The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions

Inclusion of Endogenous Plasma Dehydroepiandrosterone Sulfate and Mammographic Density in Risk Prediction Models for Breast Cancer

BACKGROUND

Endogenous hormones and mammographic density are risk factors for breast cancer. Joint analyses of the two may improve the ability to identify high-risk women.

METHODS

This study within the KARMA cohort included prediagnostic measures of plasma hormone levels of dehydroepiandrosterone (DHEA), its sulfate (DHEAS), and mammographic density in 629 cases and 1,223 controls, not using menopausal hormones. We evaluated the area under the receiver-operating curve (AUC) for risk of breast cancer by adding DHEA, DHEAS, and mammographic density to the Gail or Tyrer-Cuzick 5-year risk scores or the CAD2Y 2-year risk score.

RESULTS

DHEAS and percentage density were independently and positively associated with breast cancer risk (P = 0.007 and P < 0.001, respectively) for postmenopausal, but not premenopausal, women. No significant association was seen for DHEA. In postmenopausal women, those in the highest tertiles of both DHEAS and density were at greatest risk of breast cancer (OR, 3.5; 95% confidence interval, 1.9-6.3) compared with the lowest tertiles. Adding DHEAS significantly improved the AUC for the Gail (+2.1 units, P = 0.008) and Tyrer-Cuzick (+1.3 units, P = 0.007) risk models. Adding DHEAS to the Gail and Tyrer-Cuzick models already including mammographic density further increased the AUC by 1.2 units (P = 0.006) and 0.4 units (P = 0.007), respectively, compared with only including density.

CONCLUSIONS

DHEAS and mammographic density are independent risk factors for breast cancer and improve risk discrimination for postmenopausal breast cancer.

IMPACT

Combining DHEAS and mammographic density could help identify women at high risk who may benefit from individualized breast cancer screening and/or preventive measures among postmenopausal women.

Recreational Physical Activity Is Associated with Reduced Breast Cancer Risk in Adult Women at High Risk for Breast Cancer: A Cohort Study of Women Selected for Familial and Genetic Risk

Although physical activity is associated with lower breast cancer risk for average-risk women, it is not known if this association applies to women at high familial/genetic risk. We examined the association of recreational physical activity (self-reported by questionnaire) with breast cancer risk using the Prospective Family Study Cohort, which is enriched with women who have a breast cancer family history (N = 15,550). We examined associations of adult and adolescent recreational physical activity (quintiles of age-adjusted total metabolic equivalents per week) with breast cancer risk using multivariable Cox proportional hazards regression, adjusted for demographics, lifestyle factors, and body mass index. We tested for multiplicative interactions of physical activity with predicted absolute breast cancer familial risk based on pedigree data and with BRCA1 and BRCA2 mutation status. Baseline recreational physical activity level in the highest four quintiles compared with the lowest quintile was associated with a 20% lower breast cancer risk (HR, 0.80; 95% confidence interval, 0.68-0.93). The association was not modified by familial risk or BRCA mutation status (P interactions >0.05). No overall association was found for adolescent recreational physical activity. Recreational physical activity in adulthood may lower breast cancer risk for women across the spectrum of familial risk. SIGNIFICANCE: These findings suggest that physical activity might reduce breast cancer risk by about 20% for women across the risk continuum, including women at higher-than-average risk due to their family history or genetic susceptibility.See related commentary by Niehoff et al., p. 23.

Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk

BACKGROUND

Breast cancer (BC) risk assessment models are statistical estimates based on patient characteristics. We developed a gene expression assay to assess BC risk using benign breast biopsy tissue.

METHODS

A NanoString-based malignancy risk (MR) gene signature was validated for formalin-fixed paraffin-embedded (FFPE) tissue. It was applied to FFPE benign and BC specimens obtained from women who underwent breast biopsy, some of whom developed BC during follow-up to evaluate diagnostic capability of the MR signature. BC risk was calculated with MR score, Gail risk score, and both tests combined. Logistic regression and receiver operating characteristic curves were used to evaluate these 3 models.

RESULTS

NanoString MR demonstrated concordance between fresh frozen and FFPE malignant samples (r = 0.99). Within the validation set, 563 women with benign breast biopsies from 2007 to 2011 were identified and followed for at least 5 y; 50 women developed BC (affected) within 5 y from biopsy. Three groups were compared: benign tissue from unaffected and affected patients and malignant tissue from affected patients. Kruskal-Wallis test suggested difference between the groups (P = 0.09) with trend in higher predicted MR score for benign tissue from affected patients before development of BC. Neither the MR signature nor Gail risk score were statistically different between affected and unaffected patients; combining both tests demonstrated best predictive value (AUC = 0.71).

CONCLUSIONS

FFPE gene expression assays can be used to develop a predictive test for BC. Further investigation of the combined MR signature and Gail Model is required. Our assay was limited by scant cellularity of archived breast tissue.

Exome sequencing reveals a high prevalence of BRCA1 and BRCA2 founder variants in a diverse population-based biobank

BACKGROUND

Pathogenic variants in BRCA1 and BRCA2 (BRCA1/2) lead to increased risk of breast, ovarian, and other cancers, but most variant-positive individuals in the general population are unaware of their risk, and little is known about prevalence in non-European populations. We investigated BRCA1/2 prevalence and impact in the electronic health record (EHR)-linked BioMe Biobank in New York City.

METHODS

Exome sequence data from 30,223 adult BioMe participants were evaluated for pathogenic variants in BRCA1/2. Prevalence estimates were made in population groups defined by genetic ancestry and self-report. EHR data were used to evaluate clinical characteristics of variant-positive individuals.

RESULTS

There were 218 (0.7%) individuals harboring expected pathogenic variants, resulting in an overall prevalence of 1 in 139. The highest prevalence was in individuals with Ashkenazi Jewish (AJ; 1 in 49), Filipino and other Southeast Asian (1 in 81), and non-AJ European (1 in 103) ancestry. Among 218 variant-positive individuals, 112 (51.4%) harbored known founder variants: 80 had AJ founder variants (BRCA1 c.5266dupC and c.68_69delAG, and BRCA2 c.5946delT), 8 had a Puerto Rican founder variant (BRCA2 c.3922G>T), and 24 had one of 19 other founder variants. Non-European populations were more likely to harbor BRCA1/2 variants that were not classified in ClinVar or that had uncertain or conflicting evidence for pathogenicity (uncertain/conflicting). Within mixed ancestry populations, such as Hispanic/Latinos with genetic ancestry from Africa, Europe, and the Americas, there was a strong correlation between the proportion of African genetic ancestry and the likelihood of harboring an uncertain/conflicting variant. Approximately 28% of variant-positive individuals had a personal history, and 45% had a personal or family history of BRCA1/2-associated cancers. Approximately 27% of variant-positive individuals had prior clinical genetic testing for BRCA1/2. However, individuals with AJ founder variants were twice as likely to have had a clinical test (39%) than those with other pathogenic variants (20%).

CONCLUSIONS

These findings deepen our knowledge about BRCA1/2 variants and associated cancer risk in diverse populations, indicate a gap in knowledge about potential cancer-related variants in non-European populations, and suggest that genomic screening in diverse patient populations may be an effective tool to identify at-risk individuals.

A way forward for cancer prevention therapy: personalized risk assessment

Cancer is characterized by genetic and molecular aberrations whose number and complexity increase dramatically as cells progress along the spectrum of carcinogenesis. The pharmacologic application of agents in the context of a lower burden of dysregulated cellular processes constitutes an efficient strategy to enhance therapeutic efficacy, and underlies the rationale for using cancer prevention agents in high-risk populations. A longstanding barrier to implementing this strategy is that the risk in the general population is low for any given cancer, many people would have to be treated in order to benefit a few. Therefore, identifying and treating high-risk individuals will improve the risk: benefit ratio. Currently, risk is defined by considering a relatively low number of factors. A strategy that considers multiple factors has the ability to define a much-higher-risk cohort than the general population. This article will review the rationale for evaluating multiple risk factors so as to identify individuals at highest risk. It will use breast and lung cancer as examples, will describe currently available risk assessment tools, and will discuss ongoing efforts to expand the impact of this approach. The high potential of this strategy to provide a way forward for developing cancer prevention therapy will be highlighted.

Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool

BACKGROUND

iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data.

METHODS

iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed.

RESULTS

During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy.

CONCLUSIONS

For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b.

A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer

Importance

Moving to multigene testing for all women with breast cancer (BC) could identify many more mutation carriers who can benefit from precision prevention. However, the cost-effectiveness of this approach remains unaddressed.

Objective

To estimate incremental lifetime effects, costs, and cost-effectiveness of multigene testing of all patients with BC compared with the current practice of genetic testing (BRCA) based on family history (FH) or clinical criteria.

Design, Setting, and Participants

This cost-effectiveness microsimulation modeling study compared lifetime costs and effects of high-risk BRCA1/BRCA2/PALB2 (multigene) testing of all unselected patients with BC (strategy A) with BRCA1/BRCA2 testing based on FH or clinical criteria (strategy B) in United Kingdom (UK) and US populations. Data were obtained from 11 836 patients in population-based BC cohorts (regardless of FH) recruited to 4 large research studies. Data were collected and analyzed from January 1, 2018, through June 8, 2019. The time horizon is lifetime. Payer and societal perspectives are presented. Probabilistic and 1-way sensitivity analyses evaluate model uncertainty.

Interventions

In strategy A, all women with BC underwent BRCA1/BRCA2/PALB2 testing. In strategy B, only women with BC fulfilling FH or clinical criteria underwent BRCA testing. Affected BRCA/PALB2 carriers could undertake contralateral preventive mastectomy; BRCA carriers could choose risk-reducing salpingo-oophorectomy (RRSO). Relatives of mutation carriers underwent cascade testing. Unaffected relative carriers could undergo magnetic resonance imaging or mammography screening, chemoprevention, or risk-reducing mastectomy for BC risk and RRSO for ovarian cancer (OC) risk.

Main Outcomes and Measures

Incremental cost-effectiveness ratio (ICER) was calculated as incremental cost per quality-adjusted life-year (QALY) gained and compared with standard £30 000/QALY and $100 000/QALY UK and US thresholds, respectively. Incidence of OC, BC, excess deaths due to heart disease, and the overall population effects were estimated.

Results

BRCA1/BRCA2/PALB2 multigene testing for all patients detected with BC annually would cost £10 464/QALY (payer perspective) or £7216/QALY (societal perspective) in the United Kingdom or $65 661/QALY (payer perspective) or $61 618/QALY (societal perspective) in the United States compared with current BRCA testing based on clinical criteria or FH. This is well below UK and US cost-effectiveness thresholds. In probabilistic sensitivity analysis, unselected multigene testing remained cost-effective for 98% to 99% of UK and 64% to 68% of US health system simulations. One year's unselected multigene testing could prevent 2101 cases of BC and OC and 633 deaths in the United Kingdom and 9733 cases of BC and OC and 2406 deaths in the United States. Correspondingly, 8 excess deaths due to heart disease occurred in the United Kingdom and 35 in the United States annually.

Conclusions and Relevance

This study found unselected, high-risk multigene testing for all patients with BC to be extremely cost-effective compared with testing based on FH or clinical criteria for UK and US health systems. These findings support changing current policy to expand genetic testing to all women with BC.

Alcohol consumption, cigarette smoking, and familial breast cancer risk: findings from the Prospective Family Study Cohort (ProF-SC)

Background

Alcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman’s familial BC risk.

Methods

Using the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm.

Results

We observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85–1.23; consuming ≥ 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92–1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming ≥ 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07–1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80–1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (p_interaction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers.

Conclusions

Moderate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted familial BC risk (5-year BOADICEA < 1.25). For women with a high FRP (5-year BOADICEA ≥ 6.5%) who also consumed alcohol, being a current smoker was associated with increased BC risk.

Outcomes of women at high familial risk for breast cancer: An 8-year single-center experience

OBJECTIVES

The value of a high-risk surveillance program for mutation carriers and women at high familial breast cancer risk has not been extensively studied. A Breast and Ovarian Cancer Risk Management Clinic (BOCRMC) was established at the Royal Melbourne Hospital in 2010 to provide multimodality screening and risk management strategies for this group of women. The aims of this study were to evaluate the program and describe breast cancer diagnoses for BRCA1, BRCA2, and other germline mutation carriers as well as high-risk noncarriers attending the BOCRMC.

METHODS

Clinical data from mutation carriers and noncarriers with a ≥25% lifetime risk of developing breast cancer who attended between 2010 and 2018 were extracted from clinic records and compared. The pattern and mode of detection of cancer were determined.

RESULTS

A total of 206 mutation carriers and 305 noncarriers attended the BOCRMC and underwent screening on at least one occasion. Median age was 37 years. After a median follow-up of 34 months, 15 (seven invasive) breast cancers were identified in mutation carriers, with seven (six invasive) breast cancers identified in noncarriers. Of these, 20 (90.9%) were detected by annual screening, whereas two (9.1%) were detected as interval cancers (both in BRCA1 mutation carriers). Median size of the invasive breast cancers was 11 mm (range: 1.5-30 mm). The majority (76.9%) were axillary node negative. In women aged 25-49 years, the annualized cancer incidence was 1.6% in BRCA1, 1.4% in BRCA2 mutation carriers, and 0.5% in noncarriers. This compares to 0.06% annualized cancer incidence in the general Australian population.

CONCLUSIONS

Screening was effective at detecting early-stage cancers. The incidence of events in young noncarriers was substantially higher than in the general population. This potentially justifies ongoing management through a specialty clinic, although further research to better personalize risk assessment in noncarriers is required.

Accuracy in risk understanding among BRCA1/2-mutation carriers

OBJECTIVE

BRCA1/2-mutation carriers are at high risk of developing cancer. Since they must weigh clinical recommendations and decide on risk-reducing measures, the correct understanding of their 10-year cancer risks is essential. This study focused on the accuracy of women's subjective estimates of developing breast and ovarian cancer within ten years as prerequisite to reduce unnecessary prevention.

METHODS

59 and 52 BRCA1/2-mutation carriers provided their individual risks of developing breast or ovarian cancer in the next 10 years, along with self-reported sociodemographic and psychosocial variables. Women's risk estimates were compared with their objective cancer risks that had been communicated before.

RESULTS

22.6% of counselees under- and 53.2% of the counselees overestimated their 10-year risk of developing breast cancer. As for ovarian cancer, 5.6% under- whereas 51.9% overestimated their risk. Neither demographic factors such as education, parenthood and age, nor a prior diagnosis of breast cancer or prophylactic surgery accounted for these variations in risk accuracy.

CONCLUSION

Currently, risk communication during genetic counseling does not guarantee accurate risk estimation in BRCA-mutation carriers.

PRACTICE IMPLICATIONS

Counselors must be prepared to prevent overestimation. Counselees' risk estimates need to be assessed and corrected to enable informed decision-making and reduce risks of unnecessary preventive efforts.

Breast Cancer Risk Model Requirements for Counseling, Prevention, and Screening

Background

Incorporation of polygenic risk scores and mammographic density into models to predict breast cancer incidence can increase discriminatory accuracy (area under the receiver operating characteristic curve [AUC]) from 0.6 for models based only on epidemiologic factors to 0.7. It is timely to assess what impact these improvements will have on individual counseling and on public health prevention and screening strategies, and to determine what further improvements are needed.

Methods

We studied various clinical and public health applications using a log-normal distribution of risk.

Results

Provided they are well calibrated, even risk models with AUCs of 0.6 to 0.7 provide useful perspective for individual counseling and for weighing the harms and benefits of preventive interventions in the clinic. At the population level, they are helpful for designing preventive intervention trials, for assessing reductions in absolute risk from reducing exposure to modifiable risk factors, and for resource allocation (although a higher AUC would be desirable for risk-based allocation). Other public health applications require higher AUCs that can only be achieved with risk predictors 1.6 to 8.8 times as strong as all those yet discovered combined. Such applications are preventing an appreciable proportion of population disease when employing a high-risk prevention strategy and deciding who should be screened for subclinical disease.

Conclusions

Current and foreseeable risk models are useful for counseling and some prevention activities, but given the daunting challenge of achieving, for example, an AUC of 0.8, considerable effort should be put into finding effective preventive interventions and screening strategies with fewer adverse effects.

The role of BRCA1/2 in hereditary and familial breast and ovarian cancers

BACKGROUND

BRCA1/2 pathogenic variants have become associated with familial breast and ovarian cancers, and hereditary cancer-predisposition syndrome. With advances in molecular biology, BRCA profiling facilitates early diagnosis and the implementation of preventive and therapeutic strategies. The genes exhibit variable prevalence among different individuals and moderate interpretation complexity. BRCA deficiency is instrumental in cancer development, affects therapeutic options and is instrumental in drug resistance. In addition, BRCA1/2 profile is diverse across different groups and has been associated with the "founder effect" in certain populations.

METHODS

In this review, we aim to detail the spectrum of BRCA1/2 variants and their associated risk estimates.

RESULTS

The relationship between BRCA1/2 and hereditary and familial cancers is indisputable, yet BRCA screening methods are beset with limitations and lack clinical confidence.

CONCLUSION

This review emphasizes the importance of screening BRCA genetics, in addition to their clinical utility. Furthermore, founder variants are anticipated in the Saudi population.

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

Breast cancer risk assessment: Evaluation of screening tools for genetics referral

BACKGROUND AND PURPOSE

The United States Preventative Services Task Force (USPSTF) recommends breast cancer risk-screening tools to help primary care providers determine which unaffected patients to refer to genetic specialists. The USPSTF does not recommend one tool above others. The purpose of this study was to compare tool performance in identifying women at risk for breast cancer.

METHODS

Pedigrees of 85 women aged 40-74 years with first-degree female relative with breast cancer were evaluated using five tools: Family History Screen-7 (FHS-7), Pedigree Assessment Tool, Manchester Scoring System, Referral Screening Tool, and Ontario Family History Assessment Tool (Ontario-FHAT). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to describe each tool's ability to identify women with elevated risk as defined by Claus Model calculations (lifetime risk ≥15%). Receiver operating curves were plotted. Differences between areas under the curve were estimated and compared through logistic regression to assess for differences in tool performance.

CONCLUSIONS

Claus calculations identified 14 of 85 women with elevated risk. Two tools, Ontario-FHAT and FHS-7, identified all women with elevated risk (sensitivity 100%). The FHS-7 tool flagged all participants (specificity 0%). The Ontario-FHAT flagged 59 participants as needing referral (specificity 36.2%) and had a NPV of 100%. Area under the curve values were not significantly different between tools (all p values > .05), and thus were not helpful in discriminating between the tools.

IMPLICATIONS FOR PRACTICE

The Ontario-FHAT outperformed other tools in sensitivity and NPV; however, low specificity and PPV must be balanced against these findings. Thus, the Ontario-FHAT can help determine which women would benefit from referral to genetics specialists.

Pregnancy and Breast Cancer: Pathways to Understand Risk and Prevention

Several studies have made strong efforts to understand how age and parity modulate the risk of breast cancer. A holistic understanding of the dynamic regulation of the morphological, cellular, and molecular milieu of the mammary gland offers insights into the drivers of breast cancer development as well as into potential prophylactic interventions, the latter being a longstanding ambition of the research and clinical community aspiring to eradicate the disease. In this review we discuss mechanisms that react to pregnancy signals, and we delineate the nuances of pregnancy-associated dynamism that contribute towards either breast cancer development or prevention. Further definition of the molecular basis of parity and breast cancer risk may allow the elaboration of tools to predict and survey those who are at risk of breast cancer development.

BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors

PURPOSE

Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).

METHODS

BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.

RESULTS

Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of ≥17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk).

CONCLUSION

This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

Global Disparities in Breast Cancer Genetics Testing, Counselling and Management

Hereditary breast cancers, mainly due to BRCA1 and BRCA2 mutations, account for only 5-10% of this disease. The threshold for genetic testing is a 10% likelihood of detecting a mutation, as determined by validated models such as BOADICEA and Manchester Scoring System. A 90-95% reduction in breast cancer risk can be achieved with bilateral risk-reducing mastectomy in unaffected BRCA mutation carriers. In patients with BRCA-associated breast cancer, there is a 40% risk of contralateral breast cancer and hence risk-reducing contralateral mastectomy is recommended, which can be performed simultaneously with surgery for unilateral breast cancer. Other options for risk management include surveillance by mammogram and breast magnetic resonance imaging, and chemoprevention with hormonal agents. With the advent of next-generation sequencing and development of multigene panel testing, the cost and time taken for genetic testing have reduced, making it possible for treatment-focused genetic testing. There are also drugs such as the PARP inhibitors that specifically target the BRCA mutation. Risk management multidisciplinary clinics are designed to quantify risk, and offer advice on preventative strategies. However, such services are only possible in high-income settings. In low-resource settings, the prohibitive cost of testing and the lack of genetic counsellors are major barriers to setting up a breast cancer genetics service. Family history is often not well documented because of the stigma associated with cancer. Breast cancer genetics services remain an unmet need in low- and middle-income countries, where the priority is to optimise access to quality treatment.

Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models

BACKGROUND

Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminatory accuracy (0.53-0.64). Machine learning (ML) offers an alternative approach to standard prediction modeling that may address current limitations and improve accuracy of those tools. The purpose of this study was to compare the discriminatory accuracy of ML-based estimates against a pair of established methods-the Breast Cancer Risk Assessment Tool (BCRAT) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) models.

METHODS

We quantified and compared the performance of eight different ML methods to the performance of BCRAT and BOADICEA using eight simulated datasets and two retrospective samples: a random population-based sample of U.S. breast cancer patients and their cancer-free female relatives (N = 1143), and a clinical sample of Swiss breast cancer patients and cancer-free women seeking genetic evaluation and/or testing (N = 2481).

RESULTS

Predictive accuracy (AU-ROC curve) reached 88.28% using ML-Adaptive Boosting and 88.89% using ML-random forest versus 62.40% with BCRAT for the U.S. population-based sample. Predictive accuracy reached 90.17% using ML-adaptive boosting and 89.32% using ML-Markov chain Monte Carlo generalized linear mixed model versus 59.31% with BOADICEA for the Swiss clinic-based sample.

CONCLUSIONS

There was a striking improvement in the accuracy of classification of women with and without breast cancer achieved with ML algorithms compared to the state-of-the-art model-based approaches. High-accuracy prediction techniques are important in personalized medicine because they facilitate stratification of prevention strategies and individualized clinical management.

Do cancer risk and benefit-harm ratios influence women's consideration of risk-reducing mastectomy? A scenario-based experiment in five European countries

BACKGROUND

Personal cancer risk assessments enable stratified care, for example, offering preventive surgical measures such as risk-reducing mastectomy (RRM) to women at high risk for breast cancer. In scenario-based experiments, we investigated whether different benefit-harm ratios of RRM influence women's consideration of this, whether this consideration is influenced by women's perception of and desire to know their personal cancer risk, or by their intention to take a novel cancer risk-predictive test, and whether consideration varies across different countries.

METHOD

In January 2017, 1,675 women 40 to 75 years of age from five European countries-Czech Republic, Germany, UK, Italy, and Sweden-took part in an online scenario-based experiment. Six different scenarios of hypothetical benefit-harm ratios of RRM were presented in accessible fact box formats: Baseline risk/risk reduction pairings were 20/16, 20/4, 10/8, 10/2, 5/4, and 5/1 out of 1,000 women dying from breast cancer.

RESULTS

Varying the baseline risk of dying from breast cancer and the extent of risk reduction influenced the decision to consider RRM for 23% of women. Decisions varied by country, risk perception, and the intention to take a cancer risk-predictive test. Women who expressed a stronger intention to take such a test were more likely to consider having RRM. The desire to know one's risk of developing any female cancer in general moderated women's decisions, whereas the specific desire to know the risk of breast cancer did not.

CONCLUSIONS

In this hypothetical scenario-based study, only for a minority of women did the change in benefit-harm ratio inform their consideration of RRM. Because this consideration is influenced by risk perception and the intention to learn one's cancer risks via a cancer risk-predictive test, careful disclosure of different potential preventive measures and their benefit-harm ratios is necessary before testing for individual risk. Furthermore, information on risk testing should acknowledge country-specific sensitivities for benefit-harm ratios.

High-Resolution Bisulfite-Sequencing of Peripheral Blood DNA Methylation in Early-Onset and Familial Risk Breast Cancer Patients

PURPOSE

Understanding and explaining hereditary predisposition to cancer has focused on the genetic etiology of the disease. However, mutations in known genes associated with breast cancer, such as BRCA1 and BRCA2, account for less than 25% of familial cases of breast cancer. Recently, specific epigenetic modifications at BRCA1 have been shown to promote hereditary breast cancer, but the broader potential for epigenetic contribution to hereditary breast cancer is not yet well understood.

EXPERIMENTAL DESIGN

We examined DNA methylation through deep bisulfite sequencing of CpG islands and known promoter or regulatory regions in peripheral blood DNA from 99 patients with familial or early-onset breast or ovarian cancer, 6 unaffected BRCA mutation carriers, and 49 unaffected controls.

RESULTS

In 9% of patients, we observed altered methylation in the promoter regions of genes known to be involved in cancer, including hypermethylation at the tumor suppressor PTEN and hypomethylation at the proto-oncogene TEX14. These alterations occur in the form of allelic methylation that span up to hundreds of base pairs in length.

CONCLUSIONS

Our observations suggest a broader role for DNA methylation in early-onset, familial risk breast cancer. Further studies are warranted to clarify these mechanisms and the benefits of DNA methylation screening for early risk prediction of familial cancers.

Novel BRCA2 pathogenic variant c.5219 T > G; p.(Leu1740Ter) in a consanguineous Senegalese family with hereditary breast cancer

Background

Pathogenic variants associated with hereditary breast cancer have been reported for BRCA1 and BRCA2 (BRCA1/2) genes in patients from multiple ethnicities, but limited information is available from sub-Saharan African populations. We report a BRCA2 pathogenic variant in a Senegalese family with hereditary breast cancer.

Methods

An index case from a consanguineous family and nineteen healthy female relatives were recruited after informed consent. Along with this family, 14 other index cases with family history of breast cancer were also recruited. For the control populations we recruited 48 healthy women with no cancer diagnosis and 48 women diagnosed with sporadic breast cancer without family history. Genomic DNA was extracted from peripheral blood. All BRCA2 exons were amplified by PCR and sequenced. Sequences were compared to the BRCA2 GenBank reference sequence (NM_000059.3) using Alamut Software.

Results

We identified a novel nonsense pathogenic variant c.5219 T > G; p.(Leu1740Ter) in exon 11 of BRCA2 in the index case. The pathogenic variant was also identified in three sisters and one daughter, but was absent in the controls and unrelated cases.

Conclusions

This is the first report of a novel BRCA2 pathogenic variant in a Senegalese family with hereditary breast cancer. This result confirms the diversity of hereditary breast cancer pathogenic variants across populations and extends our knowledge of genetic susceptibility to breast cancer in Africa.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0814-y) contains supplementary material, which is available to authorized users.

Prédisposition héréditaire au cancer du sein (2)

Les progrès du séquençage à haut débit permettent de rechercher simultanément des mutations sur plusieurs gènes pour explorer la prédisposition héréditaire au cancer du sein. Selon le gène, le niveau de risque et le spectre des cancers peuvent varier. Les dispositions spécifiques de prise en charge préconisées sont modulées en fonction des gènes, classés en : (1) très haut risque, tels les gènes BRCA1/2 suivant les recommandations de l’INCa 2017 ; (2) risque élevé ; (3) augmentation modérée : dans ce dernier cas, les mesures de surveillance sont similaires à la population générale. En l’absence de mutation, d’autres facteurs de risque peuvent intervenir et des scores professionnels être calculés. Cependant, selon les recommandations de la HAS 2014, l’histoire familiale prévaut : sur cette base, le dispositif national d’oncogénétique de l’INCa a mis en place un maillage national de réseaux de suivi des personnes à haut risque, présentant ou non des mutations. Enfin, de nouvelles voies thérapeutiques spécifiques s’ouvrent pour les personnes porteuses de mutations.

Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study

Background

The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers.

Methods

We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically).

Results

From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33–1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57–0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15–0.97; combined HR = 0.29; 95% CI = 0.23–0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age.

Conclusion

Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1135-y) contains supplementary material, which is available to authorized users.

Current knowledge of risk reducing mastectomy: Indications, techniques, results, benefits, harms

The last twenty years have seen a complete change in society's attitude to the strategy of risk reduction of breast cancer in high-risk individuals by means of proactive mastectomy. Once termed 'prophylactic mastectomy', risk reducing mastectomy (RRM) was considered two decades ago not only extreme, but in some quarters almost unethical. RRM is now commonly undertaken in specialist breast units for women at high individual breast cancer risk, by virtue of an inherited breast cancer related gene mutation or from calculated high statistical risk from family history data, and the efficacy of RRM in reducing subsequent incident diagnoses of breast cancer has been published from a number of centres. RRM is offered routinely in conjunction with total breast reconstruction, using the whole range of reconstructive surgical techniques. The public announcement by the actor Angelina Jolie in 2013 that she had inherited and harboured a BRCA1 gene mutation, and was undergoing RRM and breast reconstruction to lower her intrinsic breast cancer risk, had a significant effect on public attitudes and perception. Whilst there are other means of lowering breast cancer risk by means of selective oestrogen receptor modulators, such as tamoxifen and raloxifene, their lowering effect on risk of breast cancer remains substantially less than that afforded by surgical removal of 'at risk' breast tissue. The progressive development and increasing sophistication of techniques of breast reconstructive surgery has paralleled the trend for more RRM surgery, and the substantial majority of women who opt for RRM choose immediate breast reconstruction.

Information and support needs of young women regarding breast cancer risk and genetic testing: adapting effective interventions for a novel population

Young women from hereditary breast and ovarian cancer (HBOC) families face a unique set of challenges in managing their HBOC risk, where obtaining essential information to inform decision making is key. Previous work suggests that this need for specific health information also comes at a time of heightened distress and greater individuation from family. In this report, we describe our adaptation of a previously-studied behavioral intervention for this population, utilizing a systematic approach outlined by the Centers for Disease Control and Prevention. First, we assessed the information needs and levels of distress in this population and correlates of this distress. These data then were used to inform the adaptation and piloting of a three-session telephone-based peer coaching intervention. One hundred young women (M age = 25 years) who were first or second degree relatives of BRCA1/2 mutation carriers participated. Sixty-three percent of the sample endorsed unmet HBOC information needs and they, on average, reported moderate levels of cancer-related distress (M = 21.9, SD = 14.6). Greater familial disruption was associated with greater cancer-related distress in multivariable models (p < .05). Ten women who participated in the survey completed the intervention pilot. They reported lower distress from pre- to post- (15.8 vs. 12.0), as well as significantly lower decisional conflict (p < .05) and greater endorsement of an array of healthy coping strategies (i.e., active coping, instrumental coping, positive reframing, planning, p's < .05). Our survey results suggest that young adult women from HBOC families have unmet cancer genetic information and support needs. Our pilot intervention was able to reduce levels of decisional conflict and promote the use of effective coping strategies. This approach needs to be further tested in a larger randomized trial.

Role of elastography for downgrading BI-RADS category 4a breast lesions according to risk factors

BACKGROUND

Elastography has been introduced as an additional diagnostic tool to ultrasonography (US) which helps clinicians decide whether or not to perform biopsy on US-detected lesions.

PURPOSE

To evaluate the role of strain elastography in downgrading Breast Imaging Reporting and Data System (BI-RADS) category 4a breast lesions according to personal risk factors for breast cancer in asymptomatic women.

MATERIAL AND METHODS

Strain elastography features of a total of 255 asymptomatic category 4a lesions were classified as soft and not soft (intermediate and hard). Malignancy was confirmed by surgery or biopsy, and benignity was confirmed by surgery or biopsy with no change on US for at least six months. Malignancy rates of lesions with soft and not soft elastography were calculated according to the presence of risk factors.

RESULTS

Of 255 lesions, 25 (9.8%) were malignant and 230 (90.2%) were benign. Of 195 lesions in average-risk women, the malignancy rate of lesions with soft elastography was 1.5% (1/68), which was significantly lower than the 14.2% (18/127) of lesions with not soft elastography ( P = 0.004). Of 60 lesions in increased-risk women, the malignancy rate of lesions with soft elastography was 15.0% (3/20), which was not significantly different from the 7.5% (3/40) of lesions with not soft elastography ( P = 0.390).

CONCLUSION

In average-risk women, category 4a lesions with soft elastography could be followed up with US because of a low malignancy rate of 1.5%.

Benign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort

Benign breast disease (BBD) is an established breast cancer (BC) risk factor, but it is unclear whether the magnitude of the association applies to women at familial or genetic risk. This information is needed to improve BC risk assessment in clinical settings. Using the Prospective Family Study Cohort, we used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of BBD with BC risk. We also examined whether the association with BBD differed by underlying familial risk profile (FRP), calculated using absolute risk estimates from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. During 176,756 person-years of follow-up (median: 10.9 years, maximum: 23.7) of 17,154 women unaffected with BC at baseline, we observed 968 incident cases of BC. A total of 4,704 (27%) women reported a history of BBD diagnosis at baseline. A history of BBD was associated with a greater risk of BC: HR = 1.31 (95% CI: 1.14-1.50), and did not differ by underlying FRP, with HRs of 1.35 (95% CI: 1.11-1.65), 1.26 (95% CI: 1.00-1.60), and 1.40 (95% CI: 1.01-1.93), for categories of full-lifetime BOADICEA score <20%, 20 to <35%, ≥35%, respectively. There was no difference in the association for women with BRCA1 mutations (HR: 1.64; 95% CI: 1.04-2.58), women with BRCA2 mutations (HR: 1.34; 95% CI: 0.78-2.3) or for women without a known BRCA1 or BRCA2 mutation (HR: 1.31; 95% CI: 1.13-1.53) (p_interaction  = 0.95). Women with a history of BBD have an increased risk of BC that is independent of, and multiplies, their underlying familial and genetic risk.

Women's cancers: how the discovery of BRCA genes is driving current concepts of cancer biology and therapeutics

Over the last two decades, discoveries related to the breast cancer susceptibility genes 1 and 2 (BRCA1 and BRCA2) have profoundly changed our understanding and management of hereditary breast and ovarian cancers. The concept of synthetic lethality, which arises when cells become vulnerable to a combination of deficiencies in DNA repair, has driven the expanding roles of poly (adenosine diphosphate (ADP)-ribose) polymerase inhibitors in breast and ovarian cancers, and prevention strategies are taking into account the tissue specificity, natural history (fallopian tube origin of some high-grade serous ovarian cancers) and hormone sensitivity of BRCA-associated cancers. Current research has focussed on further elucidating the roles of BRCA proteins in DNA repair, investigating other key DNA repair processes and proteins and linking aberrant DNA repair with carcinogenesis. The ultimate goal is to translate this evolving knowledge into improving the clinical care and treatment of patients with pathogenic BRCA variants or other deficiencies in homologous recombination (HR). In this review, we will discuss 1) the role of BRCA proteins in DNA repair; 2) emerging concepts in the biology of HR deficiency and 3) implications for prevention and treatment.

Familial recurrence risk with varying amount of family history

The familial recurrence risk is the probability a person will have disease, given a reported family history. When family histories are obtained as simple counts of disease among family members, as often obtained in cancer registries or surveys, we propose methods to estimate recurrence risks based on truncated binomial distributions. By this approach, we are able to obtain unbiased estimates of risk for a person with at least k-affected relatives, where k can be specified to determine how risk varies with k. We also derive robust variances of the recurrence risk estimate, to account for correlations within families, such as those induced by shared genes or shared environment, without explicitly modeling the factors that cause familial correlations. Furthermore, we illustrate how mixture models can be used to account for a sample composed of low- and high-risk families. Using simulations, we illustrate the properties of the proposed methods. Application of our methods to a family history survey of prostate cancer shows that the recurrence risk for prostate cancer increased from 16%, when there was at least one affected relative, to 52%, when there was at least five affected relatives.

Enhancer Domains in Gastrointestinal Stromal Tumor Regulate KIT Expression and Are Targetable by BET Bromodomain Inhibition

Gastrointestinal stromal tumor (GIST) is a mesenchymal neoplasm characterized by activating mutations in the related receptor tyrosine kinases KIT and PDGFRA. GIST relies on expression of these unamplified receptor tyrosine kinase (RTK) genes through a large enhancer domain, resulting in high expression levels of the oncogene required for tumor growth. Although kinase inhibition is an effective therapy for many patients with GIST, disease progression from kinase-resistant mutations is common and no other effective classes of systemic therapy exist. In this study, we identify regulatory regions of the KIT enhancer essential for KIT gene expression and GIST cell viability. Given the dependence of GIST upon enhancer-driven expression of RTKs, we hypothesized that the enhancer domains could be therapeutically targeted by a BET bromodomain inhibitor (BBI). Treatment of GIST cells with BBIs led to cell-cycle arrest, apoptosis, and cell death, with unique sensitivity in GIST cells arising from attenuation of the KIT enhancer domain and reduced KIT gene expression. BBI treatment in KIT-dependent GIST cells produced genome-wide changes in the H3K27ac enhancer landscape and gene expression program, which was also seen with direct KIT inhibition using a tyrosine kinase inhibitor (TKI). Combination treatment with BBI and TKI led to superior cytotoxic effects in vitro and in vivo, with BBI preventing tumor growth in TKI-resistant xenografts. Resistance to select BBI in GIST was attributable to drug efflux pumps. These results define a therapeutic vulnerability and clinical strategy for targeting oncogenic kinase dependency in GIST. SIGNIFICANCE: Expression and activity of mutant KIT is essential for driving the majority of GIST neoplasms, which can be therapeutically targeted using BET bromodomain inhibitors.

SEMIPARAMETRIC TRANSFORMATION MODELS WITH MULTILEVEL RANDOM EFFECTS FOR CORRELATED DISEASE ONSET IN FAMILIES

Large cohort studies are commonly launched to study risk of genetic variants or other risk factors on age at onset (AAO) of a chronic disorder. In these studies, family history data including AAO of disease in family members are collected to provide additional information and can be used to improve efficiency. Statistical analysis of these data is challenging due to missing genotypes in family members and the heterogeneous dependence attributed to both shared genetic back-ground and shared environmental factors (e.g., life style). In this paper, we propose a class of semiparametric transformation models with multilevel random effects to tackle these challenges. The proposed models include both proportional hazards model and proportional odds model as special cases. The multilevel random effects contain individual-specific random effects including kinship correlation structure dependent on the family pedigree, and a shared random effect to account for unobserved environment exposure. We use nonparametric maximum likelihood approach for inference and propose an expectation-maximization algorithm for computation in the presence of missing genotypes among family members. The obtained estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient. Simulation studies demonstrate that the proposed method performs well with finite sample sizes. Finally, the proposed method is applied to study genetic risks in an Alzheimer's disease study.

Inclusion of Plasma Prolactin Levels in Current Risk Prediction Models of Premenopausal and Postmenopausal Breast Cancer

Background

Circulating plasma prolactin is associated with breast cancer risk and may improve our ability to identify high-risk women. Mammographic density is a strong risk factor for breast cancer, but the association with prolactin is unclear. We studied the association between breast cancer, established breast cancer risk factors and plasma prolactin, and improvement of risk prediction by adding prolactin.

Methods

We conducted a nested case-control study including 721 breast cancer patients and 1400 age-matched controls. Plasma prolactin levels were assayed using immunoassay and mammographic density measured by STRATUS. Odds ratios (ORs) were calculated by multivariable adjusted logistic regression, and improvement in the area under the curve for the risk of breast cancer by adding prolactin to established risk models. Statistical tests were two-sided.

Results

In multivariable adjusted analyses, prolactin was associated with risk of premenopausal (OR, top vs bottom quintile = 1.9; 1.88 (95% confidence interval [CI] = 1.08 to 3.26) but not with postmenopausal breast cancer. In postmenopausal cases prolactin increased by 10.6% per cBIRADS category (P_trend = .03). In combined analyses of prolactin and mammographic density, ORs for women in the highest vs lowest tertile of both was 3.2 (95% CI = 1.3 to 7.7) for premenopausal women and 2.44 (95% CI = 1.44 to 4.14) for postmenopausal women. Adding prolactin to current risk models improved the area under the curve of the Gail model (+2.4 units, P = .02), Tyrer-Cuzick model (+3.8, P = .02), and the CAD2Y model (+1.7, P = .008) in premenopausal women.

Conclusion

Circulating plasma prolactin and mammographic density appear independently associated with breast cancer risk among premenopausal women, and prolactin may improve risk prediction by current risk models.

Risks of breast or ovarian cancer in BRCA1 or BRCA2 predictive test negatives: findings from the EMBRACE study

PURPOSE

BRCA1/BRCA2 predictive test negatives are proven noncarriers of a BRCA1/BRCA2 mutation that is carried by their relatives. The risk of developing breast cancer (BC) or epithelial ovarian cancer (EOC) in these women is uncertain. The study aimed to estimate risks of invasive BC and EOC in a large cohort of BRCA1/BRCA2 predictive test negatives.

METHODS

We used cohort analysis to estimate incidences, cumulative risks, and standardized incidence ratios (SIRs).

RESULTS

A total of 1,895 unaffected women were eligible for inclusion in the BC risk analysis and 1,736 in the EOC risk analysis. There were 23 incident invasive BCs and 2 EOCs. The cumulative risk of invasive BC was 9.4% (95% confidence interval (CI) 5.9-15%) by age 85 years and the corresponding risk of EOC was 0.6% (95% CI 0.2-2.6%). The SIR for invasive BC was 0.93 (95% CI 0.62-1.40) in the overall cohort, 0.85 (95% CI 0.48-1.50) in noncarriers from BRCA1 families, and 1.03 (95% CI 0.57-1.87) in noncarriers from BRCA2 families. The SIR for EOC was 0.79 (95% CI 0.20-3.17) in the overall cohort.

CONCLUSION

Our results did not provide evidence for elevated risks of invasive BC or EOC in BRCA1/BRCA2 predictive test negatives.

Non-Coding Variants in BRCA1 and BRCA2 Genes: Potential Impact on Breast and Ovarian Cancer Predisposition

BRCA1 and BRCA2 are major breast cancer susceptibility genes whose pathogenic variants are associated with a significant increase in the risk of breast and ovarian cancers. Current genetic screening is generally limited to BRCA1/2 exons and intron/exon boundaries. Most identified pathogenic variants cause the partial or complete loss of function of the protein. However, it is becoming increasingly clear that variants in these regions only account for a small proportion of cancer risk. The role of variants in non-coding regions beyond splice donor and acceptor sites, including those that have no qualitative effect on the protein, has not been thoroughly investigated. The key transcriptional regulatory elements of BRCA1 and BRCA2 are housed in gene promoters, untranslated regions, introns, and long-range elements. Within these sequences, germline and somatic variants have been described, but the clinical significance of the majority is currently unknown and it remains a significant clinical challenge. This review summarizes the available data on the impact of variants on non-coding regions of BRCA1/2 genes and their role on breast and ovarian cancer predisposition.

Familial breast cancer and DNA repair genes: Insights into known and novel susceptibility genes from the GENESIS study, and implications for multigene panel testing

Pathogenic variants in BRCA1 and BRCA2 only explain the underlying genetic cause of about 10% of hereditary breast and ovarian cancer families. Because of cost‐effectiveness, multigene panel testing is often performed even if the clinical utility of testing most of the genes remains questionable. The purpose of our study was to assess the contribution of rare, deleterious‐predicted variants in DNA repair genes in familial breast cancer (BC) in a well‐characterized and homogeneous population. We analyzed 113 DNA repair genes selected from either an exome sequencing or a candidate gene approach in the GENESIS study, which includes familial BC cases with no BRCA1 or BRCA2 mutation and having a sister with BC (N = 1,207), and general population controls (N = 1,199). Sequencing data were filtered for rare loss‐of‐function variants (LoF) and likely deleterious missense variants (MV). We confirmed associations between LoF and MV in PALB2, ATM and CHEK2 and BC occurrence. We also identified for the first time associations between FANCI, MAST1, POLH and RTEL1 and BC susceptibility. Unlike other associated genes, carriers of an ATM LoF had a significantly higher risk of developing BC than carriers of an ATM MV (OR_LoF = 17.4 vs. OR_MV = 1.6; p_Het = 0.002). Hence, our approach allowed us to specify BC relative risks associated with deleterious‐predicted variants in PALB2, ATM and CHEK2 and to add MAST1, POLH, RTEL1 and FANCI to the list of DNA repair genes possibly involved in BC susceptibility. We also highlight that different types of variants within the same gene can lead to different risk estimates.

What's new?

Pathogenic variants in BRCA1 and BRCA2 only explain the genetic cause of about 10% of hereditary breast and ovarian cancer families, and the clinical usefulness of testing other genes following the recent introduction of cost‐effective multigene panel sequencing in diagnostics laboratories remains questionable. This large case‐control study describes genetic variation in 113 DNA repair genes and specifies breast cancer relative risks associated with rare deleterious‐predicted variants in PALB2, ATM, and CHEK2. Importantly, different types of variants within the same gene can lead to different risk estimates. The results may help improve risk prediction models and define gene‐specific consensus management guidelines.

The iPrevent Online Breast Cancer Risk Assessment and Risk Management Tool: Usability and Acceptability Testing

BACKGROUND

iPrevent estimates breast cancer (BC) risk and provides tailored risk management information.

OBJECTIVE

The objective of this study was to assess the usability and acceptability of the iPrevent prototype.

METHODS

Clinicians were eligible for participation in the study if they worked in primary care, breast surgery, or genetics clinics. Female patients aged 18-70 years with no personal cancer history were eligible. Clinicians were first familiarized with iPrevent using hypothetical paper-based cases and then actor scenarios; subsequently, they used iPrevent with their patients. Clinicians and patients completed the System Usability Scale (SUS) and an Acceptability questionnaire 2 weeks after using iPrevent; patients also completed measures of BC worry, anxiety, risk perception, and knowledge pre- and 2 weeks post-iPrevent. Data were summarized using descriptive statistics.

RESULTS

The SUS and Acceptability questionnaires were completed by 19 of 20 clinicians and 37 of 43 patients. Usability was above average (SUS score >68) for 68% (13/19) clinicians and 76% (28/37) patients. The amount of information provided by iPrevent was reported as "about right" by 89% (17/19) clinicians and 89% (33/37) patients and 95% (18/19) and 97% (36/37), respectively, would recommend iPrevent to others, although 53% (10/19) clinicians and 27% (10/37) patients found it too long. Exploratory analyses suggested that iPrevent could improve risk perception, decrease frequency of BC worry, and enhance BC prevention knowledge without changing state anxiety.

CONCLUSIONS

The iPrevent prototype demonstrated good usability and acceptability. Because concerns about length could be an implementation barrier, data entry has been abbreviated in the publicly available version of iPrevent.

Consumer and clinician perspectives on personalising breast cancer prevention information

BACKGROUND

Personalised prevention of breast cancer has focused on women at very high risk, yet most breast cancers occur in women at average, or moderately increased risk (≤moderate risk).

OBJECTIVES

To determine; 1) interest of women at ≤ moderate risk (consumers) in personalised information about breast cancer risk; 2) familial cancer clinicians' (FCCs) perspective on managing women at ≤ moderate risk, and; 3) both consumers' and FCCs reactions to iPrevent, a personalised breast cancer risk assessment and risk management decision support tool.

METHODS

Seven focus groups on breast cancer risk were conducted with 49 participants; 27 consumers and 22 FCCs. Data were analysed thematically.

RESULTS

Consumers reported some misconceptions, low trust in primary care practitioners for breast cancer prevention advice and frustration that they often lacked tailored advice about breast cancer risk. They expressed interest in receiving personalised risk information using iPrevent. FCCs reported an inadequate workforce to advise women at ≤ moderate risk and reacted positively to the potential of iPrevent to assist.

CONCLUSIONS

While highlighting a potential role for iPrevent, several outstanding issues remain. For personalised prevention of breast cancer to extend beyond women at high risk, we must harness women's interest in receiving tailored information about breast cancer prevention and identify a workforce willing to advise women.

Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC)

BACKGROUND

The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk.

METHODS

We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline.

RESULTS

The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk.

CONCLUSIONS

The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.

The 10th Oxbridge varsity medical ethics debate-should we fear the rise of direct-to-consumer genetic testing?

In an increasingly data-driven age of medicine, do companies that offer genetic testing directly to patients represent an important part of personalising care, or a dangerous threat to privacy? Should we celebrate this new mechanism of patient involvement, or fear its implications?The Universities of Oxford and Cambridge addressed these issues in the 10th annual Medical Ethics Varsity Debate, through the motion: "This House Regrets the Rise of Direct-to-Consumer Genetic Testing". This article summarises and extends key arguments made in the debate, exploring the impacts of such genetic testing on both the individual patient and broader society, with special consideration as to whether companies can ever truly guarantee anonymity of genetic data.

Review of non-clinical risk models to aid prevention of breast cancer

A disease risk model is a statistical method which assesses the probability that an individual will develop one or more diseases within a stated period of time. Such models take into account the presence or absence of specific epidemiological risk factors associated with the disease and thereby potentially identify individuals at higher risk. Such models are currently used clinically to identify people at higher risk, including identifying women who are at increased risk of developing breast cancer. Many genetic and non-genetic breast cancer risk models have been developed previously. We have evaluated existing non-genetic/non-clinical models for breast cancer that incorporate modifiable risk factors. This review focuses on risk models that can be used by women themselves in the community in the absence of clinical risk factors characterization. The inclusion of modifiable factors in these models means that they can be used to improve primary prevention and health education pertinent for breast cancer. Literature searches were conducted using PubMed, ScienceDirect and the Cochrane Database of Systematic Reviews. Fourteen studies were eligible for review with sample sizes ranging from 654 to 248,407 participants. All models reviewed had acceptable calibration measures, with expected/observed (E/O) ratios ranging from 0.79 to 1.17. However, discrimination measures were variable across studies with concordance statistics (C-statistics) ranging from 0.56 to 0.89. We conclude that breast cancer risk models that include modifiable risk factors have been well calibrated but have less ability to discriminate. The latter may be a consequence of the omission of some significant risk factors in the models or from applying models to studies with limited sample sizes. More importantly, external validation is missing for most of the models. Generalization across models is also problematic as some variables may not be considered applicable to some populations and each model performance is conditioned by particular population characteristics. In conclusion, it is clear that there is still a need to develop a more reliable model for estimating breast cancer risk which has a good calibration, ability to accurately discriminate high risk and with better generalizability across populations.

Population-based genetic testing of asymptomatic women for breast and ovarian cancer susceptibility

PURPOSE

The identification of carriers of hereditary breast and ovarian cancer (HBOC) gene variants through family cancer history alone is suboptimal, and most population-based genetic testing studies have been limited to founder mutations in high-risk populations. Here, we determine the clinical utility of identifying actionable variants in a healthy cohort of women.

METHODS

Germline DNA from a subset of healthy Australian women participating in the lifepool project was screened using an 11-gene custom sequencing panel. Women with clinically actionable results were invited to attend a familial cancer clinic (FCC) for post-test genetic counseling and confirmatory testing. Outcomes measured included the prevalence of pathogenic variants, and the uptake rate of genetic counseling, risk reduction surgery, and cascade testing.

RESULTS

Thirty-eight of 5908 women (0.64%) carried a clinically actionable pathogenic variant. Forty-two percent of pathogenic variant carriers did not have a first-degree relative with breast or ovarian cancer and 89% pursued referral to an FCC. Forty-six percent (6/13) of eligible women pursued risk reduction surgery, and the uptake rate of cascade testing averaged 3.3 family members per index case.

CONCLUSION

Within our cohort, HBOC genetic testing was well accepted, and the majority of high-risk gene carriers identified would not meet eligibility criteria for genetic testing based on their existing family history.

Efficient computation of the joint probability of multiple inherited risk alleles from pedigree data

The Elston-Stewart peeling algorithm enables estimation of an individual's probability of harboring germline risk alleles based on pedigree data, and serves as the computational backbone of important genetic counseling tools. However, it remains limited to the analysis of risk alleles at a small number of genetic loci because its computing time grows exponentially with the number of loci considered. We propose a novel, approximate version of this algorithm, dubbed the peeling and paring algorithm, which scales polynomially in the number of loci. This allows extending peeling-based models to include many genetic loci. The algorithm creates a trade-off between accuracy and speed, and allows the user to control this trade-off. We provide exact bounds on the approximation error and evaluate it in realistic simulations. Results show that the loss of accuracy due to the approximation is negligible in important applications. This algorithm will improve genetic counseling tools by increasing the number of pathogenic risk alleles that can be addressed. To illustrate we create an extended five genes version of BRCAPRO, a widely used model for estimating the carrier probabilities of BRCA1 and BRCA2 risk alleles and assess its computational properties.

Current detection rates and time-to-detection of all identifiable BRCA carriers in the Greater London population

BACKGROUND

BRCA carrier identification offers opportunities for early diagnoses, targeted treatment and cancer prevention. We evaluate BRCA- carrier detection rates in general and Ashkenazi Jewish (AJ) populations across Greater London and estimate time-to-detection of all identifiable BRCA carriers.

METHODS

BRCA carrier data from 1993 to 2014 were obtained from National Health Service genetic laboratories and compared with modelled predictions of BRCA prevalence from published literature and geographical data from UK Office for National Statistics. Proportion of BRCA carriers identified was estimated. Prediction models were developed to fit BRCA detection rate data. BRCA carrier identification rates were evaluated for an 'Angelina Jolie effect'. Maps for four Greater London regions were constructed, and their relative BRCA detection rates were compared. Models developed were used to predict future time-to-identify all detectable BRCA carriers in AJ and general populations.

RESULTS

Until 2014, only 2.6% (3072/111 742 estimated) general population and 10.9% (548/4985 estimated) AJ population BRCA carriers have been identified in 16 696 608 (AJ=190 997) Greater London population. 57% general population and 54% AJ mutations were identified through cascade testing. Current detection rates mirror linear fit rather than parabolic model and will not identify all BRCA carriers. Addition of unselected ovarian/triple-negative breast cancer testing would take >250 years to identify all BRCA carriers. Doubling current detection rates can identify all 'detectable' BRCA carriers in the general population by year 2181, while parabolic and triple linear rates can identify 'detectable' BRCA carriers by 2084 and 2093, respectively. The linear fit model can identify 'detectable' AJ carriers by 2044. We did not find an Angelina Jolie effect on BRCA carrier detection rates. There was a significant difference in BRCA detection rates between geographical regions over time (P<0.001).

CONCLUSIONS

The majority of BRCA carriers have not been identified, missing key opportunities for prevention/earlier diagnosis. Enhanced and new strategies/approaches are needed.

Cost-effectiveness of Population-Based BRCA1, BRCA2, RAD51C, RAD51D, BRIP1, PALB2 Mutation Testing in Unselected General Population Women

Background

The cost-effectiveness of population-based panel testing for high- and moderate-penetrance ovarian cancer (OC)/breast cancer (BC) gene mutations is unknown. We evaluate the cost-effectiveness of population-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 mutation testing compared with clinical criteria/family history (FH) testing in unselected general population women.

Methods

A decision-analytic model comparing lifetime costs and effects of criteria/FH-based BRCA1/BRCA2 testing is compared with BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 testing in those fulfilling clinical criteria/strong FH of cancer (≥10% BRCA1/BRCA2 probability) and all women age 30 years or older. Analyses are presented for UK and US populations. Identified carriers undergo risk-reducing salpingo-oophorectomy. BRCA1/BRCA2/PALB2 carriers can opt for magnetic resonance imaging/mammography, chemoprevention, or risk-reducing mastectomy. One-way and probabilistic sensitivity analysis (PSA) enabled model uncertainty evaluation. Outcomes include OC, BC, and additional heart disease deaths. Quality-adjusted life-years (QALYs), OC incidence, BC incidence, and incremental cost-effectiveness ratio (ICER) were calculated. The time horizon is lifetime and perspective is payer.

Results

Compared with clinical criteria/FH-based BRCA1/BRCA2 testing, clinical criteria/FH-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 testing is cost-effective (ICER = £7629.65/QALY or $49 282.19/QALY; 0.04 days' life-expectancy gained). Population-based testing for BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 mutations is the most cost-effective strategy compared with current policy: ICER = £21 599.96/QALY or $54 769.78/QALY (9.34 or 7.57 days' life-expectancy gained). At £30 000/QALY and $100 000/QALY willingness-to-pay thresholds, population-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 panel testing is the preferred strategy in 83.7% and 92.7% of PSA simulations; criteria/FH-based panel testing is preferred in 16.2% and 5.8% of simulations, respectively. Population-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 testing can prevent 1.86%/1.91% of BC and 3.2%/4.88% of OC in UK/US women: 657/655 OC cases and 2420/2386 BC cases prevented per million.

Conclusions

Population-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 testing is more cost-effective than any clinical criteria/FH-based strategy. Clinical criteria/FH-based BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 testing is more cost-effective than BRCA1/BRCA2 testing alone.