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Kayar R, Tokuc E, Ozsoy E, Demir S, Kayar K, Topaktas R, Demir S, Ozturk M. The predictive impact of hematological inflammatory markers in detecting prostate cancer in patients with PI-RADS 3 lesions on multiparametric magnetic resonance imaging. Prostate 2024; 84:1244-1250. [PMID: 38926140 DOI: 10.1002/pros.24762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/13/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND The diagnostic accuracy of suspicious lesions that are classified as PI-RADS 3 in multiparametric prostate magnetic-resonance imaging (mpMRI) is controversial. This study aims to assess the predictive capacity of hematological inflammatory markers such as neutrophil-lymphocyte ratio (NLR), pan-immune-inflammation value (PIV), and systemic immune-response index (SIRI) in detecting prostate cancer in PI-RADS 3 lesions. METHODS 276 patients who underwent mpMRI and subsequent prostate biopsy after PI-RADS 3 lesion detection were included in the study. According to the biopsy results, the patients were distributed to two groups as prostate cancer (PCa) and no cancer (non-PCa). Data concerning age, PSA, prostate volume, PSA density, PI-RADS 3 lesion size, prostate biopsy results, monocyte counts (109/L), lymphocyte counts (109/L), platelet counts (109/L), neutrophils count (109/L) were recorded from the complete blood count. From these data; PIV value is obtained by monocyte × neutrophil × platelet/lymphocyte, NLR by neutrophil/lymphocyte, and SIRI by monocyte number × NLR. RESULTS Significant variations in neutrophil, lymphocyte, and monocyte levels between PCa and non-PCa patient groups were detected (p = 0.009, p = 0.001, p = 0.005 respectively, p < 0.05). NLR, PIV, and SIRI exhibited significant differences, with higher values in PCa patients (p = 0.004, p = 0.001, p < 0.001 respectively, p < 0.05). The area under curve of SIRI was 0.729, with a cut-off value of 1.20 and with a sensitivity 57.70%, and a specificity of 68.70%. CONCLUSION SIRI outperformed NLR and PIV in detecting PCa in PI-RADS 3 lesions, showcasing its potential as a valuable biomarker. Implementation of this parameter to possible future nomograms has the potential to individualize and risk-stratify the patients in prostate biopsy decision.
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Affiliation(s)
- Ridvan Kayar
- Department of Urology, Van Training and Research Hospital, University of Health Sciences, Van, Turkiye
| | - Emre Tokuc
- Department of Urology, University of Health Sciences, Haydarpasa Numune SUAM, Istanbul, Turkiye
| | - Emrah Ozsoy
- Unye Private Cakirtepe Hospital, Urology Clinic, Ordu, Turkiye
| | - Samet Demir
- Department of Urology, University of Health Sciences, Haydarpasa Numune SUAM, Istanbul, Turkiye
| | - Kemal Kayar
- Department of Urology, University of Health Sciences, Haydarpasa Numune SUAM, Istanbul, Turkiye
| | - Ramazan Topaktas
- Department of Urology, University of Health Sciences, Haydarpasa Numune SUAM, Istanbul, Turkiye
| | - Selamettin Demir
- Department of Urology, Van Training and Research Hospital, University of Health Sciences, Van, Turkiye
| | - Metin Ozturk
- Department of Urology, University of Health Sciences, Haydarpasa Numune SUAM, Istanbul, Turkiye
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Heidegger I, Frantzi M, Salcher S, Tymoszuk P, Martowicz A, Gomez-Gomez E, Blanca A, Lendinez Cano G, Latosinska A, Mischak H, Vlahou A, Langer C, Aigner F, Puhr M, Krogsdam A, Trajanoski Z, Wolf D, Pircher A. Prediction of Clinically Significant Prostate Cancer by a Specific Collagen-related Transcriptome, Proteome, and Urinome Signature. Eur Urol Oncol 2024:S2588-9311(24)00144-5. [PMID: 38851995 DOI: 10.1016/j.euo.2024.05.014] [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: 03/23/2024] [Revised: 04/23/2024] [Accepted: 05/21/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND AND OBJECTIVE While collagen density has been associated with poor outcomes in various cancers, its role in prostate cancer (PCa) remains elusive. Our aim was to analyze collagen-related transcriptomic, proteomic, and urinome alterations in the context of detection of clinically significant PCa (csPCa, International Society of Urological Pathology [ISUP] grade group ≥2). METHODS Comprehensive analyses for PCa transcriptome (n = 1393), proteome (n = 104), and urinome (n = 923) data sets focused on 55 collagen-related genes. Investigation of the cellular source of collagen-related transcripts via single-cell RNA sequencing was conducted. Statistical evaluations, clustering, and machine learning models were used for data analysis to identify csPCa signatures. KEY FINDINGS AND LIMITATIONS Differential expression of 30 of 55 collagen-related genes and 34 proteins was confirmed in csPCa in comparison to benign prostate tissue or ISUP 1 cancer. A collagen-high cancer cluster exhibited distinct cellular and molecular characteristics, including fibroblast and endothelial cell infiltration, intense extracellular matrix turnover, and enhanced growth factor and inflammatory signaling. Robust collagen-based machine learning models were established to identify csPCa. The models outcompeted prostate-specific antigen (PSA) and age, showing comparable performance to multiparametric magnetic resonance imaging (mpMRI) in predicting csPCa. Of note, the urinome-based collagen model identified four of five csPCa cases among patients with Prostate Imaging-Reporting and Data System (PI-IRADS) 3 lesions, for which the presence of csPCa is considered equivocal. The retrospective character of the study is a limitation. CONCLUSIONS AND CLINICAL IMPLICATIONS Collagen-related transcriptome, proteome, and urinome signatures exhibited superior accuracy in detecting csPCa in comparison to PSA and age. The collagen signatures, especially in cases of ambiguous lesions on mpMRI, successfully identified csPCa and could potentially reduce unnecessary biopsies. The urinome-based collagen signature represents a promising liquid biopsy tool that requires prospective evaluation to improve the potential of this collagen-based approach to enhance diagnostic precision in PCa for risk stratification and guiding personalized interventions. PATIENT SUMMARY In our study, collagen-related alterations in tissue, and urine were able to predict the presence of clinically significant prostate cancer at primary diagnosis.
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Affiliation(s)
- Isabel Heidegger
- Department of Urology, Medical University of Innsbruck, Innsbruck, Austria.
| | - Maria Frantzi
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany
| | - Stefan Salcher
- Department of Internal Medicine V, Hematology and Oncology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Agnieszka Martowicz
- Department of Internal Medicine V, Hematology and Oncology, Medical University of Innsbruck, Innsbruck, Austria
| | - Enrique Gomez-Gomez
- Urology Department, Reina Sofía University Hospital, Maimonides Institute of Biomedical Research of Cordoba, University of Cordoba, Cordoba, Spain
| | - Ana Blanca
- Urology Department, Reina Sofía University Hospital, Maimonides Institute of Biomedical Research of Cordoba, University of Cordoba, Cordoba, Spain
| | - Guillermo Lendinez Cano
- Urology Department, Biomedical Institute of Seville, University Hospital Virgen del Rocío, Seville, Spain
| | | | - Harald Mischak
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany
| | - Antonia Vlahou
- Systems Biology Center, Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - Christian Langer
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Friedrich Aigner
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Martin Puhr
- Department of Urology, Medical University of Innsbruck, Innsbruck, Austria
| | - Anne Krogsdam
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Zlatko Trajanoski
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Dominik Wolf
- Department of Internal Medicine V, Hematology and Oncology, Medical University of Innsbruck, Innsbruck, Austria
| | - Andreas Pircher
- Department of Internal Medicine V, Hematology and Oncology, Medical University of Innsbruck, Innsbruck, Austria.
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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Joshi N, Garapati K, Ghose V, Kandasamy RK, Pandey A. Recent progress in mass spectrometry-based urinary proteomics. Clin Proteomics 2024; 21:14. [PMID: 38389064 PMCID: PMC10885485 DOI: 10.1186/s12014-024-09462-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/12/2024] [Indexed: 02/24/2024] Open
Abstract
Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.
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Affiliation(s)
- Neha Joshi
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Kishore Garapati
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Vivek Ghose
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
| | - Richard K Kandasamy
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Akhilesh Pandey
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India.
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
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Khan AA, Al-Mahrouqi N, Al-Yahyaee A, Al-Sayegh H, Al-Harthy M, Al-Zadjali S. Deciphering Urogenital Cancers through Proteomic Biomarkers: A Systematic Review and Meta-Analysis. Cancers (Basel) 2023; 16:22. [PMID: 38201450 PMCID: PMC10778028 DOI: 10.3390/cancers16010022] [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: 08/30/2023] [Revised: 11/20/2023] [Accepted: 12/04/2023] [Indexed: 01/12/2024] Open
Abstract
Urogenital cancers, which include prostate, bladder, and kidney malignancies, exert a substantial impact on global cancer-related morbidity and mortality. Proteomic biomarkers, emerging as valuable tools, aim to enhance early detection, prognostic accuracy, and the development of personalized therapeutic strategies. This study undertook a comprehensive systematic review and meta-analysis of the existing literature investigating the role and potential of proteomic biomarkers in plasma, tissue, and urine samples in urogenital cancers. Our extensive search across several databases identified 1879 differentially expressed proteins from 37 studies, signifying their potential as unique biomarkers for these cancers. A meta-analysis of the significantly differentially expressed proteins was executed, accentuating the findings through visually intuitive volcano plots. A functional enrichment analysis unveiled their significant involvement in diverse biological processes, including signal transduction, immune response, cell communication, and cell growth. A pathway analysis highlighted the participation of key pathways such as the nectin adhesion pathway, TRAIL signaling pathway, and integrin signaling pathways. These findings not only pave the way for future investigations into early detection and targeted therapeutic approaches but also underscore the fundamental role of proteomics in advancing our understanding of the molecular mechanisms underpinning urogenital cancer pathogenesis. Ultimately, these findings hold remarkable potential to significantly enhance patient care and improve clinical outcomes.
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Affiliation(s)
- Aafaque Ahmad Khan
- Research Laboratories, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman; (N.A.-M.); (A.A.-Y.); (H.A.-S.); (S.A.-Z.)
| | - Nahad Al-Mahrouqi
- Research Laboratories, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman; (N.A.-M.); (A.A.-Y.); (H.A.-S.); (S.A.-Z.)
| | - Aida Al-Yahyaee
- Research Laboratories, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman; (N.A.-M.); (A.A.-Y.); (H.A.-S.); (S.A.-Z.)
| | - Hasan Al-Sayegh
- Research Laboratories, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman; (N.A.-M.); (A.A.-Y.); (H.A.-S.); (S.A.-Z.)
| | - Munjid Al-Harthy
- Medical Oncology Department, Urogenital Cancers Program, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman;
| | - Shoaib Al-Zadjali
- Research Laboratories, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat 123, Oman; (N.A.-M.); (A.A.-Y.); (H.A.-S.); (S.A.-Z.)
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Gómez Gómez E, Cano Castiñeira R, Burgos J, Rodríguez Antolín A, Miles BJ, Martínez Salamanca JI, Bianco F, Fernández L, Calmarza I, Pastor J, Butler RG, de Pedro N. ProsTAV, a novel blood-based test for biopsy decision management in significant prostate cancer. Prostate 2023; 83:1323-1331. [PMID: 37409738 DOI: 10.1002/pros.24594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/26/2023] [Accepted: 06/21/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Current pathways in early diagnosis of prostate cancer (PCa) can lead to unnecessary biopsy procedures. Here, we used telomere analysis to develop and evaluate ProsTAV®, a risk model for significant PCa (Gleason score >6), with the objective of improving the PCa diagnosis pathway. METHODS This retrospective, multicentric study analyzed telomeres from patients with serum PSA 3-10 ng/mL. High-throughput quantitative fluorescence in-situ hybridization was used to evaluate telomere-associated variables (TAVs) in peripheral blood mononucleated cells. ProsTAV® was developed by multivariate logistics regression based on three clinical variables and six TAVs. The predictive capacity and accuracy of ProsTAV® were summarized by receiver operating characteristic (ROC) curves and its clinical benefit with decision curves analysis. RESULTS Telomeres from 1043 patients were analyzed. The median age of the patients was 63 years, with a median PSA of 5.2 ng/mL and a percentage of significant PCa of 23.9%. A total of 874 patients were selected for model training and 169 patients for model validation. The area under the ROC curve of ProsTAV® was 0.71 (95% confidence interval [CI], 0.62-0.79), with a sensitivity of 0.90 (95% CI, 0.88-1.0) and specificity of 0.33 (95% CI, 0.24-0.40). The positive predictive value was 0.29 (95% CI, 0.21-0.37) and the negative predictive value was 0.91 (95% CI, 0.83-0.99). ProsTAV® would make it possible to avoid 33% of biopsies. CONCLUSIONS ProsTAV®, a predictive model based on telomere analysis through TAV, could be used to increase the prediction capacity of significant PCa in patients with PSA between 3 and 10 ng/mL.
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Affiliation(s)
- Enrique Gómez Gómez
- Department of Urology, Hospital Universitario Reina Sofía, Universidad de Córdoba, Investigación Biomédica de Córdoba, Córdoba, Spain
| | | | - Javier Burgos
- Department of Urology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria, Madrid, Spain
| | | | - Brian J Miles
- Urologic Oncology, Houston Methodist Hospital, Houston, Texas, USA
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Ferro M, Rocco B, Maggi M, Lucarelli G, Falagario UG, Del Giudice F, Crocetto F, Barone B, La Civita E, Lasorsa F, Brescia A, Catellani M, Busetto GM, Tataru OS, Terracciano D. Beyond blood biomarkers: the role of SelectMDX in clinically significant prostate cancer identification. Expert Rev Mol Diagn 2023; 23:1061-1070. [PMID: 37897252 DOI: 10.1080/14737159.2023.2277366] [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: 07/06/2023] [Accepted: 10/26/2023] [Indexed: 10/30/2023]
Abstract
INTRODUCTION New potential biomarkers to pre-intervention identification of a clinically significant prostate cancer (csPCa) will prevent overdiagnosis and overtreatment and limit quality of life impairment of PCa patients. AREAS COVERED We have developed a comprehensive review focusing our research on the increasing knowledge of the role of SelectMDX® in csPCa detection. Areas identified as clinically relevant are the ability of SelectMDX® to predict csPCa in active surveillance setting, its predictive ability when combined with multiparametric MRI and the role of SelectMDX® in the landscape of urinary biomarkers. EXPERT OPINION Several PCa biomarkers have been developed either alone or in combination with clinical variables to improve csPCa detection. SelectMDX® score includes genomic markers, age, PSA, prostate volume, and digital rectal examination. Several studies have shown consistency in the ability to improve detection of csPCa, avoidance of unnecessary prostate biopsies, helpful in decision-making for clinical benefit of PCa patients with future well designed, and impactful studies.
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Affiliation(s)
- Matteo Ferro
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Bernardo Rocco
- Unit of Urology, Department of Health Science, University of Milan, ASST Santi Paolo and Carlo, Via A. Di Rudini 8, Milan 20142, Italy
| | - Martina Maggi
- Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Giuseppe Lucarelli
- Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, Piazza Umberto I - 70121, Bari, Italy
| | - Ugo Giovanni Falagario
- Department of Urology and Organ Transplantation, University of Foggia, Via A.Gramsci 89/91, 71122 Foggia, Italy
| | - Francesco Del Giudice
- Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Felice Crocetto
- Department of Neurosciences and Reproductive Sciences and Odontostomatology, University of Naples Federico II, Via Pansini, 5 - 80131, Naples, Italy
| | - Biagio Barone
- Department of Surgical Sciences, Urology Unit, AORN Sant'Anna e San Sebastiano, Caserta, Via Ferdinando Palasciano, 81100 Caserta , Italy
| | - Evelina La Civita
- Department of Translational Medical Sciences, University of Naples "Federico II", Corso Umberto I 40 - 80138 Naples, Italy
| | - Francesco Lasorsa
- Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, Piazza Umberto I - 70121, Bari, Italy
| | - Antonio Brescia
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Michele Catellani
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Gian Maria Busetto
- Department of Urology and Organ Transplantation, University of Foggia, Via A.Gramsci 89/91, 71122 Foggia, Italy
| | - Octavian Sabin Tataru
- Department of Simulation Applied in Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mures, Gh Marinescu 35, 540142 Târgu Mures, Romania
| | - Daniela Terracciano
- Department of Translational Medical Sciences, University of Naples "Federico II", Corso Umberto I 40 - 80138 Naples, Italy
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Chen D, McCool EN, Yang Z, Shen X, Lubeckyj RA, Xu T, Wang Q, Sun L. Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics. MASS SPECTROMETRY REVIEWS 2023; 42:617-642. [PMID: 34128246 PMCID: PMC8671558 DOI: 10.1002/mas.21714] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 05/29/2021] [Accepted: 06/03/2021] [Indexed: 05/06/2023]
Abstract
Multilevel proteomics aims to delineate proteins at the peptide (bottom-up proteomics), proteoform (top-down proteomics), and protein complex (native proteomics) levels. Capillary electrophoresis-mass spectrometry (CE-MS) can achieve highly efficient separation and highly sensitive detection of complex mixtures of peptides, proteoforms, and even protein complexes because of its substantial technical progress. CE-MS has become a valuable alternative to the routinely used liquid chromatography-mass spectrometry for multilevel proteomics. This review summarizes the most recent (2019-2021) advances of CE-MS for multilevel proteomics regarding technological progress and biological applications. We also provide brief perspectives on CE-MS for multilevel proteomics at the end, highlighting some future directions and potential challenges.
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Affiliation(s)
| | | | | | - Xiaojing Shen
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, MI 48824, USA
| | - Rachele A. Lubeckyj
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, MI 48824, USA
| | - Tian Xu
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, MI 48824, USA
| | - Qianjie Wang
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, MI 48824, USA
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, MI 48824, USA
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Frantzi M, Culig Z, Heidegger I, Mokou M, Latosinska A, Roesch MC, Merseburger AS, Makridakis M, Vlahou A, Blanca-Pedregosa A, Carrasco-Valiente J, Mischak H, Gomez-Gomez E. Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination. Cancers (Basel) 2023; 15:cancers15041166. [PMID: 36831508 PMCID: PMC9954607 DOI: 10.3390/cancers15041166] [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: 12/16/2022] [Revised: 02/02/2023] [Accepted: 02/07/2023] [Indexed: 02/17/2023] Open
Abstract
(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.
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Affiliation(s)
- Maria Frantzi
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany
- Correspondence: ; Tel.: +49-511-5547-4429
| | - Zoran Culig
- Experimental Urology Department of Urology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Isabel Heidegger
- Experimental Urology Department of Urology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Marika Mokou
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany
| | - Agnieszka Latosinska
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany
| | - Marie C. Roesch
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
| | - Axel S. Merseburger
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
| | - Manousos Makridakis
- Systems Biology Center, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Antonia Vlahou
- Systems Biology Center, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Ana Blanca-Pedregosa
- Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain
| | - Julia Carrasco-Valiente
- Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain
| | - Harald Mischak
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany
- Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow G12 8TA, UK
| | - Enrique Gomez-Gomez
- Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain
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Kirk D, Kok E, Tufano M, Tekinerdogan B, Feskens EJM, Camps G. Machine Learning in Nutrition Research. Adv Nutr 2022; 13:2573-2589. [PMID: 36166846 PMCID: PMC9776646 DOI: 10.1093/advances/nmac103] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/02/2022] [Accepted: 09/22/2022] [Indexed: 01/29/2023] Open
Abstract
Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and thus lend itself as an alternative tool to deal with data of this nature. ML has already been applied in important problem areas in nutrition, such as obesity, metabolic health, and malnutrition. Despite this, experts in nutrition are often without an understanding of ML, which limits its application and therefore potential to solve currently open questions. The current article aims to bridge this knowledge gap by supplying nutrition researchers with a resource to facilitate the use of ML in their research. ML is first explained and distinguished from existing solutions, with key examples of applications in the nutrition literature provided. Two case studies of domains in which ML is particularly applicable, precision nutrition and metabolomics, are then presented. Finally, a framework is outlined to guide interested researchers in integrating ML into their work. By acting as a resource to which researchers can refer, we hope to support the integration of ML in the field of nutrition to facilitate modern research.
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Affiliation(s)
- Daniel Kirk
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Esther Kok
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Michele Tufano
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Bedir Tekinerdogan
- Information Technology Group, Wageningen University and Research, Wageningen, The Netherlands
| | - Edith J M Feskens
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Guido Camps
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands.,OnePlanet Research Center, Wageningen, The Netherlands
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Proteomic Analysis of Prostate Cancer FFPE Samples Reveals Markers of Disease Progression and Aggressiveness. Cancers (Basel) 2022; 14:cancers14153765. [PMID: 35954429 PMCID: PMC9367334 DOI: 10.3390/cancers14153765] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/29/2022] [Accepted: 07/30/2022] [Indexed: 01/27/2023] Open
Abstract
Simple Summary Prostate cancer (PCa) is the second most frequently diagnosed type of cancer in men. The lack of tools for accurate risk assessment is causing over-treatment of men with indolent PCa but also delayed detection of metastatic disease and thus high mortality. The aim of our study was to identify proteins related to the progression and aggressiveness of PCa that could serve as potential biomarkers for better risk stratification. To this end, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens (n = 86) and compared them based on grade groups and biochemical recurrence status. Based on the valuable data generated by these comparisons, we have selected seven proteins (NMP1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) as common denominators of PCa aggressiveness and persistence that could potentially be used for the development of risk assessment tools. Notably, our observations are largely validated by transcriptomics data and literature. Abstract Prostate cancer (PCa) is the second most common cancer in men. Diagnosis and risk assessment are widely based on serum Prostate Specific Antigen (PSA) and biopsy, which might not represent the exact degree of PCa risk. Towards the discovery of biomarkers for better patient stratification, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Comparative analysis of 86 PCa samples among grade groups 1–5 identified 301 significantly altered proteins. Additional analysis based on biochemical recurrence (BCR; BCR+ n = 14, BCR- n = 51) revealed 197 significantly altered proteins that indicate disease persistence. Filtering the overlapping proteins of these analyses, seven proteins (NPM1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) had increased expression in advanced grades and in BCR+/BCR- and may play a critical role in PCa aggressiveness. Notably, all seven proteins were significantly associated with progression in Prostate Cancer Transcriptome Atles (PCTA) and NPM1NPM1, UQCRH, and VCAN were further validated in The Cancer Genome Atlas (TCGA), where they were upregulated in BCR+/BCR-. UQCRH levels were also associated with poorer 5-year survival. Our study provides valuable insights into the key regulators of PCa progression and aggressiveness. The seven selected proteins could be used for the development of risk assessment tools.
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12
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A Model to Detect Significant Prostate Cancer Integrating Urinary Peptide and Extracellular Vesicle RNA Data. Cancers (Basel) 2022; 14:cancers14081995. [PMID: 35454901 PMCID: PMC9027643 DOI: 10.3390/cancers14081995] [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: 03/14/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 12/12/2022] Open
Abstract
There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77−0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p < 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1−3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%.
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13
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DeFelice BC, Fiehn O, Belafsky P, Ditterich C, Moore M, Abouyared M, Beliveau AM, Farwell DG, Bewley AF, Clayton SM, Archard JA, Pavlic J, Rao S, Kuhn M, Deng P, Halmai J, Fink KD, Birkeland AC, Anderson JD. Polyamine Metabolites as Biomarkers in Head and Neck Cancer Biofluids. Diagnostics (Basel) 2022; 12:diagnostics12040797. [PMID: 35453845 PMCID: PMC9024570 DOI: 10.3390/diagnostics12040797] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 03/09/2022] [Accepted: 03/14/2022] [Indexed: 02/04/2023] Open
Abstract
Background: Novel, non-invasive diagnostic biomarkers that facilitate early intervention in head and neck cancer are urgently needed. Polyamine metabolites have been observed to be elevated in numerous cancer types and correlated with poor prognosis. The aim of this study was to assess the concentration of polyamines in the saliva and urine from head and neck cancer (HNC) patients, compared to healthy controls. Methods: Targeted metabolomic analysis was performed on saliva and urine from 39 HNC patient samples and compared to 89 healthy controls using a quantitative, targeted liquid chromatography mass spectrometry approach. Results: The metabolites N1-acetylspermine (ASP), N8-acetylspermidine (ASD) and N1,N12-diacetylspermine (DAS) were detected at significantly different concentrations in the urine of HNC patients as compared to healthy controls. Only ASP was detected at elevated levels in HNC saliva as compared to healthy controls. Conclusion: These data suggest that assessment of polyamine-based metabolite biomarkers within the saliva and urine warrants further investigation as a potential diagnostic in HNC patients.
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Affiliation(s)
- Brian C. DeFelice
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA; (B.C.D.); (O.F.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA; (B.C.D.); (O.F.)
| | - Peter Belafsky
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Constanze Ditterich
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Michael Moore
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Marianne Abouyared
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Angela M. Beliveau
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - D. Gregory Farwell
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Arnaud F. Bewley
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Shannon M. Clayton
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Joehleen A. Archard
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Jordan Pavlic
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Shyam Rao
- Department of Radiation Oncology, University of California, Davis, CA 95616, USA;
| | - Maggie Kuhn
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
| | - Peter Deng
- Department of Neurology, University of California, Davis, CA 95616, USA; (P.D.); (J.H.); (K.D.F.)
| | - Julian Halmai
- Department of Neurology, University of California, Davis, CA 95616, USA; (P.D.); (J.H.); (K.D.F.)
| | - Kyle D. Fink
- Department of Neurology, University of California, Davis, CA 95616, USA; (P.D.); (J.H.); (K.D.F.)
| | - Andrew C. Birkeland
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
- Correspondence: (A.C.B.); (J.D.A.)
| | - Johnathon D. Anderson
- Department of Otolaryngology-Head and Neck Surgery, University of California, Davis, CA 95616, USA; (P.B.); (C.D.); (M.M.); (M.A.); (A.M.B.); (D.G.F.); (A.F.B.); (S.M.C.); (J.A.A.); (J.P.); (M.K.)
- Correspondence: (A.C.B.); (J.D.A.)
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Wang M, Gong Q, Liu W, Tan S, Xiao J, Chen C. Applications of capillary electrophoresis in the fields of environmental, pharmaceutical, clinical and food analysis (2019-2021). J Sep Sci 2022; 45:1918-1941. [PMID: 35325510 DOI: 10.1002/jssc.202100727] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 03/16/2022] [Accepted: 03/16/2022] [Indexed: 11/09/2022]
Abstract
So far, the potential of capillary electrophoresis (CE) in the application fields has been increasingly excavated due to the advantages of simple operation, short analysis time, high-resolution, less sample consumption and low cost. This review examines the implementations and advancements of CE in different application fields (environmental, pharmaceutical, clinical and food analysis) covering the literature from 2019 to 2021. In addition, ultrasmall sample injection volume (nanoliter range) and short optical path lead to relatively low concentration sensitivity of the most frequently used UV-absorption spectrophotometric detection, so the pretreatment technology being developed has been gradually utilized to overcome this problem. Despite the review is focused on the development of CE in the fields of environmental, pharmaceutical, clinical and food analysis, the new sample pretreatment techniques of microextraction and enrichment which fit excellently to CE in recent three years are also described briefly. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Mengyao Wang
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan, 410013, China
| | - Qian Gong
- Department of Pharmacy, Hunan Cancer Hospital/ The Affiliated Cancer Hospital of School of Medicine, Central South University, Changsha, Hunan, 410013, China
| | - Wenfang Liu
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan, 410013, China
| | - Songwen Tan
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan, 410013, China
| | - Jian Xiao
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Chuanpin Chen
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan, 410013, China
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15
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Mischak H, Kalvodova L. Interview with Harald Mischak. Proteomics 2022; 22:e2100390. [PMID: 35112791 DOI: 10.1002/pmic.202100390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 11/11/2022]
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16
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Frantzi M, Heidegger I, Roesch MC, Gomez-Gomez E, Steiner E, Vlahou A, Mullen W, Guler I, Merseburger AS, Mischak H, Culig Z. Validation of diagnostic nomograms based on CE-MS urinary biomarkers to detect clinically significant prostate cancer. World J Urol 2022; 40:2195-2203. [PMID: 35841414 PMCID: PMC9427869 DOI: 10.1007/s00345-022-04077-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 06/09/2022] [Indexed: 02/05/2023] Open
Abstract
PURPOSE Prostate cancer (PCa) is one of the most common cancers and one of the leading causes of death worldwide. Thus, one major issue in PCa research is to accurately distinguish between indolent and clinically significant (csPCa) to reduce overdiagnosis and overtreatment. In this study, we aim to validate the usefulness of diagnostic nomograms (DN) to detect csPCa, based on previously published urinary biomarkers. METHODS Capillary electrophoresis/mass spectrometry was employed to validate a previously published biomarker model based on 19 urinary peptides specific for csPCa. Added value of the 19-biomarker (BM) model was assessed in diagnostic nomograms including prostate-specific antigen (PSA), PSA density and the risk calculator from the European Randomized Study of Screening. For this purpose, urine samples from 147 PCa patients were collected prior to prostate biopsy and before performing digital rectal examination (DRE). The 19-BM score was estimated via a support vector machine-based software based on the pre-defined cutoff criterion of - 0.07. DNs were subsequently developed to assess added value of integrative diagnostics. RESULTS Independent validation of the 19-BM resulted in an 87% sensitivity and 65% specificity, with an AUC of 0.81, outperforming PSA (AUC PSA: 0.64), PSA density (AUC PSAD: 0.64) and ERSPC-3/4 risk calculator (0.67). Integration of 19-BM with the rest clinical variables into distinct DN, resulted in improved (AUC range: 0.82-0.88) but not significantly better performances over 19-BM alone. CONCLUSION 19-BM alone or upon integration with clinical variables into DN, might be useful for detecting csPCa by decreasing the number of biopsies.
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Affiliation(s)
- Maria Frantzi
- Department of Biomarker Research, Mosaiques Diagnostics, Hannover, Germany
| | - Isabel Heidegger
- Experimental Urology Department of Urology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Marie C. Roesch
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Enrique Gomez-Gomez
- Urology Department, Reina Sofía University Hospital, Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), University of Cordoba (UCO), Cordoba, Spain
| | - Eberhard Steiner
- Experimental Urology Department of Urology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Antonia Vlahou
- Systems Biology Center, Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - William Mullen
- Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, UK
| | - Ipek Guler
- Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), Katholiek Universiteit (KU) Leuven, University of Leuven, Leuven, Belgium
| | - Axel S. Merseburger
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Harald Mischak
- Department of Biomarker Research, Mosaiques Diagnostics, Hannover, Germany ,Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, UK
| | - Zoran Culig
- Experimental Urology Department of Urology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
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Wendt R, Siwy J, He T, Latosinska A, Wiech T, Zipfel PF, Tserga A, Vlahou A, Rupprecht H, Catanese L, Mischak H, Beige J. Molecular Mapping of Urinary Complement Peptides in Kidney Diseases. Proteomes 2021; 9:proteomes9040049. [PMID: 34941814 PMCID: PMC8709096 DOI: 10.3390/proteomes9040049] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/03/2021] [Accepted: 12/08/2021] [Indexed: 02/07/2023] Open
Abstract
Defective complement activation has been associated with various types of kidney disease. This led to the hypothesis that specific urine complement fragments may be associated with kidney disease etiologies, and disease progression may be reflected by changes in these complement fragments. We investigated the occurrence of complement fragments in urine, their association with kidney function and disease etiology in 16,027 subjects, using mass spectrometry based peptidomics data from the Human Urinary Proteome/Peptidome Database. Twenty-three different urinary peptides originating from complement proteins C3, C4 and factor B (CFB) could be identified. Most C3-derived peptides showed inverse association with estimated glomerular filtration rate (eGFR), while the majority of peptides derived from CFB demonstrated positive association with eGFR. Several peptides derived from the complement proteins C3, C4 and CFB were found significantly associated with specific kidney disease etiologies. These peptides may depict disease-specific complement activation and could serve as non-invasive biomarkers to support development of complement interventions through assessing complement activity for patients’ stratification and monitoring of drug impact. Further investigation of these complement peptides may provide additional insight into disease pathophysiology and could possibly guide therapeutic decisions, especially when targeting complement factors.
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Affiliation(s)
- Ralph Wendt
- Department of Nephrology and Kuratorium for Dialysis and Transplantation (KfH) Renal Unit, Hospital St. Georg, 04129 Leipzig, Germany;
| | - Justyna Siwy
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (J.S.); (T.H.); (A.L.); (H.M.)
| | - Tianlin He
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (J.S.); (T.H.); (A.L.); (H.M.)
| | - Agnieszka Latosinska
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (J.S.); (T.H.); (A.L.); (H.M.)
| | - Thorsten Wiech
- Nephropathology Section, Institute of Pathology, University Medical Center, 20246 Hamburg, Germany;
| | - Peter F. Zipfel
- Institute of Microbiology, Friedrich-Schiller-University, 07743 Jena, Germany;
- Department of Infection Biology, Leibniz Institute for Natural Product Researach and Infection Biology, 07745 Jena, Germany
| | - Aggeliki Tserga
- Biomedical Research Foundation, Academy of Athens, Department of Biotechnology, 11527 Athens, Greece; (A.T.); (A.V.)
| | - Antonia Vlahou
- Biomedical Research Foundation, Academy of Athens, Department of Biotechnology, 11527 Athens, Greece; (A.T.); (A.V.)
| | - Harald Rupprecht
- Department of Nephrology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany; (H.R.); (L.C.)
| | - Lorenzo Catanese
- Department of Nephrology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany; (H.R.); (L.C.)
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (J.S.); (T.H.); (A.L.); (H.M.)
| | - Joachim Beige
- Department of Nephrology and Kuratorium for Dialysis and Transplantation (KfH) Renal Unit, Hospital St. Georg, 04129 Leipzig, Germany;
- Department of Internal Medicine II, Martin-Luther-University Halle-Wittenberg, 06108 Halle (Saale), Germany
- Correspondence: ; Tel.: +49-341-909-4896
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Kašička V. Recent developments in capillary and microchip electroseparations of peptides (2019-mid 2021). Electrophoresis 2021; 43:82-108. [PMID: 34632606 DOI: 10.1002/elps.202100243] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/29/2021] [Accepted: 09/30/2021] [Indexed: 12/19/2022]
Abstract
The review provides a comprehensive overview of developments and applications of high performance capillary and microchip electroseparation methods (zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) for analysis, microscale isolation, and physicochemical characterization of peptides from 2019 up to approximately the middle of 2021. Advances in the investigation of electromigration properties of peptides and in the methodology of their analysis, such as sample preparation, sorption suppression, EOF control, and detection, are presented. New developments in the individual CE and CEC methods are demonstrated and several types of their applications are shown. They include qualitative and quantitative analysis, determination in complex biomatrices, monitoring of chemical and enzymatic reactions and physicochemical changes, amino acid, sequence, and chiral analyses, and peptide mapping of proteins. In addition, micropreparative separations and determination of significant physicochemical parameters of peptides by CE and CEC methods are described.
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Affiliation(s)
- Václav Kašička
- Institute of Organic Chemistry and Biochemistry, The Czech Academy of Sciences, Prague 6, Czechia
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19
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Helena H, Ivona V, Roman Ř, František F. Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review. J Sep Sci 2021; 45:305-324. [PMID: 34538010 PMCID: PMC9292318 DOI: 10.1002/jssc.202100621] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/07/2021] [Accepted: 09/10/2021] [Indexed: 12/17/2022]
Abstract
Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).
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Affiliation(s)
- Hrušková Helena
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic.,Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Voráčová Ivona
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
| | - Řemínek Roman
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
| | - Foret František
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
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Dunphy K, O’Mahoney K, Dowling P, O’Gorman P, Bazou D. Clinical Proteomics of Biofluids in Haematological Malignancies. Int J Mol Sci 2021; 22:ijms22158021. [PMID: 34360786 PMCID: PMC8348619 DOI: 10.3390/ijms22158021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 07/23/2021] [Accepted: 07/23/2021] [Indexed: 12/25/2022] Open
Abstract
Since the emergence of high-throughput proteomic techniques and advances in clinical technologies, there has been a steady rise in the number of cancer-associated diagnostic, prognostic, and predictive biomarkers being identified and translated into clinical use. The characterisation of biofluids has become a core objective for many proteomic researchers in order to detect disease-associated protein biomarkers in a minimally invasive manner. The proteomes of biofluids, including serum, saliva, cerebrospinal fluid, and urine, are highly dynamic with protein abundance fluctuating depending on the physiological and/or pathophysiological context. Improvements in mass-spectrometric technologies have facilitated the in-depth characterisation of biofluid proteomes which are now considered hosts of a wide array of clinically relevant biomarkers. Promising efforts are being made in the field of biomarker diagnostics for haematologic malignancies. Several serum and urine-based biomarkers such as free light chains, β-microglobulin, and lactate dehydrogenase are quantified as part of the clinical assessment of haematological malignancies. However, novel, minimally invasive proteomic markers are required to aid diagnosis and prognosis and to monitor therapeutic response and minimal residual disease. This review focuses on biofluids as a promising source of proteomic biomarkers in haematologic malignancies and a key component of future diagnostic, prognostic, and disease-monitoring applications.
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Affiliation(s)
- Katie Dunphy
- Department of Biology, National University of Ireland, W23 F2K8 Maynooth, Ireland; (K.D.); (P.D.)
| | - Kelly O’Mahoney
- Department of Haematology, Mater Misericordiae University Hospital, D07 WKW8 Dublin, Ireland; (K.O.); (P.O.)
| | - Paul Dowling
- Department of Biology, National University of Ireland, W23 F2K8 Maynooth, Ireland; (K.D.); (P.D.)
| | - Peter O’Gorman
- Department of Haematology, Mater Misericordiae University Hospital, D07 WKW8 Dublin, Ireland; (K.O.); (P.O.)
| | - Despina Bazou
- Department of Haematology, Mater Misericordiae University Hospital, D07 WKW8 Dublin, Ireland; (K.O.); (P.O.)
- Correspondence:
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21
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Hupe MC, Hempel MC, Rodler S, Frantzi M, Mischak H, Merseburger AS, Stief CG, Chaloupka M. [Diagnostic markers in urology]. Urologe A 2021; 60:1323-1330. [PMID: 34156515 DOI: 10.1007/s00120-021-01568-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Cancer diagnostics can be supplemented by disease-related biomarkers. In the course of modern patient-tailored cancer treatment, the importance of correct risk stratification, prognosis and monitoring has significantly increased. In recent years, a multitude of biomarkers and related test procedures have emerged to fulfil this purpose. The following review article summarizes the most recent developments with respect to the use of biomarkers in the diagnostics of urological cancers.
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Affiliation(s)
- Marie C Hupe
- Klinik für Urologie, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23638, Lübeck, Deutschland.
| | - Marie C Hempel
- Klinik für Urologie, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23638, Lübeck, Deutschland
| | - Severin Rodler
- Urologische Klinik und Poliklinik des Klinikums der Universität München, Campus Großhadern, Ludwig-Maximilians-Universität, Marchioninistraße 15, 81377, München, Deutschland
| | - Maria Frantzi
- Abteilung für Biomarkerforschung, Mosaiques Diagnostics GmbH, Hannover, Deutschland
| | - Harald Mischak
- Abteilung für Biomarkerforschung, Mosaiques Diagnostics GmbH, Hannover, Deutschland.,British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, Großbritannien
| | - Axel S Merseburger
- Klinik für Urologie, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23638, Lübeck, Deutschland
| | - Christian G Stief
- Urologische Klinik und Poliklinik des Klinikums der Universität München, Campus Großhadern, Ludwig-Maximilians-Universität, Marchioninistraße 15, 81377, München, Deutschland
| | - Michael Chaloupka
- Urologische Klinik und Poliklinik des Klinikums der Universität München, Campus Großhadern, Ludwig-Maximilians-Universität, Marchioninistraße 15, 81377, München, Deutschland.
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Frantzi M, Gomez-Gomez E, Mischak H. Noninvasive biomarkers to guide intervention: toward personalized patient management in prostate cancer. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2020. [DOI: 10.1080/23808993.2020.1804866] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Maria Frantzi
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany
| | | | - Harald Mischak
- Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
- Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), University of Cordoba, Cordoba, Spain
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Wendt R, Kalbitz S, Lübbert C, Kellner N, Macholz M, Schroth S, Ermisch J, Latosisnka A, Arnold B, Mischak H, Beige J, Metzger J. Urinary Proteomics Associates with COVID-19 Severity: Pilot Proof-of-Principle Data and Design of a Multicentric Diagnostic Study. Proteomics 2020; 20:e2000202. [PMID: 32960510 DOI: 10.1002/pmic.202000202] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 08/26/2020] [Indexed: 12/11/2022]
Abstract
SARS-CoV-2 infection results in a mild-to-moderate disease course in most patients, allowing outpatient self-care and quarantine. However, in approx. 10% of cases a two- or three-phasic critical disease course with starting from day 7 to 10 is observed. To facilitate and plan outpatient care, biomarkers prognosing such worsening at an early stage appear of outmost importance. In this accelerated article, we report on the identification of urinary peptides significantly associated with SARS-CoV-2 infection, and the development of a multi-marker urinary peptide based test, COVID20, that may enable prognosis of critical and fatal outcomes in COVID-19 patients. COVID20 is composed of 20 endogenous peptides mainly derived from various collagen chains that enable differentiating moderate or severe disease from critical state or death with 83% sensitivity at 100% specificity. Based on the performance in this pilot study, testing in a prospective study on 1000 patients has been initiated. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Ralph Wendt
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Sven Kalbitz
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Christoph Lübbert
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
- Department of Infectious Diseases and Tropical Medicine, Leipzig University Hospital, Leipzig, Germany
| | - Nils Kellner
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Martin Macholz
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Stefanie Schroth
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Jörg Ermisch
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | | | - Benjamin Arnold
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, St. Georg Hospital, Leipzig, Germany
| | - Harald Mischak
- Mosaiques-Diagnostics GmbH, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences, Glasgow, United Kingdom
| | - Joachim Beige
- Martin-Luther-University Halle/Wittenberg, Halle, Germany
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Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer. Diagnostics (Basel) 2020; 10:diagnostics10090658. [PMID: 32878288 PMCID: PMC7555799 DOI: 10.3390/diagnostics10090658] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 08/24/2020] [Accepted: 08/28/2020] [Indexed: 12/16/2022] Open
Abstract
Prostate cancer (PCa) is one of the most frequently diagnosed malignancies, and the fifth leading cause of cancer related mortality in men. For advanced PCa, radical prostatectomy, radiotherapy, and/or long-term androgen deprivation therapy are the recommended treatment options. However, subsequent progression to metastatic disease after initial therapy results in low 5-year survival rates (29%). Omics technologies enable the acquisition of high-resolution large datasets that can provide insights into molecular mechanisms underlying PCa pathology. For the purpose of this article, a systematic literature search was conducted through the Web of Science Database to critically evaluate recent omics-driven studies that were performed towards: (a) Biomarker development and (b) characterization of novel molecular-based therapeutic targets. The results indicate that multiple omics-based biomarkers with prognostic and predictive value have been validated in the context of PCa, with several of those being also available for commercial use. At the same time, omics-driven potential drug targets have been investigated in pre-clinical settings and even in clinical trials, holding the promise for improved clinical management of advanced PCa, as part of personalized medicine pipelines.
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Telomere-based risk models for the early diagnosis of clinically significant prostate cancer. Prostate Cancer Prostatic Dis 2020; 24:88-95. [PMID: 32367011 PMCID: PMC8012205 DOI: 10.1038/s41391-020-0232-4] [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: 01/31/2020] [Revised: 03/25/2020] [Accepted: 04/17/2020] [Indexed: 11/16/2022]
Abstract
Background The objective of this study was to explore telomere-associated variables (TAV) as complementary biomarkers in the early diagnosis of prostate cancer (PCa), analyzing their application in risk models for significant PCa (Gleason score > 6). Methods As part of a larger prospective longitudinal study of patients with suspicion of PCa undergoing prostate biopsy according to clinical practice, a subgroup of patients (n = 401) with PSA 3–10 ng/ml and no prior biopsies was used to evaluate the contribution of TAV to discern non-significant PCa from significant PCa. The cohort was randomly split for training (2/3) and validation (1/3) of the models. High-throughput quantitative fluorescence in-situ hybridization was used to evaluate TAV in peripheral blood mononucleated cells. Models were generated following principal component analysis and random forest and their utility as risk predictors was evaluated by analyzing their predictive capacity and accuracy, summarized by ROC curves, and their clinical benefit with decision curves analysis. Results The median age of the patients was 63 years, with a median PSA of 5 ng/ml and a percentage of PCa diagnosis of 40.6% and significant PCa of 19.2%. Two TAV-based risk models were selected (TAV models 1 and 2) with an AUC ≥ 0.83 in the full study cohort, and AUC > 0.76 in the internal validation cohort. Both models showed an improvement in decision capacity when compared to the application of the PCPT-RC in the low-risk probabilities range. In the validation cohort, with TAV models 1 and 2, 33% /48% of biopsies would have been avoided losing 0/10.3% of significant PCa, respectively. The models were also tested and validated on an independent, retrospective, non contemporary cohort. Conclusions Telomere analysis through TAV should be considered as a new risk-score biomarker with potential to increase the prediction capacity of significant PCa in patients with PSA between 3–10 ng/ml.
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