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Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues
Published on: October 20, 2019
Human epidermal growth factor receptor 2 fluorescence in situ hybridization and P57KIP2 immunohistochemistry using
Consuelo Lozoya López1, Ana Luisa Figueira Gouvêa1, Fabiana Resende Rodrigues1
1Department of Pathology, Fluminense Federal University, Niterói, Brazil.
Introduction:
Trophoblastic neoplasia is detected in approximately 25% of complete hydatidiform moles (CMs) and 0.5% of partial hydatidiform moles (PMs). Hydatidiform mole (HM) subtyping is important to properly monitor and predict patient outcomes. Ploidy studies generally involve diploid CMs and triploid PMs. P57KIP2, expressed in the maternal genome, is usually not detected in CM. We determined whether HER2 FISH and p57 immunostaining contributed to the histopathological classification of HMs.
Methods:
This retrospective cohort study focused on patients diagnosed with HM by histopathological examination who were followed up at a trophoblastic disease center from 2002 to 2017. Pathological samples of 108 products of conception were reviewed and reclassified according to detailed criteria. Tissue microarray technology (TMA) was used for p57 KIP2 immunostaining and HER2 FISH analysis.
Results:
Histopathological review showed 57 (53%) CMs, 47 (43%) PMs and 4 (4%) inconclusive cases. P57 immunostaining revealed 59 (55%) negative and 22 (20%) positive specimens, and 27 (25%) were inadequate for analysis. FISH HER2 detected 68 (63%) diploid and 33 (30%) triploid cases; two (2%) had oncogene amplification. The three strategies led to a diagnostic change in 28 samples (26%). The final diagnosis was CM in 75 cases (70%) and PM in 30 (28%); three cases remained inconclusive.
Discussion:
TMA is a cost-saving method that allows the simultaneous study of large case series. The combination of histopathology, HER2 FISH and p57 tests can be useful for accurately differentiating CM and PM, thus providing additional information on disease prognosis.
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