Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field

Evaluating Practical Approaches for Including MYOC Variants Alongside Common Variants for Genetics-Based Risk Stratification for Glaucoma

OBJECTIVE

Rare variants in the MYOC gene are associated with glaucoma risk, with p.Gln368Ter the most common pathogenic variant in Europeans. Genetics-based risk stratification may aid with early diagnosis for glaucoma but it is unclear how best to combine the p.Gln368Ter status with polygenic risk scores (PRS). Our study aimed to examine approaches for identifying p. Gln368Ter carriers using genotyping array data and the utility of integrating p.Gln368Ter status into glaucoma PRS.

DESIGN

Retrospective cohort study.

METHODS

We identified p.Gln368Ter carriers using directly genotyped and imputed data. Results were confirmed in a subset with sequencing data. We evaluated the combined effects of p.Gln368Ter status and PRS in stratified analyses by considering them as two separate factors and as an aggregate score.

PARTICIPANTS

A total of 58,452 participants from the Genetics of Glaucoma, the QSkin Sun and Health Study (QSKIN), and CARTaGENE projects, including 6015 with sequencing data.

MAIN OUTCOMES AND MEASURES

The concordance of direct genotyping, compared with imputation and sequencing for p.Gln368Ter identification.

RESULTS

Without appropriate quality control, substantial mis-calling may occur. Nevertheless, the p.Gln368Ter variant could be accurately genotyped in most cases by filtering individuals for call rate and heterozygosity. In 6015 individuals with sequencing data, direct genotyping exhibited perfect concordance with sequencing results. Filtered direct genotyping results showed high agreement with imputed results, with only 16 discrepancies among 57,468 individuals. When quality control is not possible (eg, heterozygosity filtering for an individual), we recommend comparing genotyped and imputed results to ensure accuracy. Incorporating p.Gln368Ter into PRS had additional effects on stratifying high-risk individuals, but did not improve risk prediction for the general population given the variant's rarity. The MYOC-enhanced PRS increased the proportion of p.Gln368Ter carriers classified as high risk from 32.31% to 75.38% in QSKIN and from 38.24% to 79.41% in CARTaGENE.

CONCLUSIONS

The p.Gln368Ter variant can be genotyped with high accuracy using array data, provided careful quality control measures are implemented. Incorporating p.Gln368Ter into glaucoma PRS improved risk stratification for carriers.

Association of Polygenic-Based Breast Cancer Risk Prediction With Patient Management

PURPOSE

Breast cancer (BC) risk prediction is more accurate when clinical and polygenic factors are combined (combined risk score [CRS]), but little is known about how CRS results affect real-world patient management.

METHODS

Deidentified medical and pharmacy claims data were linked with Tyrer-Cuzick (TC) and CRS results and evaluated for BC risk management. Patients were divided into subcohorts on the basis of lifetime risk predicted by CRS and by TC ("+": ≥20% risk, "-": <20%): CRS+ TC+, CRS+ TC-, CRS- TC+, and CRS- TC-. Claims data related to screening mammography (SM) in patients younger than 40 years, breast magnetic resonance imaging (MRI), and genetic counseling (GC) were compared 360 days before and after CRS testing. Differences in pre- and post-CRS management were evaluated using McNemar tests, and post-CRS management of subcohorts was compared using multivariable logistic regression.

RESULTS

After CRS testing, the CRS+ TC+, CRS+ TC-, and CRS- TC+ subcohorts had 1.6-2.2-fold increases in SM in patients younger than 40 years (all P < .02) and 4.7-5.6-fold increases in breast MRI (all P < .001). The CRS+ TC+ and CRS+ TC- subcohorts had 1.9-2.3-fold increases in GC (both P < .001). SM in those younger than 40 years, breast MRI, and GC did not increase in the CRS- TC- subcohort. After CRS testing, compared with the CRS- TC- subcohort, the CRS+ TC+, CRS+ TC-, and CRS- TC+ subcohorts had significantly higher odds of receiving SM before age 40 years (odds ratio [OR], 3.80-5.19), breast MRI (OR, 11.55-23.09), and GC (OR, 2.03-2.91; all P < .001).

CONCLUSION

Patients with ≥20% lifetime risk predicted by either CRS or TC were more likely to receive enhanced management compared with those who had <20% lifetime risk, suggesting that clinicians considered the CRS in BC risk management.

Polygenic risk scores in the clinic: a systematic review of stakeholders' perspectives, attitudes, and experiences

Polygenic Risk Scores (PRS) are statistical methods estimating part of an individual's genetic susceptibility to various disease phenotypes. Their potential clinical applications to enhance the prediction, prevention, and risk management of complex conditions motivate current research efforts worldwide. While a growing body of literature has highlighted the scientific and ethical limitations of PRS, the technology's clinical translation will present both opportunities and challenges for the stakeholders involved. Here, a mixed-method systematic review of empirical studies was performed to gather evidence on the perspectives, attitudes, and experiences of healthcare providers, patients, and the public regarding the use of PRS in healthcare settings. The PRISMA reporting protocol was followed and 24 articles were included. Three major themes were identified. First, we reported on participants' familiarity with the test, including their knowledge, understanding, and education on PRS' clinical use. The second theme collects stakeholders' motivations for taking the test and their perspectives on sensitive issues related to the return of results. Participants' normative stances regarding the appropriate use of PRS, their benefits, and harms were presented in the third theme. The findings underscore significant knowledge gaps and challenges in the clinical interpretation of PRS among healthcare providers. On the other hand, the provision of genetic counseling benefitted patients' understanding of PRS results and in most cases, no psychosocial burden was reported. Finally, the review highlights that stakeholders' perspectives on the clinical use of PRS are highly context-dependent, shaped by population characteristics, disease type, and social factors, emphasizing the need for tailored approaches across diverse healthcare settings.

Utilizing polygenic risk score for breast cancer risk prediction in a Taiwanese population

BACKGROUND

Breast cancer has been the most frequently diagnosed cancer among women in Taiwan since 2003. While genetic variants play a significant role in the elevated risk of breast cancer, their implications have been less explored within Asian populations. Variant-based polygenic risk scores (PRS) have emerged as valuable tools for assessing the likelihood of developing breast cancer. In light of this, we attempted to establish a predictive breast cancer PRS tailored specifically for the Taiwanese population.

METHODS

The cohort analyzed in this study comprised 28,443 control subjects and 1501 breast cancer cases. These individuals were sourced from the Taiwan Precision Medicine Initiative (TPMI) array and the breast cancer registry lists at Taichung Veterans General Hospital (TCVGH). Utilizing the breast cancer-associated Polygenic Score (PGS) Catalog, we employed logistic regression to identify the most effective PRS for predicting breast cancer risk. Subsequently, we subjected the cohort of 1501 breast cancer patients to further analysis to investigate potential heterogeneity in breast cancer risk.

RESULTS

The Polygenic Score ID PGS000508 demonstrated a significant association with breast cancer risk in Taiwanese women with a 1.498-fold increase in cancer risk(OR = 1.498, 95 % CI(1.431-1.567, p=5.38×10^-68). Individuals in the highest quartile exhibited a substantially elevated risk compared to those in the lowest quartile, with an odds ratio (OR) of 3.11 (95 % CI: 2.70-3.59; p=1.15×10^-55). In a cohort of 1501 breast cancer cases stratified by PRS distribution, women in the highest quartile were diagnosed at a significantly younger age (p=0.003) compared to those in the lowest quartile. However, no significant differences were observed between PRS quartiles in relation to clinical stage (p=0.274), pathological stage (p=0.647), or tumor subtype distribution (p=0.244).

CONCLUSION

In our study, we pinpointed PGS000508 as a significant predictive factor for breast cancer risk in Taiwanese women. Furthermore, we found that a higher PGS000508 score was associated with younger age at the time of first diagnosis among the breast cancer cases examined.

Clinical Utility of Genomic Sequencing for Hereditary Cancer Syndromes: An Observational Cohort Study

PURPOSE

Genomic sequencing (GS) is increasingly used to improve diagnoses and inform targeted therapies. GS can also be used to identify the 10% of cancer patients with an underlying hereditary cancer syndrome (HCS), who can benefit from surveillance and preventive surgery that reduce morbidity/mortality. However, the evidence on clinical utility of GS for HCS is limited: we aimed to fill this gap by assessing yield of all cancer results and associated recommendations for patients undergoing GS for HCS.

MATERIALS AND METHODS

An observational chart review and survey were conducted for cancer patients with previous uninformative cancer gene panel results, who received GS as part of the Incidental Genomics Trial (ClinicalTrials.gov identifier: NCT03597165). Descriptive statistics were used to describe demographics and clinical history. Proportions were calculated to compare frequencies of result types and recommendations made and followed.

RESULTS

A total of 276 patients were eligible and included. Participants were mostly female (n = 240), European (n = 158), and with breast cancer history (n = 168). Yield: 25 patients (9.1%) received ≥1 pathogenic/likely pathogenic variant, 246 (89%) received ≥1 variant of uncertain significance (VUS), and 27 (10%) were negative. Most pathogenic variants (20/26) were in low/moderate cancer risk genes. The mean number of VUS was 2.7/patient and higher in non-Europeans versus Europeans (3.5 v 2.5, P < .05). Recommendations: Pathogenic variants triggered 100 recommendations in 21/25 patients; most were for genetic counseling, communication to relatives, and cascade testing.

CONCLUSION

GS provided a modest increase in utility after first-tier cancer gene panels, at the cost of a high frequency of uncertain results. Furthermore, most positives were low/moderate cancer risk results that did not have corresponding evidence-based, management guidelines.

What do women want to see in a personalized breast cancer risk report? A qualitative study of Asian women of two countries

A breast cancer risk assessment tool for Asian populations, incorporating Polygenic Risk Score and Gail Model algorithm, has been established and validated. However, effective methods for delivering personalized risk information remain underexplored. This study aims to identify and develop effective methods for conveying breast cancer risk information to Asian women. Through ten focus group discussions with 32 women in Indonesia and Singapore, we explored preferences for the presentation of risk information. Participants favored comprehensive reports featuring actionable steps, simplified language, non-intimidating visuals, and personalized risk reduction recommendations. Singaporean participants, more aware of breast cancer prevention, showed a lower likelihood of seeking follow-ups upon receiving low-risk results compared to Indonesians. Overall, participants found the reports useful and advocated for similar approaches in other disease assessments. Balancing content and complexity in reports is crucial, highlighting the need for improved patient understanding and engagement with healthcare providers. Future studies could explore physicians' roles in delivering personalized risk assessments for breast cancer prevention.

Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer

BACKGROUND

Breast cancer is the most common malignancy, with a mean age of onset of approximately 60 years. Only a minority of breast cancer patients present with an early onset at or before 40 years of age. An exceptionally young age at diagnosis hints at a possible genetic etiology. Currently, known pathogenic genetic variants only partially explain the disease burden of younger patients. Thus, new knowledge is warranted regarding additional risk variants. In this study, we analyzed DNA repair genes to identify additional variants to shed light on the etiology of early-onset breast cancer.

METHODS

Germline whole-exome sequencing was conducted in a cohort of 63 patients diagnosed with breast cancer at or before 40 years of age (median 33, mean 33.02, range 23-40 years) with no known pathogenic variants in BRCA genes. After filtering, all detected rare variants were sorted by pathogenicity prediction scores (CADD score and REVEL) to identify the most damaging genetic changes. The remaining variants were then validated by comparison to a validation cohort of 121 breast cancer patients with no preselected age at cancer diagnosis (mean 51.4 years, range 28-80 years). Analysis of novel exonic variants was based on protein structure modeling.

RESULTS

Five novel, deleterious variants in the genes WRN, RNF8, TOP3A, ERCC2, and TREX2 were found in addition to a splice acceptor variant in RNF4 and two frameshift variants in EXO1 and POLE genes, respectively. There were also multiple previously reported putative risk variants in other DNA repair genes.

CONCLUSIONS

Taken together, whole-exome sequencing yielded 72 deleterious variants, including 8 novel variants that may play a pivotal role in the development of early-onset breast cancer. Although more studies are warranted, we demonstrate that young breast cancer patients tend to carry multiple deleterious variants in one or more DNA repair genes.

Using polygenic risk modification to improve breast cancer prevention: study protocol for the PRiMo multicentre randomised controlled trial

INTRODUCTION

Established personal and familial risk factors contribute collectively to a woman's risk of breast or ovarian cancer. Existing clinical services offer genetic testing for pathogenic variants in high-risk genes to investigate these risks but recent information on the role of common genomic variants, in the form of a Polygenic Risk Score (PRS), has provided the potential to further personalise breast and ovarian cancer risk assessment. Data from cohort studies support the potential of an integrated risk assessment to improve targeted risk management but experience of this approach in clinical practice is limited.

METHODS AND ANALYSIS

The polygenic risk modification trial is an Australian multicentre prospective randomised controlled trial of integrated risk assessment including personal and family risk factors with inclusion of breast and ovarian PRS vs standard care. The study will enrol women, unaffected by cancer, undergoing predictive testing at a familial cancer clinic for a pathogenic variant in a known breast cancer (BC) or ovarian cancer (OC) predisposition gene (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D). Array-based genotyping will be used to generate breast cancer (313 SNP) and ovarian cancer (36 SNP) PRS. A suite of materials has been developed for the trial including an online portal for patient consent and questionnaires, and a clinician education programme to train healthcare providers in the use of integrated risk assessment. Long-term follow-up will evaluate differences in the assessed risk and management advice, patient risk management intentions and adherence, patient-reported experience and outcomes, and the health service implications of personalised risk assessment.

ETHICS AND DISSEMINATION

This study has been approved by the Human Research Ethics Committee of Peter MacCallum Cancer Centre and at all participating centres. Study findings will be disseminated via peer-reviewed publications and conference presentations, and directly to participants.

TRIAL REGISTRATION NUMBER

ACTRN12621000009819.

Generalizability of PGS313 for breast cancer risk in a Los Angeles biobank

Polygenic scores (PGSs) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS313, which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS313 for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular electronic health record (EHR) system, genotyping platform, and quality control process. We found that the PGS313 achieved overlapping areas under the receiver operator characteristic (ROC) curve (AUCs) in females of HL (AUC = 0.68, 95% confidence interval [CI] = 0.65-0.71) and EA ancestry (AUC = 0.70, 95% CI = 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC = 0.61, 95% CI = 0.56-0.65; EAA: AUC = 0.64, 95% CI = 0.60-0.680). While PGS313 is associated with hormone-receptor-positive (HR+) disease in EA Americans (odds ratio [OR] = 1.42, 95% CI = 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS313 was significantly associated with breast cancer but with attenuated accuracy in women of AFR and EAA descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to the clinical implementation of PGSs.

Validation of a clinical breast cancer risk assessment tool combining a polygenic score for all ancestries with traditional risk factors

PURPOSE

We previously described a combined risk score (CRS) that integrates a multiple-ancestry polygenic risk score (MA-PRS) with the Tyrer-Cuzick (TC) model to assess breast cancer (BC) risk. Here, we present a longitudinal validation of CRS in a real-world cohort.

METHODS

This study included 130,058 patients referred for hereditary cancer genetic testing and negative for germline pathogenic variants in BC-associated genes. Data were obtained by linking genetic test results to medical claims (median follow-up 12.1 months). CRS calibration was evaluated by the ratio of observed to expected BCs.

RESULTS

Three hundred forty BCs were observed over 148,349 patient-years. CRS was well-calibrated and demonstrated superior calibration compared with TC in high-risk deciles. MA-PRS alone had greater discriminatory accuracy than TC, and CRS had approximately 2-fold greater discriminatory accuracy than MA-PRS or TC. Among those classified as high risk by TC, 32.6% were low risk by CRS, and of those classified as low risk by TC, 4.3% were high risk by CRS. In cases where CRS and TC classifications disagreed, CRS was more accurate in predicting incident BC.

CONCLUSION

CRS was well-calibrated and significantly improved BC risk stratification. Short-term follow-up suggests that clinical implementation of CRS should improve outcomes for patients of all ancestries through personalized risk-based screening and prevention.

Breast Cancer Screening and Prophylactic Mastectomy for High-Risk Women in Romania

Breast cancer remains a significant contributor to morbidity and mortality within oncology. Risk factors, encompassing genetic and environmental influences, significantly contribute to its prevalence. While germline mutations, notably within the BRCA genes, are commonly associated with heightened breast cancer risk, a spectrum of other variants exists among affected individuals. Diagnosis relies on imaging techniques, biopsies, biomarkers, and genetic testing, facilitating personalised risk assessment through specific scoring systems. Breast cancer screening programs employing mammography and other imaging modalities play a crucial role in early detection and management, leading to improved outcomes for affected individuals. Regular screening enables the identification of suspicious lesions or abnormalities at earlier stages, facilitating timely intervention and potentially reducing mortality rates associated with breast cancer. Genetic mutations guide screening protocols, prophylactic interventions, treatment modalities, and patient prognosis. Prophylactic measures encompass a range of interventions, including chemoprevention, hormonal inhibition, oophorectomy, and mastectomy. Despite their efficacy in mitigating breast cancer incidence, these interventions carry potential side effects and psychological implications, necessitating comprehensive counselling tailored to individual cases.

Taking the risk. A systematic review of ethical reasons and moral arguments in the clinical use of polygenic risk scores

Debates about the prospective clinical use of polygenic risk scores (PRS) have grown considerably in the last years. The potential benefits of PRS to improve patient care at individual and population levels have been extensively underlined. Nonetheless, the use of PRS in clinical contexts presents a number of unresolved ethical challenges and consequent normative gaps that hinder their optimal implementation. Here, we conducted a systematic review of reasons of the normative literature discussing ethical issues and moral arguments related to the use of PRS for the prevention and treatment of common complex diseases. In total, we have included and analyzed 34 records, spanning from 2013 to 2023. The findings have been organized in three major themes: in the first theme, we consider the potential harms of PRS to individuals and their kin. In the theme "Threats to health equity," we consider ethical concerns of social relevance, with a focus on justice issues. Finally, the theme "Towards best practices" collects a series of research priorities and provisional recommendations to be considered for an optimal clinical translation of PRS. We conclude that the use of PRS in clinical care reinvigorates old debates in matters of health justice; however, open questions, regarding best practices in clinical counseling, suggest that the ethical considerations applicable in monogenic settings will not be sufficient to face PRS emerging challenges.

Risk-stratified screening for the early detection of kidney cancer

Earlier detection and screening for kidney cancer has been identified as a key research priority, however the low prevalence of the disease in unselected populations limits the cost-effectiveness of screening. Risk-stratified screening for kidney cancer may improve early detection by targeting high-risk individuals whilst limiting harms in low-risk individuals, potentially increasing the cost-effectiveness of screening. A number of models have been identified which estimate kidney cancer risk based on both phenotypic and genetic data, and while several of the former have been shown to identify individuals at high-risk of developing kidney cancer with reasonable accuracy, current evidence does not support including a genetic component. Combined screening for lung cancer and kidney cancer has been proposed, as the two malignancies share some common risk factors. A modelling study estimated that using lung cancer risk models (currently used for risk-stratified lung cancer screening) could capture 25% of patients with kidney cancer, which is only slightly lower than using the best performing kidney cancer-specific risk models based on phenotypic data (27%-33%). Additionally, risk-stratified screening for kidney cancer has been shown to be acceptable to the public. The following review summarises existing evidence regarding risk-stratified screening for kidney cancer, highlighting the risks and benefits, as well as exploring the management of potential harms and further research needs.

Association of Genetic Markers with the Risk of Early-Onset Breast Cancer in Kazakh Women

Breast cancer is a global health problem. It is an age-dependent disease, but cases of early-onset breast cancer (eBC) are gradually increasing. There are many unresolved questions regarding eBC risk factors, mechanisms of development and screening. Only 10% of eBC cases are due to mutations in the BRCA1/BRCA2 genes, and 90% have a more complex genetic background. This poses a significant challenge to timely cancer detection in young women and highlights the need for research and awareness. Therefore, identifying genetic risk factors for eBC is essential to solving these problems. This study represents an association analysis of 144 eBC cases and 163 control participants to identify genetic markers associated with eBC risks in Kazakh women. We performed a two-stage approach in association analysis to assess genetic predisposition to eBC. First-stage genome-wide association analysis revealed two risk intronic loci in the CHI3L2 gene (p = 5.2 × 10-6) and MGAT5 gene (p = 8.4 × 10-6). Second-stage exonic polymorphisms haplotype analysis showed significant risks for seven haplotypes (p < 9.4 × 10-4). These results point to the importance of studying medium- and low-penetrant genetic markers in their haplotype combinations for a detailed understanding of the role of detected genetic markers in eBC development and prediction.

A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population

Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.

Ethical, legal, and social implications of genetic risk prediction for multifactorial disease: a narrative review identifying concerns about interpretation and use of polygenic scores

Advances in genomics have enabled the development of polygenic scores (PGS), sometimes called polygenic risk scores, in the context of multifactorial diseases and disorders such as cancer, cardiovascular disease, and schizophrenia. PGS estimate an individual's genetic predisposition, as compared to other members of a population, for conditions which are influenced by both genetic and environmental factors. There is significant interest in using genetic risk prediction afforded through PGS in public health, clinical care, and research settings, yet many acknowledge the need to thoughtfully consider and address ethical, legal, and social implications (ELSI). To contribute to this effort, this paper reports on a narrative review of the literature, with the aim of identifying and categorizing ELSI relating to genetic risk prediction in the context of multifactorial disease, which have been raised by scholars in the field. Ninety-two articles, spanning from 1977 to 2021, met the inclusion criteria for this study. Identified ELSI included potential benefits, challenges and risks that focused on concerns about interpretation and use, and ethical obligations to maximize benefits, minimize risks, promote justice, and support autonomy. This research will support geneticists, clinicians, genetic counselors, patients, patient advocates, and policymakers in recognizing and addressing ethical concerns associated with PGS; it will also guide future empirical and normative research.

Clinical utility of polygenic risk scores: a critical 2023 appraisal

Since their first appearance in the context of schizophrenia and bipolar disorder in 2009, polygenic risk scores (PRSs) have been described for a large number of common complex diseases. However, the clinical utility of PRSs in disease risk assessment or therapeutic decision making is likely limited because PRSs usually only account for the heritable component of a trait and ignore the etiological role of environment and lifestyle. We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare. In conclusion, the benefit to individual patients or the health care system in general of PRS-based extensions of existing diagnostic or treatment regimens is still difficult to judge.

Breast cancers arising in subjects with germline BRCA1 or BRCA2 mutations: Different biological and clinical entities with potentially diverse therapeutic opportunities

Breast cancers (BCs) arising in carriers of germline BRCA1 and BRCA2 pathogenic variants (PVs) have long been considered as indistinguishable biological and clinical entities. However, the loss of function of BRCA1 or BRCA2 proteins has different consequences in terms of tumor cell reliance on estrogen receptor signaling and tumor microenvironment composition. Here, we review accumulating preclinical and clinical data indicating that BRCA1 or BRCA2 inactivation may differentially affect BC sensitivity to standard systemic therapies. Based on a different crosstalk between BRCA1 or BRCA2 and the ER pathway, BRCA2-mutated Hormone Receptor-positive, HER2-negative advanced BC may be less sensitive to endocrine therapy (ET) plus CDK 4/6 inhibitors (CDK 4/6i), whereas BRCA2-mutated triple-negative breast cancer (TNBC) may be especially sensitive to immune checkpoint inhibitors. If validated in future prospective studies, these data may have relevant clinical implications, thus establishing different treatment paths in patients with BRCA1 or BRCA2 PVs.

Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank

PURPOSE

The benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening.

METHODS

We studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of loss-of-function (LoF) variants in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk.

RESULTS

In total, 147,399 were considered at high risk for developing BC within the next 2 years by at least 1 of the 4 risk prediction tools examined (Gail2-year > 0.5%: 47%, PRS2-yea r > 0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only 1 risk predictor. The overlap between individuals flagged as high-risk because of genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.

CONCLUSION

Risk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.

A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population

BACKGROUND

Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population.

AIM

To evaluate the performance of PRS models for BC in a Norwegian dataset.

METHODS

We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool.

RESULTS

The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406-1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples.

CONCLUSION

The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway.

Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer

Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.

Challenges and Opportunities for Data Science in Women's Health

The intersection of women's health and data science is a field of research that has historically trailed other fields, but more recently it has gained momentum. This growth is being driven not only by new investigators who are moving into this area but also by the significant opportunities that have emerged in new methodologies, resources, and technologies in data science. Here, we describe some of the resources and methods being used by women's health researchers today to meet challenges in biomedical data science. We also describe the opportunities and limitations of applying these approaches to advance women's health outcomes and the future of the field, with emphasis on repurposing existing methodologies for women's health.

Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe

BACKGROUND

Breast cancer (BC) is a significant health concern among European women, with the highest prevalence rates among all cancers. Existing BC prediction models account for major risks such as hereditary, hormonal and reproductive factors, but research suggests that adherence to a healthy lifestyle can reduce the risk of developing BC to some extent. Understanding the influence and predictive role of lifestyle variables in current risk prediction models could help identify actionable, modifiable, targets among high-risk population groups.

PURPOSE

To systematically review population-based BC risk prediction models applicable to European populations and identify lifestyle predictors and their corresponding parameter values for a better understanding of their relative contribution to the prediction of incident BC.

METHODS

A systematic review was conducted in PubMed, Embase and Web of Science from January 2000 to August 2021. Risk prediction models were included if (i) developed and/or validated in adult cancer-free women in Europe, (ii) based on easily ascertained information, and (iii) reported models' final predictors. To investigate further the comparability of lifestyle predictors across models, estimates were standardised into risk ratios and visualised using forest plots.

RESULTS

From a total of 49 studies, 33 models were developed and 22 different existing models, mostly from Gail (22 studies) and Tyrer-Cuzick and co-workers (12 studies) were validated or modified for European populations. Family history of BC was the most frequently included predictor (31 models), while body mass index (BMI) and alcohol consumption (26 and 21 models, respectively) were the lifestyle predictors most often included, followed by smoking and physical activity (7 and 6 models respectively). Overall, for lifestyle predictors, their modest predictive contribution was greater for riskier lifestyle levels, though highly variable model estimates across different models.

CONCLUSIONS

Given the increasing BC incidence rates in Europe, risk models utilising readily available risk factors could greatly aid in widening the population coverage of screening efforts, while the addition of lifestyle factors could help improving model performance and serve as intervention targets of prevention programmes.

Nanoparticle-Based Antioxidants in Stress Signaling and Programmed Cell Death in Breast Cancer Treatment

Breast cancer (BC) is a complex and heterogeneous disease, and oxidative stress is a hallmark of BC. Oxidative stress is characterized by an imbalance between the production of reactive oxygen species (ROS) and antioxidant defense mechanisms. ROS has been implicated in BC development and progression by inducing DNA damage, inflammation, and angiogenesis. Antioxidants have been shown to scavenge ROS and protect cells from oxidative damage, thereby regulating signaling pathways involved in cell growth, survival, and death. Plants contain antioxidants like ascorbic acid, tocopherols, carotenoids, and flavonoids, which have been found to regulate stress signaling and PCD in BC. Combining different antioxidants has shown promise in enhancing the effectiveness of BC treatment. Antioxidant nanoparticles, when loaded with antioxidants, can effectively target breast cancer cells and enhance their cellular uptake. Notably, these nanoparticles have shown promising results in inducing PCD and sensitizing breast cancer cells to chemotherapy, even in cases where resistance is observed. This review aims to explore how nanotechnology can modulate stress signaling and PCD in breast cancer. By summarizing current research, it underscores the potential of nanotechnology in enhancing antioxidant properties for the treatment of breast cancer.

Increased risk of pancreatic, thyroid, prostate and breast cancers in men with a family history of breast cancer: A population-based study

The association between a family history of breast cancer (FHBC) in female first-degree relatives (FDRs) and cancer risk in men has not been evaluated. This study aimed to compare the risks of overall and site-specific cancers in men with and without FHBC. A population-based study was conducted with 3 329 106 men aged ≥40 years who underwent national cancer screening between 2013 and 2014. Men with and without FHBC in their female FDRs were age-matched in a 1:4 ratio. Men without FHBC were defined as those without a family history of any cancer type in their FDRs. Data from 69 124 men with FHBC and 276 496 men without FHBC were analyzed. The mean follow-up period was 4.7 ± 0.9 years. Men with an FHBC in any FDR (mother or sister) had a higher risk of pancreatic, thyroid, prostate and breast cancers than those without an FHBC (adjusted hazard ratios [aHRs] (95% confidence interval [CI]): 1.35 (1.07-1.70), 1.33 (1.12-1.56), 1.28 (1.13-1.44) and 3.03 (1.130-8.17), respectively). Although an FHBC in any one of the FDRs was not associated with overall cancer risk, FHBC in both mother and sibling was a significant risk factor for overall cancer (aHR: 1.69, 95% CI:1.11-2.57) and increased the risk of thyroid cancer by 3.41-fold (95% CI: 1.10-10.61). FHBC in the mother or sister was a significant risk factor for pancreatic, thyroid, prostate and breast cancers in men; therefore, men with FHBC may require more careful BRCA1/2 mutation-related cancer surveillance.

Predicting Breast Cancer Risk for Women Veterans of African Ancestry in the Million Veteran Program

Breast cancer is a leading cause of cancer and, therefore, a major health threat for women in the United States and worldwide. We have seen over the years major advances in breast cancer prevention and care. Breast cancer screening with mammography leads to reduction in breast cancer mortality, and breast cancer prevention treatment with antiestrogens results in reduction in breast cancer incidence. More progress, however, is urgently needed for this common cancer that affects 1 in 11 American women in their lifetime. Not all women have the same breast cancer risk. A personalized approach is highly desirable as women with higher breast cancer risk may benefit from more intense breast cancer screening and/or prevention intervention while lower risk women may be spared with the cost, inconvenience, and emotional burden of these procedures. In addition to age, demographics, family history, lifestyle, and personal health, genetics is an important determinant of an individual's risk for breast cancer. Over the past 10 years, advances in cancer genomics identified multiple common genetic variants from population studies that collectively can contribute significantly to an individual's breast cancer risk. The effects of these genetic variants can be summarized as a "polygenic risk score" (PRS). We are among the first groups to prospectively evaluate the performance of these risk prediction instruments among women veterans of the Million Veteran Program (MVP). A 313-variant PRS (PRS313) predicted incident breast cancer for a prospective cohort of European (EUR) ancestry women veterans with an area under the receiver operating characteristic curve (AUC) of 0.622. The PRS313 performed less well for AFR ancestry however, with an AUC of 0.579. This is not surprising as most genome-wide association studies were conducted in people of European ancestry. This is an important area of health disparity and unmet need. The large population size and diversity of the MVP provide a unique and important opportunity to explore novel approaches to produce accurate and clinically useful genetic risk prediction instruments for minority populations.

Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival

PURPOSE

A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer.

METHODS

Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.

RESULTS

The PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.

CONCLUSION

An increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.

Predicting Cancer Risk from Germline Whole-exome Sequencing Data Using a Novel Context-based Variant Aggregation Approach

Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new direction of research has focused on extracting signals from the contexts of germline variants and evidence has emerged that patterns defined by these factors are associated with oncogenic pathways, histologic subtypes, and prognosis. It remains an open question whether aggregating germline variants using meta-features capturing their genomic, nucleotide, and epigenetic contexts can improve cancer risk prediction. This aggregation approach can potentially increase statistical power for detecting signals from rare variants, which have been hypothesized to be a major source of the missing heritability of cancer. Using germline whole-exome sequencing data from the UK Biobank, we developed risk models for 10 cancer types using known risk variants (cancer-associated SNPs and pathogenic variants in known cancer predisposition genes) as well as models that additionally include the meta-features. The meta-features did not improve the prediction accuracy of models based on known risk variants. It is possible that expanding the approach to whole-genome sequencing can lead to gains in prediction accuracy.

Significance

There is evidence that cancer is partly caused by rare genetic variants that have not yet been identified. We investigate this issue using novel statistical methods and data from the UK Biobank.

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

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.

Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study

PURPOSE

This study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study.

METHODS

Using publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell's C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years).

RESULTS

For the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method with P_T = 0.05 and R² = 0.2) derived from Japanese-ancestry GWAS, the Harrell's C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64-3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell's C-statistics 0.598 versus 0.586).

CONCLUSION

This study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.

Models of communication for polygenic scores and associated psychosocial and behavioral effects on recipients: A systematic review

PURPOSE

This study aimed to systematically review current models for communicating polygenic scores (PGS) and psycho-behavioral outcomes of receiving PGSs.

METHODS

Original research on communicating PGSs and reporting on psycho-behavioral outcomes was included. Search terms were applied to 5 databases and were limited by date (2009-2021).

RESULTS

In total, 28 articles, representing 17 studies in several disease settings were identified. There was limited consistency in PGS communication and evaluation/reporting of outcomes. Most studies (n = 14) presented risk in multiple ways (ie, numerically, verbally, and/or visually). Three studies provided personalized lifestyle advice and additional resources. Only 1 of 17 studies reported using behavior change theory to inform their PGS intervention. A total of 8 studies found no evidence of long-term negative psychosocial effects up to 12 months post result. Of 14 studies reporting on behavior, 9 found at least 1 favorable change after PGS receipt. When stratified by risk, 7 out of 9 studies found high PGS was associated with favorable changes including lifestyle, medication, and screening. Low-risk PGS was not associated with maladaptive behaviors (n = 4).

CONCLUSION

PGS has the potential to benefit health behavior. High variability among studies emphasizes the need for developing standardized guidelines for communicating PGSs and evaluating psycho-behavioral outcomes. Our findings call for development of best communication practices and evidence-based interventions informed by behavior change theories.

The current state of genetic risk models for the development of kidney cancer: a review and validation

OBJECTIVE

To review the current state of genetic risk models for predicting the development of kidney cancer, by identifying and comparing the performance of published models.

METHODS

Risk models were identified from a recent systematic review and the Cancer-PRS web directory. A narrative synthesis of the models, previous validation studies and related genome-wide association studies (GWAS) was carried out. The discrimination and calibration of the identified models was then assessed and compared in the UK Biobank (UKB) cohort (cases, 452; controls, 487 925).

RESULTS

A total of 39 genetic models predicting the development of kidney cancer were identified and 31 were validated in the UKB. Several of the genetic-only models (seven of 25) and most of the mixed genetic-phenotypic models (five of six) had some discriminatory ability (area under the receiver operating characteristic curve >0.5) in this cohort. In general, models containing a larger number of genetic variants identified in GWAS performed better than models containing a small number of variants associated with known causal pathways. However, the performance of the included models was consistently poorer than genetic risk models for other cancers.

CONCLUSIONS

Although there is potential for genetic models to identify those at highest risk of developing kidney cancer, their performance is poorer than the best genetic risk models for other cancers. This may be due to the comparatively small number of genetic variants associated with kidney cancer identified in GWAS to date. The development of improved genetic risk models for kidney cancer is dependent on the identification of more variants associated with this disease. Whether these will have utility within future kidney cancer screening pathways is yet to determined.

Is early-onset cancer an emerging global epidemic? Current evidence and future implications

Over the past several decades, the incidence of early-onset cancers, often defined as cancers diagnosed in adults <50 years of age, in the breast, colorectum, endometrium, oesophagus, extrahepatic bile duct, gallbladder, head and neck, kidney, liver, bone marrow, pancreas, prostate, stomach and thyroid has increased in multiple countries. Increased use of screening programmes has contributed to this phenomenon to a certain extent, although a genuine increase in the incidence of early-onset forms of several cancer types also seems to have emerged. Evidence suggests an aetiological role of risk factor exposures in early life and young adulthood. Since the mid-20th century, substantial multigenerational changes in the exposome have occurred (including changes in diet, lifestyle, obesity, environment and the microbiome, all of which might interact with genomic and/or genetic susceptibilities). However, the effects of individual exposures remain largely unknown. To study early-life exposures and their implications for multiple cancer types will require prospective cohort studies with dedicated biobanking and data collection technologies. Raising awareness among both the public and health-care professionals will also be critical. In this Review, we describe changes in the incidence of early-onset cancers globally and suggest measures that are likely to reduce the burden of cancers and other chronic non-communicable diseases.

Family history of breast cancer, mammographic breast density and breast cancer risk: Findings from a cohort study of Korean women

BACKGROUND

This study investigated whether the association between family history of breast cancer in first-degree relatives and breast cancer risk varies by breast density.

METHODS

Women aged 40 years and older who underwent screening between 2009 and 2010 were followed up until 2020. Family history was assessed using a self-reported questionnaire. Using Breast Imaging Reporting and Data System (BI-RADS), breast density was categorized into dense breast (heterogeneously or extremely dense) and non-dense breast (almost entirely fatty or scattered areas of fibro-glandular). Cox regression model was used to assess the association between family history and breast cancer risk.

RESULTS

Of the 4,835,507 women, 79,153 (1.6%) reported having a family history of breast cancer and 77,238 women developed breast cancer. Family history led to an increase in the 5-year cumulative incidence in women with dense- and non-dense breasts. Results from the regression model with and without adjustment for breast density yielded similar HRs in all age groups, suggesting that breast density did not modify the association between family history and breast cancer. After adjusting for breast density and other factors, family history of breast cancer was associated with an increased risk of breast cancer in all three age groups (age 40-49 years: aHR 1.96, 95% confidence interval [CI] 1.85-2.08; age 50-64 years: aHR 1.70, 95% CI 1.58-1.82, and age ≥65 years: aHR 1.95, 95% CI 1.78-2.14).

CONCLUSION

Family history of breast cancer and breast density are independently associated with breast cancer. Both factors should be carefully considered in future risk prediction models of breast cancer.

Feasibility and Acceptability of Personalized Breast Cancer Screening (DECIDO Study): A Single-Arm Proof-of-Concept Trial

The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40-50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.

Influence of germline test results on surgical decision making in women with invasive breast cancer

BACKGROUND

While therapeutic mastectomy with contralateral prophylactic mastectomy (TM+CPM) and/or bilateral salpingo-oophorectomy (BSO) are recommended for women with pathogenic variants (PV) in some cancer predisposition genes, evidence for the utility of these surgeries for women with PV in other genes currently is insufficient. In conjunction, current guidelines recommend that clinical management should not be influenced by a return of a variant of uncertain significance (VUS). Return of germline test results may, however, influence surgical decision making regardless of current guidelines. We thus evaluated surgical choices amongst a cohort of women with invasive breast cancer who underwent clinical genetic testing.

METHODS

Germline test results and all surgical procedures were extracted for women who had unilateral invasive breast cancer and had clinical testing before definitive surgery (n = 591). Results were classified as pathogenic/likely pathogenic (PV, 17.1%), VUS (19.5%) or benign/likely benign (63.4%). Data were analyzed using chi-square tests with p<0.05 defining significance.

RESULTS

Rates of TM+CPM and BSO were not significantly different for women with VUS compared to those with benign findings. Rates of TM+CPM were significantly higher for women with PV in BRCA1 and BRCA2, PALB2, PTEN and TP53, as well in genes with insufficient data to recommend risk-reducing mastectomy. Rates of BSO were significantly higher in women with PV in BRCA1 and BRCA2, PALB2, PTEN and TP53 and BRIP1, RAD51C and RAD51D compared to those with benign findings.

CONCLUSION

Overall, surgical choices for women with a VUS were more similar to those from women with benign variants than to those with PV, however, in the group with PV in genes for which insufficient evidence exists for the benefit of risk-reducing mastectomy, rates of TM+CPM were high. Thus, while the management of women with VUS is in agreement with ACMG guidelines, patients with mutations in other cancer genes demonstrate a preference for more aggressive breast surgeries.

The role of common genetic variation in presumed monogenic epilepsies

BACKGROUND

The developmental and epileptic encephalopathies (DEEs) are the most severe group of epilepsies which co-present with developmental delay and intellectual disability (ID). DEEs usually occur in people without a family history of epilepsy and have emerged as primarily monogenic, with damaging rare mutations found in 50% of patients. Little is known about the genetic architecture of patients with DEEs in whom no pathogenic variant is identified. Polygenic risk scoring (PRS) is a method that measures a person's common genetic burden for a trait or condition. Here, we used PRS to test whether genetic burden for epilepsy is relevant in individuals with DEEs, and other forms of epilepsy with ID.

METHODS

Genetic data on 2,759 cases with DEEs, or epilepsy with ID presumed to have a monogenic basis, and 447,760 population-matched controls were analysed. We compared PRS for 'all epilepsy', 'focal epilepsy', and 'genetic generalised epilepsy' (GGE) between cases and controls. We performed pairwise comparisons between cases stratified for identifiable rare deleterious genetic variants and controls.

FINDINGS

Cases of presumed monogenic severe epilepsy had an increased PRS for 'all epilepsy' (p<0.0001), 'focal epilepsy' (p<0.0001), and 'GGE' (p=0.0002) relative to controls, which explain between 0.08% and 3.3% of phenotypic variance. PRS was increased in cases both with and without an identified deleterious variant of major effect, and there was no significant difference in PRS between the two groups.

INTERPRETATION

We provide evidence that common genetic variation contributes to the aetiology of DEEs and other forms of epilepsy with ID, even when there is a known pathogenic variant of major effect. These results provide insight into the genetic underpinnings of the severe epilepsies and warrant a shift in our understanding of the aetiology of the DEEs as complex, rather than monogenic, disorders.

FUNDING

Science foundation Ireland, Human Genome Research Institute; National Heart, Lung, and Blood Institute; German Research Foundation.

Induced mammary cancer in rat models: pathogenesis, genetics, and relevance to female breast cancer

Mammary cancer, or breast cancer in women, is a polygenic disease with a complex etiopathogenesis. While much remains elusive regarding its origin, it is well established that chemical carcinogens and endogenous estrogens contribute significantly to the initiation and progression of this disease. Rats have been useful models to study induced mammary cancer. They develop mammary tumors with comparable histopathology to humans and exhibit differences in resistance or susceptibility to mammary cancer depending on strain. While some rat strains (e.g., Sprague-Dawley) readily form mammary tumors following treatment with the chemical carcinogen, 7,12-dimethylbenz[a]-anthracene (DMBA), other strains (e.g., Copenhagen) are resistant to DMBA-induced mammary carcinogenesis. Genetic linkage in inbred strains has identified strain-specific quantitative trait loci (QTLs) affecting mammary tumors, via mechanisms that act together to promote or attenuate, and include 24 QTLs controlling the outcome of chemical induction, 10 QTLs controlling the outcome of estrogen induction, and 4 QTLs controlling the outcome of irradiation induction. Moreover, and based on shared factors affecting mammary cancer etiopathogenesis between rats and humans, including orthologous risk regions between both species, rats have served as useful models for identifying methods for breast cancer prediction and treatment. These studies in rats, combined with alternative animal models that more closely mimic advanced stages of breast cancer and/or human lifestyles, will further improve our understanding of this complex disease.

Prediction of Breast Cancer using Machine Learning Approaches

BACKGROUND

Breast cancer is considered one of the most common cancers in women caused by various clinical, lifestyle, social, and economic factors. Machine learning has the potential to predict breast cancer based on features hidden in data.

OBJECTIVE

This study aimed to predict breast cancer using different machine-learning approaches applying demographic, laboratory, and mammographic data.

MATERIAL AND METHODS

In this analytical study, the database, including 5,178 independent records, 25% of which belonged to breast cancer patients with 24 attributes in each record was obtained from Motamed cancer institute (ACECR), Tehran, Iran. The database contained 5,178 independent records, 25% of which belonged to breast cancer patients containing 24 attributes in each record. The random forest (RF), neural network (MLP), gradient boosting trees (GBT), and genetic algorithms (GA) were used in this study. Models were initially trained with demographic and laboratory features (20 features). The models were then trained with all demographic, laboratory, and mammographic features (24 features) to measure the effectiveness of mammography features in predicting breast cancer.

RESULTS

RF presented higher performance compared to other techniques (accuracy 80%, sensitivity 95%, specificity 80%, and the area under the curve (AUC) 0.56). Gradient boosting (AUC=0.59) showed a stronger performance compared to the neural network.

CONCLUSION

Combining multiple risk factors in modeling for breast cancer prediction could help the early diagnosis of the disease with necessary care plans. Collection, storage, and management of different data and intelligent systems based on multiple factors for predicting breast cancer are effective in disease management.

Personalised Risk Prediction in Hereditary Breast and Ovarian Cancer: A Protocol for a Multi-Centre Randomised Controlled Trial

Women who test positive for an inherited pathogenic/likely pathogenic gene variant in BRCA1, BRCA2, PALB2, CHEK2 and ATM are at an increased risk of developing certain types of cancer-specifically breast (all) and epithelial ovarian cancer (only BRCA1, BRCA2, PALB2). Women receive broad cancer risk figures that are not personalised (e.g., 44-63% lifetime risk of breast cancer for those with PALB2). Broad, non-personalised risk estimates may be problematic for women when they are considering how to manage their risk. Multifactorial-risk-prediction tools have the potential to deliver personalised risk estimates. These may be useful in the patient's decision-making process and impact uptake of risk-management options. This randomised control trial (registration number to follow), based in genetic centres in the UK and US, will randomise participants on a 1:1 basis to either receive conventional cancer risk estimates, as per routine clinical practice, or to receive a personalised risk estimate. This personalised risk estimate will be calculated using the CanRisk risk prediction tool, which combines the patient's genetic result, family history and polygenic risk score (PRS), along with hormonal and lifestyle factors. Women's decision-making around risk management will be monitored using questionnaires, completed at baseline (pre-appointment) and follow-up (one, three and twelve months after receiving their risk assessment). The primary outcome for this study is the type and timing of risk management options (surveillance, chemoprevention, surgery) taken up over the course of the study (i.e., 12 months). The type of risk-management options planned to be taken up in the future (i.e., beyond the end of the study) and the potential impact of personalised risk estimates on women's psychosocial health will be collected as secondary-outcome measures. This study will also assess the acceptability, feasibility and cost-effectiveness of using personalised risk estimates in clinical care.

The Emerging Roles of Long Non-Coding RNAs in Intellectual Disability and Related Neurodevelopmental Disorders

In the human brain, long non-coding RNAs (lncRNAs) are widely expressed in an exquisitely temporally and spatially regulated manner, thus suggesting their contribution to normal brain development and their probable involvement in the molecular pathology of neurodevelopmental disorders (NDD). Bypassing the classic protein-centric conception of disease mechanisms, some studies have been conducted to identify and characterize the putative roles of non-coding sequences in the genetic pathogenesis and diagnosis of complex diseases. However, their involvement in NDD, and more specifically in intellectual disability (ID), is still poorly documented and only a few genomic alterations affecting the lncRNAs function and/or expression have been causally linked to the disease endophenotype. Considering that a significant fraction of patients still lacks a genetic or molecular explanation, we expect that a deeper investigation of the non-coding genome will unravel novel pathogenic mechanisms, opening new translational opportunities. Here, we present evidence of the possible involvement of many lncRNAs in the etiology of different forms of ID and NDD, grouping the candidate disease-genes in the most frequently affected cellular processes in which ID-risk genes were previously collected. We also illustrate new approaches for the identification and prioritization of NDD-risk lncRNAs, together with the current strategies to exploit them in diagnosis.

Genetic clinicians' confidence in BOADICEA comprehensive breast cancer risk estimates and counselees' psychosocial outcomes: a prospective study

Counseling for familial breast cancer focuses on communicating the gene test result (GENE) to counselees, but risk prediction models have become more complex by including non‐genetic risk factors (NGRF) and polygenic risk scores (PRS). We examined genetic clinicians' confidence in counseling and counselees' psychosocial outcomes, using the BOADICEA risk prediction tool with different categories of risk factors as input. A prospective observational study in Dutch, French and German genetic clinics was performed including 22 clinicians, and 406 of 460 (88.3%) eligible cancer‐unaffected women at high breast cancer risk assessed at pre‐test and 350 (76.1%) at post‐test. We performed multilevel analyses accounting for the clinician, and counselees' characteristics. Overall, risk estimates category by GENE versus GENE+ NGRF, or GENE+NGRF+PRS differed in 11% and 25% of counselees, respectively. In multilevel analyses, clinicians felt less confident in counseling when the full model provided lower breast cancer risks than GENE (i.e., in 8% of cases). Older counselees expressed higher breast cancer risk perception and worries about the hereditary predisposition when the full model provided higher breast cancer risks than GENE only. Genetic clinicians appear confident with breast cancer risk comprehensive models, which seem only to affect perceptions of older counselees.

[Moving toward personalized breast cancer screening: The role of Primary Care]

Breast cancer is the leading cause of death in the world among women. The Spanish National Health System (SNHS) introduced population-based breast cancer screening in 2006. As in most European programs, risk is identified on the basis of age and a mammogram is offered every two years to women aged 50-69 years. Scientific evidence is moving toward personalized screening, based on individual risk. This article presents the clinical trials that will evaluate the efficacy of personalized screening and some studies carried out in our environment on the effect of informing women of the benefits and adverse effects of screening or the acceptability and feasibility of offering personalized screening, in the Shared Decision Making context. The Preventive Activities and Health Promotion Program can help transform screening in our SNHS.

BREAst screening Tailored for HEr (BREATHE)-A study protocol on personalised risk-based breast cancer screening programme

Routine mammography screening is currently the standard tool for finding cancers at an early stage, when treatment is most successful. Current breast screening programmes are one-size-fits-all which all women above a certain age threshold are encouraged to participate. However, breast cancer risk varies by individual. The BREAst screening Tailored for HEr (BREATHE) study aims to assess acceptability of a comprehensive risk-based personalised breast screening in Singapore. Advancing beyond the current age-based screening paradigm, BREATHE integrates both genetic and non-genetic breast cancer risk prediction tools to personalise screening recommendations. BREATHE is a cohort study targeting to recruit ~3,500 women. The first recruitment visit will include questionnaires and a buccal cheek swab. After receiving a tailored breast cancer risk report, participants will attend an in-person risk review, followed by a final session assessing the acceptability of our risk stratification programme. Risk prediction is based on: a) Gail model (non-genetic), b) mammographic density and recall, c) BOADICEA predictions (breast cancer predisposition genes), and d) breast cancer polygenic risk score. For national implementation of personalised risk-based breast screening, exploration of the acceptability within the target populace is critical, in addition to validated predication tools. To our knowledge, this is the first study to implement a comprehensive risk-based mammography screening programme in Asia. The BREATHE study will provide essential data for policy implementation which will transform the health system to deliver a better health and healthcare outcomes.

Genome-wide risk prediction of common diseases across ancestries in one million people

Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.

Development and validation of polygenic risk scores for prediction of breast cancer and breast cancer subtypes in Chinese women

Background

Studies investigating breast cancer polygenic risk score (PRS) in Chinese women are scarce. The objectives of this study were to develop and validate PRSs that could be used to stratify risk for overall and subtype-specific breast cancer in Chinese women, and to evaluate the performance of a newly proposed Artificial Neural Network (ANN) based approach for PRS construction.

Methods

The PRSs were constructed using the dataset from a genome-wide association study (GWAS) and validated in an independent case-control study. Three approaches, including repeated logistic regression (RLR), logistic ridge regression (LRR) and ANN based approach, were used to build the PRSs for overall and subtype-specific breast cancer based on 24 selected single nucleotide polymorphisms (SNPs). Predictive performance and calibration of the PRSs were evaluated unadjusted and adjusted for Gail-2 model 5-year risk or classical breast cancer risk factors.

Results

The primary PRS_ANN and PRS_LRR both showed modest predictive ability for overall breast cancer (odds ratio per interquartile range increase of the PRS in controls [IQ-OR] 1.76 vs 1.58; area under the receiver operator characteristic curve [AUC] 0.601 vs 0.598) and remained to be predictive after adjustment. Although estrogen receptor negative (ER⁻) breast cancer was poorly predicted by the primary PRSs, the ER⁻ PRSs trained solely on ER⁻ breast cancer cases saw a substantial improvement in predictions of ER⁻ breast cancer.

Conclusions

The 24 SNPs based PRSs can provide additional risk information to help breast cancer risk stratification in the general population of China. The newly proposed ANN approach for PRS construction has potential to replace the traditional approaches, but more studies are needed to validate and investigate its performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09425-3.

Health influenced by genetics: A first comprehensive analysis of breast cancer high and moderate penetrance susceptibility genes in the Tunisian population

Significant advances have been made to understand the genetic basis of breast cancer. High, moderate and low penetrance variants have been identified with inter-ethnic variability in mutation frequency and spectrum. Genome wide association studies (GWAS) are widely used to identify disease-associated SNPs. Understanding the functional impact of these risk-SNPs will help the translation of GWAS findings into clinical interventions. Here we aim to characterize the genetic patterns of high and moderate penetrance breast cancer susceptibility genes and to assess the functional impact of non-coding SNPs. We analyzed BRCA1/2, PTEN, STK11, TP53, ATM, BRIP1, CHEK2 and PALB2 genotype data obtained from 135 healthy participants genotyped using Affymetrix Genome-Wide Human SNP-Array 6.0. Haplotype analysis was performed using Haploview.V4.2 and PHASE.V2.1. Population structure and genetic differentiation were assessed using principal component analysis (PCA) and fixation index (FST). Functional annotation was performed using In Silico web-based tools including RegulomeDB and VARAdb. Haplotype analysis showed distinct LD patterns with high levels of recombination and haplotype blocks of moderate to small size. Our findings revealed also that the Tunisian population tends to have a mixed origin with European, South Asian and Mexican footprints. Functional annotation allowed the selection of 28 putative regulatory variants. Of special interest were BRCA1_ rs8176318 predicted to alter the binding sites of a tumor suppressor miRNA hsa-miR-149 and PALB2_ rs120963 located in tumorigenesis-associated enhancer and predicted to strongly affect the binding of P53. Significant differences in allele frequencies were observed with populations of African and European ancestries for rs8176318 and rs120963 respectively. Our findings will help to better understand the genetic basis of breast cancer by guiding upcoming genome wide studies in the Tunisian population. Putative functional SNPs may be used to develop an efficient polygenic risk score to predict breast cancer risk leading to better disease prevention and management.