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. 2016 Sep;35(5):430-41.
doi: 10.1097/PGP.0000000000000274.

An Immunohistochemical Algorithm for Ovarian Carcinoma Typing

Martin Köbel  1 , Kurosh Rahimi, Peter F Rambau, Christopher Naugler, Cécile Le Page, Liliane Meunier, Manon de Ladurantaye, Sandra Lee, Samuel Leung, Ellen L Goode, Susan J Ramus, Joseph W Carlson, Xiaodong Li, Carol A Ewanowich, Linda E Kelemen, Barbara Vanderhyden, Diane Provencher, David Huntsman, Cheng-Han Lee, C Blake Gilks, Anne-Marie Mes Masson
Affiliations

An Immunohistochemical Algorithm for Ovarian Carcinoma Typing

Martin Köbel et al. Int J Gynecol Pathol. 2016 Sep.

Abstract

There are 5 major histotypes of ovarian carcinomas. Diagnostic typing criteria have evolved over time, and past cohorts may be misclassified by current standards. Our objective was to reclassify the recently assembled Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type cohorts using immunohistochemical (IHC) biomarkers and to develop an IHC algorithm for ovarian carcinoma histotyping. A total of 1626 ovarian carcinoma samples from the Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type were subjected to a reclassification by comparing the original with the predicted histotype. Histotype prediction was derived from a nominal logistic regression modeling using a previously reclassified cohort (N=784) with the binary input of 8 IHC markers. Cases with discordant original or predicted histotypes were subjected to arbitration. After reclassification, 1762 cases from all cohorts were subjected to prediction models (χ Automatic Interaction Detection, recursive partitioning, and nominal logistic regression) with a variable IHC marker input. The histologic type was confirmed in 1521/1626 (93.5%) cases of the Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type cohorts. The highest misclassification occurred in the endometrioid type, where most of the changes involved reclassification from endometrioid to high-grade serous carcinoma, which was additionally supported by mutational data and outcome. Using the reclassified histotype as the endpoint, a 4-marker prediction model correctly classified 88%, a 6-marker 91%, and an 8-marker 93% of the 1762 cases. This study provides statistically validated, inexpensive IHC algorithms, which have versatile applications in research, clinical practice, and clinical trials.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIG. 1
FIG. 1
The study flow chart. (A): the first reclassification part of the study was performed on the Canadian Ovarian Experimental Unified Resource (COEUR) cohort and the Alberta Ovarian Tumor Type cohort (AOVT, not shown). The previously reclassified Calculator of Ovarian Subtype Probability (COSP) prediction version 2a-generating (COSPv2a-generating) cohort was used to generate a histotype prediction using the categorical input from 8 immunohistochemistry (IHC) markers. (B) cohorts used and exclusion criteria for the second part of the study (IHC algorithm development). NAPSA indicates Napsin A.
FIG. 2
FIG. 2
Challenging cases between endometrioid (EC) and high-grade serous carcinoma (HGSC). The smaller insets beside the hematoxylin and eosin staining indicate corresponding WT1 (upper) and TP53 (lower) staining. All cases, except (A), showed the presence of WT1 and abnormal TP53 expression. (A) EC (Grade 3) reclassified from HGSC on the basis of a biomarker-assisted review (the absence of WT1) and the morphology showing a solid neoplasm (upper right) with squamoid features (lower left). (B) HGSC reclassified from the EC-based biomarker-assisted review (the presence of WT1 and abnormal TP53 expression without specific features for EC, i.e. the absence of low-grade nuclear atypia and squamous or mucinous differentiation). (C) EC (Grade 1) with weak WT1 and abnormal TP53 expression that was not reclassified by a biomarker-assisted review due to the presence of low-grade nuclear atypia and mucinous differentiation. (D) EC (Grade 2, ATiM693 in Tab. S3) with WT1 and an abnormal TP53 expression and a similar morphology compared with (C), which was reclassified to HGSC by a biomarker-assisted review, but sequencing refuted the reclassification. Concurrent TP53/PIK3CA mutations favor EC. (E) EC (Grade 3) with WT1 and abnormal TP53 expression that was not reclassified by the biomarker-assisted review due to the presence of low-grade nuclear atypia and squamous differentiation. (F) EC (Grade 3, ATiM322 in Tab. S3) with WT1 and abnormal TP53 expression and a similar morphology compared with (E), which was reclassified to HGSC by the biomarker-assisted review, but sequencing refuted the reclassification. Concurrent TP53/PIK3CA mutations favor EC.
FIG. 3
FIG. 3
The Kaplan-Meier survival analysis for reclassified endometrioid carcinoma to high-grade serous carcinoma (EC to HGSC, N=31) from the Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type cohort in comparison with reference EC (N=262) and HGSC (N=802) with available outcome data. EC indicates endometrioid carcinoma; HGSC, high-grade serous carcinoma.
FIG. 4
FIG. 4
The four-marker χ2 Automatic Interaction Detection (CHAID)-based immunohistochemistry (IHC) algorithm. Examples of images of IHC marker expression are included. TP53 abnormal is characterized by 2 patterns: diffuse overexpression and complete absence (note internal control in the latter). NAPSA expression shows granular cytoplasmic staining. CCC indicates clear cell carcinoma; EC, endometrioid carcinoma; HGSC, high-grade serous carcinoma; LGSC, low-grade serous carcinoma; MC, mucinous carcinoma; NAPSA, Napsin A.
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