Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data

Journal article


Publication Details

Author(s): Wunderle M, Olmes G, Nabieva N, Häberle L, Jud S, Hein A, Rauh C, Hack C, Erber R, Ekici AB, Hoyer J, Vasileiou G, Kraus C, Reis A, Hartmann A, Schulz-Wendtland R, Lux MP, Beckmann M, Fasching PA
Journal: Geburtshilfe und Frauenheilkunde
Publication year: 2018
Volume: 78
Journal issue: 5
Pages range: 481-492
ISSN: 0016-5751


Abstract

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that - together with previously identified common variants - more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.


FAU Authors / FAU Editors

Beckmann, Matthias Prof. Dr.
Lehrstuhl für Geburtshilfe und Frauenheilkunde
Erber, Ramona Dr. med.
Pathologisches Institut
Fasching, Peter PD Dr.
Professur für Translationale Frauenheilkunde und Geburtshilfe
Hack, Carolin PD Dr.
Medizinische Fakultät
Hartmann, Arndt Prof. Dr. med.
Lehrstuhl für Allgemeine Pathologie und Pathologische Anatomie
Hein, Alexander PD Dr.
Frauenklinik
Jud, Sebastian Dr.
Frauenklinik
Nabieva, Naiba Dr. med.
Frauenklinik
Olmes, Gregor Dr. med.
Medizinische Fakultät
Wunderle, Marius
Professur für Translationale Frauenheilkunde und Geburtshilfe


How to cite

APA:
Wunderle, M., Olmes, G., Nabieva, N., Häberle, L., Jud, S., Hein, A.,... Fasching, P.A. (2018). Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data. Geburtshilfe und Frauenheilkunde, 78(5), 481-492. https://dx.doi.org/10.1055/a-0603-4350

MLA:
Wunderle, Marius, et al. "Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data." Geburtshilfe und Frauenheilkunde 78.5 (2018): 481-492.

BibTeX: 

Last updated on 2018-19-11 at 12:53