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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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Di Minno A, Gelzo M, Caterino M, Costanzo M, Ruoppolo M, Castaldo G. Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine. Int J Mol Sci 2022; 23:5213. [PMID: 35563604 PMCID: PMC9103094 DOI: 10.3390/ijms23095213] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/29/2022] [Accepted: 05/05/2022] [Indexed: 12/12/2022] Open
Abstract
Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.
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Affiliation(s)
- Alessandro Di Minno
- Dipartimento di Farmacia, University of Naples Federico II, 80131 Naples, Italy
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
| | - Monica Gelzo
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
| | - Marianna Caterino
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
| | - Michele Costanzo
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
| | - Margherita Ruoppolo
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
| | - Giuseppe Castaldo
- CEINGE-Biotecnologie Avanzate, 80131 Naples, Italy; (M.G.); (M.C.); (M.C.); (M.R.); (G.C.)
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
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3
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Junior RP, Sonehara NM, Jardim-Perassi BV, Pal A, Asad Y, Almeida Chuffa LG, Chammas R, Raynaud FI, Zuccari DAPC. Presence of human breast cancer xenograft changes the diurnal profile of amino acids in mice. Sci Rep 2022; 12:1008. [PMID: 35046467 PMCID: PMC8770691 DOI: 10.1038/s41598-022-04994-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 01/04/2022] [Indexed: 12/25/2022] Open
Abstract
Human xenografts are extremely useful models to study the biology of human cancers and the effects of novel potential therapies. Deregulation of metabolism, including changes in amino acids (AAs), is a common characteristic of many human neoplasms. Plasma AAs undergo daily variations, driven by circadian endogenous and exogenous factors. We compared AAs concentration in triple negative breast cancer MDA-MB-231 cells and MCF10A non-tumorigenic immortalized breast epithelial cells. We also measured plasma AAs in mice bearing xenograft MDA-MB-231 and compared their levels with non-tumor-bearing control animals over 24 h. In vitro studies revealed that most of AAs were significantly different in MDA-MB-231 cells when compared with MCF10A. Plasma concentrations of 15 AAs were higher in cancer cells, two were lower and four were observed to shift across 24 h. In the in vivo setting, analysis showed that 12 out of 20 AAs varied significantly between tumor-bearing and non-tumor bearing mice. Noticeably, these metabolites peaked in the dark phase in non-tumor bearing mice, which corresponds to the active time of these animals. Conversely, in tumor-bearing mice, the peak time occurred during the light phase. In the early period of the light phase, these AAs were significantly higher in tumor-bearing animals, yet significantly lower in the middle of the light phase when compared with controls. This pilot study highlights the importance of well controlled experiments in studies involving plasma AAs in human breast cancer xenografts, in addition to emphasizing the need for more precise examination of exometabolomic changes using multiple time points.
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Affiliation(s)
- Rubens Paula Junior
- Faculdade de Medicina de São José Do Rio Preto, São José do Rio Preto, Brazil.
| | | | | | - Akos Pal
- The Institute of Cancer Research, London, UK
| | - Yasmin Asad
- The Institute of Cancer Research, London, UK
| | | | - Roger Chammas
- Instituto Do Câncer Do Estado de São Paulo, São Paulo, Brazil
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Di Minno A, Gelzo M, Stornaiuolo M, Ruoppolo M, Castaldo G. The evolving landscape of untargeted metabolomics. Nutr Metab Cardiovasc Dis 2021; 31:1645-1652. [PMID: 33895079 DOI: 10.1016/j.numecd.2021.01.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/08/2021] [Accepted: 01/13/2021] [Indexed: 02/07/2023]
Abstract
AIMS Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics. DATA SYNTHESIS Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available. CONCLUSIONS Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.
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Affiliation(s)
- Alessandro Di Minno
- Dipartimento di Farmacia, Università Degli Studi di Napoli "Federico II", Napoli, 80131, Italy; CEINGE-Biotecnologie Avanzate, Naples, Italy
| | - Monica Gelzo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy
| | - Mariano Stornaiuolo
- Dipartimento di Farmacia, Università Degli Studi di Napoli "Federico II", Napoli, 80131, Italy
| | - Margherita Ruoppolo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy
| | - Giuseppe Castaldo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy.
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Lai H, Jiang W, Zhao J, Dinglin X, Li Y, Li S, Wang Y, Yao H. Global Trend in Research and Development of CDK4/6 Inhibitors for Clinical Cancer Therapy: A Bibliometric Analysis. J Cancer 2021; 12:3539-3547. [PMID: 33995631 PMCID: PMC8120189 DOI: 10.7150/jca.51609] [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: 08/06/2020] [Accepted: 03/25/2021] [Indexed: 02/03/2023] Open
Abstract
Background: Cyclin-dependent kinase (CDK) 4/6 inhibitors are frequently used anti-cancer agents in hormone receptor-positive breast cancers. This study assessed the course of research and development (R&D) for CDK4/6 inhibitors in terms of publications over the past two decades. Methods: The Web of Science (WOS) and PubMed databases were searched to identify publications related to research on CDK4/6 inhibitors since 2001. The VOS Viewer software was used to analyze co-occurring keywords to stratify the publication data and collaborations in research. Results: There were 1395 publications related to research on CDK4/6 inhibitors since 2001. Eight of the top 10 institutions originated from the USA and the other two were a Swiss Pharmaceutical Company and French Research Institute. Bardia A, the first author for some of the articles published in the USA, was the most prolific with 25 publications. The journal with the most publications was Cancer Res with 162 publications. Basic research comprised six of the 10 most frequently cited publications and the rest consisted of three reviews and a clinical trial. The most common keywords for publications since 2011 were “palbociclib”, “abemaciclib”, “ribociclib” and “double blind”, indicating the successful development of CDK4/6 inhibitors as anticancer drugs. Conclusions: This study provides a comprehensive review of the CDK4/6 inhibitors R&D history. The data imply that drug development in this field is a decade-long process and clinical trials have been performed before clinical applications. Thereafter, research was conducted on the adverse effects and drug resistance associated with the inhibitors.
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Affiliation(s)
- Hongna Lai
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Wei Jiang
- Department of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Jianli Zhao
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Xiaoxiao Dinglin
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Yudong Li
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Shunying Li
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Ying Wang
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Herui Yao
- Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, Guangzhou 510120, China.,Breast Tumour Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
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6
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Trifonova OP, Balashova EE, Maslov DL, Grigoriev AI, Lisitsa AV, Ponomarenko EA, Archakov AI. [Blood metabolome analysis for creating a digital image of a healthy person]. BIOMEDITSINSKAIA KHIMIIA 2020; 66:216-223. [PMID: 32588827 DOI: 10.18097/pbmc20206603216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
In the frame of the work, data on the implementation of metabolomics tests in medicine have been systematized. Based on the obtained data, a set of protocols was proposed, the sequential realization of which makes it possible to conduct a blood metabolome analysis for medical purposes. Using this analysis and the number of blood samples from healthy volunteers, a prototype of a healthy person's metabolomic image has been developed; it allows visually and digitally to assess the compliance of the human blood metabolome with the norm. At the same time, 99% of the metabolic processes reflected in the blood plasma are estimated. If abnormalities are detected, the metabolomic image allows to get the value of these deviations of metabolic processes in digital terms.
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Affiliation(s)
| | | | - D L Maslov
- Institute of Biomedical Chemistry, Moscow, Russia
| | - A I Grigoriev
- Institute of Biomedical Problems of the Russian Academy of Sciences, Moscow, Russia
| | - A V Lisitsa
- Institute of Biomedical Chemistry, Moscow, Russia
| | | | - A I Archakov
- Institute of Biomedical Chemistry, Moscow, Russia
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7
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Pharmaco-Geno-Proteo-Metabolomics and Translational Research in Cancer. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019. [PMID: 31713161 DOI: 10.1007/978-3-030-24100-1_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2023]
Abstract
The diagnosis, prognosis and treatment of cancer has had a great improvement due to the "omics" technologies such as genomics, proteomics, epigenomics, pharmacogenomics, and metabolomics. The technological progress of these technologies has allowed precision medicine to become a clinical reality. The study of different biomolecules such as DNA, RNA and proteins has helped to detect alterations in genes, changes in gene expression profiles and loss or gain of protein function, which allows us to make associations and better understand the cancer biology. Data obtained from different "omics" technologies gives a complementary spectrum of information that helps us to understand and unveil new information for a better diagnosis, prognosis, prediction of new molecular targets of anticancer therapies, etc. This chapter presents a general landscape of the interaction between the Pharmaco-Geno-Proteo-Metabolomic and translational medicine research in cancer.
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Morse N, Jamaspishvili T, Simon D, Patel PG, Ren KYM, Wang J, Oleschuk R, Kaufmann M, Gooding RJ, Berman DM. Reliable identification of prostate cancer using mass spectrometry metabolomic imaging in needle core biopsies. J Transl Med 2019; 99:1561-1571. [PMID: 31160688 DOI: 10.1038/s41374-019-0265-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 04/06/2019] [Accepted: 04/29/2019] [Indexed: 01/01/2023] Open
Abstract
Metabolomic profiling can aid in understanding crucial biological processes in cancer development and progression and can also yield diagnostic biomarkers. Desorption electrospray ionization coupled to mass spectrometry imaging (DESI-MSI) has been proposed as a potential adjunct to diagnostic surgical pathology, particularly for prostate cancer. However, due to low resolution sampling, small numbers of mass spectra, and little validation, published studies have yet to test whether this method is sufficiently robust to merit clinical translation. We used over 900 spatially resolved DESI-MSI spectra to establish an accurate, high-resolution metabolic profile of prostate cancer. We identified 25 differentially abundant metabolites, with cancer tissue showing increased fatty acids (FAs) and phospholipids, along with utilization of the Krebs cycle, and benign tissue showing increased levels of lyso-phosphatidylethanolamine (PE). Additionally, we identified, for the first time, two lyso-PEs with abundance that decreased with cancer grade and two phosphatidylcholines (PChs) with increased abundance with increasing cancer grade. Importantly, we developed and internally validated a multivariate metabolomic classifier for prostate cancer using 534 spatial regions of interest (ROIs) in the training cohort and 430 ROIs in the test cohort. With excellent statistical power, the training cohort achieved a balanced accuracy of 97% and validation on testing data set demonstrated 85% balanced accuracy. Given the validated accuracy of this classifier and the correlation of differentially abundant metabolites with established patterns of prostate cancer cell metabolism, we conclude that DESI-MSI is an effective tool for characterizing prostate cancer metabolism with the potential for clinical translation.
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Affiliation(s)
- Nicole Morse
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Tamara Jamaspishvili
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - David Simon
- Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Palak G Patel
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Kevin Yi Mi Ren
- Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Jenny Wang
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Richard Oleschuk
- Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Martin Kaufmann
- Department of Surgery, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Robert J Gooding
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - David M Berman
- Cancer Biology & Genetics, Queen's Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada. .,Department of Pathology & Molecular Medicine, Queen's University, Kingston, ON, K7L 3N6, Canada.
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9
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Pinu FR, Goldansaz SA, Jaine J. Translational Metabolomics: Current Challenges and Future Opportunities. Metabolites 2019; 9:E108. [PMID: 31174372 PMCID: PMC6631405 DOI: 10.3390/metabo9060108] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 06/04/2019] [Accepted: 06/04/2019] [Indexed: 02/06/2023] Open
Abstract
Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.
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Affiliation(s)
- Farhana R Pinu
- The New Zealand Institute for Plant and Food Research, Private Bag 92169, Auckland 1142, New Zealand.
| | - Seyed Ali Goldansaz
- Department of Agriculture, Food and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2P5, Canada.
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada.
| | - Jacob Jaine
- Analytica Laboratories Ltd., Ruakura Research Centre, Hamilton 3216, New Zealand.
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Jia H, Shen X, Guan Y, Xu M, Tu J, Mo M, Xie L, Yuan J, Zhang Z, Cai S, Zhu J, Zhu Z. Predicting the pathological response to neoadjuvant chemoradiation using untargeted metabolomics in locally advanced rectal cancer. Radiother Oncol 2018; 128:548-556. [PMID: 30041962 DOI: 10.1016/j.radonc.2018.06.022] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 04/19/2018] [Accepted: 06/14/2018] [Indexed: 12/16/2022]
Abstract
PURPOSE The present study aimed to identify a panel of potential metabolite biomarkers to predict tumor response to neoadjuvant chemo-radiation therapy (NCRT) in locally advanced rectal cancer (LARC). EXPERIMENTAL DESIGN Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics was used to profile human serum samples (n = 106) from LARC patients treated with NCRT. The samples were collected from Fudan University Shanghai Cancer Center (FUSCC) from July 2014 to January 2016. Statistical methods, such as partial least squares (PLS) and Wilcoxon rank-sum test, were used to identify discriminative metabolites between NCRT-sensitive and NCRT-resistant patients according to their tumor regression grade (TRG). This trial is registered with Clinical Trials.gov, number NCT03149978. RESULTS A panel of metabolites was selected as potential predictive biomarkers of pathological response to NCRT. A total of 4810 metabolic peaks were detected, and 57 significantly dysregulated peaks were identified. These 57 metabolic peaks were used to differentiate patients using PLS in a dataset containing NCRT-sensitive (n = 56) and NCRT-resistant (n = 49) patients. The combination of 57 metabolic peaks had AUC values of 0.88, 0.81 and 0.84 in the prediction models using PLS, random forest, and support vector machine, respectively, suggesting that metabolomics has the potential ability to predict responses to NCRT. Furthermore, 15 metabolite biomarkers were identified and used to construct a logistic regression model and explore dysregulated metabolic pathways using untargeted metabolic profiling and data mining approaches. CONCLUSIONS A panel of metabolites has been identified to facilitate the prediction of tumor response to NCRT in LARC, which is promising for the generation of personalized treatment strategies for LARC patients.
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Affiliation(s)
- Huixun Jia
- Clinical Statistics Center, Fudan University Shanghai Cancer Center, PR China; Department of Oncology, Shanghai Medical College, Fudan University, PR China
| | - Xiaotao Shen
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Yun Guan
- Department of Oncology, Shanghai Medical College, Fudan University, PR China; Department of Radiation Oncology, Fudan University Shanghai Cancer Center, PR China
| | - Meimei Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Jia Tu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Miao Mo
- Clinical Statistics Center, Fudan University Shanghai Cancer Center, PR China; Department of Oncology, Shanghai Medical College, Fudan University, PR China
| | - Li Xie
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, PR China
| | - Jing Yuan
- Clinical Statistics Center, Fudan University Shanghai Cancer Center, PR China; Department of Oncology, Shanghai Medical College, Fudan University, PR China
| | - Zhen Zhang
- Department of Oncology, Shanghai Medical College, Fudan University, PR China; Department of Radiation Oncology, Fudan University Shanghai Cancer Center, PR China
| | - Sanjun Cai
- Department of Oncology, Shanghai Medical College, Fudan University, PR China; Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, PR China
| | - Ji Zhu
- Department of Oncology, Shanghai Medical College, Fudan University, PR China; Department of Radiation Oncology, Fudan University Shanghai Cancer Center, PR China.
| | - ZhengJiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, PR China; University of Chinese Academy of Sciences, Beijing, PR China.
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11
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Lu Y, Li H, Geng Y. Analysis of the Effects of δ-Tocopherol on RAW264.7 and K562 Cells Based on 1H NMR Metabonomics. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2018; 66:1039-1046. [PMID: 29313349 DOI: 10.1021/acs.jafc.7b04667] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
δ-Tocopherol (δ-TOH) is a form of vitamin E with higher bioactivity. In this study, we studied the bioactivity of δ-TOH using the IC50 of δ-TOH on RAW264.7 (80 μM) and K562 (110 μM) cells. We compared the differential metabolites from the cell lines with and without δ-TOH treatment by 1H NMR metabonomics analysis. It was found that δ-TOH affected the protein biosynthesis, betaine metabolism, and urea cycle in various ways in both cell lines. Metabolic levels of the cell lines were changed after treatment with δ-TOH as differential metabolites were produced. The betaine level in RAW264.7 cells was reduced significantly, while the l-lactic acid level in K562 cells was significantly enhanced. The metabolic changes might contribute to the switch of the respiration pattern from aerobic respiration to anaerobic respiration in K562 cells. These results are helpful in further understanding the subtoxicity of δ-TOH.
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Affiliation(s)
- Yang Lu
- Key Laboratory of Food Nutrition and Safety of SDNU, Provincial Key Laboratory of Animal Resistant Biology, College of Life Science, Shandong Normal University , Jinan 250014, China
| | - Hui Li
- Key Laboratory of Food Nutrition and Safety of SDNU, Provincial Key Laboratory of Animal Resistant Biology, College of Life Science, Shandong Normal University , Jinan 250014, China
| | - Yue Geng
- Key Laboratory of Food Nutrition and Safety of SDNU, Provincial Key Laboratory of Animal Resistant Biology, College of Life Science, Shandong Normal University , Jinan 250014, China
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12
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Shen CT, Zhang Y, Liu YM, Yin S, Zhang XY, Wei WJ, Sun ZK, Song HJ, Qiu ZL, Wang CR, Luo QY. A distinct serum metabolic signature of distant metastatic papillary thyroid carcinoma. Clin Endocrinol (Oxf) 2017; 87:844-852. [PMID: 28755525 DOI: 10.1111/cen.13437] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 07/16/2017] [Accepted: 07/21/2017] [Indexed: 02/06/2023]
Abstract
BACKGROUND Although the incidence rate for thyroid cancer seems to have begun stabilizing in recent years, an increased rate of advanced stage of this disease has been reported. Additionally, distant metastasis is one of the most important prognostic factors of patients with papillary thyroid carcinoma (PTC). Unfortunately, the underlying mechanisms of distant metastasis, as well as cell status like metabolism changes in distant metastatic tumours have not been clearly elucidated. OBJECTIVE To identify serum metabolic signature of distant metastatic PTC. DESIGN, PATIENTS AND MEASUREMENTS In this study, gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) was used to analyse the serum from 77 patients diagnosed with PTC (37 in distant metastasis group and 40 in ablation group). Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) scores plots were used to analyse the data. RESULTS Principal component analysis and OPLS-DA analyses demonstrated an evident trend of separation between 40 serum samples from the ablation group and 37 samples from distant metastasis group. A total of 31 metabolites were identified, which are related to amino acid, lipid, glucose, vitamin metabolism and diet/gut microbiota interaction. Pathway analysis showed "alanine, aspartate and glutamate metabolism" and "inositol phosphate metabolism" were the most relevant pathways. CONCLUSION Serum metabolomics profiling could significantly discriminate papillary thyroid cancer patients according to distant metastasis. Potential metabolic aberration in distant metastatic PTC could be involved in different biological behaviours of tumour cells including proliferation, invasion/migration and immune escape. Diet/gut microbiota-produced metabolites could play an important role in these effects. This work may provide new clues to find the underlying mechanisms regarding the distant metastasis of PTC as well as potential adjuvant therapy targets.
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Affiliation(s)
- Chen-Tian Shen
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yinan Zhang
- Shanghai Key Laboratory of Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- The Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yu-Min Liu
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, China
| | - Shan Yin
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, China
| | - Xin-Yun Zhang
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Wei-Jun Wei
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Zhen-Kui Sun
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Hong-Jun Song
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Zhong-Ling Qiu
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Cong-Rong Wang
- Shanghai Key Laboratory of Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- The Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Quan-Yong Luo
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
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13
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Shields PG, Berman M, Brasky TM, Freudenheim JL, Mathe E, McElroy JP, Song MA, Wewers MD. A Review of Pulmonary Toxicity of Electronic Cigarettes in the Context of Smoking: A Focus on Inflammation. Cancer Epidemiol Biomarkers Prev 2017; 26:1175-1191. [PMID: 28642230 PMCID: PMC5614602 DOI: 10.1158/1055-9965.epi-17-0358] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2017] [Revised: 05/22/2017] [Accepted: 05/24/2017] [Indexed: 12/30/2022] Open
Abstract
The use of electronic cigarettes (e-cigs) is increasing rapidly, but their effects on lung toxicity are largely unknown. Smoking is a well-established cause of lung cancer and respiratory disease, in part through inflammation. It is plausible that e-cig use might affect similar inflammatory pathways. E-cigs are used by some smokers as an aid for quitting or smoking reduction, and by never smokers (e.g., adolescents and young adults). The relative effects for impacting disease risk may differ for these groups. Cell culture and experimental animal data indicate that e-cigs have the potential for inducing inflammation, albeit much less than smoking. Human studies show that e-cig use in smokers is associated with substantial reductions in blood or urinary biomarkers of tobacco toxicants when completely switching and somewhat for dual use. However, the extent to which these biomarkers are surrogates for potential lung toxicity remains unclear. The FDA now has regulatory authority over e-cigs and can regulate product and e-liquid design features, such as nicotine content and delivery, voltage, e-liquid formulations, and flavors. All of these factors may impact pulmonary toxicity. This review summarizes current data on pulmonary inflammation related to both smoking and e-cig use, with a focus on human lung biomarkers. Cancer Epidemiol Biomarkers Prev; 26(8); 1175-91. ©2017 AACR.
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Affiliation(s)
- Peter G Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio.
| | - Micah Berman
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Public Health, Ohio
| | - Theodore M Brasky
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio
| | - Jo L Freudenheim
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York
| | - Ewy Mathe
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio
| | - Joseph P McElroy
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio
| | - Min-Ae Song
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio
| | - Mark D Wewers
- Department of Internal Medicine, The Ohio State University, Columbus, Ohio
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14
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Jianyong Z, Jianjun X, Yongzhong O, Junwen L, Haiyan L, Dongliang Y, Jinhua P, Junwen X, Huanwen C, Yiping W. Rapid discrimination of human oesophageal squamous cell carcinoma by mass spectrometry based on differences in amino acid metabolism. Sci Rep 2017. [PMID: 28623324 PMCID: PMC5473808 DOI: 10.1038/s41598-017-03375-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Oesophageal cancer (OC) is associated with high morbidity and mortality, and surgery is the most effective approach to treat it. In order to reduce surgical risks and duration of surgery, we explored a new strategy to determine tumour margins in surgery. In this study, we included 128 cancerous and 128 noncancerous database entries obtained from 32 human patients. Using internal extractive electrospray ionization-MS, in positive ion detection mode, the relative abundances of m/z 104.13, m/z 116.10, m/z 132.13, and m/z 175.13 were higher in cancer tissue while the relative abundances of m/z 82.99, m/z 133.11, m/z 147.08, m/z 154.06, and m/z 188.05 were higher in normal tissue. Using partial least squares analysis, the mass spectra of cancer samples was discriminated from those of normal tissues, and the discriminatory ions were obtained from loading plots. Dimethylglycine(m/z 104), proline(m/z 116), isoleucine(m/z 132), asparagine(m/z 133), glutamine(m/z 147), and arginine(m/z 175) were identified by collision-induced dissociation experiments. Using the ROC curve analysis, we verified the validity of six amino acids for the identification of tumour tissue. Further investigations of tissue amino acids may allow us to better understand the underlying mechanisms involved in OC and develop novel means to identify tumour tissue during operation.
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Affiliation(s)
- Zhang Jianyong
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China.,Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, Jiangxi Province, 330013, P. R. China
| | - Xu Jianjun
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China
| | - Ouyang Yongzhong
- School of Chemistry, Biology and Materials Science, East China University of Technology, Nanchang, Jiangxi Province, 330013, P. R. China
| | - Liu Junwen
- School of Chemistry, Biology and Materials Science, East China University of Technology, Nanchang, Jiangxi Province, 330013, P. R. China
| | - Lu Haiyan
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, Jiangxi Province, 330013, P. R. China
| | - Yu Dongliang
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China
| | - Peng Jinhua
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China
| | - Xiong Junwen
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China
| | - Chen Huanwen
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, Jiangxi Province, 330013, P. R. China.
| | - Wei Yiping
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006, P. R. China.
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15
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Company profile: BluePen Biomarkers LLC – integrated biomarker solutions. Future Sci OA 2016; 2:FSO124. [PMID: 28031971 PMCID: PMC5137845 DOI: 10.4155/fsoa-2016-0031] [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: 05/04/2016] [Accepted: 05/06/2016] [Indexed: 11/17/2022] Open
Abstract
BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests.
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