Exome sequencing identifies breast cancer susceptibility genes and defines the contribution of coding variants to breast cancer risk

Population-based germline breast cancer gene association studies and meta-analysis to inform wider mainstream testing

BACKGROUND

Germline genetic testing, previously restricted to familial and young-onset breast cancer, is now offered increasingly broadly to 'population-type' breast cancer patients in mainstream oncology clinics, with wide variation in the genes included.

METHODS

Weighted meta-analysis was performed for three population-based case-control studies (BRIDGES, CARRIERS and UK Biobank) comprising in total 101,397 women with breast cancer and 312,944 women without breast cancer, to quantify for 37 putative breast cancer susceptibility genes (BCSGs) the frequency of pathogenic variants (PVs) in unselected, 'population-type' breast cancer cases and their association with breast cancer and its subtypes.

RESULTS

Meta-analysed odds ratios (ORs) and frequencies of PVs in population-type breast cancer cases were generated for BRCA1 (OR= 8.73 (95% CI 7.47-10.20), 1 in 101), BRCA2 (OR=5.68 (5.13-6.30), 1 in 68) and PALB2 (OR= 4.30 (95% CI 3.68-5.03), 1 in 187). For both CHEK2 (OR=2.40 (95% CI 2.21-2.62), 1 in 73) and ATM (OR=2.16 (95%CI 1.93-2.41), 1 in 132) subgroup analysis showed stronger association with ER-positive disease. Magnitude of association and frequency of PVs were low for RAD51C (OR=1.53 (95%CI 1.15-2.04), 1 in 913), RAD51D (OR=1.76, (95%CI 1.15-2.41, 1 in 1079) and BARD1 (OR=2.34 (1.85-2.97), 1 in 672); frequencies and associations were moderately higher restricting to triple-negative breast cancers The PV-frequency in 'population-type' breast cancer cases was very low for 'syndromic' BCSGs TP53 (1 in 1844), STK11 (1 in 11,525), CDH1 (1 in 2668), PTEN (1 in 3755) and NF1 (1 in 1470), with metrics of association also modest ranging from OR=3.62 (95%CI 1.98-6.61) for TP53 down to OR=1.60 (95%CI 0.48-5.30) for STK11.

CONCLUSIONS

These metrics reflecting 'population-type' breast cancer will be informative to defining the appropriate gene set as we continue to expand to germline testing out to more unselected population-type breast cancer cases.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer

Importance

Genetic information is not being used to identify women at lower risk of breast cancer or other diseases in clinical practice. With the new US Preventive Services Task Force guidelines lowering the age for mammogram screening for all, there is a potential benefit in identifying women at lower risk of disease who may defer the start of mammographic screening. This genetic risk-based approach would help mitigate overscreening, associated costs, and anxiety.

Objective

To assess breast cancer incidence and age of onset among women at low genetic risk compared with women at average risk and evaluate the potential to delay mammography on the basis of genetic risk stratification.

Design, Setting, and Participants

This retrospective case-control study included 25 591 women from the Healthy Nevada Project sequenced by Helix between 2018 and 2022. Data extracted from electronic health records at the end of 2022 (mean length of electronic health record available was 12 years) were used for the analysis in 2023.

Main Outcomes and Measures

Breast cancer diagnosis was identified from electronic health records. Classification to the low-risk genetic group required (1) the absence of pathogenic variants or a variant of uncertain significance in BRCA1, BRCA2, PALB2, ATM, or CHEK2, and (2) a low polygenic risk score (bottom 10%) using a 313-single-nucleotide variant model.

Results

Of 25 591 women in the study (mean [SD] age was 53.8 [16.9] years), 2338 women (9.1%) were classified as having low risk for breast cancer; 410 women (1.6%) were classified as high risk; and 22 843 women (89.3%) as average risk. There was a significant reduction in breast cancer diagnosis among the low-risk group (hazard ratio, 0.39; 95% CI, 0.29-0.52; P < .001). By 45 years of age, 0.69% of women in the average-risk group were diagnosed with breast cancer, whereas women in the low-risk group reached this rate at 51 years. By 50 years of age, 1.41% of those in the average-risk group were diagnosed with breast cancer, whereas those in the low-risk group reached this rate at age 58 years. These findings suggest that deferring mammogram screening by 5 to 10 years for women at low risk of breast cancer aligns with new draft recommendations.

Conclusions and Relevance

The findings of this retrospective case-control study underscore the value of genetics in individualizing the onset of breast cancer screening. Improving breast cancer risk stratification by implementing both high-risk and low-risk strategies in screening can refine preventive measures and optimize health care resource allocation.

Comprehensive clinical, genome and transcriptomic analysis of primary ghost cell odontogenic carcinoma

OBJECTIVES

There is currently no comprehensive genome-wide description of the primary ghost cell odontogenic carcinoma (GCOC), hindering our understanding of pathogenesis. We herein present a case with comprehensive clinical, genome and transcriptomic analysis. These will serve as the first comprehensive molecular atlas for primary GCOC. A 58-year-old male underwent subtotal resection with prosthetic restoration. Genome sequencing (WGS) detected previously identified CTNNB1 mutation with novel alterations of MAP3K, EP300, and 22q11.21 region. Transcriptome results showed significant involvement of cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. These results need to be compared with more GCOCs for more accurate clinical guidance.

Ancestry-specific polygenic risk scores are risk enhancers for clinical cardiovascular disease assessments

Clinical implementation of new prediction models requires evaluation of their utility in a broad range of intended use populations. Here we develop and validate ancestry-specific Polygenic Risk Scores (PRSs) for Coronary Artery Disease (CAD) using 29,389 individuals from diverse cohorts and genetic ancestry groups. The CAD PRSs outperform published scores with an average Odds Ratio per Standard Deviation of 1.57 (SD = 0.14) and identify between 12% and 24% of individuals with high genetic risk. Using this risk factor to reclassify borderline or intermediate 10 year Atherosclerotic Cardiovascular Disease (ASCVD) risk improves assessments for both CAD (Net Reclassification Improvement (NRI) = 13.14% (95% CI 9.23-17.06%)) and ASCVD (NRI = 10.70 (95% CI 7.35-14.05)) in an independent cohort of 9,691 individuals. Our analyses demonstrate that using PRSs as Risk Enhancers improves ASCVD risk assessments outlining an approach for guiding ASCVD prevention with genetic information.