A genome-wide association study identifies a genetic variant in the SIAH2 locus associated with hormonal receptor-positive breast cancer in Japanese

The role of Siah2 in tumorigenesis and cancer therapy

Seven in absentia homolog 2 (Siah2), an RING E3 ubiquitin ligases, has been characterized to play the vital role in tumorigenesis and cancer progression. Numerous studies have determined that Siah2 promotes tumorigenesis in a variety of human malignancies such as prostate, lung, gastric, and liver cancers. However, several studies revealed that Siah2 exhibited tumor suppressor function by promoting the proteasome-mediated degradation of several oncoproteins, suggesting that Siah2 could exert its biological function according to different stages of tumor development. Moreover, Siah2 is subject to complex regulation, especially the phosphorylation of Siah2 by a variety of protein kinases to regulate its stability and activity. In this review, we describe the structure and regulation of Siah2 in human cancer. Moreover, we highlight the critical role of Siah2 in tumorigenesis. Furthermore, we note that the potential clinical applications of targeting Siah2 in cancer therapy.

Functional Screenings Identify Regulatory Variants Associated with Breast Cancer Susceptibility

Genome-wide association studies (GWAS) have identified more than 2000 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, most of which are located in the non-coding region. However, the causal SNPs functioning as gene regulatory elements still remain largely undisclosed. Here, we applied a Dinucleotide Parallel Reporter sequencing (DiR-seq) assay to evaluate 288 breast cancer risk SNPs in nine different breast cancer cell lines. Further multi-omics analysis with the ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing), DNase-seq (DNase I hypersensitive sites sequencing) and histone modification ChIP-seq (Chromatin Immunoprecipitation sequencing) nominated seven functional SNPs in breast cancer cells. Functional investigations show that rs4808611 affects breast cancer progression by altering the gene expression of NR2F6. For the other site, rs2236007, the alteration promotes the binding of the suppressive transcription factor EGR1 and results in the downregulation of PAX9 expression. The downregulated expression of PAX9 causes cancer malignancies and is associated with the poor prognosis of breast cancer patients. Our findings contribute to defining the functional risk SNPs and the related genes for breast cancer risk prediction.

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.

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.

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.

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.

A meta-analysis approach with filtering for identifying gene-level gene-environment interactions

There is a growing recognition that gene-environment interaction (G × E) plays a pivotal role in the development and progression of complex diseases. Despite a wealth of genetic data on various complex diseases/traits generated from association and sequencing studies, detecting G × E via genome-wide analysis remains challenging due to power issues. In genome-wide G × E studies, a common strategy to improve power is to first conduct a filtering test and retain only the genetic variants that pass the filtering step for subsequent G × E analyses. Two-stage, multistage, and unified tests have been proposed to jointly consider the filtering statistics in G × E tests. However, such G × E tests based on data from a single study may still be underpowered. Meanwhile, large-scale consortia have been formed to borrow strength across studies and populations. In this work, motivated by existing single-study G × E tests with filtering and the needs for meta-analysis G × E approaches based on consortia data, we propose a meta-analysis framework for detecting gene-based G × E effects, and introduce meta-analysis-based filtering statistics in the gene-level G × E tests. Simulations demonstrate the advantages of the proposed method-the ofGEM test. We apply the proposed tests to existing data from two breast cancer consortia to identify the genes harboring genetic variants with age-dependent penetrance (i.e., gene-age interaction effects). We develop an R software package ofGEM for the proposed meta-analysis tests.

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."

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.

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.

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.

Dysregulation of ubiquitin ligases in cancer

Ubiquitin ligases (UBLs) are critical components of the ubiquitin proteasome system (UPS), which governs fundamental processes regulating normal cellular homeostasis, metabolism, and cell cycle in response to external stress signals and DNA damage. Among multiple steps of the UPS system required to regulate protein ubiquitination and stability, UBLs define specificity, as they recognize and interact with substrates in a temporally- and spatially-regulated manner. Such interactions are required for substrate modification by ubiquitin chains, which marks proteins for recognition and degradation by the proteasome or alters their subcellular localization or assembly into functional complexes. UBLs are often deregulated in cancer, altering substrate availability or activity in a manner that can promote cellular transformation. Such deregulation can occur at the epigenetic, genomic, or post-translational levels. Alterations in UBL can be used to predict their contributions, affecting tumor suppressors or oncogenes in select tumors. Better understanding of mechanisms underlying UBL expression and activities is expected to drive the development of next generation modulators that can serve as novel therapeutic modalities. This review summarizes our current understanding of UBL deregulation in cancer and highlights novel opportunities for therapeutic interventions.

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.

Using parental phenotypes in case-parent studies

In studies of case-parent triads, information is often collected about history of the condition in the parents, but typically parental phenotypes are ignored. Including that information in analyses may increase power to detect genetic association for autosomal variants. Our proposed approach uses parental phenotypes to assess association independently of the usual case-parent-based association test, enabling cross-generational internal replication for findings based on offspring and their parents. Our model for parental phenotypes also resists bias due to population stratification. We combine the information from the two generations into a single coherent model that can exploit approximate equality of parental and offspring relative risks to improve power and can also test that equality. We call the resulting procedure the Parent-phenotype Informed Likelihood Ratio Test (PPI-LRT). When some parental genotypes are missing, one can use the expectation-maximization algorithm to fit the combined model. We also develop a second composite test (PPI-CT) based on a linear combination of the parent-phenotype-based test statistic and that from the traditional log-linear, transmission-based test. We evaluate the proposed methods through non-centrality parameter calculations and simulation studies and compare them to the previously proposed approaches, parenTDT and combTDT. We show that incorporation of parental phenotype data often improves statistical power. As illustration, we apply our method to a study of young-onset breast cancer and find that it improved precision for SNPs in FGFR2 and that estimated relative risks based on triads are closely replicated using the parental data.

Surgery in the era of the 'omics revolution

Background

Surgery is entering a new phase with the revolution in genomic technology. Cheap, mass access to next‐generation sequencing is now allowing the analysis of entire human genomes at the DNA and RNA level. These data sets are being used increasingly to identify the molecular differences that underlie common surgical diseases, and enable them to be stratified for patient benefit.

Methods

This article reviews the recent developments in the molecular biology of colorectal, oesophagogastric and breast cancer.

Results

The review specifically covers developments in genetic predisposition, next‐generation sequencing studies, biomarkers for stratification, prognosis and treatment, and other 'omics technologies such as metabolomics and proteomics.

Conclusion

There are unique opportunities over the next decade to change the management of surgical disease radically, using these technologies. The directions that this may take are highlighted, including future advances such as the 100 000 Genomes Project.

May individualize cancer treatment

Telomere-regulating genes and the telomere interactome in familial cancers

Telomeres are repetitive sequence structures at the ends of linear chromosomes that consist of double-stranded DNA repeats followed by a short single-stranded DNA protrusion. Telomeres need to be replicated in each cell cycle and protected from DNA-processing enzymes, tasks that cells execute using specialized protein complexes such as telomerase (that includes TERT), which aids in telomere maintenance and replication, and the shelterin complex, which protects chromosome ends. These complexes are also able to interact with a variety of other proteins, referred to as the telomere interactome, to fulfill their biological functions and control signaling cascades originating from telomeres. Given their essential role in genomic maintenance and cell-cycle control, germline mutations in telomere-regulating proteins and their interacting partners have been found to underlie a variety of diseases and cancer-predisposition syndromes. These syndromes can be characterized by progressively shortening telomeres, in which carriers can present with organ failure due to stem cell senescence among other characteristics, or can also present with long or unprotected telomeres, providing an alternative route for cancer formation. This review summarizes the critical roles that telomere-regulating proteins play in cell-cycle control and cell fate and explores the current knowledge on different cancer-predisposing conditions that have been linked to germline defects in these proteins and their interacting partners.

Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25

The genetic contributions to breast cancer development among Latinas are not well understood. Here we carry out a genome-wide association study of breast cancer in Latinas and identify a genome-wide significant risk variant, located 5′ of the Estrogen Receptor 1 gene (ESR1; 6q25 region). The minor allele for this variant is strongly protective (rs140068132: odds ratio (OR) 0.60, 95% confidence interval (CI) 0.53–0.67, P=9 × 10⁻¹⁸), originates from Indigenous Americans and is uncorrelated with previously reported risk variants at 6q25. The association is stronger for oestrogen receptor-negative disease (OR 0.34, 95% CI 0.21–0.54) than oestrogen receptor-positive disease (OR 0.63, 95% CI 0.49–0.80; P heterogeneity=0.01) and is also associated with mammographic breast density, a strong risk factor for breast cancer (P=0.001). rs140068132 is located within several transcription factor-binding sites and electrophoretic mobility shift assays with MCF-7 nuclear protein demonstrate differential binding of the G/A alleles at this locus. These results highlight the importance of conducting research in diverse populations.

Genome-wide association studies (GWAS) have revealed gene variants associated with breast cancer, but their association with breast cancer development in Latinas is not clear. Here, the authors carry out a GWAS of breast cancer in Latinas and identify a significant protective variant of Indigenous American origin in the 6q25 region.

Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1

In a three-stage genome-wide association study among East Asian women including 22,780 cases and 24,181 controls, we identified three novel genetic loci associated with breast cancer risk, including rs4951011 at 1q32.1 (in intron 2 of the ZC3H11A gene, P = 8.82 × 10⁻⁹), rs10474352 at 5q14.3 (near the ARRDC3 gene, P = 1.67 × 10⁻⁹), and rs2290203 at 15q26.1 (in intron 14 of the PRC1 gene, P = 4.25 × 10⁻⁸). These associations were replicated in European-ancestry populations including 16,003 cases and 41,335 controls (P = 0.030, 0.004, and 0.010, respectively). Data from the ENCODE project suggest that variants rs4951011 and rs10474352 may be located in an enhancer region and transcription factor binding sites, respectively. This study provides additional insights into the genetics and biology of breast cancer.

Seven In Absentia Homolog 2 (SIAH2) downregulation is associated with tamoxifen resistance in MCF-7 breast cancer cells

BACKGROUND

A significant percentage of estrogen receptor (ER)-positive breast cancers are resistant to tamoxifen therapy. Seven in Absentia Homolog 2 (SIAH2), an E3 ubiquitin protein ligase, has been shown to be associated with resistance to antiestrogens. We sought to assess its role in the resistance of a breast cancer cell line, MCF-7, to the ER antagonist, tamoxifen.

MATERIALS AND METHODS

A bioinformatic approach was used for the analysis of SIAH2 expression in breast cancer. MCF-7 and MDA-MB-231, which are ER-positive and -negative breast cancer cell lines, respectively, were used for in vitro studies. SIAH2 and ER-α were selectively knocked down in these cell lines with small-interfering RNAs. Knockdowns were confirmed with Western blot analysis and quantitative real-time polymerase chain reaction. Cells with SIAH2 knockdown were treated with tamoxifen and compared with controls.

RESULTS

Knockdown of SIAH2 followed by treatment with tamoxifen resulted in a significant decrease in the sensitivity of treated ER-positive cells. Of note, knockdown of SIAH2 resulted in downregulation of ER-α, whereas knockdown of ER-α had minimal effect on SIAH2. Consistent with this result, the bioinformatic analysis of clinical data revealed that SIAH2 expression is significantly correlated with ER positivity in human breast cancers, and low SIAH2 expression is associated with a poorer response to tamoxifen.

CONCLUSIONS

SIAH2 appears to be an important modulator of tamoxifen sensitivity in ER-positive MCF-7 cells, mediated, at least in part, through regulation of ER-α expression. Low expression of SIAH2 may be one of the mechanisms that contribute to tamoxifen resistance in human breast cancer.

Genome-wide association studies and the clinic: a focus on breast cancer

Breast cancer is the most frequently diagnosed cancer among women worldwide, and has long been considered to be a genetic disease. A wide range of genetic variants, both rare mutations and more common variants, have been shown to influence breast cancer risk. In particular, recent studies have identified a number of common genetic variants, or single nucleotide polymorphisms, that are associated with breast cancer risk. In this review, we will briefly present the genetic epidemiology of breast cancer, genome-wide association study technology and how this technology may influence breast cancer screening in the clinic.

A common variant in the SIAH2 locus is associated with estrogen receptor-positive breast cancer in the Chinese Han population

Background

Genome-wide association studies (GWAS) have identified many loci associated with breast cancer risk. These studies have primarily been conducted in populations of European descent.

Objective

To determine whether previously reported susceptibility loci in other ethnic groups are also risk factors for breast cancer in a Chinese population.

Method

We genotyped 21 previously reported single nucleotide polymorphisms (SNPs) within a female Chinese cohort of 1203 breast cancer cases and 2525 healthy controls using the Sequenom iPlex platform. Fourteen SNPs passed the quality control test. These SNPs were subjected to statistical analysis for the entire cohort and were further analyzed for estrogen receptor (ER) status. The associations of the SNPs with disease susceptibility were assessed using logistic regression, adjusting for age. The Bonferroni correction was used to conservatively account for multiple testing, and the threshold for statistical significance was P<3.57×10⁻³ (0.05/14).

Result

Although none of the SNPs showed an overall association with breast cancer, an analysis of the ER status of the breast cancer patients revealed that the SIAH2 locus (rs6788895; P = 5.73×10⁻⁴, odds ratio [OR] = 0.81) is associated with ER-positive breast cancer.

Conclusion

A common variant in the SIAH2 locus is associated with ER-positive breast cancer in the Chinese Han population. The replication of published GWAS results in other ethnic groups provides important information regarding the genetic etiology of breast cancer.

Genome-wide association study of breast cancer in the Japanese population

Breast cancer is the most common malignancy among women in worldwide including Japan. Several studies have identified common genetic variants to be associated with the risk of breast cancer. Due to the complex linkage disequilibrium structure and various environmental exposures in different populations, it is essential to identify variants associated with breast cancer in each population, which subsequently facilitate the better understanding of mammary carcinogenesis. In this study, we conducted a genome-wide association study (GWAS) as well as whole-genome imputation with 2,642 cases and 2,099 unaffected female controls. We further examined 13 suggestive loci (P<1.0×10⁻⁵) using an independent sample set of 2,885 cases and 3,395 controls and successfully validated two previously-reported loci, rs2981578 (combined P-value of 1.31×10⁻¹², OR = 1.23; 95% CI = 1.16–.30) on chromosome 10q26 (FGFR2), rs3803662 (combined P-value of 2.79×10⁻¹¹, OR = 1.21; 95% CI = 1.15–.28) and rs12922061 (combined P-value of 3.97×10⁻¹⁰, OR = 1.23; 95% CI = 1.15–.31) on chromosome 16q12 (TOX3-LOC643714). Weighted genetic risk score on the basis of three significantly associated variants and two previously reported breast cancer associated loci in East Asian population revealed that individuals who carry the most risk alleles in category 5 have 2.2 times higher risk of developing breast cancer in the Japanese population than those who carry the least risk alleles in reference category 1. Although we could not identify additional loci associated with breast cancer, our study utilized one of the largest sample sizes reported to date, and provided genetic status that represent the Japanese population. Further local and international collaborative study is essential to identify additional genetic variants that could lead to a better, accurate prediction for breast cancer.

Hereditary breast cancer: ever more pieces to the polygenic puzzle

Several susceptibility genes differentially impact on the lifetime risk for breast cancer. Technological advances over the past years have enabled the detection of genetic risk factors through high-throughput screening of large breast cancer case-control series. High- to intermediate penetrance alleles have now been identified in more than 20 genes involved in DNA damage signalling and repair, and more than 70 low-penetrance loci have been discovered through recent genome-wide association studies. In addition to classical germ-line mutation and single-nucleotide polymorphism, copy number variation and somatic mosaicism have been proposed as potential predisposing mechanisms. Many of the identified loci also appear to influence breast tumour characteristics such as estrogen receptor status. In this review, we briefly summarize present knowledge about breast cancer susceptibility genes and discuss their implications for risk prediction and clinical practice.

Genome-wide association study of chemotherapeutic agent-induced severe neutropenia/leucopenia for patients in Biobank Japan

Chemotherapeutic agents are notoriously known to have a narrow therapeutic range that often results in life-threatening toxicity. Hence, it is clinically important to identify the patients who are at high risk for severe toxicity to certain chemotherapy through a pharmacogenomics approach. In this study, we carried out multiple genome-wide association studies (GWAS) of 13 122 cancer patients who received different chemotherapy regimens, including cyclophosphamide- and platinum-based (cisplatin and carboplatin), anthracycline-based (doxorubicin and epirubicin), and antimetabolite-based (5-fluorouracil and gemcitabine) treatment, antimicrotubule agents (paclitaxel and docetaxel), and topoisomerase inhibitors (camptothecin and etoposide), as well as combination therapy with paclitaxel and carboplatin, to identify genetic variants that are associated with the risk of severe neutropenia/leucopenia in the Japanese population. In addition, we used a weighted genetic risk scoring system to evaluate the cumulative effects of the suggestive genetic variants identified from GWAS in order to predict the risk levels of individuals who carry multiple risk alleles. Although we failed to identify genetic variants that surpassed the genome-wide significance level (P < 5.0 × 10(-8) ) through GWAS, probably due to insufficient statistical power and complex clinical features, we were able to shortlist some of the suggestive associated loci. The current study is at the relatively preliminary stage, but does highlight the complexity and problematic issues associated with retrospective pharmacogenomics studies. However, we hope that verification of these genetic variants through local and international collaborations could improve the clinical outcome for cancer patients.