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Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive bio...

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Autores principales: Nitusca, Diana, Socaciu, Carmen, Socaciu, Andreea Iulia, Sirbu, Ioan Ovidiu, Bardan, Razvan, Cumpanas, Alin Adrian, Seclaman, Edward, Marian, Catalin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296965/
https://www.ncbi.nlm.nih.gov/pubmed/37367069
http://dx.doi.org/10.3390/cimb45060320
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author Nitusca, Diana
Socaciu, Carmen
Socaciu, Andreea Iulia
Sirbu, Ioan Ovidiu
Bardan, Razvan
Cumpanas, Alin Adrian
Seclaman, Edward
Marian, Catalin
author_facet Nitusca, Diana
Socaciu, Carmen
Socaciu, Andreea Iulia
Sirbu, Ioan Ovidiu
Bardan, Razvan
Cumpanas, Alin Adrian
Seclaman, Edward
Marian, Catalin
author_sort Nitusca, Diana
collection PubMed
description Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.
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spelling pubmed-102969652023-06-28 Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling Nitusca, Diana Socaciu, Carmen Socaciu, Andreea Iulia Sirbu, Ioan Ovidiu Bardan, Razvan Cumpanas, Alin Adrian Seclaman, Edward Marian, Catalin Curr Issues Mol Biol Article Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics. MDPI 2023-06-08 /pmc/articles/PMC10296965/ /pubmed/37367069 http://dx.doi.org/10.3390/cimb45060320 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nitusca, Diana
Socaciu, Carmen
Socaciu, Andreea Iulia
Sirbu, Ioan Ovidiu
Bardan, Razvan
Cumpanas, Alin Adrian
Seclaman, Edward
Marian, Catalin
Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title_full Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title_fullStr Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title_full_unstemmed Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title_short Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling
title_sort potential diagnostic biomarker detection for prostate cancer using untargeted and targeted metabolomic profiling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296965/
https://www.ncbi.nlm.nih.gov/pubmed/37367069
http://dx.doi.org/10.3390/cimb45060320
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