JOURNAL ARTICLE
Carney complex predisposes to breast cancer: prospective study of 50 women.
Published In: European Journal of Endocrinology, 2024, v. 190, n. 2. P. 121 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Vaduva, Patricia; Violon, Florian; Jouinot, Anne; Bouys, Lucas; Espiard, Stéphanie; Bonnet-Serrano, Fidéline; North, Marie Odile; Cardot-Bauters, Catherine; Raverot, Gerald; Hieronimus, Sylvie; Lefebvre, Hervé; Nunes, Marie-Laure; Tabarin, Antoine; Groussin, Lionel; Assié, Guillaume; Sibony, Mathilde; Vantyghem, Marie-Christine; Pasmant, Eric; Bertherat, Jérôme 3 of 3
Abstract
This article focuses on the characterization of breast lesions, including breast cancer, in women with Carney complex (CNC), a rare genetic syndrome primarily caused by germline loss-of-function pathogenic variants in the PRKAR1A gene. In a prospective French multicenter study of 50 women with CNC, 39% had breast lesions, with 16% diagnosed with breast carcinomas at a mean age of 44.7 years—significantly younger than the general population—and all breast cancers occurred in patients carrying PRKAR1A pathogenic variants. Genetic analysis of tumor samples revealed loss of heterozygosity at the PRKAR1A locus in invasive breast cancers, suggesting a tumor suppressor role for PRKAR1A in breast carcinogenesis. The findings indicate that women with CNC, especially those with PRKAR1A mutations, have an increased risk of breast cancer, supporting consideration of tailored early screening and follow-up strategies in this population.
Additional Information
- Source:European Journal of Endocrinology. 2024/02, Vol. 190, Issue 2, p121
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0804-4643
- DOI:10.1093/ejendo/lvae010
- Accession Number:176004734
- Copyright Statement:Copyright of European Journal of Endocrinology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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