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Published on: December 5, 2017
Human epidermal growth factor receptor 2 and proliferation Ki-67 biomarkers using a tissue microarray to refine the
Consuelo Lozoya López1, Nathália Silva Carlos Oliveira2, Fabiana Resende Rodrigues2
1Department of Pathology, Faculdade de Medicina, Universidade Federal Fluminense, Hospital Universitário Antonio Pedro (HUAP-UFF), Niterói, RJ, Brazil; Postgraduate Program in Pathology, Faculdade de Medicina, Universidade Federal Fluminense, Hospital Universitário Antonio Pedro (HUAP-UFF), Niterói, RJ, Brazil.
Introduction:
The morphology-based differential diagnosis of Hydatidiform Mole (HM) of the Complete (CHM) and Partial (PHM) types is challenging because of earlier diagnosis of HM owing to the universal application of ultrasound during antenatal care. HMs may present with amplified oncogenes or other gene mutations, resulting in recurrent or neoplastic disease. The cell proliferation markers Ki-67 and HER2 may contribute to the final HM subtype and prognosis. Much is known about the basic mechanisms of HM development; however, other molecular diagnostic and predictive markers need to be investigated.
Methods:
This was an ambispective anatomopathological study of 108 HMs cases. A tissue microarray was used for Ki-67 or HER2 immunostaining analysis. Associations between immunomarker scores and postmolar Gestational Trophoblastic Neoplasia (GTN) were analyzed via Fisher's exact and linear-by-linear association tests.
Results:
A statistically significant trend toward increased Ki-67 immunostaining in CHM samples was observed. Seventeen HM patients developed GTN, of whom 6 (35 %) had a Ki-67 score of 3+ and 9 (53 %) had Ki-67 score of 2+. Two (12 %) HM patients had a HER2 score of 3+, and 4 (23 %) HM patients had a HER2 score of 2+, of whom 2 (12 %) patients exhibited oncogene amplification by FISH HER2.
Discussion:
Ki-67 and HER2 markers may be useful for the diagnosis and prediction of HM development, providing alternative targeted therapies. This study needs to be interpreted with caution due to its small sample size, high sample exclusion rate, and the absence of significant associations between biomarkers and clinical outcomes.
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