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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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/23/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management.
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Affiliation(s)
- Mahmoud Assem Hamed
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Valerie Wasinger
- Bioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Centre, UNSW Sydney, Kensington, NSW 2052, Australia
| | - Qi Wang
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Peter Graham
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - David Malouf
- Department of Urology, St, George Hospital, Kogarah, NSW 2217, Australia
| | - Joseph Bucci
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia
| | - Yong Li
- St George and Sutherland Clinical Campuses, School of Clinical Medicine, UNSW Sydney, Kensington, NSW 2052, Australia; Cancer Care Centre, St George Hospital, Kogarah, NSW 2217, Australia.
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2
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Markin SS, Ponomarenko EA, Romashova YA, Pleshakova TO, Ivanov SV, Bedretdinov FN, Konstantinov SL, Nizov AA, Koledinskii AG, Girivenko AI, Shestakova KM, Markin PA, Moskaleva NE, Kozhevnikova MV, Chefranova ZY, Appolonova SA. A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis. Sci Rep 2024; 14:2651. [PMID: 38302683 PMCID: PMC10834974 DOI: 10.1038/s41598-024-53215-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/30/2024] [Indexed: 02/03/2024] Open
Abstract
Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects. Metabolomic profiling was conducted, involving the quantitative analysis of 87 endogenous metabolites in plasma. A novel regression method of age-adjustment correction of metabolomics data was developed. We identified 36 significantly changed metabolites which included increased cystathionine and dimethylglycine and the decreased ADMA and arginine. Tryptophan catabolism pathways showed significant alterations with increased levels of serotonin, intermediates of the kynurenine pathway and decreased intermediates of indole pathway. Amino acid profiles indicated elevated branched-chain amino acids and increased amino acid ratios. Short-chain acylcarnitines were reduced, while long-chain acylcarnitines were elevated. Based on these metabolites data, machine learning algorithms: logistic regression, support vector machine, decision trees, random forest, and gradient boosting, were used for IHD diagnostic models. Random forest demonstrated the highest accuracy with an AUC of 0.98. The metabolites Norepinephrine; Xanthurenic acid; Anthranilic acid; Serotonin; C6-DC; C14-OH; C16; C16-OH; GSG; Phenylalanine and Methionine were found to be significant and may serve as a novel preliminary panel for IHD diagnostics. Further studies are needed to confirm these findings.
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Affiliation(s)
- S S Markin
- Institute of Biomedical Chemistry, Moscow, Russia, 119121.
| | | | - Yu A Romashova
- Institute of Biomedical Chemistry, Moscow, Russia, 119121
| | - T O Pleshakova
- Institute of Biomedical Chemistry, Moscow, Russia, 119121
| | - S V Ivanov
- Institute of Biomedical Chemistry, Moscow, Russia, 119121
| | | | - S L Konstantinov
- Belgorod Regional Clinical Hospital of St. Joseph, Belgorod, Russia, 308007
| | - A A Nizov
- I.P. Pavlov Ryazan State Medical University, Ryazan, Russia, 390026
| | - A G Koledinskii
- Peoples' Friendship University of Russia, Moscow, Russia, 117198
| | - A I Girivenko
- I.P. Pavlov Ryazan State Medical University, Ryazan, Russia, 390026
| | - K M Shestakova
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University (Sechenov University), Moscow, Russia, 119435
| | - P A Markin
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University (Sechenov University), Moscow, Russia, 119435
| | - N E Moskaleva
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia, 119435
| | - M V Kozhevnikova
- Hospital Therapy No1, Department of the N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow Medical University (Sechenov University), Moscow, Russia, 119435
| | - Zh Yu Chefranova
- Belgorod Regional Clinical Hospital of St. Joseph, Belgorod, Russia, 308007
| | - S A Appolonova
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University (Sechenov University), Moscow, Russia, 119435
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia, 119435
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Wang X, Xia B, Hao Z, Kang H, Liu W, Chen Y, Jiang Q, Liu J, Gou J, Dong B, Wee ATS, Liu Y, Wei D. A closed-loop catalytic nanoreactor system on a transistor. SCIENCE ADVANCES 2023; 9:eadj0839. [PMID: 37729411 PMCID: PMC10511191 DOI: 10.1126/sciadv.adj0839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/17/2023] [Indexed: 09/22/2023]
Abstract
Precision chemistry demands miniaturized catalytic systems for sophisticated reactions with well-defined pathways. An ideal solution is to construct a nanoreactor system functioning as a chemistry laboratory to execute a full chemical process with molecular precision. However, existing nanoscale catalytic systems fail to in situ control reaction kinetics in a closed-loop manner, lacking the precision toward ultimate reaction efficiency. We find an inter-electrochemical gating effect when operating DNA framework-constructed enzyme cascade nanoreactors on a transistor, enabling in situ closed-loop reaction monitoring and modulation electrically. Therefore, a comprehensive system is developed, encapsulating nanoreactors, analyzers, and modulators, where the gate potential modulates enzyme activity and switches cascade reaction "ON" or "OFF." Such electric field-effect property enhances catalytic efficiency of enzyme by 343.4-fold and enables sensitive sarcosine assay for prostate cancer diagnoses, with a limit of detection five orders of magnitude lower than methodologies in clinical laboratory. By coupling with solid-state electronics, this work provides a perspective to construct intelligent nano-systems for precision chemistry.
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Affiliation(s)
- Xuejun Wang
- State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, China
- Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Binbin Xia
- Institute of Molecular Medicine, Department of Urology, Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Zhuang Hao
- School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
| | - Hua Kang
- State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, China
- Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Wentao Liu
- State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, China
- Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Yiheng Chen
- State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, China
- Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Qunfeng Jiang
- Department of Physics, Fudan University, Shanghai 200433, China
| | - Jingyuan Liu
- Global Clinical Operation, Johnson & Johnson, Shanghai 200233, China
| | - Jian Gou
- Department of Physics, National University of Singapore, Singapore 117542, Singapore
| | - Baijun Dong
- Institute of Molecular Medicine, Department of Urology, Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Andrew Thye Shen Wee
- Department of Physics, National University of Singapore, Singapore 117542, Singapore
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Dacheng Wei
- State Key Laboratory of Molecular Engineering of Polymers, Fudan University, Shanghai 200433, China
- Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
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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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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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Moskaleva NE, Shestakova KM, Kukharenko AV, Markin PA, Kozhevnikova MV, Korobkova EO, Brito A, Baskhanova SN, Mesonzhnik NV, Belenkov YN, Pyatigorskaya NV, Tobolkina E, Rudaz S, Appolonova SA. Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults. Metabolites 2022; 12:metabo12121185. [PMID: 36557222 PMCID: PMC9781191 DOI: 10.3390/metabo12121185] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/18/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p < 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling.
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Affiliation(s)
- Natalia E. Moskaleva
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Ksenia M. Shestakova
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Alexey V. Kukharenko
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University, 119435 Moscow, Russia
| | - Pavel A. Markin
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Maria V. Kozhevnikova
- Hospital Therapy N°1 Department of the N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow Medical University, 119992 Moscow, Russia
| | - Ekaterina O. Korobkova
- Hospital Therapy N°1 Department of the N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow Medical University, 119992 Moscow, Russia
| | - Alex Brito
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University, 119435 Moscow, Russia
| | - Sabina N. Baskhanova
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Natalia V. Mesonzhnik
- World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Yuri N. Belenkov
- Hospital Therapy N°1 Department of the N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow Medical University, 119992 Moscow, Russia
| | - Natalia V. Pyatigorskaya
- Department of Industrial Pharmacy, Institute of Vocational Education I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Elena Tobolkina
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1206 Geneva, Switzerland
- Correspondence:
| | - Serge Rudaz
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1206 Geneva, Switzerland
| | - Svetlana A. Appolonova
- Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University, 119435 Moscow, Russia
- Department of Industrial Pharmacy, Institute of Vocational Education I.M. Sechenov First Moscow State Medical University, 119435 Moscow, Russia
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Effect of Bicalutamide Combined with Docetaxel on Serum PSA and VEGF Levels in Patients with Advanced Prostate Carcinoma. DISEASE MARKERS 2022; 2022:4506350. [PMID: 36033830 PMCID: PMC9402358 DOI: 10.1155/2022/4506350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 08/04/2022] [Indexed: 11/17/2022]
Abstract
Objective. To investigate the effect of bicalutamide combined with docetaxel on the levels of prostate-specific antigen (PSA) in serum and vascular endothelial growth factor (VEGF) in patients with advanced prostate carcinoma (PCa). Methods. The clinical data of 103 patients with advanced PCa at our hospital between Feb. 2020 and Feb. 2021 were retrospectively analyzed, the 90 of whom screened by inclusion and exclusion criteria were finally chosen as research objects. They were divided into a control group and an experimental group according to the order of admission, with 45 cases in each group. The control group was treated with conventional treatment, while the experimental group underwent the combination of bicalutamide and docetaxel, and the clinical indices of the two groups were compared. Results. After treatment, the serum indices in the experimental group were remarkably lower than those in the control group (
), with remarkably lower incidence of toxic and side effects (
) and higher Expanded Prostate Cancer Index Composite (EPIC) scores (
) in the experimental group than in the control group. Conclusion. The implementation of bicalutamide combined with docetaxel in patients with advanced PCa is effective in reducing the inflammatory expression and improving quality of life and has a higher safety profile. Compared with conventional treatment, this method is of high application value, and further studies will help establish a better solution for such patients.
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8
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Liu B, Ran B, Chen C, Shi L, Liu Y, Chen H, Zhu Y. A low-cost and high-performance 3D micromixer over a wide working range and its application for high-sensitivity biomarker detection. REACT CHEM ENG 2022. [DOI: 10.1039/d2re00103a] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Homogenous mixing in microfluidic devices is often required for efficient chemical and biological reactions.Passive micromixing without external energy input has attracted much research interest. We have developed a high-performance 3D...
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9
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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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10
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Metabolic Rewiring and the Characterization of Oncometabolites. Cancers (Basel) 2021; 13:cancers13122900. [PMID: 34200553 PMCID: PMC8229816 DOI: 10.3390/cancers13122900] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 05/31/2021] [Accepted: 06/08/2021] [Indexed: 02/07/2023] Open
Abstract
Simple Summary Oncometabolites are produced by cancer cells and assist the cancer to proliferate and progress. Oncometabolites occur as a result of mutated enzymes in the tumor tissue or due to hypoxia. These processes result in either the abnormal buildup of a normal metabolite or the accumulation of an unusual metabolite. Definition of the metabolic changes that occur due to these processes has been accomplished using metabolomics, which mainly uses mass spectrometry platforms to define the content of small metabolites that occur in cells, tissues, organs and organisms. The four classical oncometabolites are fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate, which operate by inhibiting 2-oxoglutarate-dependent enzyme reactions that principally regulate gene expression and response to hypoxia. Metabolomics has also revealed several putative oncometabolites that include lactate, kynurenine, methylglyoxal, sarcosine, glycine, hypotaurine and (2R,3S)-dihydroxybutanoate. Metabolomics will continue to be critical for understanding the metabolic rewiring involving oncometabolite production that underpins many cancer phenotypes. Abstract The study of low-molecular-weight metabolites that exist in cells and organisms is known as metabolomics and is often conducted using mass spectrometry laboratory platforms. Definition of oncometabolites in the context of the metabolic phenotype of cancer cells has been accomplished through metabolomics. Oncometabolites result from mutations in cancer cell genes or from hypoxia-driven enzyme promiscuity. As a result, normal metabolites accumulate in cancer cells to unusually high concentrations or, alternatively, unusual metabolites are produced. The typical oncometabolites fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate inhibit 2-oxoglutarate-dependent dioxygenases, such as histone demethylases and HIF prolyl-4-hydroxylases, together with DNA cytosine demethylases. As a result of the cancer cell acquiring this new metabolic phenotype, major changes in gene transcription occur and the modification of the epigenetic landscape of the cell promotes proliferation and progression of cancers. Stabilization of HIF1α through inhibition of HIF prolyl-4-hydroxylases by oncometabolites such as fumarate and succinate leads to a pseudohypoxic state that promotes inflammation, angiogenesis and metastasis. Metabolomics has additionally been employed to define the metabolic phenotype of cancer cells and patient biofluids in the search for cancer biomarkers. These efforts have led to the uncovering of the putative oncometabolites sarcosine, glycine, lactate, kynurenine, methylglyoxal, hypotaurine and (2R,3S)-dihydroxybutanoate, for which further research is required.
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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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Hroncekova S, Bertok T, Hires M, Jane E, Lorencova L, Vikartovska A, Tanvir A, Kasak P, Tkac J. Ultrasensitive Ti 3C 2T X MXene/Chitosan Nanocomposite-Based Amperometric Biosensor for Detection of Potential Prostate Cancer Marker in Urine Samples. Processes (Basel) 2020; 8:580. [PMID: 33304843 PMCID: PMC7116456 DOI: 10.3390/pr8050580] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Two-dimensional layered nanomaterial Ti3C2TX (a member of the MXene family) was used to immobilise enzyme sarcosine oxidase to fabricate a nanostructured biosensor. The device was applied for detection of sarcosine, a potential prostate cancer biomarker, in urine for the first time. The morphology and structures of MXene have been characterised by atomic force microscopy (AFM) and scanning electron microscopy (SEM). Electrochemical measurements, SEM and AFM analysis revealed that MXene interfaced with chitosan is an excellent support for enzyme immobilisation to fabricate a sensitive biosensor exhibiting a low detection limit of 18 nM and a linear range up to 7.8 µM. The proposed biosensing method also provides a short response time of 2 s and high recovery index of 102.6% for detection of sarcosine spiked into urine sample in a clinically relevant range.
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Affiliation(s)
- Stefania Hroncekova
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Tomas Bertok
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Michal Hires
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Eduard Jane
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Lenka Lorencova
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Alica Vikartovska
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
| | - Aisha Tanvir
- Center for Advanced Materials, Qatar University, P. O. BOX 2713, Doha, Qatar
| | - Peter Kasak
- Center for Advanced Materials, Qatar University, P. O. BOX 2713, Doha, Qatar
| | - Jan Tkac
- Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava 845 38, Slovak Republic
- Correspondence:
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