Sharon Sand

Validity of Models for Predicting BRCA1 and BRCA2 Mutations

Context A computer software program from the University of Texas Southwestern Medical Center (CaGene) has multiple prediction models to estimate BRCA1 and BRCA2 mutation probability, which guides decisions on whether to test for a mutation. A comprehensive quantitative evaluation of how well the prediction models discriminate between persons who carry the mutation and those who do not is lacking. Contribution The authors used 7 prediction models to estimate the probability of a BRCA1/BRCA2 mutation in 3342 families. All 7 models were able to discriminate between mutation-positive and mutation-negative people. Implications The probability that someone carries the BRCA1/BRCA2 mutation should not be considered in isolation when decisions are being made about genetic testing. Other factors should be discussed with the patient and factored into the decision-making process. The Editors Deleterious mutations of BRCA1 (MIM 113705) and BRCA2 (MIM 600185) increase the risk for breast and ovarian cancer (13). Whereas deleterious variants are relatively rare in the general population, they are common among families with multiple occurrences of breast or ovarian cancer (46). When counseling a woman facing decisions about genotyping for BRCA1 and BRCA2, it is important to accurately evaluate the probability that she carries a deleterious mutation (pretest mutation probability) and the probability that a mutation will be found if she is genotyped (which depends on the accuracy of mutation testing). Reliable, evidence-based, individualized counseling strategies can enhance informed decision making, both about whether to pursue BRCA1/BRCA2 testing and what to do with the results (79). The demand for assessment of complex family histories of cancer has led to widespread use of statistical models to estimate mutation probabilities (2, 1018). Model-based predictions are currently used in counseling about genetic testing, are included in materials distributed to women considering genetic testing (1821), are used for determining eligibility for screening and prevention studies (22), and are factored into coverage decisions by insurers (23). More than a dozen models exist. They use different statistical methods and source populations, pedigree features, and predicted outcomes. In clinical practice, different models applied to the same person can give a wide range of probabilities that a BRCA1/BRCA2 mutation is present. This degree of variability raises concerns about whether some models are more accurate than others and calls for a careful independent comparative evaluation of the predictive performance of existing models. We assessed the validity of commonly used models for estimating mutation probabilities of BRCA1 and BRCA2 in individuals identified through the Cancer Genetics Network. We assembled a large set of families with history of breast cancer, ovarian cancer, or both. We used standardized computational methods across contributing institutions to evaluate 7 models. Our main goal was to measure how well these models discriminated between mutation carriers and noncarriers. Methods Study Overview We conducted a cross-sectional, multicenter analysis. For each family in the study, we identified an individual (the counselee) for whom we collected genetic test results for BRCA1, BRCA2, or both; genotyping methods; pretest estimations of mutation probability using each model; and additional information about family history of cancer. We used genetic test results as the gold standard for judging the sensitivity and specificity of the various models. We evaluated all models on every counselee, except where noted. Data Collection Table 1 summarizes the salient data (2432). Sources include 3 population-based studies and 8 data sets of individuals seen in clinics for women at high risk for a BRCA mutation. In the population-based studies, the participants reflected the demographic characteristics of a defined subpopulation (for example, all breast cancer cases in Orange County in the University of California, Irvine [UCI], study [31]). In contrast, patients from high-risk clinics had been referred because of a family history of cancer or were self-referred because of an interest in genetic testing (inclusion criteria varied across clinics). Table 1. Demographic Characteristics of Counselees and Sample Size, by Center Each center calculated all of the model probabilities for its own families. We designated the first genotyped person in each family as the counselee and computed predictions by using the genetic counseling software CaGene (University of Texas Southwestern Medical Center, Dallas, Texas) (24). The software version was customized and distributed to participating sites to ensure uniform procedures across all sites. Data entry and computation of model predictions were performed at the sites. This decentralized approach for data entry and probability calculations allowed site investigators to use pedigree information that models required but that centers could not export to a central site because of privacy concerns. In addition to model predictions, a subset of centers also exported the data required for the models to the National Cancer Institutes (NCI) Cancer Genetics Network Data Coordinating Center. The study population includes 3342 families. The institutional review boards at each participating institution approved the study protocol. All included counselees gave consent for using their data for research according to local institutional review board requirements. The Cancer Genetics Network steering committee reviewed the study design. Genetic Testing Appendix Table 1 summarizes genotyping methods by center and provides a brief description of each method. Determining whether a person carries a deleterious mutation of BRCA1 or BRCA2 is technically demanding because of the large size of these genes, the wide spectrum of mutations, and the presence of mutations whose clinical significance is unknown (3335). Commercial testing uses sequencing to search for unknown mutations or to probe for mutations that are commonly found among Ashkenazi Jewish persons. Research settings, particularly in the time in which the study was conducted, have used less expensive and less sensitive techniques (Appendix Table 1). Although sequencing is the most sensitive of the techniques used in our study, recent evidence highlights how it can miss certain mutations, such as large deletions or intronic mutations (3, 36). Therefore, the set of individuals carrying a mutation (the carriers) is not the same as the set of individuals who test positive for a mutation (the positive cases). Thus, Table 1 underestimates the true number of carriers; the size of the error varies according to the method of genotyping. Appendix Table 1. Number of Counselees, by Genotyping Method for Each Gene and Center Models We studied 7 models: BRCAPRO, the family history assessment tool (FHAT), Finnish, Myriad, NCI, University of Pennsylvania (Penn), and Yale University (Yale). Appendix Table 2 summarizes the characteristics, input variables, and output of the models. Three broad categories of models have been proposed: empirical (Finnish, Myriad, NCI, and Penn), mendelian (BRCAPRO and Yale), and expert-based (FHAT). The first step in developing an empirical model is to summarize the salient aspects of a family history in some predictor variables. The second step is to apply statistical learning techniques, such as logistic regression, to describe the relationship between these variables and the genotyping results (the dependent variable). Mendelian models represent the known modes of inheritance of deleterious genetic variants by established mathematical relationships between phenotypes (in this case, cancer status of family members) and genotypes (14, 3741). The mendelian model inputs include cancer incidence curves (penetrance) for both carriers and noncarriers and the prevalence of deleterious variants. Expert-based models calculate scores that summarize degree of risk, using algorithms constructed on the basis of clinical judgment. For example, FHAT (16) uses a 17-question interview to produce a quantitative score (score range, 0 to 45) representing the severity of family history. Appendix Table 2. Input Variables and Features of Each Model Empirical models calculate the probability of a positive test result for a mutation in the counselee (that is, the result of genetic testing), whereas mendelian models directly estimate the probability of carrying a mutation (the true mutation status of the counselee) (37). The 2 types of predictions are therefore not directly comparable, a fact often overlooked in counseling practice. Because genotyping methods are highly specific for the BRCA1 and BRCA2 genes (that is, they have a very low false-positive rate), multiplying the genotype probability by the genotyping sensitivity gives the probability of finding a mutation. Therefore, to compare an empirical model probability of a BRCA mutation with a mendelian model probability, one must know the sensitivity of the genotyping method of the study used to develop the empirical model. Expert-based scores do not have a direct probabilistic interpretation. In our analyses, we rescaled the FHAT score by dividing by its maximum value of 45. The Penn model (11) estimates the probability of a positive BRCA1 test result in any family member. We adapted it to provide the probability of a positive test in the counselee. We assigned affected counselees the same mutation probability as the family. We assigned unaffected counselees one half the family probability if the closest affected relative of the counselee is a first-degree relative and one quarter of the family probability if the closest relative is a second-degree relative. We used a version of the BRCAPRO (13, 14) model based on the genetic variables described by Iversen and colleagues (42). We defined the Yale model by postulating a si

Prevalence and Type of BRCA Mutations in Hispanics Undergoing Genetic Cancer Risk Assessment in the Southwestern United States: A Report From the Clinical Cancer Genetics Community Research Network

PURPOSE To determine the prevalence and type of BRCA1 and BRCA2 (BRCA) mutations among Hispanics in the Southwestern United States and their potential impact on genetic cancer risk assessment (GCRA). PATIENTS AND METHODS Hispanics (n = 746) with a personal or family history of breast and/or ovarian cancer were enrolled in an institutional review board-approved registry and received GCRA and BRCA testing within a consortium of 14 clinics. Population-based Hispanic breast cancer cases (n = 492) enrolled in the Northern California Breast Cancer Family Registry, negative by sequencing for BRCA mutations, were analyzed for the presence of the BRCA1 ex9-12del large rearrangement. RESULTS Deleterious BRCA mutations were detected in 189 (25%) of 746 familial clinic patients (124 BRCA1, 65 BRCA2); 21 (11%) of 189 were large rearrangement mutations, of which 62% (13 of 21) were BRCA1 ex9-12del. Nine recurrent mutations accounted for 53% of the total. Among these, BRCA1 ex9-12del seems to be a Mexican founder mutation and represents 10% to 12% of all BRCA1 mutations in clinic- and population-based cohorts in the United States. CONCLUSION BRCA mutations were prevalent in the largest study of Hispanic breast and/or ovarian cancer families in the United States to date, and a significant proportion were large rearrangement mutations. The high frequency of large rearrangement mutations warrants screening in every case. We document the first Mexican founder mutation (BRCA1 ex9-12del), which, along with other recurrent mutations, suggests the potential for a cost-effective panel approach to ancestry-informed GCRA.

A KRAS variant is a biomarker of poor outcome, platinum chemotherapy resistance and a potential target for therapy in ovarian cancer

Germline variants in the 3′ untranslated region (3′UTR) of cancer genes disrupting microRNA (miRNA) regulation have recently been associated with cancer risk. A variant in the 3′UTR of the KRAS oncogene, referred to as the KRAS variant, is associated with both cancer risk and altered tumor biology. Here, we test the hypothesis that the KRAS variant can act as a biomarker of outcome in epithelial ovarian cancer (EOC), and investigate the cause of altered outcome in KRAS variant-positive EOC patients. As this variant seems to be associated with tumor biology, we additionally test the hypothesis that this variant can be directly targeted to impact cell survival. EOC patients with complete clinical data were genotyped for the KRAS variant and analyzed for outcome (n=536), response to neoadjuvant chemotherapy (n=125) and platinum resistance (n=306). Outcome was separately analyzed for women with known BRCA mutations (n=79). Gene expression was analyzed on a subset of tumors with available tissue. Cell lines were used to confirm altered sensitivity to chemotherapy associated with the KRAS variant. Finally, the KRAS variant was directly targeted through small-interfering RNA/miRNA oligonucleotides in cell lines and survival was measured. Postmenopausal EOC patients with the KRAS variant were significantly more likely to die of ovarian cancer by multivariate analysis (hazard ratio=1.67, 95% confidence interval: 1.09–2.57, P=0.019, n=279). Perhaps explaining this finding, EOC patients with the KRAS variant were significantly more likely to be platinum resistant (odds ratio=3.18, confidence interval: 1.31–7.72, P=0.0106, n=291). In addition, direct targeting of the KRAS variant led to a significant reduction in EOC cell growth and survival in vitro. These findings confirm the importance of the KRAS variant in EOC, and indicate that the KRAS variant is a biomarker of poor outcome in EOC likely due to platinum resistance. In addition, this study supports the hypothesis that these tumors have continued dependence on such 3′UTR lesions, and that direct targeting may be a viable future treatment approach.

Health literacy, numeracy, and interpretation of graphical breast cancer risk estimates

OBJECTIVE Health literacy and numeracy are necessary to understand health information and to make informed medical decisions. This study explored the relationships among health literacy, numeracy, and ability to accurately interpret graphical representations of breast cancer risk. METHODS Participants (N=120) were recruited from the Facing Our Risk of Cancer Empowered (FORCE) membership. Health literacy and numeracy were assessed. Participants interpreted graphs depicting breast cancer risk, made hypothetical treatment decisions, and rated preference of graphs. RESULTS Most participants were Caucasian (98%) and had completed at least one year of college (93%). Fifty-two percent had breast cancer, 86% had a family history of breast cancer, and 57% had a deleterious BRCA gene mutation. Mean health literacy score was 65/66; mean numeracy score was 4/6; and mean graphicacy score was 9/12. Education and numeracy were significantly associated with accurate graph interpretation (r=0.42, p<0.001 and r=0.65, p<0.001, respectively). However, after adjusting for numeracy in multivariate linear regression, education added little to the prediction of graphicacy (r(2)=0.41 versus 0.42, respectively). CONCLUSION In our highly health-literate population, numeracy was predictive of graphicacy. PRACTICE IMPLICATIONS Effective risk communication strategies should consider the impact of numeracy on graphicacy and patient understanding.

Clinical characteristics and outcomes of BRCA-associated ovarian cancer: genotype and survival

Previous studies have suggested that BRCA-related epithelial ovarian cancer (EOC) conveys improved survival compared with that of sporadic EOC, but few studies have evaluated differences between BRCA genotypes. We compared characteristics and outcome by genotype in BRCA-associated EOC. Patients with BRCA-associated EOC who were diagnosed between January 30,1981, and December 30, 2008, were retrospectively identified through institutional review board-approved registry studies. We examined clinical characteristics, including event-free survival (EFS) and overall survival (OS), for BRCA1 versus BRCA2 patients. We identified 197 cases (148 BRCA1 cases; 49 BRCA2 cases); the median follow-up period was 63 months. BRCA2 patients were older (55.4 vs. 51.1 y; P < 0.01) and had fewer poorly differentiated tumors (67% vs. 82%; P < 0.05). No difference in EFS was observed. OS at 5 years was 75% in BRCA2 patients versus 61% in BRCA1 patients; this was not statistically significant. A non-significant trend toward improved OS was observed in BRCA2 patients with advanced-stage disease (hazard ratio = 0.59; 95% confidence interval 0.32-1.08). Age and grade differed significantly between BRCA1 and BRCA2 carriers in our study population. Whereas no overall differences in EFS or OS were observed, there was a trend toward improved OS in BRCA2 carriers with advanced-stage disease. This may reflect important differences between BRCA genotypes and should be validated in larger studies.

Outcomes from intensive training in genetic cancer risk counseling for clinicians

Purpose: Genetic cancer risk assessment is an emerging interdisciplinary practice that requires knowledge of genetics and oncology and specialized patient and family counseling skills. There is a growing need for cancer risk assessment practitioners, but most clinicians have inadequate cross-disciplinary training. An interdisciplinary course was developed to promote practitioner-level competency in cancer risk assessment to community-based clinicians.Methods: Participants were competitively selected from a pool of board-certified/eligible genetic counseling, masters-trained advanced practice nursing and physician applicants. Preference was given to clinicians with strong institutional backing practicing in underserved regions. The Continuing Medical Education/Continuing Education Unit-accredited course included didactic lectures, workshops, counseling practicum, and case conferences. Pre- and postcourse knowledge tests measured cancer genetics knowledge. Six month and one-year postcourse practice outcome surveys measured the impact of the program on professional self-efficacy and continued professional development.Results/Conclusions: Forty clinicians completed the course (23 genetic counselors, 14 nurses, and three physicians). There was a significant overall increase of 22.6% in postcourse knowledge scores (P < 0.001). Thirty-five (88%) completed prescribed practice development activities. Of 29 respondents to 1-year postcourse survey, 76% reported increased professional self-efficacy; 66% reported increase in number of patients seen, and virtually all indicated interest in additional training. Outcomes demonstrate the value and efficacy of interdisciplinary training in genetic cancer risk assessment targeted to motivated community-based clinicians. Courses such as this can help address the need for competent cancer risk assessment services in communities outside the academic health center.

Effects of a cancer genetics education programme on clinician knowledge and practice

Background: Many clinicians lack adequate knowledge about emerging standards of care related to genetic cancer risk assessment and the features of hereditary cancer needed to identify patients at risk. Objective: To determine how a clinical cancer genetics education programme for community based clinicians affected participant knowledge and changed clinical practice. Methods: The effects of the programme on participant knowledge and changes in clinical practice were measured through pre and post session knowledge questionnaires completed by 710 participants and practice impact surveys completed after one year by 69 out of 114 eligible annual conference participants sampled. Results: Respondents showed a 40% average increase in specific cancer genetics knowledge. Respondents to the post course survey reported that they used course information and materials to counsel and refer patients for hereditary cancer risk assessment (77%), shared course information with other clinicians (83%), and wanted additional cancer genetics education (80%). Conclusions: There was a significant immediate gain in cancer genetics knowledge among participants in a targeted outreach programme, and subset analysis indicated a positive long term effect on clinical practice. Clinician education that incorporates evidence based content and case based learning should lead to better identification and care of individuals with increased cancer risk.

The KRAS-Variant Is Associated with Risk of Developing Double Primary Breast and Ovarian Cancer

Purpose A germline microRNA binding site-disrupting variant, the KRAS-variant (rs61764370), is associated with an increased risk of developing several cancers. Because this variant is most strongly associated with ovarian cancer risk in patients from hereditary breast and ovarian families (HBOC), and with the risk of premenopausal triple negative breast cancer, we evaluated the association of the KRAS-variant with women with personal histories of both breast and ovarian cancer, referred to as double primary patients. Experimental Design Germline DNA from double primary patients was tested for the KRAS-variant (n = 232). Confirmation of pathologic diagnoses, age of diagnoses, interval between ovarian cancer diagnosis and sample collection, additional cancer diagnoses, and family history were obtained when available. All patients were tested for deleterious BRCA mutations. Results The KRAS-variant was significantly enriched in uninformative (BRCA negative) double primary patients, being found in 39% of patients accrued within two years of their ovarian cancer diagnosis. Furthermore, the KRAS-variant was found in 35% of uninformative double primary patients diagnosed with ovarian cancer post-menopausally, and was significantly associated with uninformative double primary patients with a positive family history. The KRAS-variant was also significantly enriched in uninformative patients who developed more then two primary cancers, being found in 48% of women with two breast primaries plus ovarian cancer or with triple primary cancers. Conclusions These findings further validate the importance of the KRAS-variant in breast and ovarian cancer risk, and support the association of this variant as a genetic marker for HBOC families previously considered uninformative.

Efficacy of the PARP inhibitor veliparib with carboplatin or as a single agent in patients with germline BRCA1- or BRCA2-associated metastatic breast cancer: California Cancer Consortium trial NCT01149083

Purpose: We aimed to establish the MTD of the poly (ADP-ribose) (PAR) polymerase inhibitor, veliparib, in combination with carboplatin in germline BRCA1- and BRCA2- (BRCA)-associated metastatic breast cancer (MBC), to assess the efficacy of single-agent veliparib, and of the combination treatment after progression, and to correlate PAR levels with clinical outcome. Experimental Design: Phase I patients received carboplatin (AUC of 5–6, every 21 days), with escalating doses (50-20 mg) of oral twice-daily (BID) veliparib. In a companion phase II trial, patients received single-agent veliparib (400 mg BID), and upon progression, received the combination at MTD. Peripheral blood mononuclear cell PAR and serum veliparib levels were assessed and correlated with outcome. Results: Twenty-seven phase I trial patients were evaluable. Dose-limiting toxicities were nausea, dehydration, and thrombocytopenia [MTD: veliparib 150 mg po BID and carboplatin (AUC of 5)]. Response rate (RR) was 56%; 3 patients remain in complete response (CR) beyond 3 years. Progression-free survival (PFS) and overall survival (OS) were 8.7 and 18.8 months. The PFS and OS were 5.2 and 14.5 months in the 44 patients in the phase II trial, with a 14% RR in BRCA1 (n = 22) and 36% in BRCA2 (n = 22). One of 30 patients responded to the combination therapy after progression on veliparib. Higher baseline PAR was associated with clinical benefit. Conclusions: Safety and efficacy are encouraging with veliparib alone and in combination with carboplatin in BRCA-associated MBC. Lasting CRs were observed when the combination was administered first in the phase I trial. Further investigation of PAR level association with clinical outcomes is warranted. Clin Cancer Res; 23(15); 4066–76. ©2017 AACR.

Development and Evaluation of a Decision Aid for BRCA Carriers with Breast Cancer

BRCA+ breast cancer patients face high risk for a second breast cancer and ovarian cancer. Helping these women decide among risk-reducing options requires effectively conveying complex, emotionally-laden, information. To support their decision-making needs, we developed a web-based decision aid (DA) as an adjunct to genetic counseling. Phase 1 used focus groups to determine decision-making needs. These findings and the Ottawa Decision Support Framework guided the DA development. Phase 2 involved nine focus groups of four stakeholder types (BRCA+ breast cancer patients, breast cancer advocates, and genetics and oncology professionals) to evaluate the DA’s decision-making utility, information content, visual display, and implementation. Overall, feedback was very favorable about the DA, especially a values and preferences ranking-exercise and an output page displaying personalized responses. Stakeholders were divided as to whether the DA should be offered at-home versus only in a clinical setting. This well-received DA will be further tested to determine accessibility and effectiveness.