Abstract
Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention.
Highlights
Individual risk for developing breast cancer varies between 11.6% for women without specific clinical risk factors and 85% for women with pathogenic germline mutations in highly penetrant genes (i.e., BRCA1, BRCA2, TP53, and PTEN) [1,2,3,4,5,6]
A number of models are available for estimation of individual breast cancer risk based on clinical factors such as family history, reproductive profile, history of prior breast biopsy, and breast density (Table 1)
Mammographic density is a strong, independent risk factor for breast cancer development with studies showing a 4-6-fold increased risk for breast cancer for women with the highest breast density category compared with women in the lowest breast density category [29,30,31,32,33,34,35,36,37,38]
Summary
Individual risk for developing breast cancer varies between 11.6% for women without specific clinical risk factors (i.e., average risk) and 85% for women with pathogenic germline mutations in highly penetrant genes (i.e., BRCA1, BRCA2, TP53, and PTEN) [1,2,3,4,5,6]. A number of models are available for estimation of individual breast cancer risk based on clinical factors such as family history, reproductive profile, history of prior breast biopsy, and breast density (Table 1). The most commonly used clinical models are the Gail [14, 15], the Claus [16], and the International Breast Cancer Intervention Study (IBIS) models [17].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
