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DOI: 10.4103/2278-330x.119888
Immunohistochemistry: A diagnostic aid in differentiating primary epithelial ovarian tumors and tumors metastatic to the ovary
Source of Support: Nill.
Abstract
Introduction: Among cancers of the female genital tract, the incidence of ovarian cancer ranks below only carcinoma of the cervix and the endometrium. Recent years have witnessed significant development in the use of immunohistochemistry in diagnostic ovarian pathology. Materials and Methods: We received 95 specimens and biopsies of primary ovarian neoplasms and neoplasms metastatic to the ovary in a period of 2 years. Of these 30 cases were of the primary surface epithelial neoplasms and seven of metastatic tumors. Discussion: The most common tumors metastasizing to the ovary originate from the gastrointestinal tract followed by the endometrium. We used a panel of six markers including cytokeratin-7 (CK7), CK20, carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), estrogen receptor (ER) and Wilms’ tumor 1 (WT1) to help classify various surface epithelial tumors as well as to differentiate them from tumors metastatic to the ovary. Conclusion: CK7 is the most helpful marker to differentiate primary ovarian carcinoma from metastatic colorectal carcinoma of the ovary. Nearly, 96% of ovarian adenocarcinomas were positive for CK7 in contrast to metastatic colorectal, which showed only 25% positivity. We also found that CK7, CK20 and CEA are useful markers to differentiate primary serous tumors from primary mucinous tumors; however, these are less helpful in differentiating ovarian mucinous adenocarcinomas from colorectal adenocarcinomas metastasizing to the ovaries. WT1 helps in typing primary surface epithelial tumors of the ovary and is also significant in determining whether a serous carcinoma within the ovary is primary or metastatic.
Key words
Colorectal carcinoma - endometrial carcinoma - epithelial ovarian neoplasms - immunohistochemistryPublikationsverlauf
Artikel online veröffentlicht:
31. Dezember 2020
© 2013. MedIntel Services Pvt Ltd. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/.)
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