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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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Hansen AF, Høiem TS, Selnaes KM, Bofin AM, Størkersen Ø, Bertilsson H, Wright AJ, Giskeødegård GF, Bathen TF, Rye MB, Tessem MB. Prediction of recurrence from metabolites and expression of TOP2A and EZH2 in prostate cancer patients treated with radiotherapy. NMR IN BIOMEDICINE 2023; 36:e4694. [PMID: 35032074 DOI: 10.1002/nbm.4694] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 11/17/2021] [Accepted: 01/07/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients. METHODS From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound-guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution-magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta-analysis. RESULTS Among radiotherapy patients with up to 11 years of follow-up, a low level of citrate was found to predict recurrence, p = 0.001 (C-index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C-index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment. CONCLUSION Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients.
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Affiliation(s)
- Ailin Falkmo Hansen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Trondheim, Norway
| | - Therese Stork Høiem
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Kirsten Margrete Selnaes
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Anna Mary Bofin
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, NTNU, Trondheim, Norway
| | - Øystein Størkersen
- Department of Pathology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Helena Bertilsson
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Alan J Wright
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Guro Fanneløb Giskeødegård
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Trondheim, Norway
| | - Tone Frost Bathen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Morten Beck Rye
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, NTNU, Trondheim, Norway
- Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
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Feng D, Shi X, Zhang F, Xiong Q, Wei Q, Yang L. Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy. Front Immunol 2022; 13:839362. [PMID: 35280985 PMCID: PMC8908254 DOI: 10.3389/fimmu.2022.839362] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 02/07/2022] [Indexed: 02/05/2023] Open
Abstract
Background We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy. Methods We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages. Results SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP. Conclusions The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.
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Affiliation(s)
- Dechao Feng
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Xu Shi
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Facai Zhang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiao Xiong
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Lu Yang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
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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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Peng Q, Wong CYP, Cheuk IWY, Teoh JYC, Chiu PKF, Ng CF. The Emerging Clinical Role of Spermine in Prostate Cancer. Int J Mol Sci 2021; 22:ijms22094382. [PMID: 33922247 PMCID: PMC8122740 DOI: 10.3390/ijms22094382] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/19/2021] [Accepted: 04/19/2021] [Indexed: 01/31/2023] Open
Abstract
Spermine, a member of polyamines, exists in all organisms and is essential for normal cell growth and function. It is highly expressed in the prostate compared with other organs and is detectable in urine, tissue, expressed prostatic secretions, and erythrocyte. A significant reduction of spermine level was observed in prostate cancer (PCa) tissue compared with benign prostate tissue, and the level of urinary spermine was also significantly lower in men with PCa. Decreased spermine level may be used as an indicator of malignant phenotype transformation from normal to malignant tissue in prostate. Studies targeting polyamines and key rate-limiting enzymes associated with spermine metabolism as a tool for PCa therapy and chemoprevention have been conducted with various polyamine biosynthesis inhibitors and polyamine analogues. The mechanism between spermine and PCa development are possibly related to the regulation of polyamine metabolism, cancer-driving pathways, oxidative stress, anticancer immunosurveillance, and apoptosis regulation. Although the specific mechanism of spermine in PCa development is still unclear, ongoing research in spermine metabolism and its association with PCa pathophysiology opens up new opportunities in the diagnostic and therapeutic roles of spermine in PCa management.
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Affiliation(s)
| | | | | | | | | | - Chi-Fai Ng
- Correspondence: (P.K.-F.C.); (C.-F.N.); Tel.: +85-235-052-625 (C.-F.N.)
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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: 59] [Impact Index Per Article: 19.7] [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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Lécuyer L, Victor Bala A, Demidem A, Rossary A, Bouchemal N, Triba MN, Galan P, Hercberg S, Partula V, Srour B, Latino-Martel P, Kesse-Guyot E, Druesne-Pecollo N, Vasson MP, Deschasaux-Tanguy M, Savarin P, Touvier M. NMR metabolomic profiles associated with long-term risk of prostate cancer. Metabolomics 2021; 17:32. [PMID: 33704614 DOI: 10.1007/s11306-021-01780-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 02/24/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Prostate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors. OBJECTIVES The aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade. METHODS A prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis. RESULTS Men with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up. CONCLUSIONS This exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.
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Affiliation(s)
- Lucie Lécuyer
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Agnès Victor Bala
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Aicha Demidem
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
| | - Adrien Rossary
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
| | - Nadia Bouchemal
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Mohamed Nawfal Triba
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Pilar Galan
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Serge Hercberg
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
- Public Health Department, Avicenne Hospital, 93000, Bobigny, France
| | - Valentin Partula
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Bernard Srour
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Paule Latino-Martel
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Emmanuelle Kesse-Guyot
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Nathalie Druesne-Pecollo
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Marie-Paule Vasson
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
- Anticancer Center Jean-Perrin, CHU Clermont-Ferrand, 63011, Clermont-Ferrand Cedex, France
| | - Mélanie Deschasaux-Tanguy
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
| | - Philippe Savarin
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Mathilde Touvier
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
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Ma Y, Chi J, Zheng Z, Attygalle A, Kim IY, Du H. Therapeutic prognosis of prostate cancer using surface-enhanced Raman scattering of patient urine and multivariate statistical analysis. JOURNAL OF BIOPHOTONICS 2021; 14:e202000275. [PMID: 32909380 DOI: 10.1002/jbio.202000275] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/26/2020] [Accepted: 09/03/2020] [Indexed: 05/20/2023]
Abstract
Surface-enhanced Raman scattering (SERS) is highly sensitive and label-free analytical technique based on Raman spectroscopy aided by field-multiplying plasmonic nanostructures. We report the use of SERS measurements of patient urine in conjunction with biostatistical algorithms to assess the treatment response of prostate cancer (PCa) in 12 recurrent (Re) and 63 nonrecurrent (NRe) patient cohorts. Multiple Raman spectra are collected from each urine sample using monodisperse silver nanoparticles (AgNPs) for Raman signal enhancement. Genetic algorithms-partial least squares-linear discriminant analysis (GA-PLS-LDA) was employed to analyze the Raman spectra. Comprehensive GA-PLS-LDA analyses of these Raman spectral features (p = 3.50 × 10-16 ) yield an accuracy of 86.6%, sensitivity of 86.0%, and specificity 87.1% in differentiating the Re and NRe cohorts. Our study suggests that SERS combined with multivariate GA-PLS-LDA algorithm can potentially be used to detect and monitor the risk of PCa relapse and to aid with decision-making for optimal intermediate secondary therapy to recurred patients.
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Affiliation(s)
- Yiwei Ma
- Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, New Jersey, USA
| | - Jingmao Chi
- Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, New Jersey, USA
| | - Zhaoyu Zheng
- Department of Chemistry and Chemical Biology, Stevens Institute of Technology, Hoboken, New Jersey, USA
| | - Athula Attygalle
- Department of Chemistry and Chemical Biology, Stevens Institute of Technology, Hoboken, New Jersey, USA
| | - Isaac Yi Kim
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
| | - Henry Du
- Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, New Jersey, USA
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9
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Pinto FG, Mahmud I, Harmon TA, Rubio VY, Garrett TJ. Rapid Prostate Cancer Noninvasive Biomarker Screening Using Segmented Flow Mass Spectrometry-Based Untargeted Metabolomics. J Proteome Res 2020; 19:2080-2091. [PMID: 32216312 DOI: 10.1021/acs.jproteome.0c00006] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Spectrometric methods with rapid biomarker detection capacity through untargeted metabolomics are becoming essential in the clinical cancer research. Liquid chromatography-mass spectrometry (LC-MS) is a rapidly developing metabolomic-based biomarker technique due to its high sensitivity, reproducibility, and separation efficiency. However, its translation to clinical diagnostics is often limited due to long data acquisition times (∼20 min/sample) and laborious sample extraction procedures when employed for large-scale metabolomics studies. Here, we developed a segmented flow approach coupled with high-resolution mass spectrometry (SF-HRMS) for untargeted metabolomics, which has the capability to acquire data in less than 1.5 min/sample with robustness and reproducibility relative to LC-HRMS. The SF-HRMS results demonstrate the capability for screening metabolite-based urinary biomarkers associated with prostate cancer (PCa). The study shows that SF-HRMS-based global metabolomics has the potential to evolve into a rapid biomarker screening tool for clinical research.
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Affiliation(s)
- Frederico G Pinto
- Instituto de Ciências Exatas e Tecnológicas, Universidade Federal de Viçosa, Campus de Rio Paranaíba, Viçosa 36570-900, Brazil
| | - Iqbal Mahmud
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida 32610, United States
| | - Taylor A Harmon
- Department of Chemistry, University of Florida, Gainesville, Florida 32603, United States
| | - Vanessa Y Rubio
- Department of Chemistry, University of Florida, Gainesville, Florida 32603, United States
| | - Timothy J Garrett
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida 32610, United States.,Southeast Center for Integrated Metabolomics, Clinical and Translational Science Institute, University of Florida, Gainesville, Florida 32610, United States
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10
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Kdadra M, Höckner S, Leung H, Kremer W, Schiffer E. Metabolomics Biomarkers of Prostate Cancer: A Systematic Review. Diagnostics (Basel) 2019; 9:E21. [PMID: 30791464 PMCID: PMC6468767 DOI: 10.3390/diagnostics9010021] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 02/13/2019] [Accepted: 02/14/2019] [Indexed: 12/27/2022] Open
Abstract
Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.
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Affiliation(s)
| | | | - Hing Leung
- Institute of Cancer Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G61 1QH, UK.
- CRUK Beatson Institute, Bearsden, Glasgow G61 1BD, UK.
| | - Werner Kremer
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93053 Regensburg, Germany.
| | - Eric Schiffer
- Numares AG, Am BioPark 9, 93053 Regensburg, Germany.
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11
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Pan J, Shao X, Zhu Y, Dong B, Wang Y, Kang X, Chen N, Chen Z, Liu S, Xue W. Surface-enhanced Raman spectroscopy before radical prostatectomy predicts biochemical recurrence better than CAPRA-S. Int J Nanomedicine 2019; 14:431-440. [PMID: 30666105 PMCID: PMC6331067 DOI: 10.2147/ijn.s186226] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Objective The objective of this study was to evaluate the performance of surface-enhanced Raman spectroscopy (SERS) in the prediction of early biochemical recurrence after radical prostatectomy (RP). Patients and methods We synthesized monodisperse gold nanoparticles as SERS-enhanced substrates and analyzed preoperative plasma samples of patients who underwent RP. The roles of clinical risk model (Cancer of the Prostate Risk Assessment [CAPRA] score) and distinctive SERS spectra on prediction of early biochemical recurrence were evaluated. The principal component analysis and linear discriminant analysis (PCA-LDA) were used to manage the spectral data and develop diagnostic algorithm. Results A total of 306 preoperative plasma Raman spectra from 102 patients were collected. SERS spectrum from those who developed early biochemical recurrence were compared to those who remained biochemical recurrence-free. The SERS detected more abundant circulating free nucleic acid bases in biochemical recurrence population, presenting significant stronger intensities at SERS spectral bands 725 and 1,328 cm−1. The addition of Raman spectral peak 1,328 cm−1 to CAPRA postsurgical (CAPRA-S) score significantly improved the predictive power of logistic regression model compared to simple CAPRA score (P<0.001). Meanwhile, the leave-one-out cross-validation method was used to validate the PCA-LDA model and revealed the sensitivity, specificity, and accuracy of 65.8%, 87.5%, and 79.4%, respectively. The receiver operating characteristic (ROC) curve was used to evaluate the performance of different models. Area under the ROC curve of the CAPRA-S score model alone was 0.77, however, when combined with Raman spectral peak 1,328 cm−1, it improved to 0.81. Conclusion Our primary results suggested that SERS could be a meaningful technique for prediction of early biochemical recurrence in prostate cancer.
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Affiliation(s)
- Jiahua Pan
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
| | - Xiaoguang Shao
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
| | - Yinjie Zhu
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
| | - Baijun Dong
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
| | - Yanqing Wang
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
| | - Xiaonan Kang
- Department of Biobank, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China
| | - Na Chen
- Shanghai Institute for Advanced Communication and Data Science, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University, Shanghai, People's Republic of China,
| | - Zhenyi Chen
- Shanghai Institute for Advanced Communication and Data Science, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University, Shanghai, People's Republic of China,
| | - Shupeng Liu
- Shanghai Institute for Advanced Communication and Data Science, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University, Shanghai, People's Republic of China,
| | - Wei Xue
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China,
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12
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Lima AR, Pinto J, Bastos MDL, Carvalho M, Guedes de Pinho P. NMR-based metabolomics studies of human prostate cancer tissue. Metabolomics 2018; 14:88. [PMID: 30830350 DOI: 10.1007/s11306-018-1384-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 06/11/2018] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. Serum prostate-specific antigen (PSA) remains the most used biomarker in the detection and management of patients with PCa, in spite of the problems related with its low specificity, false positive rate and overdiagnosis. Furthermore, PSA is unable to discriminate indolent from aggressive PCa, which can lead to overtreatment. Early diagnosed and treated PCa can have a good prognosis and is potentially curable. Therefore, the discovery of new biomarkers able to detect clinically significant aggressive PCa is urgently needed. METHODS This revision was based on an electronic literature search, using Pubmed, with Nuclear Magnetic Resonance (NMR), tissue and prostate cancer as keywords. All metabolomic studies performed in PCa tissues by NMR spectroscopy, from 2007 until March 2018, were included in this review. RESULTS In the context of cancer, metabolomics allows the analysis of the entire metabolic profile of cancer cells. Several metabolic alterations occur in cancer cells to sustain their abnormal rates of proliferation. NMR proved to be a suitable methodology for the evaluation of these metabolic alterations in PCa tissues, allowing to unveil alterations in citrate, spermine, choline, choline-related compounds, lactate, alanine and glutamate. CONCLUSION The study of the metabolic alterations associated with PCa progression, accomplished by the analysis of PCa tissue by NMR, offers a promising approach for elucidating biochemical pathways affected by PCa and also for discovering new clinical biomarkers. The main metabolomic alterations associated with PCa development and promising biomarker metabolites for diagnosis of PCa were outlined.
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Affiliation(s)
- Ana Rita Lima
- UCIBIO/REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal.
| | - Joana Pinto
- UCIBIO/REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal
| | - Maria de Lourdes Bastos
- UCIBIO/REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal
| | - Márcia Carvalho
- UCIBIO/REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal
- UFP Energy, Environment and Health Research Unit (FP-ENAS), University Fernando Pessoa, Porto, Portugal
| | - Paula Guedes de Pinho
- UCIBIO/REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal.
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13
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Profiling Prostate Cancer Therapeutic Resistance. Int J Mol Sci 2018; 19:ijms19030904. [PMID: 29562686 PMCID: PMC5877765 DOI: 10.3390/ijms19030904] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 03/16/2018] [Accepted: 03/16/2018] [Indexed: 02/06/2023] Open
Abstract
The major challenge in the treatment of patients with advanced lethal prostate cancer is therapeutic resistance to androgen-deprivation therapy (ADT) and chemotherapy. Overriding this resistance requires understanding of the driving mechanisms of the tumor microenvironment, not just the androgen receptor (AR)-signaling cascade, that facilitate therapeutic resistance in order to identify new drug targets. The tumor microenvironment enables key signaling pathways promoting cancer cell survival and invasion via resistance to anoikis. In particular, the process of epithelial-mesenchymal-transition (EMT), directed by transforming growth factor-β (TGF-β), confers stem cell properties and acquisition of a migratory and invasive phenotype via resistance to anoikis. Our lead agent DZ-50 may have a potentially high efficacy in advanced metastatic castration resistant prostate cancer (mCRPC) by eliciting an anoikis-driven therapeutic response. The plasticity of differentiated prostate tumor gland epithelium allows cells to de-differentiate into mesenchymal cells via EMT and re-differentiate via reversal to mesenchymal epithelial transition (MET) during tumor progression. A characteristic feature of EMT landscape is loss of E-cadherin, causing adherens junction breakdown, which circumvents anoikis, promoting metastasis and chemoresistance. The targetable interactions between androgens/AR and TGF-β signaling are being pursued towards optimized therapeutic regimens for the treatment of mCRPC. In this review, we discuss the recent evidence on targeting the EMT-MET dynamic interconversions to overcome therapeutic resistance in patients with recurrent therapeutically resistant prostate cancer. Exploitation of the phenotypic landscape and metabolic changes that characterize the prostate tumor microenvironment in advanced prostate cancer and consequential impact in conferring treatment resistance are also considered in the context of biomarker discovery.
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14
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Dietz C, Ehret F, Palmas F, Vandergrift LA, Jiang Y, Schmitt V, Dufner V, Habbel P, Nowak J, Cheng LL. Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3784. [PMID: 28915318 PMCID: PMC5690552 DOI: 10.1002/nbm.3784] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 06/21/2017] [Accepted: 07/10/2017] [Indexed: 05/06/2023]
Abstract
High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.
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Affiliation(s)
- Christopher Dietz
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Faculty of Medicine, Julius Maximilian University of Würzburg, 97080 Würzburg, Germany
| | - Felix Ehret
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Faculty of Medicine, Julius Maximilian University of Würzburg, 97080 Würzburg, Germany
| | - Francesco Palmas
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Department of Chemical and Geological Sciences, University of Cagliari, Cagliari, Sardinia, 09042 Italy
| | - Lindsey A. Vandergrift
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
| | - Yanni Jiang
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029 China
| | - Vanessa Schmitt
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Faculty of Medicine, Julius Maximilian University of Würzburg, 97080 Würzburg, Germany
| | - Vera Dufner
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
- Department of Hematology and Oncology, Charité Medical University of Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Piet Habbel
- Department of Hematology and Oncology, Charité Medical University of Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Johannes Nowak
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, 97080 Würzburg, Germany
| | - Leo L. Cheng
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Charlestown, Massachusetts 02129, USA
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15
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Braadland PR, Giskeødegård G, Sandsmark E, Bertilsson H, Euceda LR, Hansen AF, Guldvik IJ, Selnæs KM, Grytli HH, Katz B, Svindland A, Bathen TF, Eri LM, Nygård S, Berge V, Taskén KA, Tessem MB. Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy. Br J Cancer 2017; 117:1656-1664. [PMID: 28972967 PMCID: PMC5729443 DOI: 10.1038/bjc.2017.346] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 08/18/2017] [Accepted: 09/01/2017] [Indexed: 12/21/2022] Open
Abstract
Background: Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy. Methods: We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan–Meier survival analyses and concordance index (C-index). Results: High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively). Conclusions: Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.
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Affiliation(s)
- Peder R Braadland
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4953 Nydalen, Oslo 0424, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0313, Norway
| | - Guro Giskeødegård
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Elise Sandsmark
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Helena Bertilsson
- St Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway.,Department of Cancer Research and Molecular Medicine, Faculty of Medicine, NTNU - Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Leslie R Euceda
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Ailin F Hansen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Ingrid J Guldvik
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4953 Nydalen, Oslo 0424, Norway
| | - Kirsten M Selnæs
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Helene H Grytli
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4953 Nydalen, Oslo 0424, Norway
| | - Betina Katz
- Department of Pathology, Oslo University Hospital, Oslo 0424, Norway
| | - Aud Svindland
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0313, Norway.,Department of Pathology, Oslo University Hospital, Oslo 0424, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
| | - Lars M Eri
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0313, Norway.,Department of Urology, Oslo University Hospital, Oslo 0424, Norway
| | - Ståle Nygård
- Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo 0424, Norway
| | - Viktor Berge
- Department of Urology, Oslo University Hospital, Oslo 0424, Norway
| | - Kristin A Taskén
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4953 Nydalen, Oslo 0424, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0313, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway
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16
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Al Kadhi O, Traka MH, Melchini A, Troncoso-Rey P, Jurkowski W, Defernez M, Pachori P, Mills RD, Ball RY, Mithen RF. Increased transcriptional and metabolic capacity for lipid metabolism in the peripheral zone of the prostate may underpin its increased susceptibility to cancer. Oncotarget 2017; 8:84902-84916. [PMID: 29156692 PMCID: PMC5689582 DOI: 10.18632/oncotarget.17926] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2016] [Accepted: 05/02/2017] [Indexed: 12/31/2022] Open
Abstract
The human prostate gland comprises three distinct anatomical glandular zones, namely the peripheral, central and transitional zones. Although prostate cancer can arise throughout the prostate, it is more frequent in the peripheral zone. In contrast, hyperplasia occurs most frequently in the transitional zone. In this paper, we test the hypothesis that peripheral and transitional zones have distinct metabolic adaptations that may underlie their different inherent predispositions to cancer and hyperplasia. In order to do this, we undertook RNA sequencing and high-throughput metabolic analyses of non-cancerous tissue from the peripheral and transitional zones of patients undergoing prostatectomy. Integrated analysis of RNAseq and metabolomic data revealed that transcription of genes involved in lipid biosynthesis is higher in the peripheral zone, which was mirrored by an increase in fatty acid metabolites, such as lysolipids. The peripheral zone also exhibited increased fatty acid catabolic activity and contained higher level of neurotransmitters. Such increased capacity for de novo lipogenesis and fatty acid oxidation, which is characteristic of prostate cancer, can potentially provide a permissive growth environment within the peripheral zone for cancer growth and also transmit a metabolic growth advantage to newly emerging clones themselves. This lipo-rich priming may explain the observed susceptibility of the peripheral zone to oncogenesis.
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Affiliation(s)
- Omar Al Kadhi
- Food and Health Programme, Quadram Institute Bioscience, Norwich, UK.,Department of Urology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Maria H Traka
- Food and Health Programme, Quadram Institute Bioscience, Norwich, UK
| | | | | | | | | | - Purnima Pachori
- Platforms and Pipelines Bioinformatics, Earlham Institute, Norwich, UK
| | - Robert D Mills
- Department of Urology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Richard Y Ball
- Norfolk and Waveney Cellular Pathology Service, Norfolk and Norwich University Hospital, Norwich, UK
| | - Richard F Mithen
- Food and Health Programme, Quadram Institute Bioscience, Norwich, UK
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17
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Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies. Transl Oncol 2016; 9:357-70. [PMID: 27567960 PMCID: PMC5006818 DOI: 10.1016/j.tranon.2016.05.004] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 05/21/2016] [Accepted: 05/31/2016] [Indexed: 02/07/2023] Open
Abstract
Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.
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18
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Kelly RS, Vander Heiden MG, Giovannucci E, Mucci LA. Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence. Cancer Epidemiol Biomarkers Prev 2016; 25:887-906. [PMID: 27197278 DOI: 10.1158/1055-9965.epi-15-1223] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 03/23/2016] [Indexed: 02/07/2023] Open
Abstract
Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic, and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case-control studies of prostate cancer exploring disease prediction, diagnosis, progression, or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis, and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation, and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodologic issues remain to be addressed to maximize the utility of metabolomics in the study of prostate cancer. Cancer Epidemiol Biomarkers Prev; 25(6); 887-906. ©2016 AACR.
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Affiliation(s)
- Rachel S Kelly
- 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.
| | - Matthew G Vander Heiden
- Koch Institute for Integrative Cancer Research at Massachusetts Institute of Technology, Cambridge, Massachusetts. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Edward 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
| | - 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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19
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Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS). Metabolites 2016; 6:metabo6010011. [PMID: 27011205 PMCID: PMC4812340 DOI: 10.3390/metabo6010011] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Revised: 03/15/2016] [Accepted: 03/17/2016] [Indexed: 12/14/2022] Open
Abstract
According to World Health Organization (WHO) estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics.
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20
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Decelle EA, Cheng LL. High-resolution magic angle spinning 1H MRS in prostate cancer. NMR IN BIOMEDICINE 2014; 27:90-99. [PMID: 23529951 PMCID: PMC3797175 DOI: 10.1002/nbm.2944] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2012] [Revised: 01/23/2013] [Accepted: 02/19/2013] [Indexed: 06/02/2023]
Abstract
Prostate cancer (PCa) is the most frequently diagnosed malignancy in men worldwide, largely as a result of the increased use of the annual serum prostate-specific antigen (PSA) screening test for detection. PSA screening has saved lives, but it has also resulted in the overtreatment of many patients with PCa because of a limited ability to accurately localize and characterize PCa lesions through imaging. High-resolution magic angle spinning (HRMAS) (1)H MRS has proven to be a strong potential clinical tool for PCa diagnosis and prognosis. The HRMAS technique allows valuable metabolic information to be obtained from ex vivo intact tissue samples and also enables the performance of histopathology on the same tissue specimens. Studies have found that the quantification of individual metabolite levels and metabolite ratios, as well as metabolomic profiles, shows strong potential to improve accuracy in PCa detection, diagnosis and monitoring. Ex vivo HRMAS is also a valuable tool for the interpretation of in vivo results, including the localization of tumors, and thus has the potential to improve in vivo diagnostic tests used in the clinic. Here, we primarily review publications of HRMAS (1)H MRS and its use for the study of intact human prostate tissue.
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Affiliation(s)
- Emily A Decelle
- Departments of Pathology and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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21
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Jung K, Reszka R, Kamlage B, Bethan B, Stephan C, Lein M, Kristiansen G. Tissue metabolite profiling identifies differentiating and prognostic biomarkers for prostate carcinoma. Int J Cancer 2013; 133:2914-24. [PMID: 23737455 DOI: 10.1002/ijc.28303] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2013] [Accepted: 04/22/2013] [Indexed: 12/17/2022]
Abstract
Metabolomic research offers a deeper insight into biochemical changes in cancer metabolism and is a promising tool for identifying novel biomarkers. We aimed to evaluate the diagnostic and prognostic potential of metabolites in prostate cancer (PCa) tissue after radical prostatectomy. In matched malignant and nonmalignant prostatectomy samples from 95 PCa patients, aminoadipic acid, cerebronic acid, gluconic acid, glycerophosphoethanolamine, 2-hydroxybehenic acid, isopentenyl pyrophosphate, maltotriose, 7-methylguanine and tricosanoic acid were determined within a global metabolite profiling study using gas chromatography/liquid chromatography-mass spectrometry. The data were related to clinicopathological variables like prostate volume, tumor stage, Gleason score, preoperative prostate-specific antigen and disease recurrence in the follow-up. All nine metabolites showed higher concentrations in malignant than in nonmalignant samples except for gluconic acid and maltotriose, which had lower levels in tumors. Receiver -operating characteristics analysis demonstrated a significant discrimination for all metabolites between malignant and nonmalignant tissue with a maximal area under the curve of 0.86 for tricosanoic acid, whereas no correlation was observed between the metabolite levels and the Gleason score or tumor stage except for gluconic acid. Univariate Cox regression and Kaplan-Meier analyses showed that levels of aminoadipic acid, gluconic acid and maltotriose were associated with the biochemical tumor recurrence (prostate-specific antigen > 0.2 ng/mL). In multivariate Cox regression analyses, aminoadipic acid together with tumor stage and Gleason score remained in a model as independent marker for prediction of biochemical recurrence. This study proved that metabolites in PCa tissue can be used, in combination with traditional clinicopathological factors, as promising diagnostic and prognostic tools.
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Affiliation(s)
- Klaus Jung
- Department of Urology, University Hospital Charité, Schumannstraß 20/21, 10117 Berlin, Germany; Berlin Institute for Urologic Research, Schumannstraße 20/21, 10117 Berlin, Germany
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22
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Spur EM, Decelle EA, Cheng LL. Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry. Eur J Nucl Med Mol Imaging 2013; 40 Suppl 1:S60-71. [PMID: 23549758 DOI: 10.1007/s00259-013-2379-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 02/18/2013] [Indexed: 12/14/2022]
Abstract
Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases.
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Affiliation(s)
- Eva-Margarete Spur
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, CNY-6, 149 13th Street, Charlestown, Boston, MA 02129, USA
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23
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Kurth J, Defeo E, Cheng LL. Magnetic resonance spectroscopy: a promising tool for the diagnostics of human prostate cancer? Urol Oncol 2012; 29:562-71. [PMID: 21930088 DOI: 10.1016/j.urolonc.2011.05.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2011] [Revised: 05/27/2011] [Accepted: 05/28/2011] [Indexed: 11/18/2022]
Abstract
BACKGROUND Prostate cancer (CaP) is one of the topmost diagnosed malignant diseases worldwide. In developed countries, early cancer detection methods have led to an increase of incidence rates over the last decades; however, with great variance of the prognosis. There is no diagnostic tool for an exact prediction of tumor aggressiveness, thus there is a lack of adequate and optimal treatment planning. METHODS Electronic databases (Medline, PubMed) were scanned for scientific literature. Basic concepts of magnetic resonance spectroscopy (MRS), important results and its clinical applications were extracted and reviewed in this article. CONCLUSIONS MRS provides crucial information about the metabolic status of human prostate samples while preserving the specimens for further investigations. Single metabolites and metabolomic profiles can be quantified to distinguish benign from malignant tissue and to predict aggressiveness, such as the recurrence rates of CaP. Studies are also anticipating that MRS might be beneficially applicable for in vivo investigations in the future.
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24
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Trock BJ. Application of metabolomics to prostate cancer. Urol Oncol 2011; 29:572-81. [PMID: 21930089 PMCID: PMC3180907 DOI: 10.1016/j.urolonc.2011.08.002] [Citation(s) in RCA: 96] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2011] [Revised: 07/31/2011] [Accepted: 08/01/2011] [Indexed: 12/11/2022]
Abstract
The prostate has long been known to exhibit unique metabolite profiles. In the last decade, advances in nuclear magnetic resonance spectroscopy and mass spectrometry have been applied toward identifying metabolic alterations in prostate cancer that may provide clinically useful biomarkers. As with genomics and proteomics, advances in technology and bioinformatics have led to the application of metabolomic profiling to prostate cancer-the high throughput evaluation of a large complement of metabolites in the prostate and how they are altered by disease perturbations. Recently, high profile publications have drawn attention to the potential of metabolomic analysis to identify biomarkers for early detection or disease progression from readily accessible body fluids as well as tissue specimens from biopsy and surgery. This review will examine applications of metabolomics to prostate cancer and highlight clinical associations and potential challenges.
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Affiliation(s)
- Bruce J Trock
- Department of Urology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
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25
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DeFeo EM, Wu CL, McDougal WS, Cheng LL. A decade in prostate cancer: from NMR to metabolomics. Nat Rev Urol 2011; 8:301-11. [PMID: 21587223 DOI: 10.1038/nrurol.2011.53] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Over the past 30 years, continuous progress in the application of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopic imaging (MRSI) to the detection, diagnosis and characterization of human prostate cancer has turned what began as scientific curiosity into a useful clinical option. In vivo MRSI technology has been integrated into the daily care of prostate cancer patients, and innovations in ex vivo methods have helped to establish NMR-based prostate cancer metabolomics. Metabolomic and multimodality imaging could be the future of the prostate cancer clinic--particularly given the rationale that more accurate interrogation of a disease as complex as human prostate cancer is most likely to be achieved through paradigms involving multiple, instead of single and isolated, parameters. The research and clinical results achieved through in vivo MRSI and ex vivo NMR investigations during the first 11 years of the 21st century illustrate areas where these technologies can be best translated into clinical practice.
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Affiliation(s)
- Elita M DeFeo
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
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26
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Abstract
Molecular and cell biology have revolutionized not only diagnosis, therapy and prevention of human diseases but also greatly contributed to the understanding of their pathogenesis. Based on modern molecular and biochemical methods it is possible to identify on the one hand point mutations and single nucleotide polymorphisms. On the other hand, using high throughput array technologies, it is possible to analyse thousands of genes or gene products simultaneously, resulting in an individual gene or gene expression profile (signature). These data increasingly allow to define the individual risk for a given disease and to predict the individual prognosis of a disease as well as the efficacy of therapeutic strategies (individualized medicine). In the following sections some of the recent advances of predictive medicine and their clinical relevance will be addressed.
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Affiliation(s)
- Hubert E Blum
- Department of Medicine II, University Hospital Freiburg, Germany.
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27
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Roberts MJ, Schirra HJ, Lavin MF, Gardiner RA. Metabolomics: a novel approach to early and noninvasive prostate cancer detection. Korean J Urol 2011; 52:79-89. [PMID: 21379423 PMCID: PMC3045724 DOI: 10.4111/kju.2011.52.2.79] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2010] [Accepted: 01/07/2011] [Indexed: 12/22/2022] Open
Abstract
Prostate cancer (PCa) is the most commonly diagnosed visceral cancer in men and is responsible for the second highest cancer-related male mortality rate in Western countries, with increasing rates being reported in Korea, Japan, and China. Considering the low sensitivity of prostate-specific antigen (PSA) testing, it is widely agreed that reliable, age-independent markers of the presence, nature, and progression of PCa are required to facilitate diagnosis and timely treatment. Metabolomics or metabonomics has recently emerged as a novel method of PCa detection owing to its ability to monitor changes in the metabolic signature, within biofluids or tissue, that reflect changes in phenotype and function. This review outlines the physiology of prostate tissue and prostatic fluid in health and in malignancy in relation to metabolomics as well as the principles underlying the methods of metabolomic quantification. Promising metabolites, metabolic profiles, and their correlation with the presence and stage of PCa are summarized. Application of metabolomics to biofluids and in vivo quantification as well as the direction of current research in supplementing and improving current methods of detection are discussed. The current debate in the urology literature on sarcosine as a potential biomarker for PCa is reviewed and discussed. Metabolomics promises to be a valuable tool in the early detection of PCa that may enable earlier treatment and improved clinical outcomes.
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Affiliation(s)
- Matthew J. Roberts
- Department of Urology, University of Queensland Centre for Clinical Research, Brisbane, Australia
| | - Horst J. Schirra
- The University of Queensland, School of Chemistry and Molecular Biosciences, Brisbane, Australia
| | - Martin F. Lavin
- Queensland Institute of Medical Research, Radiation Biology and Oncology, Brisbane, Australia
- Department of Surgery, University of Queensland Centre for Clinical Research, Brisbane, Australia
| | - Robert A. Gardiner
- Department of Surgery, University of Queensland Centre for Clinical Research, Brisbane, Australia
- Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia
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28
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Chen JL, Tang HQ, Hu JD, Fan J, Hong J, Gu JZ. Metabolomics of gastric cancer metastasis detected by gas chromatography and mass spectrometry. World J Gastroenterol 2010; 16:5874-80. [PMID: 21155010 PMCID: PMC3001980 DOI: 10.3748/wjg.v16.i46.5874] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
AIM: To elucidate the underlying mechanisms of metastasis and to identify the metabolomic markers of gastric cancer metastasis.
METHODS: Gastric tumors from metastatic and non-metastatic groups were used in this study. Metabolites and different metabolic patterns were analyzed by gas chromatography, mass spectrometry and principal components analysis (PCA), respectively. Differentiation performance was validated by the area under the curve (AUC) of receiver operating characteristic curves.
RESULTS: Twenty-nine metabolites were differentially expressed in animal models of human gastric cancer. Of the 29 metabolites, 20 were up-regulated and 9 were down-regulated in metastasis group compared to non-metastasis group. PCA models from the metabolite profiles could differentiate the metastatic from the non-metastatic specimens with an AUC value of 1.0. These metabolites were mainly involved in several metabolic pathways, including glycolysis (lactic acid, alaline), serine metabolism (serine, phosphoserine), proline metabolism (proline), glutamic acid metabolism, tricarboxylic acid cycle (succinate, malic acid), nucleotide metabolism (pyrimidine), fatty acid metabolism (docosanoic acid, and octadecanoic acid), and methylation(glycine). The serine and proline metabolisms were highlighted during the progression of metastasis.
CONCLUSION: Proline and serine metabolisms play an important role in metastasis. The metabolic profiling of tumor tissue can provide new biomarkers for the treatment of gastric cancer metastasis.
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