Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium

Author:

Köbel Martin1,Kalloger Steve E.1,Lee Sandra1,Duggan Máire A.1,Kelemen Linda E.1,Prentice Leah1,Kalli Kimberly R.1,Fridley Brooke L.1,Visscher Daniel W.1,Keeney Gary L.1,Vierkant Robert A.1,Cunningham Julie M.1,Chow Christine1,Ness Roberta B.1,Moysich Kirsten1,Edwards Robert111,Modugno Francesmary111,Bunker Clareann1,Wozniak Eva L.1,Benjamin Elizabeth1,Gayther Simon A.1,Gentry-Maharaj Aleksandra1,Menon Usha1,Gilks C. Blake1,Huntsman David G.1,Ramus Susan J.1,Goode Ellen L.1

Affiliation:

1. Authors' Affiliations: 1Department of Pathology and Laboratory Medicine; 2Department of Population Health Research, Alberta Health Services-Cancer Care and Department of Medical Genetics, University of Calgary, Calgary, Alberta; 3Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada; 4Department of Medical Oncology; 5Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology; 6Division of Biomedical Statistics and Informatics, Department of Health Science Research; 7Division of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology; 8Division of Epidemiology, Department of Health Science Research, Mayo Clinic, Rochester, Minnesota; 9Biostatistics and Informatics Shared Resource, University of Kansas Medical Center, Kansas City, Kansas; 10University of Texas School of Public Health, Houston, Texas; 11Roswell Park Cancer Institute, Buffalo, New York, New York; 12Women's Cancer Research C

Abstract

Abstract Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model. Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review. Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2. Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type. Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.

Publisher

American Association for Cancer Research (AACR)

Cited by 72 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.7亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2025 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3