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Mehrotra S, Sharma S, Pandey RK. A journey from omics to clinicomics in solid cancers: Success stories and challenges. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:89-139. [PMID: 38448145 DOI: 10.1016/bs.apcsb.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading cause of death worldwide, responsible for one in six deaths and hence imposes a significant burden on global healthcare systems. High-throughput omics technologies combined with advanced imaging tools, have revolutionized our ability to interrogate the molecular landscape of tumors and has provided unprecedented understanding of the disease. Yet, there is a gap between basic research discoveries and their translation into clinically meaningful therapies for improving patient care. To bridge this gap, there is a need to analyse the vast amounts of high dimensional datasets from multi-omics platforms. The integration of multi-omics data with clinical information like patient history, histological examination and imaging has led to the novel concept of clinicomics and may expedite the bench-to-bedside transition in cancer. The journey from omics to clinicomics has gained momentum with development of radiomics which involves extracting quantitative features from medical imaging data with the help of deep learning and artificial intelligence (AI) tools. These features capture detailed information about the tumor's shape, texture, intensity, and spatial distribution. Together, the related fields of multiomics, translational bioinformatics, radiomics and clinicomics may provide evidence-based recommendations tailored to the individual cancer patient's molecular profile and clinical characteristics. In this chapter, we summarize multiomics studies in solid cancers with a specific focus on breast cancer. We also review machine learning and AI based algorithms and their use in cancer diagnosis, subtyping, prognosis and predicting treatment resistance and relapse.
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Wei Z, Wang W, Xu W, Tao L, Li Z, Zhang Y, Shao X. Studies on immunotoxicity induced by emamectin benzoate in zebrafish embryos based on metabolomics. ENVIRONMENTAL TOXICOLOGY 2024; 39:97-105. [PMID: 37665110 DOI: 10.1002/tox.23942] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/09/2023] [Accepted: 08/07/2023] [Indexed: 09/05/2023]
Abstract
Emamectin benzoate (EMB) is an insecticide for the control of agricultural lepidoptera pests, and also an anti-parasiticide for the control of exoparasites in aquaculture industry. Increased studies suggest that EMB could cause toxicity to non-targeted organisms, but its immunotoxicity to human remains unclear. In this study, zebrafish were used to investigate the immunotoxic effects induced by environmentally relevant doses of EMB. We observed that EMB exposure led to embryo mortality and delayed hatching, as well as increased malformations. Meanwhile, zebrafish exposed to EMB exhibited a significant decrease in the number of neutrophils and macrophages. In addition, untargeted metabolomics approach was developed to elucidate the mechanism of EMB-induced immunotoxicity. We found that a total of 10 shared biomarkers were identified in response to EMB exposure. Furthermore, pathway analysis identified glycerophospholipid metabolism was the most relevant pathway. Within this pathway, it was observed abnormal increases in glycerol 3-phosphate content, which could be attributed to the increased expression of GK5 and decreased expression of GPAT3. Our study provided novel and robust perspectives, which showed that EMB exposure to zebrafish embryos could cause metabolic disturbances that adversely affected development and immune system.
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Affiliation(s)
- Ziyi Wei
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Weiguo Wang
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Wenping Xu
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Liming Tao
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Zhong Li
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Yang Zhang
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Xusheng Shao
- Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai, China
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
- Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, China
- Engineering Research Center of Pharmaceutical Process Chemistry, Ministry of Education, School of Pharmacy, East China University of Science and Technology, Shanghai, China
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Yu W, Chen L, Li X, Han T, Yang Y, Hu C, Yu W, Lü Y. Alteration of Metabolic Profiles during the Progression of Alzheimer's Disease. Brain Sci 2023; 13:1459. [PMID: 37891827 PMCID: PMC10605479 DOI: 10.3390/brainsci13101459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/25/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography-mass spectrometry (GC-MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l-glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.
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Affiliation(s)
- Wuhan Yu
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (W.Y.); (L.C.)
| | - Lihua Chen
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (W.Y.); (L.C.)
| | - Xuebing Li
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (W.Y.); (L.C.)
| | - Tingli Han
- Department of Obsetric and Gyncology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
- Liggins Institute, The University of Auckland, Auckland 1023, New Zealand
| | - Yang Yang
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400716, China
| | - Cheng Hu
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (W.Y.); (L.C.)
| | - Weihua Yu
- Institutes of Neuroscience, Chongqing Medical University, Chongqing 400016, China
| | - Yang Lü
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (W.Y.); (L.C.)
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Velenosi TJ, Krausz KW, Hamada K, Dorsey TH, Ambs S, Takahashi S, Gonzalez FJ. Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer. NPJ Precis Oncol 2022; 6:70. [PMID: 36207498 PMCID: PMC9547066 DOI: 10.1038/s41698-022-00313-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/15/2022] [Indexed: 12/05/2022] Open
Abstract
Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. A pharmacometabolomics study was performed using doxorubicin sensitive and resistant TNBC patient-derived xenograft (PDX) models to detect urinary metabolic biomarkers of treatment effectiveness. Evaluation of metabolite production was assessed by directly studying tumor levels in TNBC-PDX mice and human subjects. Metabolic flux leading to biomarker production was determined using stable isotope-labeled tracers in TNBC-PDX ex vivo tissue slices. Findings were validated in 12-h urine samples from control (n = 200), ER+/PR+ (n = 200), ER+/PR+/HER2+ (n = 36), HER2+ (n = 81) and TNBC (n = 200) subjects. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Urine diacetylspermine was produced by the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N1-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. Urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.
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Affiliation(s)
- Thomas J Velenosi
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA. .,Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
| | - Kristopher W Krausz
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Keisuke Hamada
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Tiffany H Dorsey
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Shogo Takahashi
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Frank J Gonzalez
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA.
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Li D, Lu Y, Zhao F, Yan L, Yang X, Wei L, Yang X, Yuan X, Yang K. Targeted metabolomic profiles of serum amino acids and acylcarnitines related to gastric cancer. PeerJ 2022; 10:e14115. [PMID: 36221263 PMCID: PMC9548315 DOI: 10.7717/peerj.14115] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/04/2022] [Indexed: 01/21/2023] Open
Abstract
Background Early diagnosis and treatment are imperative for improving survival in gastric cancer (GC). This work aimed to assess the ability of human serum amino acid and acylcarnitine profiles in distinguishing GC cases from atrophic gastritis (AG) and control superficial gastritis (SG) patients. Methods Sixty-nine GC, seventy-four AG and seventy-two SG control patients treated from May 2018 to May 2019 in Gansu Provincial Hospitalwere included. The levels of 42 serum metabolites in the GC, AG and SG groups were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, orthogonal partial least squares discriminant analysis (OPLS-DA) and the Kruskal-Wallis H test were used to identify a metabolomic signature among the three groups. Metabolites with highest significance were examined for further validation. Receiver operating characteristic (ROC) curve analysis was carried out for evaluating diagnostic utility. Results The metabolomic analysis found adipylcarnitine (C6DC), 3-hydroxy-hexadecanoylcarnitine (C16OH), hexanoylcarnitine (C6), free carnitine (C0) and arginine (ARG) were differentially expressed (all VIP >1) and could distinguish GC patients from AG and SG cases. In comparison with the AG and SG groups, GC cases had significantly higher C6DC, C16OH, C6, C0 and ARG amounts. Jointly quantitating these five metabolites had specificity and sensitivity in GC diagnosis of 98.55% and 99.32%, respectively, with an area under the ROC curve (AUC) of 0.9977. Conclusion This study indicates C6DC, C16OH, C6, C0 and ARG could effectively differentiate GC cases from AG and SG patients, and may jointly serve as a valuable circulating multi-marker panel for GC detection.
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Affiliation(s)
- Dehong Li
- Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China,Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Yan Lu
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Fenghui Zhao
- Department of Pathology, Gansu Provincial Hospital, Lanzhou, China
| | - Li Yan
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Xingwen Yang
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Lianhua Wei
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Xiaoyan Yang
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Xiumei Yuan
- Department of Clinical laboratory, Gansu Provincial Hospital, Lanzhou, China
| | - Kehu Yang
- Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
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Bafiti V, Katsila T. Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:542-551. [PMID: 36149303 DOI: 10.1089/omi.2022.0097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.
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Affiliation(s)
- Vivi Bafiti
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
| | - Theodora Katsila
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
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Liquid Biopsy as a Tool for the Diagnosis, Treatment, and Monitoring of Breast Cancer. Int J Mol Sci 2022; 23:ijms23179952. [PMID: 36077348 PMCID: PMC9456236 DOI: 10.3390/ijms23179952] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 08/24/2022] [Accepted: 08/29/2022] [Indexed: 11/16/2022] Open
Abstract
Breast cancer (BC) is a highly heterogeneous disease. The treatment of BC is complicated owing to intratumoral complexity. Tissue biopsy and immunohistochemistry are the current gold standard techniques to guide breast cancer therapy; however, these techniques do not assess tumoral molecular heterogeneity. Personalized medicine aims to overcome these biological and clinical complexities. Advances in techniques and computational analyses have enabled increasingly sensitive, specific, and accurate application of liquid biopsy. Such progress has ushered in a new era in precision medicine, where the objective is personalized treatment of breast cancer, early screening, accurate diagnosis and prognosis, relapse detection, longitudinal monitoring, and drug selection. Liquid biopsy can be defined as the sampling of components of tumor cells that are released from a tumor and/or metastatic deposits into the blood, urine, feces, saliva, and other biological substances. Such components include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) or circulating tumor RNA (ctRNA), platelets, and exosomes. This review aims to highlight the role of liquid biopsy in breast cancer and precision medicine.
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Munley KM, Wade KL, Pradhan DS. Uncovering the seasonal brain: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a biochemical approach for studying seasonal social behaviors. Horm Behav 2022; 142:105161. [PMID: 35339904 DOI: 10.1016/j.yhbeh.2022.105161] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 03/12/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022]
Abstract
Many animals show pronounced changes in physiology and behavior across the annual cycle, and these adaptations enable individuals to prioritize investing in the neuroendocrine mechanisms underlying reproduction and/or survival based on the time of year. While prior research has offered valuable insight into how seasonal variation in neuroendocrine processes regulates social behavior, the majority of these studies have investigated how a single hormone influences a single behavioral phenotype. Given that hormones are synthesized and metabolized via complex biochemical pathways and often act in concert to control social behavior, these approaches provide a limited view of how hormones regulate seasonal changes in behavior. In this review, we discuss how seasonal influences on hormones, the brain, and social behavior can be studied using liquid chromatography-tandem mass spectrometry (LC-MS/MS), an analytical chemistry technique that enables researchers to simultaneously quantify the concentrations of multiple hormones and the activities of their synthetic enzymes. First, we examine studies that have investigated seasonal plasticity in brain-behavior interactions, specifically by focusing on how two groups of hormones, sex steroids and nonapeptides, regulate sexual and aggressive behavior. Then, we explain the operations of LC-MS/MS, highlight studies that have used LC-MS/MS to study the neuroendocrine mechanisms underlying social behavior, both within and outside of a seasonal context, and discuss potential applications for LC-MS/MS in the field of behavioral neuroendocrinology. We propose that this cutting-edge technology will provide a more comprehensive understanding of how the multitude of hormones that comprise complex neuroendocrine networks affect seasonal variation in the brain and behavior.
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Affiliation(s)
- Kathleen M Munley
- Department of Biology and Center for the Integrative Study of Animal Behavior, Indiana University, Bloomington, IN 47405, USA.
| | - Kristina L Wade
- Department of Biological Sciences, Idaho State University, Pocatello, ID 83209, USA
| | - Devaleena S Pradhan
- Department of Biological Sciences, Idaho State University, Pocatello, ID 83209, USA
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He X, Yang X, Yan X, Huang M, Xiang Z, Lou Y. Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27113517. [PMID: 35684454 PMCID: PMC9182099 DOI: 10.3390/molecules27113517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/19/2022] [Accepted: 05/27/2022] [Indexed: 11/16/2022]
Abstract
The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients. Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) was performed to obtain the metabolic profiles of 109 renal transplant patients. A partial least squares (PLS) model was constructed to screen potential biomarkers that could predict the efficacy of tacrolimus. Multinomial logistic regression analysis established a bridge that could quantify the relationship between the efficacy of tacrolimus and biomarkers. The results showed a good correlation between endogenous molecules and the efficacy of tacrolimus. Metabolites such as serum creatinine, mesobilirubinogen, L-isoleucine, 5-methoxyindoleacetate, eicosapentaenoic acid, N2-succinoylarginine, tryptophyl-arginine, and butyric acid were indicated as candidate biomarkers. In addition, the key biomarkers could correctly predict the efficacy of tacrolimus with an accuracy of 82.5%. Finally, we explored the mechanism of individual variation by pathway analysis, which showed that amino acid metabolism was significantly related to the efficacy of tacrolimus. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) showed that there was no difference in key metabolites among different pharmacodynamic groups at 1 month and 3 months after dose adjustment, suggesting that pharmacometabonomics is a useful tool to predict individual differences in pharmacodynamics and thus to facilitate individualized drug therapy.
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Affiliation(s)
- Xiaoying He
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Xi Yang
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Xiaoting Yan
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Mingzhu Huang
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
| | - Zheng Xiang
- School of Pharmaceutical Sciences, Zhejiang University City College, Hangzhou 310000, China
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
| | - Yan Lou
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
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Huang Q, Cao L, Luo N, Qian H, Wei M, Xue L, Zhou Q, Zou B, Tan L, Chu Y, Ma X, Wang C, Wu H, Zhang L, Sun L, Li D, Fan X, Miao L, Zhou G. Predicting Range of Initial Warfarin Dose Based on Pharmacometabolomic and Genetic Inputs. Clin Pharmacol Ther 2021; 110:1585-1594. [PMID: 34460938 DOI: 10.1002/cpt.2407] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 08/22/2021] [Indexed: 12/29/2022]
Abstract
Anticoagulation response to warfarin during the initial stage of therapy varies among individuals. In this study, we aimed to combine pharmacometabolomic and pharmacogenetic data to predict interindividual variation in warfarin response, and, on this basis, suggest an initial daily dose range. The baseline metabolic profiles, genotypes, and clinical information of 160 patients with heart valve disease served as the variables of the function of the last international normalized ratio measured before a patient's discharge (INRday7 ) to screen for potential biomarkers. The partial least-squares model showed that two baseline metabolites (uridine and guanosine), one single-nucleotide variation (VKORC1), and four clinical parameters (weight, creatinine level, amiodarone usage, and initial daily dose) had good predictive power for INRday7 (R2 = 0.753 for the training set, 0.643 for the test set). With these biomarkers, a machine learning algorithm (two-dimensional linear discriminant analysis-multinomial logit model) was used to predict the subgroups with extremely warfarin-sensitive or less warfarin-sensitive patients with a prediction accuracy of 91% for the training set and 90% for the test set, indicating that individual responses to warfarin could be effectively predicted. Based on this model, we have successfully designed an algorithm,"IniWarD," for predicting an effective dose range in the initial 7-day warfarin therapy. The results indicate that the daily dose range suggested by the IniWarD system is more appropriate than that of the conventional genotype-based method, and the risk of bleeding or thrombus due to warfarin could thus be avoided.
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Affiliation(s)
- Qing Huang
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,National Medical Products Administration, Key Laboratory for Impurity Profile of Chemical Drugs, Jiangsu Institute for Food and Drug Control, Nanjing, China
| | - Ling Cao
- National Medical Products Administration, Key Laboratory for Impurity Profile of Chemical Drugs, Jiangsu Institute for Food and Drug Control, Nanjing, China
| | - Nan Luo
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Hanyu Qian
- National Medical Products Administration, Key Laboratory for Impurity Profile of Chemical Drugs, Jiangsu Institute for Food and Drug Control, Nanjing, China
| | - Meng Wei
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
| | - Ling Xue
- Department of Clinical Pharmacology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Qiang Zhou
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
| | - Bingjie Zou
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Li Tan
- National Medical Products Administration, Key Laboratory for Impurity Profile of Chemical Drugs, Jiangsu Institute for Food and Drug Control, Nanjing, China
| | - Yanan Chu
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
| | - Xueping Ma
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
| | - Changtian Wang
- Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Haiwei Wu
- Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Lei Zhang
- Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Lei Sun
- Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Demin Li
- Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Xialei Fan
- National Medical Products Administration, Key Laboratory for Impurity Profile of Chemical Drugs, Jiangsu Institute for Food and Drug Control, Nanjing, China
| | - Liyan Miao
- Department of Clinical Pharmacology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Guohua Zhou
- Department of Clinical Pharmacy, Jinling Hospital, State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Department of Cardio-Thoracic Surgery, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
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Pillozzi S, Bernini A, Palchetti I, Crociani O, Antonuzzo L, Campanacci D, Scoccianti G. Soft Tissue Sarcoma: An Insight on Biomarkers at Molecular, Metabolic and Cellular Level. Cancers (Basel) 2021; 13:cancers13123044. [PMID: 34207243 PMCID: PMC8233868 DOI: 10.3390/cancers13123044] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 06/13/2021] [Accepted: 06/14/2021] [Indexed: 12/18/2022] Open
Abstract
Simple Summary Soft tissue sarcoma is a rare mesenchymal malignancy. Despite the advancements in the fields of radiology, pathology and surgery, these tumors often recur locally and/or with metastatic disease. STS is considered to be a diagnostic challenge due to the large variety of histological subtypes with clinical and histopathological characteristics which are not always distinct. One of the important clinical problems is a lack of useful biomarkers. Therefore, the discovery of biomarkers that can be used to detect tumors or predict tumor response to chemotherapy or radiotherapy could help clinicians provide more effective clinical management. Abstract Soft tissue sarcomas (STSs) are a heterogeneous group of rare tumors. Although constituting only 1% of all human malignancies, STSs represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. Over 100 histologic subtypes have been characterized to date (occurring predominantly in the trunk, extremity, and retroperitoneum), and many more are being discovered due to molecular profiling. STS mortality remains high, despite adjuvant chemotherapy. New prognostic stratification markers are needed to help identify patients at risk of recurrence and possibly apply more intensive or novel treatments. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the most relevant cellular, molecular and metabolic biomarkers for STS, and highlight advances in STS-related biomarker research.
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Affiliation(s)
- Serena Pillozzi
- Medical Oncology Unit, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy;
- Correspondence:
| | - Andrea Bernini
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy;
| | - Ilaria Palchetti
- Department of Chemistry Ugo Schiff, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy;
| | - Olivia Crociani
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy;
| | - Lorenzo Antonuzzo
- Medical Oncology Unit, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy;
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy;
| | - Domenico Campanacci
- Department of Health Science, University of Florence, Largo Brambilla 3, 50134 Florence, Italy;
| | - Guido Scoccianti
- Department of Orthopaedic Oncology and Reconstructive Surgery, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy;
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Di Minno A, Gelzo M, Stornaiuolo M, Ruoppolo M, Castaldo G. The evolving landscape of untargeted metabolomics. Nutr Metab Cardiovasc Dis 2021; 31:1645-1652. [PMID: 33895079 DOI: 10.1016/j.numecd.2021.01.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/08/2021] [Accepted: 01/13/2021] [Indexed: 02/07/2023]
Abstract
AIMS Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics. DATA SYNTHESIS Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available. CONCLUSIONS Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.
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Affiliation(s)
- Alessandro Di Minno
- Dipartimento di Farmacia, Università Degli Studi di Napoli "Federico II", Napoli, 80131, Italy; CEINGE-Biotecnologie Avanzate, Naples, Italy
| | - Monica Gelzo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy
| | - Mariano Stornaiuolo
- Dipartimento di Farmacia, Università Degli Studi di Napoli "Federico II", Napoli, 80131, Italy
| | - Margherita Ruoppolo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy
| | - Giuseppe Castaldo
- CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy.
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Zidi O, Souai N, Raies H, Ben Ayed F, Mezlini A, Mezrioui S, Tranchida F, Sabatier JM, Mosbah A, Cherif A, Shintu L, Kouidhi S. Fecal Metabolic Profiling of Breast Cancer Patients during Neoadjuvant Chemotherapy Reveals Potential Biomarkers. Molecules 2021; 26:2266. [PMID: 33919750 PMCID: PMC8070723 DOI: 10.3390/molecules26082266] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 11/17/2022] Open
Abstract
Breast cancer (BC) is the most common form of cancer among women worldwide. Despite the huge advancements in its treatment, the exact etiology of breast cancer still remains unresolved. There is an increasing interest in the role of the gut microbiome in modulating the anti-cancer therapeutic response. It seems that alteration of the microbiome-derived metabolome potentially promotes carcinogenesis. Taken together, metabolomics has arisen as a fascinating new omics field to screen promising metabolic biomarkers. In this study, fecal metabolite profiling was performed using NMR spectroscopy, to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy (NAC) for breast cancer. Metabolic profiles of feces from patients (n = 8) following chemotherapy treatment cycles were studied. Interestingly, amino acids were found to be upregulated, while lactate and fumaric acid were downregulated in patients under the second and third cycles compared with patients before treatment. Furthermore, short-chain fatty acids (SCFAs) were significantly differentiated between the studied groups. These results strongly suggest that chemotherapy treatment plays a key role in modulating the fecal metabolomic profile of BC patients. In conclusion, we demonstrate the feasibility of identifying specific fecal metabolic profiles reflecting biochemical changes that occur during the chemotherapy treatment. These data give an interesting insight that may complement and improve clinical tools for BC monitoring.
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Affiliation(s)
- Oumaima Zidi
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Nessrine Souai
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Henda Raies
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Farhat Ben Ayed
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Amel Mezlini
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
| | - Sonia Mezrioui
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Fabrice Tranchida
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Jean-Marc Sabatier
- Faculté de Pharmacie, Institute of NeuroPhysiopathology (INP), UMR 7051, 27, Boulevard Jean-Moulin, CEDEX, 13005 Marseille, France
| | - Amor Mosbah
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Ameur Cherif
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Laetitia Shintu
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Soumaya Kouidhi
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
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Jeong HC, Park JE, Seo Y, Kim MG, Shin KH. Urinary Metabolomic Profiling after Administration of Corydalis Tuber and Pharbitis Seed Extract in Healthy Korean Volunteers. Pharmaceutics 2021; 13:522. [PMID: 33918785 PMCID: PMC8069993 DOI: 10.3390/pharmaceutics13040522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 03/26/2021] [Accepted: 04/07/2021] [Indexed: 11/17/2022] Open
Abstract
Pharmacometabolomics is a useful tool to identify biomarkers that can assess and predict response after drug administration. The primary purpose of pharmacometabolomics is to better understand the mechanisms and pathways of a drug by searching endogenous metabolites that have significantly changed after drug administration. DA-9701, a prokinetic agent, consists of Pharbitis seed and Corydalis tube extract and it is known to improve the gastrointestinal motility. Although the overall mechanism of action of DA-9701 remains unclear, its active ingredients, corydaline and chlorogenic acid, act as a 5-HT3 and D2 receptor antagonist and 5-HT4 receptor agonist. To determine the significant metabolites after the administration of DA-9701, a qualitative analysis was carried out using ultra-high performance liquid chromatography coupled with orbitrap mass spectrometer followed by a multivariate analysis. Seven candidates were selected and a statistical analysis of fold change was performed over time. Our study concluded that all the seven selected metabolites were commonly involved in lipid metabolism and purine metabolism.
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Affiliation(s)
- Hyeon-Cheol Jeong
- Research Institute of Pharmaceutical Sciences, College of Pharmacy, Kyungpook National University, Daegu 41566, Korea; (H.-C.J.); (Y.S.)
| | | | - Yohan Seo
- Research Institute of Pharmaceutical Sciences, College of Pharmacy, Kyungpook National University, Daegu 41566, Korea; (H.-C.J.); (Y.S.)
| | - Min-Gul Kim
- Center for Clinical Pharmacology and Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Korea
- Department of Pharmacology, School of Medicine, Jeonbuk National University, Jeonju 54907, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University, Jeonju 54907, Korea
| | - Kwang-Hee Shin
- Research Institute of Pharmaceutical Sciences, College of Pharmacy, Kyungpook National University, Daegu 41566, Korea; (H.-C.J.); (Y.S.)
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Di Gregorio E, Miolo G, Saorin A, Muraro E, Cangemi M, Revelant A, Minatel E, Trovò M, Steffan A, Corona G. Radical Hemithoracic Radiotherapy Induces Systemic Metabolomics Changes That Are Associated with the Clinical Outcome of Malignant Pleural Mesothelioma Patients. Cancers (Basel) 2021; 13:cancers13030508. [PMID: 33572739 PMCID: PMC7866164 DOI: 10.3390/cancers13030508] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/19/2021] [Accepted: 01/25/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Radical hemithoracic radiotherapy represents a promising new advance in the field of radiation oncology and encouraging results have been achieved in the treatment of malignant pleural mesothelioma patients. This study showed that this radiotherapy modality produces significant changes in serum metabolomics profile mainly affecting arginine and polyamine biosynthesis pathways. Interestingly, individual metabolomics alterations were found associated with the clinical overall survival outcome of the radiotherapy treatment. These results highlight metabolomics profile analysis as a powerful prognostic tool useful to better understand the mechanisms underlying the interpatients variability and to identify patients who may receive the best benefit from this specific radiotherapy treatment. Abstract Radical hemithoracic radiotherapy (RHRT) represents an advanced therapeutic option able to improve overall survival of malignant pleural mesothelioma patients. This study aims to investigate the systemic effects of this radiotherapy modality on the serum metabolome and their potential implications in determining the individual clinical outcome. Nineteen patients undergoing RHRT at the dose of 50 Gy in 25 fractions were enrolled. Serum targeted metabolomics profiles were investigated at baseline and the end of radiotherapy by liquid chromatography and tandem mass spectrometry. Univariate and multivariate OPLS-DA analyses were applied to study the serum metabolomics changes induced by RHRT while PLS regression analysis to evaluate the association between such changes and overall survival. RHRT was found to affect almost all investigated metabolites classes, in particular, the amino acids citrulline and taurine, the C14, C18:1 and C18:2 acyl-carnitines as well as the unsaturated long chain phosphatidylcholines PC ae 42:5, PC ae 44:5 and PC ae 44:6 were significantly decreased. The enrichment analysis showed arginine metabolism and the polyamine biosynthesis as the most perturbed pathways. Moreover, specific metabolic changes encompassing the amino acids and acyl-carnitines resulted in association with the clinical outcome accounting for about 60% of the interpatients overall survival variability. This study highlighted that RHRT can induce profound systemic metabolic effects some of which may have a significant prognostic value. The integration of metabolomics in the clinical assessment of the malignant pleural mesothelioma could be useful to better identify the patients who can achieve the best benefit from the RHRT treatment.
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Affiliation(s)
- Emanuela Di Gregorio
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
| | - Gianmaria Miolo
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy;
| | - Asia Saorin
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
| | - Elena Muraro
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
| | - Michela Cangemi
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
| | - Alberto Revelant
- Radiation Oncology Department, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.R.); (E.M.)
| | - Emilio Minatel
- Radiation Oncology Department, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.R.); (E.M.)
| | - Marco Trovò
- Radiation Oncology Department, Azienda Sanitaria Integrata, 33100 Udine, Italy;
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
| | - Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (E.D.G.); (A.S.); (E.M.); (M.C.); (A.S.)
- Correspondence: ; Tel.: +39-0434-659-666
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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Lokhov PG, Balashova EE, Trifonova OP, Maslov DL, Archakov AI. [Ten years of the Russian metabolomics: history of development and achievements]. BIOMEDIT︠S︡INSKAI︠A︡ KHIMII︠A︡ 2020; 66:279-293. [PMID: 32893819 DOI: 10.18097/pbmc20206604279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Metabolomics is one of the omics sciences, the technologies of which are widely used today in many life sciences. Its application influenced the discovery of new biomarkers of diseases, the description of biochemical processes occurring in many organisms, laid the basis for a new generation of clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in the studies of Russian scientists, to demonstrate the main directions and achievements of the Russian science in this field. The review also highlights the history of metabolomics, existing problems and the place of Russian metabolomics in their solution.
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Affiliation(s)
- P G Lokhov
- Institute of Biomedical Chemistry, Moscow, Russia
| | | | | | - D L Maslov
- Institute of Biomedical Chemistry, Moscow, Russia
| | - A I Archakov
- Institute of Biomedical Chemistry, Moscow, Russia
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Integration of Serum Metabolomics into Clinical Assessment to Improve Outcome Prediction of Metastatic Soft Tissue Sarcoma Patients Treated with Trabectedin. Cancers (Basel) 2020; 12:cancers12071983. [PMID: 32708128 PMCID: PMC7409362 DOI: 10.3390/cancers12071983] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/15/2020] [Accepted: 07/17/2020] [Indexed: 12/13/2022] Open
Abstract
Soft tissue sarcomas (STS) are a group of rare and heterogeneous cancers with few diagnostic or prognostic biomarkers. This metabolomics study aimed to identify new serum prognostic biomarkers to improve the prediction of overall survival in patients with metastatic STS. The study enrolled 24 patients treated with the same trabectedin regimen. The baseline serum metabolomics profile, targeted to 68 metabolites encompassing amino acids and bile acids pathways, was quantified by liquid chromatography-tandem mass spectrometry. Correlations between individual metabolomics profiles and overall survival were examined and a risk model to predict survival was built by Cox multivariate regression. The median overall survival of the studied patients was 13.0 months (95% CI, 5.6–23.5). Among all the metabolites investigated, only citrulline and histidine correlated significantly with overall survival. The best Cox risk prediction model obtained integrating metabolomics and clinical data, included citrulline, hemoglobin and patients’ performance status score. It allowed to distinguish patients into a high-risk group with a low median overall survival of 2.1 months and a low- to moderate-risk group with a median overall survival of 19.1 months (p < 0.0001). The results of this metabolomics translation study indicate that citrulline, an amino acid belonging to the arginine metabolism, represents an important metabolic signature that may contribute to explain the high inter-patients overall survival variability of STS patients. The risk prediction model based on baseline serum citrulline, hemoglobin and performance status may represent a new prognostic tool for the early classification of patients with metastatic STS, according to their overall survival expectancy.
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Tayanloo-Beik A, Sarvari M, Payab M, Gilany K, Alavi-Moghadam S, Gholami M, Goodarzi P, Larijani B, Arjmand B. OMICS insights into cancer histology; Metabolomics and proteomics approach. Clin Biochem 2020; 84:13-20. [PMID: 32589887 DOI: 10.1016/j.clinbiochem.2020.06.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/01/2020] [Accepted: 06/09/2020] [Indexed: 02/06/2023]
Abstract
Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.
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Affiliation(s)
- Akram Tayanloo-Beik
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Masoumeh Sarvari
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Moloud Payab
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Kambiz Gilany
- Reproductive Immunology Research Center, Avicenna Research Institute, ACECR, Tehran, Iran; Integrative Oncology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran.
| | - Sepideh Alavi-Moghadam
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Mahdi Gholami
- Department of Toxicology & Pharmacology, Faculty of Pharmacy; Toxicology and Poisoning Research Center, Tehran University of Medical Sciences, Tehran 1416753955, Iran.
| | - Parisa Goodarzi
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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Xing X, Ma P, Huang Q, Qi X, Zou B, Wei J, Tao L, Li L, Zhou G, Song Q. Predicting Pharmacokinetics Variation of Faropenem Using a Pharmacometabonomic Approach. J Proteome Res 2019; 19:119-128. [PMID: 31617722 DOI: 10.1021/acs.jproteome.9b00436] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Xiaoqing Xing
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Pengcheng Ma
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Qing Huang
- Jiangsu Institute for Food and Drug Control, Nanjing 210008, China
| | - Xiemin Qi
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Bingjie Zou
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Jun Wei
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Lei Tao
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Lingjun Li
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Guohua Zhou
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Qinxin Song
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
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21
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Pang H, Jia W, Hu Z. Emerging Applications of Metabolomics in Clinical Pharmacology. Clin Pharmacol Ther 2019; 106:544-556. [DOI: 10.1002/cpt.1538] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 05/18/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Huanhuan Pang
- School of Pharmaceutical Sciences Tsinghua University Beijing China
| | - Wei Jia
- Cancer Biology Program University of Hawaii Cancer Center Honolulu Hawaii USA
| | - Zeping Hu
- School of Pharmaceutical Sciences Tsinghua University Beijing China
- Tsinghua‐Peking Joint Center for Life Sciences Tsinghua University Beijing China
- Beijing Frontier Research Center for Biological Structure Tsinghua University Beijing China
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22
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Pinu FR, Goldansaz SA, Jaine J. Translational Metabolomics: Current Challenges and Future Opportunities. Metabolites 2019; 9:E108. [PMID: 31174372 PMCID: PMC6631405 DOI: 10.3390/metabo9060108] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 06/04/2019] [Accepted: 06/04/2019] [Indexed: 02/06/2023] Open
Abstract
Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.
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Affiliation(s)
- Farhana R Pinu
- The New Zealand Institute for Plant and Food Research, Private Bag 92169, Auckland 1142, New Zealand.
| | - Seyed Ali Goldansaz
- Department of Agriculture, Food and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2P5, Canada.
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada.
| | - Jacob Jaine
- Analytica Laboratories Ltd., Ruakura Research Centre, Hamilton 3216, New Zealand.
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23
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Velenosi TJ, Thomson BKA, Tonial NC, RaoPeters AAE, Mio MA, Lajoie GA, Garg AX, House AA, Urquhart BL. Untargeted metabolomics reveals N, N, N-trimethyl-L-alanyl-L-proline betaine (TMAP) as a novel biomarker of kidney function. Sci Rep 2019; 9:6831. [PMID: 31048706 PMCID: PMC6497643 DOI: 10.1038/s41598-019-42992-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 04/08/2019] [Indexed: 01/19/2023] Open
Abstract
The diagnosis and prognosis of chronic kidney disease (CKD) currently relies on very few circulating small molecules, which can vary by factors unrelated to kidney function. In end-stage renal disease (ESRD), these same small molecules are used to determine dialysis dose and dialytic clearance. Therefore, we aimed to identify novel plasma biomarkers to estimate kidney function in CKD and dialytic clearance in ESRD. Untargeted metabolomics was performed on plasma samples from patients with a single kidney, non-dialysis CKD, ESRD and healthy controls. For ESRD patients, pre- and post-dialysis plasma samples were obtained from several dialysis modalities. Metabolomics analysis revealed over 400 significantly different features in non-dialysis CKD and ESRD plasma compared to controls while less than 35 features were significantly altered in patients with a single kidney. N,N,N-trimethyl-L-alanyl-L-proline betaine (TMAP, AUROC = 0.815) and pyrocatechol sulfate (AUROC = 0.888) outperformed creatinine (AUROC = 0.745) in accurately identifying patients with a single kidney. Several metabolites accurately predicted ESRD; however, when comparing pre-and post-hemodialysis, TMAP was the most robust biomarker of dialytic clearance for all modalities (AUROC = 0.993). This study describes TMAP as a novel potential biomarker of kidney function and dialytic clearance across several hemodialysis modalities.
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Affiliation(s)
- Thomas J Velenosi
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Benjamin K A Thomson
- Division of Nephrology, Department of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Nicholas C Tonial
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Adrien A E RaoPeters
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Megan A Mio
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Gilles A Lajoie
- Department of Biochemistry, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Amit X Garg
- Division of Nephrology, Department of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada.,Lawson Health Research Institute, London, Canada.,Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada
| | - Andrew A House
- Division of Nephrology, Department of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada.,Lawson Health Research Institute, London, Canada
| | - Bradley L Urquhart
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada. .,Division of Nephrology, Department of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Ontario, Canada. .,Lawson Health Research Institute, London, Canada.
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24
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Miolo G, Basile D, Carretta A, Santeufemia DA, Steffan A, Corona G. The metabolomic scent of cancer disease progression in soft tissue sarcoma: A case report. Int J Biol Markers 2019; 34:205-209. [PMID: 30852948 DOI: 10.1177/1724600818817316] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The purpose of this case report is to describe the potential that metabolomics breath analysis may have in cancer disease monitoring. The advances in mass spectrometry instrumentation allow the accurate real-time analysis of volatile metabolites exhaled in the breath. The application of such non-invasive devices may provide innovative and complementary monitoring of the physio-pathological conditions of cancer patients. CASE PRESENTATION A 59-year-old Caucasian woman with spindle cell malignant mesenchymal sarcoma of the presacral region started a first-line therapy with non-pegylated liposomal doxorubicin and ifosfamide associated with pelvic radiant treatment. After two cycles of chemotherapy plus radiotherapy, a significant pulmonary disease progression was reported. Thus, a second-line therapy with trabectedin was administered. However, after only two cycles of treatment a re-staging computed tomography scan reported further cancer disease progression of the target pulmonary lesions as well as occurrence of new satellite bilateral nodules. Real-time analysis of breath exhaled volatile organic compounds, performed by select ion flow tube mass spectrometry (SIFT-MS) during the follow-up of the patient, showed a specific metabolic pattern not observed in the breath of other soft tissue sarcoma patients who achieved clinical benefit from the treatments. CONCLUSIONS This case report revealed the importance of the non-invasive real-time volatile organic compounds breath analysis to distinguish individual specific chemo-resistance phenotypes among soft tissue sarcoma patients. Such observation seems to suggest that breath metabolomics may be particularly useful for monitoring cancer disease progression in soft tissue sarcoma patients where only cost-effective diagnostic tools, such as positron emission tomography and computed tomography, are available.
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Affiliation(s)
- Gianmaria Miolo
- 1 Medical and Preventive Oncology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Debora Basile
- 1 Medical and Preventive Oncology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy.,2 School of Medical Oncology, University of Udine, Udine, Italy
| | | | | | - Agostino Steffan
- 5 Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Giuseppe Corona
- 5 Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
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25
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Yan J, Xiang B, Wang D, Tang S, Teng M, Yan S, Zhou Z, Zhu W. Different Toxic Effects of Racemate, Enantiomers, and Metabolite of Malathion on HepG2 Cells Using High-Performance Liquid Chromatography-Quadrupole-Time-of-Flight-Based Metabolomics. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:1784-1794. [PMID: 30673264 DOI: 10.1021/acs.jafc.8b04536] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Commercial malathion is a racemic mixture that contains two enantiomers, and malathion has adverse effects on mammals. However, whether these two enantiomers have different effects on animals remains unclear. In this study, we tested the effect of racemate, enantiomers, and metabolite of malathion on the metabolomics profile of HepG2 cells. HepG2 cells showed distinct metabolic profiles when treated with rac-malathion, malaoxon, R-(+)-malathion, and S-(-)-malathion, and these differences were attributed to pathways in amino acid metabolism, oxidative stress, and inflammatory response. In addition, malathion treatment caused changes in amino acid levels, antioxidant activity, and expression of inflammatory genes in HepG2 cells. S-(-)-Malathion exhibited stronger metabolic perturbation than its enantiomer and racemate, consistent with the high level of cytotoxicity of S-(-)malathion. R-(+)-Malathion treatment caused significant oxidative stress in HepG2 cells but induced a weaker disturbance in the amino acid metabolism and a pro-inflammatory response compared to S-(-)-malathion and rac-malathion. Malaoxon caused more significant perturbation on antioxidase and a stronger antiapoptosis effect than its parent malathion. Our results provide insight into the risk assessment of malathion enantiomers and metabolites. We also demonstrate that a metabolomics approach can identify the discrepancy of the toxic effects and underlying mechanisms for enantiomers and metabolites of chiral pesticides.
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26
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Tan W, Zhong Z, Carney RP, Men Y, Li J, Pan T, Wang Y. Deciphering the metabolic role of AMPK in cancer multi-drug resistance. Semin Cancer Biol 2018; 56:56-71. [PMID: 30261277 DOI: 10.1016/j.semcancer.2018.09.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 09/02/2018] [Accepted: 09/18/2018] [Indexed: 02/07/2023]
Abstract
Multi-drug resistance (MDR) is a curious bottleneck in cancer research and chemotherapy, whereby some cells rapidly adapt to the tumor microenvironment via a myriad of heterogeneous metabolic activities. Despite being a major impediment to treatment, there is a silver lining: control over metabolic regulation could be an effective approach to overcome or correct resistance pathways. In this critical review, we comprehensively and carefully curated and analyzed large networks of previously identified proteins associated with metabolic adaptation in MDR. We employed data and text mining to study and categorize more than 600 studies in PubMed, with particular focus on AMPK, a central and fundamental modulator in the energy metabolism network that has been specifically implicated in cancer MDR pathways. We have identified one protein set of metabolic adaptations with 137 members closely related to cancer MDR processes, and a second protein set with 165 members derived from AMPK-based networks, with 28 proteins found at the intersection between the two sets. Furthermore, according to genomics analysis of the cancer genome atlas (TCGA) provisional data, the highest alteration frequency (80.0%) of the genes encoding the intersected proteins (28 proteins), ranked three cancer types with quite remarkable significance across 166 studies. The hierarchical relationships of the entire identified gene and protein networks indicate broad correlations in AMPK-mediated metabolic regulation pathways, which we use decipher and depict the metabolic roles of AMPK and demonstrate the potential of metabolic control for therapeutic intervention in MDR.
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Affiliation(s)
- Wen Tan
- School of Pharmacy, Lanzhou University, Lanzhou, Gansu province 730000, China; Micro-Nano Innovations (MiNI) Laboratory, Biomedical Engineering, University of California, Davis, CA 95616, United States
| | - Zhangfeng Zhong
- Center for Developmental Therapeutics, Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60202, United States; Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau SAR, 999078, China
| | - Randy P Carney
- Department of Biomedical Engineering, University of California Davis, Davis, CA 95616, United States
| | - Yongfan Men
- Micro-Nano Innovations (MiNI) Laboratory, Biomedical Engineering, University of California, Davis, CA 95616, United States
| | - Jiannan Li
- Micro-Nano Innovations (MiNI) Laboratory, Biomedical Engineering, University of California, Davis, CA 95616, United States
| | - Tingrui Pan
- Micro-Nano Innovations (MiNI) Laboratory, Biomedical Engineering, University of California, Davis, CA 95616, United States.
| | - Yitao Wang
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau SAR, 999078, China.
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27
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Park JE, Jeong GH, Lee IK, Yoon YR, Liu KH, Gu N, Shin KH. A Pharmacometabolomic Approach to Predict Response to Metformin in Early-Phase Type 2 Diabetes Mellitus Patients. Molecules 2018; 23:molecules23071579. [PMID: 29966242 PMCID: PMC6100517 DOI: 10.3390/molecules23071579] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Revised: 06/22/2018] [Accepted: 06/28/2018] [Indexed: 12/14/2022] Open
Abstract
Metformin is a first-line medication for type 2 diabetes mellitus (T2DM). Based on its universal use, the consideration of inter-individual variability and development of predictive biomarkers are clinically significant. We aimed to identify endogenous markers of metformin responses using a pharmacometabolomic approach. Twenty-nine patients with early-phase T2DM were enrolled and orally administered metformin daily for 6 months. A total of 22 subjects were included in the final analysis. Patients were defined as responders or non-responders based on changes in their glycated haemoglobin A1c (HbA1c) from baseline, over 3 months. Urine metabolites at baseline, as well as at the 3 and 6 month follow-ups after the start of treatment were analysed using gas chromatography-mass spectrometry and evaluated with multivariate analyses. Metabolites distinguishable between the two response groups were obtained at baseline, as well as at the 3 and 6 month follow-ups, and significantly different metabolites were listed as markers of metformin response. Among the identified metabolites, citric acid, myoinositol, and hippuric acid levels showed particularly significant differences between the non-responder and responder groups. We thus identified different metabolite profiles in the two groups of T2DM patients after metformin administration, using pharmacometabolomics. These results might facilitate a better understanding and prediction of metformin response and its variability in individual patients.
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Affiliation(s)
- Jeong-Eun Park
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Korea.
| | - Gui-Hwa Jeong
- Department of Endocrinology, Changwon Fatima Hospital, Changwon 51394, Korea.
| | - In-Kyu Lee
- Department of Endocrinology, Kyungpook National University Hospital, Daegu 41944, Korea.
| | - Young-Ran Yoon
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea.
| | - Kwang-Hyeon Liu
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Korea.
| | - Namyi Gu
- Department of Clinical Pharmacology and Therapeutics, Clinical Trial Center, Dongguk University College of Medicine and Ilsan Hospital, Goyang 10326, Korea.
| | - Kwang-Hee Shin
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Korea.
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Abstract
The new era in systems pharmacology has revolutionized the human biology. Its applicability, precise treatment, adequate response and safety measures fit into all the paradigm of medical/clinical practice. The importance of mathematical models in understanding the disease pathology and epideomology is now being realized. The advent of high-throughput technologies and the emergence of systems biology have resulted in the creation of systems pharmacogenomics and the focus is now on personalized medicine. However, there are some regulatory issues that need to be addresssed; are we ready for this universal adoption? This article details some of the infectious disease pharmacogenomics to the developments in this area.
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29
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Corona G, Cannizzaro R, Miolo G, Caggiari L, De Zorzi M, Repetto O, Steffan A, De Re V. Use of Metabolomics as a Complementary Omic Approach to Implement Risk Criteria for First-Degree Relatives of Gastric Cancer Patients. Int J Mol Sci 2018. [PMID: 29518896 PMCID: PMC5877611 DOI: 10.3390/ijms19030750] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
A positive family history is a strong and consistently reported risk factor for gastric cancer (GC). So far, it has been demonstrated that serum pepsinogens (PGs), and gastrin 17 (G17) are useful for screening individuals at elevated risk to develop atrophic gastritis but they are suboptimal biomarkers to screen individuals for GC. The main purpose of this study was to investigate serum metabolomic profiles to find additional biomarkers that could be integrated with serum PGs and G17 to improve the diagnosis of GC and the selection of first-degree relatives (FDR) at higher risk of GC development. Serum metabolomic profiles included 188 serum metabolites, covering amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexoses. Serum metabolomic profiles were performed with tandem mass spectrometry using the Biocrates AbsoluteIDQ p180 kit. The initial cohort (training set) consisted of n = 49 GC patients and n = 37 FDR. Differential metabolomic signatures among the two groups were investigated by univariate and multivariate partial least square differential analysis. The most significant metabolites were further selected and validated in an independent group of n = 22 GC patients and n = 17 FDR (validation set). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic power and the optimal cut-off for each of the discriminant markers. Multivariate analysis was applied to associate the selected serum metabolites, PGs, G17 and risk factors such as age, gender and Helicobacter pylori (H. pylori) infection with the GC and FDR has been performed and an integrative risk prediction algorithm was developed. In the training set, 40 metabolites mainly belonging to phospholipids and acylcarnitines classes were differentially expressed between GC and FDR. Out of these 40 metabolites, 9 were further confirmed in the validation set. Compared with FDR, GC patients were characterized by lower levels of hydroxylated sphingomyelins (SM(OH)22:1, SM(OH)22:2, SM(OH)24:1) and phosphatidylcholines (PC ae 40:1, PC ae 42:2, PC ae 42:3) and by higher levels of acylcarnitines derivatives (C2, C16, C18:1). The specificity and sensitivity of the integrative risk prediction analysis of metabolites for GC was 73.47% and 83.78% respectively with an area under the curve of the ROC curve of 0.811 that improves to 0.90 when metabolites were integrated with the serum PGs. The predictive risk algorithm composed of the C16, SM(OH)22:1 and PG-II serum levels according to the age of individuals, could be used to stratify FDR at high risk of GC development, and then this can be addressed with diagnostic gastroscopy.
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Affiliation(s)
- Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Renato Cannizzaro
- Oncological Gastroenterology Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Gianmaria Miolo
- Oncology B Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Laura Caggiari
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Mariangela De Zorzi
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Ombretta Repetto
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
| | - Valli De Re
- Immunopathology and Cancer Biomarkers Unit, IRCCS-National Cancer Institute, 33081 Aviano, Italy.
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30
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Miolo G, Muraro E, Caruso D, Crivellari D, Ash A, Scalone S, Lombardi D, Rizzolio F, Giordano A, Corona G. Pharmacometabolomics study identifies circulating spermidine and tryptophan as potential biomarkers associated with the complete pathological response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer. Oncotarget 2018; 7:39809-39822. [PMID: 27223427 PMCID: PMC5129972 DOI: 10.18632/oncotarget.9489] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 04/28/2016] [Indexed: 01/09/2023] Open
Abstract
Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate to guide patient selection for personalized cancer treatments. In the present study, we applied a pharmacometabolomics approach to identify biomarkers potentially associated with pathological complete response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer patients. Based on histological response the 34 patients enrolled in the study were subdivided into two groups: good responders (n = 15) and poor responders (n = 19). The pre-treatment serum targeted metabolomics profile of all patients were analyzed by liquid chromatography tandem mass spectrometry and the differences in the metabolomics profile between the two groups was investigated by multivariate partial least squares discrimination analysis. The most relevant metabolites that differentiate the two groups of patients were spermidine and tryptophan. The Good responders showed higher levels of spermidine and lower amounts of tryptophan compared with the poor responders (p < 0.001, q < 0.05). The serum level of these two metabolites identified patients who achieved a pathological complete response with a sensitivity of 90% [0.79–1.00] and a specificity of 0.87% [0.67–1.00]. These preliminary results support the role played by the individual patients' metabolism in determining the response to cancer treatments and may be a useful tool to select patients that are more likely to benefit from the trastuzumab-paclitaxel treatment.
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Affiliation(s)
- Gianmaria Miolo
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Elena Muraro
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Donatella Caruso
- Department of Pharmacological and Bimolecular Science, University of Milan, Milan, Italy
| | - Diana Crivellari
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Anthony Ash
- Department of Biological Chemistry, Norwich Research Park, Norwich, United Kingdom
| | - Simona Scalone
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Davide Lombardi
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Flavio Rizzolio
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Antonio Giordano
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA, USA
| | - Giuseppe Corona
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
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31
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Duan DD, Wang KX, Zhou YZ, Qin XM, Gao L, Du GH. Baicalein Exerts Beneficial Effects in d-Galactose-Induced Aging Rats Through Attenuation of Inflammation and Metabolic Dysfunction. Rejuvenation Res 2017; 20:506-516. [PMID: 28548620 DOI: 10.1089/rej.2017.1919] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Baicalein is a flavonoid isolated from the roots of Scutellaria baicalensis Georgi. This study aimed to ascertain the effects and potential underlying mechanisms of baicalein in d-galactose (d-gal)-induced aging rat model by integration of behavior examination, biochemical detection, and 1H nuclear magnetic resonance (NMR)-based metabolomic approach. Our findings suggest that baicalein significantly attenuated memory decline in d-gal-induced aging model, as manifested by increasing recognition index in novel object recognition test, shortening latency time, and increasing platform crossings in Morris water maze test. Baicalein significantly inhibited the releases of inflammatory mediators such as nitric oxide, interleukin-6, interleukin-1 beta, and tumor necrosis factor-α in d-gal-induced aging model. Metabolomic study revealed that 10 endogenous metabolites in cerebral cortex were considered as potential biomarkers of baicalein for its protective effect. Further metabolic pathway analysis showed that the metabolic alterations were associated with alanine, aspartate and glutamate metabolism, glycine, serine and threonine metabolism, inositol phosphate metabolism, and energy metabolism. These data indicate that baicalein improves learning and memory dysfunction in d-gal-induced aging rats. This might be achieved through attenuation of inflammation and metabolic dysfunction.
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Affiliation(s)
- Dan-Dan Duan
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China .,2 College of Chemistry and Chemical Engineering, Shanxi University , Taiyuan, PR China
| | - Ke-Xin Wang
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China .,2 College of Chemistry and Chemical Engineering, Shanxi University , Taiyuan, PR China
| | - Yu-Zhi Zhou
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China
| | - Xue-Mei Qin
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China
| | - Li Gao
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China
| | - Guan-Hua Du
- 1 Modern Research Center for Traditional Chinese Medicine, Shanxi University , Taiyuan, PR China .,3 Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing, PR China
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Puchades-Carrasco L, Pineda-Lucena A. Metabolomics Applications in Precision Medicine: An Oncological Perspective. Curr Top Med Chem 2017; 17:2740-2751. [PMID: 28685691 PMCID: PMC5652075 DOI: 10.2174/1568026617666170707120034] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 04/03/2017] [Accepted: 04/11/2017] [Indexed: 12/17/2022]
Abstract
Nowadays, cancer therapy remains limited by the conventional one-size-fits-all approach. In this context, treatment decisions are based on the clinical stage of disease but fail to ascertain the individual´s underlying biology and its role in driving malignancy. The identification of better therapies for cancer treatment is thus limited by the lack of sufficient data regarding the characterization of specific biochemical signatures associated with each particular cancer patient or group of patients. Metabolomics approaches promise a better understanding of cancer, a disease characterized by significant alterations in bioenergetic metabolism, by identifying changes in the pattern of metabolite expression in addition to changes in the concentration of individual metabolites as well as alterations in biochemical pathways. These approaches hold the potential of identifying novel biomarkers with different clinical applications, including the development of more specific diagnostic methods based on the characterization of metabolic subtypes, the monitoring of currently used cancer therapeutics to evaluate the response and the prognostic outcome with a given therapy, and the evaluation of the mechanisms involved in disease relapse and drug resistance. This review discusses metabolomics applications in different oncological processes underlining the potential of this omics approach to further advance the implementation of precision medicine in the oncology area.
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Affiliation(s)
- Leonor Puchades-Carrasco
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe / Instituto de Investigación Sanitaria La Fe, Valencia. Spain
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Chemotherapy-induced gastrointestinal toxicity is associated with changes in serum and urine metabolome and fecal microbiota in male Sprague-Dawley rats. Cancer Chemother Pharmacol 2017. [PMID: 28646338 PMCID: PMC5532424 DOI: 10.1007/s00280-017-3364-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Purpose Chemotherapy-induced gastrointestinal toxicity (CIGT) is a complex process that involves multiple pathophysiological mechanisms. We have previously shown that commonly used chemotherapeutics 5-fluorouracil, oxaliplatin, and irinotecan damage the intestinal mucosa and increase intestinal permeability to iohexol. We hypothesized that CIGT is associated with alterations in fecal microbiota and metabolome. Our aim was to characterize these changes and examine how they relate to the severity of CIGT. Methods A total of 48 male Sprague–Dawley rats were injected intraperitoneally either with 5-fluorouracil (150 mg/kg), oxaliplatin (15 mg/kg), or irinotecan (200 mg/kg). Body weight change was measured daily after drug administration and the animals were euthanized after 72 h. Blood, urine, and fecal samples were collected at baseline and at the end of the experiment. The changes in the composition of fecal microbiota were analyzed with 16S rRNA gene sequencing. Metabolic changes in serum and urine metabolome were measured with 1 mm proton nuclear magnetic resonance (1H-NMR). Results Irinotecan increased the relative abundance of Fusobacteria and Proteobacteria, while 5-FU and oxaliplatin caused only minor changes in the composition of fecal microbiota. All chemotherapeutics increased the levels of serum fatty acids and N(CH3)3 moieties and decreased the levels of Krebs cycle metabolites and free amino acids. Conclusions Chemotherapeutic drugs, 5-fluorouracil, oxaliplatin, and irinotecan, induce several microbial and metabolic changes which may play a role in the pathophysiology of CIGT. The observed changes in intestinal permeability, fecal microbiota, and metabolome suggest the activation of inflammatory processes. Electronic supplementary material The online version of this article (doi:10.1007/s00280-017-3364-z) contains supplementary material, which is available to authorized users.
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Mostafa H, Amin AM, Teh CH, Murugaiyah VA, Arif NH, Ibrahim B. Plasma metabolic biomarkers for discriminating individuals with alcohol use disorders from social drinkers and alcohol-naive subjects. J Subst Abuse Treat 2017; 77:1-5. [PMID: 28476260 DOI: 10.1016/j.jsat.2017.02.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2016] [Revised: 02/07/2017] [Accepted: 02/22/2017] [Indexed: 12/01/2022]
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Livestock metabolomics and the livestock metabolome: A systematic review. PLoS One 2017; 12:e0177675. [PMID: 28531195 PMCID: PMC5439675 DOI: 10.1371/journal.pone.0177675] [Citation(s) in RCA: 202] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 05/01/2017] [Indexed: 12/31/2022] Open
Abstract
Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.
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Amin AM, Sheau Chin L, Azri Mohamed Noor D, SK Abdul Kader MA, Kah Hay Y, Ibrahim B. The Personalization of Clopidogrel Antiplatelet Therapy: The Role of Integrative Pharmacogenetics and Pharmacometabolomics. Cardiol Res Pract 2017; 2017:8062796. [PMID: 28421156 PMCID: PMC5379098 DOI: 10.1155/2017/8062796] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2016] [Accepted: 02/14/2017] [Indexed: 12/12/2022] Open
Abstract
Dual antiplatelet therapy of aspirin and clopidogrel is pivotal for patients undergoing percutaneous coronary intervention. However, the variable platelets reactivity response to clopidogrel may lead to outcome failure and recurrence of cardiovascular events. Although many genetic and nongenetic factors are known, great portion of clopidogrel variable platelets reactivity remain unexplained which challenges the personalization of clopidogrel therapy. Current methods for clopidogrel personalization include CYP2C19 genotyping, pharmacokinetics, and platelets function testing. However, these methods lack precise prediction of clopidogrel outcome, often leading to insufficient prediction. Pharmacometabolomics which is an approach to identify novel biomarkers of drug response or toxicity in biofluids has been investigated to predict drug response. The advantage of pharmacometabolomics is that it does not only predict the response but also provide extensive information on the metabolic pathways implicated with the response. Integrating pharmacogenetics with pharmacometabolomics can give insight on unknown genetic and nongenetic factors associated with the response. This review aimed to review the literature on factors associated with the variable platelets reactivity response to clopidogrel, as well as appraising current methods for the personalization of clopidogrel therapy. We also aimed to review the literature on using pharmacometabolomics approach to predict drug response, as well as discussing the plausibility of using it to predict clopidogrel outcome.
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Affiliation(s)
- Arwa M. Amin
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia
| | - Lim Sheau Chin
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia
| | | | | | - Yuen Kah Hay
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia
| | - Baharudin Ibrahim
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia
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Khalsa J, Duffy LC, Riscuta G, Starke-Reed P, Hubbard VS. Omics for Understanding the Gut-Liver-Microbiome Axis and Precision Medicine. Clin Pharmacol Drug Dev 2017; 6:176-185. [DOI: 10.1002/cpdd.310] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 09/15/2016] [Indexed: 12/14/2022]
Affiliation(s)
- Jag Khalsa
- National Institute on Drug Abuse; National Institutes of Health; Bethesda MD USA
| | - Linda C. Duffy
- National Center for Complementary and Integrative Health; National Institutes of Health; Bethesda MD USA
| | - Gabriela Riscuta
- National Cancer Institute; National Institutes of Health; Bethesda MD USA
| | - Pamela Starke-Reed
- Agricultural Research Service; United States Department of Agriculture; Washington DC USA
| | - Van S. Hubbard
- Formerly National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; Bethesda MD
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Mostafa H, Amin AM, Teh CH, Murugaiyah V, Arif NH, Ibrahim B. Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects. Drug Alcohol Depend 2016; 169:80-84. [PMID: 27788404 DOI: 10.1016/j.drugalcdep.2016.10.016] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2016] [Revised: 10/08/2016] [Accepted: 10/12/2016] [Indexed: 01/17/2023]
Abstract
BACKGROUND Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD. OBJECTIVES To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics. METHOD Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC). RESULTS The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0). CONCLUSION This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy.
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Affiliation(s)
- Hamza Mostafa
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Malaysia
| | - Arwa M Amin
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Malaysia
| | | | | | | | - Baharudin Ibrahim
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Malaysia.
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Wang CZ, Yu C, Wen XD, Chen L, Zhang CF, Calway T, Qiu Y, Wang Y, Zhang Z, Anderson S, Wang Y, Jia W, Yuan CS. American Ginseng Attenuates Colitis-Associated Colon Carcinogenesis in Mice: Impact on Gut Microbiota and Metabolomics. Cancer Prev Res (Phila) 2016; 9:803-811. [PMID: 27443884 DOI: 10.1158/1940-6207.capr-15-0372] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 07/07/2016] [Indexed: 12/18/2022]
Abstract
Inflammatory bowel disease is a risk factor for colorectal cancer initiation and development. In this study, the effects of American ginseng on chemically induced colitis and colon carcinogenesis were evaluated using an azoxymethane (AOM)/dextran sulfate sodium (DSS) mouse model. During the acute phase on day 15, the oral administration of ginseng (15 and 30 mg/kg/day) significantly suppressed AOM/DSS-induced colitis, as demonstrated by the disease activity index and colon tissue histology. During the chronic phase in week 13, AOM/DSS-induced tumor multiplicity was significantly suppressed by ginseng. Ginseng significantly attenuated the increase of inflammatory cytokines, such as IL1α, IL1β, IL6, G-CSF, and GM-CSF. Serum metabolomics data in the PCA plots showed good separation between the AOM/DSS model and ginseng-treated mice, and the most important endogenous metabolite changes were identified. The 16S rRNA data showed that after AOM/DSS, the microbiome community in the model group was obviously changed, and ginseng inhibited these changes. Fecal metabolomics analysis supported these findings. In conclusion, oral ginseng significantly decreased AOM/DSS-induced colitis and colon carcinogenesis by inhibiting inflammatory cytokines and restoring the metabolomics and microbiota profiles accordingly. Selective endogenous small molecules could be used as biomarkers to elucidate the effects of ginseng treatment. Cancer Prev Res; 9(10); 803-11. ©2016 AACR.
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Affiliation(s)
- Chong-Zhi Wang
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. Department of Anesthesia & Critical Care, University of Chicago, Chicago, Illinois
| | - Chunhao Yu
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. School of Life Science and Chemical Engineering, Huaiyin Institute of Technology, Huaian, China
| | - Xiao-Dong Wen
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China
| | - Lina Chen
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. Department of Pharmacy, Nanjing Medical University, Nanjing, China
| | - Chun-Feng Zhang
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China
| | - Tyler Calway
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. Department of Anesthesia & Critical Care, University of Chicago, Chicago, Illinois
| | - Yunping Qiu
- Einstein-Sinai Diabetes Research Center, Albert Einstein College of Medicine, Bronx, New York
| | - Yunwei Wang
- Department of Medicine, University of Chicago, Chicago, Illinois
| | - Zhiyu Zhang
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. Department of Anesthesia & Critical Care, University of Chicago, Chicago, Illinois
| | - Samantha Anderson
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois
| | - Yitao Wang
- State Key Laboratory of Quality Research in Chinese Medicine, and Institute of Chinese Medical Sciences, University of Macau, Macau
| | - Wei Jia
- University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Chun-Su Yuan
- Tang Center for Herbal Medicine Research, University of Chicago, Chicago, Illinois. Department of Anesthesia & Critical Care, University of Chicago, Chicago, Illinois. Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, Illinois.
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Puchades-Carrasco L, Pineda-Lucena A. Metabolomics in pharmaceutical research and development. Curr Opin Biotechnol 2015; 35:73-7. [DOI: 10.1016/j.copbio.2015.04.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Revised: 04/06/2015] [Accepted: 04/07/2015] [Indexed: 12/26/2022]
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Yan Z, Yan R. Increase the accessibility and scale of targeted metabolomics: Construction of a human urinary metabolome-wide multiple reaction monitoring library using directly-coupled reversed-phase and hydrophilic interaction chromatography. Anal Chim Acta 2015; 894:65-75. [DOI: 10.1016/j.aca.2015.08.056] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Revised: 08/26/2015] [Accepted: 08/30/2015] [Indexed: 12/31/2022]
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Huang Q, Aa J, Jia H, Xin X, Tao C, Liu L, Zou B, Song Q, Shi J, Cao B, Yong Y, Wang G, Zhou G. A Pharmacometabonomic Approach To Predicting Metabolic Phenotypes and Pharmacokinetic Parameters of Atorvastatin in Healthy Volunteers. J Proteome Res 2015. [PMID: 26216528 DOI: 10.1021/acs.jproteome.5b00440] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Qing Huang
- China Pharmaceutical
University, Nanjing 210009, China
- Jiangsu Institute
for Food and Drug Control, Nanjing 210008, China
| | - Jiye Aa
- China Pharmaceutical
University, Nanjing 210009, China
| | - Huning Jia
- China Pharmaceutical
University, Nanjing 210009, China
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Xiaoqing Xin
- China Pharmaceutical
University, Nanjing 210009, China
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Chunlei Tao
- Anhui University
of Chinese Medicine, Hefei 230038, China
| | - Linsheng Liu
- Clinical
Pharmacology Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou 215006, China
| | - Bingjie Zou
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Qinxin Song
- China Pharmaceutical
University, Nanjing 210009, China
| | - Jian Shi
- China Pharmaceutical
University, Nanjing 210009, China
| | - Bei Cao
- China Pharmaceutical
University, Nanjing 210009, China
| | - Yonghong Yong
- The First Affiliated
Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Guangji Wang
- China Pharmaceutical
University, Nanjing 210009, China
| | - Guohua Zhou
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
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Abstract
Hypertension is the most prevalent chronic medical condition and a major risk factor for cardiovascular morbidity and mortality. In the majority of hypertensive cases, the underlying cause of hypertension cannot be easily identified because of the heterogeneous, polygenic and multi-factorial nature of hypertension. Metabolomics is a relatively new field of research that has been used to evaluate metabolic perturbations associated with disease, identify disease biomarkers and to both assess and predict drug safety and efficacy. Metabolomics has been increasingly used to characterize risk factors for cardiovascular disease, including hypertension, and it appears to have significant potential for uncovering mechanisms of this complex disease. This review details the analytical techniques, pre-analytical steps and study designs used in metabolomics studies, as well as the emerging role for metabolomics in gaining mechanistic insights into the development of hypertension. Suggestions as to the future direction for metabolomics research in the field of hypertension are also proposed.
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Metabolomics approach reveals effects of antihypertensives and lipid-lowering drugs on the human metabolism. Eur J Epidemiol 2014; 29:325-36. [PMID: 24816436 PMCID: PMC4050296 DOI: 10.1007/s10654-014-9910-7] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2013] [Accepted: 04/28/2014] [Indexed: 01/17/2023]
Abstract
The mechanism of antihypertensive and lipid-lowering drugs on the human organism is still not fully understood. New insights on the drugs’ action can be provided by a metabolomics-driven approach, which offers a detailed view of the physiological state of an organism. Here, we report a metabolome-wide association study with 295 metabolites in human serum from 1,762 participants of the KORA F4 (Cooperative Health Research in the Region of Augsburg) study population. Our intent was to find variations of metabolite concentrations related to the intake of various drug classes and—based on the associations found—to generate new hypotheses about on-target as well as off-target effects of these drugs. In total, we found 41 significant associations for the drug classes investigated: For beta-blockers (11 associations), angiotensin-converting enzyme (ACE) inhibitors (four assoc.), diuretics (seven assoc.), statins (ten assoc.), and fibrates (nine assoc.) the top hits were pyroglutamine, phenylalanylphenylalanine, pseudouridine, 1-arachidonoylglycerophosphocholine, and 2-hydroxyisobutyrate, respectively. For beta-blockers we observed significant associations with metabolite concentrations that are indicative of drug side-effects, such as increased serotonin and decreased free fatty acid levels. Intake of ACE inhibitors and statins associated with metabolites that provide insight into the action of the drug itself on its target, such as an association of ACE inhibitors with des-Arg(9)-bradykinin and aspartylphenylalanine, a substrate and a product of the drug-inhibited ACE. The intake of statins which reduce blood cholesterol levels, resulted in changes in the concentration of metabolites of the biosynthesis as well as of the degradation of cholesterol. Fibrates showed the strongest association with 2-hydroxyisobutyrate which might be a breakdown product of fenofibrate and, thus, a possible marker for the degradation of this drug in the human organism. The analysis of diuretics showed a heterogeneous picture that is difficult to interpret. Taken together, our results provide a basis for a deeper functional understanding of the action and side-effects of antihypertensive and lipid-lowering drugs in the general population.
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Zhu H, Luo M. Chemical structure informing statistical hypothesis testing in metabolomics. Bioinformatics 2014; 30:514-22. [PMID: 24319000 DOI: 10.1093/bioinformatics/btt708] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Metabolomics has been shown as an effective tool to study various biological and biomedical phenotypes, whereas interrogating the inherently noisy metabolite concentration data with limited sample size remains a major challenge. Accumulating evidence suggests that metabolites' structures are relevant to their bioactivities. RESULTS We present a new strategy to boost the statistical power of hypothesis testing in metabolomics by incorporating quantitative molecular descriptors for each metabolite. The strategy selects potentially informative summary molecular descriptors and outputs chemical structure-informed false discovery rates. The effectiveness of the proposed strategy is demonstrated by both simulation studies and a real application. In a metabolomic study on Alzheimer's disease, the posterior inclusion probability for summary molecular descriptors reaches 0.97. By incorporating the structure data, our approach uniquely identifies multiple Alzheimer's disease signatures, which are consistent with existing evidence. These results evidently suggest the value of the proposed approach for metabolomic hypothesis-testing problems. AVAILABILITY AND IMPLEMENTATION A code package implementing the strategy is freely available at https://github.com/HongjieZhu/CIMA.git.
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Affiliation(s)
- Hongjie Zhu
- Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ 08807, USA, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, USA, Exploratory Clinical & Translational Research, Bristol-Myers Squibb, Princeton, NJ 08543, USA and Center for Human Health Assessment, The Hamner Institutes for Health Sciences, Durham, NC 27709, USA
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Fisher E, Boenink M, van der Burg S, Woodbury N. Responsible healthcare innovation: anticipatory governance of nanodiagnostics for theranostics medicine. Expert Rev Mol Diagn 2014; 12:857-70. [DOI: 10.1586/erm.12.125] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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Kim HJ, Yoon YR. Pharmacometabolomics: Current Applications and Future Perspectives. Transl Clin Pharmacol 2014. [DOI: 10.12793/tcp.2014.22.1.8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Hyun-Ju Kim
- Department of Molecular Medicine, Cell and Matrix Research Institute, School of Medicine, Kyungpook National University, Daegu 700-422, Korea and Clinical Trial Center, Kyungpook National University Hospital, Daegu 700-721, Korea
| | - Young-Ran Yoon
- Department of Molecular Medicine, Cell and Matrix Research Institute, School of Medicine, Kyungpook National University, Daegu 700-422, Korea and Clinical Trial Center, Kyungpook National University Hospital, Daegu 700-721, Korea
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Yousri NA, Kastenmüller G, Gieger C, Shin SY, Erte I, Menni C, Peters A, Meisinger C, Mohney RP, Illig T, Adamski J, Soranzo N, Spector TD, Suhre K. Long term conservation of human metabolic phenotypes and link to heritability. Metabolomics 2014; 10:1005-1017. [PMID: 25177233 PMCID: PMC4145193 DOI: 10.1007/s11306-014-0629-y] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Accepted: 01/27/2014] [Indexed: 01/17/2023]
Abstract
Changes in an individual's human metabolic phenotype (metabotype) over time can be indicative of disorder-related modifications. Studies covering several months to a few years have shown that metabolic profiles are often specific for an individual. This "metabolic individuality" and detected changes may contribute to personalized approaches in human health care. However, it is not clear whether such individual metabotypes persist over longer time periods. Here we investigate the conservation of metabotypes characterized by 212 different metabolites of 818 participants from the Cooperative Health Research in the Region of Augsburg; Germany population, taken within a 7-year time interval. For replication, we used paired samples from 83 non-related individuals from the TwinsUK study. Results indicated that over 40 % of all study participants could be uniquely identified after 7 years based on their metabolic profiles alone. Moreover, 95 % of the study participants showed a high degree of metabotype conservation (>70 %) whereas the remaining 5 % displayed major changes in their metabolic profiles over time. These latter individuals were likely to have undergone important biochemical changes between the two time points. We further show that metabolite conservation was positively associated with heritability (rank correlation 0.74), although there were some notable exceptions. Our results suggest that monitoring changes in metabotypes over several years can trace changes in health status and may provide indications for disease onset. Moreover, our study findings provide a general reference for metabotype conservation over longer time periods that can be used in biomarker discovery studies.
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Affiliation(s)
- Noha A. Yousri
- 0000 0004 0582 4340grid.416973.eDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Qatar Foundation, P.O. Box 24144, Doha, Qatar
- 0000 0001 2260 6941grid.7155.6Computers and System Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, Egypt
| | - Gabi Kastenmüller
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Christian Gieger
- 0000 0004 0483 2525grid.4567.0Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - So-Youn Shin
- 0000 0004 0606 5382grid.10306.34Human Genetics, Wellcome Trust Sanger Institute, Hinxton, CB10 1HH UK
- 0000 0004 1936 7603grid.5337.2MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Idil Erte
- 0000 0001 2322 6764grid.13097.3cDepartment of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH UK
| | - Cristina Menni
- 0000 0001 2322 6764grid.13097.3cDepartment of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH UK
| | - Annette Peters
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Christa Meisinger
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | | | - Thomas Illig
- 0000 0000 9529 9877grid.10423.34Hannover Unified Biobank, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany
| | - Jerzy Adamski
- 0000 0004 0483 2525grid.4567.0Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Nicole Soranzo
- 0000 0004 0606 5382grid.10306.34Human Genetics, Wellcome Trust Sanger Institute, Hinxton, CB10 1HH UK
| | - Tim D. Spector
- 0000 0001 2322 6764grid.13097.3cDepartment of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH UK
| | - Karsten Suhre
- 0000 0004 0582 4340grid.416973.eDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Qatar Foundation, P.O. Box 24144, Doha, Qatar
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
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Cacciatore S, Hu X, Viertler C, Kap M, Bernhardt GA, Mischinger HJ, Riegman P, Zatloukal K, Luchinat C, Turano P. Effects of intra- and post-operative ischemia on the metabolic profile of clinical liver tissue specimens monitored by NMR. J Proteome Res 2013; 12:5723-9. [PMID: 24124761 DOI: 10.1021/pr400702d] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Metabolomic profiles of tissues could greatly contribute to advancements in personalized medicine but are influenced by differences in adopted preanalytical procedures; nonhomogeneous pre- and post-excision ischemia times are potential sources of variability. In this study, we monitored the impact of ischemia on the metabolic profiles, acquired with high-resolution magic-angle-spinning (1)H NMR, of 162 human liver samples collected during and up to 6 h after routine surgery. The profiles changed significantly as a function of intraoperative warm ischemia (WI) and postresection cold ischemia (CI) time, with significant variations in the concentration of the same 16 metabolites. Therefore, a tight control of the preanalytical phase is essential for reliable metabolomic analyses of liver diseases. The NMR profiles provide a reliable "fingerprint" of ischemia and have predictive value: the best-performing predictive models are found to discriminate extreme time points of CI (0' vs 360 ') in the training set with cross-validation accuracy of ~90%; samples in the validation cohort can discriminate short (≤60') from long (≥180') CI with an accuracy of ~80%. For WI, the corresponding figures are 95.6 and 92%, respectively. Therefore, ischemia NMR profiles might become a tool for tissue quality control in biobanks.
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Affiliation(s)
- Stefano Cacciatore
- CERM, University of Florence , Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy
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Abstract
BACKGROUND Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics. METHODS A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013. RESULTS Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals. CONCLUSIONS Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, School of Science, University of Greenwich, Chatham Maritime, UK
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