Literature DB >> 30659330

[Sex cord-stromal tumors of the ovary : Current aspects with a focus on granulosa cell tumors, Sertoli-Leydig cell tumors, and gynandroblastomas].

F Kommoss1, H-A Lehr2.   

Abstract

Sex cord-stromal tumors of the ovary (SCSTO) comprise a heterogeneous and fascinating group of neoplasms with diverse clinicopathological features, including benign lesions as well as tumors with malignant potential. Clinically, SCSTO may be associated with hyperestrogenic or androgenic function as a result of steroid hormone production by the tumor cells.Histological diagnosis may be challenging due to complex and sometimes overlapping morphological features of the various tumor types. A panel of immunohistochemical sex cord markers (e. g. inhibin-α, calretinin) has proven to be helpful in confirming the cellular lineage of SCSTO and differentiating them from other sex cord-like ovarian lesions. Recently, molecular analysis of SCSTO has led to the discovery of specific molecular events such as FOXL2 and DICER1 mutations. In selected diagnostically challenging cases, mutation analysis of FOXL2 and DICER1 may be helpful in the differential diagnosis. Molecular analysis is also expected to help advance the classification of SCSTO, and it may hold prognostic potential and form the basis for future type-specific therapies.This review focuses on the clinicopathological as well as the molecular features of adult and juvenile granulosa cell tumors (AGCTs and JGCTs) as well as Sertoli-Leydig cell tumors (SLCTs), these being the most relevant lesions with malignant potential in the SCSTO category. In addition, recently published molecular findings among rare ovarian gynandroblastomas (GABs) are described, which may also impact the future classification of SCSTO.

Entities:  

Keywords:  Forkhead box protein L2; Granulosa cell tumor; Gynandroblastoma; Human DICER1 protein; Sertoli-Leydig cell tumor

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Year:  2019        PMID: 30659330     DOI: 10.1007/s00292-018-0562-3

Source DB:  PubMed          Journal:  Pathologe        ISSN: 0172-8113            Impact factor:   1.011


  2 in total

1.  Analytical Validation of a Deep Neural Network Algorithm for the Detection of Ovarian Cancer.

Authors:  Gerard Reilly; Rowan G Bullock; Jessica Greenwood; Daniel R Ure; Erin Stewart; Pierre Davidoff; Justin DeGrazia; Herbert Fritsche; Charles J Dunton; Nitin Bhardwaj; Lesley E Northrop
Journal:  JCO Clin Cancer Inform       Date:  2022-06

Review 2.  Molecular Pathways and Targeted Therapies for Malignant Ovarian Germ Cell Tumors and Sex Cord-Stromal Tumors: A Contemporary Review.

Authors:  Asaf Maoz; Koji Matsuo; Marcia A Ciccone; Shinya Matsuzaki; Maximilian Klar; Lynda D Roman; Anil K Sood; David M Gershenson
Journal:  Cancers (Basel)       Date:  2020-05-29       Impact factor: 6.639

  2 in total

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