European polygenic risk score for prediction of breast cancer shows similar performance in Asian women

Characterizing the Relationship between Expression Quantitative Trait Loci (eQTLs), DNA Methylation Quantitative Trait Loci (mQTLs), and Breast Cancer Risk Variants

PURPOSE

To assess the association of a polygenic risk score (PRS) for functional genetic variants with the risk of developing breast cancer.

METHODS

Summary data-based Mendelian randomization (SMR) and heterogeneity in dependent instruments (HEIDI) were used to identify breast cancer risk variants associated with gene expression and DNA methylation levels. A new SMR-based PRS was computed from the identified variants (functional PRS) and compared to an established 313-variant breast cancer PRS (GWAS PRS). The two scores were evaluated in 3560 breast cancer cases and 3383 non-cancer controls and also in a prospective study (n = 10,213) comprising 418 cases.

RESULTS

We identified 149 variants showing pleiotropic association with breast cancer risk (eQTLHEIDI > 0.05 = 9, mQTLHEIDI > 0.05 = 165). The discriminatory ability of the functional PRS (AUCcontinuous [95% CI]: 0.540 [0.526 to 0.553]) was found to be lower than that of the GWAS PRS (AUCcontinuous [95% CI]: 0.609 [0.596 to 0.622]). Even when utilizing 457 distinct variants from both the functional and GWAS PRS, the combined discriminatory performance remained below that of the GWAS PRS (AUCcontinuous, combined [95% CI]: 0.561 [0.548 to 0.575]). A binary high/low-risk classification based on the 80th centile PRS in controls revealed a 6% increase in cases using the GWAS PRS compared to the functional PRS. The functional PRS identified an additional 12% of high-risk cases but also led to a 13% increase in high-risk classification among controls. Similar findings were observed in the SCHS prospective cohort, where the GWAS PRS outperformed the functional PRS, and the highest-performing PRS, a combined model, did not significantly improve over the GWAS PRS.

CONCLUSIONS

While this study identified potentially functional variants associated with breast cancer risk, their inclusion did not substantially enhance the predictive accuracy of the GWAS PRS.

Comprehensive Inherited Risk Estimation for Risk-Based Breast Cancer Screening in Women

PURPOSE

Family history (FH) and pathogenic variants (PVs) are used for guiding risk surveillance in selected high-risk women but little is known about their impact for breast cancer screening on population level. In addition, polygenic risk scores (PRSs) have been shown to efficiently stratify breast cancer risk through combining information about common genetic factors into one measure.

METHODS

In longitudinal real-life data, we evaluate PRS, FH, and PVs for stratified screening. Using FinnGen (N = 117,252), linked to the Mass Screening Registry for breast cancer (1992-2019; nationwide organized biennial screening for age 50-69 years), we assessed the screening performance of a breast cancer PRS and compared its performance with FH of breast cancer and PVs in moderate- (CHEK2)- to high-risk (PALB2) susceptibility genes.

RESULTS

Effect sizes for FH, PVs, and high PRS (>90th percentile) were comparable in screening-aged women, with similar implications for shifting age at screening onset. A high PRS identified women more likely to be diagnosed with breast cancer after a positive screening finding (positive predictive value [PPV], 39.5% [95% CI, 37.6 to 41.5]). Combinations of risk factors increased the PPVs up to 45% to 50%. A high PRS conferred an elevated risk of interval breast cancer (hazard ratio [HR], 2.78 [95% CI, 2.00 to 3.86] at age 50 years; HR, 2.48 [95% CI, 1.67 to 3.70] at age 60 years), and women with a low PRS (<10th percentile) had a low risk for both interval- and screen-detected breast cancers.

CONCLUSION

Using real-life screening data, this study demonstrates the effectiveness of a breast cancer PRS for risk stratification, alone and combined with FH and PVs. Further research is required to evaluate their impact in a prospective risk-stratified screening program, including cost-effectiveness.

Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes

Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction

The 313-variant polygenic risk score (PRS313) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.

Integrating a Polygenic Risk Score into a clinical setting would impact risk predictions in familial breast cancer

BACKGROUND

Low-impact genetic variants identified in population-based genetic studies are not routinely measured as part of clinical genetic testing in familial breast cancer (BC). We studied the consequences of integrating an established Polygenic Risk Score (PRS) (BCAC 313, PRS313) into clinical sequencing of women with familial BC in Sweden.

METHODS

We developed an add-on sequencing panel to capture 313 risk variants in addition to the clinical screening of hereditary BC genes. Index patients with no pathogenic variant from 87 families, and 1000 population controls, were included in comparative PRS calculations. Including detailed family history, sequencing results and tumour pathology information, we used BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.6 to estimate contralateral and lifetime risks without and with PRS313.

RESULTS

Women with BC but no pathogenic variants in hereditary BC genes have a higher PRS313 compared with population controls (mean+0.78 SD, p<3e-9). Implementing PRS313 in the clinical risk estimation before their BC diagnosis would have changed the recommended follow-up in 24%-45% of women.

CONCLUSIONS

Our results show the potential impact of incorporating PRS313 directly in the clinical genomic investigation of women with familial BC.

Polygenic risk score model for renal cell carcinoma in the Korean population and relationship with lifestyle-associated factors

BACKGROUND

The polygenic risk score (PRS) is used to predict the risk of developing common complex diseases or cancers using genetic markers. Although PRS is used in clinical practice to predict breast cancer risk, it is more accurate for Europeans than for non-Europeans because of the sample size of training genome-wide association studies (GWAS). To address this disparity, we constructed a PRS model for predicting the risk of renal cell carcinoma (RCC) in the Korean population.

RESULTS

Using GWAS analysis, we identified 43 Korean-specific variants and calculated the PRS. Subsequent to plotting receiver operating characteristic (ROC) curves, we selected the 31 best-performing variants to construct an optimal PRS model. The resultant PRS model with 31 variants demonstrated a prediction rate of 77.4%. The pathway analysis indicated that the identified non-coding variants are involved in regulating the expression of genes related to cancer initiation and progression. Notably, favorable lifestyle habits, such as avoiding tobacco and alcohol, mitigated the risk of RCC across PRS strata expressing genetic risk.

CONCLUSION

A Korean-specific PRS model was established to predict the risk of RCC in the underrepresented Korean population. Our findings suggest that lifestyle-associated factors influencing RCC risk are associated with acquired risk factors indirectly through epigenetic modification, even among individuals in the higher PRS category.

Principles and methods for transferring polygenic risk scores across global populations

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

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.

Evaluation of optimal methods and ancestries for calculating polygenic risk scores in East Asian population

Polygenic risk scores (PRSs) have been studied for predicting human diseases, and various methods for PRS calculation have been developed. Most PRS studies to date have focused on European ancestry, and the performance of PRS has not been sufficiently assessed in East Asia. Herein, we evaluated the predictive performance of PRSs for East Asian populations under various conditions. Simulation studies using data from the Korean cohort, Health Examinees (HEXA), demonstrated that SBayesRC and PRS-CS outperformed other PRS methods (lassosum, LDpred-funct, and PRSice) in high fixed heritability (0.3 and 0.7). In addition, we generated PRSs using real-world data from HEXA for ten diseases: asthma, breast cancer, cataract, coronary artery disease, gastric cancer, glaucoma, hyperthyroidism, hypothyroidism, osteoporosis, and type 2 diabetes (T2D). We utilized the five previous PRS methods and genome-wide association study (GWAS) data from two biobank-scale datasets [European (UK Biobank) and East Asian (BioBank Japan) ancestry]. Additionally, we employed PRS-CSx, a PRS method that combines GWAS data from both ancestries, to generate a total of 110 PRS for ten diseases. Similar to the simulation results, SBayesRC showed better predictive performance for disease risk than the other methods. Furthermore, the East Asian GWAS data outperformed those from European ancestry for breast cancer, cataract, gastric cancer, and T2D, but neither of the two GWAS ancestries showed a significant advantage on PRS performance for the remaining six diseases. Based on simulation data and real data studies, it is expected that SBayesRC will offer superior performance for East Asian populations, and PRS generated using GWAS from non-East Asian may also yield good results.

From Hazard Rate to Age-at-Onset Distribution: Mind the Gap

A recent study published in the journal claimed that genetic susceptibility to breast cancer occurs mainly due to rare inherited variants. The claim relies on a set of deductive arguments following observations on patterns of age-at-onset distribution of the disease among twin pairs. In this brief commentary, we point out a major gap in the given argument due to the interchangeable use of hazard rates and age-at-onset distribution, and thus conclude that the published study does not provide any evidence against polygenic risk of breast cancer due to common variants. See related article by Yasui et al., p. 1518.

Early breast cancer risk detection: a novel framework leveraging polygenic risk scores and machine learning

BACKGROUND

Breast cancer (BC) is the most common cancer and the second leading cause of cancer death in women; an estimated one in eight women in the USA will develop BC during her lifetime. However, current methods of BC screening, including clinical breast exams, mammograms, biopsies and others, are often underused due to limited access, expense and a lack of risk awareness, causing 30% (up to 80% in low-income and middle-income countries) of patients with BC to miss the precious early detection phase.

METHODS

This study creates a key step to supplement the current BC diagnostic pipeline: a prescreening platform, prior to traditional detection and diagnostic steps. We have developed BREast CAncer Risk Detection Application (BRECARDA), a novel framework that personalises BC risk assessment using artificial intelligence neural networks to incorporate relevant genetic and non-genetic risk factors. A polygenic risk score (PRS) was enhanced by employing AnnoPred and validated by fivefolds cross-validation, outperforming three existing state-of-the-art PRS methods.

RESULTS

We used data from 97 597 female participants of the UK BioBank to train our algorithm. Using the enhanced PRS thus trained together with non-genetic information, BRECARDA was evaluated in a testing dataset with 48 074 UK Biobank female participants and achieved a high accuracy of 94.28% and area under the curve of 0.7861. Our optimised AnnoPred outperformed other state-of-the-art methods on quantifying genetic risk, indicating its potential for supplementing the current BC detection tests, population screening and risk evaluation.

CONCLUSION

BRECARDA can enhance disease risk prediction, identify high-risk individuals for BC screening, facilitate disease diagnosis and improve population-level screening efficiency. It can serve as a valuable and supplemental platform to assist doctors in BC diagnosis and evaluation.

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.

Polygenic scores in cancer

Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.

Breast cancer polygenic risk scores derived in White European populations are not calibrated for women of Ashkenazi Jewish descent

PURPOSE

Polygenic risk scores (PRSs) are a major component of accurate breast cancer (BC) risk prediction but require ethnicity-specific calibration. Ashkenazi Jewish (AJ) population is assumed to be of White European (WE) origin in some commercially available PRSs despite differing effect allele frequencies (EAFs). We conducted a case-control study of WE and AJ women from the Predicting Risk of Cancer at Screening Study. The Breast Cancer in Northern Israel Study provided a separate AJ population-based case-control validation series.

METHODS

All women underwent Illumina OncoArray single-nucleotide variation (SNV; formerly single-nucleotide polymorphism [SNP]) analysis. Two PRSs were assessed, SNV142 and SNV78. A total of 221 of 2243 WE women (discovery: cases = 111; controls = 110; validation: cases = 651; controls = 1772) and 221 AJ women (cases = 121; controls = 110) were included from the UK study; the Israeli series consisted of 2045 AJ women (cases = 1331; controls = 714). EAFs were obtained from the Genome Aggregation Database.

RESULTS

In the UK study, the mean SNV142 PRS demonstrated good calibration and discrimination in WE population, with mean PRS of 1.33 (95% CI 1.18-1.48) in cases and 1.01 (95% CI 0.89-1.13) in controls. In AJ women from Manchester, the mean PRS of 1.54 (1.38-1.70) in cases and 1.20 (1.08-1.32) in controls demonstrated good discrimination but overestimation of BC relative risk. After adjusting for EAFs for the AJ population, mean risk was corrected (mean SNV142 PRS cases = 1.30 [95% CI 1.16-1.44] and controls = 1.02 [95% CI 0.92-1.12]). This was recapitulated in the larger Israeli data set with good discrimination (area under the curve = 0.632 [95% CI 0.607-0.657] for SNV142).

CONCLUSION

AJ women should not be given BC relative risk predictions based on PRSs calibrated to EAFs from the WE population. PRSs need to be recalibrated using AJ-derived EAFs. A simple recalibration using the mean PRS adjustment ratio likely performs well.

Clinical Impact of Polygenic Risk Score for Breast Cancer Risk Prediction in 382 Individuals with Hereditary Breast and Ovarian Cancer Syndrome

Single nucleotide polymorphisms are currently not considered in breast cancer (BC) risk predictions used in daily practice of genetic counselling and clinical management of familial BC in Germany. This study aimed to assess the clinical value of incorporating a 313-variant-based polygenic risk score (PRS) into BC risk calculations in a cohort of German women with suspected hereditary breast and ovarian cancer syndrome (HBOC). Data from 382 individuals seeking counselling for HBOC were analysed. Risk calculations were performed using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm with and without the inclusion of the PRS. Changes in risk predictions and their impact on clinical management were evaluated. The PRS led to changes in risk stratification based on 10-year risk calculations in 13.6% of individuals. Furthermore, the inclusion of the PRS in BC risk predictions resulted in clinically significant changes in 12.0% of cases, impacting the prevention recommendations established by the German Consortium for Hereditary Breast and Ovarian Cancer. These findings support the implementation of the PRS in genetic counselling for personalized BC risk assessment.

Assessing the performance of European-derived cardiometabolic polygenic risk scores in South-Asians and their interplay with family history

BACKGROUND & AIMS

We aimed to assess the performance of European-derived polygenic risk scores (PRSs) for common metabolic diseases such as coronary artery disease (CAD), obesity, and type 2 diabetes (T2D) in the South Asian (SAS) individuals in the UK Biobank. Additionally, we studied the interaction between PRS and family history (FH) in the same population.

METHODS

To calculate the PRS, we used a previously published model derived from the EUR population and applied it to the individuals of SAS ancestry from the UKB study. Each PRS was adjusted according to an individual's genotype location in the principal components (PC) space to derive an ancestry adjusted PRS (aPRS). We calculated the percentiles based on aPRS and stratified individuals into three aPRS categories: low, intermediate, and high. Considering the intermediate-aPRS percentile as a reference, we compared the low and high aPRS categories and generated the odds ratio (OR) estimates. Further, we measured the combined role of aPRS and first-degree family history (FH) in the SAS population.

RESULTS

The risk of developing severe obesity for SAS individuals was almost twofold higher for individuals with high aPRS than for those with intermediate aPRS, with an OR of 1.95 (95% CI = 1.71-2.23, P < 0.01). At the same time, the risk of severe obesity was lower in the low-aPRS group (OR = 0.60, CI = 0.53-0.67, P < 0.01). Results in the same direction were found in the EUR data, where the low-PRS group had an OR of 0.53 (95% CI = 0.51-0.56, P < 0.01) and the high-PRS group had an OR of 2.06 (95% CI = 2.00-2.12, P < 0.01). We observed similar results for CAD and T2D. Further, we show that SAS individuals with a familial history of CAD and T2D with high-aPRS are associated with a higher risk of these diseases, implying a greater genetic predisposition.

CONCLUSION

Our findings suggest that CAD, obesity, and T2D GWAS summary statistics generated predominantly from the EUR population can be potentially used to derive aPRS in SAS individuals for risk stratification. With future GWAS recruiting more SAS participants and tailoring the PRSs towards SAS ancestry, the predictive power of PRS is likely to improve further.

The disparities in prognostic prediction and annualized hazard function in different molecular subtypes between young Chinese and White American women with breast cancer

Background and objectives

The prognostic disparities in different molecular subtypes between young Chinese and White American breast cancer patients remain unclear. The goal of this study was to explore the prognostic differences in different molecular subtypes between Chinese and White American patients aged ≤ 40 years.

Methods

We included Chinese and White female breast cancer patients at or under the age of 40 from the Surveillance, Epidemiology, and End Results database (SEER) and the West China Hospital of Sichuan University. The chi-square test, log-rank test, and Cox proportional hazards model were employed to evaluate the distribution and survival disparities in the two racial/ethnic cohorts and different molecular subtypes. An annualized hazard function was used to calculate the annual failure rate among different molecular subtypes.

Results

This study included 20,859 female breast cancer patients at or under the age of 40, of whom 18,400 were White women and 2,459 were Chinese women. With a median follow-up time of 47 months, the 5-year breast cancer-specific survival (BCSS) rates for young Chinese and White women were 93.9% and 90.0%, respectively (P< 0.001). Molecular subtype was found to be a significant predictor in both young Chinese and White patients (P< 0.001), but different trends were observed in the two racial/ethnic cohorts when exploring the association between BCSS and molecular subtypes. Among young White patients, the hormone receptor (HoR) (+)/epidermal growth factor receptor 2 (HER2) (+) subtype had the best 5-year BCSS rate, while in young Chinese patients, the HoR (+)/HER2 (+) and HoR (+)/HER2 (-) showed comparable survival curves and both showed superior 5-year BCSS than other subtypes. Stratification by molecular subtypes, young Chinese patients demonstrated a superior 5-year BCSS in HoR (+)/HER2 (-) (96.3% vs 92.9%, P< 0.001) and triple-negative subtypes (88% vs 81.7%, P= 0.006) compared to young White American patients, while no significant differences were found in HoR (+)/HER2 (+) and HER2 enriched tumors. The annual hazard function for BCSS showed that there were significantly different trends in the HoR (+)/HER2 (-) and HoR (+)/HER2 (+) subtypes between young Chinese and White patients.

Conclusions

There are disparities in prognosis and annualized hazard function between young Chinese and White females with breast cancer in different molecular subtypes.

Family history and breast cancer risk for Asian women: a systematic review and meta-analysis

BACKGROUND

Studies of women of European ancestry have shown that the average familial relative risk for first-degree relatives of women with breast cancer is approximately twofold, but little is known for Asian women. We aimed to provide evidence for the association between family history and breast cancer risk for Asian women by systematically reviewing published literature.

METHODS

Studies reporting the familial relative risk of breast cancer for Asian women were searched in three online databases and complemented by a manual search. Odds ratios (ORs) for the association between family history and breast cancer risk were pooled across all included studies and by subgroups in terms of the type of family history, age, menopausal status and geographical region.

RESULTS

The pooled OR for women who have a first-degree relative with breast cancer was 2.46 (95% confidence interval [CI]: 2.03, 2.97). There was no evidence that the familial risk differed by the type of affected relative (mother versus sisters), the woman's age (< 50 years versus ≥ 50 years), menopausal status (pre versus post) and geographical region (East and Southeast Asia versus other regions) (all P > 0.3). The pooled ORs for women of Asian ancestry with a family history in any relative were similar for those living in non-Asian countries (2.26, 95% CI: 1.42, 3.59) compared with those living in Asian countries (2.18, 95% CI: 1.85, 2.58).

CONCLUSIONS

Family history of breast cancer is associated with an approximately twofold relative risk of breast cancer for Asian women, which is of similar magnitude to that observed for women of European ancestry. This implies that similar familial factors are implicated in breast cancer risk between women of European and Asian ancestries. Genetic factors are likely to play a substantial role in explaining the breast cancer familial risk for Asian women, as similar risks were observed across different living environments and cultures.

Polygenic risk scores for prediction of breast cancer in Korean women

BACKGROUND

Polygenic risk scores (PRSs) for breast cancer, developed using European and Asian genome-wide association studies (GWAS), have been shown to have good discrimination in Asian women. However, prospective calibration of absolute risk prediction models, based on a PRS or PRS combined with lifestyle, clinical and environmental factors, in Asian women is limited.

METHODS

We consider several PRSs trained using European and/or Asian GWAS. For each PRS, we evaluate the discrimination and calibration of three absolute risk models among 41 031 women from the Korean Cancer Prevention Study (KCPS)-II Biobank: (i) a model using incidence, mortality and risk factor distributions (reference inputs) among US women and European relative risks; (ii) a recalibrated model, using Korean reference but European relative risks; and (iii) a fully Korean-based model using Korean reference and relative risk estimates from KCPS.

RESULTS

All Asian and European PRS improved discrimination over lifestyle, clinical and environmental (Qx) factors in Korean women. US-based absolute risk models overestimated the risks for women aged ≥50 years, and this overestimation was larger for models that only included PRS (expected-to-observed ratio E/O = 1.2 for women <50, E/O = 2.7 for women ≥50). Recalibrated and Korean-based risk models had better calibration in the large, although the risk in the highest decile was consistently overestimated. Absolute risk projections suggest that risk-reducing lifestyle changes would lead to larger absolute risk reductions among women at higher PRS.

CONCLUSIONS

Absolute risk models incorporating PRS trained in European and Asian GWAS and population-appropriate average age-specific incidences may be useful for risk-stratified interventions in Korean women.

TP53 somatic mutations in Asian breast cancer are associated with subtype-specific effects

BACKGROUND

Recent genomics studies of breast cancer in Asian cohorts have found a higher prevalence of TP53 mutations in Asian breast cancer patients relative to Caucasian patients. However, the effect of TP53 mutations on Asian breast tumours has not been comprehensively studied.

METHODS

Here, we report an analysis of 492 breast cancer samples from the Malaysian Breast Cancer cohort where we examined the impact of TP53 somatic mutations in relation to PAM50 subtypes by comparing whole exome and transcriptome data from tumours with mutant and wild-type TP53.

RESULTS

We found that the magnitude of impact of TP53 somatic mutations appears to vary between different subtypes. TP53 somatic mutations were associated with higher HR deficiency scores as well as greater upregulation of gene expression pathways in luminal A and luminal B tumours compared to the basal-like and Her2-enriched subtypes. The only pathways that were consistently dysregulated when comparing tumours with mutant and wild-type TP53 across different subtypes were the mTORC1 signalling and glycolysis pathways.

CONCLUSION

These results suggest that therapies that target TP53 or other downstream pathways may be more effective against luminal A and B tumours in the Asian population.

Clinical applicability of the Polygenic Risk Score for breast cancer risk prediction in familial cases

BACKGROUND

Common low-risk variants are presently not used to guide clinical management of familial breast cancer (BC). We explored the additive impact of a 313-variant-based Polygenic Risk Score (PRS₃₁₃) relative to standard gene testing in non-BRCA1/2 Dutch BC families.

METHODS

We included 3918 BC cases from 3492 Dutch non-BRCA1/2 BC families and 3474 Dutch population controls. The association of the standardised PRS₃₁₃ with BC was estimated using a logistic regression model, adjusted for pedigree-based family history. Family history of the controls was imputed for this analysis. SEs were corrected to account for relatedness of individuals. Using the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.5 model, lifetime risks were retrospectively calculated with and without individual PRS₃₁₃. For 2586 cases and 2584 controls, the carrier status of pathogenic variants (PVs) in ATM, CHEK2 and PALB2 was known.

RESULTS

The family history-adjusted PRS₃₁₃ was significantly associated with BC (per SD OR=1.97, 95% CI 1.84 to 2.11). Including the PRS₃₁₃ in BOADICEA family-based risk prediction would have changed screening recommendations in up to 27%, 36% and 34% of cases according to BC screening guidelines from the USA, UK and the Netherlands (National Comprehensive Cancer Network, National Institute for Health and Care Excellence, and Netherlands Comprehensive Cancer Organisation), respectively. For the population controls, without information on family history, this was up to 39%, 44% and 58%, respectively. Among carriers of PVs in known moderate BC susceptibility genes, the PRS₃₁₃ had the largest impact for CHEK2 and ATM.

CONCLUSIONS

Our results support the application of the PRS₃₁₃ in risk prediction for genetically uninformative BC families and families with a PV in moderate BC risk genes.

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.

Risk-Stratified Breast Cancer Screening Incorporating a Polygenic Risk Score: A Survey of UK General Practitioners’ Knowledge and Attitudes

A polygenic risk score (PRS) quantifies the aggregated effects of common genetic variants in an individual. A ‘personalised breast cancer risk assessment’ combines PRS with other genetic and nongenetic risk factors to offer risk-stratified screening and interventions. Large-scale studies are evaluating the clinical utility and feasibility of implementing risk-stratified screening; however, General Practitioners’ (GPs) views remain largely unknown. This study aimed to explore GPs’: (i) knowledge of risk-stratified screening; (ii) attitudes towards risk-stratified screening; and (iii) preferences for continuing professional development. A cross-sectional online survey of UK GPs was conducted between July–August 2022. The survey was distributed by the Royal College of General Practitioners and via other mailing lists and social media. In total, 109 GPs completed the survey; 49% were not familiar with the concept of PRS. Regarding risk-stratified screening pathways, 75% agreed with earlier and more frequent screening for women at high risk, 43% neither agreed nor disagreed with later and less screening for women at lower-than-average risk, and 55% disagreed with completely removing screening for women at much lower risk. In total, 81% felt positive about the potential impact of risk-stratified screening towards patients and 62% felt positive about the potential impact on their practice. GPs selected training of healthcare professionals as the priority for future risk-stratified screening implementation, preferring online formats for learning. The results suggest limited knowledge of PRS and risk-stratified screening amongst GPs. Training—preferably using online learning formats—was identified as the top priority for future implementation. GPs felt positive about the potential impact of risk-stratified screening; however, there was hesitance and disagreement towards a low-risk screening pathway.

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease

BACKGROUND

Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors.

OBJECTIVE

To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study.

RESULTS

All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS₃₁₃ in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively).

CONCLUSION

Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.

Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1 updates to tumour pathology and cancer incidence

BACKGROUND

BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) for breast cancer and the epithelial tubo-ovarian cancer (EOC) models included in the CanRisk tool (www.canrisk.org) provide future cancer risks based on pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors.

METHODS

BOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1, RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult height as continuous.

RESULTS

BARD1, RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34%-44% of these carriers would be reclassified to the near-population and 15%-22% to the high-risk categories based on the UK National Institute for Health and Care Excellence guidelines. Under the EOC multifactorial model, 62%, 35% and 3% of PALB2 carriers have lifetime EOC risks of <5%, 5%-10% and >10%, respectively. Including height as continuous, increased the breast cancer relative risk variance from 0.002 to 0.010.

CONCLUSIONS

These extensions will allow for better personalised risks for BARD1, RAD51C, RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.

Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition

PURPOSE

Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases.

MATERIALS AND METHODS

Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution.

RESULTS

In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10-308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women.

CONCLUSION

The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

The clinical utility of polygenic risk scores in genomic medicine practices: a systematic review

Genomic medicine aims to improve health using the individual genomic data of people to inform care. While clinical utility of genomic medicine in many monogenic, Mendelian disorders is amply demonstrated, clinical utility is less evident in polygenic traits, e.g., coronary artery disease or breast cancer. Polygenic risk scores (PRS) are subsets of individual genotypes designed to capture heritability of common traits, and hence to allow the stratification of risk of the trait in a population. We systematically reviewed the PubMed database for unequivocal evidence of clinical utility of polygenic risk scores, using stringent inclusion and exclusion criteria. While we identified studies demonstrating clinical validity in conditions where medical intervention based on a PRS is likely to benefit patient outcome, we did not identify a single study demonstrating unequivocally such a benefit, i.e. clinical utility. We conclude that while the routine use of PRSs hold great promise, translational research is still needed before they should enter mainstream clinical practice.

PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

BACKGROUND

Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.

METHODS

We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.

RESULTS

The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.

CONCLUSIONS

Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

The SCRIPT trial: study protocol for a randomised controlled trial of a polygenic risk score to tailor colorectal cancer screening in primary care

Background

Polygenic risk scores (PRSs) can predict the risk of colorectal cancer (CRC) and target screening more precisely than current guidelines using age and family history alone. Primary care, as a far-reaching point of healthcare and routine provider of cancer screening and risk information, may be an ideal location for their widespread implementation.

Methods

This trial aims to determine whether the SCRIPT intervention results in more risk-appropriate CRC screening after 12 months in individuals attending general practice, compared with standard cancer risk reduction information. The SCRIPT intervention consists of a CRC PRS, tailored risk-specific screening recommendations and a risk report for participants and their GP, delivered in general practice. Patients aged between 45 and 70 inclusive, attending their GP, will be approached for participation. For those over 50, only those overdue for CRC screening will be eligible to participate. Two hundred and seventy-four participants will be randomised to the intervention or control arms, stratified by general practice, using a computer-generated allocation sequence. The primary outcome is risk-appropriate CRC screening after 12 months. For those in the intervention arm, risk-appropriate screening is defined using PRS-derived risk; for those in the control arm, it is defined using family history and national screening guidelines. Timing, type and results of the previous screening are considered in both arms. Objective health service data will capture screening behaviour. Secondary outcomes include cancer-specific worry, risk perception, predictors of CRC screening behaviour, screening intentions and health service use at 1, 6 and 12 months post-intervention delivery.

Discussion

This trial aims to determine whether a PRS-derived personalised CRC risk estimate delivered in primary care increases risk-appropriate CRC screening. A future population risk-stratified CRC screening programme could incorporate risk assessment within primary care while encouraging adherence to targeted screening recommendations.

Trial registration

Australian and New Zealand Clinical Trial Registry ACTRN12621000092897p. Registered on 1 February 2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06734-7.

Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Role of Polygenic Risk Score in Cancer Precision Medicine of Non-European Populations: A Systematic Review

The development of new screening methods and diagnostic tests for traits, common diseases, and cancer is linked to the advent of precision genomic medicine, in which health care is individually adjusted based on a person’s lifestyle, environmental influences, and genetic variants. Based on genome-wide association study (GWAS) analysis, rapid and continuing progress in the discovery of relevant single nucleotide polymorphisms (SNPs) for traits or complex diseases has increased interest in the potential application of genetic risk models for routine health practice. The polygenic risk score (PRS) estimates an individual’s genetic risk of a trait or disease, calculated by employing a weighted sum of allele counts combined with non-genetic variables. However, 98.38% of PRS records held in public databases relate to the European population. Therefore, PRSs for multiethnic populations are urgently needed. We performed a systematic review to discuss the role of polygenic risk scores in advancing precision medicine for different cancer types in multiethnic non-European populations.

The relationship of breast cancer deaths with age groups and urbanization of the population: a multi-country analysis

Aim: In this retrospective observational study, it was aimed to evaluate the relationship between breast cancer deaths and demographic properties of countries. Material and Method: The research was conducted on World Health Organization (WHO) 10th International Classification of Diseases (ICD-10) mortality list and World Bank Country Reports (WBCR). Total breast cancer-related deaths, age groups and urban population rates of 14 countries between 1996 and 2017 were evaluated. Results: Both uncontrolled and controlled correlation analysis results showed that population age distribution had a significant correlation with total breast cancer-related deaths (p0.05). Generalized Linear Model (GLM) results showed that only the country had a significant effect on total breast cancer related deaths (p0.05). Conclusion: Although reasons such as age and urbanization play an important role among breast cancer risk factors, it is found that they do not affect mortality rates. A total of 22 years of WHO data and 14 country results showed that deaths due to breast cancer are only related to the country. Therefore, countries can minimize deaths due to breast cancer by carrying out more effective struggles, early diagnosis, treatment and awareness activities.

TGFBR1*6A as a modifier of breast cancer risk and progression: advances and future prospects

There is growing evidence that germline mutations in certain genes influence cancer susceptibility, tumor evolution, as well as clinical outcomes. Identification of a disease-causing genetic variant enables testing and diagnosis of at-risk individuals. For breast cancer, several genes such as BRCA1, BRCA2, PALB2, ATM, and CHEK2 act as high- to moderate-penetrance cancer susceptibility genes. Genotyping of these genes informs genetic risk assessment and counseling, as well as treatment and management decisions in the case of high-penetrance genes. TGFBR1*6A (rs11466445) is a common variant of the TGF-β receptor type I (TGFBR1) that has a global minor allelic frequency (MAF) of 0.051 according to the 1000 Genomes Project Consortium. It is emerging as a high frequency, low penetrance tumor susceptibility allele associated with increased cancer risk among several cancer types. The TGFBR1*6A allele has been associated with increased breast cancer risk in women, OR 1.15 (95% CI 1.01–1.31). Functionally, TGFBR1*6A promotes breast cancer cell proliferation, migration, and invasion through the regulation of the ERK pathway and Rho-GTP activation. This review discusses current findings on the genetic, functional, and mechanistic associations between TGFBR1*6A and breast cancer risk and proposes future directions as it relates to genetic association studies and mechanisms of action for tumor growth, metastasis, and immune suppression.

Challenges for precision public health communication in the era of genomic medicine

Although still in the early stages of development, the advent of fast, high-output, and cost-effective next-generation DNA sequencing technology is moving precision medicine into public health. Before this shift toward next-generation sequencing in public health settings, individual patients met geneticists after showing symptoms and through limited family screening. In the new era of precision public health, everyone is a possible participant in genetic sequencing, simply by being born (newborn screening), by donating blood (biobanking), or through population screening. These initiatives are increasingly offered to individuals throughout their life and more individuals are encountering opportunities to use DNA sequencing. This article raises awareness of these growing areas and calls for different models of public engagement and communication about genomics, including screening asymptomatic populations, obtaining consent for unspecified and unforeseen future uses of genomic data, and managing variants of uncertain significance. Given that such communication challenges loom large, established norms of practice in genomic medicine and research should be reconsidered.

Advances in breast cancer screening modalities and status of global screening programs

Breast cancer (BC) is the most prevalent malignancy worldwide, and a continued upward trend has been predicted in the coming decades. Screening in selected targeted populations, which is effective in reducing cancer‐related mortality, has been widely implemented in many countries. This review summarizes the advances in BC screening techniques, organized or opportunistic BC screening programs across different countries, and screening modalities recommended by different academic authorities. Mammography is the most widely used and effective technique for BC screening. Other complementary techniques include ultrasound, clinical breast examination, and magnetic resonance imaging. Novel screening tests, including digital breast tomosynthesis and liquid biopsies, are still under development. Globally, the implementation status of BC screening programs is uneven, which is reflected by differences in screening modes, techniques, and population coverage. The recommended optimal screening strategies varied according to the authoritative guidelines. The effectiveness of current screening programs is influenced by several factors, including low detection rate, high false‐positive rate, and unsatisfactory coverage and uptake rates. Exploration of accurate BC risk prediction models and the development of risk‐stratified screening strategies are highly warranted in future research.

Mammography is the most widely used and most effective technique; other complementary techniques include ultrasound, clinical breast examination, and magnetic resonance imaging. Globally, the implementation status of breast cancer screening programs is uneven, which is reflected by differences in screening modes, techniques, and examination coverage. Combining effective risk prediction models and advanced screening techniques for risk‐stratified screening strategies may be the future direction.

Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification

BACKGROUND

Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear.

METHODS

In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%.

RESULTS

Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history.

CONCLUSIONS

Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.

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.

Polygenic risk scores for prediction of breast cancer risk in Asian populations

PURPOSE

Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.

METHODS

The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).

RESULTS

The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.

CONCLUSION

PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

Incorporating Polygenic Risk Scores and Nongenetic Risk Factors for Breast Cancer Risk Prediction Among Asian Women

IMPORTANCE

Polygenic risk scores (PRSs) have shown promise in breast cancer risk prediction; however, limited studies have been conducted among Asian women.

OBJECTIVE

To develop breast cancer risk prediction models for Asian women incorporating PRSs and nongenetic risk factors.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study included women of Asian ancestry from the Asia Breast Cancer Consortium. PRSs were developed using data from genomewide association studies (GWASs) of breast cancer conducted among 123 041 women with Asian ancestry (including 18 650 women with breast cancer) using 3 approaches: (1) reported PRS for women with European ancestry; (2) breast cancer-associated single-nucleotide variations (SNVs) identified by fine-mapping of GWAS-identified risk loci; and (3) genomewide risk prediction algorithms. A nongenetic risk score (NGRS) was built, including 7 well-established nongenetic risk factors, using data of 416 case participants and 1558 control participants from a prospective cohort study. PRSs were initially validated in an independent data set including 1426 case participants and 1323 control participants and further evaluated, along with the NGRS, in the second data set including 368 case participants and 736 control participants nested within a prospective cohort study.

MAIN OUTCOMES AND MEASURES

Logistic regression was used to examine associations of risk scores with breast cancer risk to estimate odds ratios (ORs) with 95% CIs and area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 126 894 women of Asian ancestry were included; 20 444 (16.1%) had breast cancer. The mean (SD) age ranged from 49.1 (10.8) to 54.4 (10.4) years for case participants and 50.6 (9.5) to 54.0 (7.4) years for control participants among studies that provided demographic characteristics. In the prospective cohort, a PRS with 111 SNVs developed using the fine-mapping approach (PRS111) showed a prediction performance comparable with a genomewide PRS that included more than 855 000 SNVs. The OR per SD increase of PRS111 score was 1.67 (95% CI, 1.46-1.92), with an AUC of 0.639 (95% CI, 0.604-0.674). The NGRS had a limited predictive ability (AUC, 0.565; 95% CI, 0.529-0.601). Compared with the average risk group (40th-60th percentile), women in the top 5% of PRS111 and NGRS were at a 3.84-fold (95% CI, 2.30-6.46) and 2.10-fold (95% CI, 1.22-3.62) higher risk of breast cancer, respectively. The prediction model including both PRS111 and NGRS achieved the highest prediction accuracy (AUC, 0.648; 95% CI, 0.613-0.682).

CONCLUSIONS AND RELEVANCE

In this study, PRSs derived using breast cancer risk-associated SNVs had similar predictive performance in Asian and European women. Including nongenetic risk factors in models further improved prediction accuracy. These findings support the utility of these models in developing personalized screening and prevention strategies.

Feasibility of personalized screening and prevention recommendations in the general population through breast cancer risk assessment: results from a dedicated risk clinic

PURPOSE

A personalized approach to prevention and early detection based on known risk factors should contribute to early diagnosis and treatment of breast cancer. We initiated a risk assessment clinic for all women wishing to undergo an individual breast cancer risk assessment.

METHODS

Women underwent a complete breast cancer assessment including a questionnaire, mammogram with evaluation of breast density, collection of saliva sample, consultation with a radiologist, and a breast cancer specialist. Women aged 40 or older, with 0 or 1 first-degree relative with breast cancer diagnosed after the age of 40 were eligible for risk assessment using MammoRisk, a machine learning-based tool that provides an individual 5-year estimated risk of developing breast cancer based on the patient's clinical data and breast density, with or without polygenic risk scores (PRSs). DNA was extracted from saliva samples for genotyping of 76 single-nucleotide polymorphisms. The individual risk was communicated to the patient, with individualized screening and prevention recommendations.

RESULTS

A total of 290 women underwent breast cancer assessment, among which 196 women (68%) were eligible for risk assessment using MammoRisk (median age 52, range 40-72). When PRS was added to MammoRisk, 40% (n = 78) of patients were assigned a different risk category, with 28% (n = 55) of patients changing from intermediate to moderate or high risk.

CONCLUSION

Individual risk assessment is feasible in the general population. Screening recommendations could be given based on individual risk. The use of PRS changed the risk score and screening recommendations in 40% of women.

The importance of ethnicity: Are breast cancer polygenic risk scores ready for women who are not of White European origin?

Polygenic risk scores (PRS) for disease risk stratification show great promise for application in general populations, but most are based on data from individuals of White European origin. We assessed two well validated PRS (SNP18, SNP143) in the Predicting-Risk-of-Cancer-At-Screening (PROCAS) study in North-West England for breast cancer prediction based on ethnicity. Overall, 9475 women without breast cancer at study entry, including 645 who subsequently developed invasive breast cancer or ductal carcinoma in situ provided DNA. All were genotyped for SNP18 and a subset of 1868 controls were genotyped for SNP143. For White Europeans both PRS discriminated well between individuals with and without cancer. For n = 395 Black (n = 112), Asian (n = 119), mixed (n = 44) or Jewish (n = 120) women without cancer both PRS overestimated breast cancer risk, being most marked for women of Black and Jewish origin (P < .001). SNP143 resulted in a potential mean 40% breast cancer risk overestimation in the combined group of non-White/non-European origin. SNP-PRS that has been normalized based on White European ethnicity for breast cancer should not be used to predict risk in women of other ethnicities. There is an urgent need to develop PRS specific for other ethnicities, in order to widen access of this technology.

TYMS 3'-UTR Polymorphism: A Novel Association with FOLFIRINOX-Induced Neurotoxicity in Pancreatic Cancer Patients

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy that has the worst 5-year survival rate of all of the common malignant tumors. Surgery, chemotherapy, and/or chemoradiation remain the main tactics for PDAC treatment. The efficacy of chemotherapy is often compromised because of the substantial risk of severe toxicities. In our study, we focused on identification of polymorphisms in the genes involved in drug metabolism, DNA repair and replication that are associated with inter-individual differences in drug-induced toxicities. Using the microarray, we genotyped 12 polymorphisms in the DPYD, XPC, GSTP1, MTHFR, ERCC1, UGT1A1, and TYMS genes in 78 PDAC patients treated with FOLFIRINOX. It was found that the TYMS rs11280056 polymorphism (6 bp-deletion in TYMS 3'-UTR) predicted grade 1-2 neurotoxicity (p = 0.0072 and p = 0.0019, according to co-dominant (CDM) and recessive model (RM), respectively). It is the first report on the association between TYMS rs11280056 and peripheral neuropathy. We also found that PDAC patients carrying the GSTP1 rs1695 GG genotype had a decreased risk for grade 3-4 hematological toxicity as compared to those with the AA or AG genotypes (p = 0.032 and p = 0.014, CDM and RM, respectively). Due to relatively high p-values, we consider that the impact of GSTP1 rs1695 requires further investigation in a larger sample size.

Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention

Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual's genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.

Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia

Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its application in medicine. However, none has applied ANN to predict the efficacy of folic acid treatment to Hyperhomocysteinemia (HHcy). The efficacy has been proved to associate with both genetic and environmental factors while previous studies just focused on the latter one. The explained variance genetic risk score (EV-GRS) had better power and could represent the effect of genetic architectures. Our aim was to add EV-GRS into environmental factors to establish ANN to predict the efficacy of folic acid therapy to HHcy. We performed the prospective cohort research enrolling 638 HHcy patients. The multilayer perception algorithm was applied to construct ANN. To evaluate the effect of ANN, we also established logistic regression (LR) model to compare with ANN. According to our results, EV-GRS was statistically associated with the efficacy no matter analyzed as a continuous variable (OR = 3.301, 95%CI 1.954-5.576, P < 0.001) or category variable (OR = 3.870, 95%CI 2.092-7.159, P < 0.001). In our ANN model, the accuracy was 84.78%, the Youden's index was 0.7073 and the AUC was 0.938. These indexes above indicated higher power. When compared with LR, the AUC, accuracy, and Youden's index of the ANN model (84.78%, 0.938, 0.7073) were all slightly higher than the LR model (83.33% 0.910, 0.6687). Therefore, clinical application of the ANN model may be able to better predict the folic acid efficacy to HHcy than the traditional LR model. When testing two models in the validation set, we got the same conclusion. This study appears to be the first one to establish the ANN model which added EV-GRS into environmental factors to predict the efficacy of folic acid to HHcy. This model would be able to offer clinicians a new method to make decisions and individual therapeutic plans.

Potential of polygenic risk scores for improving population estimates of women's breast cancer genetic risks

PURPOSE

Breast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown.

METHODS

The Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known.

RESULTS

Generally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer.

CONCLUSION

PRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.

Communicating polygenic risk scores in the familial breast cancer clinic

OBJECTIVE

To describe the communication of polygenic risk scores (PRS) in the familial breast cancer setting.

METHODS

Consultations between genetic healthcare providers (GHP) and female patients who received their PRS for breast cancer risk were recorded (n = 65). GHPs included genetic counselors (n = 8) and medical practitioners (n = 5) (i.e. clinical geneticists and oncologists). A content analysis was conducted and logistic regression was used to assess differences in communication behaviors between genetic counselors (n = 8) and medical practitioners (n = 5).

RESULTS

Of the 65 patients, 31 (47.7 %) had a personal history of breast cancer, 18 of whom received an increased PRS (relative risk >1.2). 25/34 unaffected patients received an increased PRS. Consultations were primarily clinician-driven and focused on biomedical information. There was little difference between the biomedical information provided by genetic counselors and medical practitioners. However, genetic counselors were significantly more likely to utilize strategies to build patient rapport and counseling techniques.

CONCLUSIONS

Our findings provide one of the earliest reports on how breast cancer PRSs are communicated to women.

PRACTICE IMPLICATIONS

Key messages for communicating PRSs were identified, namely: discussing differences between polygenic and monogenic testing, the multifactorial nature of breast cancer risk, polygenic inheritance and current limitation of PRSs.

Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry

BACKGROUND

Polygenic risk scores (PRSs) have been demonstrated to identify women of European, Asian, and Latino ancestry at elevated risk of developing breast cancer (BC). We evaluated the performance of existing PRSs trained in European ancestry populations among women of African ancestry.

METHODS

We assembled genotype data for women of African ancestry, including 9241 case subjects and 10 193 control subjects. We evaluated associations of 179- and 313-variant PRSs with overall and subtype-specific BC risk. PRS discriminatory accuracy was assessed using area under the receiver operating characteristic curve. We also evaluated a recalibrated PRS, replacing the index variant with variants in each region that better captured risk in women of African ancestry and estimated lifetime absolute risk of BC in African Americans by PRS category.

RESULTS

For overall BC, the odds ratio per SD of the 313-variant PRS (PRS313) was 1.27 (95% confidence interval [CI] = 1.23 to 1.31), with an area under the receiver operating characteristic curve of 0.571 (95% CI = 0.562 to 0.579). Compared with women with average risk (40th-60th PRS percentile), women in the top decile of PRS313 had a 1.54-fold increased risk (95% CI = 1.38-fold to 1.72-fold). By age 85 years, the absolute risk of overall BC was 19.6% for African American women in the top 1% of PRS313 and 6.7% for those in the lowest 1%. The recalibrated PRS did not improve BC risk prediction.

CONCLUSION

The PRSs stratify BC risk in women of African ancestry, with attenuated performance compared with that reported in European, Asian, and Latina populations. Future work is needed to improve BC risk stratification for women of African ancestry.

Mammographic features are associated with cardiometabolic disease risk and mortality

Aims

In recent years, microcalcifications identified in routine mammograms were found to be associated with cardiometabolic disease in women. Here, we aimed to systematically evaluate the association of microcalcifications and other mammographic features with cardiometabolic disease risk and mortality in a large screening cohort and to understand a potential genetic contribution.

Methods and results

This study included 57 867 women from a prospective mammographic screening cohort in Sweden (KARMA) and 49 583 sisters. Cardiometabolic disease diagnoses and mortality and medication were extracted by linkage to Swedish population registries with virtually no missing data. In the cardiometabolic phenome-wide association study, we found that a higher number of microcalcifications were associated with increased risk for multiple cardiometabolic diseases, particularly in women with pre-existing cardiometabolic diseases. In contrast, dense breasts were associated with a lower incidence of cardiometabolic diseases. Importantly, we observed similar associations in sisters of KARMA women, indicating a potential genetic overlap between mammographic features and cardiometabolic traits. Finally, we observed that the presence of microcalcifications was associated with increased cardiometabolic mortality in women with pre-existing cardiometabolic diseases (hazard ratio and 95% confidence interval: 1.79 [1.24–2.58], P = 0.002) while we did not find such effects in women without cardiometabolic diseases.

Conclusions

We found that mammographic features are associated with cardiometabolic risk and mortality. Our results strengthen the notion that a combination of mammographic features and other breast cancer risk factors could be a novel and affordable tool to assess cardiometabolic health in women attending mammographic screening.

DNA methylation and breast cancer-associated variants

BACKGROUND

A breast cancer polygenic risk score (PRS) comprising 313 common variants reliably predicts disease risk. We examined possible relationships between genetic variation, regulation, and expression to clarify the molecular alterations associated with these variants.

METHODS

Genome-wide methylomic variation was quantified (MethylationEPIC) in Asian breast cancer patients (1152 buffy coats from peripheral whole blood). DNA methylation (DNAm) quantitative trait loci (mQTL) mapping was performed for 235 of the 313 variants with minor allele frequencies > 5%. Stability of identified mQTLs (p < 5e-8) across lifetime was examined using a public mQTL database. Identified mQTLs were also mapped to expression quantitative trait loci (eQTLs) in the Genotype-Tissue Expression Project and the eQTLGen Consortium.

RESULTS

Breast cancer PRS was not associated with DNAm. A higher proportion of significant cis-mQTLs were observed. Of 822 significant cis-mQTLs (179 unique variants) identified in our dataset, 141 (59 unique variants) were significant (p < 5e-8) in a public mQTL database. Eighty-six percent (121/141) of the matched mQTLs were consistent at multiple time points (birth, childhood, adolescence, pregnancy, middle age, post-diagnosis, or treatment). Ninety-three variants associated with DNAm were also cis-eQTLs (35 variants not genome-wide significant). Multiple loci in the breast cancer PRS are associated with DNAm, contributing to the polygenic nature of the disease. These mQTLs are mostly stable over time.

CONCLUSIONS

Consistent results from DNAm and expression data may reveal new candidate genes not previously associated with breast cancer.