Genetic Info Helps Clarify Risk of Hereditary Breast Cancer

NEW YORK (GenomeWeb) – Incorporating some well-known genetic risk factors when assessing a woman's risk of non-BRCA-associated hereditary breast cancer can help to more accurately predict risk than just family history alone, according to a study published this week in Genetics in Medicine.

Researchers from the University of Utah and elsewhere used 24 well-known breast cancer risk SNPs that are not in the BRCA1 or BRCA2 genes to come up with a risk score for 4,365 women from two familial breast cancer cohorts, and compared that to a risk score based on family history alone.

The goal of the study was to see whether this panel of 24 SNPs could help to better stratify women already considered to be at an elevated risk due to family history in order to determine which women should receive additional screening, such as magnetic resonance imaging.

The study examined women from two different cohorts: the Breast Cancer Family Registry (BCFR) and the Kathleen Cuningham Consortium Foundation for Research into Familial Breast Cancer (kConFab) cohorts, and included women who had already been diagnosed with breast cancer as well as unaffected women.

The researchers genotyped the women using either capture-based next-generation sequencing, or a SNP genotyping array. They then generated a risk score based on the presence or absence of the SNP, its allele frequency, and the relative risk associated with it.

Next, they used a model called BOADICEA to predict breast cancer risk in 18,000 unaffected women from the two cohorts. The BOADICEA tool predicts a woman's risk of breast and ovarian cancers for 10 years and until the age of 80.

Looking at the genetic risk scores of the 2,869 women who were unaffected and the 1,496 women who were affected with breast cancer, the researchers found "highly significant" differences. Unaffected women had a mean genetic risk score of 2.170, slightly higher than their theoretical risk score of 2.123 based on having a positive family history. Affected women, meantime, had a risk score of 2.25. The unaffected women were followed for an average of 7.4 years, during which time 205 of them developed breast cancer.

Next, the researchers wanted to see the impact of combining the genetic risk scores with the family-history-based risk scores. The US recommends that women with a greater than 20 percent lifetime risk of breast cancer get MRI screening along with mammograms, while in the UK the threshold for MRI screening is 25 percent.

When the researchers added in risk assessment based on genetics to the family-history-based assessment, they noted that 249 of 1,585 women, or 16 percent, who were below the 20 percent risk threshold, moved above that. When using the higher threshold of 25 percent and including both genetic and family history-based risk assessments, 232 out of 2,176 women, or 11 percent, would move above the threshold.

"Inclusion of risk scores based on [breast cancer]-associated SNPs in risk assessment can provide more accurate risk prediction than family history alone and can influence recommendations for cancer screening and prevention modalities for high-risk women," the authors wrote.

CNN reports that researchers have tied a new variant to opioid addiction risk.

Organoids derived from patients' tumors may help determine what chemotherapy treatment patients would benefit from, according to New Scientist.

An initiative from GenomeAsia 100K hopes to increase the number of South Asians in genetic research, according to NBC News.

In Science this week: genomic analysis of ancient and modern horses indicates population turnover, and more.

Sponsored by

In this webinar, Jill Viles, an Iowa mother with no clinical training, shares her story of how she self-diagnosed her rare condition, a muscle-wasting disease caused by a mutation in the LMNA gene. She will also discuss how she discovered that a mutation in the same gene is the underlying cause for the excess muscle phenotype exhibited by Canadian Olympic hurdler Priscilla Lopes-Schliep. 

Sponsored by
Swift Biosciences

This webinar will discuss an optimized protocol for methyl-CpG binding domain sequencing (MBD-seq), which enables comprehensive, adequately powered, and cost-effective large-scale methylome-wide association studies (MWAS) of almost all 28 million CpG sites in the genome.

Sponsored by

This webinar will share how clinical genetics labs can integrate cytogenetics and molecular data to assess abnormalities using a single sample on a single workflow platform.

Sponsored by
Dovetail Genomics

Proximity ligation technology generates multi-dimensional next-generation sequencing data that is proving to solve unmet needs in genomic research.