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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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Bi X, Wang J, Xue B, He C, Liu F, Chen H, Lin LL, Dong B, Li B, Jin C, Pan J, Xue W, Ye J. SERSomes for metabolic phenotyping and prostate cancer diagnosis. Cell Rep Med 2024; 5:101579. [PMID: 38776910 PMCID: PMC11228451 DOI: 10.1016/j.xcrm.2024.101579] [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: 09/27/2023] [Revised: 03/08/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
Molecular phenotypic variations in metabolites offer the promise of rapid profiling of physiological and pathological states for diagnosis, monitoring, and prognosis. Since present methods are expensive, time-consuming, and still not sensitive enough, there is an urgent need for approaches that can interrogate complex biological fluids at a system-wide level. Here, we introduce hyperspectral surface-enhanced Raman spectroscopy (SERS) to profile microliters of biofluidic metabolite extraction in 15 min with a spectral set, SERSome, that can be used to describe the structures and functions of various molecules produced in the biofluid at a specific time via SERS characteristics. The metabolite differences of various biofluids, including cell culture medium and human serum, are successfully profiled, showing a diagnosis accuracy of 80.8% on the internal test set and 73% on the external validation set for prostate cancer, discovering potential biomarkers, and predicting the tissue-level pathological aggressiveness. SERSomes offer a promising methodology for metabolic phenotyping.
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Affiliation(s)
- Xinyuan Bi
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Jiayi Wang
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Bingsen Xue
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China; Shanghai Artificial Intelligence Laboratory, Shanghai, China
| | - Chang He
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Fugang Liu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Haoran Chen
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Linley Li Lin
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Baijun Dong
- Department of Urology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Science, Shanghai, P.R. China
| | - Butang Li
- Department of Urology, Ningbo Hangzhou Bay Hospital, Ningbo, Zhejiang, P.R. China
| | - Cheng Jin
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China; Shanghai Artificial Intelligence Laboratory, Shanghai, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, P.R. China.
| | - Jiahua Pan
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China.
| | - Wei Xue
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China.
| | - Jian Ye
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, P.R. China; Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China.
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Zniber M, Lamminen T, Taimen P, Boström PJ, Huynh TP. 1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia. Heliyon 2024; 10:e28949. [PMID: 38617934 PMCID: PMC11015411 DOI: 10.1016/j.heliyon.2024.e28949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/27/2024] [Accepted: 03/27/2024] [Indexed: 04/16/2024] Open
Abstract
Background Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies. Significance This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies. Results The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.
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Affiliation(s)
- Mohammed Zniber
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
| | - Tarja Lamminen
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Pekka Taimen
- Institute of Biomedicine and FICAN West Cancer Centre, University of Turku and Department of Pathology, Turku University Hospital, Turku, Finland
| | - Peter J. Boström
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Tan-Phat Huynh
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
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Evin D, Evinová A, Baranovičová E, Šarlinová M, Jurečeková J, Kaplán P, Poláček H, Halašová E, Dušenka R, Briš L, Brožová MK, Sivoňová MK. Integrative Metabolomic Analysis of Serum and Selected Serum Exosomal microRNA in Metastatic Castration-Resistant Prostate Cancer. Int J Mol Sci 2024; 25:2630. [PMID: 38473877 DOI: 10.3390/ijms25052630] [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: 01/17/2024] [Revised: 02/19/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease due to the absence of effective therapies. A more comprehensive understanding of molecular events, encompassing the dysregulation of microRNAs (miRs) and metabolic reprogramming, holds the potential to unveil precise mechanisms underlying mCRPC. This study aims to assess the expression of selected serum exosomal miRs (miR-15a, miR-16, miR-19a-3p, miR-21, and miR-141a-3p) alongside serum metabolomic profiling and their correlation in patients with mCRPC and benign prostate hyperplasia (BPH). Blood serum samples from mCRPC patients (n = 51) and BPH patients (n = 48) underwent metabolome analysis through 1H-NMR spectroscopy. The expression levels of serum exosomal miRs in mCRPC and BPH patients were evaluated using a quantitative real-time polymerase chain reaction (qRT-PCR). The 1H-NMR metabolomics analysis revealed significant alterations in lactate, acetate, citrate, 3-hydroxybutyrate, and branched-chain amino acids (BCAAs, including valine, leucine, and isoleucine) in mCRPC patients compared to BPH patients. MiR-15a, miR-16, miR-19a-3p, and miR-21 exhibited a downregulation of more than twofold in the mCRPC group. Significant correlations were predominantly observed between lactate, citrate, acetate, and miR-15a, miR-16, miR-19a-3p, and miR-21. The importance of integrating metabolome analysis of serum with selected serum exosomal miRs in mCRPC patients has been confirmed, suggesting their potential utility for distinguishing of mCRPC from BPH.
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Affiliation(s)
- Daniel Evin
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
- Clinic of Nuclear Medicine, Jessenius Faculty of Medicine in Martin, University Hospital in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Andrea Evinová
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Eva Baranovičová
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Miroslava Šarlinová
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Jana Jurečeková
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Peter Kaplán
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Hubert Poláček
- Clinic of Nuclear Medicine, Jessenius Faculty of Medicine in Martin, University Hospital in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Erika Halašová
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Róbert Dušenka
- Clinic of Urology, Jessenius Faculty of Medicine in Martin, University Hospital in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Lukáš Briš
- Clinic of Urology, Jessenius Faculty of Medicine in Martin, University Hospital in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Martina Knoško Brožová
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
| | - Monika Kmeťová Sivoňová
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 03601 Martin, Slovakia
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Bansal N, Kumar M, Gupta A. Richer than previously probed: An application of 1H NMR reveals one hundred metabolites using only fifty microliter serum. Biophys Chem 2024; 305:107153. [PMID: 38088005 DOI: 10.1016/j.bpc.2023.107153] [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: 11/03/2023] [Revised: 11/22/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
The classical approach restricts the detection of metabolites in serum samples by using nuclear magnetic resonance (NMR) spectroscopy; however, the presence of copious proteins and lipoproteins emphasize and necessitate the development of a contemporary, high-throughput tactic. To eliminate the lipoproteins and proteins from sera to engender filtered sera (FS), the study was executed with 50 μl serum obtained from five healthy individuals with 5 years of age difference from 25 to 45 years old and the application of a unique mechanical filter with molecular weight cut-off value of 2KDa. The 10 μl FS from each individual was pooled to make 50 μl final volume filled in a co-axial tube for acquisition of a battery of 1D/2D investigations at 800 MHz NMR spectrometer and the assigned metabolites was confirmed through mass spectrometry as well as by comparing 1H NMR spectra of individual metabolites. This innovative tactic is commissioning to reveal more than 100 metabolites. In contrast to the protein precipitation method, 24 new metabolites were recognized in the present study. The present innovative approach characterizes nucleosides, nitrogenous bases, and volatile metabolites that possibly produce a landmark for the delineation of a comprehensive metabolic profile applicable for detection of the molecular cause of pathogenicity, early-stage disease detection and prognosis, inborn error of metabolism, and forensic investigations exerting the least volume of FS and NMR spectroscopy. The assignment of 100 metabolites using 1H NMR-based FS is described for the first time in the present report.
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Affiliation(s)
- Navneeta Bansal
- Department of Urology, King George's Medical University, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George's Medical University, Lucknow, India.
| | - Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
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Polachini GM, de Castro TB, Smarra LFS, Henrique T, de Paula CHD, Severino P, López RVM, Carvalho AL, de Mattos Zeri AC, Silva IDCG, Tajara EH. Plasma metabolomics of oral squamous cell carcinomas based on NMR and MS approaches provides biomarker identification and survival prediction. Sci Rep 2023; 13:8588. [PMID: 37237049 DOI: 10.1038/s41598-023-34808-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
Metabolomics has proven to be an important omics approach to understand the molecular pathways underlying the tumour phenotype and to identify new clinically useful markers. The literature on cancer has illustrated the potential of this approach as a diagnostic and prognostic tool. The present study aimed to analyse the plasma metabolic profile of patients with oral squamous cell carcinoma (OSCC) and controls and to compare patients with metastatic and primary tumours at different stages and subsites using nuclear magnetic resonance and mass spectrometry. To our knowledge, this is the only report that compared patients at different stages and subsites and replicates collected in diverse institutions at different times using these methodologies. Our results showed a plasma metabolic OSCC profile suggestive of abnormal ketogenesis, lipogenesis and energy metabolism, which is already present in early phases but is more evident in advanced stages of the disease. Reduced levels of several metabolites were also associated with an unfavorable prognosis. The observed metabolomic alterations may contribute to inflammation, immune response inhibition and tumour growth, and may be explained by four nonexclusive views-differential synthesis, uptake, release, and degradation of metabolites. The interpretation that assimilates these views is the cross talk between neoplastic and normal cells in the tumour microenvironment or in more distant anatomical sites, connected by biofluids, signalling molecules and vesicles. Additional population samples to evaluate the details of these molecular processes may lead to the discovery of new biomarkers and novel strategies for OSCC prevention and treatment.
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Affiliation(s)
- Giovana Mussi Polachini
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Tialfi Bergamin de Castro
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Luis Fabiano Soares Smarra
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil
| | - Tiago Henrique
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Carlos Henrique Diniz de Paula
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Patricia Severino
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | | | - André Lopes Carvalho
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, SP, Brazil
| | | | | | - Eloiza H Tajara
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil.
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.
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Dubey R, Sinha N, Jagannathan NR. Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research. NMR IN BIOMEDICINE 2023; 36:e4686. [PMID: 34970810 DOI: 10.1002/nbm.4686] [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: 07/07/2021] [Revised: 11/18/2021] [Accepted: 12/21/2021] [Indexed: 06/14/2023]
Abstract
Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.
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Affiliation(s)
- Richa Dubey
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Naranamangalam R Jagannathan
- Department of Radiology, Chettinad Hospital & Research Institute, Chettinad Academy of Research & Education, Kelambakkam, India
- Department of Radiology, Sri Ramachandra Institute of Higher Education & Research, Chennai, India
- Department of Electrical Engineering, Indian Institute Technology, Madras, Chennai, India
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Krishnan S, Kanthaje S, Punchappady DR, Mujeeburahiman M, Ratnacaram CK. Circulating metabolite biomarkers: a game changer in the human prostate cancer diagnosis. J Cancer Res Clin Oncol 2023; 149:951-967. [PMID: 35764700 DOI: 10.1007/s00432-022-04113-y] [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: 04/20/2022] [Accepted: 06/06/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE Prostate cancer (PCa) is the second most commonly diagnosed cancer in men in Western and Asian countries. Serum prostate-specific antigen (PSA) test has been the routine diagnostic method despite the tremendous research in diagnostic markers for early detection of PCa. A shift towards a promising and potential biomarker for PCa detection is through metabolomic profiling of biofluids, particularly the blood and urine samples. Finding reliable, routinely usable circulating metabolite biomarkers may not be a distant reality. METHODS We performed a PubMed-based literature search of metabolite biomarkers in blood and urine for the early detection of prostate cancer. The timeline of these searches was limited between 2007 and 2022 and the following keywords were used: 'metabolomics', 'liquid biopsy', 'circulating metabolites', 'serum metabolite', 'plasma metabolite', and 'urine metabolite' with respect to 'prostate cancer'. We focussed only on diagnosis-based studies with only the subject-relevant articles published in the English language and excluded all of the other irrelevant publications that included prostate tissue biomarkers and cell line biomarkers. RESULTS We have consolidated all the blood and urine-based potential metabolite candidates in individual as well as panels, including lipid classes, fatty acids, amino acids, and volatile organic compounds which may become useful for PCa diagnosis. CONCLUSION All these metabolome findings unveil the impact of different dimensions of PCa development, giving a promising strategy to diagnose the disease since suspected individuals can be subjected to repeated and largescale blood and urine testing.
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Affiliation(s)
- Sabareeswaran Krishnan
- Yenepoya Research Centre, Yenepoya (Deemed to Be University), University Road, Deralakatte, Mangaluru, 575018, Karnataka, India
- Department of Urology, Yenepoya Medical College Hospital, Deralakatte, Mangaluru, 575018, Karnataka, India
| | - Shruthi Kanthaje
- Yenepoya Research Centre, Yenepoya (Deemed to Be University), University Road, Deralakatte, Mangaluru, 575018, Karnataka, India
| | - Devasya Rekha Punchappady
- Yenepoya Research Centre, Yenepoya (Deemed to Be University), University Road, Deralakatte, Mangaluru, 575018, Karnataka, India
| | - M Mujeeburahiman
- Department of Urology, Yenepoya Medical College Hospital, Deralakatte, Mangaluru, 575018, Karnataka, India.
| | - Chandrahas Koumar Ratnacaram
- Yenepoya Research Centre, Yenepoya (Deemed to Be University), University Road, Deralakatte, Mangaluru, 575018, Karnataka, India.
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Jin Y, Fan S, Jiang W, Zhang J, Yang L, Xiao J, An H, Ren L. Two effective models based on comprehensive lipidomics and metabolomics can distinguish BC versus HCs, and TNBC versus non-TNBC. Proteomics Clin Appl 2022; 17:e2200042. [PMID: 36443927 DOI: 10.1002/prca.202200042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/10/2022] [Accepted: 11/22/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND Lipidomics and metabolomics are closely related to tumor phenotypes, and serum lipoprotein subclasses and small-molecule metabolites are considered as promising biomarkers for breast cancer (BC) diagnosis. This study aimed to explore potential biomarker models based on lipidomic and metabolomic analysis that could distinguish BC from healthy controls (HCs) and triple-negative BC (TNBC) from non-TNBC. METHODS Blood samples were collected from 114 patients with BC and 75 HCs. A total of 112 types of lipoprotein subclasses and 30 types of small-molecule metabolites in the serum were detected by 1 H-NMR. All lipoprotein subclasses and small-molecule metabolites were subjected to a three-step screening process in the order of significance (p < 0.05), univariate regression (p < 0.1), and lasso regression (nonzero coefficient). Discriminant models of BC versus HCs and TNBC versus non-TNBC were established using binary logistic regression. RESULTS We developed a valid discriminant model based on three-biomarker panel (formic acid, TPA2, and L6TG) that could distinguish patients with BC from HCs. The area under the receiver operating characteristic curve (AUC) was 0.999 (95% confidence interval [CI]: 0.995-1.000) and 0.990 (95% CI: 0.959-1.000) in the training and validation sets, respectively. Based on the panel (D-dimer, CA15-3, CEA, L5CH, glutamine, and ornithine), a discriminant model was established to differentiate between TNBC and non-TNBC, with AUC of 0.892 (95% CI: 0.778-0.967) and 0.905 (95% CI: 0.754-0.987) in the training and validation sets, respectively. CONCLUSION This study revealed lipidomic and metabolomic differences between BC versus HCs and TNBC versus non-TNBC. Two validated discriminatory models established against lipidomic and metabolomic differences can accurately distinguish BC from HCs and TNBC from non-TNBC. IMPACT Two validated discriminatory models can be used for early BC screening and help BC patients avoid time-consuming, expensive, and dangerous BC screening.
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Affiliation(s)
- Yu Jin
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Shuoqing Fan
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Wenna Jiang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jingya Zhang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Lexin Yang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jiawei Xiao
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Haohua An
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Li Ren
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
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Relevance of Emerging Metabolomics-Based Biomarkers of Prostate Cancer: A Systematic Review. Expert Rev Mol Med 2022; 24:e25. [PMID: 35730322 DOI: 10.1017/erm.2022.20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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11
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Zhang X, Xia B, Zheng H, Ning J, Zhu Y, Shao X, Liu B, Dong B, Gao H. Identification of characteristic metabolic panels for different stages of prostate cancer by 1H NMR-based metabolomics analysis. Lab Invest 2022; 20:275. [PMID: 35715864 PMCID: PMC9205125 DOI: 10.1186/s12967-022-03478-5] [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: 01/26/2022] [Accepted: 06/11/2022] [Indexed: 12/14/2022]
Abstract
Background Prostate cancer (PCa) is the second most prevalent cancer in males worldwide, yet detecting PCa and its metastases remains a major challenging task in clinical research setups. The present study aimed to characterize the metabolic changes underlying the PCa progression and investigate the efficacy of related metabolic panels for an accurate PCa assessment. Methods In the present study, 75 PCa subjects, 62 PCa patients with bone metastasis (PCaB), and 50 benign prostatic hyperplasia (BPH) patients were enrolled, and we performed a cross-sectional metabolomics analysis of serum samples collected from these subjects using a 1H nuclear magnetic resonance (NMR)-based metabolomics approach. Results Multivariate analysis revealed that BPH, PCa, and PCaB groups showed distinct metabolic divisions, while univariate statistics integrated with variable importance in the projection (VIP) scores identified a differential metabolite series, which included energy, amino acid, and ketone body metabolism. Herein, we identified a series of characteristic serum metabolic changes, including decreased trends of 3-HB and acetone as well as elevated trends of alanine in PCa patients compared with BPH subjects, while increased levels of 3-HB and acetone as well as decreased levels of alanine in PCaB patients compared with PCa. Additionally, our results also revealed the metabolic panels of discriminant metabolites coupled with the clinical parameters (age and body mass index) for discrimination between PCa and BPH, PCaB and BPH, PCaB and PCa achieved the AUC values of 0.828, 0.917, and 0.872, respectively. Conclusions Overall, our study gave successful discrimination of BPH, PCa and PCaB, and we characterized the potential metabolic alterations involved in the PCa progression and its metastases, including 3-HB, acetone and alanine. The defined biomarker panels could be employed to aid in the diagnosis and classification of PCa in clinical practice. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03478-5.
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Affiliation(s)
- Xi Zhang
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China
| | - Binbin Xia
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Hong Zheng
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China
| | - Jie Ning
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yinjie Zhu
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Xiaoguang Shao
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Binrui Liu
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China
| | - Baijun Dong
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
| | - Hongchang Gao
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China. .,Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China. .,Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, 325000, China.
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12
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Resurreccion EP, Fong KW. The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer. Metabolites 2022; 12:metabo12060488. [PMID: 35736421 PMCID: PMC9230859 DOI: 10.3390/metabo12060488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/21/2022] [Accepted: 05/24/2022] [Indexed: 02/06/2023] Open
Abstract
Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.
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Affiliation(s)
- Eleazer P. Resurreccion
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40506, USA;
| | - Ka-wing Fong
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40506, USA;
- Markey Cancer Center, University of Kentucky, Lexington, KY 40506, USA
- Correspondence: ; Tel.: +1-859-562-3455
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13
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Amante E, Cerrato A, Alladio E, Capriotti AL, Cavaliere C, Marini F, Montone CM, Piovesana S, Laganà A, Vincenti M. Comprehensive biomarker profiles and chemometric filtering of urinary metabolomics for effective discrimination of prostate carcinoma from benign hyperplasia. Sci Rep 2022; 12:4361. [PMID: 35288652 PMCID: PMC8921285 DOI: 10.1038/s41598-022-08435-2] [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: 10/04/2021] [Accepted: 03/04/2022] [Indexed: 11/23/2022] Open
Abstract
Prostate cancer (PCa) is the most commonly diagnosed cancer in male individuals, principally affecting men over 50 years old, and is the leading cause of cancer-related deaths. Actually, the measurement of prostate-specific antigen level in blood is affected by limited sensitivity and specificity and cannot discriminate PCa from benign prostatic hyperplasia patients (BPH). In the present paper, 20 urine samples from BPH patients and 20 from PCa patients were investigated to develop a metabolomics strategy useful to distinguish malignancy from benign hyperplasia. A UHPLC-HRMS untargeted approach was carried out to generate two large sets of candidate biomarkers. After mass spectrometric analysis, an innovative chemometric data treatment was employed involving PLS-DA classification with repeated double cross-validation and permutation test to provide a rigorously validated PLS-DA model. Simultaneously, this chemometric approach filtered out the most effective biomarkers and optimized their relative weights to yield the highest classification efficiency. An unprecedented portfolio of prostate carcinoma biomarkers was tentatively identified including 22 and 47 alleged candidates from positive and negative ion electrospray (ESI+ and ESI-) datasets. The PLS-DA model based on the 22 ESI+ biomarkers provided a sensitivity of 95 ± 1% and a specificity of 83 ± 3%, while that from the 47 ESI- biomarkers yielded an 88 ± 3% sensitivity and a 91 ± 2% specificity. Many alleged biomarkers were annotated, belonging to the classes of carnitine and glutamine metabolites, C21 steroids, amino acids, acetylcholine, carboxyethyl-hydroxychroman, and dihydro(iso)ferulic acid.
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Affiliation(s)
- Eleonora Amante
- Department of Chemistry, University of Turin, Via P. Giuria 7, 10125, Turin, Italy
| | - Andrea Cerrato
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Eugenio Alladio
- Department of Chemistry, University of Turin, Via P. Giuria 7, 10125, Turin, Italy
- Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Orbassano, Turin, Italy
| | - Anna Laura Capriotti
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy.
| | - Chiara Cavaliere
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Federico Marini
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Carmela Maria Montone
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Susy Piovesana
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Aldo Laganà
- Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Marco Vincenti
- Department of Chemistry, University of Turin, Via P. Giuria 7, 10125, Turin, Italy
- Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Orbassano, Turin, Italy
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14
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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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15
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Jagannathan N, Reddy RR. Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer. Indian J Urol 2022; 38:99-109. [PMID: 35400867 PMCID: PMC8992727 DOI: 10.4103/iju.iju_416_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 12/16/2021] [Accepted: 02/09/2022] [Indexed: 12/24/2022] Open
Abstract
Nuclear magnetic resonance (NMR) metabolomics is a powerful analytical technique and a tool which has unique characteristics and capabilities for the evaluation of a number of biochemicals/metabolites of cancer and other disease processes that are present in biofluids (urine and blood) and tissues. The potential of NMR metabolomics in prostate cancer (PCa) has been explored by researchers and its usefulness has been documented. A large number of metabolites such as citrate, choline, and sarcosine were detected by NMR metabolomics from biofluids and tissues related to PCa and their levels were compared with controls and benign prostatic hyperplasia. The changes in the levels of these metabolites aid in the diagnosis and help to understand the dysregulated metabolic pathways in PCa. We review recent studies on in vitro and ex vivo NMR spectroscopy-based PCa metabolomics and its possible role as a diagnostic tool.
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16
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Haroon M, Tahir M, Nawaz H, Majeed MI, Al-Saadi AA. Surface-enhanced Raman scattering (SERS) spectroscopy for prostate cancer diagnosis: A review. Photodiagnosis Photodyn Ther 2021; 37:102690. [PMID: 34921990 DOI: 10.1016/j.pdpdt.2021.102690] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/28/2021] [Accepted: 12/13/2021] [Indexed: 12/13/2022]
Abstract
The present review focuses on the diagnosis of prostate cancer using surface enhanced Raman scattering (SERS) spectroscopy. On the basis of literature search, SERS-based analysis for prostate cancer detection of different sample types is reported in the present study. Prostate cancer is responsible for nearly one-tenth of all cell cancer deaths among men. Significant efforts have been dedicated to establish precise and sensitive monitoring techniques to detect prostate cancer biomarkers in different types of body samples. Among the various spectro-analytical techniques investigated to achieve this objective, SERS spectroscopy has been proven as a promising approach that provides noticeable enhancements of the Raman sensitivity when the target biomolecules interact with a nanostructured surface. The purpose of this review is to give a brief overview of the SERS-basedapproach and other spectro-analytical strategies being used for the detection and quantification of prostate cancer biomarkers. The revolutionary development of SERS methods for the diagnosis of prostate cancer has been discussed in more details based on the reported literature. It has been noticed that the SERS-based immunoassay presents reliable results for the prostate cancer quantification. The EC-SERS, which integrates electrochemistry with the SERS model, could also offer a potential ultrasensitive strategy, although its application in prostate cancer analysis has been still limited.
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Affiliation(s)
- Muhammad Haroon
- Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
| | - Muhammad Tahir
- Department of Chemistry, University of Agriculture Faisalabad, Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Pakistan
| | | | - Abdulaziz A Al-Saadi
- Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia; Interdisciplinary Research Center (IRC) in Refinery and Advanced Chemicals, Dhahran 31261, Saudi Arabia.
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17
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Kumar D, Bansal N, Gupta A, Mandhani A, Lal H, Kumar M, Sankhwar SN. Metabolomics of prostate cancer: Knock-in versus knock-out prostate. J Pharm Biomed Anal 2021; 205:114333. [PMID: 34461489 DOI: 10.1016/j.jpba.2021.114333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/16/2021] [Accepted: 08/18/2021] [Indexed: 10/20/2022]
Abstract
Several metabolomics-derived biomarkers of prostate cancer (PC) have been reported with pre-radical prostatectomy (RP) (knock-in PC) conditions; however, uncontested PC biomarkers panel appraisal and investigation of correlative evidence of these measures is lacking through post-RP (knock-out PC). We sought to explore patients' filtered serum-based metabolomics derived signature measures in knock-in PC (n = 90) using nuclear magnetic resonance spectroscopy and multiple rigorous statistical analyses, and to develop the correlative evidence of these measures through knock-out PC (n = 90) follow-up on the 15th and 30th days. The glutamate, citrate and glycine were observed as hallmarks of PC. Observed trends revealed; augmented glutamate level in knock-in PC following a sudden drop and subsequently upside of glutamate at 15th and 30th days of knock-out PC, reduction of citrate in knock-in PC subsequently gradual increase of citrate in knock-out PC, and glycine lessening in knock-in PC following augmentation on 30th day of knock-out PC. This study-based evidence clears the doubts regarding the discovery of metabolomics-derived PC biomarkers.
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Affiliation(s)
- Deepak Kumar
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Navneeta Bansal
- Department of Urology, King George's Medical University, Lucknow, India
| | - Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
| | - Anil Mandhani
- Department of Urology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Hira Lal
- Department of Radiodiagnosis, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George's Medical University, Lucknow, India
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18
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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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19
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Cerrato A, Bedia C, Capriotti AL, Cavaliere C, Gentile V, Maggi M, Montone CM, Piovesana S, Sciarra A, Tauler R, Laganà A. Untargeted metabolomics of prostate cancer zwitterionic and positively charged compounds in urine. Anal Chim Acta 2021; 1158:338381. [PMID: 33863412 DOI: 10.1016/j.aca.2021.338381] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/03/2021] [Accepted: 03/04/2021] [Indexed: 02/07/2023]
Abstract
Prostate cancer, a leading cause of cancer-related deaths worldwide, principally occurs in over 50-year-old men. Nowadays there is urgency to discover biomarkers alternative to prostate-specific antigen, as it cannot discriminate patients with benign prostatic hyperplasia from clinically significant forms of prostatic cancer. In the present paper, 32 benign prostatic hyperplasia and 41 prostatic cancer urine samples were collected and analyzed. Polar and positively charged metabolites were therein investigated using an analytical platform comprising an up to 40-fold analyte enrichment step by graphitized carbon black solid-phase extraction, HILIC separation, and untargeted high-resolution mass spectrometry analysis. These classes of compounds are often neglected in common metabolomics experiments even though previous studies reported their significance in cancer biomarker discovery. The complex metabolomics big datasets, generated by the UHPLC-HRMS, were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest data and their analysis by the Multivariate Curve-Resolution Alternating Least Squares chemometrics method. This approach allowed the resolution and tentative identification of the metabolites differentially expressed by the two data sets. Among these, amino acids and carnitine derivatives were tentatively identified highlighting the importance of the proposed methodology for cancer biomarker research.
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Affiliation(s)
- Andrea Cerrato
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Carmen Bedia
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Anna Laura Capriotti
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy.
| | - Chiara Cavaliere
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Vincenzo Gentile
- Dipartimento di Scienze Ginecologio-ostetriche e Scienze Urologiche, Sapienza Università, di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Martina Maggi
- Dipartimento di Scienze Ginecologio-ostetriche e Scienze Urologiche, Sapienza Università, di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Carmela Maria Montone
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Susy Piovesana
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Alessandro Sciarra
- Dipartimento di Scienze Ginecologio-ostetriche e Scienze Urologiche, Sapienza Università, di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Roma Tauler
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Aldo Laganà
- Dipartimento di Chimica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy; CNR NANOTEC, Campus Ecotekne, University of Salento, Via Monteroni, 73100, Lecce, Italy
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20
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Metabolic regulation of prostate cancer heterogeneity and plasticity. Semin Cancer Biol 2020; 82:94-119. [PMID: 33290846 DOI: 10.1016/j.semcancer.2020.12.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 11/12/2020] [Accepted: 12/03/2020] [Indexed: 02/07/2023]
Abstract
Metabolic reprogramming is one of the main hallmarks of cancer cells. It refers to the metabolic adaptations of tumor cells in response to nutrient deficiency, microenvironmental insults, and anti-cancer therapies. Metabolic transformation during tumor development plays a critical role in the continued tumor growth and progression and is driven by a complex interplay between the tumor mutational landscape, epigenetic modifications, and microenvironmental influences. Understanding the tumor metabolic vulnerabilities might open novel diagnostic and therapeutic approaches with the potential to improve the efficacy of current tumor treatments. Prostate cancer is a highly heterogeneous disease harboring different mutations and tumor cell phenotypes. While the increase of intra-tumor genetic and epigenetic heterogeneity is associated with tumor progression, less is known about metabolic regulation of prostate cancer cell heterogeneity and plasticity. This review summarizes the central metabolic adaptations in prostate tumors, state-of-the-art technologies for metabolic analysis, and the perspectives for metabolic targeting and diagnostic implications.
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21
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Gómez-Cebrián N, García-Flores M, Rubio-Briones J, López-Guerrero JA, Pineda-Lucena A, Puchades-Carrasco L. Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients. J Proteome Res 2020; 19:4082-4092. [PMID: 32924497 DOI: 10.1021/acs.jproteome.0c00493] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.
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Affiliation(s)
- Nuria Gómez-Cebrián
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.,Laboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología (FIVO), Valencia 46009, Spain
| | - María García-Flores
- Laboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología (FIVO), Valencia 46009, Spain.,IVO-CIPF Joint Research Unit of Cancer, Príncipe Felipe Research Centre (CIPF), Valencia 46012, Spain
| | - José Rubio-Briones
- Department of Urology, Fundación Instituto Valenciano de Oncología (FIVO), Valencia 46009, Spain
| | - José Antonio López-Guerrero
- Laboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología (FIVO), Valencia 46009, Spain.,IVO-CIPF Joint Research Unit of Cancer, Príncipe Felipe Research Centre (CIPF), Valencia 46012, Spain.,Department of Basic Medical Sciences, School of Medicine, Catholic University of Valencia 'San Vicente Martir', Valencia 46001, Spain
| | - Antonio Pineda-Lucena
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.,Molecular Therapeutics Program, Centro de Investigación Médica Aplicada, Navarra 31008, Spain
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22
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Sharma U, Jagannathan NR. Metabolism of prostate cancer by magnetic resonance spectroscopy (MRS). Biophys Rev 2020; 12:1163-1173. [PMID: 32918707 DOI: 10.1007/s12551-020-00758-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/04/2020] [Indexed: 12/11/2022] Open
Abstract
Understanding the metabolism of prostate cancer (PCa) is important for developing better diagnostic approaches and also for exploring new therapeutic targets. Magnetic resonance spectroscopy (MRS) techniques have been shown to be useful in the detection and quantification of metabolites. PCa illustrates metabolic phenotype, showing lower levels of citrate (Cit), a key metabolite of oxidative phosphorylation and alteration in several metabolic pathways to sustain tumor growth. Recently, dynamic nuclear polarization (DNP) studies have documented high rates of glycolysis (Warburg phenomenon) in PCa. High-throughput metabolic profiling strategies using MRS on variety of samples including intact tissues, biofluids like prostatic fluid, seminal fluid, blood plasma/sera, and urine have also played a vital role in understanding the abnormal metabolic activity of PCa patients. The enhanced analytical potential of these techniques in the detection and quantification of a large number of metabolites provides an in-depth understanding of metabolic rewiring associated with the tumorigenesis. Metabolomics analysis offers dual advantages of identification of diagnostic and predictive biomarkers as well as in understanding the altered metabolic pathways which can be targeted for inhibiting the cancer progression. This review briefly describes the potential applications of in vivo 1H MRS, high-resolution magic angle spinning spectroscopy (HRMAS) and in vitro MRS methods in understanding the metabolic changes of PCa and its usefulness in the management of PCa patients.
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Affiliation(s)
- Uma Sharma
- Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Naranamangalam R Jagannathan
- Department of Radiology, Chettinad Hospital & Research Institute, Chettinad Academy of Research & Education, Kelambakkam, TN, 603103, India.
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, 600116, India.
- Department of Electrical Engineering, Indian Institute Technology Madras, Chennai, 600 036, India.
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23
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Markin PA, Brito A, Moskaleva N, Lartsova EV, Shpot YV, Lerner YV, Mikhajlov VY, Potoldykova NV, Enikeev DV, La Frano MR, Appolonova SA. Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score. Metabolomics 2020; 16:74. [PMID: 32556743 DOI: 10.1007/s11306-020-01694-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 06/05/2020] [Indexed: 12/24/2022]
Abstract
INTRODUCTION The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling. OBJECTIVE To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa). METHODS Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined. RESULTS The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)]. CONCLUSIONS This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.
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Affiliation(s)
- Pavel A Markin
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991
- PhD Program in Nanosciences and Advanced Technologies, University of Verona, Verona, Italy
| | - Alex Brito
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991.
| | - Natalia Moskaleva
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991
| | - Ekaterina V Lartsova
- University Clinical Hospital, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Yevgeny V Shpot
- Research Institute of Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Yulia V Lerner
- Department of Pathological Anatomy, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Vasily Y Mikhajlov
- University Clinical Hospital, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Natalia V Potoldykova
- Research Institute of Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Dimitry V Enikeev
- Research Institute of Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Michael R La Frano
- Department of Food Science and Nutrition, California Polytechnic State University, San Luis Obispo, CA, USA
- Center for Health Research, California Polytechnic State University, San Luis Obispo, CA, USA
| | - Svetlana A Appolonova
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991.
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24
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Gupta A, Bansal N, Mitash N, Kumar D, Kumar M, Sankhwar SN, Mandhani A, Singh UP. NMR-derived targeted serum metabolic biomarkers appraisal of bladder cancer: A pre- and post-operative evaluation. J Pharm Biomed Anal 2020; 183:113134. [PMID: 32070930 DOI: 10.1016/j.jpba.2020.113134] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 01/24/2020] [Accepted: 01/26/2020] [Indexed: 12/23/2022]
Abstract
With high morbidity and mortality, urinary bladder cancer (BC) ranks fifth among common cancers globally. The inherent limitations of urine cytology and cystoscopy, and marginal enhancements in the rate of survival promt us to develop surrogate serum based metabolic biomarkers of screening, identification, and follow-up protocols of management for BC patients. Earlier, we exhibited that abnormal expression levels of dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine in serum may be used as signature metabolites to differentiate BC from healthy controls (HC) (J. Proteome Res. 2013; 12(12):5839-50). Here we further gauge and validate these observations by comparing pre-operative to post-operative follow-up BC patients. This study was conducted on 160 sera samples involving HC (n = 52), pre-operative (n = 55) and post-operative (n = 53) BC cases. 1H nuclear magnetic resonance (NMR) spectroscopy was used to generate serum metabolic profiles and to gauge aberrantly expressed metabolites. The targeted metabolomic approach revealed that the expression levels of these signature metabolites were progressively and significantly decreased in post-operative follow-up at the interval of 30, 60, and 90 days compared to pre-operative BC sera samples and were maintained at HC levels. Serum metabolic biomarkers appear to be an inspiring and least-invasive tactic for detection and prognosticating BC patient follow-up.
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Affiliation(s)
- Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
| | - Navneeta Bansal
- Department of Urology, King George's Medical University, Lucknow, India
| | | | - Deepak Kumar
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George's Medical University, Lucknow, India
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25
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Wu XM, Jin C, Gu YL, Chen WQ, Zhu MQ, Zhang S, Zhang Z. Gluconokinase IDNK Promotes Cell Proliferation and Inhibits Apoptosis in Hepatocellular Carcinoma. Onco Targets Ther 2020; 13:1767-1776. [PMID: 32161472 PMCID: PMC7049873 DOI: 10.2147/ott.s234055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 02/13/2020] [Indexed: 01/20/2023] Open
Abstract
Purpose Hepatocellular carcinoma (HCC) is one of the deadliest cancers globally with a poor prognosis. Breakthroughs in the treatment of HCC are urgently needed. This study explored the role of IDNK in the development and progression of HCC. Methods IDNK expression was suppressed using short hairpin (shRNA) in BEL-7404 and Huh-7 cells. The expression of IDNK in HCC cells after IDNK knockdown was evaluated by real-time quantitative RT-PCR analysis and Western blot. After IDNK silencing, the proliferation and apoptosis of HCC cells were evaluated by Celigo cell counting, flow cytometry analysis, MTT assay, and caspase3/7 assay. Gene expressions in BEL-7404 cells transfected with IDNK shRNA lentivirus plasmid and blank control plasmid were evaluated by microarray analysis. The differentially expressed genes induced by deregulation of IDNKwere identified, followed by pathway analysis. Results The expression of IDNK at the mRNA and protein levels was considerably reduced in shRNA IDNK transfected cells. Knockdown of IDNK significantly inhibited HCC cell proliferation and increased cell apoptosis. A total of 1196 genes (585 upregulated and 611 downregulated) were differentially expressed in IDNK knockdown BEL-7404 cells. The pathway of tRNA charging with Z-score = -3 was significantly inhibited in BEL-7404 cells with IDNK knockdown. Conclusion IDNK plays a key role in the proliferation and apoptosis of HCC cells. IDNK may be a candidate therapeutic target for HCC.
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Affiliation(s)
- Xiao-Min Wu
- Department of Integrated Traditional Chinese and Western Medicine Oncology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214062, People's Republic of China
| | - Cheng Jin
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214041, People's Republic of China
| | - Yuan-Long Gu
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214041, People's Republic of China
| | - Wu-Qiang Chen
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214041, People's Republic of China
| | - Mao-Qun Zhu
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214041, People's Republic of China
| | - Shuo Zhang
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214041, People's Republic of China
| | - Zhen Zhang
- Department of Integrated Traditional Chinese and Western Medicine Oncology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214062, People's Republic of China
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26
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Gholizadeh N, Pundavela J, Nagarajan R, Dona A, Quadrelli S, Biswas T, Greer PB, Ramadan S. Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer. Urol Oncol 2020; 38:150-173. [PMID: 31937423 DOI: 10.1016/j.urolonc.2019.10.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 09/22/2019] [Accepted: 10/31/2019] [Indexed: 01/17/2023]
Abstract
Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.
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Affiliation(s)
- Neda Gholizadeh
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia
| | - Jay Pundavela
- Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Rajakumar Nagarajan
- Human Magnetic Resonance Center, Institute for Applied Life Sciences, University of Massachusetts Amherst, MA, USA
| | - Anthony Dona
- Kolling Institute of Medical Research, Royal North Shore Hospital, University of Sydney, St Leonards, NSW, Australia
| | - Scott Quadrelli
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia; Radiology Department, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Tapan Biswas
- Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India
| | - Peter B Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia; Radiation Oncology, Calvary Mater Newcastle, Newcastle, NSW, Australia
| | - Saadallah Ramadan
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia; Imaging Centre, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
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27
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Song Z, Wang H, Yin X, Deng P, Jiang W. Application of NMR metabolomics to search for human disease biomarkers in blood. Clin Chem Lab Med 2019; 57:417-441. [PMID: 30169327 DOI: 10.1515/cclm-2018-0380] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Accepted: 07/16/2018] [Indexed: 02/05/2023]
Abstract
Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.
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Affiliation(s)
- Zikuan Song
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Haoyu Wang
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Xiaotong Yin
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Pengchi Deng
- Analytical and Testing Center, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Wei Jiang
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China
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28
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Ranjan R, Sinha N. Nuclear magnetic resonance (NMR)-based metabolomics for cancer research. NMR IN BIOMEDICINE 2019; 32:e3916. [PMID: 29733484 DOI: 10.1002/nbm.3916] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/01/2018] [Accepted: 02/12/2018] [Indexed: 06/08/2023]
Abstract
Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research.
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Affiliation(s)
- Renuka Ranjan
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
- School of Biotechnology, Institute of Science Banaras Hindu University, Varanasi, India
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
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29
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Mycielska ME, Mohr MTJ, Schmidt K, Drexler K, Rümmele P, Haferkamp S, Schlitt HJ, Gaumann A, Adamski J, Geissler EK. Potential Use of Gluconate in Cancer Therapy. Front Oncol 2019; 9:522. [PMID: 31275855 PMCID: PMC6593216 DOI: 10.3389/fonc.2019.00522] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 05/30/2019] [Indexed: 12/12/2022] Open
Abstract
We have recently discovered that cancer cells take up extracellular citrate through plasma membrane citrate transporter (pmCiC) and advantageously use citrate for their metabolism. Citrate uptake can be blocked with gluconate and this results in decreased tumor growth and altered metabolic characteristics of tumor tissue. Interestingly, gluconate, considered to be physiologically neutral, is incidentally used in medicine as a cation carrier, but not as a therapeutically active substance. In this review we discuss the results of our recent research with available literature and suggest that gluconate may be useful in the treatment of cancer.
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Affiliation(s)
- Maria E Mycielska
- Section of Experimental Surgery, Department of Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Markus T J Mohr
- Metempyrosis-Data Analysis in Medicine and Information Technology, Regensburg, Germany
| | - Katharina Schmidt
- Section of Experimental Surgery, Department of Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Konstantin Drexler
- Department of Dermatology, University Hospital Regensburg, Regensburg, Germany
| | - Petra Rümmele
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sebastian Haferkamp
- Department of Dermatology, University Hospital Regensburg, Regensburg, Germany
| | - Hans J Schlitt
- Section of Experimental Surgery, Department of Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Andreas Gaumann
- Institute of Pathology Kaufbeuren-Ravensburg, Kaufbeuren, Germany
| | - Jerzy Adamski
- Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Lehrstuhl Für Experimentelle Genetik, Technische Universität München, Munich, Germany.,Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Edward K Geissler
- Section of Experimental Surgery, Department of Surgery, University Hospital Regensburg, Regensburg, Germany
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30
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Gómez-Cebrián N, Rojas-Benedicto A, Albors-Vaquer A, López-Guerrero JA, Pineda-Lucena A, Puchades-Carrasco L. Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers. Metabolites 2019; 9:metabo9030048. [PMID: 30857149 PMCID: PMC6468766 DOI: 10.3390/metabo9030048] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/01/2019] [Accepted: 03/04/2019] [Indexed: 02/06/2023] Open
Abstract
Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients' biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa.
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Affiliation(s)
- Nuria Gómez-Cebrián
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
- Laboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología, Valencia 46009, Spain.
| | - Ayelén Rojas-Benedicto
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | - Arturo Albors-Vaquer
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | | | - Antonio Pineda-Lucena
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | - Leonor Puchades-Carrasco
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
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31
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Clendinen CS, Gaul DA, Monge ME, Arnold RS, Edison AS, Petros JA, Fernández FM. Preoperative Metabolic Signatures of Prostate Cancer Recurrence Following Radical Prostatectomy. J Proteome Res 2019; 18:1316-1327. [PMID: 30758971 DOI: 10.1021/acs.jproteome.8b00926] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Technological advances in mass spectrometry (MS), liquid chromatography (LC) separations, nuclear magnetic resonance (NMR) spectroscopy, and big data analytics have made possible studying metabolism at an "omics" or systems level. Here, we applied a multiplatform (NMR + LC-MS) metabolomics approach to the study of preoperative metabolic alterations associated with prostate cancer recurrence. Thus far, predicting which patients will recur even after radical prostatectomy has not been possible. Correlation analysis on metabolite abundances detected on serum samples collected prior to surgery from prostate cancer patients ( n = 40 remission vs n = 40 recurrence) showed significant alterations in a number of pathways, including amino acid metabolism, purine and pyrimidine synthesis, tricarboxylic acid cycle, tryptophan catabolism, glucose, and lactate. Lipidomics experiments indicated higher lipid abundances on recurrent patients for a number of classes that included triglycerides, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, diglycerides, acyl carnitines, and ceramides. Machine learning approaches led to the selection of a 20-metabolite panel from a single preoperative blood sample that enabled prediction of recurrence with 92.6% accuracy, 94.4% sensitivity, and 91.9% specificity under cross-validation conditions.
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Affiliation(s)
- Chaevien S Clendinen
- School of Chemistry and Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States
| | - David A Gaul
- School of Chemistry and Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States
| | - María Eugenia Monge
- Centro de Investigaciones en Bionanociencias (CIBION) , Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) , Godoy Cruz 2390 , C1425FQD, Ciudad de Buenos Aires , Argentina
| | - Rebecca S Arnold
- Department of Urology , Emory University , Atlanta , Georgia 30308 , United States
| | - Arthur S Edison
- Department of Genetics and Biochemistry and Molecular Biology, Complex Carbohydrate Research Center , University of Georgia , Athens , Georgia 30602 , United States
| | - John A Petros
- Department of Urology , Emory University , Atlanta , Georgia 30308 , United States.,Atlanta VA Medical Center , Atlanta , Georgia 30033 , United States
| | - Facundo M Fernández
- School of Chemistry and Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States
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32
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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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33
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Yang B, Liao GQ, Wen XF, Chen WH, Cheng S, Stolzenburg JU, Ganzer R, Neuhaus J. Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer. J Zhejiang Univ Sci B 2018; 18:921-933. [PMID: 29119730 DOI: 10.1631/jzus.b1600441] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.
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Affiliation(s)
- Bo Yang
- Department of Urology, Zhoupu Hospital, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Guo-Qiang Liao
- Department of Urology, Zhoupu Hospital, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Xiao-Fei Wen
- Department of Urology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Wei-Hua Chen
- Department of Urology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Sheng Cheng
- Department of Urology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
| | - Jens-Uwe Stolzenburg
- Department of Urology, University Hospital of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany
| | - Roman Ganzer
- Department of Urology, University Hospital of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany
| | - Jochen Neuhaus
- Department of Urology, Zhoupu Hospital, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China.,Division of Urology, Research Laboratory, University of Leipzig, Liebigstraße 19, 04103 Leipzig, Germany
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34
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Giskeødegård GF, Madssen TS, Euceda LR, Tessem MB, Moestue SA, Bathen TF. NMR-based metabolomics of biofluids in cancer. NMR IN BIOMEDICINE 2018; 32:e3927. [PMID: 29672973 DOI: 10.1002/nbm.3927] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 02/13/2018] [Accepted: 03/07/2018] [Indexed: 06/08/2023]
Abstract
This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.
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Affiliation(s)
- Guro F Giskeødegård
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Torfinn S Madssen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Leslie R Euceda
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Siver A Moestue
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
- Department of Health Science, Nord University, Bodø, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
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35
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Beyond the limit of assignment of metabolites using minimal serum samples and 1H NMR spectroscopy with cross-validation by mass spectrometry. J Pharm Biomed Anal 2018; 151:356-364. [PMID: 29413985 DOI: 10.1016/j.jpba.2018.01.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 01/06/2018] [Accepted: 01/08/2018] [Indexed: 12/21/2022]
Abstract
Identification of NMR-based metabolic indexes is limited by the deleterious effects of copious proteins and lipoproteins in the serum that accentuate the need for advance and high-throughput method. We tried to explore the use of a novel filtration (2KDa molecular weight cut-off) approach to remove the proteins from serum following use of less sample volume (only 150 μL of filtered serum), combining an array of 1D/2D NMR experiments (at 800 MHz spectrometer), spiking experiments with standard compounds, and validated by mass spectrometry. This novel method enabled the identification of a large number (n = 73) of metabolites and their percentage of abundance in the present study cohort. Mass spectrometry further validates and confirms the presence of all these 73 metabolites using same filtered serum. This study reveals seven new metabolites (citrulline, inosine, taurine, trimethyl amine, methylmalonate, uracil, methanol) in filtered serum using 1D/2D NMR spectroscopy that were not observed in earlier available literature using protein precipitation approach. This novel method delineates volatile metabolites, nitrogenous bases and nucleosides that may provide a milestone for the identification of inborn error of metabolism, pathogenicity at molecular level, disease identification and prognosis, and forensic studies using minimal volume of filtered serum samples and NMR spectroscopy.
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36
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Armitage EG, Ciborowski M. Applications of Metabolomics in Cancer Studies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 965:209-234. [PMID: 28132182 DOI: 10.1007/978-3-319-47656-8_9] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.
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Affiliation(s)
- Emily Grace Armitage
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad CEU San Pablo, Campus Monteprincipe, Madrid, Spain. .,Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical Veterinary and Life Sciences, Sir Graeme Davies Building, University of Glasgow, Glasgow, UK. .,Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
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37
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Chen N, Rong M, Shao X, Zhang H, Liu S, Dong B, Xue W, Wang T, Li T, Pan J. Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL. Int J Nanomedicine 2017; 12:5399-5407. [PMID: 28794631 PMCID: PMC5538684 DOI: 10.2147/ijn.s137756] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4-10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA-LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.
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Affiliation(s)
- Na Chen
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University
| | - Ming Rong
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University
| | - Xiaoguang Shao
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai
| | - Heng Zhang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University
| | - Shupeng Liu
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University.,Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, People's Republic of China
| | - Baijun Dong
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai
| | - Wei Xue
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai
| | - Tingyun Wang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University
| | - Taihao Li
- Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, People's Republic of China
| | - Jiahua Pan
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai
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38
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Ameta K, Gupta A, Kumar S, Sethi R, Kumar D, Mahdi AA. Essential hypertension: A filtered serum based metabolomics study. Sci Rep 2017; 7:2153. [PMID: 28526818 PMCID: PMC5438387 DOI: 10.1038/s41598-017-02289-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 04/13/2017] [Indexed: 02/07/2023] Open
Abstract
Despite the easy and reliable methods of blood pressure measurement, the screening of essential hypertension (EH) is usually ignored due to delayed onset of symptoms. A probe into the biochemical changes in hypertension would serve as a welcome asset to provide insight into the mechanistic aspects of EH. Filtered serum samples from 64 EH patients and 59 healthy controls (HC) were analysed using 800 MHz nuclear magnetic resonance (NMR) spectroscopy. Application of principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) following receiver operating characteristic (ROC) curve of NMR data reveals significantly perturbed metabolites: alanine, arginine, methionine, pyruvate, adenine, and uracil. This set of metabolites correctly classified 99% of cases from HC and also showed excellent correlation in both isolated elevated diastolic blood pressure (DBP) cases and combined elevated systolic-diastolic blood pressure cases. Proton NMR metabolomics of EH may prove helpful in defining associated biomarkers and serve as an alternate diagnostic tool with judicious clinical assessment.
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Affiliation(s)
- Keerti Ameta
- Department of Biochemistry, King George's Medical University, Lucknow, India
| | - Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
| | - Sudeep Kumar
- Department of Cardiology, SGPGIMS, Lucknow, India
| | - Rishi Sethi
- Department of Cardiology, King George's Medical University, Lucknow, India
| | - Deepak Kumar
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Abbas Ali Mahdi
- Department of Biochemistry, King George's Medical University, Lucknow, India
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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40
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Gupta A, Kumar S, Kashyap S, Kumar D, Kapoor A. Nuclear Magnetic Resonance-Based Metabolomics of Human Filtered Serum: A Great White Hope in Appraisal of Chronic Stable Angina and Myocardial Infarction. J Appl Lab Med 2016; 1:280-293. [PMID: 33626845 DOI: 10.1373/jalm.2016.020776] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Accepted: 08/17/2016] [Indexed: 11/06/2022]
Abstract
BACKGROUND Biochemical detection of chronic stable angina (CSA) and myocardial infarction (MI) are challenging. To address the shortcomings of the conventional biochemical approach for detection of MI, we applied serum lacking proteins and lipoprotein-based metabolomics in an approach using proton nuclear magnetic resonance (1H NMR) spectroscopy for screening of coronary artery disease (CAD) and especially MI. Our aim was to discover differential biomarkers among subjects with normal coronary (NC), CSA, and MI. METHODS The study comprised serum samples from nondiabetic angiographically proven CAD [CSA (n = 88), MI (n = 90)] and NC (n = 55). 1H NMR spectroscopy was used to acquire metabolomics data. Clinical variables such as troponin I (TI), lactate dehydrogenase (LD), creatine kinase (CK, CK-MB, CK-MM), serum creatinine, and lipid profiles were also measured in all subjects. Metabolomic data and clinical measures were appraised separately using a chemometric approach and ROC analysis. RESULTS The screening outcomes revealed that the pattern of methylguanidine, lactate, creatinine, threonine, aspartate, and trimethylamine (TMA), and TI, LD, CK, and serum creatinine were changed in CAD compared to NC. Statistical analysis demonstrated high precision (93.6% by NMR and 67.4% by clinical measures) to distinguish CAD from NC. Further analysis indicated that methylguanidine, arginine, and threonine, and TI, LD, and serum creatinine were significantly changed in CSA compared to MI. Statistical analysis demonstrated high accuracy (88.2% by NMR and 92.1% by clinical measures) to discriminate CSA from MI. CONCLUSIONS In contrast to other laboratory methods, 1H NMR-based metabolomics of filtered sera appears to be a robust, rapid, and minimally invasive approach to probe CSA and MI.
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Affiliation(s)
| | - Sudeep Kumar
- Department of Cardiology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Shiridhar Kashyap
- Department of Cardiology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | | | - Aditya Kapoor
- Department of Cardiology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
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