Literature DB >> 31846522

Practical roles for molecular diagnostic testing in ovarian adult granulosa cell tumour, Sertoli-Leydig cell tumour, microcystic stromal tumour and their mimics.

Joseph T Rabban1, Anthony N Karnezis2, W Patrick Devine3.   

Abstract

Within the last decade, molecular advances have provided insights into the genetics of several ovarian sex cord-stromal tumours that have otherwise been enigmatic. Chief among these advances are the identification of FOXL2, DICER1 and CTNNB1 mutations in adult granulosa cell tumours, Sertoli-Leydig cell tumours (SLCTs), and microcystic stromal tumours (MCSTs), respectively. As access to molecular diagnostic laboratories continues to become more widely available, the potential roles for tumour mutation testing in the pathological diagnosis of these tumours merit discussion. Furthermore, links to inherited cancer susceptibility syndromes may exist for some women with SLCT (DICER1 syndrome) and MCST [familial adenomatous polyposis (FAP)]. This review will address practical issues in deciding when and how to apply mutation testing in the diagnosis of these three sex cord-stromal tumours. The pathologist's role in recommending referral for formal risk assessment for DICER1 syndrome and FAP will also be discussed.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  CTNNB1; DICER1; FOXL2; Sertoli-Leydig cell tumour; granulosa cell tumour; microcystic stromal tumour

Year:  2020        PMID: 31846522     DOI: 10.1111/his.13978

Source DB:  PubMed          Journal:  Histopathology        ISSN: 0309-0167            Impact factor:   5.087


  4 in total

1.  Embryonal rhabdomyosarcoma of the uterine corpus: a clinicopathological and molecular analysis of 21 cases highlighting a frequent association with DICER1 mutations.

Authors:  Jennifer A Bennett; Zehra Ordulu; Robert H Young; Andre Pinto; Koen Van de Vijver; Eike Burandt; Pankhuri Wanjari; Rajeev Shah; Leanne de Kock; William D Foulkes; W Glenn McCluggage; Lauren L Ritterhouse; Esther Oliva
Journal:  Mod Pathol       Date:  2021-05-20       Impact factor: 7.842

2.  Diagnosis and Prediction of Endometrial Carcinoma Using Machine Learning and Artificial Neural Networks Based on Public Databases.

Authors:  Dongli Zhao; Zhe Zhang; Zhonghuang Wang; Zhenglin Du; Meng Wu; Tingting Zhang; Jialu Zhou; Wenming Zhao; Yuanguang Meng
Journal:  Genes (Basel)       Date:  2022-05-24       Impact factor: 4.141

Review 3.  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

Review 4.  Ovarian microcystic stromal tumor with omental metastasis: the first case report and literature review.

Authors:  Xiaxia Man; Zhentong Wei; Baogang Wang; Wanying Li; Lingling Tong; Liang Guo; Songling Zhang
Journal:  J Ovarian Res       Date:  2021-05-27       Impact factor: 4.234

  4 in total

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