Identification of a functional genetic variant at 16q12.1 for breast cancer risk: results from the Asia Breast Cancer Consortium

Machine Learning Study of SNPs in Noncoding Regions to Predict Non-small Cell Lung Cancer Susceptibility

Non-small cell lung cancer (NSCLC) is the most common pathological subtype of lung cancer. Both environmental and genetic factors have been reported to impact the lung cancer susceptibility. We conducted a genome-wide association study (GWAS) of 287 NSCLC patients and 467 healthy controls in a Chinese population using the Illumina Genome-Wide Asian Screening Array Chip on 712,095 SNPs (single nucleotide polymorphisms). Using logistic regression modeling, GWAS identified 17 new noncoding region SNP loci associated with the NSCLC risk, and the top three (rs80040741, rs9568547, rs6010259) were under a stringent p-value (<3.02e-6). Notably, rs80040741 and rs6010259 were annotated from the intron regions of MUC3A and MLC1, respectively. Together with another five SNPs previously reported in Chinese NSCLC patients and another four covariates (e.g., smoking status, age, low dose CT screening, sex), a predictive model by machine learning methods can separate the NSCLC from healthy controls with an accuracy of 86%. This is the first time to apply machine learning method in predicting the NSCLC susceptibility using both genetic and clinical characteristics. Our findings will provide a promising method in NSCLC early diagnosis and improve our understanding of applying machine learning methods in precision medicine.

Single nucleotide polymorphisms associated with female breast cancer susceptibility in Chinese population

Breast cancer is a complex disease influenced by both external and internal factors, among which genetic factors play a critical role. Single-nucleotide polymorphisms (SNPs) are major contributors to the heritability of breast cancer, and their frequencies vary across ethnic groups. In this study, we aimed to investigate the association between 34 SNPs identified in previous genome-wide association studies (GWAS) and overall breast cancer risk, as well as breast cancer subtypes, in the Chinese female population. To accomplish this, we conducted an extensive association analysis using the high-throughput Sequenom MassARRAY® platform in a case-control study comprising 1848 breast cancer patients and 709 healthy controls. Our analysis, which utilized the SNPassoc package in R based on chi-squared (χ2) test and genetic model analysis, identified significant associations between breast cancer risk and SNP rs12493607 (TGFBR2, risk allele C, OR = 1.28 [1.11-1.47], P = 0.0005), as well as a less conservatively significant association with rs4784227 (CASC16, risk allele T, OR = 1.24 [1.08-1.42], P = 0.0017) and rs2046210 (ESR1, risk allele A, OR = 1.50 [1.16-1.95], P = 0.0016). Furthermore, our stratified analyses revealed that rs12493607 was significantly associated with invasive carcinoma, estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, HER2-negative, and young (aged younger than 45) breast cancer. SNP rs4784227 and rs3803662 (CASC16) were associated with invasive carcinoma and ER-positive breast cancer, while rs2046210 was linked to ductal carcinoma in situ, ER-negative, PR-negative, HER2-positive, and elder (aged more than 45) breast cancers. SNPs rs10484919 (ESR1) and rs1038304 (CCDC170) showed links to HER2-positive breast cancer, and rs616488 (PEX14) with premenopausal breast cancer. In summary, our study shed light on the relationship between SNPs and breast cancer susceptibility within a vast Chinese cohort, supporting the development of polygenetic risk scores for the Chinese population. These findings provide valuable insights into the genetic basis of breast cancer and have important implications for risk prediction, early detection, and personalized treatment of this disease.

Refining the genetic risk of breast cancer with rare haplotypes and pattern mining

Hundreds of common variants have been found to confer small but significant differences in breast cancer risk, supporting the widely accepted polygenic model of inherited predisposition. Using a novel closed-pattern mining algorithm, we provide evidence that rare haplotypes may refine the association of breast cancer risk with common germline alleles. Our method, called Chromosome Overlap, consists in iteratively pairing chromosomes from affected individuals and looking for noncontiguous patterns of shared alleles. We applied Chromosome Overlap to haplotypes of genotyped SNPs from female breast cancer cases from the UK Biobank at four loci containing common breast cancer-risk SNPs. We found two rare (frequency <0.1%) haplotypes bearing a GWAS hit at 11q13 (hazard ratio = 4.21 and 16.7) which replicated in an independent, European ancestry population at P < 0.05, and another at 22q12 (frequency <0.2%, hazard ratio = 2.58) which expanded the risk pool to noncarriers of a GWAS hit. These results suggest that rare haplotypes (or mutations) may underlie the "synthetic association" of breast cancer risk with at least some common variants.

Comparisons of clinical characteristics, prognosis, epidemiological factors, and genetic susceptibility between HER2-low and HER2-zero breast cancer among Chinese females

BACKGROUND

Traditional human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) is recommended to be divided into HER2-low and HER2-zero subtypes due to different prognosis. However, few studies investigated their differences in clinical characteristics and prognosis among Chinese HER2-negative BC and their stratified differences by hormone receptor (HR), while fewer studies investigated their differences in epidemiological factors and genetic susceptibility.

METHODS

A total of 11,911 HER2-negative BC were included to compare the clinical characteristics and prognosis between HER2-zero and HER2-low BC, and 4227 of the 11,911 HER2-negative BC were further compared to 5653 controls to investigate subtype-specific epidemiological factors and single nucleotide polymorphisms(SNPs).

RESULTS

Overall, 64.2% of HER2-negative BC were HER2-low BC, and the stratified proportions of HER2-low BC were 61.9% and 75.2% for HR-positive and HR-negative BC, respectively. Compared to HER2-zero BC, HER2-low BC among HR-positive BC showed younger age at diagnosis, later stage, poorer differentiation, and higher Ki-67, while elder age at diagnosis and lower mortality were observed for HER2-low BC among HR-negative BC (all p values <0.05). Compared to healthy controls, both HER2-low and HER2-zero BC are associated with similar epidemiological factors and SNPs. However, stronger interaction between epidemiological factors and polygenic risk scores were observed for HER2-zero BC than HER2-low BC among either HR-positive [odds ratios: 10.71 (7.55-15.17) and 8.84 (6.19-12.62) for the highest risk group compared to the lowest risk group] or HR-negative BC [7.00 (3.14-15.63) and 5.70 (3.26-9.98)].

CONCLUSIONS

HER2-low BC should deserve more attention than HER2-zero BC, especially in HR-negative BC, due to larger proportion, less clinical heterogeneity, better prognosis, and less susceptibility to risk factors.

Association between the CASC16 rs4784227 polymorphism and breast cancer risk and prognosis in a northeast Chinese Han population

Background

Breast cancer (BC) poses a serious threat to women worldwide. This research was designed to explore the association between the rs4784227 polymorphism of cancer susceptibility candidate gene 16 (CASC16) and BC susceptibility and prognosis, aiming to provide further information for the early detection of BC and to accelerate comprehensive cancer management.

Methods

A total of 1,733 subjects were recruited for this case-control study, of which 828 are BC patients and 905 are healthy individuals. The relevance between SNP rs4784227 and BC risk in diverse genetic models was analyzed by using the SNPStats analysis program and was assessed by odds ratios (ORs) and 95% confidence intervals (CIs) using the binary logistic regression model. Pearson's χ ² test was used to determine the correlation between the polymorphism and clinical characteristics of BC patients. Additionally, univariate survival analysis was performed by the Kaplan-Meier method and log-rank test, and multivariate survival analysis was performed by Cox regression.

Results

SNP rs4784227 was significantly associated with susceptibility to BC in the dominant model (CT/TT versus CC, OR = 1.237, 95% CI = 1.012-1.513, P = 0.038). The minor allele of SNP rs4784227 was significantly linked to an increased risk of BC (OR = 1.197, 95% CI = 1.022-1.401, P = 0.026). In addition, the rs4784227 polymorphism of CASC16 was associated with perineural invasion (P = 0.030), menstrual status (P = 0.016) and histological grade (P = 0.001, P = 0.003, P = 0.025; respectively) of BC patients. There was no significant association between the genotypes of rs4784227 and disease-free survival (DFS) or overall survival (OS) of breast cancer patients (P > 0.05).

Conclusions

The rs4784227 polymorphism of CASC16 may affect susceptibility to breast cancer and is associated with perineural invasion, menstrual status and histological grade in BC patients. Additionally, our results could not confirm that this polymorphism was related to breast cancer prognosis.

Association between the rs4784227-CASC16 polymorphism and the risk of breast cancer: A meta-analysis

OBJECTIVE

Although several studies have identified an association between the rs4784227-cancer susceptibility candidate gene 16 (CASC16) polymorphism and breast cancer, the results remain inconclusive. Therefore, we conducted a meta-analysis to assess the relationship between the rs4784227-CASC16 polymorphism and breast cancer risk.

METHODS

Studies were searched in the PubMed, Web of Science, Embase, Google Scholar, and Cochran Library databases until June 10, 2021, to identify all potential literature on rs4784227-CASC16 polymorphism and breast cancer risk association. Fixed-effect or random-effect models were used to calculate odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). Subgroup analyses, publication bias, and sensitivity analyses were also conducted.

RESULTS

Seventeen eligible studies involving 34,719 subjects (18,445 cases and 16,274 healthy controls) from 7 articles were included in the current meta-analysis. The pooled ORs regarding the association between the rs4784227-CASC16 polymorphism and breast cancer risk were statistically significant [T vs C: OR = 1.244, 95% CI = 1.202-1.287; TT vs CT + CC: OR = 1.407, 95% CI = 1.296-1.528; CC vs CT + TT: OR = 0.777, 95% CI = 0.745-0.811; TT vs CC: OR = 1.544, 95% CI = 1.419-1.681; CT vs CC: OR = 1.244, 95% CI = 1.189-1.301]. On subgroup analysis, the rs4784227-CASC16 T/C gene has a certain correlation with breast cancer susceptibility in Asian and North American populations, but no significant risk in the Australian population.

CONCLUSION

Our pooled analysis showed a significant association between the rs4784227- (T) allele and breast cancer susceptibility in Asian and North American populations, and intervention with this mutation might be a new therapeutic strategy for breast cancer. However, large-scale and well-designed studies are needed in different populations to further evaluate the role of the rs4784227-CASC16 polymorphism in breast cancer.

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.

Does Direct-to-Consumer Personal Genetic Testing Improve Gynecological Cancer Screening Uptake among Never-Screened Attendees? A Randomized Controlled Study

The clinical impact of direct-to-consumer genetic testing (DTC-GT) on health behavior change has remained controversial. The aim of this study is to clarify the short-term effects of DTC-GT on gynecological cancer screening uptake among middle-aged never-screened Japanese women in a randomized controlled trial (RCT). A total of 144 women aged 45-50 who had never undergone gynecological cancer screening were randomly selected to receive health education (control group), or health education and DTC-GT (intervention group), at a 1:1 ratio. We compared the gynecological screening uptake during the follow-up period. Furthermore, to estimate the impact of learning of an elevated genetic cancer risk in the intervention group, we conducted an analysis dichotomized by genetic risk category. A total of 139 women completed the one-year follow-up survey (69 in the control group and 70 in the intervention group). The follow-up period did not differ between control and intervention groups (the median follow-up period was 276 days and 279 days, respectively, p = 0.746). There were 7 (9.7%) women in the control group and 10 (13.9%) in the intervention group who attended breast cancer screening (p = 0.606), and 9 (12.5%) women from both groups attended cervical cancer screening (p = 1.000). Likewise, there were no significant differences in cancer screening uptake in the analysis stratified by risk category within the intervention group. In conclusion, there was no significant effect of DTC-GT on gynecological cancer screening uptake in this RCT setting. Increasing cancer screening attendance may require a combination of well-established intervention strategies and DTC-GT. Clinical Trial Registration: UMIN-CTR Identifier, UMIN000031709.

A Personal Breast Cancer Risk Stratification Model Using Common Variants and Environmental Risk Factors in Japanese Females

Simple Summary

Breast cancer remains the most common cancer in females, warranting the development of new approaches to prevention. One such approach is personalized prevention using genetic risk models. Here, we developed a risk model using both genetic and environmental risk factors. Results showed that a genetic risk score defined by the number of risk alleles for 14 breast cancer risk SNPs clearly stratified breast cancer risk. Moreover, the combination of this genetic risk score model with an environmental risk model which included established environmental risk factors showed significantly better C-statistics than the environmental risk model alone. This genetic risk score model in combination with the environmental model may be suitable for stratifying individual breast cancer risk, and may form the basis for a new personalized approach to breast cancer prevention.

Abstract

Personalized approaches to prevention based on genetic risk models have been anticipated, and many models for the prediction of individual breast cancer risk have been developed. However, few studies have evaluated personalized risk using both genetic and environmental factors. We developed a risk model using genetic and environmental risk factors using 1319 breast cancer cases and 2094 controls from three case–control studies in Japan. Risk groups were defined based on the number of risk alleles for 14 breast cancer susceptibility loci, namely low (0–10 alleles), moderate (11–16) and high (17+). Environmental risk factors were collected using a self-administered questionnaire and implemented with harmonization. Odds ratio (OR) and C-statistics, calculated using a logistic regression model, were used to evaluate breast cancer susceptibility and model performance. Respective breast cancer ORs in the moderate- and high-risk groups were 1.69 (95% confidence interval, 1.39–2.04) and 3.27 (2.46–4.34) compared with the low-risk group. The C-statistic for the environmental model of 0.616 (0.596–0.636) was significantly improved by combination with the genetic model, to 0.659 (0.640–0.678). This combined genetic and environmental risk model may be suitable for the stratification of individuals by breast cancer risk. New approaches to breast cancer prevention using the model are warranted.

Correlation between Lsp1 (Rs3817198) and Casc (Rs4784227) Polymorphisms and the Susceptibility to Breast Cancer

BACKGROUND

Breast cancer is classified as one of the common cancers among women worldwide. Within numerous genetic factors involved in the development of breast cancer, lsp1 and casc genes are both located on breast cancer susceptibility locus. While the SNP rs3817198 in lsp1 gene has a twilight association with breast cancer in different populations, casc rs4784227 polymorphisms have been reported to associate with breast tumor appearance in Asian, European, and African ancestry populations. The present report was designed a case-control group aimed at assessing the association of these two SNPs with breast cancer risk in the Iranian population.

METHODS

In the case-control study of rs3817198 and rs4784227 polymorphisms in 100 women with breast cancer and 100 healthy women were examined by Tetra Arms PCR. Data collected using SPSS software and chi-square test and correlation coefficient were used for statistical analysis.

RESULTS

The results of current study showed that the Chi-square of lsp1 rs3817198 and casc rs4784227 polymorphism genotypes in breast cancer, were reported to be 51.613 and 47.920, respectively. Also there has been a significance level of both polymorphisms resulting in the frequency of genotypes in these two polymorphisms between case and control group.

CONCLUSION

Our finding thus suggested that in both polymorphisms, homozygote genotype showed strong correlation with cancer susceptibility. While, TT genotype in lsp1 rs3817198 showed significant association with pathogenic properties, in the case of casc rs4784227 genotypes CC, and in second place, TT showed similar correlation.

Identification of two novel breast cancer loci through large-scale genome-wide association study in the Japanese population

Genome-wide association studies (GWAS) have successfully identified about 70 genomic loci associated with breast cancer. Owing to the complexity of linkage disequilibrium and environmental exposures in different populations, it is essential to perform regional GWAS for better risk prediction. This study aimed to investigate the genetic architecture and to assess common genetic risk model of breast cancer with 6,669 breast cancer patients and 21,930 female controls in the Japanese population. This GWAS identified 11 genomic loci that surpass genome-wide significance threshold of P < 5.0 × 10⁻⁸ with nine previously reported loci and two novel loci that include rs9862599 on 3q13.11 (ALCAM) and rs75286142 on 21q22.12 (CLIC6-RUNX1). Validation study was carried out with 981 breast cancer cases and 1,394 controls from the Aichi Cancer Center. Pathway analyses of GWAS signals identified association of dopamine receptor medicated signaling and protein amino acid deacetylation with breast cancer. Weighted genetic risk score showed that individuals who were categorized in the highest risk group are approximately 3.7 times more likely to develop breast cancer compared to individuals in the lowest risk group. This well-powered GWAS is a representative study to identify SNPs that are associated with breast cancer in the Japanese population.

Association of polymorphisms in LOC105377871 and CASC16 with breast cancer in the northwest Chinese Han population

BACKGROUND

Breast cancer represents the cancer with the highest incidence and mortality among women in the world, and its pathogenesis is complex. Single nucleotide polymorphisms (SNPs) are one of the factors that influence the risk of breast cancer. The present study aimed to investigate the effects of LOC105377871 and CASC16 polymorphisms on the risk of breast cancer in the northwest Chinese Han population.

METHODS

We selected 503 breast cancer patients and 503 healthy controls for the present study. Genotyping was performed using the Agena MassARRAY system (Agenea Bioscience, San Diego, CA, USA) and we evaluated the association between SNPs (rs17530068 and rs4784227) and the risk of breast cancer in four genetic models. Unconditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

It was found that the rs17530068 increased the breast cancer risk in log-additive model (p = 0.047, OR = 1.23, 95% CI = 1.00-1.50). After stratification, the "T" allele of rs4784227 increased the risk of lymph node metastasis in breast cancer patients (allele: p = 0.025, OR = 1.51, 95% CI = 1.05-2.17; codominant model: p = 0.008, OR = 1.99, 95% CI = 1.20-3.31; dominant model: p = 0.008, OR = 1.94, 95% CI = 1.19-3.16; log-additive model: p = 0.023, OR = 1.52, 95% CI = 1.06-2.19).

CONCLUSIONS

The results of the present study show that, in the northwest Chinese Han population, SNP rs17530068 (LOC105377871) increases the risk of breast cancer and SNP rs4784227 (CASC16) promotes lymph node metastasis in breast cancer patients.

Association of rs4784227-CASC16 (LOC643714 locus) and rs4782447-ACSF3 polymorphisms and their association with breast cancer risk among Iranian population

TOX3 and FOXA1 proteins are believed to be involved in the susceptibility of breast cancer. rs4784227-CASC16 and rs4782447-ACSF3, as single nucleotide polymorphisms (SNPs), located at the 16q may affect the FOXA1 DNA binding sequence change and therefore may enhance the FOXA1-binding affinity to the promoter of TOX3 gene. This study aimed to investigate the association of these SNPs/haplotypes with breast cancer susceptibility in an Iranian population. We conducted a case-control study of 1072 blood samples (505 breast cancer patients and 567 controls). Genotyping of rs4784227-CASC16 and rs4782447-ACSF3 SNPs was carried out by ARMS-PCR. Moreover, statistical analysis was done using SPSS version 20.0 (IBM Inc., Chicago, IL, USA), PHASE v 2.1 and SNP analyser 2.0. There was a strongly significant statistical association between alleles and genotypes of rs4784227-CASC16 with breast cancer risk in our study population (p<0.05). Moreover, a significant association was demonstrated between TA haplotype and breast cancer risk (OR=0.78; 95% CI (0.62-0.96); P-_value=0.025). In this respect, although we did not observe a statistically significant association between rs4782447-ACSF3 with breast cancer susceptibility, the combination of the effects of rs4784227-CASC16 and rs4782447-ACSF3 SNPs may also affect the risk. This is in line with other studies suggesting these SNPs as risk-associated polymorphisms which may lead to a change in the affinity of FOXA1, as a distal enhancer, to TOX3 and thus change in TOX3 expression, which can eventually affect the risk of breast cancer.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

Genetic Epidemiology of Breast Cancer in Latin America

The last 10 years witnessed an acceleration of our understanding of what genetic factors underpin the risk of breast cancer. Rare high- and moderate-penetrance variants such as those in the BRCA genes account for a small proportion of the familial risk of breast cancer. Low-penetrance alleles are expected to underlie the remaining heritability. By now, there are about 180 genetic polymorphisms that are associated with risk, most of them of modest effect. In combination, they can be used to identify women at the lowest or highest ends of the risk spectrum, which might lead to more efficient cancer prevention strategies. Most of these variants were discovered in populations of European descent. As a result, we might be failing to discover additional polymorphisms that could explain risk in other groups. This review highlights breast cancer genetic epidemiology studies conducted in Latin America, and summarizes the information that they provide, with special attention to similarities and differences with studies in other populations. It includes studies of common variants, as well as moderate- and high-penetrance variants. In addition, it addresses the gaps that need to be bridged in order to better understand breast cancer genetic risk in Latin America.

Identification of novel common breast cancer risk variants at the 6q25 locus among Latinas

Background

Breast cancer is a partially heritable trait and genome-wide association studies (GWAS) have identified over 180 common genetic variants associated with breast cancer. We have previously performed breast cancer GWAS in Latinas and identified a strongly protective single nucleotide polymorphism (SNP) at 6q25, with the protective minor allele originating from indigenous American ancestry. Here we report on fine mapping of the 6q25 locus in an expanded sample of Latinas.

Methods

We performed GWAS in 2385 cases and 6416 controls who were either US Latinas or Mexican women. We replicated the top SNPs in 2412 cases and 1620 controls of US Latina, Mexican, and Colombian women. In addition, we validated the top novel variants in studies of African, Asian and European ancestry. In each dataset we used logistic regression models to test the association between SNPs and breast cancer risk and corrected for genetic ancestry using either principal components or genetic ancestry inferred from ancestry informative markers using a model-based approach.

Results

We identified a novel set of SNPs at the 6q25 locus associated with genome-wide levels of significance (p = 3.3 × 10^− 8 - 6.0 × 10^− 9) not in linkage disequilibrium (LD) with variants previously reported at this locus. These SNPs were in high LD (r² > 0.9) with each other, with the top SNP, rs3778609, associated with breast cancer with an odds ratio (OR) and 95% confidence interval (95% CI) of 0.76 (0.70–0.84). In a replication in women of Latin American origin, we also observed a consistent effect (OR 0.88; 95% CI 0.78–0.99; p = 0.037). We also performed a meta-analysis of these SNPs in East Asians, African ancestry and European ancestry populations and also observed a consistent effect (rs3778609, OR 0.95; 95% CI 0.91–0.97; p = 0.0017).

Conclusion

Our study adds to evidence about the importance of the 6q25 locus for breast cancer susceptibility. Our finding also highlights the utility of performing additional searches for genetic variants for breast cancer in non-European populations.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1085-9) contains supplementary material, which is available to authorized users.

Interaction between genetic ancestry and common breast cancer susceptibility variants in Colombian women

Latino women show lower incidences of breast cancer (BC) than non-Hispanic whites. Large-scale genetic association studies have identified variants robustly associated with BC risk in European women. We examine here the relevance of these variants to Colombian BC and possible interactions with genetic ancestry. Native American, European and African proportions were estimated for 1022 Colombian BC cases and 1023 controls. Logistic regression was applied to assess the association between 78 variants and BC risk and interactions between the variants and ancestry proportions. We constructed a multifactorial risk score combining established BC risk factors, associated risk variants and individual ancestry proportions. Each 1% increase in the Native American proportion translated into a 2.2% lower BC risk (95% CI: 1.4-2.9). Thirteen variants were associated with BC in Colombian women, with allele frequencies and risk effects partially different from European women. Ancestry proportions moderated the risk effects of two variants. The ability of Native American proportions to separate Colombian cases and controls (area-under-the-curve (AUC) = 0.61) was similar to the discriminative ability of family history of BC in first-degree female relatives (AUC = 0.58) or the combined effect of all 13 associated risk variants (AUC = 0.57). Our findings demonstrate ample potential for individualized BC prevention in Hispanic women taking advantage of individual Native American proportions, information on established susceptibility factors and recently identified common risk variants.

Chromatin accessibility prediction via a hybrid deep convolutional neural network

Motivation

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies.

Results

We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases.

Availability and implementation

Deopen is freely available at https://github.com/kimmo1019/Deopen.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Comprehensive cis-eQTL Analysis Revealed Target Genes in Breast Cancer Susceptibility Loci Identified in Genome-wide Association Studies

Genome-wide association studies (GWASs) have identified more than 150 common genetic loci for breast cancer risk. However, the target genes and underlying mechanisms remain largely unknown. We conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using normal or tumor breast transcriptome data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project. We identified a total of 101 genes for 51 lead variants after combing the results of a meta-analysis of METABRIC and TCGA, and the results from GTEx at a Benjamini-Hochberg (BH)-adjusted p < 0.05. Using luciferase reporter assays in both estrogen-receptor positive (ER⁺) and negative (ER^-) cell lines, we showed that alternative alleles of potential functional single-nucleotide polymorphisms (SNPs), rs11552449 (DCLRE1B), rs7257932 (SSBP4), rs3747479 (MRPS30), rs2236007 (PAX9), and rs73134739 (ATG10), could significantly change promoter activities of their target genes compared to reference alleles. Furthermore, we performed in vitro assays in breast cancer cell lines, and our results indicated that DCLRE1B, MRPS30, and ATG10 played a vital role in breast tumorigenesis via certain disruption of cell behaviors. Our findings revealed potential target genes for associations of genetic susceptibility risk loci and provided underlying mechanisms for a better understanding of the pathogenesis of breast cancer.

A functional variant rs4442975 modulating FOXA1-binding affinity does not influence the risk or progression of breast cancer in Chinese Han population

The DNA-binding protein FOXA1 has been shown to regulate nearly all estrogen receptor-chromatin interactions, thereby influencing target gene expression levels in breast cancer (BC) cells. Recently, the rs4442975 T-allele, which disrupts the recruitment of FOXA1 and interacts with the IGFBP5 promoter, was associated to BC susceptibility in a European population. We conducted a hospital-based case-control study that included 1227 cases and 1285 controls to explore the potential association between rs4442975 and BC risk in Chinese Han population, and the effect of this SNP on BC progression was also observed in cases. No significant associations between rs4442975 and BC risk were observed under any genetic models, with an odds ratio of 0.96 (95% confidence interval = 0.81-1.15) under the additive model. When stratified based on estrogen or progesterone receptor expression, smoking or drinking habits, or menopausal status, similar negative associations were observed for all subgroups. No significant associations were observed between rs4442975 and traditional progression factors such as tumor size, nodal status, distant metastasis, or TNM staging. These results reveal that rs4442975 may not confer a risk of BC occurrence or progression in the Chinese Han population, which indicates a distinct association related to genetic heterogeneity across ethnic populations.

Genetic determinants of sporadic breast cancer in Sri Lankan women

Background

While a range of common genetic variants have been identified to be associated with risk of sporadic breast cancer in several Western studies, little is known about their role in South Asian populations. Our objective was to examine the association between common genetic variants in breast cancer related genes and risk of breast cancer in a cohort of Sri Lankan women.

Methods

A case-control study of 350 postmenopausal women with breast cancer and 350 healthy postmenopausal women was conducted. Genotyping using the iPLEX GOLD assay was done for 56 haplotype-tagging single nucleotide polymorphisms (SNPs) in 36 breast cancer related genes. Testing for association was done using an additive genetic model. Odds ratios and 95% confidence intervals were calculated using adjusted logistic regression models.

Results

Four SNPs [rs3218550 (XRCC2), rs6917 (PHB), rs1801516 (ATM), and rs13689 (CDH1)] were significantly associated with risk of breast cancer. The rs3218550 T allele and rs6917 A allele increased breast cancer risk by 1.5-fold and 1.4-fold, respectively. The CTC haplotype defined by the SNPs rs3218552|rs3218550|rs3218536 on chromosome 7 (P = 0.0088) and the CA haplotype defined by the SNPs rs1049620|rs6917 on chromosome 17 (P = 0.0067) were significantly associated with increased risk of breast cancer. The rs1801516 A allele and the rs13689 C allele decreased breast cancer risk by 0.6-fold and 0.7-fold, respectively.

Conclusions

These findings suggest that common genetic polymorphisms in the XRCC2, PHB, CDH1 and ATM genes are associated with risk of breast cancer among Sri Lankan postmenopausal women. The exact biological mechanisms of how these variants regulate overall breast cancer risk need further evaluation using functional studies.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4112-4) contains supplementary material, which is available to authorized users.

The breast cancer susceptibility-related polymorphisms at the TOX3/LOC643714 locus associated with lung cancer risk in a Han Chinese population

It has been well established that besides environmental factors, genetic factors are also associated with lung cancer risk. However, to date, the prior identified genetic variants and loci only explain a small fraction of the familial risk of lung cancer. Hence it is vital to investigate the remaining missing heritability to understand the development and process of lung cancer. In the study, to test our hypothesis that the previously identified breast cancer risk-associated genetic polymorphisms at the TOX3/LOC643714 locus might contribute to lung cancer risk, 16 SNPs at the TOX3/LOC643714 locus were evaluated in a Han Chinese population based on a case-control study. Pearson's chi-square test or Fisher's exact test revealed that rs9933638, rs12443621, and rs3104746 were significantly associated with lung cancer risk (P < 0.001, P < 0.001, and P = 0.005, respectively). Logistic regression analyses displayed that lung cancer risk of individuals with rs9933638(GG+GA) were 1.89 times higher than that of rs9933638AA carriers (OR = 1.893, 95% CI = 1.308-2.741, P = 0.001). Similar findings were manifested for rs12443621 (OR = 1.824, 95% CI = 1.272-2.616, P = 0.001, rs12443621(GG+GA) carriers vs. rs12443621AA carriers) and rs3104746 (OR = 1.665, 95% CI = 1.243-2.230, P = 0.001, rs3104746TT carriers vs. rs3104746(TA+AA) carriers). The study discovered for the first time that three SNPs (rs9933638, rs12443621, and rs3104746) at the TOX3/LOC643714 locus contributed to lung cancer risk, providing new evidences that lung cancer and breast cancer are linked at the molecular and genetic level to a certain extent.

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

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157–3.100), 2.013 (95% CI = 1.227–3.302) and 1.751 (95% CI = 1.073–2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

Genetic variants in long noncoding RNA H19 contribute to the risk of breast cancer in a southeast China Han population

The long noncoding RNA (lncRNA) H19 is a maternally expressed imprinted gene that plays important roles in tumorigenesis, progression, and metastasis. However, the association between polymorphisms on H19 and breast cancer (BC) susceptibility has remained obscure. In this case–control study, we assessed the interaction between two lncRNA H19 single-nucleotide polymorphisms (SNPs) (rs217727 C>T, rs2839698 C>T) and the risk of BC in a Chinese Han population. In total, 1,005 BC cases and 1,020 healthy controls were enrolled in this study. Correlations between genotypes and BC risk were evaluated by multivariate logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs). False-positive report probability calculation was also utilized to identify false-positive associations. We observed that the rs217727 T variant was consistently significantly associated with an increased risk of BC in both codominant and dominant models (CT vs CC, OR 1.25, 95% CI 1.03–1.51; TT vs CC, OR 1.56, 95% CI 1.15–2.09; CT + TT vs CC, OR 1.31, 95% CI 1.09–1.57), and all associations remained significant after Bonferroni correction (P<0.025). Subsequent stratified analyses also revealed that associations between BC risk and rs217727 genotypes were more profound in patients with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, and hormone receptor-positive–HER2-negative molecular subtypes (all passed the threshold for Bonferroni correction, P<0.005). These findings extend available data on the association of H19 polymorphisms and BC susceptibility. Based on these results, we encourage further large-scale studies and functional research to confirm our findings and better elucidate the underlying biological mechanisms.

Genetic and environmental factors and serum hormones, and risk of estrogen receptor-positive breast cancer in pre- and postmenopausal Japanese women

Breast cancer incidence in Japanese women has more than tripled over the past two decades. We have previously shown that this marked increase is mostly due to an increase in the estrogen receptor (ER)-positive, HER2-negative subtype. We conducted a case-control study; ER-positive, HER2-negative breast cancer patients who were diagnosed since 2011 and women without disease were recruited. Environmental factors, serum levels of testosterone and 25-hydroxyvitamin D, and common genetic variants reported as predictors of ER-positive breast cancer or found in Asian women were evaluated between patients and controls in pre- and postmenopausal women. To identify important risk predictors, risk prediction models were created by logistic regression models. In premenopausal women, two environmental factors (history of breastfeeding, and history of benign breast disease) and four genetic variants (TOX3-rs3803662, ESR1-rs2046210, 8q24-rs13281615, and SLC4A7-rs4973768) were considered to be risk predictors, whereas three environmental factors (body mass index, history of breastfeeding, and hyperlipidemia), serum levels of testosterone and 25-hydroxyvitamin D, and two genetic variants (TOX3-rs3803662 and ESR1-rs2046210) were identified as risk predictors. Inclusion of common genetic variants and serum hormone measurements as well as environmental factors improved risk assessment models. The decline in the birthrate according to recent changes of lifestyle might be the main cause of the recent notable increase in the incidence of ER-positive breast cancer in Japanese women.

A functional BRCA1 coding sequence genetic variant contributes to prognosis of triple-negative breast cancer, especially after radiotherapy

PURPOSE

As a subtype of breast cancer, triple-negative breast cancer (TNBC) shows poor prognosis and high heterogeneity. Precise identification of TNBC subgroups relevant to clinical prognosis is crucial in the design and administration of individualized treatments. This study aimed to evaluate the prognostic value of the functional BRCA1 rs799917 genetic variant in TNBC.

METHODS

Associations between the rs799917 polymorphism and progression risk were investigated after genotyping 370 TNBC patients. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox regression.  RESULTS: We found that the rs799917T allele was associated with a significantly increased risk of disease progression and shortened progression-free survival time (PFS) (P = 0.001 for log-rank test). Notably, TNBC patients with the rs799917 CC genotype showed about 22 months prolonged PFS compared to the TT genotype after radiotherapy (HR 4.44, 95% CI 1.98-9.93; P = 2.9 × 10^-4). Additionally, in overweight patients, the mean PFS of the rs799917TT genotype was 10 months shorter than that of the CC genotype (HR 3.57, 95% CI 1.46-8.73, P = 0.005).

CONCLUSIONS

Our findings demonstrate that the functional BRCA1 genetic variant contributes to prognosis of TNBC. Our study also highlights the clinical potential of this polymorphism in the screening of high-risk TNBC patients for recurrence and the possibility of patient-tailored decisions especially during radiotherapy.

Evaluating genetic variants associated with breast cancer risk in high and moderate-penetrance genes in Asians

Over the past 20 years, high-penetrance pathogenic mutations in genes BRCA1, BRCA2, TP53, PTEN, STK11 and CDH1 and moderate-penetrance mutations in genes CHEK2, ATM, BRIP1, PALB2, RAD51C, RAD50 and NBN have been identified for breast cancer. In this study, we investigated whether there are additional variants in these 13 genes associated with breast cancer among women of Asian ancestry. We analyzed up to 654 single nucleotide polymorphisms (SNPs) from 6269 cases and 6624 controls of Asian descent included in the Breast Cancer Association Consortium (BCAC), and up to 236 SNPs from 5794 cases and 5529 controls included in the Shanghai Breast Cancer Genetics Study (SBCGS). We found three missense variants with minor allele frequency (MAF) <0.05: rs80358978 (Gly2508Ser), rs80359065 (Lys2729Asn) and rs11571653 (Met784Val) in the BRCA2 gene, showing statistically significant associations with breast cancer risk, with P-values of 1.2 × 10-4, 1.0 × 10-3 and 5.0 × 10-3, respectively. In addition, we found four low-frequency variants (rs8176085, rs799923, rs8176173 and rs8176258) in the BRCA1 gene, one common variant in the CHEK2 gene (rs9620817), and one common variant in the PALB2 gene (rs13330119) associated with breast cancer risk at P < 0.01. Our study identified several new risk variants in BRCA1, BRCA2, CHEK2, and PALB2 genes in relation to breast cancer risk in Asian women. These results provide further insights that, in addition to the high/moderate penetrance mutations, other low-penetrance variants in these genes may also contribute to breast cancer risk.

A sequence-based method to predict the impact of regulatory variants using random forest

Background

Most disease-associated variants identified by genome-wide association studies (GWAS) exist in noncoding regions. In spite of the common agreement that such variants may disrupt biological functions of their hosting regulatory elements, it remains a great challenge to characterize the risk of a genetic variant within the implicated genome sequence. Therefore, it is essential to develop an effective computational model that is not only capable of predicting the potential risk of a genetic variant but also valid in interpreting how the function of the genome is affected with the occurrence of the variant.

Results

We developed a method named kmerForest that used a random forest classifier with k-mer counts to predict accessible chromatin regions purely based on DNA sequences. We demonstrated that our method outperforms existing methods in distinguishing known accessible chromatin regions from random genomic sequences. Furthermore, the performance of our method can further be improved with the incorporation of sequence conservation features. Based on this model, we assessed importance of the k-mer features by a series of permutation experiments, and we characterized the risk of a single nucleotide polymorphism (SNP) on the function of the genome using the difference between the importance of the k-mer features affected by the occurrence of the SNP. We conducted a series of experiments and showed that our model can well discriminate between pathogenic and normal SNPs. Particularly, our model correctly prioritized SNPs that are proved to be enriched for the binding sites of FOXA1 in breast cancer cell lines from previous studies.

Conclusions

We presented a novel method to interpret functional genetic variants purely base on DNA sequences. The proposed k-mer based score offers an effective means of measuring the impact of SNPs on the function of the genome, and thus shedding light on the identification of genetic risk factors underlying complex traits and diseases.

Genomic Disparities in Breast Cancer Among Latinas

BACKGROUND

Breast cancer is the most common cancer diagnosed among Latinas in the United States and the leading cause of cancer-related death among this population. Latinas tend to be diagnosed at a later stage and have worse prognostic features than their non-Hispanic white counterparts. Genetic and genomic factors may contribute to observed breast cancer health disparities in Latinas.

METHODS

We provide a landscape of our current understanding and the existing gaps that need to be filled across the cancer prevention and control continuum.

RESULTS

We summarize available data on mutations in high and moderate penetrance genes for inherited risk of breast cancer and the associated literature on disparities in awareness of and uptake of genetic counseling and testing in Latina populations. We also discuss common genetic polymorphisms and risk of breast cancer in Latinas. In the treatment setting, we examine tumor genomics and pharmacogenomics in Latina patients with breast cancer.

CONCLUSIONS

As the US population continues to diversify, extending genetic and genomic research into this underserved and understudied population is critical. By understanding the risk of breast cancer among ethnically diverse populations, we will be better positioned to make treatment advancements for earlier stages of cancer, identify more effective and ideally less toxic treatment regimens, and increase rates of survival.

A polygenic risk score for breast cancer risk in a Taiwanese population

BACKGROUND

Multiple common variants identified by genome-wide association studies showed limited evidence of the risk of breast cancer in Taiwan. In this study, we analyzed the breast cancer risk in relation to 13 individual single-nucleotide polymorphisms (SNPs) identified by a GWAS in an Asian population.

METHODS

In total, 446 breast cancer patients and 514 healthy controls were recruited for this case-control study. In addition, we developed a polygenic risk score (PRS) including those variants significantly associated with breast cancer risk, and also evaluated the contribution of PRS and clinical risk factors to breast cancer using receiver operating characteristic curve (AUC).

RESULTS

Logistic regression results showed that nine individual SNPs were significantly associated with breast cancer risk after multiple testing. Among all SNPs, six variants, namely FGFR2 (rs2981582), HCN1 (rs981782), MAP3K1 (rs889312), TOX3 (rs3803662), ZNF365 (rs10822013), and RAD51B (rs3784099), were selected to create PRS model. A dose-response association was observed between breast cancer risk and the PRS. Women in the highest quartile of PRS had a significantly increased risk compared to women in the lowest quartile (odds ratio 2.26; 95% confidence interval 1.51-3.38). The AUC for a model which contained the PRS in addition to clinical risk factors was 66.52%, whereas that for a model which with established risk factors only was 63.38%.

CONCLUSIONS

Our data identified a genetic risk predictor of breast cancer in Taiwanese population and suggest that risk models including PRS and clinical risk factors are useful in discriminating women at high risk of breast cancer from those at low risk.

Previous GWAS hits in relation to young-onset breast cancer

PURPOSE

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered.

METHODS

Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects.

RESULTS

Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR = 1.39; p = 7.0 × 10-6), rs12662670-G (ESR1, RR = 1.56; p = 5.7 × 10-4), rs2981579-A (FGFR2, RR = 1.24; p = 0.002), and rs999737-G (RAD51B, RR = 1.37; p = 0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p = 2.2 × 10-7) and consistent with a multiplicative joint effect (multiplicative-fit p = 0.27). With the multiplicative formulation, the case sister's genetic risk score exceeded that of her unaffected sister in 59% of families.

CONCLUSIONS

The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry

BACKGROUND

Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry.

METHODS

We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk.

RESULTS

We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P < 0.05. Compared with women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively.

CONCLUSION

Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

Genetic and Epigenetic Regulation of TOX3 Expression in Breast Cancer

Genome wide association studies (GWAS) have identified low penetrance and high frequency single nucleotide polymorphisms (SNPs) that contribute to genetic susceptibility of breast cancer. The SNPs at 16q12, close to the TOX3 and CASC16 genes, represent one of the susceptibility loci identified by GWAS, showing strong evidence for breast cancer association across various populations. To examine molecular mechanisms of TOX3 regulation in breast cancer, we investigated both genetic and epigenetic factors using cell lines and datasets derived from primary breast tumors available through The Cancer Genome Atlas (TCGA). TOX3 expression is highly up-regulated in luminal subtype tumors compared to normal breast tissues or basal-like tumors. Expression quantitative trait loci (eQTL) analyses revealed significant associations of rs3803662 and rs4784227 genotypes with TOX3 expression in breast tumors. Bisulfite sequencing of four CpG islands in the TOX3 promoter showed a clear difference between luminal and basal-like cancer cell lines. 5-Aza-2’-deoxycytidine treatment of a basal-like cancer cell line increased expression of TOX3. TCGA dataset verified significantly lower levels of methylation of the promoter in luminal breast tumors with an inverse correlation between methylation and expression of TOX3. Methylation QTL (mQTL) analyses showed a weak or no correlation of rs3803662 or rs4784227 with TOX3 promoter methylation in breast tumors, indicating an independent relationship between the genetic and epigenetic events. These data suggest a complex system of TOX3 regulation in breast tumors, driven by germline variants and somatic epigenetic modifications in a subtype specific manner.

Genome-wide association study in East Asians identifies two novel breast cancer susceptibility loci

Breast cancer is one of the most common malignancies among women worldwide. Genetic factors have been shown to play an important role in breast cancer aetiology. We conducted a two-stage genome-wide association study (GWAS) including 14 224 cases and 14 829 controls of East Asian women to search for novel genetic susceptibility loci for breast cancer. Single nucleotide polymorphisms (SNPs) in two loci were found to be associated with breast cancer risk at the genome-wide significance level. The first locus, represented by rs12118297 at 1p22.3 (near the LMO4 gene), was associated with breast cancer risk with odds ratio (OR) and (95% confidence interval (CI)) of 0.91 (0.88-0.94) and a P-value of 4.48 × 10^{-  8} This association was replicated in another study, DRIVE GAME-ON Consortium, including 16 003 cases and 41 335 controls of European ancestry (OR = 0.95, 95% CI = 0.91-0.99, P-value = 0.019). The second locus, rs16992204 at 21q22.12 (near the LINC00160 gene), was associated with breast cancer risk with OR (95% CI) of 1.13 (1.07-1.18) and a P-value of 4.63 × 10 ^{-  8} The risk allele frequency for this SNP is zero in European-ancestry populations in 1000 Genomes Project and thus its association with breast cancer risk cannot be assessed in DRIVE GAME-ON Consortium. Functional annotation using the ENCODE data indicates that rs12118297 might be located in a repressed element and locus 21q22.12 may affect breast cancer risk through regulating LINC00160 expressions and interaction with oestrogen receptor signalling. Our findings provide additional insights into the genetics of breast cancer.

Analysis of functional germline variants in APOBEC3 and driver genes on breast cancer risk in Moroccan study population

BACKGROUND

Breast cancer (BC) is the most prevalent cancer in women and a major public health problem in Morocco. Several Moroccan studies have focused on studying this disease, but more are needed, especially at the genetic and molecular levels. Therefore, we investigated the potential association of several functional germline variants in the genes commonly mutated in sporadic breast cancer.

METHODS

In this case-control study, we examined 36 single nucleotide polymorphisms (SNPs) in 13 genes (APOBEC3A, APOBEC3B, ARID1B, ATR, MAP3K1, MLL2, MLL3, NCOR1, RUNX1, SF3B1, SMAD4, TBX3, TTN), which were located in the core promoter, 5'-and 3'UTR or which were nonsynonymous SNPs to assess their potential association with inherited predisposition to breast cancer development. Additionally, we identified a ~29.5-kb deletion polymorphism between APOBEC3A and APOBEC3B and explored possible associations with BC. A total of 226 Moroccan breast cancer cases and 200 matched healthy controls were included in this study.

RESULTS

The analysis showed that12 SNPs in 8 driver genes, 4 SNPs in APOBEC3B gene and 1 SNP in APOBEC3A gene were associated with BC risk and/or clinical outcome at P ≤ 0.05 level. RUNX1_rs8130963 (odds ratio (OR) = 2.25; 95 % CI 1.42-3.56; P = 0.0005; dominant model), TBX3_rs8853 (OR = 2.04; 95 % CI 1.38-3.01; P = 0.0003; dominant model), TBX3_rs1061651 (OR= 2.14; 95 % CI1.43-3.18; P = 0.0002; dominant model), TTN_rs12465459 (OR = 2.02; 95 % confidence interval 1.33-3.07; P = 0.0009; dominant model), were the most significantly associated SNPs with BC risk. A strong association with clinical outcome were detected for the genes SMAD4 _rs3819122 with tumor size (OR = 0.45; 95 % CI 0.25-0.82; P = 0.009) and TTN_rs2244492 with estrogen receptor (OR = 0.45; 95 % CI 0.25-0.82; P = 0.009).

CONCLUSION

Our results suggest that genetic variations in driver and APOBEC3 genes were associated with the risk of BC and may have impact on clinical outcome. However, the reported association between the deletion polymorphism and BC risk was not confirmed in the Moroccan population. These preliminary findings require replication in larger studies.

A family-based, genome-wide association study of young-onset breast cancer: inherited variants and maternally mediated effects

Young-onset breast cancer shows certain phenotypic and etiologic differences from older-onset breast cancer and may be influenced by some distinct genetic variants. Few genetic studies of breast cancer have targeted young women and no studies have examined whether maternal variants influence disease in their adult daughters through prenatal effects. We conducted a family-based, genome-wide association study of young-onset breast cancer (age at diagnosis <50 years). A total of 602 188 single-nucleotide polymorphisms (SNPs) were genotyped for 1279 non-Hispanic white cases and their parents or sisters. We used likelihood-based log-linear models to test for transmission asymmetry within families and for maternally mediated genetic effects. Three autosomal SNPs (rs28373882, P=2.8 × 10(-7); rs879162, P=9.2 × 10(-7); rs12606061, P=9.1 × 10(-7)) were associated with risk of young-onset breast cancer at a false-discovery rate below 0.20. None of these loci has been previously linked with young-onset or overall breast cancer risk, and their functional roles are unknown. There was no evidence of maternally mediated, X-linked, or mitochondrial genetic effects, and no notable findings within cancer subcategories defined by menopausal status, estrogen receptor status, or by tumor invasiveness. Further investigations are needed to explore other potential genetic, epigenetic, or epistatic mechanisms and to confirm the association between these three novel loci and young-onset breast cancer.

TOX3 protein expression is correlated with pathological characteristics in breast cancer

TOX3 is a newly identified gene that has been observed to correlate with breast cancer by genome-wide association studies (GWAS) in recent years. In addition, it has been noted that single-nucleotide polymorphisms (SNPs) in the TOX3 gene have a strong correlation with estrogen receptor (ER)-positive tumors. However, the role of TOX3 in breast carcinoma development is still unclear. There are limited studies on the subject of TOX3 mRNA expression in breast tumors and little information on the variation of TOX3 protein expression in relation to the clinical pathological features in breast cancer and healthy tissues. In this study, we characterize the protein expression of TOX3 in breast tumors with respect to various clinical and pathological characteristics and explore the correlation between TOX3 protein expression and ER-positive tumors. A breast cancer tissue microarray containing 267 human breast tumors and 25 healthy controls, breast cancer cell lines (ZR-75-1, MDA-MB-231, MCF-7 and Bcap-37) with positive or negative ER expression, tumor tissues and matched controls were used to analyze the protein expression levels of TOX3 by immunohistochemistry, western blot analysis and quantitative polymerase chain reaction. Among the 267 breast tumor specimens, ER expression was detected in 66 tumor tissues. The expression levels of TOX3 increased in breast carcinoma tissue compared with controls, and were higher in advanced carcinoma (T3 and T4), lymph node metastases tissues (N2) and stage III tissues. Furthermore, TOX3 protein expression was more intense in ER-positive tumors, but did not demonstrate a statistical significance. However, it was significantly increased in ER-positive breast cancer cell lines (ZR-75-1, MCF-7 and Bcap-37) compared with the MDA-MB-231 cell line, which had ER-negative expression. Our findings provide support to the hypothesis that TOX3 has a strong correlation with the development of breast cancer. The current study is likely to assist in investigating the mechanisms involved in breast cancer development.

A pilot genome-wide association study of breast cancer susceptibility loci in Indonesia

Genome-wide association studies (GWASs) of the entire genome provide a systematic approach for revealing novel genetic susceptibility loci for breast cancer. However, genetic association studies have hitherto been primarily conducted in women of European ancestry. Therefofre we here performed a pilot GWAS with a single nucleotide polymorphism (SNP) array 5.0 platform from Affymetrix® that contains 443,813 SNPs to search for new genetic risk factors in 89 breast cancer cases and 46 healthy women of Indonesian ancestry. The case-control association of the GWAS finding set was evaluated using PLINK. The strengths of allelic and genotypic associations were assessed using logistic regression analysis and reported as odds ratios (ORs) and P values; P values less than 1.00x10(-8) and 5.00x10(-5) were required for significant association and suggestive association, respectively. After analyzing 292,887 SNPs, we recognized 11 chromosome loci that possessed suggestive associations with breast cancer risk. Of these, however, there were only four chromosome loci with identified genes: chromosome 2p.12 with the CTNNA2 gene [Odds ratio (OR)=1.20, 95% confidence interval (CI)=1.13-1.33, P=1.08x10(-7)]; chromosome 18p11.2 with the SOGA2 gene (OR=1.32, 95%CI=1.17-1.44, P=6.88x10(-6)); chromosome 5q14.1 with the SSBP2 gene (OR=1.22, 95%CI=1.11-1.34, P=4.00x10(-5)); and chromosome 9q31.1 with the TEX10 gene (OR=1.24, 95%CI=1.12-1.35, P=4.68x10(-5)). This study identified 11 chromosome loci which exhibited suggestive associations with the risk of breast cancer among Indonesian women.

Variants in 6q25.1 Are Associated with Mammographic Density in Malaysian Chinese Women

BACKGROUND

Mammographic density is an established risk factor for breast cancer and has a strong heritable component. Genome-wide association studies (GWAS) for mammographic density conducted in women of European descent have identified several genetic associations, but none of the studies have been tested in Asians. We sought to investigate whether these genetic loci, and loci associated with breast cancer risk and breast size, are associated with mammographic density in an Asian cohort.

METHODS

We conducted genotyping by mass spectrometry in 1,189 women (865 Chinese, 187 Indian, and 137 Malay). Quantitative measurements of mammographic density were performed using ImageJ, a fully automated thresholding technique. The associations of SNPs to densities were analyzed using linear regression models.

RESULTS

We successfully evaluated the associations of 36 SNPs with mammographic densities. After adjusting for age, body mass index, parity, and menopausal status, we found that in our cohort of 865 Malaysian Chinese, three SNPs in the 6q25.1 region near ESR1 (rs2046210, rs12173570, and rs10484919) that were associated with mammographic density, breast cancer risk, or breast size in previous GWAS were significantly associated with both percentage density and absolute dense area. We could not replicate the most significant association found previously in European women (rs10995190, ZNF365 gene) because the minor allele was absent for Asian women.

CONCLUSION

We found that the directions of genetic associations were similar to those reported in Caucasian women.

IMPACT

Our results show that even in Asian women with lower population risk to breast cancer, there is shared heritability between mammographic density and breast cancer risk.

Evaluation of potential regulatory function of breast cancer risk locus at 6q25.1

In a genome-wide association study conducted among Chinese women, we identified the single nucleotide polymorphism (SNP) rs2046210 at 6q25.1 for breast cancer risk. To explore a potential regulatory role for this risk locus, we measured expression levels of nine genes at the locus in breast cancer tissue and adjacent normal tissue samples obtained from 67 patients recruited in the Shanghai Breast Cancer Study. We found that rs2046210 had a statistically significant association with the expression levels of the AKAP12 and ESR1 genes in adjacent normal breast tissues. Women who carry the AA/AG risk genotypes had higher expressions of these two genes compared to those who carry G/G genotypes (P = 0.02 and 0.04 for the AKAP12 and ESR1, respectively). However, no significant differences of SNP rs2046210 with gene expression levels were found in tumor tissues. In The Cancer Genome Atlas samples, the AA/AG risk genotypes of SNP rs2046210 were associated with a significantly higher expression level of the AKAP12 gene and a lower level of the ESR1 gene in tumor tissue. Functional analysis using ENCODE data revealed that SNP rs7763637, which is in strong linkage disequilibrium with SNP rs2046210, is likely a potential functional variant, regulating the AKAP12 gene. Taken together, these results from our study suggest that the association between the 6q25.1 locus and breast cancer risk may be mediated through SNPs that regulate expressions of the AKAP12 gene.

Proper Use of Allele-Specific Expression Improves Statistical Power for cis-eQTL Mapping with RNA-Seq Data

Studies of expression quantitative trait loci (eQTLs) offer insight into the molecular mechanisms of loci that were found to be associated with complex diseases and the mechanisms can be classified into cis- and trans-acting regulation. At present, high-throughput RNA sequencing (RNA-seq) is rapidly replacing expression microarrays to assess gene expression abundance. Unlike microarrays that only measure the total expression of each gene, RNA-seq also provides information on allele-specific expression (ASE), which can be used to distinguish cis-eQTLs from trans-eQTLs and, more importantly, enhance cis-eQTL mapping. However, assessing the cis-effect of a candidate eQTL on a gene requires knowledge of the haplotypes connecting the candidate eQTL and the gene, which cannot be inferred with certainty. The existing two-stage approach that first phases the candidate eQTL against the gene and then treats the inferred phase as observed in the association analysis tends to attenuate the estimated cis-effect and reduce the power for detecting a cis-eQTL. In this article, we provide a maximum-likelihood framework for cis-eQTL mapping with RNA-seq data. Our approach integrates the inference of haplotypes and the association analysis into a single stage, and is thus unbiased and statistically powerful. We also develop a pipeline for performing a comprehensive scan of all local eQTLs for all genes in the genome by controlling for false discovery rate, and implement the methods in a computationally efficient software program. The advantages of the proposed methods over the existing ones are demonstrated through realistic simulation studies and an application to empirical breast cancer data from The Cancer Genome Atlas project.

GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding

MOTIVATION

The majority of disease-associated variants identified in genome-wide association studies reside in noncoding regions of the genome with regulatory roles. Thus being able to interpret the functional consequence of a variant is essential for identifying causal variants in the analysis of genome-wide association studies.

RESULTS

We present GERV (generative evaluation of regulatory variants), a novel computational method for predicting regulatory variants that affect transcription factor binding. GERV learns a k-mer-based generative model of transcription factor binding from ChIP-seq and DNase-seq data, and scores variants by computing the change of predicted ChIP-seq reads between the reference and alternate allele. The k-mers learned by GERV capture more sequence determinants of transcription factor binding than a motif-based approach alone, including both a transcription factor's canonical motif and associated co-factor motifs. We show that GERV outperforms existing methods in predicting single-nucleotide polymorphisms associated with allele-specific binding. GERV correctly predicts a validated causal variant among linked single-nucleotide polymorphisms and prioritizes the variants previously reported to modulate the binding of FOXA1 in breast cancer cell lines. Thus, GERV provides a powerful approach for functionally annotating and prioritizing causal variants for experimental follow-up analysis.

AVAILABILITY AND IMPLEMENTATION

The implementation of GERV and related data are available at http://gerv.csail.mit.edu/.

Interaction between common breast cancer susceptibility variants, genetic ancestry, and nongenetic risk factors in Hispanic women

BACKGROUND

Most genetic variants associated with breast cancer risk have been discovered in women of European ancestry, and only a few genome-wide association studies (GWAS) have been conducted in minority groups. This research disparity persists in post-GWAS gene-environment interaction analyses. We tested the interaction between hormonal and lifestyle risk factors for breast cancer, and ten GWAS-identified SNPs among 2,107 Hispanic women with breast cancer and 2,587 unaffected controls, to gain insight into a previously reported gene by ancestry interaction in this population.

METHODS

We estimated genetic ancestry with a set of 104 ancestry-informative markers selected to discriminate between Indigenous American and European ancestry. We used logistic regression models to evaluate main effects and interactions.

RESULTS

We found that the rs13387042-2q35(G/A) SNP was associated with breast cancer risk only among postmenopausal women who never used hormone therapy [per A allele OR: 0.94 (95% confidence intervals, 0.74-1.20), 1.20 (0.94-1.53), and 1.49 (1.28-1.75) for current, former, and never hormone therapy users, respectively, Pinteraction 0.002] and premenopausal women who breastfed >12 months [OR: 1.01 (0.72-1.42), 1.19 (0.98-1.45), and 1.69 (1.26-2.26) for never, <12 months, and >12 months breastfeeding, respectively, Pinteraction 0.014].

CONCLUSIONS

The correlation between genetic ancestry, hormone replacement therapy use, and breastfeeding behavior partially explained a previously reported interaction between a breast cancer risk variant and genetic ancestry in Hispanic women.

IMPACT

These results highlight the importance of understanding the interplay between genetic ancestry, genetics, and nongenetic risk factors and their contribution to breast cancer risk.

The Role of Constitutional Copy Number Variants in Breast Cancer

Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans.

Association of three SNPs in TOX3 and breast cancer risk: Evidence from 97275 cases and 128686 controls

The associations of SNPs in TOX3 gene with breast cancer risk were investigated by some Genome-wide association studies and epidemiological studies, but the study results were contradictory. To derive a more precise estimate of the associations, we conducted a meta-analysis. ORs with 95% CI were used to assess the strength of association between TOX3 polymorphisms and breast cancer risk in fixed or random effect model. A total of 37 publications with 97275 cases and 128686 controls were identified. We observed that the rs3803662 C > T, rs12443621 A > G and rs8051542 C > T were all correlated with increased risk of breast cancer. In the stratified analyses by ethnicity, significantly elevated risk was detected for all genetic models of the three SNPs in Caucasians. In Asian populations, there were significant associations of rs3803662 and rs8051542 with breast cancer risk. Whereas there was no evidence for statistical significant association between the three SNPs and breast cancer risk in Africans. Additionally, we observed different associations of rs3803662 with breast cancer risk based on different ER subtype and BRCA1/BRCA2 mutation carriers. In conclusion, the meta-analysis suggested that three SNPs in TOX3 were significantly associated with breast cancer risk in different populations.