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Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer

Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 – >10...

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Autores principales: Burdelski, Christoph, Matuszewska, Aleksandra, Kluth, Martina, Koop, Christina, Grupp, Katharina, Steurer, Stefan, Wittmer, Corinna, Minner, Sarah, Tsourlakis, Maria Christina, Sauter, Guido, Schlomm, Thorsten, Simon, Ronald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5003445/
https://www.ncbi.nlm.nih.gov/pubmed/27600340
http://dx.doi.org/10.3390/microarrays3020137
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author Burdelski, Christoph
Matuszewska, Aleksandra
Kluth, Martina
Koop, Christina
Grupp, Katharina
Steurer, Stefan
Wittmer, Corinna
Minner, Sarah
Tsourlakis, Maria Christina
Sauter, Guido
Schlomm, Thorsten
Simon, Ronald
author_facet Burdelski, Christoph
Matuszewska, Aleksandra
Kluth, Martina
Koop, Christina
Grupp, Katharina
Steurer, Stefan
Wittmer, Corinna
Minner, Sarah
Tsourlakis, Maria Christina
Sauter, Guido
Schlomm, Thorsten
Simon, Ronald
author_sort Burdelski, Christoph
collection PubMed
description Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 – >10,000 tumors. We found a strong association between the “prognostic power” of individual markers and the number of tissues that should be minimally included in such studies. The prognostic relevance of more than 90% of the 39 IHC markers could be detected if ≥6400 tissue samples were analyzed. Studying markers of tissue quality, including immunohistochemistry of ets-related gene (ERG) and vimentin, and fluorescence in-situ hybridization analysis of human epidermal growth factor receptor 2 (HER2), we found that 18% of tissues in our tissue microarray (TMA) showed signs of reduced tissue preservation and limited immunoreactivity. Comparing the results of Kaplan-Meier survival analyses or associations to ERG immunohistochemistry in subsets of tumors with and without exclusion of these defective tissues did not reveal statistically relevant differences. In summary, our study demonstrates that TMA-based marker validation studies using biochemical recurrence as an endpoint require at least 6400 individual tissue samples for establishing statistically relevant associations between the expression of molecular markers and patient outcome if weak to moderate prognosticators should also be reliably identified.
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spelling pubmed-50034452016-09-06 Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer Burdelski, Christoph Matuszewska, Aleksandra Kluth, Martina Koop, Christina Grupp, Katharina Steurer, Stefan Wittmer, Corinna Minner, Sarah Tsourlakis, Maria Christina Sauter, Guido Schlomm, Thorsten Simon, Ronald Microarrays (Basel) Article Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 – >10,000 tumors. We found a strong association between the “prognostic power” of individual markers and the number of tissues that should be minimally included in such studies. The prognostic relevance of more than 90% of the 39 IHC markers could be detected if ≥6400 tissue samples were analyzed. Studying markers of tissue quality, including immunohistochemistry of ets-related gene (ERG) and vimentin, and fluorescence in-situ hybridization analysis of human epidermal growth factor receptor 2 (HER2), we found that 18% of tissues in our tissue microarray (TMA) showed signs of reduced tissue preservation and limited immunoreactivity. Comparing the results of Kaplan-Meier survival analyses or associations to ERG immunohistochemistry in subsets of tumors with and without exclusion of these defective tissues did not reveal statistically relevant differences. In summary, our study demonstrates that TMA-based marker validation studies using biochemical recurrence as an endpoint require at least 6400 individual tissue samples for establishing statistically relevant associations between the expression of molecular markers and patient outcome if weak to moderate prognosticators should also be reliably identified. MDPI 2014-04-17 /pmc/articles/PMC5003445/ /pubmed/27600340 http://dx.doi.org/10.3390/microarrays3020137 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Burdelski, Christoph
Matuszewska, Aleksandra
Kluth, Martina
Koop, Christina
Grupp, Katharina
Steurer, Stefan
Wittmer, Corinna
Minner, Sarah
Tsourlakis, Maria Christina
Sauter, Guido
Schlomm, Thorsten
Simon, Ronald
Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title_full Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title_fullStr Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title_full_unstemmed Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title_short Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer
title_sort qualitative and quantitative requirements for assessing prognostic markers in prostate cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5003445/
https://www.ncbi.nlm.nih.gov/pubmed/27600340
http://dx.doi.org/10.3390/microarrays3020137
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