Reach Us +44-1764910199
All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.


The Diagnostic Utility of Immunohistochemistry in Undifferentiated Ovarian Carcinoma

Background: The impact of diagnostic immunohistochemistry (IHC) for the surgical pathology is legendary especially when it provides true identity of undifferentiated tumors. It is very important for the plane of management and prognostication, and it also provides further insights into the pathogenesis of these tumors. So, this study was undertaken to determine the role and significance of IHC for accurate diagnosis and subtyping of undifferentiated ovarian carcinoma as it is essential in guiding therapy and prognosis.

Material and methods: IHC staining performed on 20 cases of undifferentiated ovarian carcinomas. A panel of antibodies was chosen to confirm the epithelial origin of these tumors and to exclude the possibility of ovarian metastasis from other sites.

Results: IHC staining results showed that: 2 cases were malignant mesothelioma (calretinin+, panCKA1/A3+, CK7+, EMA+, vimentin+). Two other cases were granulosa cell tumor (inhibin+, calertinin+, vimentin+). Sixteen cases were undifferentiated ovarian carcinoma (PAX8+, vimentin+, panCKA1/A3+, CK7+, EMA+).

Conclusion: The designed combinations of immunostaining profiles are helpful in the diagnosis of tumor origin and could offer a fast and correct prediction of the primary tumor site. PanCKA1/A3, CK7, CK20, vimentin, EMA, calertinin, inhibin, PAX8, GCDFP15 antibodies were sufficient for classification in most cases, whereas CA125 and CEA may help in supporting the diagnosis.


Hala Abdeldayem Mouhamed

Abstract | Full-Text | PDF

Share this  Facebook  Twitter  LinkedIn  Google+
Flyer image

Abstracted/Indexed in

  • Google Scholar
  • China National Knowledge Infrastructure (CNKI)
  • CiteFactor
  • WorldCat
  • Publons
  • Geneva Foundation for Medical Education and Research
  • Secret Search Engine Labs