age of Bloodstains by Mass-Spectrometry: A Metabolomic Approach. Anal Chem 2018; 90:12431-12441. [PMID: 30350957 DOI: 10.1021/acs.analchem.8b01367] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Bloodstains are common evidence in crime scenes, containing significant information, including genetic information. Although efforts have been made to reliably determine the time of incident by analyzing the elapsed time of the bloodstain, there has been limited success. To identify candidate metabolites in bloodstains over time, we prepared bloodstain samples using filter paper and analyzed the metabolites by high-performance liquid chromatography-mass spectrometry (HPLC-MS)/MS over a 21-day period. Using Venn diagrams and by multivariate analysis, we selected 62 candidate molecular features. We found by partial least-squares discriminant analysis (PLS-DA) that the group can be classified with an accuracy of 75.0%, and the R2 and Q2 values were 0.7513 and 0.6998, respectively. Five metabolites were successfully identified based on candidate molecular features. The level of two metabolites, l-tryptophan and ergothioneine, decreased with time. The concentration of candidate metabolites that we propose reliably increased or decreased with time, thus, enabling the measurement of elapsed time of the bloodstain. This study is the first to identify markers used to analyze the elapsed time of bloodstains through metabolomics analysis.
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Affiliation(s)
- Ae Eun Seok
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea
| | - Jiyeong Lee
- Department of Biomedical Laboratory Science, College of Health Sciences , Eulji University , Seongnam-si , Gyeonggi-do 13135 , Republic of Korea
| | - You-Rim Lee
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea
| | - Yoo-Jin Lee
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea
| | - Hyo-Jin Kim
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea
| | - Chunhwa Ihm
- Department of Laboratory Medicine , Eulji University Hospital , Daejeon , 35233 , Republic of Korea
| | - Ho Joong Sung
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea.,Department of Biomedical Laboratory Science, College of Health Sciences , Eulji University , Seongnam-si , Gyeonggi-do 13135 , Republic of Korea
| | - Sung Hee Hyun
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea.,Department of Biomedical Laboratory Science , Eulji University , Daejeon , 34824 , Republic of Korea
| | - Hee-Gyoo Kang
- Department of Senior Healthcare, BK21 Plus Program, Graduate School , Eulji University , Daejeon , 34824 , Republic of Korea.,Department of Biomedical Laboratory Science, College of Health Sciences , Eulji University , Seongnam-si , Gyeonggi-do 13135 , Republic of Korea
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López-López Á, López-Gonzálvez Á, Barker-Tejeda TC, Barbas C. A review of validated biomarkers obtained through metabolomics. Expert Rev Mol Diagn 2018; 18:557-575. [PMID: 29808702 DOI: 10.1080/14737159.2018.1481391] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.
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Affiliation(s)
- Ángeles López-López
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Ángeles López-Gonzálvez
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Tomás Clive Barker-Tejeda
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Coral Barbas
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
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Bamji-Stocke S, van Berkel V, Miller DM, Frieboes HB. A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment. Metabolomics 2018; 14:81. [PMID: 29983671 PMCID: PMC6033515 DOI: 10.1007/s11306-018-1376-2] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 05/29/2018] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort. OBJECTIVES This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes. METHOD We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals. RESULT Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis. CONCLUSION We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.
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Affiliation(s)
- Sanaya Bamji-Stocke
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA
| | - Victor van Berkel
- Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, KY, USA
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA
| | - Donald M Miller
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA
| | - Hermann B Frieboes
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA.
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA.
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Chen Y, Ma Z, Zhong J, Li L, Min L, Xu L, Li H, Zhang J, Wu W, Dai L. Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer. Sci Rep 2018; 8:7137. [PMID: 29740076 PMCID: PMC5940703 DOI: 10.1038/s41598-018-25552-z] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 04/24/2018] [Indexed: 12/21/2022] Open
Abstract
Non-small cell lung cancer (NSCLC) is one of the most common malignancies worldwide. In this study, we investigated Ultrahigh Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry and Gas Chromatography Time-of-Flight/Mass Spectrometry-based non-targeted metabolomic profiles of serum samples obtained from early-stage NSCLC patients and healthy controls (HC). Metabolic pathways and the biological relevance of potential biomarkers were extensively studied to gain insights into dysregulated metabolism in NSCLC. The identified biomarker candidates were further externally validated via a targeted metabolomics analysis. The global metabolomics profiles could clearly distinguish NSCLC patients from HC. Phosphatidylcholine (PC) levels were found to be dysregulated in glycerophospholipid (GPL) metabolism, which was the top altered pathway in early-stage NSCLC. Compared with those in HC, significant increases in the levels of saturated and monounsaturated PCs such as PC (15:0/18:1), PC (18:0/16:0) and PC (18:0/20:1) were observed in NSCLC. Additionally, relative to those in HC, the levels of 9 polyunsaturated PCs, namely, PC (17:2/2:0), PC (18:4/3:0), and PC (15:0/18:2), and so on were significantly decreased in NSCLC patients. A panel of 12 altered PCs had good diagnostic performance in differentiating early-stage NSCLC patients from HC, and these PCs may thus be used as serum biomarkers for the early diagnosis of NSCLC.
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Affiliation(s)
- Yingrong Chen
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Zhihong Ma
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Jing Zhong
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Liqin Li
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Lishan Min
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Limin Xu
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Hongwei Li
- Cardiothoracic Surgery, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Jianbin Zhang
- Cardiothoracic Surgery, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Wei Wu
- Internal Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China
| | - Licheng Dai
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou, 313000, P.R. China.
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Jing F, Hu X, Cao Y, Xu M, Wang Y, Jing Y, Hu X, Gao Y, Zhu Z. Discriminating gastric cancer and gastric ulcer using human plasma amino acid metabolic profile. IUBMB Life 2018; 70:553-562. [PMID: 29626382 DOI: 10.1002/iub.1748] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 03/15/2018] [Indexed: 12/21/2022]
Abstract
Patients with gastric ulcer (GU) have a significantly higher risk of developing gastric cancer (GC), especially within 2 years after diagnosis. The main way to improve the prognosis of GC is to predict the tumorigenesis and metastasis in the early stage. The objective of this study was to demonstrate the ability of human plasma amino acid metabolic profile for discriminating GC and GU. In this study, we first used liquid chromatography-tandem mass spectrometry technique to characterize the plasma amino acid metabolism in GC and GU patients. Plasma samples were collected from 84 GC patients and 82 GU patients, and 22 amino acids were detected in each patient. Partial least squares-discriminant analysis model was performed to analyze the data of these amino acids. We observed seven differential amino acids between GC and GU. A regression analysis model was established using these seven amino acids. Finally, a panel of five differential amino acids, including glutamine, ornithine, histidine, arginine and tryptophan, was identified for discriminating GC and GU with good specificity and sensitivity. The receiver operating characteristic curve was used to evaluate diagnostic ability of the regression model and area under the curve was 0.922. In conclusion, this study demonstrated the potential values of plasma amino acid metabolic profile and metabolomic analysis technique in assisting diagnosis of GC. More studies are needed to highlight the theoretical strengths of metabolomics to understand the potential metabolic mechanisms in GC. © 2018 IUBMB Life, 70(6):553-562, 2018.
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Affiliation(s)
| | - Xin Hu
- Internal Medicine Ward, General Hospital of Benxi Iron and Steel Co. Ltd., Benxi, China
| | - Yunfeng Cao
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
| | - Minghao Xu
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
- Cancer Center, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Yuanyuan Wang
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
- Cancer Center, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Yu Jing
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
- Cancer Center, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Xiaodan Hu
- Jinzhou Medical University, Jinzhou, China
| | - Yu Gao
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
- Cancer Center, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Zhitu Zhu
- Key Laborotary of Liaoning Tumor Clinical Metabolomics, Jinzhou, China
- Cancer Center, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
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Bandu R, Mok HJ, Kim KP. Phospholipids as cancer biomarkers: Mass spectrometry-based analysis. MASS SPECTROMETRY REVIEWS 2018; 37:107-138. [PMID: 27276657 DOI: 10.1002/mas.21510] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 05/19/2016] [Indexed: 05/02/2023]
Abstract
Lipids, particularly phospholipids (PLs), are key components of cellular membrane. PLs play important and diverse roles in cells such as chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions in tissues. All these cellular processes are pertinent to cells that undergo transformation, cancer progression, and metastasis. Thus, there is a strong possibility that some classes of PLs are expected to present in cancer cells and tissues in cellular physiology. The mass spectrometric soft-ionization techniques, electrospray ionization (ESI), and matrix-assisted laser desorption/ionization (MALDI) are well-established in the proteomics field, have been used for lipidomic analysis in cancer research. This review focused on the applications of mass spectrometry (MS) mainly on ESI-MS and MALDI-MS in the structural characterization, molecular composition and key roles of various PLs present in cancer cells, tissues, blood, and urine, and on their importance for cancer-related problems as well as challenges for development of novel PL-based biomarkers. The profiling of PLs helps to rationalize their functions in biological systems, and will also provide diagnostic information to elucidate mechanisms behind the control of cancer, diabetes, and neurodegenerative diseases. The investigation of cellular PLs with MS methods suggests new insights on various cancer diseases and clinical applications in the drug discovery and development of biomarkers for various PL-related different cancer diseases. PL profiling in tissues, cells and body fluids also reflect the general condition of the whole organism and can indicate the existence of cancer and other diseases. PL profiling with MS opens new prospects to assess alterations of PLs in cancer, screening specific biomarkers and provide a basis for the development of novel therapeutic strategies. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:107-138, 2018.
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Affiliation(s)
- Raju Bandu
- Department of Applied Chemistry, College of Applied Science, Kyung Hee University, Yong-in City, 446-701, Korea
| | - Hyuck Jun Mok
- Department of Applied Chemistry, College of Applied Science, Kyung Hee University, Yong-in City, 446-701, Korea
| | - Kwang Pyo Kim
- Department of Applied Chemistry, College of Applied Science, Kyung Hee University, Yong-in City, 446-701, Korea
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Zhang X, Hou H, Chen H, Liu Y, Wang A, Hu Q. Serum metabolomics of laryngeal cancer based on liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Biomed Chromatogr 2018; 32:e4181. [PMID: 29272549 DOI: 10.1002/bmc.4181] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 10/27/2017] [Accepted: 12/13/2017] [Indexed: 12/23/2022]
Abstract
The discovery of new laryngeal cancer-related metabolite biomarkers could help to facilitate early diagnosis. A serum metabolomics study from laryngeal cancer patients and healthy individuals was conducted using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Univariate and multivariate statistics were used to discriminate laryngeal cancer patients and healthy individuals. 1-Palmitoyl-sn-glycero-3-phosphocholine (LysoPC 16:0), 1-o-hexadecyl-2-acetyl-sn-glycero-3-phosphocholine (PAF) and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine were found to be significantly different between the laryngeal cancer group and the healthy group. They are mainly involved in phospholipids catabolism, linoleic acid metabolism, α-linoleic acid metabolism and arachidonic acid metabolism. The area under the curve of the biomarker combined by two metabolites (LysoPC 16:0 and PAF) was 0.935, the sensitivity was 0.962 and the specificity was 0.825. LysoPC 16:0 and PAF may show diagnostic potential for laryngeal carcinoma.
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Affiliation(s)
- Xiaotao Zhang
- China National Tobacco Quality Supervision and Test Center, Zhengzhou High and New Technology Industries Development Zone, Zhengzhou, China.,Institute of Applied Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Hongwei Hou
- China National Tobacco Quality Supervision and Test Center, Zhengzhou High and New Technology Industries Development Zone, Zhengzhou, China
| | - Huan Chen
- China National Tobacco Quality Supervision and Test Center, Zhengzhou High and New Technology Industries Development Zone, Zhengzhou, China
| | - Yong Liu
- Institute of Applied Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - An Wang
- Institute of Applied Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Qingyuan Hu
- China National Tobacco Quality Supervision and Test Center, Zhengzhou High and New Technology Industries Development Zone, Zhengzhou, China.,Institute of Applied Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
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Zhang H, Cui L, Liu W, Wang Z, Ye Y, Li X, Wang H. 1H NMR metabolic profiling of gastric cancer patients with lymph node metastasis. Metabolomics 2018; 14:47. [PMID: 29541009 PMCID: PMC5840249 DOI: 10.1007/s11306-018-1344-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients. OBJECTIVES We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC. METHODS 1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n = 40), LNM-negative GC patients (n = 40) and normal controls (n = 40). RESULTS There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM. CONCLUSION To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.
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Affiliation(s)
- Hailong Zhang
- Joint National Laboratory for Antibody Drug Engineering, Henan Key Laboratory of Cellular and Molecular Immunology, Henan University, Kaifeng, 475004, Henan, China
- School of Basic Medicine, Henan University, Kaifeng, 475004, Henan, China
| | - Longzhen Cui
- School of Basic Medicine, Henan University, Kaifeng, 475004, Henan, China
| | - Wen Liu
- School of Basic Medicine, Henan University, Kaifeng, 475004, Henan, China
| | - Zhenfeng Wang
- Joint National Laboratory for Antibody Drug Engineering, Henan Key Laboratory of Cellular and Molecular Immunology, Henan University, Kaifeng, 475004, Henan, China
| | - Yang Ye
- Joint National Laboratory for Antibody Drug Engineering, Henan Key Laboratory of Cellular and Molecular Immunology, Henan University, Kaifeng, 475004, Henan, China
| | - Xue Li
- School of Basic Medicine, Henan University, Kaifeng, 475004, Henan, China
| | - Huijuan Wang
- Joint National Laboratory for Antibody Drug Engineering, Henan Key Laboratory of Cellular and Molecular Immunology, Henan University, Kaifeng, 475004, Henan, China.
- School of Basic Medicine, Henan University, Kaifeng, 475004, Henan, China.
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Review of recent developments in determining volatile organic compounds in exhaled breath as biomarkers for lung cancer diagnosis. Anal Chim Acta 2017; 996:1-9. [DOI: 10.1016/j.aca.2017.09.021] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Revised: 09/08/2017] [Accepted: 09/09/2017] [Indexed: 12/20/2022]
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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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