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Integration of Molecular Data in the Prognostic Stratification and Management of Endometrial Carcinoma

In the last years, the TCGA-based molecular classifier have been progressively integrated in the management of endometrial carcinoma. While molecular assays are increasingly available across pathology laboratories, the additional costs will expectedly be compensated by a reduction in overtreatments...

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Bibliographic Details
Published in:Journal of personalized medicine 2022-12, Vol.12 (12), p.2083
Main Authors: Raffone, Antonio, Travaglino, Antonio, Raimondo, Diego, Casadio, Paolo, Seracchioli, Renato, Zannoni, Gian Franco, Mollo, Antonio
Format: Article
Language:English
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Summary:In the last years, the TCGA-based molecular classifier have been progressively integrated in the management of endometrial carcinoma. While molecular assays are increasingly available across pathology laboratories, the additional costs will expectedly be compensated by a reduction in overtreatments and a prevention of recurrences. The additional time might be shortened by assessing molecular markers on biopsy specimens. Retrospective data suggest that the molecular classifier will have a major impact of on the risk stratification, with many patients having their risk class down- or upstaged based on mutations or p53 abnormalities, respectively. However, there are still several issues to be resolved, such as the prognostic value of the TCGA classifier in each FIGO stage, or the type of adjuvant treatment most suitable for each molecular group. Other issues regard the prognostic stratification of the mismatch repair-deficient and "no specific molecular profile" groups, which currently follows the same criteria; however, the former seems to be prognostically consistent regardless of FIGO grade and histotype, whereas the latter appears highly heterogeneous. Numerous clinical, histological, immunohistochemical and molecular markers have been proposed to refine the TCGA classification, but their prognostic value is still undefined. Hopefully, prospective data collected in the next years will help resolving these issues.
ISSN:2075-4426
2075-4426
DOI:10.3390/jpm12122083