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Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies

BACKGROUND: Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype spe...

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Autores principales: Köbel, Martin, Kalloger, Steve E, Boyd, Niki, McKinney, Steven, Mehl, Erika, Palmer, Chana, Leung, Samuel, Bowen, Nathan J, Ionescu, Diana N, Rajput, Ashish, Prentice, Leah M, Miller, Dianne, Santos, Jennifer, Swenerton, Kenneth, Gilks, C. Blake, Huntsman, David
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2592352/
https://www.ncbi.nlm.nih.gov/pubmed/19053170
http://dx.doi.org/10.1371/journal.pmed.0050232
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author Köbel, Martin
Kalloger, Steve E
Boyd, Niki
McKinney, Steven
Mehl, Erika
Palmer, Chana
Leung, Samuel
Bowen, Nathan J
Ionescu, Diana N
Rajput, Ashish
Prentice, Leah M
Miller, Dianne
Santos, Jennifer
Swenerton, Kenneth
Gilks, C. Blake
Huntsman, David
author_facet Köbel, Martin
Kalloger, Steve E
Boyd, Niki
McKinney, Steven
Mehl, Erika
Palmer, Chana
Leung, Samuel
Bowen, Nathan J
Ionescu, Diana N
Rajput, Ashish
Prentice, Leah M
Miller, Dianne
Santos, Jennifer
Swenerton, Kenneth
Gilks, C. Blake
Huntsman, David
author_sort Köbel, Martin
collection PubMed
description BACKGROUND: Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis. METHODS AND FINDINGS: In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1) in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%–2.4%) but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1.2%–2.3%), but is a favourable prognostic marker within the high-grade serous subtype (RR 0.5, 95% CI 0.3%–0.8%). CONCLUSIONS: The association of biomarker expression with survival varies substantially between subtypes, and can easily be overlooked in whole cohort analyses. To avoid this effect, each subtype within a cohort should be analyzed discretely. Ovarian carcinoma subtypes are different diseases, and these differences should be reflected in clinical research study design and ultimately in the management of ovarian carcinoma.
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spelling pubmed-25923522008-12-02 Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies Köbel, Martin Kalloger, Steve E Boyd, Niki McKinney, Steven Mehl, Erika Palmer, Chana Leung, Samuel Bowen, Nathan J Ionescu, Diana N Rajput, Ashish Prentice, Leah M Miller, Dianne Santos, Jennifer Swenerton, Kenneth Gilks, C. Blake Huntsman, David PLoS Med Research Article BACKGROUND: Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis. METHODS AND FINDINGS: In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1) in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%–2.4%) but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1.2%–2.3%), but is a favourable prognostic marker within the high-grade serous subtype (RR 0.5, 95% CI 0.3%–0.8%). CONCLUSIONS: The association of biomarker expression with survival varies substantially between subtypes, and can easily be overlooked in whole cohort analyses. To avoid this effect, each subtype within a cohort should be analyzed discretely. Ovarian carcinoma subtypes are different diseases, and these differences should be reflected in clinical research study design and ultimately in the management of ovarian carcinoma. Public Library of Science 2008-12 2008-12-02 /pmc/articles/PMC2592352/ /pubmed/19053170 http://dx.doi.org/10.1371/journal.pmed.0050232 Text en : © 2008 Köbel et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Köbel, Martin
Kalloger, Steve E
Boyd, Niki
McKinney, Steven
Mehl, Erika
Palmer, Chana
Leung, Samuel
Bowen, Nathan J
Ionescu, Diana N
Rajput, Ashish
Prentice, Leah M
Miller, Dianne
Santos, Jennifer
Swenerton, Kenneth
Gilks, C. Blake
Huntsman, David
Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title_full Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title_fullStr Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title_full_unstemmed Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title_short Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies
title_sort ovarian carcinoma subtypes are different diseases: implications for biomarker studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2592352/
https://www.ncbi.nlm.nih.gov/pubmed/19053170
http://dx.doi.org/10.1371/journal.pmed.0050232
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