izpis_h1_title_alt

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
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)

.pdfPDF - Presentation file, Download (1,54 MB)
MD5: 31C7E0EA2B665251D691741DC5C72855
URLURL - Source URL, Visit https://www.sciencedirect.com/science/article/pii/S0960977623005660 This link opens in a new window

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.

Language:English
Keywords:early breast cancer, polygenic risk score, risk prediction, Tyrer Cuzick algorithm
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:MF - Faculty of Medicine
FŠ - Faculty of Sport
Publication status:Published
Publication version:Version of Record
Year:2023
Number of pages:6 str.
Numbering:Vol. 72, art. 103590
PID:20.500.12556/RUL-152893 This link opens in a new window
UDC:618.1
ISSN on article:0960-9776
DOI:10.1016/j.breast.2023.103590 This link opens in a new window
COBISS.SI-ID:171467523 This link opens in a new window
Publication date in RUL:11.12.2023
Views:188
Downloads:18
Metadata:XML RDF-CHPDL DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Record is a part of a journal

Title:The Breast
Shortened title:Breast
Publisher:Elsevier
ISSN:0960-9776
COBISS.SI-ID:1316116 This link opens in a 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.

Secondary language

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

Projects

Funder:ARRS - Slovenian Research Agency
Project number:P3-0352
Name:Družine s povišano ali visoko ogroženostjo za raka: svetovanje, odkrivanje mutacij in preprečevanje raka

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back