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Christopoulou I, Kostopoulou E, Matzarapi K, Chasapi SA, Spyroulias GA, Varvarigou A. Identification of Novel Biomarkers in Late Preterm Neonates with Respiratory Distress Syndrome (RDS) Using Urinary Metabolomic Analysis. Metabolites 2023; 13:metabo13050644. [PMID: 37233686 DOI: 10.3390/metabo13050644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 04/30/2023] [Accepted: 05/03/2023] [Indexed: 05/27/2023] Open
Abstract
Urine metabolomics is gaining traction as a means of identifying metabolic signatures associated with health and disease states. Thirty-one (31) late preterm (LP) neonates admitted to the neonatal intensive care unit (NICU) and 23 age-matched healthy LPs admitted to the maternity ward of a tertiary hospital were included in the study. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed for urine metabolomic analysis on the 1st and 3rd days of life of the neonates. The data were analyzed using univariate and multivariate statistical analysis. A unique metabolic pattern of enhanced metabolites was identified in the NICU-admitted LPs from the 1st day of life. Metabolic profiles were distinct in LPs presenting with respiratory distress syndrome (RDS). The discrepancies likely reflect differences in the gut microbiota, either due to variations in nutrient intake or as a result of medical interventions, such as the administration of antibiotics and other medications. Altered metabolites could potentially serve as biomarkers for identifying critically ill LP neonates or those at high risk for adverse outcomes later in life, including metabolic risks. The discovery of novel biomarkers may uncover potential targets for drug discovery and optimal periods for effective intervention, offering a personalized approach.
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Affiliation(s)
- Irene Christopoulou
- Department of Paediatrics, University of Patras Medical School, General University Hospital, 26500 Patras, Greece
| | - Eirini Kostopoulou
- Department of Paediatrics, University of Patras Medical School, General University Hospital, 26500 Patras, Greece
| | | | | | | | - Anastasia Varvarigou
- Department of Paediatrics, University of Patras Medical School, General University Hospital, 26500 Patras, Greece
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Serum Metabolomics Profiling Reveals Metabolic Alterations Prior to a Diagnosis with Non-Small Cell Lung Cancer among Chinese Community Residents: A Prospective Nested Case-Control Study. Metabolites 2022; 12:metabo12100906. [PMID: 36295809 PMCID: PMC9610639 DOI: 10.3390/metabo12100906] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/18/2022] [Accepted: 09/22/2022] [Indexed: 11/17/2022] Open
Abstract
The present high mortality of lung cancer in China stems mainly from the lack of feasible, non-invasive and early disease detection biomarkers. Serum metabolomics profiling to reveal metabolic alterations could expedite the disease detection process and suggest those patients who are harboring disease. Using a nested case-control design, we applied ultra-high-performance liquid chromatography/mass spectrometry (LC-MS)-based serum metabolomics to reveal the metabolomic alterations and to indicate the presence of non-small cell lung cancer (NSCLC) using serum samples collected prior to disease diagnoses. The studied serum samples were collected from 41 patients before a NSCLC diagnosis (within 3.0 y) and 38 matched the cancer-free controls from the prospective Shanghai Suburban Adult Cohort. The NSCLC patients markedly presented cellular metabolism alterations in serum samples collected prior to their disease diagnoses compared with the cancer-free controls. In total, we identified 18 significantly expressed metabolites whose relative abundance showed either an upward or a downward trend, with most of them being lipid and lipid-like molecules, organic acids, and nitrogen compounds. Choline metabolism in cancer, sphingolipid, and glycerophospholipid metabolism emerged as the significant metabolic disturbance of NSCLC. The metabolites involved in these biological processes may be the distinctive features associated with NSCLC prior to a diagnosis.
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Zhuang J, Yang X, Zheng Q, Li K, Cai L, Yu H, Lv J, Bai K, Cao Q, Li P, Yang H, Wang J, Lu Q. Metabolic Profiling of Bladder Cancer Patients' Serum Reveals Their Sensitivity to Neoadjuvant Chemotherapy. Metabolites 2022; 12:metabo12060558. [PMID: 35736490 PMCID: PMC9229374 DOI: 10.3390/metabo12060558] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 02/07/2023] Open
Abstract
Numerous patients with muscle-invasive bladder cancer develop low responsiveness to cisplatin. Our purpose was to explore differential metabolites derived from serum in bladder cancer patients treated with neoadjuvant chemotherapy (NAC). Data of patients diagnosed with cT2-4aNxM0 was collected. Blood samples were retained prospectively before the first chemotherapy for untargeted metabolomics by 1H-NMR and UPLC-MS. To identify characterized metabolites, multivariate statistical analyses were applied, and the intersection of the differential metabolites discovered by the two approaches was used to identify viable biomarkers. A total of 18 patients (6 NAC-sensitive patients and 12 NAC-resistant patients) were enrolled. There were 29 metabolites detected by 1H-NMR and 147 metabolites identified by UPLC-MS. Multivariate statistics demonstrated that in the sensitive group, glutamine and taurine were considerably increased compared to their levels in the resistant group, while glutamate and hypoxanthine were remarkably decreased. Pathway analysis and enrichment analysis showed significant alterations in amino acid pathways, suggesting that response to chemotherapy may be related to amino acid metabolism. In addition, hallmark analysis showed that DNA repair played a regulatory role. Overall, serum metabolic profiles of NAC sensitivity are significantly different in bladder cancer patients. Glycine, hypoxanthine, taurine and glutamine may be the potential biomarkers for clinical treatment. Amino acid metabolism has potential value in enhancing drug efficacy.
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Affiliation(s)
- Juntao Zhuang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Xiao Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Qi Zheng
- Center of Molecular Metabolism, Nanjing University of Science and Technology, Nanjing 210094, China;
| | - Kai Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Lingkai Cai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Hao Yu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Jiancheng Lv
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Kexin Bai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Qiang Cao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Pengchao Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Haiwei Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Junsong Wang
- Center of Molecular Metabolism, Nanjing University of Science and Technology, Nanjing 210094, China;
- Correspondence: (J.W.); (Q.L.)
| | - Qiang Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
- Correspondence: (J.W.); (Q.L.)
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Zidi O, Souai N, Raies H, Ben Ayed F, Mezlini A, Mezrioui S, Tranchida F, Sabatier JM, Mosbah A, Cherif A, Shintu L, Kouidhi S. Fecal Metabolic Profiling of Breast Cancer Patients during Neoadjuvant Chemotherapy Reveals Potential Biomarkers. Molecules 2021; 26:2266. [PMID: 33919750 PMCID: PMC8070723 DOI: 10.3390/molecules26082266] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 11/17/2022] Open
Abstract
Breast cancer (BC) is the most common form of cancer among women worldwide. Despite the huge advancements in its treatment, the exact etiology of breast cancer still remains unresolved. There is an increasing interest in the role of the gut microbiome in modulating the anti-cancer therapeutic response. It seems that alteration of the microbiome-derived metabolome potentially promotes carcinogenesis. Taken together, metabolomics has arisen as a fascinating new omics field to screen promising metabolic biomarkers. In this study, fecal metabolite profiling was performed using NMR spectroscopy, to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy (NAC) for breast cancer. Metabolic profiles of feces from patients (n = 8) following chemotherapy treatment cycles were studied. Interestingly, amino acids were found to be upregulated, while lactate and fumaric acid were downregulated in patients under the second and third cycles compared with patients before treatment. Furthermore, short-chain fatty acids (SCFAs) were significantly differentiated between the studied groups. These results strongly suggest that chemotherapy treatment plays a key role in modulating the fecal metabolomic profile of BC patients. In conclusion, we demonstrate the feasibility of identifying specific fecal metabolic profiles reflecting biochemical changes that occur during the chemotherapy treatment. These data give an interesting insight that may complement and improve clinical tools for BC monitoring.
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Affiliation(s)
- Oumaima Zidi
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Nessrine Souai
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Henda Raies
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Farhat Ben Ayed
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Amel Mezlini
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
| | - Sonia Mezrioui
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Fabrice Tranchida
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Jean-Marc Sabatier
- Faculté de Pharmacie, Institute of NeuroPhysiopathology (INP), UMR 7051, 27, Boulevard Jean-Moulin, CEDEX, 13005 Marseille, France
| | - Amor Mosbah
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Ameur Cherif
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Laetitia Shintu
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Soumaya Kouidhi
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
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Miller IJ, Peters SR, Overmyer KA, Paulson BR, Westphall MS, Coon JJ. Real-time health monitoring through urine metabolomics. NPJ Digit Med 2019; 2:109. [PMID: 31728416 PMCID: PMC6848197 DOI: 10.1038/s41746-019-0185-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 10/22/2019] [Indexed: 12/15/2022] Open
Abstract
Current healthcare practices are reactive and based on limited physiological information collected months or years apart. By enabling patients and healthy consumers access to continuous measurements of health, wearable devices and digital medicine stand to realize highly personalized and preventative care. However, most current digital technologies provide information on a limited set of physiological traits, such as heart rate and step count, which alone offer little insight into the etiology of most diseases. Here we propose to integrate data from biohealth smartphone applications with continuous metabolic phenotypes derived from urine metabolites. This combination of molecular phenotypes with quantitative measurements of lifestyle reflect the biological consequences of human behavior in real time. We present data from an observational study involving two healthy subjects and discuss the challenges, opportunities, and implications of integrating this new layer of physiological information into digital medicine. Though our dataset is limited to two subjects, our analysis (also available through an interactive web-based visualization tool) provides an initial framework to monitor lifestyle factors, such as nutrition, drug metabolism, exercise, and sleep using urine metabolites.
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Affiliation(s)
- Ian J. Miller
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
| | - Sean R. Peters
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
| | | | - Brett R. Paulson
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
| | - Michael S. Westphall
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
| | - Joshua J. Coon
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
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Seow WJ, Shu XO, Nicholson JK, Holmes E, Walker DI, Hu W, Cai Q, Gao YT, Xiang YB, Moore SC, Bassig BA, Wong JYY, Zhang J, Ji BT, Boulangé CL, Kaluarachchi M, Wijeyesekera A, Zheng W, Elliott P, Rothman N, Lan Q. Association of Untargeted Urinary Metabolomics and Lung Cancer Risk Among Never-Smoking Women in China. JAMA Netw Open 2019; 2:e1911970. [PMID: 31539079 PMCID: PMC6755532 DOI: 10.1001/jamanetworkopen.2019.11970] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
IMPORTANCE Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood. OBJECTIVE To assess the association between metabolomics and lung cancer risk among never-smoking women. DESIGN, SETTING, AND PARTICIPANTS This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women's Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018. EXPOSURES Untargeted ultra-high-performance liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured. MAIN OUTCOMES AND MEASURES Incident lung cancer. RESULTS Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P < .001; false discovery rate = 0.039). Furthermore, this peak was weakly correlated with self-reported dietary soy intake (ρ = 0.21; P < .001). Increasing tertiles of this metabolite were associated with lower lung cancer risk (in comparison with first tertile, odds ratio for second tertile, 0.52 [95% CI, 0.34-0.80]; and odds ratio for third tertile, 0.46 [95% CI, 0.30-0.70]), and the association was consistent across different histological subtypes and follow-up times. Additionally, metabolic pathway analysis found several systemic biological alterations that were associated with lung cancer risk, including 1-carbon metabolism, nucleotide metabolism, oxidative stress, and inflammation. CONCLUSIONS AND RELEVANCE This prospective study of the untargeted urinary metabolome and lung cancer among never-smoking women in China provides support for the hypothesis that soy-based metabolites are associated with lower lung cancer risk in never-smoking women and suggests that biological processes linked to air pollution may be associated with higher lung cancer risk in this population.
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Affiliation(s)
- Wei Jie Seow
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Jeremy K. Nicholson
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Elaine Holmes
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Douglas I. Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
- State Key Laboratory of Oncogene and Related Genes, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Steven C. Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Bryan A. Bassig
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Jason Y. Y. Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Jinming Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Claire L. Boulangé
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Manuja Kaluarachchi
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Anisha Wijeyesekera
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Paul Elliott
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- MRC-PHE Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, United Kingdom
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, United Kingdom
- Health Data Research UK London at Imperial College London, United Kingdom
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
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Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. A Review. Metabolites 2019; 9:metabo9050102. [PMID: 31121909 PMCID: PMC6572290 DOI: 10.3390/metabo9050102] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 05/13/2019] [Accepted: 05/17/2019] [Indexed: 12/24/2022] Open
Abstract
Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted.
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Capillary electrophoresis mass spectrometry as a tool for untargeted metabolomics. Bioanalysis 2017; 9:99-130. [PMID: 27921456 DOI: 10.4155/bio-2016-0216] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Highly polar and ionic metabolites, such as sugars, most amino acids, organic acids or nucleotides are not retained by conventional reversed-phase LC columns and polar stationary phases and hydrophilic-interaction LC lacks of robustness, which is still limiting their applications for untargeted metabolomics where reproducibility is a must. Biological samples such as blood, urine or even tissues include many hydrophilic compounds secreted from cells, their analysis is essential for biomarker discovery, disease progression or treatment effects. This review focuses on CE coupled to MS as a mature technique for untargeted metabolomics including sample pretreatment, types of matrices, analytical methods, applications and data treatment strategies for polar compound analysis in biological matrices. The main applications and results of CE-MS in untargeted metabolomics are discussed and presented in a tabulated format.
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KAWAI T. Recent Studies on Online Sample Preconcentration Methods inCapillary Electrophoresis Coupled with Mass Spectrometry. CHROMATOGRAPHY 2017. [DOI: 10.15583/jpchrom.2017.001] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Affiliation(s)
- Takayuki KAWAI
- Quantitative Biology Center, RIKEN
- Japan Science and Technology Agency, PRESTO
- Graduate School of Frontier Biosciences, Osaka University
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Affiliation(s)
- Rachel K Harstad
- University of Minnesota , Department of Chemistry, 207 Pleasant Street South East, Minneapolis, Minnesota 55455, United States
| | - Alexander C Johnson
- University of Minnesota , Department of Chemistry, 207 Pleasant Street South East, Minneapolis, Minnesota 55455, United States
| | - Megan M Weisenberger
- University of Minnesota , Department of Chemistry, 207 Pleasant Street South East, Minneapolis, Minnesota 55455, United States
| | - Michael T Bowser
- University of Minnesota , Department of Chemistry, 207 Pleasant Street South East, Minneapolis, Minnesota 55455, United States
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Poinsot V, Ong-Meang V, Gavard P, Couderc F. Recent advances in amino acid analysis by capillary electromigration methods, 2013-2015. Electrophoresis 2015; 37:142-61. [DOI: 10.1002/elps.201500302] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 08/19/2015] [Accepted: 08/19/2015] [Indexed: 12/17/2022]
Affiliation(s)
- Véréna Poinsot
- Université Paul Sabatier, Université de Toulouse, Laboratoire des IMRCP; Toulouse Cedex France
| | - Varravaddheay Ong-Meang
- Université Paul Sabatier, Université de Toulouse, Laboratoire des IMRCP; Toulouse Cedex France
| | - Pierre Gavard
- Université Paul Sabatier, Université de Toulouse, Laboratoire des IMRCP; Toulouse Cedex France
| | - François Couderc
- Université Paul Sabatier, Université de Toulouse, Laboratoire des IMRCP; Toulouse Cedex France
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Klepárník K. Recent advances in combination of capillary electrophoresis with mass spectrometry: Methodology and theory. Electrophoresis 2014; 36:159-78. [DOI: 10.1002/elps.201400392] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2014] [Revised: 09/11/2014] [Accepted: 09/11/2014] [Indexed: 12/15/2022]
Affiliation(s)
- Karel Klepárník
- Institute of Analytical Chemistry; Academy of Sciences of the Czech Republic; Brno Czech Republic
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14
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Buzatto AZ, de Sousa AC, Guedes SF, Cieslarová Z, Simionato AVC. Metabolomic investigation of human diseases biomarkers by CE and LC coupled to MS. Electrophoresis 2014; 35:1285-307. [PMID: 24375663 DOI: 10.1002/elps.201300470] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2013] [Revised: 12/18/2013] [Accepted: 12/19/2013] [Indexed: 12/13/2022]
Abstract
Metabolomics is one of the most recent trends in the "omics" era that investigates the end products of an organism activity, that is, all metabolites in a biological system, which are small molecules (less than 1000 Da) from different chemical classes. Metabolomics represents a tool to assess the biochemical activity of a living system through the analysis of substrates and products processed during the metabolism. The analysis of the metabolic profile (nontargeted analysis, i.e. a comparison between samples profiles of individuals) and of specific metabolites (targeted analysis, which quantifies a selected group of metabolites) in biological samples provides an insight into the metabolic state and the biochemical processes of the organism and, therefore, may indicate the onset and the stage of different diseases. An early and accurate diagnosis is essential for successful treatment and probable cure of most illnesses; hence, the investigation of metabolites as disease biomarkers has increased considerably in recent years. This review aims to present the most relevant works that address the nontargeted and targeted analysis of metabolites in different diseases for the past 10 years, including kidney and neurological disorders, cardiovascular diseases, diabetes, and cancer, using CE and LC coupled with the accurate detection of mass spectroscopy.
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Affiliation(s)
- Adriana Z Buzatto
- Institute of Chemistry, University of Campinas - Unicamp, Campinas, Brazil
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Robledo VR, Smyth WF. Review of the CE-MS platform as a powerful alternative to conventional couplings in bio-omics and target-based applications. Electrophoresis 2014; 35:2292-308. [DOI: 10.1002/elps.201300561] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2013] [Revised: 01/24/2014] [Accepted: 01/24/2014] [Indexed: 02/01/2023]
Affiliation(s)
- Virginia Rodríguez Robledo
- Faculty of Pharmacy; Department of Analytical Chemistry and Food Technology; University of Castilla-La Mancha (UCLM); Albacete Spain
| | - William Franklin Smyth
- School of Pharmacy and Pharmaceutical Sciences; University of Ulster; Coleraine Northern Ireland UK
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Martinez-Outschoorn UE, Lisanti MP, Sotgia F. Catabolic cancer-associated fibroblasts transfer energy and biomass to anabolic cancer cells, fueling tumor growth. Semin Cancer Biol 2014; 25:47-60. [PMID: 24486645 DOI: 10.1016/j.semcancer.2014.01.005] [Citation(s) in RCA: 311] [Impact Index Per Article: 31.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Revised: 01/17/2014] [Accepted: 01/17/2014] [Indexed: 12/22/2022]
Abstract
Fibroblasts are the most abundant "non-cancerous" cells in tumors. However, it remains largely unknown how these cancer-associated fibroblasts (CAFs) promote tumor growth and metastasis, driving chemotherapy resistance and poor clinical outcome. This review summarizes new findings on CAF signaling pathways and their emerging metabolic phenotypes that promote tumor growth. Although it is well established that altered cancer metabolism enhances tumor growth, little is known about the role of fibroblast metabolism in tumor growth. New studies reveal that metabolic coupling occurs between catabolic fibroblasts and anabolic cancer cells, in many types of human tumors, including breast, prostate, and head & neck cancers, as well as lymphomas. These catabolic phenotypes observed in CAFs are secondary to a ROS-induced metabolic stress response. Mechanistically, this occurs via HIF1-alpha and NFκB signaling, driving oxidative stress, autophagy, glycolysis and senescence in stromal fibroblasts. These catabolic CAFs then create a nutrient-rich microenvironment, to metabolically support tumor growth, via the local stromal generation of mitochondrial fuels (lactate, ketone bodies, fatty acids, glutamine, and other amino acids). New biomarkers of this catabolic CAF phenotype (such as caveolin-1 (Cav-1) and MCT4), which are reversible upon treatment with anti-oxidants, are strong predictors of poor clinical outcome in various types of human cancers. How cancer cells metabolically reprogram fibroblasts can also help us to understand the effects of cancer cells at an organismal level, explaining para-neoplastic phenomena, such as cancer cachexia. In conclusion, cancer should be viewed more as a systemic disease, that engages the host-organism in various forms of energy-transfer and metabolic co-operation, across a whole-body "ecosystem".
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Affiliation(s)
| | - Michael P Lisanti
- Manchester Breast Centre & Breakthrough Breast Cancer Research Unit, Institute of Cancer Sciences, University of Manchester, UK; Manchester Centre for Cellular Metabolism (MCCM), University of Manchester, UK.
| | - Federica Sotgia
- Manchester Breast Centre & Breakthrough Breast Cancer Research Unit, Institute of Cancer Sciences, University of Manchester, UK; Manchester Centre for Cellular Metabolism (MCCM), University of Manchester, UK.
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17
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The potential of electrophoretic sample pretreatment techniques and new instrumentation for bioanalysis, with a focus on peptidomics and metabolomics. Bioanalysis 2013; 5:2785-801. [DOI: 10.4155/bio.13.254] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
This Review highlights the potential of new electromigration-based sample pretreatment techniques for bioanalysis. Sample pretreatment is a challenging part of the analytical workflow, especially in the fields of peptidomics and metabolomics, where the analytes are very diverse, both in physicochemical properties and in endogenous concentration. Electromigration-based techniques have several strengths, such as fast selective analyte concentration and that complementary information on the content of a sample can be obtained when compared with more conventional (chromatography-based) techniques. In the past decade, various new electromigration-based sample pretreatment techniques have been developed, and importantly, new instrumental setups. In this Review, we provide an introduction on electromigration and its strengths. Then, selected examples of electromigration-based sample pretreatment techniques and instrumentation are discussed, namely free-flow electrophoresis, isoelectric focusing, isotachophoresis, electrodialysis, electromembrane extraction and electroextraction. Finally, the promising perspectives of electromigration-based sample pretreatment techniques are outlined.
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