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

Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions

Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 and Wnt/β-catenin pathways. Single-cell RNA sequencing or in vitro experiment data provided additional functional evidence for 105 genes. Our study uncovered large numbers of association signals and candidate susceptibility genes for breast cancer, uncovered breast cancer genetics and biology, and supported the value of including multi-ancestry data in fine-mapping analyses.

Novel insights into the genetic architecture of pregnancy glycemic traits from 14,744 Chinese maternities

Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.

Exploring Disparities in Pancreatic Ductal Adenocarcinoma Outcomes among Asian and Pacific Islander Subgroups

Pancreatic ductal adenocarcinoma (PDAC) is a challenging malignancy with known disparities in outcomes across ethnicities. Studies specifically investigating PDAC in Asian populations are sparse, overlooking the rich diversity within this group. This research seeks to fill that gap by examining survival differences across the broad spectrum of Asian ethnicities, acknowledging the complexity and varied experiences within these communities. Utilizing the National Cancer Database from 2004 to 2019, we categorized patients into East Asian, Southeast Asian, South Asian, and Pacific Islander groups. Non-Asians or Pacific Islanders were excluded. Overall survival was analyzed using a Cox hazards model. The study consisted of 13,254 patients. Most patients were East Asian (59.4%, n = 7,866). Southeast Asians exhibited the poorest survival in unadjusted analysis (HR, 1.32; 95% confidence interval, 1.23-1.42; P < 0.001) compared with South Asians who exhibited the best survival. Multivariable analysis revealed significantly worse survival for East Asians and Pacific Islanders relative to South Asians, whereas Southeast Asians' results were not significantly different. Asian subgroup differences notably affect PDAC outcomes. Research on genetic and cultural aspects, especially in Southeast Asians, and tackling health disparities are crucial for enhancing survival in this diverse disease.

SIGNIFICANCE

This study highlights the significant survival disparities among Asian subgroups with pancreatic cancer, utilizing a large national database. By differentiating among East Asian, Southeast Asian, South Asian, and Pacific Islander groups, it underscores the need for tailored research and healthcare approaches. Addressing these differences is essential for developing culturally sensitive interventions and potentially improving outcomes in a disease that uniquely affects these diverse populations.

A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Genetic and lifestyle factors for breast cancer risk assessment in Southeast China

BACKGROUND

Despite the rising incidence and mortality of breast cancer among women in China, there are currently few predictive models for breast cancer in the Chinese population and with low accuracy. This study aimed to identify major genetic and life-style risk factors in a Chinese population for potential application in risk assessment models.

METHODS

A case-control study in southeast China was conducted including 1321 breast cancer patients and 2045 controls during 2013-2016, in which the data were randomly divided into a training set and a test set on a 7:3 scale. The association between genetic and life-style factors and breast cancer was examined using logistic regression models. Using AUC curves, we also compared the performance of the logistic model to machine learning models, namely LASSO regression model and support vector machine (SVM), and the scores calculated from CKB, Gail and Tyrer-Cuzick models in the test set.

RESULTS

Among all factors considered, the best model was achieved when polygenetic risk score, lifestyle, and reproductive factors were considered jointly in the logistic regression model (AUC = 0.73; 95% CI: 0.70-0.77). The models created in this study performed better than those using scores calculated from the CKB, Gail, and Tyrer-Cuzick models. However, the logistic model and machine learning models did not significantly differ from one another.

CONCLUSION

In summary, we have found genetic and lifestyle risk predictors for breast cancer with moderate discrimination, which might provide reference for breast cancer screening in southeast China. Further population-based studies are needed to validate the model for future applications in personalized breast cancer screening programs.

Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics

By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10-8 and a Bonferroni-corrected p < 4.6 × 10-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.

The Identification of Large Rearrangements Involving Intron 2 of the CDH1 Gene in BRCA1/2 Negative and Breast Cancer Susceptibility

E-cadherin, a CDH1 gene product, is a calcium-dependent cell-cell adhesion molecule playing a critical role in the establishment of epithelial architecture, maintenance of cell polarity, and differentiation. Germline pathogenic variants in the CDH1 gene are associated with hereditary diffuse gastric cancer (HDGC), and large rearrangements in the CDH1 gene are now being reported as well. Because CDH1 pathogenic variants could be associated with breast cancer (BC) susceptibility, CDH1 rearrangements could also impact it. The aim of our study is to identify rearrangements in the CDH1 gene in 148 BC cases with no BRCA1 and BRCA2 pathogenic variants. To do so, a zoom-in CGH array, covering the exonic, intronic, and flanking regions of the CDH1 gene, was used to screen our cohort. Intron 2 of the CDH1 gene was specifically targeted because it is largely reported to include several regulatory regions. As results, we detected one large rearrangement causing a premature stop in exon 3 of the CDH1 gene in a proband with a bilateral lobular breast carcinoma and a gastric carcinoma (GC). Two large rearrangements in the intron 2, a deletion and a duplication, were also reported only with BC cases without any familial history of GC. No germline rearrangements in the CDH1 coding region were detected in those families without GC and with a broad range of BC susceptibility. This study confirms the diversity of large rearrangements in the CDH1 gene. The rearrangements identified in intron 2 highlight the putative role of this intron in CDH1 regulation and alternative transcripts. Recurrent duplication copy number variations (CNV) are found in this region, and the deletion encompasses an alternative CDH1 transcript. Screening for large rearrangements in the CDH1 gene could be important for genetic testing of BC.

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.

Undergraduate laboratory series that employs a complete polymerase chain reaction-restriction fragment length polymorphism experiment for determination of a single nucleotide polymorphism in CYP2R1 gene

Nowadays, novel Biochemistry lab techniques are being introduced at a very fast pace in scientific research. This requires development of new labs for undergraduate Biochemistry courses to equip the students with up-to-date techniques. However, the time limit of Biochemistry labs for undergraduate students represents a major obstacle. This article presents a clear set of laboratory exercises designed to introduce students to the use of polymerase chain reaction-restriction-fragment length polymorphism (PCR-RFLP) as a means of detection of genetic variants. Three consecutive lab experiments have been designed for the undergraduate students to serve this purpose. The first session was performed in a computer lab (dry lab) where students were taught how to obtain a specific gene sequence, identify an exact single nucleotide polymorphism location, choose the target sequence for amplification, design specific primers for this particular sequence and choose the most suitable restriction enzyme from web tools. The second and third lab sessions were performed as wet labs where in the second lab session, students optimized PCR conditions and performed a successful PCR. The PCR products were kept for use in the third lab session where they utilized the selected restriction enzyme and carried out gel electrophoresis to determine the exact genotype.

Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10-3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10-4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

Cancer health disparities in racial/ethnic minorities in the United States

There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA-African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.

Cancer classification based on chromatin accessibility profiles with deep adversarial learning model

Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not directly support the high-dimensional omics data across the whole genome (Such as ATAC-seq profiles). In this study, based on the deep adversarial learning, we present an end-to-end approach ClusterATAC to leverage high-dimensional features and explore the classification results. On the ATAC-seq dataset and RNA-seq dataset, ClusterATAC has achieved excellent performance. Since ATAC-seq data plays a crucial role in the study of the effects of non-coding regions on the molecular classification of cancers, we explore the clustering solution obtained by ClusterATAC on the pan-cancer ATAC dataset. In this solution, more than 70% of the clustering are single-tumor-type-dominant, and the vast majority of the remaining clusters are associated with similar tumor types. We explore the representative non-coding loci and their linked genes of each cluster and verify some results by the literature search. These results suggest that a large number of non-coding loci affect the development and progression of cancer through its linked genes, which can potentially advance cancer diagnosis and therapy.

Identification of Novel BRCA1 and RAD50 Mutations Associated With Breast Cancer Predisposition in Tunisian Patients

Background

Deleterious mutations on BRCA1/2 genes are known to confer high risk of developing breast and ovarian cancers. The identification of these mutations not only helped in selecting high risk individuals that need appropriate prevention approaches but also led to the development of the PARP-inhibitors targeted therapy. This study aims to assess the prevalence of the most frequent BRCA1 mutation in Tunisia, c.211dupA, and provide evidence of its common origin as well as its clinicopathological characteristics. We also aimed to identify additional actionable variants using classical and next generation sequencing technologies (NGS) which would allow to implement cost-effective genetic testing in limited resource countries.

Patients and Methods

Using sanger sequencing, 112 breast cancer families were screened for c.211dupA. A set of patients that do not carry this mutation were investigated using NGS. Haplotype analysis was performed to assess the founder effect and to estimate the age of this mutation. Correlations between genetic and clinical data were also performed.

Results

The c.211dupA mutation was identified in 8 carriers and a novel private BRCA1 mutation, c.2418dupA, was identified in one carrier. Both mutations are likely specific to North-Eastern Tunisia. Haplotype analysis supported the founder effect of c.211dupA and showed its recent origin. Phenotype-genotype correlation showed that both BRCA1 mutations seem to be associated with a severe phenotype. Whole Exome Sequencing (WES) analysis of a BRCA negative family revealed a Variant of Unknown Significance, c.3647C > G on RAD50. Molecular modeling showed that this variant could be classified as deleterious as it is responsible for destabilizing the RAD50 protein structure. Variant prioritization and pathway analysis of the WES data showed additional interesting candidate genes including MITF and ANKS6.

Conclusion

We recommend the prioritization of BRCA1-c.211dupA screening in high risk breast cancer families originating from the North-East of Tunisia. We also highlighted the importance of NGS in detecting novel mutations, such as RAD50-c.3647C > G. In addition, we strongly recommend using data from different ethnic groups to review the pathogenicity of this variant and reconsider its classification in ClinVar.

LINC00160 mediates sunitinib resistance in renal cell carcinoma via SAA1 that is implicated in STAT3 activation and compound transportation

Patients with advanced renal cell carcinoma who are resistant to sunitinib currently have limited clinical options for treatment. Therefore, it is necessary to explore the biological basis of sunitinib resistance and to uncover new targets for the intervention of sunitinib resistance. In this study, we identified that LINC00160 was associated with sunitinib resistance in renal cell carcinoma. Resistant tumor cells highly expressed LINC00160 to recruit transcriptional factor TFAP2A, which bound to SAA1 promoter regions and activated its expression. On one hand, SAA1 linked to ABCB1 protein, which facilitated sunitinib cellular efflux and diminished drug accumulation. On the other hand, SAA1 stimulated JAK-STAT signaling pathways, which countered cellular survival inhibition from drug. All these regulatory networks were well organized and collaborated, thus promoting sunitinib resistance in renal cell carcinoma. LINC00160 mediates sunitinib resistance in renal cell carcinoma via SAA1 that is implicated in STAT3 activation and compound transportation, which offers an opportunity for targeted intervention and molecular therapies in the future.

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

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

Identification of 5 Gene Signatures in Survival Prediction for Patients with Lung Squamous Cell Carcinoma Based on Integrated Multiomics Data Analysis

Background

Lung squamous cell carcinoma (LSCC) is a frequently diagnosed cancer worldwide, and it has a poor prognosis. The current study is aimed at developing the prediction of LSCC prognosis by integrating multiomics data including transcriptome, copy number variation data, and mutation data analysis, so as to predict patients' survival and discover new therapeutic targets.

Methods

RNASeq, SNP, CNV data, and LSCC patients' clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and the samples were randomly divided into two groups, namely, the training set and the validation set. In the training set, the genes related to prognosis and those with different copy numbers or with different SNPs were integrated to extract features using random forests, and finally, robust biomarkers were screened. In addition, a gene-related prognostic model was established and further verified in the test set and GEO validation set.

Results

We obtained a total of 804 prognostic-related genes and 535 copy amplification genes, 621 copy deletions genes, and 388 significantly mutated genes in genomic variants; noticeably, these genomic variant genes were found closely related to tumor development. A total of 51 candidate genes were obtained by integrating genomic variants and prognostic genes, and 5 characteristic genes (HIST1H2BH, SERPIND1, COL22A1, LCE3C, and ADAMTS17) were screened through random forest feature selection; we found that many of those genes had been reported to be related to LSCC progression. Cox regression analysis was performed to establish 5-gene signature that could serve as an independent prognostic factor for LSCC patients and can stratify risk samples in training set, test set, and external validation set (p < 0.01), and the 5-year survival areas under the curve (AUC) of both training set and validation set were > 0.67.

Conclusion

In the current study, 5 gene signatures were constructed as novel prognostic markers to predict the survival of LSCC patients. The present findings provide new diagnostic and prognostic biomarkers and therapeutic targets for LSCC treatment.

Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants

Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10-8. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women.

The association of CASC16 variants with breast Cancer risk in a northwest Chinese female population

Purpose

Genetic variants play a critical role in the development of breast cancer. This investigation aimed to explore the association between CASC16 polymorphisms and breast cancer susceptibility.

Methods

We conducted a case-control study of 681 patients and 680 healthy individuals to investigate the correlation of five SNPs with breast cancer in a Northwest Chinese female population. Odds ratios (OR) and 95% confidence intervals (CIs) were used to assess the association.

Results

Our study found that rs4784227 and rs12922061 were significantly related to an increased susceptibility to breast cancer (OR 1.22, p = 0.022; OR 1.21, p = 0.026). While rs3803662 was a protective role in breast cancer risk (OR 0.69, p = 0.042). Stratified analyses indicated that rs4784227 and rs12922061 would increase breast cancer susceptibility at age >  50 years. Rs3803662 was a reduced factor of breast cancer risk by age ≤ 50 years. Rs4784227 was significantly increased risk of breast cancer in stage III/IV. The rs45544231 and rs3112612 had a protective effect on breast cancer with tumor size > 2 cm. Rs4784227 and rs12922061 could enhance breast cancer risk in lymph node metastasis positive individuals. CASC16 rs12922061 and rs4784227 polymorphisms correlated with an increased risk of breast cancer in BMI >  24 kg/m². Haplotype analyses revealed that G_rs45544231 T_rs12922061 A_rs3112612 and G_rs45544231 C_rs12922061 A_rs3112612 haplotypes decreased breast cancer risk.

Conclusion

Our study revealed that CASC16 genetic variants were significantly related to breast cancer susceptibility, which might give scientific evidence for exploring the molecular mechanism of breast cancer.

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.

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.

A novel SNP-set analytical method without distinguishing common variants or rare variants in genome-wide association study

Single nucleotide polymorphism (SNP)-set analysis in genome-wide association studies (GWASs) has become a hot topic. Most existing SNP-set analystic methods are designed and work well according to the different natures of common or rare variants and associated diseases. But the information that the disease associated variants are common or rare cannot be gained in advance. Therefore, in this research, we proposed a new and powerful weighted function method without distinguishing common or rare variants to select tagging SNP-set. We applied our selection method to sequence kernel association test (SKAT) and compared the power with some existing methods. The simulation results showed that our method has higher power not only than SKAT in un-weighted case, but also than SKAT in other weighted functions. Moreover, the power is improved significantly when the minor allele frequency (MAF) of causal SNP is relatively small.

Elucidating the Underlying Functional Mechanisms of Breast Cancer Susceptibility Through Post-GWAS Analyses

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide polymorphisms (SNPs) associated with the susceptibility to breast cancer. Together, these SNPs explain 18% of the familial relative risk, which is estimated to be nearly half of the total familial breast cancer risk that is collectively explained by low-risk susceptibility alleles. An important aspect of this success has been the access to large sample sizes through collaborative efforts within the Breast Cancer Association Consortium (BCAC), but also collaborations between cancer association consortia. Despite these achievements, however, understanding of each variant's underlying mechanism and how these SNPs predispose women to breast cancer remains limited and represents a major challenge in the field, particularly since the vast majority of the GWAS-identified SNPs are located in non-coding regions of the genome and are merely tags for the causal variants. In recent years, fine-scale mapping studies followed by functional evaluation of putative causal variants have begun to elucidate the biological function of several GWAS-identified variants. In this review, we discuss the findings and lessons learned from these post-GWAS analyses of 22 risk loci. Identifying the true causal variants underlying breast cancer susceptibility and their function not only provides better estimates of the explained familial relative risk thereby improving polygenetic risk scores (PRSs), it also increases our understanding of the biological mechanisms responsible for causing susceptibility to breast cancer. This will facilitate the identification of further breast cancer risk alleles and the development of preventive medicine for those women at increased risk for developing the disease.

The coexistence of copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) at a locus can result in distorted calculations of the significance in associating SNPs to disease

With the recent advance in genome-wide association studies (GWAS), disease-associated single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) have been extensively reported. Accordingly, the issue of incorrect identification of recombination events that can induce the distortion of multi-allelic or hemizygous variants has received more attention. However, the potential distorted calculation bias or significance of a detected association in a GWAS due to the coexistence of CNVs and SNPs in the same genomic region may remain under-recognized. Here we performed the association study within a congenital scoliosis (CS) cohort whose genetic etiology was recently elucidated as a compound inheritance model, including mostly one rare variant deletion CNV null allele and one common variant non-coding hypomorphic haplotype of the TBX6 gene. We demonstrated that the existence of a deletion in TBX6 led to an overestimation of the contribution of the SNPs on the hypomorphic allele. Furthermore, we generalized a model to explain the calculation bias, or distorted significance calculation for an association study, that can be 'induced' by CNVs at a locus. Meanwhile, overlapping between the disease-associated SNPs from published GWAS and common CNVs (overlap 10%) and pathogenic/likely pathogenic CNVs (overlap 99.69%) was significantly higher than the random distribution (p < 1 × 10^-6 and p = 0.034, respectively), indicating that such co-existence of CNV and SNV alleles might generally influence data interpretation and potential outcomes of a GWAS. We also verified and assessed the influence of colocalizing CNVs to the detection sensitivity of disease-associated SNP variant alleles in another adolescent idiopathic scoliosis (AIS) genome-wide association study. We proposed that detecting co-existent CNVs when evaluating the association signals between SNPs and disease traits could improve genetic model analyses and better integrate GWAS with robust Mendelian principles.

Breast Cancer Family History and Contralateral Breast Cancer Risk in Young Women: An Update From the Women's Environmental Cancer and Radiation Epidemiology Study

Purpose The Women's Environmental Cancer and Radiation Epidemiology (WECARE) study demonstrated the importance of breast cancer family history on contralateral breast cancer (CBC) risk, even for noncarriers of deleterious BRCA1/2 mutations. With the completion of WECARE II, updated risk estimates are reported. Additional analyses that exclude women negative for deleterious mutations in ATM, CHEK2*1100delC, and PALB2 were performed. Patients and Methods The WECARE Study is a population-based case-control study that compared 1,521 CBC cases with 2,212 individually matched unilateral breast cancer (UBC) controls. Participants were younger than age 55 years when diagnosed with a first invasive breast cancer between 1985 and 2008. Women were interviewed about breast cancer risk factors, including family history. A subset of women was screened for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2. Rate ratios (RRs) were estimated using multivariable conditional logistic regression. Cumulative absolute risks (ARs) were estimated by combining RRs from the WECARE Study and population-based SEER*Stat cancer incidence data. Results Women with any first-degree relative with breast cancer had a 10-year AR of 8.1% for CBC (95% CI, 6.7% to 9.8%). Risks also were increased if the relative was diagnosed at an age younger than 40 years (10-year AR, 13.5%; 95% CI, 8.8% to 20.8%) or with CBC (10-year AR, 14.1%; 95% CI, 9.5% to 20.7%). These risks are comparable with those seen in BRCA1/2 deleterious mutation carriers (10-year AR, 18.4%; 95% CI, 16.0% to 21.3%). In the subset of women who tested negative for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2, estimates were unchanged. Adjustment for known breast cancer single-nucleotide polymorphisms did not affect estimates. Conclusion Breast cancer family history confers a high CBC risk, even after excluding women with deleterious mutations. Clinicians are urged to use detailed family histories to guide treatment and future screening decisions for young women with breast cancer.

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.

Identification of breast cancer associated variants that modulate transcription factor binding

Genome-wide association studies (GWAS) have discovered thousands loci associated with disease risk and quantitative traits, yet most of the variants responsible for risk remain uncharacterized. The majority of GWAS-identified loci are enriched for non-coding single-nucleotide polymorphisms (SNPs) and defining the molecular mechanism of risk is challenging. Many non-coding causal SNPs are hypothesized to alter transcription factor (TF) binding sites as the mechanism by which they affect organismal phenotypes. We employed an integrative genomics approach to identify candidate TF binding motifs that confer breast cancer-specific phenotypes identified by GWAS. We performed de novo motif analysis of regulatory elements, analyzed evolutionary conservation of identified motifs, and assayed TF footprinting data to identify sequence elements that recruit TFs and maintain chromatin landscape in breast cancer-relevant tissue and cell lines. We identified candidate causal SNPs that are predicted to alter TF binding within breast cancer-relevant regulatory regions that are in strong linkage disequilibrium with significantly associated GWAS SNPs. We confirm that the TFs bind with predicted allele-specific preferences using CTCF ChIP-seq data. We used The Cancer Genome Atlas breast cancer patient data to identify ANKLE1 and ZNF404 as the target genes of candidate TF binding site SNPs in the 19p13.11 and 19q13.31 GWAS-identified loci. These SNPs are associated with the expression of ZNF404 and ANKLE1 in breast tissue. This integrative analysis pipeline is a general framework to identify candidate causal variants within regulatory regions and TF binding sites that confer phenotypic variation and disease risk.

Genome-Wide Association Studies of Cancer in Diverse Populations

Genome-wide association studies (GWAS) of cancer have identified more than 700 risk loci, of which approximately 80% were first discovered in European ancestry populations, approximately 15% in East Asians, 3% in multiethnic scans, and less than 1% in African and Latin American populations. These percentages closely mirror the distribution of samples included in the discovery phase of cancer GWAS to date (84% European, 11% East Asian, 4% African, and 1% Latin American ancestry). GWAS in non-European ancestry populations have provided insight into ancestry-specific variation in cancer and have pointed to regions of susceptibility that are of particular importance in certain populations. Uncovering and characterizing cancer risk loci in diverse populations is critical for understanding underlying biological mechanisms and developing future genetic risk prediction models in non-European ancestry populations. New GWAS and continued collaborations will be required to eliminate population inequalities in the number of studies, sample sizes, and variant content on GWAS arrays, and to better align genetic research in cancer to the global distribution of race/ethnicity Cancer Epidemiol Biomarkers Prev; 27(4); 405-17. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."