Decision letter: Polygenic risk scores for the prediction of common cancers in East Asians: A population-based prospective cohort study

To evaluate the utility of polygenic risk scores (PRSs) in identifying high-risk individuals, different publicly available PRSs for breast (n=85), prostate (n=37), colorectal (n=22), and lung cancers (n=11) were examined in a prospective study of 21,694 Chinese adults. We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals (CI) of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS. A total of 495 breast, 308 prostate, 332 female-colorectal, 409 male-colorectal, 181 female-lung, and 381 male-lung incident cancers were identified. The area under receiver operating characteristic curve for the best-performing site-specific PRS were 0.61 (PGS000873, breast), 0.70 (PGS00662, prostate), 0.65 (PGS000055, female-colorectal), 0.60 (PGS000734, male-colorectal), 0.56 (PGS000721, female-lung), and 0.58 (PGS000070, male-lung), respectively. Compared to the middle quintile, individuals in the highest cancer-specific PRS quintile were 64% more likely to develop cancers of the breast, prostate, and colorectal. For lung cancer, the lowest cancer-specific PRS quintile was associated with 28-34% decreased risk compared to the middle quintile. In contrast, the HR observed for quintiles 4 (female-lung: 0.95 [0.61-1.47]; male-lung: 1.14 [0.82-1.57]) and 5 (female-lung: 0.95 [0.61-1.47]) were not significantly different from that for the middle quintile. Site-specific PRSs can stratify the risk of developing breast, prostate, and colorectal cancers in this East Asian population. Appropriate correction factors may be required to improve calibration. This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022).The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health (NIH) (R01 CA144034 and UM1 CA182876).

Background:To evaluate the utility of polygenic risk scores (PRSs) in identifying high-risk individuals, different publicly available PRSs for breast (n=85), prostate (n=37), colorectal (n=22), and lung cancers (n=11) were examined in a prospective study of 21,694 Chinese adults.Methods:We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals (CI) of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS.Results:A total of 495 breast, 308 prostate, 332 female-colorectal, 409 male-colorectal, 181 female-lung, and 381 male-lung incident cancers were identified. The area under receiver operating characteristic curve for the best-performing site-specific PRS were 0.61 (PGS000873, breast), 0.70 (PGS00662, prostate), 0.65 (PGS000055, female-colorectal), 0.60 (PGS000734, male-colorectal), 0.56 (PGS000721, female-lung), and 0.58 (PGS000070, male-lung), respectively. Compared to the middle quintile, individuals in the highest cancer-specific PRS quintile were 64% more likely to develop cancers of the breast, prostate, and colorectal. For lung cancer, the lowest cancer-specific PRS quintile was associated with 28–34% decreased risk compared to the middle quintile. In contrast, the HR observed for quintiles 4 (female-lung: 0.95 [0.61–1.47]; male-lung: 1.14 [0.82–1.57]) and 5 (female-lung: 0.95 [0.61–1.47]) were not significantly different from that for the middle quintile.Conclusions:Site-specific PRSs can stratify the risk of developing breast, prostate, and colorectal cancers in this East Asian population. Appropriate correction factors may be required to improve calibration.Funding:This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022).The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health (NIH) (R01 CA144034 and UM1 CA182876).

Background: A polygenic risk score (PRS) for breast cancer including 313 common variants developed by the Breast Cancer Association Consortium (BCAC) has been demonstrated to identify women who are at high risk of developing breast cancer [odds ratio (OR 95%CI) = 1.61 (1.57-1.65) per SD] in women of European ancestry. In the present study, we examined the performance of the 313-variant PRS and a PRS including 179 variants reaching genome-wide significance in previous genome-wide association studies (GWAS), in women of African ancestry. Methods: We assembled genotype data for women of African ancestry from 28 breast cancer studies, including a total of 9,241 cases and 10,193 controls. We constructed the 179-variant and 313-variant PRSs with relative risk weights for each variant estimated in women of European ancestry in BCAC. The associations between the two PRSs and overall, ER+ and ER- breast cancer risk were estimated using logistic regression adjusting for age, study site and principal components. Discriminatory accuracy of the PRSs was evaluated using the receiver operating characteristic curve (AUROC). We then recalibrated the 179-variant PRS by replacing index variants with variants in each region that better captured risk in women of African ancestry and used relative risk weights estimated in women of African ancestry. We also assessed PRS performance by age (<55 versus ≥ 55 years). Results: Both the 179 and 313- variant PRSs were significantly associated with overall, ER+ and ER- breast cancer risk, with odds ratios (OR) per standard deviation of 1.21~1.37 and AUROCs ranging from 0.57 to 0.59. The 179-variant PRS outperformed in ER- cancer [1.31(1.24,1.37) per SD] while the 313-SNP PRS was better for overall [1.27(1.23,1.31) per SD] and ER+ cancer [1.37(1.32,1.43) per SD]. For overall breast cancer, compared to women with average risk (40th-60th PRS percentiles), women in the top decile of PRS had a 1.54 (95% CI: 1.38, 1.72)-fold increased risk. The performance of the recalibrated 179-variant PRS was not improved (average AUROC=0.56). The PRS ORs did not differ significantly across age strata (P-value for age interaction = 0.63). Conclusion: Our study shows that both 179 and 313 variant PRS stratify breast cancer risk in women of African ancestry, with attenuated performance compared to that reported in European and in Latina populations. Future work is needed to improve breast cancer risk stratification for women of African ancestry. Citation Format: Zhaohui Du, Guimin Gao, Babatunde Adedokun, Thomas Ahearn, Kathryn L. Lunetta, Gary Zirpoli, Melissa Troester, Edward A. Ruiz-Narváez, Stephen Haddad, Jonine Figueroa, Esther M. John, Leslie Bernstein, Wei Zheng, Jennifer J. Hu, Regina G. Ziegler, Sarah Nyante, Elisa V. Bandera, Sue A. Ingles, Michael F. Press, Sandra L. Deming, Jorge L. Rodriguez-Gil, Song Yao, Temidayo O. Ogundiran, Oladosu A. Ojengbede, William Blot, Katherine L. Nathanson, Anselm Hennis, Barbara Nemesure, Stefan Ambs, Lara E. Sucheston-Campbell, Jeannette T. Bensen, Stephen J. Chanock, Andrew F. Olshan, Christine B. Ambrosone, David V. Conti, Olufunmilayo I. Olopade, Julie R. Palmer, Montserrat Garcia-Closas, Dezheng Huo, Christopher A. Haiman. Evaluating a polygenic risk score for breast cancer in women of African ancestry [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2320.

Challenges With Colorectal Cancer Family History Assessment—Motivation to Translate Polygenic Risk Scores Into Practice

Familial aggregation of esophageal cancer.

Personalized, Genomic-Based Care Could Mean a Paradigm Shift

Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

10553 Background: Polygenic risk score (PRS) is a valuable tool for predicting the risk of breast cancer (BC). However, limited studies have been conducted in Chinese women. This study aimed to develop and validate a PRS which could be used to identify individuals with high risk of breast cancer. The associations between the PRS and patients' clinicopathological characteristics or survival outcomes were also evaluated. Methods: The PRS was developed based on findings from genome-wide association studies (GWAS) and validated in four independent cohorts with a three-stage design. A total of 7,056 patients and 6,659 controls were enrolled from Fujian Medical University Union Hospital (FJMUUH) and Shanghai Breast Cancer Genetics Study (SBCGS). Five approaches were utilized to calculate the PRS, including repeated logistic regression (RLR), logistic ridge regression (LRR), artificial neural network (ANN), random forest (RF) and support vector machine (SVM). Logistic regression analyses were performed to assess the association between established PRS and clinicopathological characteristics. The correlation between PRS and patients' survival outcomes was evaluated by cox regression models. Results: The LRR-based PRS was indicated to have the best predictive accuracy among five approaches (AUC = 0.601, OR per 1 SD increase = 1.39, Table 1). Women in the top 5% and 80-95% percentiles of PRS had a 1.43-fold and a 1.34-fold elevated risk of developing breast cancer compared with those at average risk (PRS in 40-60th percentiles). The predictive performance of PRS for patients with HER-2 positive tumors was demonstrated to be higher than that of HER-2 negative tumors (AUC = 0.612 vs 0.585, OR = 1.47 vs 1.35). It was also identified that the PRS was not correlated with age at diagnosis nor tumor characteristics. In survival analyses, an increase in PRS was associated with unfavorable disease-free survival (DFS) for ER negative patients (HR = 1.48, 95% CI = 1.08-2.03, p = 0.016). However, this association diminished after adjusting for clinicopathological characteristics. Regarding overall survival (OS), we observed significant correlations between increased PRS and overall survival (adjusted HR = 1.35, 95% CI = 1.05-1.75, p = 0.021), especially among ER negative patients (adjusted HR = 1.57, 95% CI = 1.07-2.30, p = 0.021) in the multivariate model. Conclusions: The PRS could provide additional information for Chinese women at high risk of breast cancer and holds significant value for BC screening. An increase in PRS also indicates an unfavorable prognosis and could play a crucial role in the clinical management of breast cancer patients at the time of diagnosis.

It is proposed that, through restriction to individuals delineated as high risk, polygenic risk scores (PRSs) might enable more efficient targeting of existing cancer screening programmes and enable extension into new age ranges and disease types. To address this proposition, we present an overview of the performance of PRS tools (ie, models and sets of single nucleotide polymorphisms) alongside harms and benefits of PRS-stratified cancer screening for eight example cancers (breast, prostate, colorectal, pancreas, ovary, kidney, lung, and testicular cancer). For this modelling analysis, we used age-stratified cancer incidences for the UK population from the National Cancer Registration Dataset (2016-18) and published estimates of the area under the receiver operating characteristic curve for current, future, and optimised PRS for each of the eight cancer types. For each of five PRS-defined high-risk quantiles (ie, the top 50%, 20%, 10%, 5%, and 1%) and according to each of the three PRS tools (ie, current, future, and optimised) for the eight cancers, we calculated the relative proportion of cancers arising, the odds ratios of a cancer arising compared with the UK population average, and the lifetime cancer risk. We examined maximal attainable rates of cancer detection by age stratum from combining PRS-based stratification with cancer screening tools and modelled the maximal impact on cancer-specific survival of hypothetical new UK programmes of PRS-stratified screening. The PRS-defined high-risk quintile (20%) of the population was estimated to capture 37% of breast cancer cases, 46% of prostate cancer cases, 34% of colorectal cancer cases, 29% of pancreatic cancer cases, 26% of ovarian cancer cases, 22% of renal cancer cases, 26% of lung cancer cases, and 47% of testicular cancer cases. Extending UK screening programmes to a PRS-defined high-risk quintile including people aged 40-49 years for breast cancer, 50-59 years for colorectal cancer, and 60-69 years for prostate cancer has the potential to avert, respectively, a maximum of 102, 188, and 158 deaths annually. Unstratified screening of the full population aged 48-49 years for breast cancer, 58-59 years for colorectal cancer, and 68-69 years for prostate cancer would use equivalent resources and avert, respectively, an estimated maximum of 80, 155, and 95 deaths annually. These maximal modelled numbers will be substantially attenuated by incomplete population uptake of PRS profiling and cancer screening, interval cancers, non-European ancestry, and other factors. Under favourable assumptions, our modelling suggests modest potential efficiency gain in cancer case detection and deaths averted for hypothetical new PRS-stratified screening programmes for breast, prostate, and colorectal cancer. Restriction of screening to high-risk quantiles means many or most incident cancers will arise in those assigned as being low-risk. To quantify real-world clinical impact, costs, and harms, UK-specific cluster-randomised trials are required. The Wellcome Trust.

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS’s association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06–1.21, p = 4.0 × 10–4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

Polygenic score: An anchor holding the whole life course.

Background: Aggressive breast cancers have increased proliferation or metastatic potential and portend a poor prognosis. The ability to identify women at elevated risk of aggressive cancers could have major implications for screening and prevention, yet there are no available tools for predicting aggressive cancer risk. We sought to construct a polygenic risk score (PRS) for aggressive breast cancers by leveraging the associations of single nucleotide polymorphisms (SNPs) with tumor gene expression. We used as our measure of aggressiveness the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. We hypothesized that known breast cancer susceptibility SNPs would have differential associations with ROR-P, which could then be used to construct a PRS for ROR-P. Methods: We developed our PRS in a case-only analysis of 3 studies containing SNP genotypes and tumor gene expression: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 TRIAL (total n=2,363). We used linear regression models to evaluate individual SNP associations with ROR-P, adjusted for genetic ancestry and study. We then constructed PRS using varying p-value thresholds and used cross-validation to identify the PRS with highest model r2. To assess whether the ROR-P PRS was associated with poor prognosis, we performed survival analysis in two longitudinal cohorts of breast cancer patients: the UK Biobank (women with incident invasive cancers only) and the Pathways Study. These studies included 10,196 total cases with 785 deaths. We built Cox proportional hazards models to evaluate the association between the ROR-P PRS (adjusted for genetic ancestry) and breast cancer-specific survival (BCSS) in both studies. We then performed meta-analysis of the Cox model results. We also constructed joint models containing the ROR-P PRS and a PRS representing the case-case risk of ER-negative vs. ER-positive cancer, PRSER-/ER+. Results: We tested the associations between 226 breast cancer susceptibility SNPs and ROR-P. The best-performing PRS contained 76 SNPs and had a cross-validated r2 of 0.051. In the UK Biobank and Pathways Study, higher ROR-P PRS was associated with worse BCSS, with nearly identical effects observed in each study, HR per standard deviation of 1.13 (95% CI 1.05-1.21, p=9.0x10-4) in meta-analysis. The ROR-P PRS’s effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS was providing additional prognostic information beyond ER status. Conclusions: We used breast cancer susceptibility SNPs to construct a PRS for ROR-P, a prognostic signature recapitulating aggressiveness, and found the ROR-P PRS to be associated with worse BCSS. Our findings represent an improvement on current PRS for overall breast cancer risk, which preferentially predict cancers with favorable prognosis. Given that aggressive cancers are more likely to present as advanced cancers even among women undergoing routine screening, our findings could potentially identify women who may benefit from more intensive screening. Citation Format: Yiwey Shieh, Jacquelyn Roger, Christina Yau, Denise Wolf, Gillian Hirst, Lamorna Swigart, Scott Huntsman, Donglei Hu, Jovia Nierenberg, Pooja Middha, Rachel Heise, Linda Kachuri, Qianqian Zhu, Song Yao, Christine Ambrosone, Marilyn Kwan, Bette Caan, John Witte, Lawrence Kushi, Laura van ’T. Veer, Laura Esserman, Elad Ziv. Development and testing of a polygenic risk score for breast cancer. Aggressiveness. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr PR008.

Background: Breast cancer is the most common cancer among women worldwide. Mutations in high and moderate penetrance genes account for ~10% of breast cancer cases. The remaining genetic predisposition is explained by multiple common genetic variants of relatively small effect. Genome-wide association studies in individuals of mostly European and Asian genetic ancestry have identified multiple risk-associated loci which can be combined into a polygenic risk score (PRS) to predict breast cancer. Our aim was to assess the association of a 313 polymorphism-PRS score (313-PRS) previously published and breast cancer risk in women of a relatively high proportion of Indigenous American ancestry from Peru. Methods: Breast cancer patients were recruited at the Instituto Nacional de Enfermedades Neoplásicas in Lima, Peru, to be part of The Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC, N=1,755). Women without a diagnosis of breast cancer from a pregnancy outcomes study conducted in Lima, Peru, were included as ‘convenience' controls (N=3,342). Genome-wide genotype data were available for all women and missing genotypes were imputed using the Michigan Imputation Server including individuals from 1000 Genomes Project phase III as the reference panel. The 313 polymorphisms were extracted from the imputed data set for further analysis without imputation-r2 filter. Logistic regression was used to test the association between standardized PRS residuals (after adjustment for genetic ancestry) and breast cancer risk. Results: The 313-PRS was positively associated with breast cancer risk in women from Lima, Peru. (OR lowest decile vs. intermediate deciles=0.56, 95%CI= 0.44-0.71, p= 0.00001; OR highest decile vs. intermediate deciles=1.58, 95%CI=1.27-1.95, p= 0.000035). Analysis stratified by quartiles of Indigenous American ancestry did not show heterogeneity. AUROC curve analysis showed similar estimates for all quartiles of Indigenous American ancestry ranging from 0.59 (Q1-lowest ancestry) to 0.61 (Q4-highest ancestry). Conclusion: We confirmed the association between the previously published 313-PRS and breast cancer risk in highly Indigenous American women from Peru. The magnitude of the association and AUROC curve were not statistically significantly different by quartiles of Indigenous American ancestry. The similarity in the AUROC curve estimates by ancestry in a study where the highest ancestry quartile (Q4) includes women with more than 91% Indigenous American ancestry suggests that PRS developed in mostly European women could be used in Latin American populations of high Indigenous American ancestry. Citation Format: Valentina A. Zavala, Tatiana Vidaurre, Xiaosong Huang, Sandro Casavilca, Jeannie Navarro, Michelle A. Williams, Sixto E. Sanchez, Bizu Gelaye, Laura Fejerman. Assessment of previously reported polygenic risk score for breast cancer in Peruvian women [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-203.

10572 Background: Effective breast cancer prevention and management require accurate risk prediction tools. Polygenic risk scores (PRS) have shown promise but are often less effective in non-European populations due to differences in genetic architecture. This study evaluates PRS performance and adaptation for breast cancer in the Thai population, addressing disparities in underrepresented groups. Methods: We retrospectively analyzed breast cancer cases from the Genomics Thailand project at Siriraj Hospital and general population controls from the National Health Examination Survey (NHES) in Thailand. Whole-genome sequencing was performed for cases, and genotyping with imputation was done for controls using the TOPMed r2 reference panel. Clinical data were extracted from electronic medical records. PRS were constructed using SBayesRC, incorporating variants from publicly available genome-wide association study (GWAS) summary statistics and variant functional annotations. Logistic regression and area under the receiver operating characteristic curve (AUC) analyses were conducted using R. Results: The discovery cohort included 975 cases and 1,502 controls, with 230 cases and 265 controls in the validation cohort. Of the 330 previously reported GWAS loci, only 231 lead variants were identified in our dataset. We further analyzed variants near these lead variants within the 330 loci, identifying nominal associations with breast cancer for 329 loci (p<0.05). Four PRS models were tested: (1) 231 variants, (2) ~7 million functional variants based on European (EUR) data, (3) East Asian (EAS) models, and (4) combined EUR and EAS models. The EUR-based model (AUC 0.66) outperformed the 231-variant model (AUC 0.59) and the population-specific EAS model (AUC 0.58) at p<0.05. The combined EUR and EAS models showed no significant improvement over the EUR model alone (AUC 0.66 for both, p=0.69). Individuals in the highest PRS risk group (above the 90 th percentile) had an odds ratio (OR) of 3.34 for breast cancer compared to the rest of the population (95% confidence interval: 2.54–4.42, p<0.05). Among 249 patients with pathology data, PRS was not associated with tumor size, estrogen receptor status, or nodal metastasis. Conclusions: In the Thai population, PRS derived from large-scale European GWAS provided the highest prediction accuracy for breast cancer risk. The limited transferability of a top-variant PRS (e.g., 330-variant model) underscores the challenge posed by variant availability in this population. Validation in prospective studies is essential to optimize PRS utility and address disparities in genetic risk prediction.

Background: Health care professionals often consider family history the most important indicator of invasive breast cancer (IBC) risk and may assume women without a family history of breast cancer (FHBC) are at low risk for IBC. This analysis compared the incidence of IBC in postmenopausal women (PMW) with and without FHBC who were enrolled in the placebo arms of 2 clinical trials.Materials and Methods: The study population for this analysis was PMW with osteoporosis or women with or at high risk for coronary artery disease (CAD). The breast cancer risk (BCR) score [or absolute risk] was calculated using the breast cancer risk assessment (BCRA) tool from the National Cancer Institute (NCI). Descriptive statistics (eg, mean age, BCR score) were calculated for women with or without FHBC. The BCR score was binned into unit intervals and, within each unit, the number of patients, number of IBC cases, and the IBC incidence rates were calculated.Results: Of the 6322 patients included in this analysis (excluding patients ≥86 years old, or with a history of ductal carcinoma in situ or lobular carcinoma in situ), 92 developed IBC (Table 1). For PMW with FHBC [164;12.9%], the mean (±SD) age was 71.3±6.9, the mean BCR score (%) was 3.65±1.09, and all 164 (100%) had a BCR score ≥1.66%, which is consistent with the NSABP Breast Cancer Prevention Trial's definition of “high risk.” For women without FHBC, the mean age was 70.8±6.7, the mean BCR score was 1.74±0.44 and 598 (55.1%) women belonged to the high risk group. For women with or at high risk for CAD and FHBC [443; 8.8%], the mean age was 68.9±6.8, the mean BCR score was 3.52±1.25, and 441 (99.5%) were in the high-risk group. Among women without FHBC (n=4589), the mean age was 67.3±6.6, the mean BCR score was 1.54±0.40, and 1605 (35.0%) were at high risk for IBC. The incidence rate of IBC increased as the absolute risk of breast cancer increased or if FHBC was present, more IBC cases were recorded in women with a lower absolute risk of breast cancer or without a FHBC (Figure 1).Discussion: In general, incidence rates of IBC correlated with BCR estimates and incidence rates were higher as BCR scores increased. However, the majority of women who developed breast cancer had scores between 1% and 2% and did not have FHBC (76/92; 82.6%); many women with IBC (40/92; 43.5%) had BCR scores below the defined high risk cutoff of 1.66%.Total number of all patients, IBC cases and incidence rates grouped by unit BCRA tool score intervalsBCRA Tool Score (%)No. PatientsNo. IBC CasesIBC Incidence Rate(0,1]36610.52(1,2]4602602.61(2,3]881163.74(3,4]369116.28(4,5]35 (5,6]27215.81(6,7]21 (7,8]18222.9(8,9]1 (9,10]1 (10,11] (11,12]1 Total632292 Figure 1: Invasive breast cancer cases and incidence rate by unit BCRA tool risk intervals. The number of cases represented by the black and gray bars are stacked and not additive. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6066.