Date Published: December 2, 2008
Publisher: Public Library of Science
Author(s): Martin Köbel, Steve E Kalloger, Niki Boyd, Steven McKinney, Erika Mehl, Chana Palmer, Samuel Leung, Nathan J Bowen, Diana N Ionescu, Ashish Rajput, Leah M Prentice, Dianne Miller, Jennifer Santos, Kenneth Swenerton, C. Blake Gilks, David Huntsman, Steven Narod
Abstract: BackgroundAlthough 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 FindingsIn 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%).ConclusionsThe 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.
Partial Text: Ovarian carcinoma is a heterogeneous disease. On the basis of histopathological examination, pathologists classify ovarian carcinoma into serous, clear cell, endometrioid, and mucinous subtypes. Each of theses subtypes is associated with different genetic risk factors and molecular events during oncogenesis [1,2], and characterized by distinct mRNA expression profiles [3,4]. These subtypes differ dramatically in frequency, when early stage carcinomas (where the majority are nonserous carcinomas ) and advanced stage carcinomas (which are predominantly of serous subtype ) are compared.
Ovarian carcinomas subtypes are associated with distinct genetic risk factors, underlying molecular events during oncogenesis, stage at diagnosis, and responses to chemotherapy. With slight modification of the WHO criteria for histopathological assignment for subtype we have recently shown that classification of ovarian carcinomas into five subtypes (high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous) is reproducible and is supported by biomarker expression data .