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Santos MD, Barros I, Brandão P, Lacerda L. Amino Acid Profiles in the Biological Fluids and Tumor Tissue of CRC Patients. Cancers (Basel) 2023; 16:69. [PMID: 38201497 PMCID: PMC10778074 DOI: 10.3390/cancers16010069] [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: 11/18/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024] Open
Abstract
Amino acids are the building blocks of proteins and essential players in pathways such as the citric acid and urea cycle, purine and pyrimidine biosynthesis, and redox cell signaling. Therefore, it is unsurprising that these molecules have a significant role in cancer metabolism and its metabolic plasticity. As one of the most prevalent malign diseases, colorectal cancer needs biomarkers for its early detection, prognostic, and prediction of response to therapy. However, the available biomarkers for this disease must be more powerful and present several drawbacks, such as high costs and complex laboratory procedures. Metabolomics has gathered substantial attention in the past two decades as a screening platform to study new metabolites, partly due to the development of techniques, such as mass spectrometry or liquid chromatography, which have become standard practice in diagnostic procedures for other diseases. Extensive metabolomic studies have been performed in colorectal cancer (CRC) patients in the past years, and several exciting results concerning amino acid metabolism have been found. This review aims to gather and present findings concerning alterations in the amino acid plasma pool of colorectal cancer patients.
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Affiliation(s)
- Marisa Domingues Santos
- Colorectal Unit, Hospital de Santo António, Centro Hospitalar Universitário de Santo António, 4050-651 Porto, Portugal;
- UMIB—Unit for Multidisciplinary Research in Biomedicine, ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4050-313 Porto, Portugal; (I.B.); (L.L.)
- ITR—Laboratory for Integrative and Translational Research in Population Health, 4050-313 Porto, Portugal
| | - Ivo Barros
- UMIB—Unit for Multidisciplinary Research in Biomedicine, ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4050-313 Porto, Portugal; (I.B.); (L.L.)
| | - Pedro Brandão
- Colorectal Unit, Hospital de Santo António, Centro Hospitalar Universitário de Santo António, 4050-651 Porto, Portugal;
- UMIB—Unit for Multidisciplinary Research in Biomedicine, ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4050-313 Porto, Portugal; (I.B.); (L.L.)
- ITR—Laboratory for Integrative and Translational Research in Population Health, 4050-313 Porto, Portugal
| | - Lúcia Lacerda
- UMIB—Unit for Multidisciplinary Research in Biomedicine, ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4050-313 Porto, Portugal; (I.B.); (L.L.)
- ITR—Laboratory for Integrative and Translational Research in Population Health, 4050-313 Porto, Portugal
- Genetic Laboratory Service, Centro de Genética Médica Jacinto de Magalhães, Centro Hospitalar Universitário de Santo António, 4050-651 Porto, Portugal
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Bull C, Hazelwood E, Bell JA, Tan V, Constantinescu AE, Borges C, Legge D, Burrows K, Huyghe JR, Brenner H, Castellvi-Bel S, Chan AT, Kweon SS, Le Marchand L, Li L, Cheng I, Pai RK, Figueiredo JC, Murphy N, Gunter MJ, Timpson NJ, Vincent EE. Identifying metabolic features of colorectal cancer liability using Mendelian randomization. eLife 2023; 12:RP87894. [PMID: 38127078 PMCID: PMC10735227 DOI: 10.7554/elife.87894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023] Open
Abstract
Background Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. Methods To investigate whether changes in circulating metabolites characterize the early stages of colorectal cancer (CRC) development, we examined the associations between a genetic risk score (GRS) associated with CRC liability (72 single-nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N = 6221). Linear regression models were applied to examine the associations between genetic liability to CRC and circulating metabolites measured in the same individuals at age 8 y, 16 y, 18 y, and 25 y. Results The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P < 0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N = 118,466, median age 58 y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. Conclusions These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism and suggest that fatty acids may play an important role in CRC development. Funding This work was supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol, the Wellcome Trust, the Medical Research Council, Diabetes UK, the University of Bristol NIHR Biomedical Research Centre, and Cancer Research UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work used the computational facilities of the Advanced Computing Research Centre, University of Bristol - http://www.bristol.ac.uk/acrc/.
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Affiliation(s)
- Caroline Bull
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
- Translational Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Emma Hazelwood
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Vanessa Tan
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Andrei-Emil Constantinescu
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Carolina Borges
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Danny Legge
- Translational Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer CenterSeattleUnited States
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ)HeidelbergGermany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT)HeidelbergGermany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Sergi Castellvi-Bel
- Gastroenterology Department, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of BarcelonaBarcelonaSpain
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical SchoolBostonUnited States
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical SchoolBostonUnited States
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical SchoolBostonUnited States
- Broad Institute of Harvard and MITCambridgeUnited States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard UniversityBostonUnited States
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard UniversityBostonUnited States
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical SchoolGwangjuRepublic of Korea
- Jeonnam Regional Cancer Center, Chonnam National University Hwasun HospitalHwasunRepublic of Korea
| | | | - Li Li
- Department of Family Medicine, University of VirginiaCharlottesvilleUnited States
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California, San FranciscoSan FranciscoUnited States
- University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San FranciscoSan FranciscoUnited States
| | - Rish K Pai
- Department of Pathology and Laboratory Medicine, Mayo ClinicScottsdaleUnited States
| | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical CenterLos AngelesUnited States
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on CancerLyonFrance
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on CancerLyonFrance
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
- Translational Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
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Di Giovanni N, Meuwis MA, Louis E, Focant JF. Correlations for untargeted GC × GC-HRTOF-MS metabolomics of colorectal cancer. Metabolomics 2023; 19:85. [PMID: 37740774 DOI: 10.1007/s11306-023-02047-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 08/28/2023] [Indexed: 09/25/2023]
Abstract
INTRODUCTION Modern comprehensive instrumentations provide an unprecedented coverage of complex matrices in the form of high-dimensional, information rich data sets. OBJECTIVES In addition to the usual biomarker research that focuses on the detection of the studied condition, we aimed to define a proper strategy to conduct a correlation analysis on an untargeted colorectal cancer case study with a data set of 102 variables corresponding to metabolites obtained from serum samples analyzed with comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOF-MS). Indeed, the strength of association existing between the metabolites contains potentially valuable information about the molecular mechanisms involved and the underlying metabolic network associated to a global perturbation, at no additional analytical effort. METHODS Following Anscombe's quartet, we took particular attention to four main aspects. First, the presence of non-linear relationships through the comparison of parametric and non-parametric correlation coefficients: Pearson's r, Spearman's rho, Kendall's tau and Goodman-Kruskal's gamma. Second, the visual control of the detected associations through scatterplots and their associated regressions and angles. Third, the effect and handling of atypical samples and values. Fourth, the role of the precision of the data on the attribution of the ranks through the presence of ties. RESULTS Kendall's tau was found the method of choice for the data set at hand. Its application highlighted 17 correlations significantly altered in the active state of colorectal cancer (CRC) in comparison to matched healthy controls (HC), from which 10 were specific to this state in comparison to the remission one (R-CRC) investigated on distinct patients. 15 metabolites involved in the correlations of interest, on the 25 unique ones obtained, were annotated (Metabolomics Standards Initiative level 2). CONCLUSIONS The metabolites highlighted could be used to better understand the pathology. The systematic investigation of the methodological aspects that we expose allows to implement correlation analysis to various fields and many specific cases.
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Affiliation(s)
- Nicolas Di Giovanni
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août,B6c, B-4000, Liège, Sart Tilman, Belgium
| | - Marie-Alice Meuwis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de L'Hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Edouard Louis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de L'Hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Jean-François Focant
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août,B6c, B-4000, Liège, Sart Tilman, Belgium.
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Alhhazmi AA, Alhamawi RM, Almisned RM, Almutairi HA, Jan AA, Kurdi SM, Almutawif YA, Mohammed-Saeid W. Gut Microbial and Associated Metabolite Markers for Colorectal Cancer Diagnosis. Microorganisms 2023; 11:2037. [PMID: 37630597 PMCID: PMC10457972 DOI: 10.3390/microorganisms11082037] [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: 06/14/2023] [Revised: 07/29/2023] [Accepted: 07/30/2023] [Indexed: 08/27/2023] Open
Abstract
Globally, colorectal cancer (CRC) is the second most common cause of mortality worldwide. Considerable evidence indicates that dysbiosis of the gut microbial community and its metabolite secretions play a fundamental role in advanced adenoma (ADA) and CRC development and progression. This study is a systematic review that aims to assess the clinical association between gut microbial markers and/or gut and circulating metabolites with ADA and CRC. Five electronic databases were searched by four independent reviewers. Only controlled trials that compared ADA and/or CRC with healthy control (HC) using either untargeted (16s rRNA gene or whole genome sequencing) or targeted (gene-based real-time PCR) identification methods for gut microbiome profile, or untargeted or targeted metabolite profiling approaches from the gut or serum/plasma, were eligible. Three independent reviewers evaluated the quality of the studies using the Cochrane Handbook for Systematic Reviews of Interventions. Twenty-four studies were eligible. We identified strong evidence of two microbial markers Fusobacterium and Porphyromonas for ADA vs. CRC, and nine microbial markers Lachnospiraceae-Lachnoclostridium, Ruminococcaceae-Ruminococcus, Parvimonas spp., Parvimonas micra, Enterobacteriaceae, Fusobacterium spp., Bacteroides, Peptostreptococcus-Peptostreptococcus stomatis, Clostridia spp.-Clostridium hylemonae, Clostridium symbiosum, and Porphyromonas-Porphyromonas asaccharolytica for CRC vs. HC. The remaining metabolite marker evidence between the various groups, including ADA vs. HC, ADA vs. HC, and CRC vs. HC, was not of sufficient quality to support additional findings. The identified gut microbial markers can be used in a panel for diagnosing ADA and/or CRC. Further research in the metabolite markers area is needed to evaluate the possibility to use in diagnostic or prognostic markers for colorectal cancer.
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Affiliation(s)
- Areej A. Alhhazmi
- Medical Laboratories Technology Department, College of Applied Medical Sciences, Taibah University, P.O. Box 344, Al-Madinah Al-Munawarah 42353, Saudi Arabia; (R.M.A.); (S.M.K.); (Y.A.A.)
| | - Renad M. Alhamawi
- Medical Laboratories Technology Department, College of Applied Medical Sciences, Taibah University, P.O. Box 344, Al-Madinah Al-Munawarah 42353, Saudi Arabia; (R.M.A.); (S.M.K.); (Y.A.A.)
| | - Reema M. Almisned
- Seha Polyclinic, P.O. Box 150, Al-Madinah Al-Munawarah 41311, Saudi Arabia;
| | - Hanouf A. Almutairi
- Bioscience Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), P.O. Box 6900, Thuwal 23955, Saudi Arabia;
| | - Ahdab A. Jan
- Abdulla Fouad Medical Supplies and Services (AFMS), P.O. Box 150, Al-Madinah Al-Munawarah 21414, Saudi Arabia;
| | - Shahad M. Kurdi
- Medical Laboratories Technology Department, College of Applied Medical Sciences, Taibah University, P.O. Box 344, Al-Madinah Al-Munawarah 42353, Saudi Arabia; (R.M.A.); (S.M.K.); (Y.A.A.)
| | - Yahya A. Almutawif
- Medical Laboratories Technology Department, College of Applied Medical Sciences, Taibah University, P.O. Box 344, Al-Madinah Al-Munawarah 42353, Saudi Arabia; (R.M.A.); (S.M.K.); (Y.A.A.)
| | - Waleed Mohammed-Saeid
- Department of Pharmaceutics and Pharmaceutical Technology, College of Pharmacy, Taibah University, P.O. Box 344, Al-Madinah Al-Munawarah 42353, Saudi Arabia;
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Madrid-Gambin F, Oller S, Marco S, Pozo ÓJ, Andres-Lacueva C, Llorach R. Quantitative plasma profiling by 1H NMR-based metabolomics: impact of sample treatment. Front Mol Biosci 2023; 10:1125582. [PMID: 37333016 PMCID: PMC10273206 DOI: 10.3389/fmolb.2023.1125582] [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: 12/16/2022] [Accepted: 05/22/2023] [Indexed: 06/20/2023] Open
Abstract
Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.
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Affiliation(s)
- Francisco Madrid-Gambin
- Applied Metabolomics Research Group, IMIM—Institut Hospital del Mar d’Investigacions Mèdiques, Barcelona, Spain
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Sergio Oller
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Electronics and Biomedical Engineering, Faculty of Physics, University of Barcelona, Barcelona, Spain
| | - Santiago Marco
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Electronics and Biomedical Engineering, Faculty of Physics, University of Barcelona, Barcelona, Spain
| | - Óscar J. Pozo
- Applied Metabolomics Research Group, IMIM—Institut Hospital del Mar d’Investigacions Mèdiques, Barcelona, Spain
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Sant Coloma de Gramanet, Spain
- Food Innovation Network (XIA), Santa Coloma de Gramanet, Spain
- Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Santa Coloma de Gramanet, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Rafael Llorach
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Sant Coloma de Gramanet, Spain
- Food Innovation Network (XIA), Santa Coloma de Gramanet, Spain
- Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Santa Coloma de Gramanet, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
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Costantini S, Di Gennaro E, Capone F, De Stefano A, Nasti G, Vitagliano C, Setola SV, Tatangelo F, Delrio P, Izzo F, Avallone A, Budillon A. Plasma metabolomics, lipidomics and cytokinomics profiling predict disease recurrence in metastatic colorectal cancer patients undergoing liver resection. Front Oncol 2023; 12:1110104. [PMID: 36713567 PMCID: PMC9875807 DOI: 10.3389/fonc.2022.1110104] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 12/22/2022] [Indexed: 01/13/2023] Open
Abstract
Purpose In metastatic colorectal cancer (mCRC) patients (pts), treatment strategies integrating liver resection with induction chemotherapy offer better 5-year survival rates than chemotherapy alone. However, liver resection is a complex and costly procedure, and recurrence occurs in almost 2/3rds of pts, suggesting the need to identify those at higher risk. The aim of this work was to evaluate whether the integration of plasma metabolomics and lipidomics combined with the multiplex analysis of a large panel of plasma cytokines can be used to predict the risk of relapse and other patient outcomes after liver surgery, beyond or in combination with clinical morphovolumetric criteria. Experimental design Peripheral blood metabolomics and lipidomics were performed by 600 MHz NMR spectroscopy on plasma from 30 unresectable mCRC pts treated with bevacizumab plus oxaliplatin-based regimens within the Obelics trial (NCT01718873) and subdivided into responder (R) and non-R (NR) according to 1-year disease-free survival (DFS): ≥ 1-year (R, n = 12) and < 1-year (NR, n = 18). A large panel of cytokines, chemokines, and growth factors was evaluated on the same plasma using Luminex xMAP-based multiplex bead-based immunoassay technology. A multiple biomarkers model was built using a support vector machine (SVM) classifier. Results Sparse partial least squares discriminant analysis (sPLS-DA) and loading plots obtained by analyzing metabolomics profiles of samples collected at the time of response evaluation when resectability was established showed significantly different levels of metabolites between the two groups. Two metabolites, 3-hydroxybutyrate and histidine, significantly predicted DFS and overall survival. Lipidomics analysis confirmed clear differences between the R and NR pts, indicating a statistically significant increase in lipids (cholesterol, triglycerides and phospholipids) in NR pts, reflecting a nonspecific inflammatory response. Indeed, a significant increase in proinflammatory cytokines was demonstrated in NR pts plasma. Finally, a multiple biomarkers model based on the combination of presurgery plasma levels of 3-hydroxybutyrate, cholesterol, phospholipids, triglycerides and IL-6 was able to correctly classify patients by their DFS with good accuracy. Conclusion Overall, this exploratory study suggests the potential of these combined biomarker approaches to predict outcomes in mCRC patients who are candidates for liver metastasis resection after induction treatment for defining personalized management and treatment strategies.
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Affiliation(s)
- Susan Costantini
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Elena Di Gennaro
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Francesca Capone
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Alfonso De Stefano
- Experimental Clinical Abdominal Oncology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Guglielmo Nasti
- Innovative Therapy for Abdominal Metastases Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Carlo Vitagliano
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Sergio Venanzio Setola
- Radiology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Fabiana Tatangelo
- Pathology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Paolo Delrio
- Colorectal Oncological Surgery Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Francesco Izzo
- Hepatobiliary Surgery Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Antonio Avallone
- Experimental Clinical Abdominal Oncology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Alfredo Budillon
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy,*Correspondence: Alfredo Budillon,
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Wishart DS, Rout M, Lee BL, Berjanskii M, LeVatte M, Lipfert M. Practical Aspects of NMR-Based Metabolomics. Handb Exp Pharmacol 2023; 277:1-41. [PMID: 36271165 DOI: 10.1007/164_2022_613] [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] [Indexed: 06/16/2023]
Abstract
While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.
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Affiliation(s)
- David S Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada.
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.
| | - Manoj Rout
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Brian L Lee
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Mark Berjanskii
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Marcia LeVatte
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Matthias Lipfert
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
- Reference Standard Management & NMR QC, Lonza Group AG, Visp, Switzerland
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Zheng R, Su R, Xing F, Li Q, Liu B, Wang D, Du Y, Huang K, Yan F, Wang J, Chen H, Feng S. Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer. Anal Chem 2022; 94:11821-11830. [PMID: 35976989 DOI: 10.1021/acs.analchem.2c02072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.
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Affiliation(s)
- Ran Zheng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Rui Su
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Fan Xing
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Qing Li
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Botong Liu
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Daguang Wang
- Department of Gastric Colorectal and Anal Surgery, First Hospital of Jilin University, Changchun 130021, China
| | - Yechao Du
- Department of Gastric Colorectal and Anal Surgery, First Hospital of Jilin University, Changchun 130021, China
| | - Keke Huang
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Fei Yan
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Jianfeng Wang
- Department of Radiotherapy, China-Japan Union Hospital of Jilin University, Changchun 130021, China
| | - Huanwen Chen
- School of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Shouhua Feng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
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9
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Chen F, Dai X, Zhou CC, Li KX, Zhang YJ, Lou XY, Zhu YM, Sun YL, Peng BX, Cui W. Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma. Gut 2022; 71:1315-1325. [PMID: 34462336 PMCID: PMC9185821 DOI: 10.1136/gutjnl-2020-323476] [Citation(s) in RCA: 122] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 08/12/2021] [Indexed: 12/18/2022]
Abstract
OBJECTIVE To profile gut microbiome-associated metabolites in serum and investigate whether these metabolites could distinguish individuals with colorectal cancer (CRC) or adenoma from normal healthy individuals. DESIGN Integrated analysis of untargeted serum metabolomics by liquid chromatography-mass spectrometry and metagenome sequencing of paired faecal samples was applied to identify gut microbiome-associated metabolites with significantly altered abundance in patients with CRC and adenoma. The ability of these metabolites to discriminate between CRC and colorectal adenoma was tested by targeted metabolomic analysis. A model based on gut microbiome-associated metabolites was established and evaluated in an independent validation cohort. RESULTS In total, 885 serum metabolites were significantly altered in both CRC and adenoma, including eight gut microbiome-associated serum metabolites (GMSM panel) that were reproducibly detected by both targeted and untargeted metabolomics analysis and accurately discriminated CRC and adenoma from normal samples. A GMSM panel-based model to predict CRC and colorectal adenoma yielded an area under the curve (AUC) of 0.98 (95% CI 0.94 to 1.00) in the modelling cohort and an AUC of 0.92 (83.5% sensitivity, 84.9% specificity) in the validation cohort. The GMSM model was significantly superior to the clinical marker carcinoembryonic antigen among samples within the validation cohort (AUC 0.92 vs 0.72) and also showed promising diagnostic accuracy for adenomas (AUC=0.84) and early-stage CRC (AUC=0.93). CONCLUSION Gut microbiome reprogramming in patients with CRC is associated with alterations of the serum metabolome, and GMSMs have potential applications for CRC and adenoma detection.
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Affiliation(s)
- Feng Chen
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xudong Dai
- Dept of Clinical Research, Precogify Pharmaceutical Co, Ltd, Beijing, China
| | - Chang-Chun Zhou
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Ke-Xin Li
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yu-Juan Zhang
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiao-Ying Lou
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yuan-Min Zhu
- Department of Gastroenterology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, China
| | - Yan-Lai Sun
- Department of Gastrointestinal Cancer Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Bao-Xiang Peng
- Clinical Laboratory, Linyi Cancer Hospital, Linyi, China
| | - Wei Cui
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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10
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Zhang J, Du Y, Zhang Y, Xu Y, Fan Y, Li Y. 1H-NMR Based Metabolomics Technology Identifies Potential Serum Biomarkers of Colorectal Cancer Lung Metastasis in a Mouse Model. Cancer Manag Res 2022; 14:1457-1469. [PMID: 35444465 PMCID: PMC9015044 DOI: 10.2147/cmar.s348981] [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: 11/22/2021] [Accepted: 03/28/2022] [Indexed: 11/29/2022] Open
Abstract
Background Lung metastasis is a common metastasis site of colorectal cancer which largely reduces the quality of life and survival rates of patients. The discovery of potential novel diagnostic biomarkers is very meaningful for the early diagnosis of colorectal cancer with lung metastasis. Methods In the present study, the metabonomic profiling of serum samples of lung metastasis mice was analyzed by 1H-nuclear magnetic resonance (1H-NMR). Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to elucidate the distinguishing metabolites between different groups, and all achieved excellent separations, which indicated that metastatic mice could be differentiated from control mice based on the metabolic profiles at serum levels. Furthermore, during lung metastasis of colorectal cancer, metabolic phenotypes changed significantly, and some of metabolites were identified. Results Among these metabolites, approximately 15 were closely associated with the lung metastasis process. Pathway enrichment analysis results showed deregulation of metabolic pathways participating in the process of lung metastasis, such as synthesis and degradation of ketone bodies pathway, amino acid metabolism pathway and pyruvate metabolism pathway. Conclusion The present study demonstrated the metabolic disturbances of serum samples of mice during the lung metastasis process of colorectal cancer and provides potential diagnostic biomarkers for the disease.
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Affiliation(s)
- Junfei Zhang
- Shanxi Provincial People’s Hospital Affiliated to Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
| | - Yuanxin Du
- Department of Pharmacology, Basic Medical Sciences Center, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
| | - Yongcai Zhang
- First Hospital of Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
| | - Yanan Xu
- Medical Imaging Department of Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
| | - Yanying Fan
- Department of Pharmacology, Basic Medical Sciences Center, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
| | - Yan Li
- Department of Pharmacology, Basic Medical Sciences Center, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, People’s Republic of China
- Correspondence: Yan Li; Yanying Fan, Department of Pharmacology, Basic Medical Sciences Center, Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, 56#, Xin Jian South Road, Taiyuan, Shanxi Province, 030001, People’s Republic of China, Email ;
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11
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Metabolomic Pathway Activity with Genomic Single-Nucleotide Polymorphisms Associated with Colorectal Cancer Recurrence and 5-Year Overall Survival. J Gastrointest Cancer 2022; 54:247-258. [PMID: 35239102 DOI: 10.1007/s12029-022-00813-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Metabolomic analysis in colorectal cancer (CRC) is an emerging research area with both prognostic and therapeutic targeting potential. We aimed to identify metabolomic pathway activity prognostic for CRC recurrence and overall survival and cross-reference such metabolomic data with prognostic genomic single-nucleotide polymorphisms (SNPs). METHODS A systematic search of PubMed, Embase and Cochrane Library was performed for studies reporting prognostic metabolomic pathway activity in CRC in keeping with PRISMA guidelines. The QUADOMICS tool was used to assess study quality. MetaboAnalyst software (version4.0) was used to map metabolites that were associated with recurrence and survival in CRC to recognise metabolic pathways and identify genomic SNPs associated with CRC prognosis, referencing the following databases: Human Metabolome Database (HMDB), the Small Molecule Pathway Database (SMPDB), PubChem and Kyoto Encyclopaedia of Genes and Genomes (KEGG) Pathway Database. RESULTS Nine studies met the inclusion criteria, reporting on 1117 patients. Increased metabolic activity in the urea cycle (p = 0.002, FDR = 0.198), ammonia recycling (p = 0.004, FDR = 0.359) and glycine and serine metabolism (p = 0.004, FDR = 0.374) was prognostic of CRC recurrence. Increased activity in aspartate metabolism (p < 0.001, FDR = 0.079) and ammonia recycling (p = 0.004, FDR = 0.345) was prognostic of survival. Eight resulting SNPs were prognostic for CRC recurrence (rs2194980, rs1392880, rs2567397, rs715, rs169712, rs2300701, rs313408, rs7018169) and three for survival (rs2194980, rs169712, rs12106698) of which two overlapped with recurrence (rs2194980, rs169712). CONCLUSIONS With a caveat on study heterogeneity, specific metabolites and metabolic pathway activity appear evident in the setting of poor prognostic colorectal cancers and such metabolic signatures are associated with specific genomic SNPs.
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12
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Li Z, Deng X, Luo J, Lei Y, Jin X, Zhu J, Lv G. Metabolomic Comparison of Patients With Colorectal Cancer at Different Anticancer Treatment Stages. Front Oncol 2022; 11:574318. [PMID: 35186705 PMCID: PMC8855116 DOI: 10.3389/fonc.2021.574318] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 11/05/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The difficulties of early diagnosis of colorectal cancer (CRC) result in a high mortality rate. The ability to predict the response of a patient to surgical resection or chemotherapy may be of great value for clinicians when planning CRC treatments. Metabolomics is an emerging tool for biomarker discovery in cancer research. Previous reports have indicated that the metabolic profile of individuals can be significantly altered between CRC patients and healthy controls. However, metabolic changes in CRC patients at different treatment stages have not been explored. METHODS To this end, we performed nuclear magnetic resonance (NMR)-based metabolomic analysis to determine metabolite aberrations in CRC patients before and after surgical resection or chemotherapy. In general, a total of 106 urine samples from four clinical groups, namely, healthy volunteers (n = 31), presurgery CRC patients (n = 25), postsurgery CRC patients (n = 25), and postchemotherapy CRC patients (n = 25), were collected and subjected to further analysis. RESULTS In the present study, we identified five candidate metabolites, namely, N-phenylacetylglycine, succinate, 4-hydroxyphenylacetate, acetate, and arabinose, in CRC patients compared with healthy individuals, three of which were reported for the first time. Furthermore, approximately ten metabolites were uniquely identified at each stage of CRC treatment, serving as good candidates for biomarker panel selection. CONCLUSION In summary, these potential metabolite candidates may provide promising early diagnostic and monitoring approaches for CRC patients at different anticancer treatment stages.
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Affiliation(s)
| | | | | | | | | | | | - Guoqing Lv
- Department of Gastroinerstinal Surgery, Peking University Shenzhen Hospital, Shenzhen, China
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13
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Tevini J, Eder SK, Huber-Schönauer U, Niederseer D, Strebinger G, Gostner JM, Aigner E, Datz C, Felder TK. Changing Metabolic Patterns along the Colorectal Adenoma–Carcinoma Sequence. J Clin Med 2022; 11:jcm11030721. [PMID: 35160173 PMCID: PMC8836789 DOI: 10.3390/jcm11030721] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/18/2022] [Accepted: 01/27/2022] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) is a major public health burden and one of the leading causes of cancer-related deaths worldwide. Screening programs facilitate early diagnosis and can help to reduce poor outcomes. Serum metabolomics can extract vital molecular information that may increase the sensitivity and specificity of colonoscopy in combination with histopathological examination. The present study identifies serum metabolite patterns of treatment-naïve patients, diagnosed with either advanced adenoma (AA) or CRC in colonoscopy screenings, in the framework of the SAKKOPI (Salzburg Colon Cancer Prevention Initiative) program. We used a targeted flow injection analysis and liquid chromatography-tandem mass spectrometry metabolomics approach (FIA- and LC-MS/MS) to characterise the serum metabolomes of an initial screening cohort and two validation cohorts (in total 66 CRC, 76 AA and 93 controls). The lipidome was significantly perturbed, with a proportion of lipid species being downregulated in CRC patients, as compared to AA and controls. The predominant alterations observed were in the levels of lyso-lipids, glycerophosphocholines and acylcarnitines, but additionally, variations in the quantity of hydroxylated sphingolipids could be detected. Changed amino acid metabolism was restricted mainly to metabolites of the arginine/dimethylarginine/NO synthase pathway. The identified metabolic divergences observed in CRC set the foundation for mechanistic studies to characterise biochemical pathways that become deregulated during progression through the adenoma to carcinoma sequence and highlight the key importance of lipid metabolites. Biomarkers related to these pathways could improve the sensitivity and specificity of diagnosis, as well as the monitoring of therapies.
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Affiliation(s)
- Julia Tevini
- Department of Laboratory Medicine, Paracelsus Medical University, 5020 Salzburg, Austria;
| | - Sebastian K. Eder
- First Department of Medicine, Paracelsus Medical University, 5020 Salzburg, Austria; (S.K.E.); (E.A.)
- Department of Pediatrics and Adolescent Medicine, St. Anna Children’s Hospital, Medical University of Vienna, 1090 Vienna, Austria
| | - Ursula Huber-Schönauer
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
| | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland;
| | - Georg Strebinger
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
| | - Johanna M. Gostner
- Institute of Medical Biochemistry, Innsbruck Medical University, 6020 Innsbruck, Austria;
| | - Elmar Aigner
- First Department of Medicine, Paracelsus Medical University, 5020 Salzburg, Austria; (S.K.E.); (E.A.)
| | - Christian Datz
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
- Correspondence: (C.D.); (T.K.F.); Tel.: +43-5-7255-58126 (T.K.F.)
| | - Thomas K. Felder
- Department of Laboratory Medicine, Paracelsus Medical University, 5020 Salzburg, Austria;
- Correspondence: (C.D.); (T.K.F.); Tel.: +43-5-7255-58126 (T.K.F.)
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14
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Rattner JI, Kopciuk KA, Vogel HJ, Tang PA, Shapiro JD, Tu D, Jonker DJ, Siu LL, O'Callaghan CJ, Bathe OF. Early detection of treatment futility in patients with metastatic colorectal cancer. Oncotarget 2022; 13:61-72. [PMID: 35028011 PMCID: PMC8746015 DOI: 10.18632/oncotarget.28165] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 12/10/2021] [Indexed: 11/25/2022] Open
Abstract
PURPOSE Chemotherapy options for treating CRC have rapidly expanded in recent years, and few have predictive biomarkers. Oncologists are challenged with evidence-based selection of treatments, and response is evaluated retrospectively based on serial imaging beginning after 2-3 months. As a result, cumulative toxicities may appear in patients who will not benefit. Early recognition of non-benefit would reduce cumulative toxicities. Our objective was to determine treatment-related changes in the circulating metabolome corresponding to treatment futility. METHODS Metabolomic studies were performed on serial plasma samples from patients with CRC in a randomized controlled trial of cetuximab vs. cetuximab + brivanib (N = 188). GC-MS quantified named 94 metabolites and concentrations were evaluated at baseline, Weeks 1, 4 and 12 after treatment initiation. In a discovery cohort (N = 68), a model distinguishing changes in metabolites associated with radiographic disease progression and response was generated using OPLS-DA. A cohort of 120 patients was used for validation of the model. RESULTS By one week after treatment, a stable model of 21 metabolites could distinguish between progression and partial response (R2Y = 0.859; Q2Y = 0.605; P = 5e-4). In the validation cohort, patients with the biomarker had a significantly shorter OS (P < 0.0001). In a separate cohort of patients with HCC on axitinib, appearance of the biomarker also signified a shorter PFS (1.7 months vs. 9.2 months, P = 0.001). CONCLUSION We have identified changes in the metabolome that appear within 1 week of starting treatment associated with treatment futility. The novel approach described is applicable to future efforts in developing a biomarker for early assessment of treatment efficacy.
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Affiliation(s)
- Jodi I Rattner
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Karen A Kopciuk
- Department of Mathematics and Statistics, Faculty of Science, University of Calgary, Calgary, Canada
| | - Hans J Vogel
- Department Biological Sciences, Faculty of Science, University of Calgary, Calgary, Canada
| | - Patricia A Tang
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Department of Surgery and Oncology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Jeremy D Shapiro
- Department of Medical Oncology, Monash University, Melbourne, Victoria, Australia
| | - Dongsheng Tu
- Department of Community Health and Epidemiology, Queens University, Kingston, Canada
| | - Derek J Jonker
- Division of Medical Oncology, Ottawa Hospital Cancer Centre, Ottawa, Canada
| | - Lillian L Siu
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada
| | - Chris J O'Callaghan
- Department of Community Health and Epidemiology, Queens University, Kingston, Canada
| | - Oliver F Bathe
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Department of Surgery and Oncology, Cumming School of Medicine, University of Calgary, Calgary, Canada
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15
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Salmerón AM, Tristán AI, Abreu AC, Fernández I. Serum Colorectal Cancer Biomarkers Unraveled by NMR Metabolomics: Past, Present, and Future. Anal Chem 2022; 94:417-430. [PMID: 34806875 PMCID: PMC8756394 DOI: 10.1021/acs.analchem.1c04360] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Ana M. Salmerón
- Department of Chemistry and
Physics, Research Centre CIAIMBITAL, University
of Almería, Ctra. Sacramento, s/n, 04120 Almería, Spain
| | - Ana I. Tristán
- Department of Chemistry and
Physics, Research Centre CIAIMBITAL, University
of Almería, Ctra. Sacramento, s/n, 04120 Almería, Spain
| | - Ana C. Abreu
- Department of Chemistry and
Physics, Research Centre CIAIMBITAL, University
of Almería, Ctra. Sacramento, s/n, 04120 Almería, Spain
| | - Ignacio Fernández
- Department of Chemistry and
Physics, Research Centre CIAIMBITAL, University
of Almería, Ctra. Sacramento, s/n, 04120 Almería, Spain
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16
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Exploring Serum NMR-Based Metabolomic Fingerprint of Colorectal Cancer Patients: Effects of Surgery and Possible Associations with Cancer Relapse. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app112311120] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background: Colorectal cancer (CRC) is the fourth most commonly diagnosed and third most deadly cancer worldwide. Surgery is the main treatment option for early disease; however, a relevant proportion of CRC patients relapse. Here, variations among preoperative and postoperative serum metabolomic fingerprint of CRC patients were studied, and possible associations between metabolic variations and cancer relapse were explored. Methods: A total of 41 patients with stage I-III CRC, planned for radical resection, were enrolled. Serum samples, collected preoperatively (t0) and 4–6 weeks after surgery before the start of any treatment (t1), were analyzed via NMR spectroscopy. NMR data were analyzed using multivariate and univariate statistical approaches. Results: Serum metabolomic fingerprints show differential clustering between t0 and t1 (82–85% accuracy). Pyruvate, HDL-related parameters, acetone, and 3-hydroxybutyrate appear to be the major players in this discrimination. Eight out of the 41 CRC patients enrolled developed cancer relapse. Postoperative, relapsed patients show an increase of pyruvate and HDL-related parameters, and a decrease of Apo-A1 Apo-B100 ratio and VLDL-related parameters. Conclusions: Surgery significantly alters the metabolomic fingerprint of CRC patients. Some metabolic changes seem to be associated with the development of cancer relapse. These data, if validated in a larger cohort, open new possibilities for risk stratification in patients with early-stage CRC.
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17
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Di Donato S, Vignoli A, Biagioni C, Malorni L, Mori E, Tenori L, Calamai V, Parnofiello A, Di Pierro G, Migliaccio I, Cantafio S, Baraghini M, Mottino G, Becheri D, Del Monte F, Miceli E, McCartney A, Di Leo A, Luchinat C, Biganzoli L. A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting. Cancers (Basel) 2021; 13:cancers13112762. [PMID: 34199435 PMCID: PMC8199587 DOI: 10.3390/cancers13112762] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/14/2021] [Accepted: 05/29/2021] [Indexed: 12/26/2022] Open
Abstract
Simple Summary Around 30–40% of patients with early stage colorectal cancer (eCRC) experience relapse after surgery. Current recommendations for adjuvant therapy are based on suboptimal risk-stratification tools. In elderly patients, risk of relapse assessment is particularly important to ultimately avoid unnecessary chemotherapy-related toxicity in this frailer population. Serum metabolomics via NMR spectroscopy may improve risk stratification by identifying patients with residual micrometastases after surgery and thus at higher risk of relapse. We evaluated the serum metabolomic fingerprints of 94 elderly patients with eCRC (65 relapse free and 29 relapsed), and of 75 elderly patients with metastatic disease. Metabolomics efficiently discriminated patients with relapse-free eCRC from those with metastatic disease, correctly predicting relapse in 69% of relapsed eCRC patients. The metabolomic score was strongly and independently associated with prognosis. Our data suggest metabolomics as a valid addition to standard tools to refine risk stratification for eCRC and warrant further investigation. Abstract Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.
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Affiliation(s)
- Samantha Di Donato
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
- Correspondence: ; Tel.: +39-057-480-2520
| | - Alessia Vignoli
- Magnetic Resonance Center, University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Chiara Biagioni
- Bioinformatics Unit, Medical Oncology Department, New Hospital of Prato S. Stefano, 59100 Prato, Italy;
| | - Luca Malorni
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
- “Sandro Pitigliani” Translational Research Unit, New Hospital of Prato, Stefano, 59100 Prato, Italy;
| | - Elena Mori
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Leonardo Tenori
- Magnetic Resonance Center, University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Vanessa Calamai
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Annamaria Parnofiello
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
- Department of Medicine (DAME), University of Udine, 33100 Udine, Italy
| | - Giulia Di Pierro
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Ilenia Migliaccio
- “Sandro Pitigliani” Translational Research Unit, New Hospital of Prato, Stefano, 59100 Prato, Italy;
| | - Stefano Cantafio
- Department of Surgery, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (S.C.); (M.B.)
| | - Maddalena Baraghini
- Department of Surgery, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (S.C.); (M.B.)
| | - Giuseppe Mottino
- Department of Geriatrics, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (G.M.); (D.B.)
| | - Dimitri Becheri
- Department of Geriatrics, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (G.M.); (D.B.)
| | - Francesca Del Monte
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Elisangela Miceli
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Amelia McCartney
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
- School of Clinical Sciences, Monash University, 3168 Clayton, Australia
| | - Angelo Di Leo
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
| | - Claudio Luchinat
- Magnetic Resonance Center, University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
| | - Laura Biganzoli
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (L.M.); (E.M.); (V.C.); (A.P.); (G.D.P.); (F.D.M.); (E.M.); (A.M.); (A.D.L.); (L.B.)
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Mika A, Duzowska K, Halinski LP, Pakiet A, Czumaj A, Rostkowska O, Dobrzycka M, Kobiela J, Sledzinski T. Rearrangements of Blood and Tissue Fatty Acid Profile in Colorectal Cancer - Molecular Mechanism and Diagnostic Potential. Front Oncol 2021; 11:689701. [PMID: 34123858 PMCID: PMC8190393 DOI: 10.3389/fonc.2021.689701] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/04/2021] [Indexed: 12/14/2022] Open
Abstract
Colorectal cancer (CRC) is often diagnosed at an advanced stage due to the invasiveness of colonoscopy; thus, non-invasive CRC diagnostics are desirable. CRC is associated with lipid alterations. We aimed to verify whether fatty acid (FA) profiles in CRC patients may serve as a potential diagnostic tool for CRC diagnosis. FA profiles were assayed by GC-MS in cancer tissue, paired normal mucosa and serum from CRC patients and healthy controls. The levels of very long FAs – VLCFAs (26:0, 28:0 and 26:1) were the most highly increased FAs in cancer tissue compared to normal colon mucosa. Moreover, these FA were present in serum of CRC patients, they were absent in the serum of healthy subjects, or present in only trace amounts. To verify if cancer cells are the source of small amounts of these VLCFAs in the serum of patients we performed experiment in HT-29 CRC cells, which proved that CRC cells can produce and release VLCFAs into the blood. Most importantly, we defined a panel of FAs that may be assayed in a single analysis that definitely distinguishes CRC patients and healthy subjects, which was confirmed by PLS-DA and multivariate ROC analysis (AUC = 0.985). This study shows that selected FA panel may serve as a diagnostic marker for CRC.
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Affiliation(s)
- Adriana Mika
- Department of Pharmaceutical Biochemistry, Faculty of Pharmacy, Medical University of Gdansk, Gdansk, Poland.,Department of Environmental Analysis, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Katarzyna Duzowska
- Department of Pharmaceutical Biochemistry, Faculty of Pharmacy, Medical University of Gdansk, Gdansk, Poland
| | - Lukasz P Halinski
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Alicja Pakiet
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Aleksandra Czumaj
- Department of Pharmaceutical Biochemistry, Faculty of Pharmacy, Medical University of Gdansk, Gdansk, Poland
| | - Olga Rostkowska
- Department of General, Endocrine and Transplant Surgery, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
| | - Malgorzata Dobrzycka
- Department of General, Endocrine and Transplant Surgery, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
| | - Jaroslaw Kobiela
- Department of General, Endocrine and Transplant Surgery, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
| | - Tomasz Sledzinski
- Department of Pharmaceutical Biochemistry, Faculty of Pharmacy, Medical University of Gdansk, Gdansk, Poland
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Abstract
Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.
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Răchieriu C, Eniu DT, Moiş E, Graur F, Socaciu C, Socaciu MA, Hajjar NA. Lipidomic Signatures for Colorectal Cancer Diagnosis and Progression Using UPLC-QTOF-ESI +MS. Biomolecules 2021; 11:biom11030417. [PMID: 33799830 PMCID: PMC8035671 DOI: 10.3390/biom11030417] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 03/02/2021] [Accepted: 03/08/2021] [Indexed: 12/15/2022] Open
Abstract
Metabolomics coupled with bioinformatics may identify relevant biomolecules such as putative biomarkers of specific metabolic pathways related to colorectal diagnosis, classification and prognosis. This study performed an integrated metabolomic profiling of blood serum from 25 colorectal cancer (CRC) cases previously classified (Stage I to IV) compared with 16 controls (disease-free, non-CRC patients), using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI+ MS). More than 400 metabolites were separated and identified, then all data were processed by the advanced Metaboanalyst 5.0 online software, using multi- and univariate analysis, including specificity/sensitivity relationships (area under the curve (AUC) values), enrichment and pathway analysis, identifying the specific pathways affected by cancer progression in the different stages. Several sub-classes of lipids including phosphatidylglycerols (phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and PAs), fatty acids and sterol esters as well as ceramides confirmed the “lipogenic phenotype” specific to CRC development, namely the upregulated lipogenesis associated with tumor progression. Both multivariate and univariate bioinformatics confirmed the relevance of some putative lipid biomarkers to be responsible for the altered metabolic pathways in colorectal cancer.
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Affiliation(s)
- Claudiu Răchieriu
- Surgery Department, County Hospital Alba, 510118 Alba Iulia, Romania;
- Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400015 Cluj-Napoca, Romania; (E.M.); (F.G.); (N.A.H.)
| | - Dan Tudor Eniu
- Oncology Department, Iuliu Hațieganu University of Medicine and Pharmacy, 400015 Cluj-Napoca, Romania;
| | - Emil Moiş
- Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400015 Cluj-Napoca, Romania; (E.M.); (F.G.); (N.A.H.)
| | - Florin Graur
- Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400015 Cluj-Napoca, Romania; (E.M.); (F.G.); (N.A.H.)
| | - Carmen Socaciu
- University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania
- Research Center for Applied Biotechnology in Diagnosis and Molecular Therapy, 400478 Cluj-Napoca, Romania
- Correspondence: (C.S.); (M.A.S.)
| | - Mihai Adrian Socaciu
- Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400015 Cluj-Napoca, Romania; (E.M.); (F.G.); (N.A.H.)
- Correspondence: (C.S.); (M.A.S.)
| | - Nadim Al Hajjar
- Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400015 Cluj-Napoca, Romania; (E.M.); (F.G.); (N.A.H.)
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21
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Di Giovanni N, Meuwis MA, Louis E, Focant JF. Specificity of metabolic colorectal cancer biomarkers in serum through effect size. Metabolomics 2020; 16:88. [PMID: 32789702 DOI: 10.1007/s11306-020-01707-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 07/30/2020] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Colorectal cancer is one of the most diagnosed cancers, leading to numerous deaths. In addition to existing screening methods, metabolic profiling could help both to diagnose and to understand the various states of the disease. OBJECTIVES Find specific candidate biomarkers (CB) in serum of patients with colorectal cancer (CRC), in comparison to the situation after remission (R-CRC), evaluated on distinct patients. METHODS All serum samples were analyzed using comprehensive two-dimensional gas chromatography (GC × GC) coupled to high resolution time of flight mass spectrometry (TOF-MS) through an optimized and validated untargeted analytical method regulated by a quality control (QC) system. First, we used a specific multi-approaches data (pre)processing workflow to highlight, annotate and assess the performances of the most altered metabolites between CRC patients (n = 18) and healthy control samples (HC, n = 19) specifically matched for age and gender, two of the most influential confounding factors. On the contrary, due to the difficulty to control for all clinical and demographic traits when sampling small cohorts, the samples from patients in remission (n = 17) were not matched. Because of the consequent risk of bias, the usual null hypothesis significance tests (NHST) could not be applied reliably. Therefore, we compared the R-CRC samples to another specifically matched group of healthy controls (R-HC, n = 17), and used this comparison to indirectly address the difference between patients with colorectal cancer and patients in remission through a measure called effect size (ES) whose methodological aspects were investigated. RESULTS 24 candidate biomarkers were found significantly altered and able to discriminate the CRC and HC samples efficiently (Receiver Operating Characteristic (ROC) area under the curve (AUC) of 0.86, sensitivity and specificity of 0.72 and 0.78). 10 of those were found to have signals close to healthy levels in the R-CRC samples and were therefore specific to colorectal cancer. In the point-biserial case studied here, r-like (strength of association) and d-like (standardized mean difference) ES were directly convertible and only linear and rank-based ES were different. We therefore used and recommend Hedges' g, Spearman's rho and Kendall's tau, along with an unstandardized ES. The confidence intervals, that quantify the uncertainty of the measure, were well represented through scatterplots and distribution curves. CONCLUSION The candidate biomarkers found, along with their specificity, could help for the detection of colorectal cancer, the diagnosis of remission, and for the understanding of its pathophysiology, after proper validation on independent cohorts. The effect size, here applied on a MS global profiling data set, is an ideal complement to NHST and a useful tool to compare and combine distinct cohorts, within a study as well as between studies (meta-analysis).
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Affiliation(s)
- Nicolas Di Giovanni
- Department of Chemistry, Organic & Biological Analytical Chemistry Group, University of Liège, Allée du 6 août, B6c, B-4000, Liège (Sart Tilman), Belgium
| | - Marie-Alice Meuwis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, University of Liège, Quartier Hôpital, Avenue de l'hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Edouard Louis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, University of Liège, Quartier Hôpital, Avenue de l'hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Jean-François Focant
- Department of Chemistry, Organic & Biological Analytical Chemistry Group, University of Liège, Allée du 6 août, B6c, B-4000, Liège (Sart Tilman), Belgium.
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22
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Discovery and predictive modeling of urine microbiome, metabolite and cytokine biomarkers in hospitalized patients with community acquired pneumonia. Sci Rep 2020; 10:13418. [PMID: 32770049 PMCID: PMC7414893 DOI: 10.1038/s41598-020-70461-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 06/26/2020] [Indexed: 02/07/2023] Open
Abstract
Pneumonia is the leading cause of infectious related death costing 12 billion dollars annually in the United States alone. Despite improvements in clinical care, total mortality remains around 4%, with inpatient mortality reaching 5–10%. For unknown reasons, mortality risk remains high even after hospital discharge and there is a need to identify those patients most at risk. Also of importance, clinical symptoms alone do not distinguish viral from bacterial infection which may delay appropriate treatment and may contribute to short-term and long-term mortality. Biomarkers have the potential to provide point of care diagnosis, identify high-risk patients, and increase our understanding of the biology of disease. However, there have been mixed results on the diagnostic performance of many of the analytes tested to date. Urine represents a largely untapped source for biomarker discovery and is highly accessible. To test this hypothesis, we collected urine from hospitalized patients with community-acquired pneumonia (CAP) and performed a comprehensive screen for urinary tract microbiota signatures, metabolite, and cytokine profiles. CAP patients were diagnosed with influenza or bacterial (Streptococcus pneumoniae and Staphylococcus aureus) etiologies and compared with healthy volunteers. Microbiome signatures showed marked shifts in taxonomic levels in patients with bacterial etiology versus influenza and CAP versus normal. Predictive modeling of 291 microbial and metabolite values achieved a + 90% accuracy with LASSO in predicting specific pneumonia etiology. This study demonstrates that urine from patients hospitalized with pneumonia may serve as a reliable and accessible sample to evaluate biomarkers that may diagnose etiology and predict clinical outcomes.
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23
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Yang Y, Zhang F, Gao S, Wang Z, Li M, Wei H, Zhong R, Chen W. Simultaneous Determination of 34 Amino Acids in Tumor Tissues from Colorectal Cancer Patients Based on the Targeted UHPLC-MS/MS Method. JOURNAL OF ANALYTICAL METHODS IN CHEMISTRY 2020; 2020:4641709. [PMID: 32802550 PMCID: PMC7416278 DOI: 10.1155/2020/4641709] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 04/22/2020] [Accepted: 05/01/2020] [Indexed: 06/11/2023]
Abstract
A targeted ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was established and validated for the simultaneous determination of 34 amino acids in tissue samples from colorectal cancer (CRC) patients. The chromatographic separation was achieved on an Agilent ZORBAX SB-C18 column (3.0 × 150 mm, 5 μm) with a binary gradient elution system (A, 0.02% heptafluorobutyric acid and 0.2% formic acid in water, v/v; B, methanol). The run time was 10 min. The multiple reaction monitoring mode was chosen with an electrospray ionization source operating in the positive ionization mode for data acquisition. The linear correlation coefficients were >0.99 for all the analytes in their corresponding calibration ranges. The sample was pretreated based on tissue homogenate and protein precipitation with a 100 mg aliquot sample. The average recovery and matrix effect for 34 amino acids and 3 internal standards were 39.00%∼146.95% and 49.45%∼173.63%, respectively. The intra- and interday accuracy for all the analytes ranged from -13.52% to 14.21% (RSD ≤8.57%) and from -14.52% to 12.59% (RSD ≤10.31%), respectively. Deviations of stability under different conditions were within ±15% for all the analytes. This method was applied to simultaneous quantification of 34 amino acids in tissue samples from 94 CRC patients.
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Affiliation(s)
- Yang Yang
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
- Department of Pharmacy, The 71st Group Army Hospital of CPLA Army, The Affiliated Huaihai Hospital of Xuzhou Medical University, Xuzhou 221004, China
- Department of Laboratory Diagnostics, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Feng Zhang
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Shouhong Gao
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Zhipeng Wang
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Mingming Li
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Hua Wei
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Renqian Zhong
- Department of Laboratory Diagnostics, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
| | - Wansheng Chen
- Department of Pharmacy, Changzheng Hospital, The Second Military Medical University of CPLA, Shanghai 200003, China
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Geijsen AJ, van Roekel EH, van Duijnhoven FJ, Achaintre D, Bachleitner‐Hofmann T, Baierl A, Bergmann MM, Boehm J, Bours MJ, Brenner H, Breukink SO, Brezina S, Chang‐Claude J, Herpel E, de Wilt JH, Gicquiau A, Gigic B, Gumpenberger T, Hansson BM, Hoffmeister M, Holowatyj AN, Karner‐Hanusch J, Keski‐Rahkonen P, Keulen ET, Koole JL, Leeb G, Ose J, Schirmacher P, Schneider MA, Schrotz‐King P, Stift A, Ulvik A, Vogelaar FJ, Wesselink E, van Zutphen M, Gsur A, Habermann N, Kampman E, Scalbert A, Ueland PM, Ulrich AB, Ulrich CM, Weijenberg MP, Kok DE. Plasma metabolites associated with colorectal cancer stage: Findings from an international consortium. Int J Cancer 2020; 146:3256-3266. [PMID: 31495913 PMCID: PMC7216900 DOI: 10.1002/ijc.32666] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 07/06/2019] [Accepted: 07/26/2019] [Indexed: 12/12/2022]
Abstract
Colorectal cancer is the second most common cause of cancer-related death globally, with marked differences in prognosis by disease stage at diagnosis. We studied circulating metabolites in relation to disease stage to improve the understanding of metabolic pathways related to colorectal cancer progression. We investigated plasma concentrations of 130 metabolites among 744 Stages I-IV colorectal cancer patients from ongoing cohort studies. Plasma samples, collected at diagnosis, were analyzed with liquid chromatography-mass spectrometry using the Biocrates AbsoluteIDQ™ p180 kit. We assessed associations between metabolite concentrations and stage using multinomial and multivariable logistic regression models. Analyses were adjusted for potential confounders as well as multiple testing using false discovery rate (FDR) correction. Patients presented with 23, 28, 39 and 10% of Stages I-IV disease, respectively. Concentrations of sphingomyelin C26:0 were lower in Stage III patients compared to Stage I patients (pFDR < 0.05). Concentrations of sphingomyelin C18:0 and phosphatidylcholine (diacyl) C32:0 were statistically significantly higher, while citrulline, histidine, phosphatidylcholine (diacyl) C34:4, phosphatidylcholine (acyl-alkyl) C40:1 and lysophosphatidylcholines (acyl) C16:0 and C17:0 concentrations were lower in Stage IV compared to Stage I patients (pFDR < 0.05). Our results suggest that metabolic pathways involving among others citrulline and histidine, implicated previously in colorectal cancer development, may also be linked to colorectal cancer progression.
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Affiliation(s)
- Anne J.M.R. Geijsen
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
| | - Eline H. van Roekel
- Department of Epidemiology, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | | | - David Achaintre
- Biomarkers GroupInternational Agency for Research on CancerLyonFrance
| | | | - Andreas Baierl
- Department of Statistics and Operations ResearchUniversity of ViennaViennaAustria
| | | | - Jürgen Boehm
- Huntsman Cancer InstituteSalt Lake CityUT
- Department of Population Health SciencesUniversity of UtahSalt Lake CityUT
| | - Martijn J.L. Bours
- Department of Epidemiology, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Hermann Brenner
- Division of Preventive OncologyNational Center for Tumor Diseases and German Cancer Research CenterHeidelbergGermany
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
- German Cancer Consortium (DKTK)German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Stéphanie O. Breukink
- Department of Surgery, GROW School for Oncology and Development BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Stefanie Brezina
- Institute of Cancer Research, Department of Medicine IMedical University of ViennaViennaAustria
| | - Jenny Chang‐Claude
- Division of Cancer EpidemiologyGerman Cancer Research CenterHeidelbergGermany
| | - Esther Herpel
- Institute of PathologyUniversity of HeidelbergHeidelbergGermany
| | - Johannes H.W. de Wilt
- Department of Surgery, Division of Surgical Oncology and Gastrointestinal SurgeryRadboud University Medical CenterNijmegenThe Netherlands
| | - Audrey Gicquiau
- Biomarkers GroupInternational Agency for Research on CancerLyonFrance
| | - Biljana Gigic
- Department of General, Visceral and Transplantation SurgeryUniversity of HeidelbergHeidelbergGermany
| | - Tanja Gumpenberger
- Institute of Cancer Research, Department of Medicine IMedical University of ViennaViennaAustria
| | - Bibi M.E. Hansson
- Department of SurgeryCanisius‐Wilhelmina HospitalNijmegenThe Netherlands
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Andreana N. Holowatyj
- Huntsman Cancer InstituteSalt Lake CityUT
- Department of Population Health SciencesUniversity of UtahSalt Lake CityUT
| | | | | | - Eric T.P. Keulen
- Department of Internal Medicine and GastroenterologyZuyderland Medical CenterSittardThe Netherlands
| | - Janna L. Koole
- Department of Epidemiology, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | | | - Jennifer Ose
- Huntsman Cancer InstituteSalt Lake CityUT
- Department of Population Health SciencesUniversity of UtahSalt Lake CityUT
| | | | - Martin A. Schneider
- Department of General, Visceral and Transplantation SurgeryUniversity of HeidelbergHeidelbergGermany
| | - Petra Schrotz‐King
- Division of Preventive OncologyNational Center for Tumor Diseases and German Cancer Research CenterHeidelbergGermany
| | - Anton Stift
- Department of SurgeryMedical University ViennaViennaAustria
| | | | | | - Evertine Wesselink
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
| | - Moniek van Zutphen
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
| | - Andrea Gsur
- Institute of Cancer Research, Department of Medicine IMedical University of ViennaViennaAustria
| | - Nina Habermann
- Division of Preventive OncologyNational Center for Tumor Diseases and German Cancer Research CenterHeidelbergGermany
- Genome BiologyEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Ellen Kampman
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
| | - Augustin Scalbert
- Biomarkers GroupInternational Agency for Research on CancerLyonFrance
| | | | - Alexis B. Ulrich
- Department of General, Visceral and Transplantation SurgeryUniversity of HeidelbergHeidelbergGermany
| | - Cornelia M. Ulrich
- Huntsman Cancer InstituteSalt Lake CityUT
- Department of Population Health SciencesUniversity of UtahSalt Lake CityUT
| | - Matty P. Weijenberg
- Department of Epidemiology, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Dieuwertje E. Kok
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
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Hassan HA, Ammar NM, Serag A, Shaker OG, El Gendy AN, Abdel-Hamid AHZ. Metabolomics driven analysis of obesity-linked colorectal cancer patients via GC-MS and chemometrics: A pilot study. Microchem J 2020. [DOI: 10.1016/j.microc.2020.104742] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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26
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Nannini G, Meoni G, Amedei A, Tenori L. Metabolomics profile in gastrointestinal cancers: Update and future perspectives. World J Gastroenterol 2020; 26:2514-2532. [PMID: 32523308 PMCID: PMC7265149 DOI: 10.3748/wjg.v26.i20.2514] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/11/2020] [Accepted: 05/15/2020] [Indexed: 02/06/2023] Open
Abstract
Despite recent progress in diagnosis and therapy, gastrointestinal (GI) cancers remain one of the most important causes of death with a poor prognosis due to late diagnosis. Serum tumor markers and detection of occult blood in the stool are the current tests used in the clinic of GI cancers; however, these tests are not useful as diagnostic screening since they have low specificity and low sensitivity. Considering that one of the hallmarks of cancer is dysregulated metabolism and metabolomics is an optimal approach to illustrate the metabolic mechanisms that belong to living systems, is now clear that this -omics could open a new way to study cancer. In the last years, nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for diseases' diagnosis nevertheless a few studies focus on the NMR capability to find new biomarkers for early diagnosis of GI cancers. For these reasons in this review, we will give an update on the status of NMR metabolomic studies for the diagnosis and development of GI cancers using biological fluids.
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Affiliation(s)
- Giulia Nannini
- Department of Experimental and Clinical Medicine, University of Florence, Florence 50134, Italy
| | - Gaia Meoni
- Giotto Biotech Srl, and CERM (University of Florence), Florence 50019, Italy
| | - Amedeo Amedei
- Department of Experimental and Clinical Medicine, University of Florence, Florence 50134, Italy
- SOD of Interdisciplinary Internal Medicine, Azienda Ospedaliera Universitaria Careggi, Florence 50134, Italy
| | - Leonardo Tenori
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine, Florence 50019, Italy
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27
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Mu C, Corley MJ, Lee RWY, Wong M, Pang A, Arakaki G, Miyamoto R, Rho JM, Mickiewicz B, Dowlatabadi R, Vogel HJ, Korchemagin Y, Shearer J. Metabolic Framework for the Improvement of Autism Spectrum Disorders by a Modified Ketogenic Diet: A Pilot Study. J Proteome Res 2019; 19:382-390. [PMID: 31696714 DOI: 10.1021/acs.jproteome.9b00581] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The ketogenic diet (KD) can improve the core features of autism spectrum disorders (ASD) in some children, but the effects on the overall metabolism remain unclear. This pilot study investigated the behavioral parameters in relation to blood metabolites and trace elements in a cohort of 10 typically developed controls (TC) and 17 children with ASD at baseline and following 3 months of treatment with a modified KD regimen. A nontargeted, multiplatform metabolomic approach was employed, including gas chromatography-mass spectrometry, 1H nuclear magnetic resonance spectroscopy, and inductively coupled plasma-mass spectrometry. The associations among plasma metabolites, trace elements, and behavior scores were investigated. Employing a combination of metabolomic platforms, 118 named metabolites and 73 trace elements were assessed. Relative to TC, a combination of glutamate, galactonate, and glycerol discriminated ASD with 88% accuracy. ASD had higher concentrations of galactose intermediates, gut microbe-derived trimethylamine N-oxide and N-acetylserotonin, and lower concentrations of 3-hydroxybutyrate and selenium at baseline. Following 3 months of KD intervention, the levels of circulating ketones and acetylcarnitine were increased. KD restored lower selenium levels in ASD to that of controls, and correlation analysis identified a novel negative correlation between the changes in selenium and behavior scores. Based on the different behavior responses to KD, we found that high responders had greater concentrations of 3-hydroxybutyrate and ornithine, with lower galactose. These findings enhance our current understanding of the metabolic derangements present in ASD and may be of utility in predicting favorable responses to KD intervention.
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Affiliation(s)
| | - Michael J Corley
- John A. Burns School of Medicine, Department of Native Hawaiian Health , University of Hawaii , Honolulu , Hawaii 96822 , United States
| | - Ryan W Y Lee
- Shriners Hospitals for Children , Honolulu , Hawaii 96826 , United States
| | - Miki Wong
- Shriners Hospitals for Children , Honolulu , Hawaii 96826 , United States
| | - Alina Pang
- John A. Burns School of Medicine, Department of Native Hawaiian Health , University of Hawaii , Honolulu , Hawaii 96822 , United States
| | - Gaye Arakaki
- Shriners Hospitals for Children , Honolulu , Hawaii 96826 , United States
| | - Rob Miyamoto
- Shriners Hospitals for Children , Honolulu , Hawaii 96826 , United States
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28
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Ranjan R, Sinha N. Nuclear magnetic resonance (NMR)-based metabolomics for cancer research. NMR IN BIOMEDICINE 2019; 32:e3916. [PMID: 29733484 DOI: 10.1002/nbm.3916] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/01/2018] [Accepted: 02/12/2018] [Indexed: 06/08/2023]
Abstract
Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research.
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Affiliation(s)
- Renuka Ranjan
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
- School of Biotechnology, Institute of Science Banaras Hindu University, Varanasi, India
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
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29
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Lin Y, Ma C, Bezabeh T, Wang Z, Liang J, Huang Y, Zhao J, Liu X, Ye W, Tang W, Ouyang T, Wu R. 1 H NMR-based metabolomics reveal overlapping discriminatory metabolites and metabolic pathway disturbances between colorectal tumor tissues and fecal samples. Int J Cancer 2019; 145:1679-1689. [PMID: 30720869 DOI: 10.1002/ijc.32190] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 01/29/2019] [Indexed: 02/05/2023]
Abstract
Previous studies have compared fecal metabolites from healthy and colorectal cancer (CRC) patients to predict the pro-CRC signatures. However, the systemic mechanistic link between feces and colonic tissues of CRC patients is still limited. The current study was a paralleled investigation of colonic tumor tissues and their normal adjacent tissues alongside patient-matched feces by using 1 H nuclear magnetic resonance spectroscopy combined with pattern recognition to investigate how fecal metabolic phenotypes are linked to the changes in colorectal tumor profiles. A set of overlapping discriminatory metabolites across feces and tumor tissues of CRC were identified, including elevated levels of lactate, glutamate, alanine, succinate and reduced amounts of butyrate. These changes could indicate the networks for metabolic pathway perturbations in CRC potentially involved in the disruptions of glucose and glycolytic metabolism, TCA cycle, glutaminolysis, and short chain fatty acids metabolism. Furthermore, changes in fecal acetate were positively correlated with alterations of glucose and myo-inositol in colorectal tumor tissues, implying enhanced energy production for rapid cell proliferation. Compared to other fecal metabolites, acetate demonstrated the highest diagnostic performance for diagnosing CRC, with an AUC of 0.843 in the training set, and a good predictive ability in the validation set. Overall, these associations provide evidence of distinct metabolic signatures and metabolic pathway disturbances between the colonic tissues and feces within the same individual, and changes of fecal metabolic signature could reflect the CRC tissue microenvironment, highlighting the significance of the distinct fecal metabolic profiles as potential novel and noninvasive relevant indicators for CRC detection.
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Affiliation(s)
- Yan Lin
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Changchun Ma
- Radiation Oncology, Cancer Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Tedros Bezabeh
- College of Natural & Applied Sciences, University of Guam, UOG Station, Mangilao, Guam
| | - Zhening Wang
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Jiahao Liang
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Yao Huang
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Jiayun Zhao
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Xinmu Liu
- Department of Surgery, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Wei Ye
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Wan Tang
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Ting Ouyang
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
| | - Renhua Wu
- Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong Province, China
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30
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Hashim NAA, Ab-Rahim S, Suddin LS, Saman MSA, Mazlan M. Global serum metabolomics profiling of colorectal cancer. Mol Clin Oncol 2019; 11:3-14. [PMID: 31289671 PMCID: PMC6535638 DOI: 10.3892/mco.2019.1853] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 04/09/2019] [Indexed: 02/06/2023] Open
Abstract
Accurate diagnosis of colorectal cancer (CRC) relies on the use of invasive tools such as colonoscopy and sigmoidoscopy. Non-invasive tools are less sensitive in detecting the disease, particularly in the early stage. A number of researchers have used metabolomics analyses on serum/plasma samples of patients with CRC compared with normal healthy individuals in an effort to identify biomarkers for CRC. The aim of the present review is to compare reported serum metabolomics profiles of CRC and to identify common metabolites affected among these studies. A literature search was performed to include any experimental studies on global metabolomics profile of CRC using serum/plasma samples published up to March 2018. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used to assess the quality of the studies reviewed. In total, nine studies were included. The studies used various analytical platforms and were performed on different populations. A pathway enrichment analysis was performed using the data from all the studies under review. The most affected pathways identified were protein biosynthesis, urea cycle, ammonia recycling, alanine metabolism, glutathione metabolism and citric acid cycle. The metabolomics analysis revealed levels of metabolites of glycolysis, tricarboxylic acid cycle, anaerobic respiration, protein, lipid and glutathione metabolism were significantly different between cancer and control samples. Although the majority of differentiating metabolites identified were different in the different studies, there were several metabolites that were common. These metabolites include pyruvic acid, glucose, lactic acid, malic acid, fumaric acid, 3-hydroxybutyric acid, tryptophan, phenylalanine, tyrosine, creatinine and ornithine. The consistent dysregulation of these metabolites among the different studies suggest the possibility of common diagnostic biomarkers for CRC.
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Affiliation(s)
- Nurul Azmir Amir Hashim
- Faculty of Medicine, Universiti Teknologi MARA, Cawangan Selangor, Sungai Buloh, Selangor 47000, Malaysia
| | - Sharaniza Ab-Rahim
- Faculty of Medicine, Universiti Teknologi MARA, Cawangan Selangor, Sungai Buloh, Selangor 47000, Malaysia
| | - Leny Suzana Suddin
- Faculty of Medicine, Universiti Teknologi MARA, Cawangan Selangor, Sungai Buloh, Selangor 47000, Malaysia
| | - Mohd Shahril Ahmad Saman
- Faculty of Medicine, Universiti Teknologi MARA, Cawangan Selangor, Sungai Buloh, Selangor 47000, Malaysia
| | - Musalmah Mazlan
- Faculty of Medicine, Universiti Teknologi MARA, Cawangan Selangor, Sungai Buloh, Selangor 47000, Malaysia
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31
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Chetwynd AJ, Ogilvie LA, Nzakizwanayo J, Pazdirek F, Hoch J, Dedi C, Gilbert D, Abdul-Sada A, Jones BV, Hill EM. The potential of nanoflow liquid chromatography-nano electrospray ionisation-mass spectrometry for global profiling the faecal metabolome. J Chromatogr A 2019; 1600:127-136. [PMID: 31047664 DOI: 10.1016/j.chroma.2019.04.028] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 04/01/2019] [Accepted: 04/11/2019] [Indexed: 01/03/2023]
Abstract
Faeces are comprised of a wide array of metabolites arising from the circulatory system as well as the human microbiome. A global metabolite analysis (metabolomics) of faecal extracts offers the potential to uncover new compounds which may be indicative of the onset of bowel diseases such as colorectal cancer (CRC). To date, faecal metabolomics is still in its infancy and the compounds of low abundance present in faecal extracts poorly characterised. In this study, extracts of faeces from healthy subjects were profiled using a sensitive nanoflow-nanospray LC-MS platform which resulted in highly repeatable peak retention times (<2% CV) and intensities (<15% CV). Analysis of the extracts revealed wide coverage of the faecal metabolome including detection of low abundant signalling compounds such as sex steroids and eicosanoids, alongside highly abundant pharmaceuticals and tetrapyrrole metabolites. A small pilot study investigating differences in metabolomics profiles of faecal samples obtained from 7 CRC, 25 adenomatous polyp and 26 healthy groups revealed that secondary bile acids, conjugated androgens, eicosanoids, phospholipids and an unidentified haem metabolite were potential classes of metabolites that discriminated between the CRC and control sample groups. However, much larger follow up studies are needed to confirm which components of the faecal metabolome are associated with actual CRC disease rather than dietary influences. This study reveals the potential of nanospray-nanoflow LC-MS profiling of faecal samples from large scale cohort studies for uncovering the role of the faecal metabolome in colorectal disease formation.
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Affiliation(s)
- Andrew J Chetwynd
- School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG, UK; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, UK
| | - Lesley A Ogilvie
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, BN2 4GJ, UK
| | - Jonathan Nzakizwanayo
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, BN2 4GJ, UK
| | - Filip Pazdirek
- Surgery Department, 2nd Medical Faculty of Charles University and University Hospital Motol, Prague, Czech Republic
| | - Jiří Hoch
- Surgery Department, 2nd Medical Faculty of Charles University and University Hospital Motol, Prague, Czech Republic
| | - Cinzia Dedi
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, BN2 4GJ, UK
| | - Duncan Gilbert
- Sussex Cancer Centre, Royal Sussex County Hospital, Brighton, BN2 5DA, UK
| | - Alaa Abdul-Sada
- School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG, UK
| | - Brian V Jones
- School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, BN2 4GJ, UK; Department of Biology and Biochemistry, University of Bath, Bath, BA2 7AY, UK
| | - Elizabeth M Hill
- School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG, UK.
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32
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Amin S, Rattner J, Keramati MR, Farshidfar F, McNamara MG, Knox JJ, Kopciuk K, Vogel HJ, Bathe OF. A strategy for early detection of response to chemotherapy drugs based on treatment-related changes in the metabolome. PLoS One 2019; 14:e0213942. [PMID: 30939138 PMCID: PMC6445409 DOI: 10.1371/journal.pone.0213942] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 02/22/2019] [Indexed: 12/25/2022] Open
Abstract
We describe a biomarker-based approach to delivering chemotherapy that entails monitoring treatment changes in the circulating metabolome that reflect efficacy. In-vitro, multiple tumor cell lines were exposed to numerous chemotherapeutics. Supernatants were collected at baseline and 72 hours post treatment. MTT assays were used to quantify growth inhibition. Clinical samples were derived from a phase II clinical trial of second-line axitinib in patients with advanced hepatocellular carcinoma. Sera were collected at baseline and 2–4 weeks after treatment initiation. Response to therapy was estimated by CT scan at 8 weeks. Samples were analyzed by gas chromatography-mass spectrometry to identify metabolomic changes associated with response. In vitro, we found drug-specific and generalizable patterns of change in the extracellular metabolome accompany growth inhibition. A cell death signature was also identified. This approach was also applied to clinical samples. While the in vitro signatures were detectable in vivo, a more robust signal was identified clinically that appeared within 4 weeks of administering drug that distinguished individuals with a treatment response. These changes were extinguished as tumor growth resumed. Serial monitoring of the metabolome during chemotherapy is a means to follow treatment efficacy and emergence of resistance, informing the oncologist whether to modify treatment.
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Affiliation(s)
- Shahil Amin
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Jodi Rattner
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Mohammad Reza Keramati
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
- Department of Surgery, Tehran University of Medical Sciences, Tehran, Iran
| | - Farshad Farshidfar
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Mairéad G. McNamara
- Department of Medical Oncology, The Christie NHS Foundation Trust and Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
| | - Jennifer J. Knox
- Department of Oncology, Princess Margaret Cancer Centre and University of Toronto, Toronto, Canada
| | - Karen Kopciuk
- Department of Mathematics and Biostatistics, University of Calgary, Calgary, Canada
| | - Hans J. Vogel
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Oliver F. Bathe
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
- Department of Surgery, University of Calgary, Calgary, Canada
- Department of Oncology, University of Calgary, Calgary, Canada
- * E-mail:
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33
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Mass Spectrometry-Based Profiling of Metabolites in Human Biofluids. Methods Mol Biol 2019. [PMID: 30725458 DOI: 10.1007/978-1-4939-9027-6_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Cancer poses a daunting challenge to researchers and clinicians alike. Early diagnosis, accurate prognosis, and prediction of therapeutic response remain elusive in most types of cancer. In addition, lacunae in our understanding of cancer biology continue to hinder advancement of therapeutic strategies. Metabolic reprogramming has been identified as integral to pathogenesis and progression of the disease. Consequently, analysis of biofluid metabolome has emerged as a promising approach to further our understanding of disease biology as well as to identify cancer biomarkers. However, unbiased identification of robust and meaningful differences in metabolic signatures remains a non-trivial task. This chapter describes a generalized strategy for global metabolic profiling of human biofluids using ultra-performance liquid chromatography (UPLC) and mass spectrometry, which together offer a sensitive, high-throughput, and versatile platform. A step-by-step protocol for performing untargeted metabolic profiling of urine and serum (or plasma), using hydrophilic interaction liquid chromatography (HILIC) or reverse-phase (RP) chromatography coupled with electrospray ionization mass spectrometry (ESI-MS) to multivariate data analysis and identification of metabolites of interest has been detailed.
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34
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Wang G, Li Y, Liu M, Guo N, Han C, Liu D, Li D, Yang M, Peng Y, Liu Y, Yu K, Wang C. Determination of volatile organic compounds in SW620 colorectal cancer cells and tumor-bearing mice. J Pharm Biomed Anal 2019; 167:30-37. [PMID: 30738241 DOI: 10.1016/j.jpba.2019.01.050] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/29/2019] [Accepted: 01/29/2019] [Indexed: 12/13/2022]
Abstract
Early diagnosis and early treatment are important factors in reducing colorectal cancer (CRC) metastasis and mortality. Volatile organic compounds (VOCs) released by the human body have great potential for use in clinical diagnosis and therapeutic monitoring for CRC. The aim of our study was to identify VOCs with high specificity and high sensitivity for CRC and to provide a method for early diagnosis of CRC. Gas chromatography-mass spectrometry (GC-MS) was utilized to analyze metabolites in both the in vivo and in vitro experimental groups. In vivo, VOCs were analyzed in the blood of mice after cell inoculation and tumor resection. In vitro experiments were performed by comparing changes in VOCs in an HCoEpiC cell group, control group, SW620 cell group and Arsenic trioxide + SW620 group. We observed changes in VOCs in a series of CRC SW620 cells in vivo and in vitro. Among these changes, we found that the concentrations of 8 substances, including acetone, increased with tumor growth. Nine substances were found to be significantly elevated in the SW620 cancer cell group compared with the other groups. Only one substance was consumed by the tumor in both the in vivo and in vitro experiments. Our study showed that alkanes, lipids, alcohols, ketones, aldehyde, butylated hydroxytoluene (BHT) and hexamethylcyclotrisiloxane all existed at different levels in SW620 CRC cells compared to those in normal cells. We need more research to further confirm this hypothesis.
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Affiliation(s)
- Guiyue Wang
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yuhang Li
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Miao Liu
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Nana Guo
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ci Han
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Desheng Liu
- Department of Critical Care Medicine, the First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Dandan Li
- Department of Critical Care Medicine, the First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Mengyuan Yang
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yahui Peng
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yansong Liu
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Kaijiang Yu
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China.
| | - Changsong Wang
- Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China.
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35
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Zaimenko I, Jaeger C, Brenner H, Chang-Claude J, Hoffmeister M, Grötzinger C, Detjen K, Burock S, Schmitt CA, Stein U, Lisec J. Non-invasive metastasis prognosis from plasma metabolites in stage II colorectal cancer patients: The DACHS study. Int J Cancer 2019; 145:221-231. [PMID: 30560999 DOI: 10.1002/ijc.32076] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 12/03/2018] [Indexed: 12/16/2022]
Abstract
Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case-control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis.
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Affiliation(s)
- Inna Zaimenko
- Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin, and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
| | - Carsten Jaeger
- Berlin Institute of Health, Berlin, Germany.,Medical Department, Division of Hematology, Oncology, and Tumor Immunology, Charité - Universitätsmedizin Berlin, Molekulares Krebsforschungszentrum (MKFZ), Berlin, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carsten Grötzinger
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Hepatology and Gastroenterology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Katharina Detjen
- Department of Hepatology and Gastroenterology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Susen Burock
- Charité Comprehensive Cancer Center, Berlin, Germany
| | - Clemens A Schmitt
- Medical Department, Division of Hematology, Oncology, and Tumor Immunology, Charité - Universitätsmedizin Berlin, Molekulares Krebsforschungszentrum (MKFZ), Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ulrike Stein
- Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin, and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jan Lisec
- Medical Department, Division of Hematology, Oncology, and Tumor Immunology, Charité - Universitätsmedizin Berlin, Molekulares Krebsforschungszentrum (MKFZ), Berlin, Germany.,Division of Analytical Chemistry, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany
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36
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Abstract
Metabolomics is a comprehensive characterization of the small polar molecules (metabolites) in different biological systems. One of the analytical platforms commonly used to study metabolic alterations in biofluid samples is proton nuclear magnetic resonance (1H NMR) spectroscopy. NMR spectroscopy is very specific, quantitative, and highly reproducible. Moreover, sample preparation for NMR experiments is very simple and straightforward, and this gives NMR spectroscopy a distinct advantage over other metabolic profiling methods. It has already been shown that 1H NMR-based profiling of biological fluids can be effective in differentiating benign from malignant lesions and in investigating the efficacy of specific cancer treatments. Therefore, 1H NMR spectroscopy may become a promising tool for early noninvasive diagnosis and rapid assessment of treatment effects in cancer patients. Here, we describe a detailed protocol for 1H NMR metabolite profiling in serum, plasma, and urine samples, including sample collection procedures, sample preparation for 1H NMR experiments, spectral acquisition and processing, and quantitative profiling of 1H NMR spectra. We also discuss several aspects of appropriate study design and some multivariate statistical methods that are commonly used to analyze metabolomics datasets.
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37
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Yusof HM, Ab-Rahim S, Suddin LS, Saman MSA, Mazlan M. Metabolomics Profiling on Different Stages of Colorectal Cancer: A Systematic Review. Malays J Med Sci 2018; 25:16-34. [PMID: 30914860 PMCID: PMC6419892 DOI: 10.21315/mjms2018.25.5.3] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 05/16/2018] [Indexed: 12/18/2022] Open
Abstract
Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Early diagnosis and accurate staging of the disease is vital to improve the prognosis. Metabolomics has been used to identify changes in metabolite profiles in the different stages of cancer in order to introduce new non-invasive molecular tools for staging. In this systematic review, we aim to identify the common metabolite changes in human biological samples and the dominant metabolic pathways associated with CRC progression. A broad systematic search was carried out from selected databases. Four reviewers screened and reviewed the titles, abstracts, and full-text articles according to the inclusion and exclusion criteria. Quality assessment was conducted on the eight articles which met the criteria. Data showed that the metabolites involved with redox status, energy metabolism and intermediates of amino acids, choline and nucleotides metabolism were the most affected during CRC progression. However, there were differences in the levels of individual metabolites detected between the studies, and this might be due to the study population, sample preparation, analytical platforms used and statistical tools. In conclusion, this systematic review highlights the changes in metabolites from early to late stages of CRC. Moreover, biomarkers for prognosis are important to reduce CRC-related mortality.
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Affiliation(s)
- Hazwani Mohd Yusof
- Faculty of Medicine, Universiti Teknologi MARA, Jalan Hospital, 47000 Sg Buloh, Selangor, Malaysia
| | - Sharaniza Ab-Rahim
- Faculty of Medicine, Universiti Teknologi MARA, Jalan Hospital, 47000 Sg Buloh, Selangor, Malaysia
| | - Leny Suzana Suddin
- Faculty of Medicine, Universiti Teknologi MARA, Jalan Hospital, 47000 Sg Buloh, Selangor, Malaysia
| | - Mohd Shahril Ahmad Saman
- Faculty of Medicine, Universiti Teknologi MARA, Jalan Hospital, 47000 Sg Buloh, Selangor, Malaysia
| | - Musalmah Mazlan
- Faculty of Medicine, Universiti Teknologi MARA, Jalan Hospital, 47000 Sg Buloh, Selangor, Malaysia
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Marchand CR, Farshidfar F, Rattner J, Bathe OF. A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation. Metabolites 2018; 8:E59. [PMID: 30274369 PMCID: PMC6316283 DOI: 10.3390/metabo8040059] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 09/27/2018] [Accepted: 09/28/2018] [Indexed: 12/24/2022] Open
Abstract
Despite the significant advantages of metabolomic biomarkers, no diagnostic tests based on metabolomics have been introduced to clinical use. There are many reasons for this, centered around substantial obstacles in developing clinically useful metabolomic biomarkers. Most significant is the need for interdisciplinary teams with expertise in metabolomics, analysis of complex clinical and metabolomic data, and clinical care. Importantly, the clinical need must precede biomarker discovery, and the experimental design for discovery and validation must reflect the purpose of the biomarker. Standard operating procedures for procuring and handling samples must be developed from the beginning, to ensure experimental integrity. Assay design is another challenge, as there is not much precedent informing this. Another obstacle is that it is not yet clear how to protect any intellectual property related to metabolomic biomarkers. Viewing a metabolomic biomarker as a natural phenomenon would inhibit patent protection and potentially stifle commercial interest. However, demonstrating that a metabolomic biomarker is actually a derivative of a natural phenomenon that requires innovation would enhance investment in this field. Finally, effective knowledge translation strategies must be implemented, which will require engagement with end users (clinicians and lab physicians), patient advocate groups, policy makers, and payer organizations. Addressing each of these issues comprises the framework for introducing a metabolomic biomarker to practice.
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Affiliation(s)
- Calena R Marchand
- Faculty of Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
| | - Farshad Farshidfar
- Department of Oncology, University of Calgary, Calgary, AB T2N 1N4, Canada.
- Arnie Charbonneau Cancer Research Institute, University of Calgary, Calgary, AB T2N 1N4, Canada.
| | - Jodi Rattner
- Arnie Charbonneau Cancer Research Institute, University of Calgary, Calgary, AB T2N 1N4, Canada.
| | - Oliver F Bathe
- Department of Oncology, University of Calgary, Calgary, AB T2N 1N4, Canada.
- Arnie Charbonneau Cancer Research Institute, University of Calgary, Calgary, AB T2N 1N4, Canada.
- Department of Surgery, University of Calgary, Calgary, AB T2N 1N4, Canada.
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Lee PY, Chin SF, Low TY, Jamal R. Probing the colorectal cancer proteome for biomarkers: Current status and perspectives. J Proteomics 2018; 187:93-105. [PMID: 29953962 DOI: 10.1016/j.jprot.2018.06.014] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 06/13/2018] [Accepted: 06/23/2018] [Indexed: 02/07/2023]
Abstract
Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.
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Affiliation(s)
- Pey Yee Lee
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000 Kuala Lumpur, Malaysia.
| | - Siok-Fong Chin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000 Kuala Lumpur, Malaysia
| | - Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000 Kuala Lumpur, Malaysia
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000 Kuala Lumpur, Malaysia
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Farshidfar F, Kopciuk KA, Hilsden R, McGregor SE, Mazurak VC, Buie WD, MacLean A, Vogel HJ, Bathe OF. A quantitative multimodal metabolomic assay for colorectal cancer. BMC Cancer 2018; 18:26. [PMID: 29301511 PMCID: PMC5755335 DOI: 10.1186/s12885-017-3923-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 12/14/2017] [Indexed: 02/08/2023] Open
Abstract
Background Early diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation. Methods The well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed. Results The metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y = 0.83, Q2Y = 0.75, CV-ANOVA p-value < 0.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93–1.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R2Y = 0.30, Q2Y = 0.20, CV-ANOVA p-value = 0.01; internal AUROC = 0.82 (95% CI, 0.72–0.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly. Conclusion The diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker. Electronic supplementary material The online version of this article (10.1186/s12885-017-3923-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Farshad Farshidfar
- Department of Surgery, University of Calgary, Calgary, AB, Canada.,Department of Oncology, University of Calgary, Calgary, AB, Canada
| | - Karen A Kopciuk
- Department Mathematics and Statistics, University of Calgary, Calgary, AB, Canada.,Population Health Research, Alberta Health Services, Calgary, AB, Canada
| | - Robert Hilsden
- Department of Medicine, University of Calgary, Calgary, AB, Canada.,Forzani & MacPhail Colon Cancer Screening Centre, Calgary, AB, Canada
| | - S Elizabeth McGregor
- Department of Oncology, University of Calgary, Calgary, AB, Canada.,Population Health Research, Alberta Health Services, Calgary, AB, Canada
| | - Vera C Mazurak
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada
| | - W Donald Buie
- Department of Surgery, University of Calgary, Calgary, AB, Canada
| | - Anthony MacLean
- Department of Surgery, University of Calgary, Calgary, AB, Canada
| | - Hans J Vogel
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Oliver F Bathe
- Department of Surgery, University of Calgary, Calgary, AB, Canada. .,Department of Oncology, University of Calgary, Calgary, AB, Canada. .,Division of Surgical Oncology, Tom Baker Cancer Centre, 1331 - 29th St NW, Calgary, AB, T2N 4N2, Canada.
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Djukovic D, Zhang J, Raftery D. Colorectal Cancer Detection Using Targeted LC-MS Metabolic Profiling. Methods Mol Biol 2018; 1765:229-240. [PMID: 29589312 DOI: 10.1007/978-1-4939-7765-9_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Colorectal cancer (CRC) is one of the most commonly diagnosed malignancies and causes of cancer death. While the mortality rates from CRC have steadily declined, 50,000 individuals in the USA (and many times this number worldwide) still succumb to this illness every year. Early detection of CRC is the most critical need for improving 5-year survival and cure rates. Currently available CRC diagnostic techniques often miss early stage disease such that only 40% of newly diagnosed CRC patients are treated for local disease, Therefore, development of new screening methods that are highly sensitive, specific, noninvasive and easily accessible are critically desired for the early diagnosis and significant reduction in death rate from CRC. In this chapter we describe a targeted LC-MS based metabolic profiling approach used for the discovery of CRC metabolite biomarker candidates, based on highly reproducible hydrophilic interaction liquid chromatography coupled to triple-quadrupole mass spectrometry (HILIC-LC-QQQ-MS). A partial least squares-discriminant analysis (PLS-DA) model was able to differentiate CRC patients from both healthy controls and polyp patients, as well as to distinguish CRC patients based on the cancer stage.
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Affiliation(s)
- Danijel Djukovic
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
| | - Jiangjiang Zhang
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
| | - Daniel Raftery
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.
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Wang Z, Lin Y, Liang J, Huang Y, Ma C, Liu X, Yang J. NMR-based metabolomic techniques identify potential urinary biomarkers for early colorectal cancer detection. Oncotarget 2017; 8:105819-105831. [PMID: 29285295 PMCID: PMC5739682 DOI: 10.18632/oncotarget.22402] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 08/29/2017] [Indexed: 02/05/2023] Open
Abstract
Better early detection methods are needed to improve the outcomes of patients with colorectal cancer (CRC). Proton nuclear magnetic resonance spectroscopy (1H-NMR), a potential non-invasive early tumor detection method, was used to profile urine metabolites from 55 CRC patients and 40 healthy controls (HCs). Pattern recognition through orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to 1H-NMR processed data. Model specificity was confirmed by comparison with esophageal cancers (EC, n=18). Unique metabolomic profiles distinguished all CRC stages from HC urine samples. A total of 16 potential biomarker metabolites were identified in stage I/II CRC, indicating amino acid metabolism, glycolysis, tricarboxylic acid (TCA) cycle, urea cycle, choline metabolism, and gut microflora metabolism pathway disruptions. Metabolite profiles from early stage CRC and EC patients were also clearly distinguishable, suggesting that upper and lower gastrointestinal cancers have different metabolomic profiles. Our study assessed important metabolomic variations in CRC patient urine samples, provided information complementary to that collected from other biofluid-based metabolomics analyses, and elucidated potential underlying metabolic mechanisms driving CRC. Our results support the utility of NMR-based urinary metabolomics fingerprinting in early diagnosis of CRC.
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Affiliation(s)
- Zhening Wang
- Radiology Department, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Yan Lin
- Radiology Department, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Jiahao Liang
- Radiology Department, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Yao Huang
- Radiology Department, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Changchun Ma
- Radiation Oncology, Affiliated Tumor Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Xingmu Liu
- Surgery Department, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
| | - Jurong Yang
- Shantou University Central Laboratory and NMR Unit, Shantou 515041, Guangdong Province, China
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43
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Considine EC, Thomas G, Boulesteix AL, Khashan AS, Kenny LC. Critical review of reporting of the data analysis step in metabolomics. Metabolomics 2017; 14:7. [PMID: 30830321 DOI: 10.1007/s11306-017-1299-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 11/13/2017] [Indexed: 12/29/2022]
Abstract
INTRODUCTION We present the first study to critically appraise the quality of reporting of the data analysis step in metabolomics studies since the publication of minimum reporting guidelines in 2007. OBJECTIVES The aim of this study was to assess the standard of reporting of the data analysis step in metabolomics biomarker discovery studies and to investigate whether the level of detail supplied allows basic understanding of the steps employed and/or reuse of the protocol. For the purposes of this review we define the data analysis step to include the data pretreatment step and the actual data analysis step, which covers algorithm selection, univariate analysis and multivariate analysis. METHOD We reviewed the literature to identify metabolomic studies of biomarker discovery that were published between January 2008 and December 2014. Studies were examined for completeness in reporting the various steps of the data pretreatment phase and data analysis phase and also for clarity of the workflow of these sections. RESULTS We analysed 27 papers, published anytime in 2008 until the end of 2014 in the area or biomarker discovery in serum metabolomics. The results of this review showed that the data analysis step in metabolomics biomarker discovery studies is plagued by unclear and incomplete reporting. Major omissions and lack of logical flow render the data analysis' workflows in these studies impossible to follow and therefore replicate or even imitate. CONCLUSIONS While we await the holy grail of computational reproducibility in data analysis to become standard, we propose that, at a minimum, the data analysis section of metabolomics studies should be readable and interpretable without omissions such that a data analysis workflow diagram could be extrapolated from the study and therefore the data analysis protocol could be reused by the reader. That inconsistent and patchy reporting obfuscates reproducibility is a given. However even basic understanding and reuses of protocols are hampered by the low level of detail supplied in the data analysis sections of the studies that we reviewed.
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Affiliation(s)
- E C Considine
- The Irish Centre for Fetal and Neonatal Translational Research (INFANT), Department of Obstetrics and Gynaecology, University College Cork, Cork, Ireland.
| | - G Thomas
- SQU4RE, Sint-Alfonsusstraat 17, 8800, Roeselare, Belgium
| | - A L Boulesteix
- Department of Medical Informatics, Biometry and Epidemiology, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - A S Khashan
- The Irish Centre for Fetal and Neonatal Translational Research (INFANT), Department of Obstetrics and Gynaecology, University College Cork, Cork, Ireland
- Department of Epidemiology and Public Health, University College Cork, Cork, Ireland
| | - L C Kenny
- The Irish Centre for Fetal and Neonatal Translational Research (INFANT), Department of Obstetrics and Gynaecology, University College Cork, Cork, Ireland
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Rattner J, Bathe OF. Monitoring for Response to Antineoplastic Drugs: The Potential of a Metabolomic Approach. Metabolites 2017; 7:metabo7040060. [PMID: 29144383 PMCID: PMC5746740 DOI: 10.3390/metabo7040060] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Revised: 10/09/2017] [Accepted: 11/13/2017] [Indexed: 12/20/2022] Open
Abstract
For most cancers, chemotherapeutic options are rapidly expanding, providing the oncologist with substantial choices. Therefore, there is a growing need to select the best systemic therapy, for any individual, that effectively halts tumor progression with minimal toxicity. Having the capability to predict benefit and to anticipate toxicity would be ideal, but remains elusive at this time. An alternative approach is an adaptive approach that involves close observation for treatment response and emergence of resistance. Currently, response to systemic therapy is estimated using radiographic tests. Unfortunately, radiographic estimates of response are imperfect and radiographic signs of response can be delayed. This is particularly problematic for targeted agents, as tumor shrinkage is often not apparent with these drugs. As a result, patients are exposed to prolonged courses of toxic drugs that may ultimately be found to be ineffective. A biomarker-based adaptive strategy that involves the serial analysis of the metabolome is attractive. The metabolome changes rapidly with changes in physiology. Changes in the circulating metabolome associated with various antineoplastic agents have been described, but further work will be required to understand what changes signify clinical benefit. We present an investigative approach for the discovery and validation of metabolomic response biomarkers, which consists of serial analysis of the metabolome and linkage of changes in the metabolome to measurable therapeutic benefit. Potential pitfalls in the development of metabolomic biomarkers of response and loss of response are reviewed.
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Affiliation(s)
- Jodi Rattner
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Oliver F Bathe
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Surgery, Tom Baker Cancer Center, University of Calgary, 1331 29th St NW, Calgary, AB T2N 4N2, Canada.
- Department of Oncology, Tom Baker Cancer Center, University of Calgary, 1331 29th St NW, Calgary, AB T2N 4N2, Canada.
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Li Y, Wang C, Li D, Deng P, Shao X, Hu J, Liu C, Jie H, Lin Y, Li Z, Qian X, Zhang H, Zhao Y. 1H-NMR-based metabolic profiling of a colorectal cancer CT-26 lung metastasis model in mice. Oncol Rep 2017; 38:3044-3054. [PMID: 28901465 DOI: 10.3892/or.2017.5954] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 06/26/2017] [Indexed: 02/05/2023] Open
Abstract
Lung metastasis is an important cause for the low 5-year survival rate of colorectal cancer patients. Understanding the metabolic profile of lung metastasis of colorectal cancer is important for developing molecular diagnostic and therapeutic approaches. We carried out the metabonomic profiling of lung tissue samples on a mouse lung metastasis model of colorectal cancer using 1H-nuclear magnetic resonance (1H-NMR). The lung tissues of mice were collected at different intervals after marine colon cancer cell line CT-26 was intravenously injected into BALB/c mice. The distinguishing metabolites of lung tissue were investigated using 1H-NMR-based metabonomic assay, which is a highly sensitive and non-destructive method for biomarker identification. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to analyze 1H-NMR profiling data to seek potential biomarkers. All of the 3 analyses achieved excellent separations between the normal and metastasis groups. A total of 42 metabolites were identified, ~12 of which were closely correlated with the process of metastasis from colon to lung. These altered metabolites indicated the disturbance of metabolism in metastatic tumors including glycolysis, TCA cycle, glutaminolysis, choline metabolism and serine biosynthesis. Our findings firstly identified the distinguishing metabolites in mouse colorectal cancer lung metastasis models, and indicated that the metabolite disturbance may be associated with the progression of lung metastasis from colon cancer. The altered metabolites may be potential biomarkers that provide a promising molecular approach for clinical diagnosis and mechanistic study of colorectal cancer with lung metastasis.
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Affiliation(s)
- Yan Li
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Chunting Wang
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Dandan Li
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Pengchi Deng
- Analytical and Testing Center, Sichuan University, Chengdu, Sichuan 610041, P.R. China
| | - Xiaoni Shao
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Jing Hu
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Chunqi Liu
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Hui Jie
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Yiyun Lin
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Zhuoling Li
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Xinying Qian
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Huaqin Zhang
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
| | - Yinglan Zhao
- Pharmacodynamics Pharmacokinetics Early Safety Evaluation Model Animals, Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, P.R. China
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Attri KS, Murthy D, Singh PK. Racial disparity in metabolic regulation of cancer. Front Biosci (Landmark Ed) 2017; 22:1221-1246. [PMID: 28199202 DOI: 10.2741/4543] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Genetic mutations and metabolic reprogramming are two key hallmarks of cancer, required for proliferation, invasion, and metastasis of the disease. While genetic mutations, whether inherited or acquired, are critical for the initiation of tumor development, metabolic reprogramming is an effector mechanism imperative for adaptational transition during the progression of cancer. Recent findings in the literature emphasize the significance of molecular cross-talk between these two cellular processes in regulating signaling and differentiation of cancer cells. Genome-wide sequencing analyses of cancer genomes have highlighted the association of various genic mutations in predicting cancer risk and survival. Oncogenic mutational frequency is heterogeneously distributed among various cancer types in different populations, resulting in varying susceptibility to cancer risk. In this review, we explore and discuss the role of genetic mutations in metabolic enzymes and metabolic oncoregulators to stratify cancer risk in persons of different racial backgrounds.
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Affiliation(s)
- Kuldeep S Attri
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA
| | - Divya Murthy
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA
| | - Pankaj K Singh
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA,
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Brasili E, Filho VC. Metabolomics of cancer cell cultures to assess the effects of dietary phytochemicals. Crit Rev Food Sci Nutr 2017; 57:1328-1339. [DOI: 10.1080/10408398.2014.964799] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Elisa Brasili
- Department of Environmental Biology, “Sapienza” University of Rome, Rome, Italy
| | - Valdir Cechinel Filho
- Programa de Pós-Graduação em Ciências Farmacêuticas e Núcleo de Investigações Químico-Farmacêuticas/CCS, Universidade do Vale do Itajaí, Itajaí, SC, Brazil
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48
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Esposito MR, Aveic S, Seydel A, Tonini GP. Neuroblastoma treatment in the post-genomic era. J Biomed Sci 2017; 24:14. [PMID: 28178969 PMCID: PMC5299732 DOI: 10.1186/s12929-017-0319-y] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 01/31/2017] [Indexed: 02/07/2023] Open
Abstract
Neuroblastoma is an embryonic malignancy of early childhood originating from neural crest cells and showing heterogeneous biological, morphological, genetic and clinical characteristics. The correct stratification of neuroblastoma patients within risk groups (low, intermediate, high and ultra-high) is critical for the adequate treatment of the patients. High-throughput technologies in the Omics disciplines are leading to significant insights into the molecular pathogenesis of neuroblastoma. Nonetheless, further study of Omics data is necessary to better characterise neuroblastoma tumour biology. In the present review, we report an update of compounds that are used in preclinical tests and/or in Phase I-II trials for neuroblastoma. Furthermore, we recapitulate a number of compounds targeting proteins associated to neuroblastoma: MYCN (direct and indirect inhibitors) and downstream targets, Trk, ALK and its downstream signalling pathways. In particular, for the latter, given the frequency of ALK gene deregulation in neuroblastoma patients, we discuss on second-generation ALK inhibitors in preclinical or clinical phases developed for the treatment of neuroblastoma patients resistant to crizotinib. We summarise how Omics drive clinical trials for neuroblastoma treatment and how much the research of biological targets is useful for personalised medicine. Finally, we give an overview of the most recent druggable targets selected by Omics investigation and discuss how the Omics results can provide us additional advantages for overcoming tumour drug resistance.
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Affiliation(s)
- Maria Rosaria Esposito
- Paediatric Research Institute, Fondazione Città della Speranza, Neuroblastoma Laboratory, Corso Stati Uniti, 4, Padua, 35127, Italy.
| | - Sanja Aveic
- Paediatric Research Institute, Fondazione Città della Speranza, Neuroblastoma Laboratory, Corso Stati Uniti, 4, Padua, 35127, Italy
| | - Anke Seydel
- Department of Biology, University of Padua, Padua, Italy
| | - Gian Paolo Tonini
- Paediatric Research Institute, Fondazione Città della Speranza, Neuroblastoma Laboratory, Corso Stati Uniti, 4, Padua, 35127, Italy
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McConnell YJ, Farshidfar F, Weljie AM, Kopciuk KA, Dixon E, Ball CG, Sutherland FR, Vogel HJ, Bathe OF. Distinguishing Benign from Malignant Pancreatic and Periampullary Lesions Using Combined Use of ¹H-NMR Spectroscopy and Gas Chromatography-Mass Spectrometry. Metabolites 2017; 7:metabo7010003. [PMID: 28098776 PMCID: PMC5372206 DOI: 10.3390/metabo7010003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 12/09/2016] [Accepted: 01/08/2017] [Indexed: 12/13/2022] Open
Abstract
Previous work demonstrated that serum metabolomics can distinguish pancreatic cancer from benign disease. However, in the clinic, non-pancreatic periampullary cancers are difficult to distinguish from pancreatic cancer. Therefore, to test the clinical utility of this technology, we determined whether any pancreatic and periampullary adenocarcinoma could be distinguished from benign masses and biliary strictures. Sera from 157 patients with malignant and benign pancreatic and periampullary lesions were analyzed using proton nuclear magnetic resonance (1H-NMR) spectroscopy and gas chromatography–mass spectrometry (GC-MS). Multivariate projection modeling using SIMCA-P+ software in training datasets (n = 80) was used to generate the best models to differentiate disease states. Models were validated in test datasets (n = 77). The final 1H-NMR spectroscopy and GC-MS metabolomic profiles consisted of 14 and 18 compounds, with AUROC values of 0.74 (SE 0.06) and 0.62 (SE 0.08), respectively. The combination of 1H-NMR spectroscopy and GC-MS metabolites did not substantially improve this performance (AUROC 0.66, SE 0.08). In patients with adenocarcinoma, glutamate levels were consistently higher, while glutamine and alanine levels were consistently lower. Pancreatic and periampullary adenocarcinomas can be distinguished from benign lesions. To further enhance the discriminatory power of metabolomics in this setting, it will be important to identify the metabolomic changes that characterize each of the subclasses of this heterogeneous group of cancers.
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Affiliation(s)
- Yarrow J McConnell
- Department of Oncology, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Surgery, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Farshad Farshidfar
- Department of Oncology, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Aalim M Weljie
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Pharmacology, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Karen A Kopciuk
- Department of Oncology, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Elijah Dixon
- Department of Oncology, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Surgery, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Chad G Ball
- Department of Surgery, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | | | - Hans J Vogel
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 4N2, Canada.
| | - Oliver F Bathe
- Department of Oncology, University of Calgary, Calgary, AB T2N 4N2, Canada.
- Department of Surgery, University of Calgary, Calgary, AB T2N 4N2, Canada.
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Sheff JG, Farshidfar F, Bathe OF, Kopciuk K, Gentile F, Tuszynski J, Barakat K, Schriemer DC. Novel Allosteric Pathway of Eg5 Regulation Identified through Multivariate Statistical Analysis of Hydrogen-Exchange Mass Spectrometry (HX-MS) Ligand Screening Data. Mol Cell Proteomics 2017; 16:428-437. [PMID: 28062800 DOI: 10.1074/mcp.m116.064246] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 11/12/2016] [Indexed: 11/06/2022] Open
Abstract
The mitotic kinesin Eg5 is an important target in cancer chemotherapy. A structurally diverse collection of canonical loop L5 inhibitors engage an allosteric pathway that includes elements of its microtubule binding region. However, recent evidence suggests that Eg5 may permit alternative allosteric mechanisms. Terpendole E, a natural-product Eg5 inhibitor, is active against mutants resistant to canonical loop L5 inhibitors and appears to offer a unique mode of inhibition. To investigate the variety of inhibitor responses, the structure-function properties of eighteen kinesin inhibitors were quantified with hydrogen-exchange mass spectrometry (HX-MS), functional analysis and molecular modeling. A unique strategy for high-density data analysis was implemented, based on a scalable multivariate statistical method, as current HX-MS routines have a limited capacity to guide a characterization of ligands when additional functional data is available. Inhibitor evaluation was achieved using orthogonal partial least squares projection to latent structures discriminant analysis (OPLS-DA). The strategy generated a model that identified functionally-significant conformational elements involved in kinesin inhibition, confirming the canonical allosteric pathway and identifying a novel response pathway. Terpendole E is demonstrated to be an atypical L5 site inhibitor, where binding induces an allosteric effect mediated by a destabilization in the β-sheet core of the molecular motor, an element involved in mechanochemical coupling for structurally-related kinesins. The analysis suggests that a different approach to inhibitor development may be fruitful.
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Affiliation(s)
- Joey G Sheff
- From the ‡Department of Chemistry, University of Calgary, Calgary, Alberta, Canada
| | - Farshad Farshidfar
- §Department of Surgery, University of Calgary, Calgary, Alberta, Canada.,¶Department of Oncology, University of Calgary, Calgary, Alberta, Canada
| | - Oliver F Bathe
- §Department of Surgery, University of Calgary, Calgary, Alberta, Canada.,¶Department of Oncology, University of Calgary, Calgary, Alberta, Canada
| | - Karen Kopciuk
- ‖Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada.,**Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, AB, Canada
| | - Francesco Gentile
- ‡‡Department of Physics, University of Alberta, Edmonton, Alberta, Canada
| | - Jack Tuszynski
- ‡‡Department of Physics, University of Alberta, Edmonton, Alberta, Canada.,§§Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
| | - Khaled Barakat
- ¶¶Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Canada
| | - David C Schriemer
- From the ‡Department of Chemistry, University of Calgary, Calgary, Alberta, Canada; .,‖‖Department of Biochemistry and Molecular Biology, University of Calgary, Alberta Canada
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