Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese

DCIS and LCIS: Are the Risk Factors for Developing In Situ Breast Cancer Different?

Ductal carcinoma in situ (DCIS) is widely accepted as a precursor of invasive ductal carcinoma (IDC). Lobular carcinoma in situ (LCIS) is considered a risk factor for invasive lobular carcinoma (ILC), and it is unclear whether LCIS is also a precursor. Therefore, it would be expected that similar risk factors predispose to both DCIS and IDC, but not necessarily LCIS and ILC. This study examined associations with risk factors using data from 3075 DCIS cases, 338 LCIS cases, and 1584 controls aged 35-60, recruited from the UK-based GLACIER and ICICLE case-control studies between 2007 and 2012. Analysis showed that breastfeeding in parous women was protective against DCIS and LCIS, which is consistent with research on invasive breast cancer (IBC). Additionally, long-term use of HRT in post-menopausal women increased the risk of DCIS and LCIS, with a stronger association in LCIS, similar to the association with ILC. Contrary to findings with IBC, parity and the number of births were not protective against DCIS or LCIS, while oral contraceptives showed an unexpected protective effect. These findings suggest both similarities and differences in risk factors for DCIS and LCIS compared to IBC and that there may be justification for increased breast surveillance in post-menopausal women taking long-term HRT.

Development of a Breast Cancer Risk Prediction Model Incorporating Polygenic Risk Scores and Nongenetic Risk Factors for Korean Women

BACKGROUND

To develop a breast cancer prediction model for Korean women using published polygenic risk scores (PRS) combined with nongenetic risk factors (NGRF).

METHODS

Thirteen PRS models generated from single or multiple combinations of the Asian and European PRSs were evaluated among 20,434 Korean women. The AUC and increase in OR per SD were compared for each PRS. The PRSs with the highest predictive power were combined with NGRFs; then, an integrated prediction model was established using the Individualized Coherent Absolute Risk Estimation (iCARE) tool. The absolute breast cancer risk was stratified for 18,142 women with available follow-up data.

RESULTS

PRS38_ASN+PRS190_EB, a combination of Asian and European PRSs, had the highest AUC (0.621) among PRSs, with an OR per SD increase of 1.45 (95% confidence interval: 1.31-1.61). Compared with the average risk group (35%-65%), women in the top 5% had a 2.5-fold higher risk of breast cancer. Incorporating NGRFs yielded a modest increase in the AUC of women ages >50 years. For PRS38_ASN+PRS190_EB+NGRF, the average absolute risk was 5.06%. The lifetime absolute risk at age 80 years for women in the top 5% was 9.93%, whereas that of women in the lowest 5% was 2.22%. Women at higher risks were more sensitive to NGRF incorporation.

CONCLUSIONS

Combined Asian and European PRSs were predictive of breast cancer in Korean women. Our findings support the use of these models for personalized screening and prevention of breast cancer.

IMPACT

Our study provides insights into genetic susceptibility and NGRFs for predicting breast cancer in Korean women.

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.

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.

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.

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.

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.

Cost effectiveness analysis of a polygenic risk tailored breast cancer screening programme in Singapore

BACKGROUND

This study aimed to evaluate the cost-effectiveness of a breast cancer screening programme that incorporates genetic testing using breast cancer associated single nucleotide polymorphisms (SNPs), against the current biennial mammogram-only screening programme to aid in its implementation into the current programme in Singapore.

METHODS

A Markov model was used to compare the costs and health outcomes of the current screening programme, against a polygenic risk-tailored screening programme, which can advise a long-term screening strategy depending on the individual's polygenic risk. The model took the perspective of the healthcare system, with a time horizon of 40 years, following women from the age of 35 to 74. Epidemiological and cost data were taken from Asian studies, and an annual discount rate of 3% was used. The model outcome was the incremental cost-effectiveness ratio (ICER), calculated from the difference in costs per quality-adjusted life year (QALY). Scenarios with varying risk thresholds for each polygenic risk group were examined. One-way and probabilistic sensitivity analyses were performed to assess parameter uncertainty.

RESULTS

The ICER for a polygenic risk-tailored breast cancer screening programme, compared with the current biennial mammogram-only screening programme, was - 3713.80 SGD/QALY, with incremental costs < 0 and incremental effects > 0. The scenario analysis of different polygenic risk cutoffs showed that the ICERs remain negative, with all ICERs falling within the south-east quadrant of the cost-effectiveness plane, indicating that tailored screening is more cost effective than mammogram-only screening, with lower costs and higher QALYs to be gained. This suggests that a polygenic risk-tailored breast cancer screening programme is cost effective, entailing lower cost than the current mammogram-only programme, while causing no additional harm to women.

CONCLUSION

Results from this cost-effectiveness analysis show that polygenic risk-tailored screening is cost effective with an ICER of - 3713.80 SGD/QALY. Tailored screening remains cost effective even across varying percentile cutoffs for each risk group. While the results look promising for incorporating polygenic risk into the current breast cancer screening programme, further studies should be conducted to address various limitations.

Deep neural network improves the estimation of polygenic risk scores for breast cancer

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA, and LDpred. In the test cohort with 50% prevalence, the Area Under the receiver operating characteristic Curve (AUC) were 67.4% for DNN, 64.2% for BLUP, 64.5% for BayesA, and 62.4% for LDpred. BLUP, BayesA, and LPpred all generated PRS that followed a normal distribution in the case population. However, the PRS generated by DNN in the case population followed a bimodal distribution composed of two normal distributions with distinctly different means. This suggests that DNN was able to separate the case population into a high-genetic-risk case subpopulation with an average PRS significantly higher than the control population and a normal-genetic-risk case subpopulation with an average PRS similar to the control population. This allowed DNN to achieve 18.8% recall at 90% precision in the test cohort with 50% prevalence, which can be extrapolated to 65.4% recall at 20% precision in a general population with 12% prevalence. Interpretation of the DNN model identified salient variants that were assigned insignificant p values by association studies, but were important for DNN prediction. These variants may be associated with the phenotype through nonlinear relationships.

Breast Cancer Risk Prediction in Korean Women: Review and Perspectives on Personalized Breast Cancer Screening

Due to an increasing proportion of older individuals and the adoption of a westernized lifestyle, the incidence rate of breast cancer is expected to rapidly increase within the next 10 years in Korea. The National Cancer Screening Program (NCSP) of Korea recommends biennial breast cancer screening through mammography for women aged 40-69 years old and according to individual risk and preference for women above 70 years old. There is an ongoing debate on how to most effectively screen for breast cancer, with many proponents of personalized screening, or screening according to individual risk, for women under 70 years old as well. However, to accurately stratify women into risk categories, further study using more refined personalized characteristics, including potentially incorporating a polygenic risk score (PRS), may be needed. While most breast cancer risk prediction models were developed in Western countries, the Korean Breast Cancer Risk Assessment Tool (KoBCRAT) was developed in 2013, and several other risk models have been developed for Asian women specifically. This paper reviews these models compared to commonly used models developed using primarily Caucasian women, namely, the modified Gail, Breast Cancer Surveillance Consortium, Rosner and Colditz, and Tyrer-Cuzick models. In addition, this paper reviews studies in which PRS is included in risk prediction in Asian women. Finally, this paper discusses and explores strategies toward development and implementation of personalized screening for breast cancer in Korea.

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

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.

The emerging field of polygenic risk scores and perspective for use in clinical care

Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.

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

Polygenic factors are estimated to account for an additional 18% of the familial relative risk of breast cancer, with those at the highest level of polygenic risk distribution having a least a twofold increased risk of the disease. Polygenic testing promises to revolutionize health services by providing personalized risk assessments to women at high-risk of breast cancer and within population breast screening programs. However, implementation of polygenic testing needs to be considered in light of its current limitations, such as limited risk prediction for women of non-European ancestry. This article aims to provide a comprehensive review of the evidence for polygenic breast cancer risk, including the discovery of variants associated with breast cancer at the genome-wide level of significance and the use of polygenic risk scores to estimate breast cancer risk. We also review the different applications of this technology including testing of women from high-risk breast cancer families with uninformative genetic testing results, as a moderator of monogenic risk, and for population screening programs. Finally, a potential framework for introducing testing for polygenic risk in familial cancer clinics and the potential challenges with implementing this technology in clinical practice are discussed.

Genetic Testing to Guide Risk-Stratified Screens for Breast Cancer

Breast cancer screening modalities and guidelines continue to evolve and are increasingly based on risk factors, including genetic risk and a personal or family history of cancer. Here, we review genetic testing of high-penetrance hereditary breast and ovarian cancer genes, including BRCA1 and BRCA2, for the purpose of identifying high-risk individuals who would benefit from earlier screening and more sensitive methods such as magnetic resonance imaging. We also consider risk-based screening in the general population, including whether every woman should be genetically tested for high-risk genes and the potential use of polygenic risk scores. In addition to enabling early detection, the results of genetic screens of breast cancer susceptibility genes can be utilized to guide decision-making about when to elect prophylactic surgeries that reduce cancer risk and the choice of therapeutic options. Variants of uncertain significance, especially missense variants, are being identified during panel testing for hereditary breast and ovarian cancer. A finding of a variant of uncertain significance does not provide a basis for increased cancer surveillance or prophylactic procedures. Given that variant classification is often challenging, we also consider the role of multifactorial statistical analyses by large consortia and functional tests for this purpose.

Polygenic Determinants for Subsequent Breast Cancer Risk in Survivors of Childhood Cancer: The St Jude Lifetime Cohort Study (SJLIFE)

PURPOSE

The risk of subsequent breast cancer among female childhood cancer survivors is markedly elevated. We aimed to determine genetic contributions to this risk, focusing on polygenic determinants implicated in breast cancer susceptibility in the general population.

EXPERIMENTAL DESIGN

Whole-genome sequencing (30×) was performed on survivors in the St Jude Lifetime Cohort, and germline mutations in breast cancer predisposition genes were classified for pathogenicity. A polygenic risk score (PRS) was constructed for each survivor using 170 established common risk variants. Relative rate (RR) and 95% confidence interval (95% CI) of subsequent breast cancer incidence were estimated using multivariable piecewise exponential regression.

RESULTS

The analysis included 1,133 female survivors of European ancestry (median age at last follow-up = 35.4 years; range, 8.4-67.4), of whom 47 were diagnosed with one or more subsequent breast cancers (median age at subsequent breast cancer = 40.3 years; range, 24.5-53.0). Adjusting for attained age, age at primary diagnosis, chest irradiation, doses of alkylating agents and anthracyclines, and genotype eigenvectors, RRs for survivors with PRS in the highest versus lowest quintiles were 2.7 (95% CI, 1.0-7.3), 3.0 (95% CI, 1.1-8.1), and 2.4 (95% CI, 0.1-81.1) for all survivors and survivors with and without chest irradiation, respectively. Similar associations were observed after excluding carriers of pathogenic/likely pathogenic mutations in breast cancer predisposition genes. Notably, the PRS was associated with the subsequent breast cancer rate under the age of 45 years (RR = 3.2; 95% CI, 1.2-8.3).

CONCLUSIONS

Genetic profiles comprised of small-effect common variants and large-effect predisposing mutations can inform personalized breast cancer risk and surveillance/intervention in female childhood cancer survivors.

ZNF423: A New Player in Estrogen Receptor-Positive Breast Cancer

Preventive therapy can target hormone-responsive breast cancer (BC) by treatment with selective estrogen receptor modulators (SERMs) and reduce the incidence of BC. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) with relevant predictive values, SNPs in the ZNF423 gene were associated with decreased risk of BC during SERM therapy, and SNPs in the Cathepsin O gene with an increased risk. ZNF423, which was not previously associated with BC is a multifunctional transcription factor known to have a role in development, neurogenesis, and adipogenesis and is implicated in other types of cancer. ZNF423 is transcriptionally controlled by the homolog ZNF521, early B cell factor transcription factor, epigenetic silencing of the promoter by CpG island hyper-methylation, and also by ZNF423 itself in an auto-regulatory loop. In BC cells, ZNF423 expression is found to be induced by estrogen, dependent on the binding of the estrogen receptor and calmodulin-like 3 to SNPs in ZNP423 intronic sites in proximity to consensus estrogen response elements. ZNF423 has also been shown to play a mechanistic role by trans-activating the tumor suppressor BRCA1 and thus modulating the DNA damage response. Even though recent extensive trial studies did not classify these SNPs with the highest predictive values, for inclusion in polygenic SNP analysis, the mechanism unveiled in these studies has introduced ZNF423 as a factor important in the control of the estrogen response. Here, we aim at providing an overview of ZNF423 expression and functional role in human malignancies, with a specific focus on its implication in hormone-responsive BC.