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Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa
The high recurrence rate and invasive diagnostic and monitoring methods in bladder cancer (BCa) clinical management require the development of new non-invasive molecular tools for early detection, particularly for low-grade and low-stage BCa as well as for risk stratification. By using an in-solutio...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573217/ https://www.ncbi.nlm.nih.gov/pubmed/37834386 http://dx.doi.org/10.3390/ijms241914938 |
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author | Davalieva, Katarina Kiprijanovska, Sanja Ivanovski, Ognen Trifunovski, Aleksandar Saidi, Skender Dimovski, Aleksandar Popov, Zivko |
author_facet | Davalieva, Katarina Kiprijanovska, Sanja Ivanovski, Ognen Trifunovski, Aleksandar Saidi, Skender Dimovski, Aleksandar Popov, Zivko |
author_sort | Davalieva, Katarina |
collection | PubMed |
description | The high recurrence rate and invasive diagnostic and monitoring methods in bladder cancer (BCa) clinical management require the development of new non-invasive molecular tools for early detection, particularly for low-grade and low-stage BCa as well as for risk stratification. By using an in-solution digestion method and label-free data-independent LC-MS/MS coupled with ion mobility, we profiled the BCa tissues from initiation to advanced stages and confidently identified and quantified 1619 proteins (≥2 peptides). A statistically significant difference in abundance (Anova ≤ 0.05) showed 494 proteins. Significant correlation with stage with steady up or down with BCa stages showed 15 proteins. Testing of NNMT, GALK1, and HTRA1 in urine samples showed excellent diagnostic potential for NNMT and GALK1 with AUC of 1.000 (95% CI: 1.000–1.000; p < 0.0001) and 0.801 (95% CI: 0.655–0.947; p < 0.0001), respectively. NNMT and GALK1 also showed very good potential in discriminating non-invasive low-grade from invasive high-grade BCa with AUC of 0.763 (95% CI: 0.606–0.921; p = 0.001) and 0.801 (95% CI: 0.653–0.950; p < 0.0001), respectively. The combination of NNMT and GALK1 increased prognostic accuracy (AUC = 0.813). Our results broaden the range of potential novel candidates for non-invasive BCa diagnosis and prognosis. |
format | Online Article Text |
id | pubmed-10573217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105732172023-10-14 Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa Davalieva, Katarina Kiprijanovska, Sanja Ivanovski, Ognen Trifunovski, Aleksandar Saidi, Skender Dimovski, Aleksandar Popov, Zivko Int J Mol Sci Article The high recurrence rate and invasive diagnostic and monitoring methods in bladder cancer (BCa) clinical management require the development of new non-invasive molecular tools for early detection, particularly for low-grade and low-stage BCa as well as for risk stratification. By using an in-solution digestion method and label-free data-independent LC-MS/MS coupled with ion mobility, we profiled the BCa tissues from initiation to advanced stages and confidently identified and quantified 1619 proteins (≥2 peptides). A statistically significant difference in abundance (Anova ≤ 0.05) showed 494 proteins. Significant correlation with stage with steady up or down with BCa stages showed 15 proteins. Testing of NNMT, GALK1, and HTRA1 in urine samples showed excellent diagnostic potential for NNMT and GALK1 with AUC of 1.000 (95% CI: 1.000–1.000; p < 0.0001) and 0.801 (95% CI: 0.655–0.947; p < 0.0001), respectively. NNMT and GALK1 also showed very good potential in discriminating non-invasive low-grade from invasive high-grade BCa with AUC of 0.763 (95% CI: 0.606–0.921; p = 0.001) and 0.801 (95% CI: 0.653–0.950; p < 0.0001), respectively. The combination of NNMT and GALK1 increased prognostic accuracy (AUC = 0.813). Our results broaden the range of potential novel candidates for non-invasive BCa diagnosis and prognosis. MDPI 2023-10-06 /pmc/articles/PMC10573217/ /pubmed/37834386 http://dx.doi.org/10.3390/ijms241914938 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 Davalieva, Katarina Kiprijanovska, Sanja Ivanovski, Ognen Trifunovski, Aleksandar Saidi, Skender Dimovski, Aleksandar Popov, Zivko Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title | Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title_full | Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title_fullStr | Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title_full_unstemmed | Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title_short | Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa |
title_sort | proteomics profiling of bladder cancer tissues from early to advanced stages reveals nnmt and galk1 as biomarkers for early detection and prognosis of bca |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573217/ https://www.ncbi.nlm.nih.gov/pubmed/37834386 http://dx.doi.org/10.3390/ijms241914938 |
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