A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer

Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized i...
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Gespeichert in:

Autor*in:	Denise Drago [verfasserIn] Annapaola Andolfo [verfasserIn] Ettore Mosca [verfasserIn] Alessandro Orro [verfasserIn] Luigi Nocera [verfasserIn] Vito Cucchiara [verfasserIn] Matteo Bellone [verfasserIn] Francesco Montorsi [verfasserIn] Alberto Briganti [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	prostate cancer eps-urine metabolomics prediction diagnosis

Übergeordnetes Werk:	In: Cancer Biology & Medicine - China Anti-Cancer Association, 2019, 18(2021), 2, Seite 604-615
Übergeordnetes Werk:	volume:18 ; year:2021 ; number:2 ; pages:604-615

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.20892/j.issn.2095-3941.2020.0617

Katalog-ID:	DOAJ05289682X

Internformat


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650		4	\|a prostate
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653		0	\|a Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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allfields	10.20892/j.issn.2095-3941.2020.0617 doi (DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749 DE-627 ger DE-627 rakwb eng RC254-282 Denise Drago verfasserin aut A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies. prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Annapaola Andolfo verfasserin aut Ettore Mosca verfasserin aut Alessandro Orro verfasserin aut Luigi Nocera verfasserin aut Vito Cucchiara verfasserin aut Matteo Bellone verfasserin aut Francesco Montorsi verfasserin aut Alberto Briganti verfasserin aut In Cancer Biology & Medicine China Anti-Cancer Association, 2019 18(2021), 2, Seite 604-615 (DE-627)72193739X (DE-600)2676322-9 20953941 nnns volume:18 year:2021 number:2 pages:604-615 https://doi.org/10.20892/j.issn.2095-3941.2020.0617 kostenfrei https://doaj.org/article/50aeba4fda354560855a428811f19749 kostenfrei http://www.cancerbiomed.org/index.php/cocr/article/view/1861 kostenfrei https://doaj.org/toc/2095-3941 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 2 604-615
spelling	10.20892/j.issn.2095-3941.2020.0617 doi (DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749 DE-627 ger DE-627 rakwb eng RC254-282 Denise Drago verfasserin aut A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies. prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Annapaola Andolfo verfasserin aut Ettore Mosca verfasserin aut Alessandro Orro verfasserin aut Luigi Nocera verfasserin aut Vito Cucchiara verfasserin aut Matteo Bellone verfasserin aut Francesco Montorsi verfasserin aut Alberto Briganti verfasserin aut In Cancer Biology & Medicine China Anti-Cancer Association, 2019 18(2021), 2, Seite 604-615 (DE-627)72193739X (DE-600)2676322-9 20953941 nnns volume:18 year:2021 number:2 pages:604-615 https://doi.org/10.20892/j.issn.2095-3941.2020.0617 kostenfrei https://doaj.org/article/50aeba4fda354560855a428811f19749 kostenfrei http://www.cancerbiomed.org/index.php/cocr/article/view/1861 kostenfrei https://doaj.org/toc/2095-3941 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 2 604-615
allfields_unstemmed	10.20892/j.issn.2095-3941.2020.0617 doi (DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749 DE-627 ger DE-627 rakwb eng RC254-282 Denise Drago verfasserin aut A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies. prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Annapaola Andolfo verfasserin aut Ettore Mosca verfasserin aut Alessandro Orro verfasserin aut Luigi Nocera verfasserin aut Vito Cucchiara verfasserin aut Matteo Bellone verfasserin aut Francesco Montorsi verfasserin aut Alberto Briganti verfasserin aut In Cancer Biology & Medicine China Anti-Cancer Association, 2019 18(2021), 2, Seite 604-615 (DE-627)72193739X (DE-600)2676322-9 20953941 nnns volume:18 year:2021 number:2 pages:604-615 https://doi.org/10.20892/j.issn.2095-3941.2020.0617 kostenfrei https://doaj.org/article/50aeba4fda354560855a428811f19749 kostenfrei http://www.cancerbiomed.org/index.php/cocr/article/view/1861 kostenfrei https://doaj.org/toc/2095-3941 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 2 604-615
allfieldsGer	10.20892/j.issn.2095-3941.2020.0617 doi (DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749 DE-627 ger DE-627 rakwb eng RC254-282 Denise Drago verfasserin aut A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies. prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Annapaola Andolfo verfasserin aut Ettore Mosca verfasserin aut Alessandro Orro verfasserin aut Luigi Nocera verfasserin aut Vito Cucchiara verfasserin aut Matteo Bellone verfasserin aut Francesco Montorsi verfasserin aut Alberto Briganti verfasserin aut In Cancer Biology & Medicine China Anti-Cancer Association, 2019 18(2021), 2, Seite 604-615 (DE-627)72193739X (DE-600)2676322-9 20953941 nnns volume:18 year:2021 number:2 pages:604-615 https://doi.org/10.20892/j.issn.2095-3941.2020.0617 kostenfrei https://doaj.org/article/50aeba4fda354560855a428811f19749 kostenfrei http://www.cancerbiomed.org/index.php/cocr/article/view/1861 kostenfrei https://doaj.org/toc/2095-3941 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 2 604-615
allfieldsSound	10.20892/j.issn.2095-3941.2020.0617 doi (DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749 DE-627 ger DE-627 rakwb eng RC254-282 Denise Drago verfasserin aut A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies. prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Annapaola Andolfo verfasserin aut Ettore Mosca verfasserin aut Alessandro Orro verfasserin aut Luigi Nocera verfasserin aut Vito Cucchiara verfasserin aut Matteo Bellone verfasserin aut Francesco Montorsi verfasserin aut Alberto Briganti verfasserin aut In Cancer Biology & Medicine China Anti-Cancer Association, 2019 18(2021), 2, Seite 604-615 (DE-627)72193739X (DE-600)2676322-9 20953941 nnns volume:18 year:2021 number:2 pages:604-615 https://doi.org/10.20892/j.issn.2095-3941.2020.0617 kostenfrei https://doaj.org/article/50aeba4fda354560855a428811f19749 kostenfrei http://www.cancerbiomed.org/index.php/cocr/article/view/1861 kostenfrei https://doaj.org/toc/2095-3941 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 2 604-615
language	English
source	In Cancer Biology & Medicine 18(2021), 2, Seite 604-615 volume:18 year:2021 number:2 pages:604-615
sourceStr	In Cancer Biology & Medicine 18(2021), 2, Seite 604-615 volume:18 year:2021 number:2 pages:604-615
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	prostate cancer eps-urine metabolomics prediction diagnosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens
isfreeaccess_bool	true
container_title	Cancer Biology & Medicine
authorswithroles_txt_mv	Denise Drago @@aut@@ Annapaola Andolfo @@aut@@ Ettore Mosca @@aut@@ Alessandro Orro @@aut@@ Luigi Nocera @@aut@@ Vito Cucchiara @@aut@@ Matteo Bellone @@aut@@ Francesco Montorsi @@aut@@ Alberto Briganti @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	72193739X
id	DOAJ05289682X
language_de	englisch
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callnumber-first	R - Medicine
author	Denise Drago
spellingShingle	Denise Drago misc RC254-282 misc prostate misc cancer misc eps-urine misc metabolomics misc prediction misc diagnosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
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topic_title	RC254-282 A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer prostate cancer eps-urine metabolomics prediction diagnosis
topic	misc RC254-282 misc prostate misc cancer misc eps-urine misc metabolomics misc prediction misc diagnosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_unstemmed	misc RC254-282 misc prostate misc cancer misc eps-urine misc metabolomics misc prediction misc diagnosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_browse	misc RC254-282 misc prostate misc cancer misc eps-urine misc metabolomics misc prediction misc diagnosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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title	A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
ctrlnum	(DE-627)DOAJ05289682X (DE-599)DOAJ50aeba4fda354560855a428811f19749
title_full	A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
author_sort	Denise Drago
journal	Cancer Biology & Medicine
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author_browse	Denise Drago Annapaola Andolfo Ettore Mosca Alessandro Orro Luigi Nocera Vito Cucchiara Matteo Bellone Francesco Montorsi Alberto Briganti
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class	RC254-282
format_se	Elektronische Aufsätze
author-letter	Denise Drago
doi_str_mv	10.20892/j.issn.2095-3941.2020.0617
author2-role	verfasserin
title_sort	novel expressed prostatic secretion (eps)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
callnumber	RC254-282
title_auth	A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
abstract	Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.
abstractGer	Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.
abstract_unstemmed	Objective: Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH). Methods: We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy. Results: We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3). Conclusions: A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.
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title_short	A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer
url	https://doi.org/10.20892/j.issn.2095-3941.2020.0617 https://doaj.org/article/50aeba4fda354560855a428811f19749 http://www.cancerbiomed.org/index.php/cocr/article/view/1861 https://doaj.org/toc/2095-3941
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A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer

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