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Title:Breast cancer risk prediction using Tyrer-Cuzick algorithm with an 18-SNPs polygenic risk score in a European population with below-average breast cancer incidence
Authors:ID Oblak, Tjaša (Author)
ID Škerl, Petra (Author)
ID Narang, Benjamin J. (Author)
ID Blagus, Rok (Author)
ID Krajc, Mateja (Author)
ID Novaković, Srdjan (Author)
ID Žgajnar, Janez (Author)
Files:.pdf PDF - Presentation file, download (1,54 MB)
MD5: 30126FCF8DD7081DEACE47978CED93DA
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo OI - Institute of Oncology
Abstract:Goals: To determine whether an 18 single nucleotide polymorphisms (SNPs) polygenic risk score (PRS18) improves breast cancer (BC) risk prediction for women at above-average risk of BC, aged 40-49, in a Central European population with BC incidence below EU average. Methods: 502 women aged 40-49 years at the time of BC diagnosis completed a questionnaire on BC risk factors (as per Tyrer-Cuzick algorithm) with data known at age 40 and before BC diagnosis. Blood samples were collected for DNA isolation. 250 DNA samples from healthy women aged 50 served as a control cohort. 18 BC-associated SNPs were genotyped in both groups and PRS18 was calculated. The predictive power of PRS18 to detect BC was evaluated using a ROC curve. 10-year BC risk was calculated using the Tyrer-Cuzick algorithm adapted to the Slovenian incidence rate (S-IBIS): first based on questionnaire-based risk factors and, second, including PRS18. Results: The AUC for PRS18 was 0.613 (95 % CI 0.570-0.657). 83.3 % of women were classified at above-average risk for BC with S-IBIS without PRS18 and 80.7 % when PRS18 was included. Conclusion: BC risk prediction models and SNPs panels should not be automatically used in clinical practice in different populations without prior population-based validation. In our population the addition of an 18SNPs PRS to questionnaire-based risk factors in the Tyrer-Cuzick algorithm in general did not improve BC risk stratification, however, some improvements were observed at higher BC risk scores and could be valuable in distinguishing women at intermediate and high risk of BC.
Keywords:early breast cancer, polygenic risk score, risk prediction
Publication status:Published
Publication version:Version of Record
Submitted for review:27.09.2023
Article acceptance date:09.10.2023
Publication date:12.10.2023
Publisher:Elsevier
Year of publishing:2023
Number of pages:str. [1-10]
Numbering:Vol. 72, št.
Source:Amsterdam
PID:20.500.12556/DiRROS-18506 New window
UDC:618.1
ISSN on article:0960-9776
DOI:10.1016/j.breast.2023.103590 New window
COBISS.SI-ID:171467523 New window
Copyright:by Authors
Publication date in DiRROS:21.03.2024
Views:739
Downloads:213
Metadata:XML DC-XML DC-RDF
:
OBLAK, Tjaša, ŠKERL, Petra, NARANG, Benjamin J., BLAGUS, Rok, KRAJC, Mateja, NOVAKOVIĆ, Srdjan and ŽGAJNAR, Janez, 2023, Breast cancer risk prediction using Tyrer-Cuzick algorithm with an 18-SNPs polygenic risk score in a European population with below-average breast cancer incidence. The Breast [online]. 2023. Vol. 72, p. 1–10. [Accessed 7 April 2025]. DOI 10.1016/j.breast.2023.103590. Retrieved from: https://dirros.openscience.si/IzpisGradiva.php?lang=eng&id=18506
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Record is a part of a journal

Title:The Breast
Shortened title:Breast
Publisher:Churchill Livingstone
ISSN:0960-9776
COBISS.SI-ID:1316116 New window

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:12.10.2023

Secondary language

Language:Slovenian
Keywords:zgodnji rak dojke, poligenski dejavniki tveganja, napoved tveganja


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