Integrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing

Perceived benefits and barriers to implementing precision preventive care: Results of a national physician survey

Polygenic risk scores (PRS) may improve risk-stratification in preventive care. Their clinical implementation will depend on primary care physicians' (PCPs) uptake. We surveyed PCPs in a national physician database about the perceived clinical utility, benefits, and barriers to the use of PRS in preventive care. Among 367 respondents (participation rate 96.3%), mean (SD) age was 54.9 (12.9) years, 137 (37.3%) were female, and mean (SD) time since medical school graduation was 27.2 (13.3) years. Respondents reported greater perceived utility for more clinical action (e.g., earlier or more intensive screening, preventive medications, or lifestyle modification) for patients with high-risk PRS than for delayed or discontinued prevention actions for low-risk patients (p < 0.001). Respondents most often chose out-of-pocket costs (48%), lack of clinical guidelines (24%), and insurance discrimination concerns (22%) as extreme barriers. Latent class analysis identified 3 subclasses of respondents. Skeptics (n = 83, 22.6%) endorsed less agreement with individual clinical utilities, saw patient anxiety and insurance discrimination as significant barriers, and agreed less often that PRS could help patients make better health decisions. Learners (n = 134, 36.5%) and enthusiasts (n = 150, 40.9%) expressed similar levels of agreement that PRS had utility for preventive actions and that PRS could be useful for patient decision-making. Compared with enthusiasts, however, learners perceived greater barriers to the clinical use of PRS. Overall results suggest that PCPs generally endorse using PRS to guide medical decision-making about preventive care, and barriers identified suggest interventions to address their needs and concerns.

The role of polygenic risk scores in breast cancer risk perception and decision-making

Polygenic risk scores (PRS) have the potential to improve the accuracy of clinical risk assessments, yet questions about their clinical validity and readiness for clinical implementation persist. Understanding how individuals integrate and act on the information provided by PRS is critical for their effective integration into routine clinical care, yet few studies have examined how individuals respond to the receipt of polygenic risk information. We conducted an embedded Ethical, Legal, and Social Implications (ELSI) study to examine if and how unaffected participants in a US population breast cancer screening trial understood and utilized PRS, as part of a multifactorial risk score combining traditional risk factors with a genetic risk assessment, to make screening and risk-reduction decisions. Semi-structured qualitative interviews were conducted with 24 trial participants who were designated at elevated risk for breast cancer due to their combined risk score. Interviews were analyzed using a grounded theory approach. Participants understood PRS conceptually and accepted it as one of many risk factors to consider, yet the value and meaning they ascribed to this risk estimate varied. Most participants reported financial and insurance barriers to enhanced screening with MRI and were not interested in taking risk-reducing medications. These findings contribute to our understanding of how PRS may be best translated from research to clinical care. Furthermore, they illuminate ethical concerns about identifying risk and making recommendations based on polygenic risk in a population screening context where many may have trouble accessing appropriate care.

Toward more personalized breast cancer risk assessment: The polygenic risk score

ABSTRACT

Healthcare providers often are uncertain about how best to assess and manage breast cancer risk. Women at average risk wonder when to start mammography and how often to go. Women at increased risk might inquire about genetic testing, MRI screening, and preventive measures. Patients who carry gene mutations face higher stakes and more complex risk management choices, but only some are aware of their status. This article helps clinicians stratify breast cancer risk and discusses a newer genomic test, the polygenic risk score, that may enable more personalized risk management and decision-making.

Extended genetic analysis and tumor characteristics in over 4600 women with suspected hereditary breast and ovarian cancer

BACKGROUND

Genetic screening for pathogenic variants (PVs) in cancer predisposition genes can affect treatment strategies, risk prediction and preventive measures for patients and families. For decades, hereditary breast and ovarian cancer (HBOC) has been attributed to PVs in the genes BRCA1 and BRCA2, and more recently other rare alleles have been firmly established as associated with a high or moderate increased risk of developing breast and/or ovarian cancer. Here, we assess the genetic variation and tumor characteristics in a large cohort of women with suspected HBOC in a clinical oncogenetic setting.

METHODS

Women with suspected HBOC referred from all oncogenetic clinics in Sweden over a six-year inclusion period were screened for PVs in 13 clinically relevant genes. The genetic outcome was compared with tumor characteristics and other clinical data collected from national cancer registries and hospital records.

RESULTS

In 4622 women with breast and/or ovarian cancer the overall diagnostic yield (the proportion of women carrying at least one PV) was 16.6%. BRCA1/2 PVs were found in 8.9% of women (BRCA1 5.95% and BRCA2 2.94%) and PVs in the other breast and ovarian cancer predisposition genes in 8.2%: ATM (1.58%), BARD1 (0.45%), BRIP1 (0.43%), CDH1 (0.11%), CHEK2 (3.46%), PALB2 (0.84%), PTEN (0.02%), RAD51C (0.54%), RAD51D (0.15%), STK11 (0) and TP53 (0.56%). Thus, inclusion of the 11 genes in addition to BRCA1/2 increased diagnostic yield by 7.7%. The yield was, as expected, significantly higher in certain subgroups such as younger patients, medullary breast cancer, higher Nottingham Histologic Grade, ER-negative breast cancer, triple-negative breast cancer and high grade serous ovarian cancer. Age and tumor subtype distributions differed substantially depending on genetic finding.

CONCLUSIONS

This study contributes to understanding the clinical and genetic landscape of breast and ovarian cancer susceptibility. Extending clinical genetic screening from BRCA1 and BRCA2 to 13 established cancer predisposition genes almost doubles the diagnostic yield, which has implications for genetic counseling and clinical guidelines. The very low yield in the syndrome genes CDH1, PTEN and STK11 questions the usefulness of including these genes on routine gene panels.

Integration of a Cross-Ancestry Polygenic Model With Clinical Risk Factors Improves Breast Cancer Risk Stratification

PURPOSE

To develop and validate a cross-ancestry integrated risk score (caIRS) that combines a cross-ancestry polygenic risk score (caPRS) with a clinical estimator for breast cancer (BC) risk. We hypothesized that the caIRS is a better predictor of BC risk than clinical risk factors across diverse ancestry groups.

METHODS

We used diverse retrospective cohort data with longitudinal follow-up to develop a caPRS and integrate it with the Tyrer-Cuzick (T-C) clinical model. We tested the association between the caIRS and BC risk in two validation cohorts including > 130,000 women. We compared model discrimination for 5-year and remaining lifetime BC risk between the caIRS and T-C and assessed how the caIRS would affect screening in the clinic.

RESULTS

The caIRS outperformed T-C alone for all populations tested in both validation cohorts and contributed significantly to risk prediction beyond T-C. The area under the receiver operating characteristic curve improved from 0.57 to 0.65, and the odds ratio per standard deviation increased from 1.35 (95% CI, 1.27 to 1.43) to 1.79 (95% CI, 1.70 to 1.88) in validation cohort 1 with similar improvements observed in validation cohort 2. We observed the largest gain in positive predictive value using the caIRS in Black/African American women across both validation cohorts, with an approximately two-fold increase and an equivalent negative predictive value as the T-C. In a multivariate, age-adjusted logistic regression model including both caIRS and T-C, caIRS remained significant, indicating that caIRS provides information over T-C alone.

CONCLUSION

Adding a caPRS to the T-C model improves BC risk stratification for women of multiple ancestries, which could have implications for screening recommendations and prevention.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Translational Genomic Research: The Association between Genetic Profiles and Cognitive Functioning or Cardiac Function Among Breast Cancer Survivors Completing Chemotherapy

Introduction: Emerging evidence suggests that Chemotherapy (CT) treated breast cancer survivors (BCS) who have "risk variants" in genes may be more susceptible to cognitive impairment (CI) and/or poor cardiac phenotypes. The objective of this preliminary study was to examine whether there is a relationship between genetic variants and objective/subjective cognitive or cardiac phenotypes. Methods and Analysis: BCS were recruited from Moffitt Cancer Center, Morsani College of Medicine, AdventHealth Tampa and Sarasota Memorial Hospital. Genomic DNA were collected at baseline for genotyping analysis. A total of 16 single nucleotide polymorphisms (SNPs) from 14 genes involved in cognitive or cardiac function were evaluated. Three genetic models (additive, dominant, and recessive) were used to test correlation coefficients between genetic variants and objective/subjective measures of cognitive functioning and cardiac outcomes (heart rate, diastolic blood pressure, systolic blood pressure, respiration rate, and oxygen saturation). Results: BCS (207 participants) with a mean age of 56 enrolled in this study. The majority were non-Hispanic white (73.7%), married (63.1%), and received both CT and radiation treatment (77.3%). Three SNPs in genes related to cognitive functioning (rs429358 in APOE, rs1800497 in ANKK1, rs10119 in TOMM40) emerged with the most consistent significant relationship with cognitive outcomes. Among five candidate SNPs related to cardiac functioning, rs8055236 in CDH13 and rs1801133 in MTHER emerged with potential significant relationships with cardiac phenotype. Conclusions: These preliminary results provide initial targets to further examine whether BCS with specific genetic profiles may preferentially benefit from interventions designed to improve cognitive and cardiac functioning following CT.

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

A Polygenic Score for Type 2 Diabetes Improves Risk Stratification Beyond Current Clinical Screening Factors in an Ancestrally Diverse Sample

A substantial proportion of the adult United States population with type 2 diabetes (T2D) are undiagnosed, calling into question the comprehensiveness of current screening practices, which primarily rely on age, family history, and body mass index (BMI). We hypothesized that a polygenic score (PGS) may serve as a complementary tool to identify high-risk individuals. The T2D polygenic score maintained predictive utility after adjusting for family history and combining genetics with family history led to even more improved disease risk prediction. We observed that the PGS was meaningfully related to age of onset with implications for screening practices: there was a linear and statistically significant relationship between the PGS and T2D onset (-1.3 years per standard deviation of the PGS). Evaluation of U.S. Preventive Task Force and a simplified version of American Diabetes Association screening guidelines showed that addition of a screening criterion for those above the 90th percentile of the PGS provided a small increase the sensitivity of the screening algorithm. Among T2D-negative individuals, the T2D PGS was associated with prediabetes, where each standard deviation increase of the PGS was associated with a 23% increase in the odds of prediabetes diagnosis. Additionally, each standard deviation increase in the PGS corresponded to a 43% increase in the odds of incident T2D at one-year follow-up. Using complications and forms of clinical intervention (i.e., lifestyle modification, metformin treatment, or insulin treatment) as proxies for advanced illness we also found statistically significant associations between the T2D PGS and insulin treatment and diabetic neuropathy. Importantly, we were able to replicate many findings in a Hispanic/Latino cohort from our database, highlighting the value of the T2D PGS as a clinical tool for individuals with ancestry other than European. In this group, the T2D PGS provided additional disease risk information beyond that offered by traditional screening methodologies. The T2D PGS also had predictive value for the age of onset and for prediabetes among T2D-negative Hispanic/Latino participants. These findings strengthen the notion that a T2D PGS could play a role in the clinical setting across multiple ancestries, potentially improving T2D screening practices, risk stratification, and disease management.

Comprehensive Breast Cancer Risk Assessment for CHEK2 and ATM Pathogenic Variant Carriers Incorporating a Polygenic Risk Score and the Tyrer-Cuzick Model

PURPOSE

Breast cancer risks for CHEK2 and ATM pathogenic variant (PV) carriers are modified by an 86-single nucleotide polymorphism polygenic risk score (PRS) and individual clinical factors. Here, we describe comprehensive risk prediction models for women of European ancestry combining PV status, PRS, and individual clinical variables.

MATERIALS AND METHODS

This study included deidentified clinical records from 358,095 women of European ancestry who received testing with a multigene panel (September 2013 to November 2019). Model development included CHEK2 PV carriers (n = 4,286), ATM PV carriers (n = 2,666), and women negative for other breast cancer risk gene PVs (n = 351,143). Odds ratios (ORs) were calculated using multivariable logistic regression with adjustment for familial cancer history. Risk estimates incorporating PV status, PRS, and Tyrer-Cuzick v7.02 were calculated using a Fixed-Stratified method that accounts for correlations between risk factors. Stratification of PV carriers into risk categories on the basis of remaining lifetime risk (RLR) was assessed in independent cohorts of PV carriers.

RESULTS

ORs for association of PV status with breast cancer were 2.01 (95% CI, 1.88 to 2.16) and 1.83 (95% CI, 1.68 to 2.00) for CHEK2 and ATM PV carriers, respectively. ORs for PRS per one standard deviation were 1.51 (95% CI, 1.37 to 1.66) and 1.45 (95% CI, 1.30 to 1.64) in CHEK2 and ATM PV carriers, respectively. Using the combined model (PRS plus Tyrer-Cuzick plus PV status), RLR was low (≤ 20%) for 24.2% of CHEK2 PV carriers, medium (20%-50%) for 63.8%, and high (> 50%) for 12.0%. Among ATM PV carriers, RLR was low for 31.5% of patients, medium for 58.5%, and high for 9.7%.

CONCLUSION

In CHEK2 and ATM PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.