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Chen Y, Lin PH, Freedland SJ, Chi JT. Metabolic Response to Androgen Deprivation Therapy of Prostate Cancer. Cancers (Basel) 2024; 16:1991. [PMID: 38893112 PMCID: PMC11171316 DOI: 10.3390/cancers16111991] [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: 03/29/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024] Open
Abstract
Prostate cancer (PC) stands as the most frequently diagnosed non-skin cancer and ranks as the second highest cause of cancer-related deaths among men in the United States. For those facing non-metastatic PC necessitating intervention, solely local treatments may not suffice, leading to a possible transition toward systemic therapies, including androgen deprivation therapy (ADT), chemotherapy, and therapies targeting androgen. Yet, these systemic treatments often bring about considerable adverse effects. Additionally, it is observed that overweight men are at a higher risk of developing aggressive forms of PC, advancing to metastatic stages, and succumbing to the disease. Consequently, there is a pressing demand for new treatment options that carry fewer side effects and enhance the current standard treatments, particularly for the majority of American men who are overweight or obese. In this article, we will review the metabolic response to ADT and how lifestyle modulation can mitigate these ADT-associated metabolic responses with a particular focus on the two clinical trials, Carbohydrate and Prostate Study 1 (CAPS1) and Carbohydrate and Prostate Study 2 (CAPS2), which tested the effects of low-carbohydrate diets on the metabolic side effects of ADT and PC progression, respectively. Furthermore, we will summarize the findings of serum metabolomic studies to elucidate the potential mechanisms by which ADT and low-carbohydrate diets can affect the metabolic response to mitigate the metabolic side effects while maximizing therapeutic efficacy.
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Affiliation(s)
- Yubin Chen
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27708, USA;
- Center of Applied Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Pao-Hwa Lin
- Department of Medicine, Duke University, Durham, NC 27708, USA;
| | - Stephen J. Freedland
- Center for Integrated Research in Cancer and Lifestyle, Cedars-Sinai, Los Angeles, CA 90048, USA;
- Durham VA Medical Center, Durham, NC 27708, USA
| | - Jen-Tsan Chi
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27708, USA;
- Center of Applied Genomic Technologies, Duke University, Durham, NC 27708, USA
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2
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Dong X, Qu Y, Sheng T, Fan Y, Chen S, Yuan Q, Ma G, Ge Y. HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers. Aging (Albany NY) 2024; 16:7487-7504. [PMID: 38683118 PMCID: PMC11087094 DOI: 10.18632/aging.205779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/03/2024] [Indexed: 05/01/2024]
Abstract
Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.
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Affiliation(s)
- Xun Dong
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Yaoyao Qu
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Tongtong Sheng
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuanming Fan
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Silu Chen
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qinbo Yuan
- Department of Urology, Wuxi Fifth People’s Hospital, Wuxi, China
| | - Gaoxiang Ma
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
- The Clinical Metabolomics Center, China Pharmaceutical University, Nanjing, China
- Deparment of Oncology, Pukou Hospital of Chinese Medicine affiliated to China Pharmaceutical University, Nanjing, China
| | - Yuqiu Ge
- Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, China
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3
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Harewood R, Rothwell JA, Bešević J, Viallon V, Achaintre D, Gicquiau A, Rinaldi S, Wedekind R, Prehn C, Adamski J, Schmidt JA, Jacobs I, Tjønneland A, Olsen A, Severi G, Kaaks R, Katzke V, Schulze MB, Prada M, Masala G, Agnoli C, Panico S, Sacerdote C, Jakszyn PG, Sánchez MJ, Castilla J, Chirlaque MD, Atxega AA, van Guelpen B, Heath AK, Papier K, Tong TYN, Summers SA, Playdon M, Cross AJ, Keski-Rahkonen P, Chajès V, Murphy N, Gunter MJ. Association between pre-diagnostic circulating lipid metabolites and colorectal cancer risk: a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). EBioMedicine 2024; 101:105024. [PMID: 38412638 PMCID: PMC10907191 DOI: 10.1016/j.ebiom.2024.105024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 01/26/2024] [Accepted: 02/05/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Altered lipid metabolism is a hallmark of cancer development. However, the role of specific lipid metabolites in colorectal cancer development is uncertain. METHODS In a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), we examined associations between pre-diagnostic circulating concentrations of 97 lipid metabolites (acylcarnitines, glycerophospholipids and sphingolipids) and colorectal cancer risk. Circulating lipids were measured using targeted mass spectrometry in 1591 incident colorectal cancer cases (55% women) and 1591 matched controls. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between concentrations of individual lipid metabolites and metabolite patterns with colorectal cancer risk. FINDINGS Of the 97 assayed lipids, 24 were inversely associated (nominally p < 0.05) with colorectal cancer risk. Hydroxysphingomyelin (SM (OH)) C22:2 (ORper doubling 0.60, 95% CI 0.47-0.77) and acylakyl-phosphatidylcholine (PC ae) C34:3 (ORper doubling 0.71, 95% CI 0.59-0.87) remained associated after multiple comparisons correction. These associations were unaltered after excluding the first 5 years of follow-up after blood collection and were consistent according to sex, age at diagnosis, BMI, and colorectal subsite. Two lipid patterns, one including 26 phosphatidylcholines and all sphingolipids, and another 30 phosphatidylcholines, were weakly inversely associated with colorectal cancer. INTERPRETATION Elevated pre-diagnostic circulating levels of SM (OH) C22:2 and PC ae C34:3 and lipid patterns including phosphatidylcholines and sphingolipids were associated with lower colorectal cancer risk. This study may provide insight into potential links between specific lipids and colorectal cancer development. Additional prospective studies are needed to validate the observed associations. FUNDING World Cancer Research Fund (reference: 2013/1002); European Commission (FP7: BBMRI-LPC; reference: 313010).
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Affiliation(s)
- Rhea Harewood
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France.
| | - Joseph A Rothwell
- Centre for Epidemiology and Population Health (U1018), Exposome and Heredity Team, Faculté de Médecine, Université Paris-Saclay, UVSQ, INSERM, Gustave Roussy, F-94805, Villejuif, France
| | - Jelena Bešević
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - David Achaintre
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France; School of Plant Sciences and Food Security, Faculty of Biology, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Audrey Gicquiau
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Roland Wedekind
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Jerzy Adamski
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597; Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia
| | - Julie A Schmidt
- Department of Clinical Medicine, Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Olof Palmes Allé 43-45, 8200 Aarhus N, Denmark
| | - Inarie Jacobs
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Diet, Cancer and Health, Strandboulevarden 49, DK-2100, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Anja Olsen
- Danish Cancer Society Research Center, Diet, Cancer and Health, Strandboulevarden 49, DK-2100, Copenhagen, Denmark; The Department of Public Health, University of Aarhus, Aarhus, Denmark
| | - Gianluca Severi
- Centre for Epidemiology and Population Health (U1018), Exposome and Heredity Team, Faculté de Médecine, Université Paris-Saclay, UVSQ, INSERM, Gustave Roussy, F-94805, Villejuif, France; Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Verena Katzke
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany; Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Marcela Prada
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian, 1, 20133, Milan, Italy
| | - Salvatore Panico
- Dipartimento Di Medicina Clinica E Chirurgia Federico Ii University, Naples, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Via Santena 7, 10126, Turin, Italy
| | - Paula Gabriela Jakszyn
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain; Blanquerna School of Health Sciences, Ramon Llull University, Barcelona, Spain
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), 18011, Granada, Spain; Instituto de Investigación Biosanitaria ibs.GRANADA, 18012, Granada, Spain; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Granada, 18071, Granada, Spain
| | - Jesús Castilla
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain; Instituto de Salud Pública de Navarra - IdiSNA, Pamplona, Spain
| | - María-Dolores Chirlaque
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain; Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia University, Murcia, Spain
| | - Amaia Aizpurua Atxega
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastian, Spain; Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain
| | - Bethany van Guelpen
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Keren Papier
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Tammy Y N Tong
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Scott A Summers
- Department of Nutrition and Integrative Physiology and the Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, Utah, USA
| | - Mary Playdon
- Department of Nutrition and Integrative Physiology and the Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, Utah, USA; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, Utah, USA
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Pekka Keski-Rahkonen
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Véronique Chajès
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Neil Murphy
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC), 25 Av. Tony Garnier, 69007, Lyon, France; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
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4
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Fuller H, Zhu Y, Nicholas J, Chatelaine HA, Drzymalla EM, Sarvestani AK, Julián-Serrano S, Tahir UA, Sinnott-Armstrong N, Raffield LM, Rahnavard A, Hua X, Shutta KH, Darst BF. Metabolomic epidemiology offers insights into disease aetiology. Nat Metab 2023; 5:1656-1672. [PMID: 37872285 PMCID: PMC11164316 DOI: 10.1038/s42255-023-00903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 09/06/2023] [Indexed: 10/25/2023]
Abstract
Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.
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Affiliation(s)
- Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yiwen Zhu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jayna Nicholas
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Haley A Chatelaine
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Emily M Drzymalla
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afrand K Sarvestani
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | | | - Usman A Tahir
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Xinwei Hua
- Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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5
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Yu CT, Farhat Z, Livinski AA, Loftfield E, Zanetti KA. Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review. Cancer Epidemiol Biomarkers Prev 2023; 32:1130-1145. [PMID: 37410086 PMCID: PMC10472112 DOI: 10.1158/1055-9965.epi-23-0045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 04/26/2023] [Accepted: 06/28/2023] [Indexed: 07/07/2023] Open
Abstract
An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.
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Affiliation(s)
- Catherine T. Yu
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland
| | - Zeinab Farhat
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Alicia A. Livinski
- National Institutes of Health Library, Office of Research Services, Office of the Director, National Institutes of Health, Bethesda, Maryland
| | - Erikka Loftfield
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Krista A. Zanetti
- Office of Nutrition Research, Division of Program Coordination, Planning, and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, Maryland
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6
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Scheinberg T, Mak B, Butler L, Selth L, Horvath LG. Targeting lipid metabolism in metastatic prostate cancer. Ther Adv Med Oncol 2023; 15:17588359231152839. [PMID: 36743527 PMCID: PMC9893394 DOI: 10.1177/17588359231152839] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 01/05/2023] [Indexed: 02/04/2023] Open
Abstract
Despite key advances in the treatment of prostate cancer (PCa), a proportion of men have de novo resistance, and all will develop resistance to current therapeutics over time. Aberrant lipid metabolism has long been associated with prostate carcinogenesis and progression, but more recently there has been an explosion of preclinical and clinical data which is informing new clinical trials. This review explores the epidemiological links between obesity and metabolic syndrome and PCa, the evidence for altered circulating lipids in PCa and their potential role as biomarkers, as well as novel therapeutic strategies for targeting lipids in men with PCa, including therapies widely used in cardiovascular disease such as statins, metformin and lifestyle modification, as well as novel targeted agents such as sphingosine kinase inhibitors, DES1 inhibitors and agents targeting FASN and beta oxidation.
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Affiliation(s)
- Tahlia Scheinberg
- Medical Oncology, Chris O’Brien Lifehouse, Camperdown NSW, Australia,Advanced Prostate Cancer Group, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia,University of Sydney, Camperdown, NSW, Australia
| | - Blossom Mak
- Medical Oncology, Chris O’Brien Lifehouse, Camperdown NSW, Australia,Advanced Prostate Cancer Group, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia,University of Sydney, Camperdown, NSW, Australia
| | - Lisa Butler
- Prostate Cancer Research Group, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia,South Australian Immunogenomics Cancer Institute and Freemason’s Centre for Male Health and Wellbeing, University of Adelaide, South Australia, Australia
| | - Luke Selth
- South Australian Immunogenomics Cancer Institute and Freemason’s Centre for Male Health and Wellbeing, University of Adelaide, South Australia, Australia,Dame Roma Mitchell Cancer Research Labs, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia,Flinders Health and Medical Research Institute, Flinders University, College of Medicine and Public Health, Bedford Park, Australia
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7
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Wanjari UR, Mukherjee AG, Gopalakrishnan AV, Murali R, Dey A, Vellingiri B, Ganesan R. Role of Metabolism and Metabolic Pathways in Prostate Cancer. Metabolites 2023; 13:183. [PMID: 36837801 PMCID: PMC9962346 DOI: 10.3390/metabo13020183] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 01/21/2023] [Accepted: 01/21/2023] [Indexed: 01/27/2023] Open
Abstract
Prostate cancer (PCa) is the common cause of death in men. The pathophysiological factors contributing to PCa are not well known. PCa cells gain a protective mechanism via abnormal lipid signaling and metabolism. PCa cells modify their metabolism in response to an excessive intake of nutrients to facilitate advancement. Metabolic syndrome (MetS) is inextricably linked to the carcinogenic progression of PCa, which heightens the severity of the disease. It is hypothesized that changes in the metabolism of the mitochondria contribute to the onset of PCa. The studies of particular alterations in the progress of PCa are best accomplished by examining the metabolome of prostate tissue. Due to the inconsistent findings written initially, additional epidemiological research is required to identify whether or not MetS is an aspect of PCa. There is a correlation between several risk factors and the progression of PCa, one of which is MetS. The metabolic symbiosis between PCa cells and the tumor milieu and how this type of crosstalk may aid in the development of PCa is portrayed in this work. This review focuses on in-depth analysis and evaluation of the metabolic changes that occur within PCa, and also aims to assess the effect of metabolic abnormalities on the aggressiveness status and metabolism of PCa.
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Affiliation(s)
- Uddesh Ramesh Wanjari
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Anirban Goutam Mukherjee
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Abilash Valsala Gopalakrishnan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Reshma Murali
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Abhijit Dey
- Department of Life Sciences, Presidency University, Kolkata 700073, India
| | - Balachandar Vellingiri
- Stem Cell and Regenerative Medicine/Translational Research, Department of Zoology, School of Basic Sciences, Central University of Punjab (CUPB), Bathinda 151401, India
| | - Raja Ganesan
- Institute for Liver and Digestive Diseases, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea
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8
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Östman JR, Pinto RC, Ebbels TMD, Thysell E, Hallmans G, Moazzami AA. Identification of prediagnostic metabolites associated with prostate cancer risk by untargeted mass spectrometry-based metabolomics: A case-control study nested in the Northern Sweden Health and Disease Study. Int J Cancer 2022; 151:2115-2127. [PMID: 35866293 PMCID: PMC9804595 DOI: 10.1002/ijc.34223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 06/13/2022] [Accepted: 06/29/2022] [Indexed: 01/07/2023]
Abstract
Prostate cancer (PCa) is the most common cancer form in males in many European and American countries, but there are still open questions regarding its etiology. Untargeted metabolomics can produce an unbiased global metabolic profile, with the opportunity for uncovering new plasma metabolites prospectively associated with risk of PCa, providing insights into disease etiology. We conducted a prospective untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis using prediagnostic fasting plasma samples from 752 PCa case-control pairs nested within the Northern Sweden Health and Disease Study (NSHDS). The pairs were matched by age, BMI, and sample storage time. Discriminating features were identified by a combination of orthogonal projection to latent structures-effect projections (OPLS-EP) and Wilcoxon signed-rank tests. Their prospective associations with PCa risk were investigated by conditional logistic regression. Subgroup analyses based on stratification by disease aggressiveness and baseline age were also conducted. Various free fatty acids and phospholipids were positively associated with overall risk of PCa and in various stratification subgroups. Aromatic amino acids were positively associated with overall risk of PCa. Uric acid was positively, and glucose negatively, associated with risk of PCa in the older subgroup. This is the largest untargeted LC-MS based metabolomics study to date on plasma metabolites prospectively associated with risk of developing PCa. Different subgroups of disease aggressiveness and baseline age showed different associations with metabolites. The findings suggest that shifts in plasma concentrations of metabolites in lipid, aromatic amino acid, and glucose metabolism are associated with risk of developing PCa during the following two decades.
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Affiliation(s)
- Johnny R Östman
- Department of Molecular Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Rui C Pinto
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Timothy M D Ebbels
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Elin Thysell
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden
| | - Ali A Moazzami
- Department of Molecular Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
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9
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Debik J, Isaksen SH, Strømmen M, Spraul M, Schäfer H, Bathen TF, Giskeødegård GF. Effect of Delayed Centrifugation on the Levels of NMR-Measured Lipoproteins and Metabolites in Plasma and Serum Samples. Anal Chem 2022; 94:17003-17010. [PMID: 36454175 DOI: 10.1021/acs.analchem.2c02167] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Metabolic profiling is widely used for large-scale association studies, based on biobank material. The main obstacle to the translation of metabolomic findings into clinical application is the lack of standardization, making validation in independent cohorts challenging. One reason for this is sensitivity of metabolites to preanalytical conditions. We present a systematic investigation of the effect of delayed centrifugation on the levels of NMR-measured metabolites and lipoproteins in serum and plasma samples. Blood was collected from 20 anonymous donors, of which 10 were recruited from an obesity clinic. Samples were stored at room temperature until centrifugation after 30 min, 1, 2, 4, or 8 h, which is within a realistic time scenario in clinical practice. The effect of delaying centrifugation on plasma and serum metabolic concentrations, and on concentrations of lipoprotein subfractions, was investigated. Our results show that lipoproteins are only minimally affected by a delay in centrifugation while metabolite levels are more sensitive to a delay. Metabolites significantly increased or decreased in concentration depending on delay duration. Further, we describe differences in the stability of serum and plasma, showing that plasma is more stable for metabolites, while lipoprotein subfractions are equally stable for both types of matrices.
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Affiliation(s)
- Julia Debik
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim 7491, Norway.,K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Sylvia Hetlelid Isaksen
- Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Magnus Strømmen
- Centre for Obesity Research, Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway.,The Clinical Research Ward, Department for Research and Development, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway.,Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Manfred Spraul
- Bruker BioSpin AIC Division, Ettlingen, Rheinstetten 76287, Germany
| | - Hartmut Schäfer
- Bruker BioSpin AIC Division, Ettlingen, Rheinstetten 76287, Germany
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim 7491, Norway.,Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway
| | - Guro F Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim 7491, Norway.,Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway
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10
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Breeur M, Ferrari P, Dossus L, Jenab M, Johansson M, Rinaldi S, Travis RC, His M, Key TJ, Schmidt JA, Overvad K, Tjønneland A, Kyrø C, Rothwell JA, Laouali N, Severi G, Kaaks R, Katzke V, Schulze MB, Eichelmann F, Palli D, Grioni S, Panico S, Tumino R, Sacerdote C, Bueno-de-Mesquita B, Olsen KS, Sandanger TM, Nøst TH, Quirós JR, Bonet C, Barranco MR, Chirlaque MD, Ardanaz E, Sandsveden M, Manjer J, Vidman L, Rentoft M, Muller D, Tsilidis K, Heath AK, Keun H, Adamski J, Keski-Rahkonen P, Scalbert A, Gunter MJ, Viallon V. Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition. BMC Med 2022; 20:351. [PMID: 36258205 PMCID: PMC9580145 DOI: 10.1186/s12916-022-02553-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/05/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.
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Affiliation(s)
- Marie Breeur
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Pietro Ferrari
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Mazda Jenab
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Mattias Johansson
- Genetics Branch, International Agency for Research on Cancer, 69372 CEDEX 08, Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Tim J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University Hospital and Aarhus University, DK-8200, Aarhus N, Denmark
| | - Kim Overvad
- Department of Public Health, Aarhus University, DK-8000, Aarhus C, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center Diet, Genes and Environment Nutrition and Biomarkers, DK-2100, Copenhagen, Denmark
| | - Cecilie Kyrø
- Danish Cancer Society Research Center Diet, Genes and Environment Nutrition and Biomarkers, DK-2100, Copenhagen, Denmark
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Nasser Laouali
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558, Nuthetal, Germany
| | - Fabian Eichelmann
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558, Nuthetal, Germany
- German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany
| | - Domenico Palli
- Institute of Cancer Research, Prevention and Clinical Network (ISPRO), 50139, Florence, Italy
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, 80131, Naples, Italy
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research, AIRE-ONLUS, 97100, Ragusa, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology Città della Salute e della Scienza University-Hospital, 10126, Turin, Italy
| | - Bas Bueno-de-Mesquita
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720, BA, Bilthoven, The Netherlands
| | - Karina Standahl Olsen
- Department of Community Medicine, UiT The Arctic University of Norway, N-9037, Tromsø, Norway
| | | | - Therese Haugdahl Nøst
- Department of Community Medicine, UiT The Arctic University of Norway, N-9037, Tromsø, Norway
| | - J Ramón Quirós
- Public Health Directorate, 33006, Oviedo, Asturias, Spain
| | - Catalina Bonet
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
| | - Miguel Rodríguez Barranco
- Escuela Andaluza de Salud Pública (EASP), 18011, Granada, Spain
- Instituto de Investigación Biosanitaria ibs. GRANADA, 18012, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
| | - María-Dolores Chirlaque
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia University, 30003, Murcia, Spain
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Navarra Public Health Institute, 31003, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008, Pamplona, Spain
| | - Malte Sandsveden
- Department of Clinical Sciences Malmö Lund University, SE-214 28, Malmö, Sweden
| | - Jonas Manjer
- Departement of Surgery, Skåne University Hospital Malmö, Lund University, SE-214 28, Malmö, Sweden
| | - Linda Vidman
- Department of Radiation Sciences, Oncology Umeå University, SE-901 87, Umeå, Sweden
| | - Matilda Rentoft
- Department of Radiation Sciences, Oncology Umeå University, SE-901 87, Umeå, Sweden
| | - David Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Kostas Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Hector Keun
- Department of Surgery and Cancer, Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, 1000, Ljubljana, Slovenia
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Augustin Scalbert
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France.
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11
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Bai Y, Cao Q, Guan X, Meng H, Feng Y, Wang C, Fu M, Hong S, Zhou Y, Yuan F, Zhang X, He M, Guo H. Metabolic linkages between zinc exposure and lung cancer risk: A nested case-control study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 837:155796. [PMID: 35561928 DOI: 10.1016/j.scitotenv.2022.155796] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 06/15/2023]
Abstract
Epidemiologic studies have suggested that elevated concentrations of zinc are associated with a decreased risk of lung cancer, but the underlying mechanisms remain to be investigated. The metabolites are highly sensitive to environmental stress, which will help to reveal the linkages between zinc exposure and lung cancer risk. We designed a nested case-control study including 101 incident lung cancer cases and 1:2 age- and sex-frequency-matched 202 healthy controls from the Dongfeng-Tongji (DFTJ) cohort. Their plasma level of zinc was determined by using inductively coupled plasma-mass spectrometry (ICP-MS) and plasma profiles of metabolites were detected by using an untargeted metabolomics approach. The generalized linear models (GLM) were applied to assess the associations of plasma zinc with metabolites, and the mediation effects of zinc-related metabolites on zinc-lung cancer association were further testified. The concentrations of 55 metabolites had linear dose-response relationships with plasma zinc at a false discovery rate (FDR) < 0.05, among which L-proline, phosphatidylcholine (PC, 34:2), phosphatidylethanolamine (PE, O-36:5), L-altrose, and sphingomyelin (SM, 40:3) showed different levels between lung cancer cases and healthy controls (fold change = 0.92, 0.95, 1.07, 0.90, and 1.08, respectively, and all P < 0.05). The plasma concentration of SM(40:3) was negatively associated with incident risk of lung cancer [OR(95%CI) = 0.71(0.55, 0.91), P = 0.007] and could mediate 41.7% of the association between zinc and lung cancer risk (P = 0.004). Moreover, compared to the traditional factors, addition of SM(40:3) exerted improved prediction performance for incident risk of lung cancer [AUC(95%CIs) = 0.714(0.654, 0.775) vs. 0.663(0.600, 0.727), P = 0.030]. Our findings revealed metabolic profiles with zinc exposure and provide new insight into the alternations of metabolites underpinning the links between zinc exposure and lung cancer development.
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Affiliation(s)
- Yansen Bai
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; Institute for Chemical Carcinogenesis and State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 511436, China
| | - Qiang Cao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Hua Meng
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yue Feng
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Fangfang Yuan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Meian He
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Huan Guo
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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12
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Grenville ZS, Noor U, His M, Viallon V, Rinaldi S, Aglago EK, Amiano P, Brunkwall L, Chirlaque MD, Drake I, Eichelmann F, Freisling H, Grioni S, Heath AK, Kaaks R, Katzke V, Mayén-Chacon AL, Milani L, Moreno-Iribas C, Pala V, Olsen A, Sánchez MJ, Schulze MB, Tjønneland A, Tsilidis KK, Weiderpass E, Winkvist A, Zamora-Ros R, Key TJ, Smith-Byrne K, Travis RC, Schmidt JA. Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer. Nutrients 2022; 14:3306. [PMID: 36014812 PMCID: PMC9415102 DOI: 10.3390/nu14163306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 11/16/2022] Open
Abstract
Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.
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Affiliation(s)
- Zoe S. Grenville
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Urwah Noor
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Elom K. Aglago
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastian, Spain
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, 20014 San Sebastián, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Louise Brunkwall
- Department of Clinical Sciences, Lund University, 221 84 Malmö, Sweden
| | - María Dolores Chirlaque
- CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia University, 30008 Murcia, Spain
| | - Isabel Drake
- Department of Clinical Sciences, Lund University, 221 84 Malmö, Sweden
- Skåne University Hospital, 214 28 Malmö, Sweden
| | - Fabian Eichelmann
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, Germany
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Alicia K. Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Rudolf Kaaks
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Ana-Lucia Mayén-Chacon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Lorenzo Milani
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, 10124 Turin, Italy
| | - Conchi Moreno-Iribas
- CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Navarra Public Health Institute, 31003 Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
| | - Valeria Pala
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Anja Olsen
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark
- Department of Public Health, Aarhus University, DK-8000 Aarhus, Denmark
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, 18071 Granada, Spain
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, Germany
| | - Anne Tjønneland
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, DK-1353 Copenhagen, Denmark
| | - Konstantinos K. Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, 45110 Ioannina, Greece
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
| | - Anna Winkvist
- Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, 901 87 Umeå, Sweden
- Department of Internal Medicine and Clinical Nutrition, The Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, 08908 Barcelona, Spain
| | - Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Julie A. Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Department of Clinical Epidemiology, Department of Clinical Medicine, University Hospital, Aarhus University and Aarhus, DK-8200 Aarhus N, Denmark
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13
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Wedekind R, Rothwell JA, Viallon V, Keski-Rahkonen P, Schmidt JA, Chajes V, Katzke V, Johnson T, Santucci de Magistris M, Krogh V, Amiano P, Sacerdote C, Redondo-Sánchez D, Huerta JM, Tjønneland A, Pokharel P, Jakszyn P, Tumino R, Ardanaz E, Sandanger TM, Winkvist A, Hultdin J, Schulze MB, Weiderpass E, Gunter MJ, Huybrechts I, Scalbert A. Determinants of blood acylcarnitine concentrations in healthy individuals of the European Prospective Investigation into Cancer and Nutrition. Clin Nutr 2022; 41:1735-1745. [PMID: 35779425 PMCID: PMC9358353 DOI: 10.1016/j.clnu.2022.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 04/07/2022] [Accepted: 05/28/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND & AIMS Circulating levels of acylcarnitines (ACs) have been associated with the risk of various diseases such as cancer and type 2 diabetes. Diet and lifestyle factors have been shown to influence AC concentrations but a better understanding of their biological, lifestyle and metabolic determinants is needed. METHODS Circulating ACs were measured in blood by targeted (15 ACs) and untargeted metabolomics (50 ACs) in 7770 and 395 healthy participants of the European Prospective Investigation into Cancer and Nutrition (EPIC), respectively. Associations with biological and lifestyle characteristics, dietary patterns, self-reported intake of individual foods, estimated intake of carnitine and fatty acids, and fatty acids in plasma phospholipid fraction and amino acids in blood were assessed. RESULTS Age, sex and fasting status were associated with the largest proportion of AC variability (partial-r up to 0.19, 0.18 and 0.16, respectively). Some AC species of medium or long-chain fatty acid moiety were associated with the corresponding fatty acids in plasma (partial-r = 0.24) or with intake of specific foods such as dairy foods containing the same fatty acid. ACs of short-chain fatty acid moiety (propionylcarnitine and valerylcarnitine) were moderately associated with concentrations of branched-chain amino acids (partial-r = 0.5). Intake of most other foods and of carnitine showed little association with AC levels. CONCLUSIONS Our results show that determinants of ACs in blood vary according to their fatty acid moiety, and that their concentrations are related to age, sex, diet, and fasting status. Knowledge on their potential determinants may help interpret associations of ACs with disease risk and inform on potential dietary and lifestyle factors that might be modified for disease prevention.
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Affiliation(s)
- Roland Wedekind
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France.
| | - Joseph A Rothwell
- (CESP), Faculté de Medicine, Université Paris-Saclay, Inserm, Villejuif, France; Institut Gustave Roussy, Villejuif, France
| | - Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Veronique Chajes
- International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Vna Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Theron Johnson
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori di Milano, Milan, Italy
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastian, Spain; Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città Della Salute e Della Scienza University-Hospital, Via Santena 7, 10126 Turin, Italy
| | - Daniel Redondo-Sánchez
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain; Instituto de Investigación Biosanitaria Ibs.GRANADA, 18012 Granada, Spain
| | - José María Huerta
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Pratik Pokharel
- Danish Cancer Society Research Center, Copenhagen, Denmark; Institute for Nutrition Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Paula Jakszyn
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain; Blanquerna School of Health Sciences, Ramon Llull University, Barcelona, Spain
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research AIRE - ONLUS, Ragusa, Italy
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; Navarra Public Health Institute, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Torkjel M Sandanger
- Department of Community Medicine, UiT - the Arctic University of Norway, Langnes, Tromsø, Norway
| | - Anna Winkvist
- Sustainable Health, Dept Epidemiology and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Johan Hultdin
- Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; University of Potsdam, Institute of Nutritional Science, Potsdam, Germany
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Inge Huybrechts
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
| | - Augustin Scalbert
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon, France
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14
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Relevance of Emerging Metabolomics-Based Biomarkers of Prostate Cancer: A Systematic Review. Expert Rev Mol Med 2022; 24:e25. [PMID: 35730322 DOI: 10.1017/erm.2022.20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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15
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Song Y, Cai C, Song Y, Sun X, Liu B, Xue P, Zhu M, Chai W, Wang Y, Wang C, Li M. A Comprehensive Review of Lipidomics and Its Application to Assess Food Obtained from Farm Animals. Food Sci Anim Resour 2022; 42:1-17. [PMID: 35028570 PMCID: PMC8728500 DOI: 10.5851/kosfa.2021.e59] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/10/2021] [Accepted: 10/13/2021] [Indexed: 12/04/2022] Open
Abstract
Lipids are one of the major macronutrients essential for adequate growth and
maintenance of human health. Their structure is not only complex but also
diverse, which makes systematic and holistic analyses challenging; consequently,
little is known regarding the relationship between phenotype and mechanism of
action. In recent years, rapid advancements have been made in the fields of
lipidomics and bioinformatics. In comparison with traditional approaches, mass
spectrometry-based lipidomics can rapidly identify as well as quantify
>1,000 lipid species at the same time, facilitating comprehensive, robust
analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics
is now being widely applied in various fields, particularly food and nutrition
science. In this review, we discuss lipid classification, extraction techniques,
and detection and analysis using lipidomics. We also cover how lipidomics is
being used to assess food obtained from livestock and poultry. The information
included herein should serve as a reference to determine how to characterize
lipids in animal food samples, enhancing our understanding of the application of
lipidomics in the field in animal husbandry.
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Affiliation(s)
- Yinghua Song
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Changyun Cai
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Yingzi Song
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Xue Sun
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Baoxiu Liu
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Peng Xue
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Mingxia Zhu
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Wenqiong Chai
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Yonghui Wang
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Changfa Wang
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
| | - Mengmeng Li
- College of Agronomy, Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 252059, China
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16
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Temprosa M, Moore SC, Zanetti KA, Appel N, Ruggieri D, Mazzilli KM, Chen KL, Kelly RS, Lasky-Su JA, Loftfield E, McClain K, Park B, Trijsburg L, Zeleznik OA, Mathé EA. COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia. Am J Epidemiol 2022; 191:147-158. [PMID: 33889934 PMCID: PMC8897993 DOI: 10.1093/aje/kwab120] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 04/14/2021] [Accepted: 04/14/2021] [Indexed: 12/13/2022] Open
Abstract
Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed. Unlike other Web-based tools, COMETS Analytics enables standardized analyses to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing 2 data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiologic researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Ewy A Mathé
- Correspondence to Dr. Ewy Mathé, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, MD 20850 (e-mail: )
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17
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Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients. Int J Mol Sci 2021; 22:ijms222413540. [PMID: 34948336 PMCID: PMC8707654 DOI: 10.3390/ijms222413540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/10/2021] [Accepted: 12/15/2021] [Indexed: 01/02/2023] Open
Abstract
Malignant cells differ from benign ones in their metabolome and it is largely unknown whether this difference is reflected in the metabolic profile of their microvesicles (MV), which are secreted into the blood of cancer patients. Here, they are present together with MV from the various blood and endothelial cells. Harvesting MV from 78 breast cancer patients (BC) and 30 controls, we characterized the whole blood MV metabolome using targeted and untargeted mass spectrometry. Especially (lyso)-phosphatidylcholines and sphingomyelins were detected in a relevant abundance. Eight metabolites showed a significant discriminatory power between BC and controls. High concentrations of lysoPCaC26:0 and PCaaC38:5 were associated with shorter overall survival. Comparing BC subtype-specific metabolome profiles, 24 metabolites were differentially expressed between luminal A and luminal B. Pathway analysis revealed alterations in the glycerophospholipid metabolism for the whole cancer cohort and in the ether lipid metabolism for the molecular subtype luminal B. Although this mixture of blood-derived MV contains only a minor number of tumor MV, a combination of metabolites was identified that distinguished between BC and controls as well as between molecular subtypes, and was predictive for overall survival. This suggests that these metabolites represent promising biomarkers and, moreover, that they may be functionally relevant for tumor progression.
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18
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Saigusa D, Hishinuma E, Matsukawa N, Takahashi M, Inoue J, Tadaka S, Motoike IN, Hozawa A, Izumi Y, Bamba T, Kinoshita K, Ekroos K, Koshiba S, Yamamoto M. Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values. Metabolites 2021; 11:652. [PMID: 34677367 PMCID: PMC8538467 DOI: 10.3390/metabo11100652] [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: 06/28/2021] [Revised: 09/16/2021] [Accepted: 09/17/2021] [Indexed: 12/18/2022] Open
Abstract
Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.
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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; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- 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; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Masatomo Takahashi
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
| | - Jin Inoue
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Shu Tadaka
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Ikuko N. Motoike
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan;
| | - Yoshihiro Izumi
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Takeshi Bamba
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Kim Ekroos
- Lipidomics Consulting Ltd., 02230 Espoo, Finland;
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- 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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19
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Viallon V, His M, Rinaldi S, Breeur M, Gicquiau A, Hemon B, Overvad K, Tjønneland A, Rostgaard-Hansen AL, Rothwell JA, Lecuyer L, Severi G, Kaaks R, Johnson T, Schulze MB, Palli D, Agnoli C, Panico S, Tumino R, Ricceri F, Verschuren WMM, Engelfriet P, Onland-Moret C, Vermeulen R, Nøst TH, Urbarova I, Zamora-Ros R, Rodriguez-Barranco M, Amiano P, Huerta JM, Ardanaz E, Melander O, Ottoson F, Vidman L, Rentoft M, Schmidt JA, Travis RC, Weiderpass E, Johansson M, Dossus L, Jenab M, Gunter MJ, Lorenzo Bermejo J, Scherer D, Salek RM, Keski-Rahkonen P, Ferrari P. A New Pipeline for the Normalization and Pooling of Metabolomics Data. Metabolites 2021; 11:631. [PMID: 34564446 PMCID: PMC8467830 DOI: 10.3390/metabo11090631] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/10/2021] [Accepted: 09/13/2021] [Indexed: 01/10/2023] Open
Abstract
Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.
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Affiliation(s)
- Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Marie Breeur
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Audrey Gicquiau
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Bertrand Hemon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Kim Overvad
- Department of Public Health, Aarhus University Bartholins Alle 2, DK-8000 Aarhus, Denmark;
| | - Anne Tjønneland
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark; (A.T.); (A.L.R.-H.)
| | | | - Joseph A. Rothwell
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
| | - Lucie Lecuyer
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
| | - Gianluca Severi
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
- Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence, 50134 Florence, Italy
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (R.K.); (T.J.)
| | - Theron Johnson
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (R.K.); (T.J.)
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany;
- Institute of Nutritional Science, University of Potsdam, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), 50139 Florence, Italy;
| | - Claudia Agnoli
- Epidemiology and Prevention Unit Department of Research, Fondazione IRCCS—Istituto Nazionale dei Tumori, 20133 Milan, Italy;
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, 80131 Naples, Italy;
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7), 97100 Ragusa, Italy;
| | - Fulvio Ricceri
- Department of Clinical and Biological Sciences, University of Turin, 10043 Orbassano, Italy;
- Unit of Epidemiology, Regional Health Service ASL TO3, 10095 Grugliasco, Italy
| | - W. M. Monique Verschuren
- National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands; (W.M.M.V.); (P.E.)
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
| | - Peter Engelfriet
- National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands; (W.M.M.V.); (P.E.)
| | - Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
| | - Roel Vermeulen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
- Institute for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, 3584 CM Utrecht, The Netherlands
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, P.O. Box 6050, 9037 Tromsø, Norway; (T.H.N.); (I.U.)
| | - Ilona Urbarova
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, P.O. Box 6050, 9037 Tromsø, Norway; (T.H.N.); (I.U.)
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L’Hospitalet de Llobregat, Spain;
| | - Miguel Rodriguez-Barranco
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain;
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
| | - Pilar Amiano
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastián, Spain
- Biodonostia Health Research Institute, Group of Epidemiology of Chronic and Communicable Diseases, 20014 San Sebastián, Spain
| | - José Maria Huerta
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, 30007 Murcia, Spain
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Navarra Public Health Institute, 31003 Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
| | - Olle Melander
- Department of Clincal Sciences, Lund University, SE-21 428 Malmö, Sweden;
- Department of Emergency and Internal Medicine, Skåne University Hospital, SE-20 502 Malmö, Sweden
| | - Filip Ottoson
- Department of Immunotechnology, Lund University, SE-22 100 Lund, Sweden;
| | - Linda Vidman
- Department of Radiation Sciences, Oncology, Umeå University, SE-901 87 Umeå, Sweden; (L.V.); (M.R.)
| | - Matilda Rentoft
- Department of Radiation Sciences, Oncology, Umeå University, SE-901 87 Umeå, Sweden; (L.V.); (M.R.)
| | - Julie A. Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (J.A.S.); (R.C.T.)
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (J.A.S.); (R.C.T.)
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France;
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France;
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Mazda Jenab
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Marc J. Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Justo Lorenzo Bermejo
- Statistical Genetics Group, Institute of Medical Biometry, University of Heidelberg, 69120 Heidelberg, Germany; (J.L.B.); (D.S.)
| | - Dominique Scherer
- Statistical Genetics Group, Institute of Medical Biometry, University of Heidelberg, 69120 Heidelberg, Germany; (J.L.B.); (D.S.)
| | - Reza M. Salek
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Pietro Ferrari
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
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Dossus L, Kouloura E, Biessy C, Viallon V, Siskos AP, Dimou N, Rinaldi S, Merritt MA, Allen N, Fortner R, Kaaks R, Weiderpass E, Gram IT, Rothwell JA, Lécuyer L, Severi G, Schulze MB, Nøst TH, Crous-Bou M, Sánchez MJ, Amiano P, Colorado-Yohar SM, Gurrea AB, Schmidt JA, Palli D, Agnoli C, Tumino R, Sacerdote C, Mattiello A, Vermeulen R, Heath AK, Christakoudi S, Tsilidis KK, Travis RC, Gunter MJ, Keun HC. Prospective analysis of circulating metabolites and endometrial cancer risk. Gynecol Oncol 2021; 162:475-481. [PMID: 34099314 PMCID: PMC8336647 DOI: 10.1016/j.ygyno.2021.06.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 06/01/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. RESULTS After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. CONCLUSION These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.
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Affiliation(s)
- Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
| | - Eirini Kouloura
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK; European Food Safety Authority, Via Carlo Magno 1A, 43126 Parma, Italy
| | - Carine Biessy
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Vivian Viallon
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Alexandros P Siskos
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK
| | - Niki Dimou
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Melissa A Merritt
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Renee Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elisabete Weiderpass
- Office of the Director, International Agency for Research on Cancer, Lyon, France
| | - Inger T Gram
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Troms, Norway
| | - Joseph A Rothwell
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Lucie Lécuyer
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France; Department of Statistics, Computer Science and Applications "G. Parenti" (DISIA), University of Florence, Italy
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Troms, Norway
| | - Marta Crous-Bou
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Barcelona, Spain; Nutrition and Cancer Group, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston,USA
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Pilar Amiano
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, BioDonostia Research Institute, Donostia-San Sebastian, Spain
| | - Sandra M Colorado-Yohar
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain; Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Aurelio Barricarte Gurrea
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Navarra Public Health Institute, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA) Pamplona, Spain
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Domenico Palli
- Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Cancer Risk Factors and Life-Style Epidemiology Unit, Florence, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP) Ragusa, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Amalia Mattiello
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Transplantation, King's College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Hector C Keun
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK
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21
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Varela-López A, Vera-Ramírez L, Giampieri F, Navarro-Hortal MD, Forbes-Hernández TY, Battino M, Quiles JL. The central role of mitochondria in the relationship between dietary lipids and cancer progression. Semin Cancer Biol 2021; 73:86-100. [DOI: 10.1016/j.semcancer.2021.01.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 12/31/2020] [Accepted: 01/01/2021] [Indexed: 12/20/2022]
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Chi JT, Lin PH, Tolstikov V, Oyekunle T, Alvarado GCG, Ramirez-Torres A, Chen EY, Bussberg V, Chi B, Greenwood B, Sarangarajan R, Narain NR, Kiebish MA, Freedland SJ. The influence of low-carbohydrate diets on the metabolic response to androgen-deprivation therapy in prostate cancer. Prostate 2021; 81:618-628. [PMID: 33949711 PMCID: PMC8167376 DOI: 10.1002/pros.24136] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 03/21/2021] [Accepted: 04/12/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Prostate cancer (PC) is the second most lethal cancer for men. For metastatic PC, standard first-line treatment is androgen deprivation therapy (ADT). While effective, ADT has many metabolic side effects. Previously, we found in serum metabolome analysis that ADT reduced androsterone sulfate, 3-hydroxybutyric acid, acyl-carnitines but increased serum glucose. Since ADT reduced ketogenesis, we speculate that low-carbohydrate diets (LCD) may reverse many ADT-induced metabolic abnormalities in animals and humans. METHODS In a multicenter trial of patients with PC initiating ADT randomized to no diet change (control) or LCD, we previously showed that LCD intervention led to significant weight loss, reduced fat mass, improved insulin resistance, and lipid profiles. To determine whether and how LCD affects ADT-induced metabolic changes, we analyzed serum metabolites after 3-, and 6-months of ADT on LCD versus control. RESULTS We found androsterone sulfate was most consistently reduced by ADT and was slightly further reduced in the LCD arm. Contrastingly, LCD intervention increased 3-hydroxybutyric acid and various acyl-carnitines, counteracting their reduction during ADT. LCD also reversed the ADT-reduced lactic acid, alanine, and S-adenosyl methionine (SAM), elevating glycolysis metabolites and alanine. While the degree of androsterone reduction by ADT was strongly correlated with glucose and indole-3-carboxaldehyde, LCD disrupted such correlations. CONCLUSIONS Together, LCD intervention significantly reversed many ADT-induced metabolic changes while slightly enhancing androgen reduction. Future research is needed to confirm these findings and determine whether LCD can mitigate ADT-linked comorbidities and possibly delaying disease progression by further lowering androgens.
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Affiliation(s)
- Jen-Tsan Chi
- Department of Molecular Genetics and Microbiology, Center for Genomics and Computational Biology
- Corresponding Authors: Jen-Tsan Chi: , 1-919-6684759, 101 Science Drive, DUMC 3382, CIEMAS 2177A, Durham, NC 27708, Stephen J. Freedland: , 1-310-423-3497, 8635, W. Third St., Suite 1070W, Los Angeles, CA 90048
| | - Pao-Hwa Lin
- Department of Medicine, Division of Nephrology, Duke University Medical Center, Durham, North Carolina USA
| | | | - Taofik Oyekunle
- Duke Cancer Institute, Duke University Medical Center, Durham, NC USA
| | | | - Adela Ramirez-Torres
- Center for Integrated Research in Cancer and Lifestyle, Cedars-Sinai, Los Angeles, CA
| | | | | | - Bo Chi
- Department of Molecular Genetics and Microbiology, Center for Genomics and Computational Biology
| | | | | | | | | | - Stephen J. Freedland
- Center for Integrated Research in Cancer and Lifestyle, Cedars-Sinai, Los Angeles, CA
- Durham VA Medical Center, Durham, NC, USA
- Corresponding Authors: Jen-Tsan Chi: , 1-919-6684759, 101 Science Drive, DUMC 3382, CIEMAS 2177A, Durham, NC 27708, Stephen J. Freedland: , 1-310-423-3497, 8635, W. Third St., Suite 1070W, Los Angeles, CA 90048
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Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury. Brain Behav Immun 2021; 95:45-60. [PMID: 33524553 PMCID: PMC9004489 DOI: 10.1016/j.bbi.2021.01.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 12/20/2020] [Accepted: 01/21/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Inflammatory cascades following traumatic brain injury (TBI) can have both beneficial and detrimental effects on recovery. Single biomarker studies do not adequately reflect the major arms of immunity and their relationships to long-term outcomes. Thus, we applied treelet transform (TT) analysis to identify clusters of interrelated inflammatory markers reflecting major components of systemic immune function for which substantial variation exists among individuals with moderate-to-severe TBI. METHODS Serial blood samples from 221 adults with moderate-to-severe TBI were collected over 1-6 months post-injury (n = 607 samples). Samples were assayed for 33 inflammatory markers using Millipore multiplex technology. TT was applied to standardized mean biomarker values generated to identify latent patterns of correlated markers. Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. RESULTS When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS-specific dendrogram and overall dendrogram. CONCLUSIONS TT effectively characterized chronic, systemic immunity among a cohort of individuals with moderate-to-severe TBI. We posit that chronic chemokine levels are effector molecules propagating cellular immune dysfunction, while chronic soluble receptors are inflammatory damage readouts perpetuated, in part, by persistent dysfunctional cellular immunity to impact neuro-recovery.
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Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer. Toxins (Basel) 2021; 13:toxins13070461. [PMID: 34209281 PMCID: PMC8309959 DOI: 10.3390/toxins13070461] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 06/21/2021] [Accepted: 06/29/2021] [Indexed: 02/06/2023] Open
Abstract
Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.
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25
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Crudele L, Piccinin E, Moschetta A. Visceral Adiposity and Cancer: Role in Pathogenesis and Prognosis. Nutrients 2021; 13:nu13062101. [PMID: 34205356 PMCID: PMC8234141 DOI: 10.3390/nu13062101] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/14/2021] [Accepted: 06/16/2021] [Indexed: 12/11/2022] Open
Abstract
The prevalence of being overweight and obese has been expanded dramatically in recent years worldwide. Obesity usually occurs when the energetic introit overtakes energy expenditure from metabolic and physical activity, leading to fat accumulation mainly in the visceral depots. Excessive fat accumulation represents a risk factor for many chronic diseases, including cancer. Adiposity, chronic low-grade inflammation, and hyperinsulinemia are essential factors of obesity that also play a crucial role in tumor onset. In recent years, several strategies have been pointed toward boundary fat accumulation, thus limiting the burden of cancer attributable to obesity. While remodeling fat via adipocytes browning seems a tempting prospect, lifestyle interventions still represent the main pathway to prevent cancer and enhance the efficacy of treatments. Specifically, the Mediterranean Diet stands out as one of the best dietary approaches to curtail visceral adiposity and, therefore, cancer risk. In this Review, the close relationship between obesity and cancer has been investigated, highlighting the biological mechanisms at the basis of this link. Finally, strategies to remodel fat, including browning and lifestyle interventions, have been taken into consideration as a major perspective to limit excess body weight and tumor onset.
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Affiliation(s)
- Lucilla Crudele
- Department of Interdisciplinary Medicine, University of Bari “Aldo Moro”, 70124 Bari, Italy; (L.C.); (E.P.)
- Department of Biomedical Sciences and Human Oncology, University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Elena Piccinin
- Department of Interdisciplinary Medicine, University of Bari “Aldo Moro”, 70124 Bari, Italy; (L.C.); (E.P.)
- Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Antonio Moschetta
- Department of Interdisciplinary Medicine, University of Bari “Aldo Moro”, 70124 Bari, Italy; (L.C.); (E.P.)
- INBB, National Institute for Biostructures and Biosystems, 00136 Rome, Italy
- National Cancer Center, IRCCS Istituto Tumori Giovanni Paolo II, 70124 Bari, Italy
- Correspondence: ; Tel.: +39-080-559-3262
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26
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Nabi MM, Mamun MA, Islam A, Hasan MM, Waliullah ASM, Tamannaa Z, Sato T, Kahyo T, Setou M. Mass spectrometry in the lipid study of cancer. Expert Rev Proteomics 2021; 18:201-219. [PMID: 33793353 DOI: 10.1080/14789450.2021.1912602] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.
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Affiliation(s)
- Md Mahamodun Nabi
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,Institute of Food and Radiation Biology, Atomic Energy Research Establishment, Ganakbari, Savar, Dhaka, Bangladesh
| | - Md Al Mamun
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Ariful Islam
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Md Mahmudul Hasan
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - A S M Waliullah
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Zinat Tamannaa
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Tomohito Sato
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Tomoaki Kahyo
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,International Mass Imaging Center, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Mitsutoshi Setou
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,International Mass Imaging Center, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,Department of Systems Molecular Anatomy, Institute for Medical Photonics Research, Preeminent Medical Photonics Education & Research Center, Hamamatsu, Shizuoka, Japan
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27
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Aftabi Y, Soleymani J, Jouyban A. Efficacy of Analytical Technologies in Metabolomics Studies of the Gastrointestinal Cancers. Crit Rev Anal Chem 2021; 52:1593-1605. [PMID: 33757389 DOI: 10.1080/10408347.2021.1901646] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
According to the reports of the World Health Organization and the International Agency for Research on Cancer, cancer is the second leading cause of human death worldwide. However, early-stage detection of cancers can efficiently enhance the chance of therapy and saving lives. Metabolomics strategies apply a variety of approaches to discover new potential diagnoses, prognoses, and/or therapeutic biomarkers of various diseases. Metabolomics aims to identify and measure different low-molecular-weight biomolecules in physiological environments. In these studies, special metabolites are extracted from biological samples and identified using analytical techniques. Afterward, using data processing programs discovering significantly associated biomarkers is pursued. In the present review, we aimed to discuss recently reported analytical approaches on the metabolomics studies of gastrointestinal cancers including gastric, colorectal, and esophageal cancers. The gas- and liquid-chromatography with different detectors have been shown that are the main analytical techniques and for metabolites quantification, nuclear magnetic resonance has been utilized as a master method.
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Affiliation(s)
- Younes Aftabi
- Tuberculosis and Lung Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.,Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Jafar Soleymani
- Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.,Liver and Gastrointestinal Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Abolghasem Jouyban
- Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.,Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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28
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Yi X, Li Y, Hu X, Wang F, Liu T. Changes in phospholipid metabolism in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells. J Cancer 2021; 12:2893-2902. [PMID: 33854590 PMCID: PMC8040901 DOI: 10.7150/jca.48906] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 03/04/2021] [Indexed: 01/05/2023] Open
Abstract
Background: To explore the changes in lipids in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells and develop an inexpensive and rapid technique for screening lipid-based biomarkers of prostate cancer. Methods: Exosomes were extracted from LnCap, PC3 and DU-145 cells, and their lipid composition was analyzed quantitatively using high-throughput mass spectrometry. Exosomes released by LnCap prostate cancer cells were also purified using a modified procedure based on polyethylene glycol (PEG) precipitation. Results: Exosomes extracted from LnCap cells contained higher proportions of phosphatidyl choline, phosphatidyl ethanolamine and phosphatidyl inositol lipids than whole LnCap cells. Lysophosphatidylcholine, a harmful intermediate product of phosphatidylcholine metabolism in vivo, was not found in LnCap cells but in exosomes. Phospholipids were different in exosomes from LnCap, PC3 and DU-145 prostate cancer cells. The main lipid pathways involved, i.e., glycerophospholipid metabolism, autophagy, and ferroptosis pathways, were also different in these cells. Exosomes isolated by this modified PEG precipitation technique were similar in purity to those obtained using a commercial kit. Conclusions: This study demonstrates that phosphatidylcholine and its harmful product lysophosphatidylcholine may play important roles in hormone-sensitive prostate cancer. Phospholipid exosome metabolism was changed in hormone-sensitive and hormone-resistant prostate cancer cells. The LPC, lipid pathway of autophagy and ferroptosis may act as therapeutic targets. The possibility of purifying prostate cancer cell exosomes using modified PEG precipitation is suitable for cancer screening.
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Affiliation(s)
- Xianlin Yi
- Department of Urology, The Affiliated Cancer Hospital of Guangxi Medical University & Guangxi Cancer Research Institute, Nanning 530021,China
| | - You Li
- Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, PR China.,Life science institute of East China Normal University, Shanghai 200241, P.R. China
| | - XiaoGang Hu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, P.R. China
| | - FuBing Wang
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, P.R. China
| | - Tiangang Liu
- Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, PR China.,Wuhan infectious diseases and cancer research center, Chinese Academy of Medical Sciences, Wuhan 430071, P.R. China.,Hubei Engineering Laboratory for Synthetic Microbiology, Wuhan Institute of Biotechnology, Wuhan 430075, PR China
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29
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Schmidt JA, Fensom GK, Rinaldi S, Scalbert A, Gunter MJ, Holmes MV, Key TJ, Travis RC. NMR Metabolite Profiles in Male Meat-Eaters, Fish-Eaters, Vegetarians and Vegans, and Comparison with MS Metabolite Profiles. Metabolites 2021; 11:121. [PMID: 33672542 PMCID: PMC7923783 DOI: 10.3390/metabo11020121] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 02/12/2021] [Accepted: 02/14/2021] [Indexed: 12/23/2022] Open
Abstract
Metabolomics may help to elucidate mechanisms underlying diet-disease relationships and identify novel risk factors for disease. To inform the design and interpretation of such research, evidence on diet-metabolite associations and cross-assay comparisons is needed. We aimed to compare nuclear magnetic resonance (NMR) metabolite profiles between meat-eaters, fish-eaters, vegetarians and vegans, and to compare NMR measurements to those from mass spectrometry (MS), clinical chemistry and capillary gas-liquid chromatography (GC). We quantified 207 serum NMR metabolite measures in 286 male participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Oxford cohort. Using univariate and multivariate analyses, we found that metabolite profiles varied by diet group, especially for vegans; the main differences compared to meat-eaters were lower levels of docosahexaenoic acid, total n-3 and saturated fatty acids, cholesterol and triglycerides in very-low-density lipoproteins, various lipid factions in high-density lipoprotein, sphingomyelins, tyrosine and creatinine, and higher levels of linoleic acid, total n-6, polyunsaturated fatty acids and alanine. Levels in fish-eaters and vegetarians differed by metabolite measure. Concentrations of 13 metabolites measured using both NMR and MS, clinical chemistry or GC were mostly similar. In summary, vegans' metabolite profiles were markedly different to those of men consuming animal products. The studied metabolomics platforms are complementary, with limited overlap between metabolite classes.
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Affiliation(s)
- Julie A. Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (G.K.F.); (T.J.K.); (R.C.T.)
| | - Georgina K. Fensom
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (G.K.F.); (T.J.K.); (R.C.T.)
- Department of International Development, University of Oxford, Oxford OX1 3TB, UK
| | - Sabina Rinaldi
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, 69372 Lyon, France; (S.R.); (A.S.); (M.J.G.)
| | - Augustin Scalbert
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, 69372 Lyon, France; (S.R.); (A.S.); (M.J.G.)
| | - Marc J. Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, 69372 Lyon, France; (S.R.); (A.S.); (M.J.G.)
| | - Michael V. Holmes
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK;
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (G.K.F.); (T.J.K.); (R.C.T.)
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (G.K.F.); (T.J.K.); (R.C.T.)
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30
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Wood PL, Muir W, Christmann U, Gibbons P, Hancock CL, Poole CM, Emery AL, Poovey JR, Hagg C, Scarborough JH, Christopher JS, Dixon AT, Craney DJ. Lipidomics of the chicken egg yolk: high-resolution mass spectrometric characterization of nutritional lipid families. Poult Sci 2021; 100:887-899. [PMID: 33518142 PMCID: PMC7858096 DOI: 10.1016/j.psj.2020.11.020] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 10/26/2020] [Accepted: 11/09/2020] [Indexed: 02/06/2023] Open
Abstract
While previous studies have characterized the fatty acids and global lipid families of the chicken egg yolk, there have been no publications characterizing the individual lipids in these lipid families. Such an in-depth characterization of egg yolk lipids is essential to define the potential benefits of egg yolk consumption for the supply of structural and anti-inflammatory lipids. Historically, the major focus has been on the cholesterol content of eggs and the potential negative health benefits of this lipid, while ignoring the essential roles of cholesterol in membranes and as a precursor to other essential sterols. A detailed analysis of egg yolk lipids, using high-resolution mass spectrometric analyses and tandem mass spectrometry to characterize the fatty acid substituents of complex structural lipids, was used to generate the first in-depth characterization of individual lipids within lipid families. Egg yolks were isolated from commercial eggs (Full Circle Market) and lipids extracted with methyl-t-butylether before analyses via high-resolution mass spectrometry. This analytical platform demonstrates that chicken egg yolks provide a rich nutritional source of complex structural lipids required for lipid homeostasis. These include dominant glycerophosphocholines (GPC) (34:2 and 36:2), plasmalogen GPC (34:1, 36:1), glycerophosphoethanolamines (GPE) 38:4 and 36:2), plasmalogen GPE (36:2 and 34:1), glycerophosphoserines (36:2 and 38:4), glycerophosphoinositols (38:4), glycerophosphoglycerols (36:2), N-acylphosphatidylethanolamines (NAPE) (56:6), plasmalogen NAPE (54:4 and 56:6), sphingomyelins (16:0), ceramides (22:0 and 24:0), cyclic phosphatidic acids (16:0 and 18:0), monoacylglycerols (18:1 and 18:2), diacylglycerols (36:3 and 36:2), and triacylglycerols (52:3). Our data indicate that the egg yolk is a rich source of structural and energy-rich lipids. In addition, the structural lipids possess ω-3 and ω-6 fatty acids that are essential precursors of endogenous anti-inflammatory lipid mediators. These data indicate that eggs are a valuable nutritional addition to the diets of individuals that do not have cholesterol issues.
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Affiliation(s)
- Paul L Wood
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA.
| | - William Muir
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Undine Christmann
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Philippa Gibbons
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Courtney L Hancock
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Cathleen M Poole
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Audrey L Emery
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Jesse R Poovey
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Casey Hagg
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Jon H Scarborough
- DeBusk College of Osteopathic Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Jordon S Christopher
- DeBusk College of Osteopathic Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Alexander T Dixon
- DeBusk College of Osteopathic Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
| | - Dustin J Craney
- DeBusk College of Osteopathic Medicine, Lincoln Memorial University, Harrogate, TN 37752, USA
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31
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Stepien M, Keski-Rahkonen P, Kiss A, Robinot N, Duarte-Salles T, Murphy N, Perlemuter G, Viallon V, Tjønneland A, Rostgaard-Hansen AL, Dahm CC, Overvad K, Boutron-Ruault MC, Mancini FR, Mahamat-Saleh Y, Aleksandrova K, Kaaks R, Kühn T, Trichopoulou A, Karakatsani A, Panico S, Tumino R, Palli D, Tagliabue G, Naccarati A, Vermeulen RCH, Bueno-de-Mesquita HB, Weiderpass E, Skeie G, Ramón Quirós J, Ardanaz E, Mokoroa O, Sala N, Sánchez MJ, Huerta JM, Winkvist A, Harlid S, Ohlsson B, Sjöberg K, Schmidt JA, Wareham N, Khaw KT, Ferrari P, Rothwell JA, Gunter M, Riboli E, Scalbert A, Jenab M. Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study. Int J Cancer 2021; 148:609-625. [PMID: 32734650 DOI: 10.1002/ijc.33236] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 06/16/2020] [Accepted: 06/26/2020] [Indexed: 12/19/2022]
Abstract
Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.
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Affiliation(s)
- Magdalena Stepien
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Pekka Keski-Rahkonen
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Agneta Kiss
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Nivonirina Robinot
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Talita Duarte-Salles
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
- Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Gabriel Perlemuter
- INSERM UMRS U996 - Intestinal Microbiota, Macrophages and Liver Inflammation, Clamart, France
- Université Paris-Sud, Clamart, France
- AP-HP, Hepato-gastroenterology and Nutrition, Antoine-Béclère Hospital, Clamart, France
| | - Vivian Viallon
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Anne Tjønneland
- Diet, Genes and Environment Unit, Danish Cancer Society Research Center, Copenhagen, Denmark
| | | | - Christina C Dahm
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Marie-Christine Boutron-Ruault
- CESP, Faculté de médecine-Université Paris-Sud, Faculté de médecine-UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | - Francesca Romana Mancini
- CESP, Faculté de médecine-Université Paris-Sud, Faculté de médecine-UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | - Yahya Mahamat-Saleh
- CESP, Faculté de médecine-Université Paris-Sud, Faculté de médecine-UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | - Krasimira Aleksandrova
- Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbrücke, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Dept. of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Anna Karakatsani
- Hellenic Health Foundation, Athens, Greece
- Second Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, "ATTIKON" University Hospital, Haidari, Greece
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP) Ragusa, Ragusa, Italy
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Giovanna Tagliabue
- Lombardy Cancer Registry Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Alessio Naccarati
- Molecular and Genetic Epidemiology Unit, Italian Institute for Genomic Medicine (IIGM) Torino, Torino, Italy
| | - Roel C H Vermeulen
- Institute of Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Hendrik Bastiaan Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Elisabete Weiderpass
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Guri Skeie
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | | | - Eva Ardanaz
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Olatz Mokoroa
- CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Public Health Division of Gipuzkoa, Biodonostia Research Institute, San Sebastian, Spain
| | - Núria Sala
- Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Program and Translational Research Laboratory, Catalan Institute of Oncology (IDIBELL), Barcelona, Spain
| | - Maria-Jose Sánchez
- CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs. Granada. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | - José María Huerta
- CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
| | - Anna Winkvist
- The Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
- Department of Public Health and Clinical Medicine, Nutrition Research, Umeå University, Umeå, Sweden
| | - Sophia Harlid
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Bodil Ohlsson
- Skåne University Hospital, Department of Internal Medicine, Lund University, Malmö, Sweden
| | - Klas Sjöberg
- Skåne University Hospital, Department of Gastroenterology and Nutrition, Lund University, Malmö, Sweden
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Kay-Tee Khaw
- University of Cambridge, School of Clinical Medicine, Clinical Gerontology Unit, Addenbrooke's Hospital, Cambridge, UK
| | - Pietro Ferrari
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Joseph A Rothwell
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
- Institut Gustave Roussy, Villejuif, France
| | - Marc Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Augustin Scalbert
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Mazda Jenab
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
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32
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Metabolic regulation of prostate cancer heterogeneity and plasticity. Semin Cancer Biol 2020; 82:94-119. [PMID: 33290846 DOI: 10.1016/j.semcancer.2020.12.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 11/12/2020] [Accepted: 12/03/2020] [Indexed: 02/07/2023]
Abstract
Metabolic reprogramming is one of the main hallmarks of cancer cells. It refers to the metabolic adaptations of tumor cells in response to nutrient deficiency, microenvironmental insults, and anti-cancer therapies. Metabolic transformation during tumor development plays a critical role in the continued tumor growth and progression and is driven by a complex interplay between the tumor mutational landscape, epigenetic modifications, and microenvironmental influences. Understanding the tumor metabolic vulnerabilities might open novel diagnostic and therapeutic approaches with the potential to improve the efficacy of current tumor treatments. Prostate cancer is a highly heterogeneous disease harboring different mutations and tumor cell phenotypes. While the increase of intra-tumor genetic and epigenetic heterogeneity is associated with tumor progression, less is known about metabolic regulation of prostate cancer cell heterogeneity and plasticity. This review summarizes the central metabolic adaptations in prostate tumors, state-of-the-art technologies for metabolic analysis, and the perspectives for metabolic targeting and diagnostic implications.
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33
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Butler LM, Perone Y, Dehairs J, Lupien LE, de Laat V, Talebi A, Loda M, Kinlaw WB, Swinnen JV. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention. Adv Drug Deliv Rev 2020; 159:245-293. [PMID: 32711004 PMCID: PMC7736102 DOI: 10.1016/j.addr.2020.07.013] [Citation(s) in RCA: 284] [Impact Index Per Article: 71.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 07/02/2020] [Accepted: 07/16/2020] [Indexed: 02/06/2023]
Abstract
With the advent of effective tools to study lipids, including mass spectrometry-based lipidomics, lipids are emerging as central players in cancer biology. Lipids function as essential building blocks for membranes, serve as fuel to drive energy-demanding processes and play a key role as signaling molecules and as regulators of numerous cellular functions. Not unexpectedly, cancer cells, as well as other cell types in the tumor microenvironment, exploit various ways to acquire lipids and extensively rewire their metabolism as part of a plastic and context-dependent metabolic reprogramming that is driven by both oncogenic and environmental cues. The resulting changes in the fate and composition of lipids help cancer cells to thrive in a changing microenvironment by supporting key oncogenic functions and cancer hallmarks, including cellular energetics, promoting feedforward oncogenic signaling, resisting oxidative and other stresses, regulating intercellular communication and immune responses. Supported by the close connection between altered lipid metabolism and the pathogenic process, specific lipid profiles are emerging as unique disease biomarkers, with diagnostic, prognostic and predictive potential. Multiple preclinical studies illustrate the translational promise of exploiting lipid metabolism in cancer, and critically, have shown context dependent actionable vulnerabilities that can be rationally targeted, particularly in combinatorial approaches. Moreover, lipids themselves can be used as membrane disrupting agents or as key components of nanocarriers of various therapeutics. With a number of preclinical compounds and strategies that are approaching clinical trials, we are at the doorstep of exploiting a hitherto underappreciated hallmark of cancer and promising target in the oncologist's strategy to combat cancer.
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Affiliation(s)
- Lisa M Butler
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, SA 5005, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
| | - Ylenia Perone
- Department of Surgery and Cancer, Imperial College London, Imperial Centre for Translational and Experimental Medicine, London, UK
| | - Jonas Dehairs
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Leslie E Lupien
- Program in Experimental and Molecular Medicine, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 037560, USA
| | - Vincent de Laat
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Ali Talebi
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Massimo Loda
- Pathology and Laboratory Medicine, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - William B Kinlaw
- The Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 03756, USA
| | - Johannes V Swinnen
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium.
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34
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Röhnisch HE, Kyrø C, Olsen A, Thysell E, Hallmans G, Moazzami AA. Identification of metabolites associated with prostate cancer risk: a nested case-control study with long follow-up in the Northern Sweden Health and Disease Study. BMC Med 2020; 18:187. [PMID: 32698845 PMCID: PMC7376662 DOI: 10.1186/s12916-020-01655-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 06/03/2020] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Prostate cancer is the second most frequently diagnosed cancer in men. Metabolomics can potentially provide new insights into the aetiology of prostate cancer by identifying new metabolic risk factors. This study investigated the prospective association between plasma metabolite concentrations and prostate cancer risk, both overall and by stratifying for disease aggressiveness and baseline age. METHODS In a case-control study nested in the Northern Sweden Health and Disease Study, pre-diagnostic concentrations of 148 plasma metabolites were determined using targeted mass spectrometry- and nuclear magnetic resonance-based metabolomics in 777 prostate cancer cases (follow-up ≥ 5 years) and 777 matched controls. Associations between prostate cancer risk and metabolite concentrations were investigated using conditional logistic regression conditioned on matching factors (body mass index, age and sample storage time). Corrections for multiple testing were performed using false discovery rate (20%) and Bonferroni. Metabolomics analyses generated new hypotheses, which were investigated by leveraging food frequency questionnaires (FFQs) and oral glucose tolerance tests performed at baseline. RESULTS After correcting for multiple testing, two lysophosphatidylcholines (LPCs) were positively associated with risk of overall prostate cancer (all ages and in older subjects). The strongest association was for LPC C17:0 in older subjects (OR = 2.08; 95% CI 1.45-2.98; p < 0.0001, significant also after the Bonferroni correction). Observed associations with risk of overall prostate cancer in younger subjects were positive for glycine and inverse for pyruvate. For aggressive prostate cancer, there were positive associations with six glycerophospholipids (LPC C17:0, LPC C20:3, LPC C20:4, PC ae C38:3, PC ae C38:4 and PC ae C40:2), while there was an inverse association with acylcarnitine C18:2. Moreover, plasma LPC C17:0 concentrations positively correlated with estimated dietary intake of fatty acid C17:0 from the FFQs. The associations between glycerophospholipids and prostate cancer were stronger in case-controls with normal glucose tolerance. CONCLUSIONS Several glycerophospholipids were positively associated with risk of overall and aggressive prostate cancer. The strongest association was observed for LPC C17:0. The associations between glycerophospholipids and prostate cancer risk were stronger in case-controls with normal glucose tolerance, suggesting a link between the glucose metabolism status and risk of prostate cancer.
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Affiliation(s)
- Hanna E Röhnisch
- Department of Molecular Sciences, Swedish University of Agricultural Sciences, Box 7015, 75007, Uppsala, Sweden
| | - Cecilie Kyrø
- Unit of Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anja Olsen
- Unit of Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Elin Thysell
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden
| | - Ali A Moazzami
- Department of Molecular Sciences, Swedish University of Agricultural Sciences, Box 7015, 75007, Uppsala, Sweden.
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35
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Semba RD. Perspective: The Potential Role of Circulating Lysophosphatidylcholine in Neuroprotection against Alzheimer Disease. Adv Nutr 2020; 11:760-772. [PMID: 32190891 PMCID: PMC7360459 DOI: 10.1093/advances/nmaa024] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 01/02/2020] [Accepted: 02/19/2020] [Indexed: 12/28/2022] Open
Abstract
Alzheimer disease (AD), the most common cause of dementia, is a progressive disorder involving cognitive impairment, loss of learning and memory, and neurodegeneration affecting wide areas of the cerebral cortex and hippocampus. AD is characterized by altered lipid metabolism in the brain. Lower concentrations of long-chain PUFAs have been described in the frontal cortex, entorhinal cortex, and hippocampus in the brain in AD. The brain can synthesize only a few fatty acids; thus, most fatty acids must enter the brain from the blood. Recent studies show that PUFAs such as DHA (22:6) are transported across the blood-brain barrier (BBB) in the form of lysophosphatidylcholine (LPC) via a specific LPC receptor at the BBB known as the sodium-dependent LPC symporter 1 (MFSD2A). Higher dietary PUFA intake is associated with decreased risk of cognitive decline and dementia in observational studies; however, PUFA supplementation, with fatty acids esterified in triacylglycerols did not prevent cognitive decline in clinical trials. Recent studies show that LPC is the preferred carrier of PUFAs across the BBB into the brain. An insufficient pool of circulating LPC containing long-chain fatty acids could potentially limit the supply of long-chain fatty acids to the brain, including PUFAs such as DHA, and play a role in the pathobiology of AD. Whether adults with low serum LPC concentrations are at greater risk of developing cognitive decline and AD remains a major gap in knowledge. Preventing and treating cognitive decline and the development of AD remain a major challenge. The LPC pathway is a promising area for future investigators to identify modifiable risk factors for AD.
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Affiliation(s)
- Richard D Semba
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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36
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Knuplez E, Marsche G. An Updated Review of Pro- and Anti-Inflammatory Properties of Plasma Lysophosphatidylcholines in the Vascular System. Int J Mol Sci 2020; 21:ijms21124501. [PMID: 32599910 PMCID: PMC7350010 DOI: 10.3390/ijms21124501] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/19/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022] Open
Abstract
Lysophosphatidylcholines are a group of bioactive lipids heavily investigated in the context of inflammation and atherosclerosis development. While present in plasma during physiological conditions, their concentration can drastically increase in certain inflammatory states. Lysophosphatidylcholines are widely regarded as potent pro-inflammatory and deleterious mediators, but an increasing number of more recent studies show multiple beneficial properties under various pathological conditions. Many of the discrepancies in the published studies are due to the investigation of different species or mixtures of lysophatidylcholines and the use of supra-physiological concentrations in the absence of serum or other carrier proteins. Furthermore, interpretation of the results is complicated by the rapid metabolism of lysophosphatidylcholine (LPC) in cells and tissues to pro-inflammatory lysophosphatidic acid. Interestingly, most of the recent studies, in contrast to older studies, found lower LPC plasma levels associated with unfavorable disease outcomes. Being the most abundant lysophospholipid in plasma, it is of utmost importance to understand its physiological functions and shed light on the discordant literature connected to its research. LPCs should be recognized as important homeostatic mediators involved in all stages of vascular inflammation. In this review, we want to point out potential pro- and anti-inflammatory activities of lysophospholipids in the vascular system and highlight recent discoveries about the effect of lysophosphatidylcholines on immune cells at the endothelial vascular interface. We will also look at their potential clinical application as biomarkers.
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Affiliation(s)
- Eva Knuplez
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
- Correspondence: (E.K.); (G.M.); Tel.: +43-385-74115 (E.K.); +43-316-385-74128 (G.M.)
| | - Gunther Marsche
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
- Correspondence: (E.K.); (G.M.); Tel.: +43-385-74115 (E.K.); +43-316-385-74128 (G.M.)
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37
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Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective. Metabolites 2020; 10:metabo10060249. [PMID: 32549391 PMCID: PMC7345423 DOI: 10.3390/metabo10060249] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 06/02/2020] [Accepted: 06/04/2020] [Indexed: 12/11/2022] Open
Abstract
The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.
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38
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Chi JT, Lin PH, Tolstikov V, Oyekunle T, Chen EY, Bussberg V, Greenwood B, Sarangarajan R, Narain NR, Kiebish MA, Freedland SJ. Metabolomic effects of androgen deprivation therapy treatment for prostate cancer. Cancer Med 2020; 9:3691-3702. [PMID: 32232974 PMCID: PMC7286468 DOI: 10.1002/cam4.3016] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 03/10/2020] [Accepted: 03/10/2020] [Indexed: 12/11/2022] Open
Abstract
Androgen deprivation therapy (ADT) is the main treatment strategy for men with metastatic prostate cancer (PC). However, ADT is associated with various metabolic disturbances, including impaired glucose tolerance, insulin resistance and weight gain, increasing risk of diabetes and cardiovascular death. Much remains unknown about the metabolic pathways and disturbances altered by ADT and the mechanisms. We assessed the metabolomic effects of ADT in the serum of 20 men receiving ADT. Sera collected before (baseline), 3 and 6 months after initiation of ADT was used for the metabolomics and lipidomics analyses. The ADT‐associated metabolic changes were identified by univariable and multivariable statistical analysis, ANOVA, and Pearson correlation. We found multiple key changes. First, ADT treatments reduced the steroid synthesis as reflected by the lower androgen sulfate and other steroid hormones. Greater androgen reduction was correlated with higher serum glucose levels, supporting the diabetogenic role of ADT. Second, ADT consistently decreased the 3‐hydroxybutyric acid and ketogenesis. Third, many acyl‐carnitines were reduced, indicating the effects on the fatty acid metabolism. Fourth, ADT was associated with a corresponding reduction in 3‐formyl indole (a.k.a. indole‐3‐carboxaldehyde), a microbiota‐derived metabolite from the dietary tryptophan. Indole‐3‐carboxaldehyde is an agonist for the aryl hydrocarbon receptor and regulates the mucosal reactivity and inflammation. Together, these ADT‐associated metabolomic analyses identified reduction in steroid synthesis and ketogenesis as prominent features, suggesting therapeutic potential of restricted ketogenic diets, though this requires formal testing. ADT may also impact the microbial production of indoles related to the immune pathways. Future research is needed to determine the functional impact and underlying mechanisms to prevent ADT‐linked comorbidities and diabetes risk.
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Affiliation(s)
- Jen-Tsan Chi
- Department of Molecular Genetics and Microbiology, Center for Genomics and Computational Biology, Duke University Medical Center, Durham, NC, USA
| | - Pao-Hwa Lin
- Department of Medicine, Division of Nephrology, Duke University Medical Center, Durham, NC, USA
| | | | - Taofik Oyekunle
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
| | | | | | | | | | | | | | - Stephen J Freedland
- Center for Integrated Research in Cancer and Lifestyle, Cedars-Sinai, Los Angeles, CA, USA.,Durham VA Medical Center, Durham, NC, USA
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39
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Zoni E, Minoli M, Bovet C, Wehrhan A, Piscuoglio S, Ng CKY, Gray PC, Spahn M, Thalmann GN, Kruithof-de Julio M. Preoperative plasma fatty acid metabolites inform risk of prostate cancer progression and may be used for personalized patient stratification. BMC Cancer 2019; 19:1216. [PMID: 31842810 PMCID: PMC6916032 DOI: 10.1186/s12885-019-6418-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 11/29/2019] [Indexed: 02/06/2023] Open
Abstract
Background Little is known about the relationship between the metabolite profile of plasma from pre-operative prostate cancer (PCa) patients and the risk of PCa progression. In this study we investigated the association between pre-operative plasma metabolites and risk of biochemical-, local- and metastatic-recurrence, with the aim of improving patient stratification. Methods We conducted a case-control study within a cohort of PCa patients recruited between 1996 and 2015. The age-matched primary cases (n = 33) were stratified in low risk, high risk without progression and high risk with progression as defined by the National Comprehensive Cancer Network. These samples were compared to metastatic (n = 9) and healthy controls (n = 10). The pre-operative plasma from primary cases and the plasma from metastatic patients and controls were assessed with untargeted metabolomics by LC-MS. The association between risk of progression and metabolite abundance was calculated using multivariate Cox proportional-hazard regression and the relationship between metabolites and outcome was calculated using median cut-off normalized values of metabolite abundance by Log-Rank test using the Kaplan Meier method. Results Medium-chain acylcarnitines (C6-C12) were positively associated with the risk of PSA progression (p = 0.036, median cut-off) while long-chain acylcarnitines (C14-C16) were inversely associated with local (p = 0.034) and bone progression (p = 0.0033). In primary cases, medium-chain acylcarnitines were positively associated with suberic acid, which also correlated with the risk of PSA progression (p = 0.032, Log-Rank test). In the metastatic samples, this effect was consistent for hexanoylcarnitine, L.octanoylcarnitine and decanoylcarnitine. Medium-chain acylcarnitines and suberic acid displayed the same inverse association with tryptophan, while indoleacetic acid, a breakdown product of tryptophan metabolism was strongly associated with PSA (p = 0.0081, Log-Rank test) and lymph node progression (p = 0.025, Log-Rank test). These data were consistent with the increased expression of indoleamine 2,3 dioxygenase (IDO1) in metastatic versus primary samples (p = 0.014). Finally, functional experiments revealed a synergistic effect of long chain fatty acids in combination with dihydrotestosterone administration on the transcription of androgen responsive genes. Conclusions This study strengthens the emerging link between fatty acid metabolism and PCa progression and suggests that measuring levels of medium- and long-chain acylcarnitines in pre-operative patient plasma may provide a basis for improving patient stratification.
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Affiliation(s)
- Eugenio Zoni
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland
| | - Martina Minoli
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland
| | - Cédric Bovet
- University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Anne Wehrhan
- University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Salvatore Piscuoglio
- Institute of Pathology, University Hospital Basel, University of Basel, Basel, Switzerland.,Visceral Surgery Research Laboratory, Clarunis, Department of Biomedicine, University of Basel, Basel, Switzerland.,Clarunis Universitäres Bauchzentrum Basel, Basel, Switzerland
| | - Charlotte K Y Ng
- Visceral Surgery Research Laboratory, Clarunis, Department of Biomedicine, University of Basel, Basel, Switzerland.,Department for BioMedical Research, Oncogenomics, University of Bern, Bern, Switzerland
| | - Peter C Gray
- ScienceMedia Inc, 8910 University Center Ln Suite 400, San Diego, CA, 92122, USA
| | - Martin Spahn
- Zentrum für Urologie Zürich und Prostatakarzinomzentrum Hirslanden ZürichKlinik Hirslanden, Zürich, Switzerland.,Department of Urology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - George N Thalmann
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland.,Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Marianna Kruithof-de Julio
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland. .,Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
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