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Hamed MA, Wasinger V, Wang Q, Graham P, Malouf D, Bucci J, Li Y. Prostate cancer-derived extracellular vesicles metabolic biomarkers: Emerging roles for diagnosis and prognosis. J Control Release 2024; 371:126-145. [PMID: 38768661 DOI: 10.1016/j.jconrel.2024.05.029] [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: 02/05/2024] [Revised: 04/23/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management.
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Affiliation(s)
- Mahmoud Assem Hamed
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Valerie Wasinger
- Bioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Centre, UNSW Sydney, Kensington, NSW 2052, Australia
| | - Qi Wang
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Peter Graham
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - David Malouf
- Department of Urology, St, George Hospital, Kogarah, NSW 2217, Australia
| | - Joseph Bucci
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Yong Li
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia.
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2
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Li YD, Ren ZJ, Gou YQ, Wei-Tan, Liu C, Gao L. Development and validation of a model for predicting the risk of prostate cancer. Int Urol Nephrol 2024; 56:973-980. [PMID: 37831385 DOI: 10.1007/s11255-023-03837-1] [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: 06/25/2023] [Accepted: 10/03/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Abnormal hematologic parameters before patients undergoing prostate biopsy play a pivotal role in guiding the surgical management of prostate cancer (PCa) incidence. This study aims to establish the first nomogram for predicting PCa risk for better surgical management. METHODS We retrospectively reviewed and analyzed the data including basic information, preoperative hematologic parameters, and imaging examination of 540 consecutive patients who underwent transrectal ultrasound (TRUS)-guided prostate biopsy for elevated prostate-specific antigen (PSA) in our medical center between 2017 and 2021. Logistic regression analysis was used to determine the risk factors for PCa occurrence, and the nomogram was constructed to predict PCa occurrence. Finally, the data including 121 consecutive patients in 2022 were prospectively collected to further verify the results. RESULTS In retrospective analyses, univariate and multivariate logistic analyses identified that three variables including age, diabetes, and De Ritis ratio (aspartate transaminase/alanine transaminase, AST/ALT) were determined to be significantly associated with PCa occurrence. A nomogram was constructed based on these variables for predicting the risk of PCa, and a satisfied predictive accuracy of the model was determined with a C-index of 0.765, supported by a prospective validation group with a C-index of 0.736. The Decision curve analysis showed promising clinical application. In addition, our results also showed that the De Ritis ratio was significantly correlated with the clinical stage of PCa patients, including T, N, and M stages, but insignificantly related to the Gleason score. CONCLUSIONS The increased De Ritis ratio was significantly associated with the risk and clinical stage of PCa and this nomogram with good discrimination could effectively improve individualized surgical management for patient underdoing prostate biopsy.
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Affiliation(s)
- Ya-Dong Li
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Zheng-Ju Ren
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Yuan-Qing Gou
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Wei-Tan
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Chuan Liu
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
| | - Liang Gao
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
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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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4
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Wang W, Rong Z, Wang G, Hou Y, Yang F, Qiu M. Cancer metabolites: promising biomarkers for cancer liquid biopsy. Biomark Res 2023; 11:66. [PMID: 37391812 DOI: 10.1186/s40364-023-00507-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 05/27/2023] [Indexed: 07/02/2023] Open
Abstract
Cancer exerts a multitude of effects on metabolism, including the reprogramming of cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation of cancer cells and adaptation to the tumor microenvironment. There is a growing body of evidence suggesting that aberrant metabolites play pivotal roles in tumorigenesis and metastasis, and have the potential to serve as biomarkers for personalized cancer therapy. Importantly, high-throughput metabolomics detection techniques and machine learning approaches offer tremendous potential for clinical oncology by enabling the identification of cancer-specific metabolites. Emerging research indicates that circulating metabolites have great promise as noninvasive biomarkers for cancer detection. Therefore, this review summarizes reported abnormal cancer-related metabolites in the last decade and highlights the application of metabolomics in liquid biopsy, including detection specimens, technologies, methods, and challenges. The review provides insights into cancer metabolites as a promising tool for clinical applications.
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Affiliation(s)
- Wenxiang Wang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China
| | - Zhiwei Rong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, 100191, China
| | - Guangxi Wang
- Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yan Hou
- Department of Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Clinical Research Center, Peking University, Beijing, 100191, China
| | - Fan Yang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China.
| | - Mantang Qiu
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China.
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Xu Z, Marchionni L, Wang S. MultiNEP: a multi-omics network enhancement framework for prioritizing disease genes and metabolites simultaneously. Bioinformatics 2023; 39:btad333. [PMID: 37216914 PMCID: PMC10250081 DOI: 10.1093/bioinformatics/btad333] [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: 12/30/2022] [Revised: 04/28/2023] [Accepted: 05/19/2023] [Indexed: 05/24/2023] Open
Abstract
MOTIVATION Many studies have successfully used network information to prioritize candidate omics profiles associated with diseases. The metabolome, as the link between genotypes and phenotypes, has accumulated growing attention. Using a "multi-omics" network constructed with a gene-gene network, a metabolite-metabolite network, and a gene-metabolite network to simultaneously prioritize candidate disease-associated metabolites and gene expressions could further utilize gene-metabolite interactions that are not used when prioritizing them separately. However, the number of metabolites is usually 100 times fewer than that of genes. Without accounting for this imbalance issue, we cannot effectively use gene-metabolite interactions when simultaneously prioritizing disease-associated metabolites and genes. RESULTS Here, we developed a Multi-omics Network Enhancement Prioritization (MultiNEP) framework with a weighting scheme to reweight contributions of different sub-networks in a multi-omics network to effectively prioritize candidate disease-associated metabolites and genes simultaneously. In simulation studies, MultiNEP outperforms competing methods that do not address network imbalances and identifies more true signal genes and metabolites simultaneously when we down-weight relative contributions of the gene-gene network and up-weight that of the metabolite-metabolite network to the gene-metabolite network. Applications to two human cancer cohorts show that MultiNEP prioritizes more cancer-related genes by effectively using both within- and between-omics interactions after handling network imbalance. AVAILABILITY AND IMPLEMENTATION The developed MultiNEP framework is implemented in an R package and available at: https://github.com/Karenxzr/MultiNep.
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Affiliation(s)
- Zhuoran Xu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, United States
| | - Luigi Marchionni
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, United States
| | - Shuang Wang
- Department of Biostatistics, Columbia University, New York, NY 10032, United States
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6
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Bedia C, Dalmau N, Nielsen LK, Tauler R, Marín de Mas I. A Multi-Level Systems Biology Analysis of Aldrin's Metabolic Effects on Prostate Cancer Cells. Proteomes 2023; 11:proteomes11020011. [PMID: 37092452 PMCID: PMC10123692 DOI: 10.3390/proteomes11020011] [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: 02/10/2023] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 04/25/2023] Open
Abstract
Although numerous studies support a dose-effect relationship between Endocrine disruptors (EDs) and the progression and malignancy of tumors, the impact of a chronic exposure to non-lethal concentrations of EDs in cancer remains unknown. More specifically, a number of studies have reported the impact of Aldrin on a variety of cancer types, including prostate cancer. In previous studies, we demonstrated the induction of the malignant phenotype in DU145 prostate cancer (PCa) cells after a chronic exposure to Aldrin (an ED). Proteins are pivotal in the regulation and control of a variety of cellular processes. However, the mechanisms responsible for the impact of ED on PCa and the role of proteins in this process are not yet well understood. Here, two complementary computational approaches have been employed to investigate the molecular processes underlying the acquisition of malignancy in prostate cancer. First, the metabolic reprogramming associated with the chronic exposure to Aldrin in DU145 cells was studied by integrating transcriptomics and metabolomics via constraint-based metabolic modeling. Second, gene set enrichment analysis was applied to determine (i) altered regulatory pathways and (ii) the correlation between changes in the transcriptomic profile of Aldrin-exposed cells and tumor progression in various types of cancer. Experimental validation confirmed predictions revealing a disruption in metabolic and regulatory pathways. This alteration results in the modification of protein levels crucial in regulating triacylglyceride/cholesterol, linked to the malignant phenotype observed in Aldrin-exposed cells.
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Affiliation(s)
- Carmen Bedia
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
| | - Nuria Dalmau
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
| | - Lars K Nielsen
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Romà Tauler
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
| | - Igor Marín de Mas
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Lyngby, Denmark
- CAG Center for Endotheliomics, Copenhagen University Hospital, 2100 Rigshospitalet, Denmark
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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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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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Huang J, Zhao B, Weinstein SJ, Albanes D, Mondul AM. Metabolomic profile of prostate cancer-specific survival among 1812 Finnish men. BMC Med 2022; 20:362. [PMID: 36280842 PMCID: PMC9594924 DOI: 10.1186/s12916-022-02561-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Abnormal metabolism and perturbations in metabolic pathways play significant roles in the development and progression of prostate cancer; however, comprehensive metabolomic analyses of human data are lacking and needed to elucidate the interrelationships. METHODS We examined the serum metabolome in relation to prostate cancer survival in a cohort of 1812 cases in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Using an ultrahigh-performance LC-MS/MS platform, we identified 961 known metabolites in prospectively collected serum. Median survival time from diagnosis to prostate cancer-specific death (N=472) was 6.6 years (interquartile range=2.9-11.1 years). Cox proportional hazards regression models estimated hazard ratios and 95% confidence intervals of the associations between the serum metabolites (in quartiles) and prostate cancer death, adjusted for age at baseline and diagnosis, disease stage, and Gleason sum. In order to calculate risk scores, we first randomly divided the metabolomic data into a discovery set (70%) and validated in a replication set (30%). RESULTS Overall, 49 metabolites were associated with prostate cancer survival after Bonferroni correction. Notably, higher levels of the phospholipid choline, amino acid glutamate, long-chain polyunsaturated fatty acid (n6) arachidonate (20:4n6), and glutamyl amino acids gamma-glutamylglutamate, gamma-glutamylglycine, and gamma-glutamylleucine were associated with increased risk of prostate cancer-specific mortality (fourth versus first quartile HRs=2.07-2.14; P-values <5.2×10-5). By contrast, the ascorbate/aldarate metabolite oxalate, xenobiotics S-carboxymethyl-L-cysteine, fibrinogen cleavage peptides ADpSGEGDFXAEGGGVR and fibrinopeptide B (1-12) were related to reduced disease-specific mortality (fourth versus first quartile HRs=0.82-0.84; P-value <5.2×10-5). Further adjustment for years from blood collection to cancer diagnosis, body mass index, smoking intensity and duration, and serum total and high-density lipoprotein cholesterol did not alter the results. Participants with a higher metabolic score based on the discovery set had an elevated risk of prostate cancer-specific mortality in the replication set (fourth versus first quartile, HR=3.9, P-value for trend<0.0001). CONCLUSIONS The metabolic traits identified in this study, including for choline, glutamate, arachidonate, gamma-glutamyl amino acids, fibrinopeptides, and endocannabinoid and redox pathways and their composite risk score, corroborate our previous analysis of fatal prostate cancer and provide novel insights and potential leads regarding the molecular basis of prostate cancer progression and mortality.
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Affiliation(s)
- Jiaqi Huang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.,Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Bin Zhao
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Alison M Mondul
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA.
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10
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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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11
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Lysophosphatidylcholine: Potential Target for the Treatment of Chronic Pain. Int J Mol Sci 2022; 23:ijms23158274. [PMID: 35955410 PMCID: PMC9368269 DOI: 10.3390/ijms23158274] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/22/2022] [Accepted: 07/23/2022] [Indexed: 12/26/2022] Open
Abstract
The bioactive lipid lysophosphatidylcholine (LPC), a major phospholipid component of oxidized low-density lipoprotein (Ox-LDL), originates from the cleavage of phosphatidylcholine by phospholipase A2 (PLA2) and is catabolized to other substances by different enzymatic pathways. LPC exerts pleiotropic effects mediated by its receptors, G protein-coupled signaling receptors, Toll-like receptors, and ion channels to activate several second messengers. Lysophosphatidylcholine (LPC) is increasingly considered a key marker/factor positively in pathological states, especially inflammation and atherosclerosis development. Current studies have indicated that the injury of nervous tissues promotes oxidative stress and lipid peroxidation, as well as excessive accumulation of LPC, enhancing the membrane hyperexcitability to induce chronic pain, which may be recognized as one of the hallmarks of chronic pain. However, findings from lipidomic studies of LPC have been lacking in the context of chronic pain. In this review, we focus in some detail on LPC sources, biochemical pathways, and the signal-transduction system. Moreover, we outline the detection methods of LPC for accurate analysis of each individual LPC species and reveal the pathophysiological implication of LPC in chronic pain, which makes it an interesting target for biomarkers and the development of medicine regarding chronic pain.
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12
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Krupenko SA, Cole SA, Hou R, Haack K, Laston S, Mehta NR, Comuzzie AG, Butte NF, Voruganti VS. Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children. Am J Clin Nutr 2022; 116:500-510. [PMID: 35460232 PMCID: PMC9348975 DOI: 10.1093/ajcn/nqac091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 02/15/2022] [Accepted: 04/21/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion. OBJECTIVES We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort. METHODS We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members. RESULTS All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes. CONCLUSIONS Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.
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Affiliation(s)
- Sergey A Krupenko
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ruixue Hou
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Sandra Laston
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA,South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Nitesh R Mehta
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,USDA/ARS Children Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Nancy F Butte
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,USDA/ARS Children Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
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13
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Tan K, Naylor MJ. The Influence of Modifiable Factors on Breast and Prostate Cancer Risk and Disease Progression. Front Physiol 2022; 13:840826. [PMID: 35330933 PMCID: PMC8940211 DOI: 10.3389/fphys.2022.840826] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 02/11/2022] [Indexed: 12/31/2022] Open
Abstract
Breast and prostate cancers are among the most commonly diagnosed cancers worldwide, and together represented almost 20% of all new cancer diagnoses in 2020. For both cancers, the primary treatment options are surgical resection and sex hormone deprivation therapy, highlighting the initial dependence of these malignancies on the activity of both endogenous and exogenous hormones. Cancer cell phenotype and patient prognosis is not only determined by the collection of specific gene mutations, but through the interaction and influence of a wide range of different local and systemic components. While genetic risk factors that contribute to the development of these cancers are well understood, increasing epidemiological evidence link modifiable lifestyle factors such as physical exercise, diet and weight management, to drivers of disease progression such as inflammation, transcriptional activity, and altered biochemical signaling pathways. As a result of this significant impact, it is estimated that up to 50% of cancer cases in developed countries could be prevented with changes to lifestyle and environmental factors. While epidemiological studies of modifiable risk factors and research of the biological mechanisms exist mostly independently, this review will discuss how advances in our understanding of the metabolic, protein and transcriptional pathways altered by modifiable lifestyle factors impact cancer cell physiology to influence breast and prostate cancer risk and prognosis.
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Affiliation(s)
- Keely Tan
- Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Matthew J Naylor
- Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
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14
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Yu M, Wen W, Yi X, Zhu W, Aa J, Wang G. Plasma Metabolomics Reveals Diagnostic Biomarkers and Risk Factors for Esophageal Squamous Cell Carcinoma. Front Oncol 2022; 12:829350. [PMID: 35198450 PMCID: PMC8859148 DOI: 10.3389/fonc.2022.829350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 01/19/2022] [Indexed: 01/15/2023] Open
Abstract
Esophageal squamous carcinoma (ESCC) has a high morbidity and mortality rate. Identifying risk metabolites associated with its progression is essential for the early prevention and treatment of ESCC. A total of 373 ESCC, 40 esophageal squamous dysplasia (ESD), and 218 healthy controls (HC) subjects were enrolled in this study. Gas chromatography-mass spectrometry (GC/MS) was used to acquire plasma metabolic profiles. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate the potential diagnosis and prediction ability markers. The levels of alpha-tocopherol and cysteine were progressively decreased, while the levels of aminomalonic acid were progressively increased during the various stages (from precancerous lesions to advanced-stage) of exacerbation in ESCC patients. Alpha-tocopherol performed well for the differential diagnosis of HC and ESD/ESCC (AUROC>0.90). OR calculations showed that a high level of aminomalonic acid was not only a risk factor for further development of ESD to ESCC (OR>13.0) but also a risk factor for lymphatic metastasis in ESCC patients (OR>3.0). A low level of alpha-tocopherol was a distinguished independent risk factor of ESCC (OR< 0.5). The panel constructed by glycolic acid, oxalic acid, glyceric acid, malate and alpha-tocopherol performed well in distinguishing between ESD/ESCC from HC in the training and validation set (AUROC>0.95). In conclusion, the oxidative stress function was impaired in ESCC patients, and improving the body’s antioxidant function may help reduce the early occurrence of ESCC.
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Affiliation(s)
- Mengjie Yu
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
| | - Wei Wen
- Department of Thoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xin Yi
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
| | - Wei Zhu
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Jiye Aa, ; Wei Zhu,
| | - Jiye Aa
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
- *Correspondence: Jiye Aa, ; Wei Zhu,
| | - Guangji Wang
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
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15
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Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches. Cancers (Basel) 2022; 14:cancers14030596. [PMID: 35158864 PMCID: PMC8833769 DOI: 10.3390/cancers14030596] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 01/14/2022] [Accepted: 01/20/2022] [Indexed: 12/17/2022] Open
Abstract
Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.
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16
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Dai D, Yang Y, Yu J, Dang T, Qin W, Teng L, Ye J, Jiang H. Interactions between gastric microbiota and metabolites in gastric cancer. Cell Death Dis 2021; 12:1104. [PMID: 34819503 PMCID: PMC8613192 DOI: 10.1038/s41419-021-04396-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 11/02/2021] [Accepted: 11/10/2021] [Indexed: 12/18/2022]
Abstract
The development and progression of gastric cancer (GC) is greatly influenced by gastric microbiota and their metabolites. Here, we characterized the gastric microbiome and metabolome profiles of 37 GC tumor tissues and matched non-tumor tissues using 16s rRNA gene sequencing and ultrahigh performance liquid chromatography tandem mass spectrometry, respectively. Microbial diversity and richness were higher in GC tumor tissues than in non-tumor tissues. The abundance of Helicobacter was increased in non-tumor tissues, while the abundance of Lactobacillus, Streptococcus, Bacteroides, Prevotella, and 6 additional genera was increased in the tumor tissues. The untargeted metabolome analysis revealed 150 discriminative metabolites, among which the relative abundance of the amino acids, carbohydrates and carbohydrate conjugates, glycerophospholipids, and nucleosides was higher in tumor tissues compared to non-tumor tissues. The targeted metabolome analysis further demonstrated that the combination of 1-methylnicotinamide and N-acetyl-D-glucosamine-6-phosphate could serve as a robust biomarker for distinction between GC tumors and non-tumor tissues. Correlation analysis revealed that Helicobacter and Lactobacillus were negatively and positively correlated with the majority of differential metabolites in the classes of amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids, respectively, suggesting that Helicobacter and Lactobacillus might play a role in degradation and synthesis of the majority of differential metabolites in these classes, respectively. Acinetobacter, Comamonas, Faecalibacterium, Sphingomonas, and Streptococcus were also significantly correlated with many differential amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids. In conclusion, the differences in metabolome profiles between GC tumor and matched non-tumor tissues may be partly due to the collective activities of Helicobacter, Lactobacillus, and other bacteria, which eventually affects GC carcinogenesis and progression.
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Affiliation(s)
- Daofeng Dai
- Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
| | - Yan Yang
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jieqing Yu
- Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Tianfeng Dang
- Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Wenjing Qin
- Human Genetic Resources Center, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Lisong Teng
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Jing Ye
- Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
| | - Hongqun Jiang
- Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
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17
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Xu B, Chen Y, Chen X, Gan L, Zhang Y, Feng J, Yu L. Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone. Front Oncol 2021; 11:730638. [PMID: 34722271 PMCID: PMC8554118 DOI: 10.3389/fonc.2021.730638] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 09/23/2021] [Indexed: 12/15/2022] Open
Abstract
Objective Prostate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4–10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4–10 ng/ml was explored. Methods A total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4–10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles. Results Several differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student’s t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4–10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG). Conclusion The findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4–10 ng/ml.
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Affiliation(s)
- Bei Xu
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Yan Chen
- Department of Clinical Pharmacy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xi Chen
- Department of Application Support Center, SCIEX Analytical Instrument Trading Co., Shanghai, China
| | - Lingling Gan
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Yamei Zhang
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Jiafu Feng
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Lin Yu
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
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18
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Lin X, Lécuyer L, Liu X, Triba MN, Deschasaux-Tanguy M, Demidem A, Liu Z, Palama T, Rossary A, Vasson MP, Hercberg S, Galan P, Savarin P, Xu G, Touvier M. Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry. Cancers (Basel) 2021; 13:3140. [PMID: 34201735 PMCID: PMC8268247 DOI: 10.3390/cancers13133140] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/16/2021] [Accepted: 06/18/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa. METHODS Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). RESULTS Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower. CONCLUSION Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.
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Affiliation(s)
- Xiangping Lin
- Sorbonne Paris Nord University, Chemistry Structures Properties of Biomaterials and Therapeutic Agents Laboratory (CSPBAT), Nanomédecine Biomarqueurs Détection Team (NBD), The National Center for Scientific Research (CNRS), UMR 7244, 74 Rue Marcel
Cachin, CEDEX, 93017 Bobigny, France; (X.L.); (M.N.T.); (T.P.)
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; (X.L.); (G.X.)
| | - Lucie Lécuyer
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France; (L.L.); (S.H.); (P.G.); (M.T.)
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; (X.L.); (G.X.)
| | - Mohamed N. Triba
- Sorbonne Paris Nord University, Chemistry Structures Properties of Biomaterials and Therapeutic Agents Laboratory (CSPBAT), Nanomédecine Biomarqueurs Détection Team (NBD), The National Center for Scientific Research (CNRS), UMR 7244, 74 Rue Marcel
Cachin, CEDEX, 93017 Bobigny, France; (X.L.); (M.N.T.); (T.P.)
| | - Mélanie Deschasaux-Tanguy
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France; (L.L.); (S.H.); (P.G.); (M.T.)
| | - Aïcha Demidem
- Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Human Nutrition Unit (UNH), Clermont Auvergne University, INRAE, UMR 1019, CRNH Auvergne, 63000 Clermont-Ferrand, France; (A.D.); (A.R.); (M.-P.V.)
| | - Zhicheng Liu
- School of Pharmacy, Anhui Medical University, Hefei 230032, China;
| | - Tony Palama
- Sorbonne Paris Nord University, Chemistry Structures Properties of Biomaterials and Therapeutic Agents Laboratory (CSPBAT), Nanomédecine Biomarqueurs Détection Team (NBD), The National Center for Scientific Research (CNRS), UMR 7244, 74 Rue Marcel
Cachin, CEDEX, 93017 Bobigny, France; (X.L.); (M.N.T.); (T.P.)
| | - Adrien Rossary
- Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Human Nutrition Unit (UNH), Clermont Auvergne University, INRAE, UMR 1019, CRNH Auvergne, 63000 Clermont-Ferrand, France; (A.D.); (A.R.); (M.-P.V.)
| | - Marie-Paule Vasson
- Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Human Nutrition Unit (UNH), Clermont Auvergne University, INRAE, UMR 1019, CRNH Auvergne, 63000 Clermont-Ferrand, France; (A.D.); (A.R.); (M.-P.V.)
- Anticancer Center Jean-Perrin, CHU Clermont-Ferrand, CEDEX, 63011 Clermont-Ferrand, France
| | - Serge Hercberg
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France; (L.L.); (S.H.); (P.G.); (M.T.)
| | - Pilar Galan
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France; (L.L.); (S.H.); (P.G.); (M.T.)
| | - Philippe Savarin
- Sorbonne Paris Nord University, Chemistry Structures Properties of Biomaterials and Therapeutic Agents Laboratory (CSPBAT), Nanomédecine Biomarqueurs Détection Team (NBD), The National Center for Scientific Research (CNRS), UMR 7244, 74 Rue Marcel
Cachin, CEDEX, 93017 Bobigny, France; (X.L.); (M.N.T.); (T.P.)
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; (X.L.); (G.X.)
| | - Mathilde Touvier
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France; (L.L.); (S.H.); (P.G.); (M.T.)
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19
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Salciccia S, Capriotti AL, Laganà A, Fais S, Logozzi M, De Berardinis E, Busetto GM, Di Pierro GB, Ricciuti GP, Del Giudice F, Sciarra A, Carroll PR, Cooperberg MR, Sciarra B, Maggi M. Biomarkers in Prostate Cancer Diagnosis: From Current Knowledge to the Role of Metabolomics and Exosomes. Int J Mol Sci 2021; 22:ijms22094367. [PMID: 33922033 PMCID: PMC8122596 DOI: 10.3390/ijms22094367] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 04/18/2021] [Accepted: 04/20/2021] [Indexed: 12/13/2022] Open
Abstract
Early detection of prostate cancer (PC) is largely carried out using assessment of prostate-specific antigen (PSA) level; yet it cannot reliably discriminate between benign pathologies and clinically significant forms of PC. To overcome the current limitations of PSA, new urinary and serum biomarkers have been developed in recent years. Although several biomarkers have been explored in various scenarios and patient settings, to date, specific guidelines with a high level of evidence on the use of these markers are lacking. Recent advances in metabolomic, genomics, and proteomics have made new potential biomarkers available. A number of studies focused on the characterization of the specific PC metabolic phenotype using different experimental approaches has been recently reported; yet, to date, research on metabolomic application for PC has focused on a small group of metabolites that have been known to be related to the prostate gland. Exosomes are extracellular vesicles that are secreted from all mammalian cells and virtually detected in all bio-fluids, thus allowing their use as tumor biomarkers. Thanks to a general improvement of the technical equipment to analyze exosomes, we are able to obtain reliable quantitative and qualitative information useful for clinical application. Although some pilot clinical investigations have proposed potential PC biomarkers, data are still preliminary and non-conclusive.
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Affiliation(s)
- Stefano Salciccia
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
| | - Anna Laura Capriotti
- Department of Chemistry, Sapienza Rome University, 00161 Rome, Italy; (A.L.C.); (A.L.); (B.S.)
| | - Aldo Laganà
- Department of Chemistry, Sapienza Rome University, 00161 Rome, Italy; (A.L.C.); (A.L.); (B.S.)
| | - Stefano Fais
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, 00161 Rome, Italy; (S.F.); (M.L.)
| | - Mariantonia Logozzi
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, 00161 Rome, Italy; (S.F.); (M.L.)
| | - Ettore De Berardinis
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
| | - Gian Maria Busetto
- Department of Urology and Renal Transplantation, University of Foggia, Policlinico Riuniti, 71122 Foggia, Italy;
| | - Giovanni Battista Di Pierro
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
| | - Gian Piero Ricciuti
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
| | - Francesco Del Giudice
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
| | - Alessandro Sciarra
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
- Correspondence: ; Tel.: +39-0649974201; Fax: +39-0649970284
| | - Peter R. Carroll
- Department of Urology, UCSF Helen Diller Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA; (P.R.C.); (M.R.C.)
| | - Matthew R. Cooperberg
- Department of Urology, UCSF Helen Diller Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA; (P.R.C.); (M.R.C.)
| | - Beatrice Sciarra
- Department of Chemistry, Sapienza Rome University, 00161 Rome, Italy; (A.L.C.); (A.L.); (B.S.)
| | - Martina Maggi
- Department of Urology, Sapienza Rome University, Policlinico Umberto I, 00161 Rome, Italy; (S.S.); (E.D.B.); (G.B.D.P.); (G.P.R.); (F.D.G.); (M.M.)
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20
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Review of novel liquid-based biomarkers for prostate cancer: towards personalised and targeted medicine. JOURNAL OF RADIOTHERAPY IN PRACTICE 2021. [DOI: 10.1017/s1460396921000248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Abstract
Background:
Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortalities in both American and Canadian men. At present, serum prostate-specific antigen levels remain the most commonly used test to detect prostate cancer, and the standard and definitive diagnosis of the disease is via prostate biopsy. Conventional tissue biopsies are usually invasive, expensive, painful, time-consuming, and unsuitable for screening and need to be consistently evaluated by expert pathologists and have limited repeatability. Consequently, liquid biopsies are emerging as a favourable alternative to conventional tissue biopsies, providing a non-invasive and cost-effective approach for screening, diagnosis, treatment and monitoring of prostate cancer patients.
Materials and methods:
We searched several databases from August to December 2020 for relevant studies published in English between 2000 and 2020 and reporting on liquid-based biomarkers available in detectable quantities in patient bodily fluid samples. In this narrative review paper, we describe seven novel and promising liquid-based biomarkers that potentially account for individual patient variability as well as used in disease risk assessment, screening for early disease detection and diagnosis, identification of patients’ risk for metastatic disease and subsequent relapse, monitoring patient response to specific treatment and providing clinicians the potential to stratify patients likely to benefit from a particular treatment.
Conclusions:
The concept of precision medicine from prevention to treatment techniques that take individual patient variability into account will depend on the development of effective clinical biomarkers that interrogate key aberrant pathways potentially targetable with molecular targets or immunologic therapies. Liquid-based biomarkers with high sensitivity and specificity for prostate cancer are emerging as minimally invasive, lower risk, readily obtainable and easily repeatable technique for screening for early disease detection and diagnosis, patient stratification at diagnosis into different risk categories, identification of patients’ risk for metastatic disease and subsequent relapse, and real-time monitoring of patient response to specific treatment. Thus, effective liquid-based biomarkers will potentially shift the treatment paradigm of prostate cancer towards more personalised and targeted medicine.
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21
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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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22
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Feng X, Zhou CK, Clish CB, Wilson KM, Pernar CH, Dickerman BA, Loda M, Finn SP, Penney KL, Schmidt DR, Heiden MGV, Giovannucci EL, Ebot EM, Mucci LA. Association of Prediagnostic Blood Metabolomics with Prostate Cancer Defined by ERG or PTEN Molecular Subtypes. Cancer Epidemiol Biomarkers Prev 2021; 30:1000-1008. [PMID: 33627383 DOI: 10.1158/1055-9965.epi-20-1363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/24/2020] [Accepted: 02/19/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The TMPRSS2:ERG gene fusion and PTEN loss are two of the most common somatic molecular alterations in prostate cancer. Here, we investigated the association of prediagnostic-circulating metabolomics and prostate cancer defined by ERG or PTEN status to improve understanding of these etiologically distinct molecular prostate cancer subtypes. METHODS The study was performed among 277 prostate cancer cases with ERG status, 211 with PTEN status, and 294 controls nested in the Health Professionals Follow-up Study (HPFS) and the Physicians' Health Study (PHS). We profiled 223 polar and non-polar metabolites using LC-MS in prediagnostic plasma specimens. We applied enrichment analysis and multinomial logistic regression models to identify biological metabolite classes and individual metabolites associated with prostate cancer defined by ERG or PTEN status. RESULTS Compared with noncancer controls, sphingomyelin (P: 0.01), ceramide (P: 0.04), and phosphatidylethanolamine (P: 0.03) circulating levels were enriched among ERG-positive prostate cancer cases. Sphingomyelins (P: 0.02), ceramides (P: 0.005), and amino acids (P: 0.02) were enriched among tumors exhibiting PTEN-loss; unsaturated diacylglycerols (P: 0.003) were enriched among PTEN-intact cases; and unsaturated triacylglycerols were enriched among both PTEN-loss (P: 0.001) and PTEN-intact (P: 0.0001) cases. Although several individual metabolites identified in the above categories were nominally associated with ERG or PTEN-defined prostate cancer, none remained significant after accounting for multiple testing. CONCLUSIONS The molecular process of prostate carcinogenesis may be distinct for men with different metabolomic profiles. IMPACT These novel findings provide insights into the metabolic environment for the development of prostate cancer.
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Affiliation(s)
- Xiaoshuang Feng
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
| | - Cindy Ke Zhou
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | | | - Kathryn M Wilson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Claire H Pernar
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Barbra A Dickerman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Massimo Loda
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Stephen P Finn
- Department of Histopathology Research, Trinity College, Dublin, Ireland
| | - Kathryn L Penney
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Daniel R Schmidt
- David H. Koch Institute for Integrative Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts.,Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Matthew G Vander Heiden
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,David H. Koch Institute for Integrative Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Edward L Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Ericka M Ebot
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
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