Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study

The FGFR2 Variant rs13387042 is Associated With Breast Cancer Risk: A Meta-Analysis and Systematic Review

OBJECTIVE

The association of FGFR2-rs13387042 polymorphism with breast cancer (BC) susceptibility in women remains inconclusive due to varying reports. In this study, we conducted a meta-analysis to explore the relationship between FGFR2-rs13387042 polymorphism and susceptibility to BC.

METHODS

Relevant literature were acquired through searches across multiple databases. Odds ratio (OR) values were pooled to assess the risk of BC for different alleles and genotypes. The heterogeneity among the included literature was evaluated. Sensitivity analysis was used to verify the stability of the results. Egger's linear regression test was used to assess the significance of publication bias of the included literature.

RESULTS

A total of 17 publications were included, encompassing 122,607 cases and 175,966 controls. There was significantly increased risk of BC for allele A compared with G (OR = 1.15, 95% CI = 1.14-1.67, P < .001), genotype AA compared with GG (OR = 1.34, 95% CI = 1.29-1.38, P < .001), and genotype GA compared with GG (OR = 1.19, 95% CI = 1.12-1.26, P < .001). Both Egger's test and funnel plot indicated the presence of publication bias. After adjusting potential publication bias by the trim-and-fill method, the comparison of allele A versus G (OR = 1.15, 95% CI = 1.13-1.17, P < .001), genotype AA versus GG (OR = 1.32, 95% CI = 1.28-1.37, P < .001), and genotype GA versus GG (OR = 1.15, 95% CI = 1.09-1.22, P < .001) remained statistically significant. In various subgroups, the allele A showed significantly higher risk of BC upon allele G in estrogen receptor (ER) positive BC, ER negative BC, progesterone receptor (PR) positive BC, PR negative BC, triple-negative BC, pathological grade I BC, grade II BC, and grade III breast cancer. The subsequent sensitivity analysis suggested the above findings stable and reliable.

CONCLUSION

In this study, we found that the allele A of the FGFR2-rs13387042 polymorphism is associated with increased risk of developing breast cancer. This study underscores its potential as a genetic marker for personalized risk assessment and targeted interventions.

Polygenic scores in cancer

Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.

Update Breast Cancer 2022 Part 3 - Early-Stage Breast Cancer

This review summarizes recent developments in the prevention and treatment of patients with early-stage breast cancer. The individual disease risk for different molecular subtypes was investigated in a large epidemiological study. With regard to treatment, new data are available from long-term follow-up of the Aphinity study, as well as new data on neoadjuvant therapy with atezolizumab in HER2-positive patients. Biomarkers, such as residual cancer burden, were investigated in the context of pembrolizumab therapy. A Genomic Grade Index study in elderly patients is one of a group of studies investigating the use of modern multigene tests to identify patients with an excellent prognosis in whom chemotherapy may be avoided. These and other aspects of the latest developments in the diagnosis and treatment of breast cancer are described in this review.

The interplay between XPG-Asp1104His polymorphism and reproductive risk factors elevates risk of breast cancer in Tanzanian women: A multiple interaction analysis

BACKGROUND

Reproductive history and genetics are well-known risk factors of breast cancer (BC). Little is known about how these factors interact to effect BC. This study investigated the association of ten polymorphisms in DNA repair genes with BC susceptibility in the Tanzanian samples and further analyzed the association between reproductive risk factors and disease risk METHODS: A hospital-based case-control study in 263 histopathological confirmed BC patients and 250 age-matched cancer-free controls was carried out. Allelic, genotypic, and haplotype association analyses were executed. Also, multifactor dimensionality reduction (MDR), and interaction dendrogram approaches were performed.

RESULTS

The frequency of genotypic and allelic variants of XRCC1-Arg399Gln (rs25487), XRCC2-Arg188His (rs3218536), XRCC3-Thr241Met (rs861539), XPG-Asp1104His (rs17655), and MSH2-Gly322Asp (rs4987188) were significantly different between the groups (p < 0.05). Moreover, XRCC1-Arg399Gln (rs25487), XRCC3-Thr241Met (rs861539), and XPG-Asp1104His (rs17655) were associated with the increased risk of BC in co-dominant, dominant, recessive, and additive genetic-inheritance models (p < 0.05). XRCC1-Arg/Gln genotype indicated a 3.1-fold increased risk of BC in pre-menopausal patients (p = 0.001) while XPG-His/His genotype showed a 1.2-fold increased risk in younger BC patients (<40 years) (p = 0.028). Asp/His+His/His genotypes indicated a 1.3-fold increased risk of BC in PR+ patients and a 1.1-fold decreased risk of BC in luminal-A patients (p = 0.014, p = 0.020, respectively). MDR analysis revealed a positive interaction between BC and the XPG-Asp1104His (rs17655) together with family history of cancer in the first-degree relatives. Dendrogram analysis indicated that the XPG-Asp1104His (rs17655) and family history of cancer in first-degree relatives were significantly synergistic and might be associated with an elevated risk of BC in Tanzania.

CONCLUSIONS

The XPG-Asp1104His (rs17655) might exert both independent and interactive effects on BC development in the Tanzanian women.

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women

Background

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this.

Methods

We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test.

Results

After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6).

Conclusion

In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk.

Impact

Our study suggests a limited role of gene-environment interactions in breast cancer risk.

The distribution of reproductive risk factors disclosed the heterogeneity of receptor-defined breast cancer subtypes among Tanzanian women

Background

Recent epidemiological studies suggest that reproductive factors are associated with breast cancer (BC) molecular subtypes. However, these associations have not been thoroughly studied in the African populations. The present study aimed to investigate the prevalence of BC molecular subtypes and assess their association with reproductive factors in Tanzanian BC patients.

Methods

This hospital-based case-only cross-sectional study consisted of 263 histologically confirmed BC patients in Tanzania. Clinico-pathological data, socio-demographic characteristics, anthropometric measurements, and reproductive risk factors were examined using the Chi-square test and one-way ANOVA. The association among reproductive factors and BC molecular subtypes was analyzed using multinomial logistic regression. The heterogeneity of the associations was assessed using the Wald test.

Results

We found evident subtype heterogeneity for reproductive factors. We observed that post-menopausal status was more prevalent in luminal-A subtype, while compared to luminal-A subtype, luminal-B and HER-2 enriched subtypes were less likely to be found in post-menopausal women (OR: 0.21, 95%CI 0.10–0.41, p = 0.001; OR: 0.39, 95%CI 0.17–0.89, p = 0.026, respectively). Also, the luminal-B subtype was more likely to be diagnosed in patients aged ≤ 40 years than the luminal-A subtype (OR: 2.80, 95%CI 1.46–5.32, p = 0.002). Women who had their first full-term pregnancy at < 30 years were more likely to be of luminal-B (OR: 2.71, 95%CI 1.18–4.17, p = 0.018), and triple-negative (OR: 2.28, 95%CI 1.02–4.07, p = 0.044) subtypes relative to luminal-A subtype. Furthermore, we observed that breastfeeding might have reduced odds of developing luminal-A, luminal-B and triple-negative subtypes. Women who never breastfed were more likely to be diagnosed with luminal-B and triple-negative subtypes when compared to luminal-A subtype (OR: 0.46, 95%CI 0.22–0.95, p = 0.035; OR: 0.41, 95%CI 0.20–0.85, p = 0.017, respectively).

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Conclusion

Our results are the first data reporting reproductive factors heterogeneity among BC molecular subtypes in Tanzania. Our findings suggest that breast-feeding may reduce the likelihood of developing luminal-A, luminal-B, and triple-negative subtypes. Meanwhile, the first full-term pregnancy after 30 years of age could increase the chance of developing luminal-A subtype, a highly prevalent subtype in Tanzania. More interventions to promote modifiable risk factors across multiple levels may most successfully reduce BC incidence in Africa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-021-01536-6.

LncRNA polymorphisms and breast cancer risk

Breast cancer (BC) is the most prevalent cancer in females and the second reason of cancer-related mortality in females in the world. It is thought to be a complex interaction of variables like personal lifestyle, climate, genetics, and reproductive factors. Many polymorphisms have been linked to cancer in genome-wide association experiments, and they are linked to long non-coding RNAs (lncRNAs). LncRNAs, which have > 200 nucleotides in their transcripts, affect many biological processes, including differentiation, migration, apoptosis, cell cycle, and cell proliferation. Different lncRNAs with tumor suppressor and oncogenic roles have been shown to have elevated expression levels in the development of BC. Single-nucleotide polymorphisms (SNPs) in lncRNAs can affect the expression level, structure, and function of lncRNAs. LncRNA polymorphisms are predictive of cancer incidence, making them useful for early detection and customized therapy control. SNPs may affect genetic susceptibility to BC. This study was set to see whether there was a link between lncRNA polymorphisms and the risk of BC. Accordingly, the individual and combined genotypes of lncRNA-related variants could predict BC and clinical and care outcomes. However, further large-scale trials of diverse ethnic groups and comprehensive health records should be performed to validate the results. Furthermore, adequate functional assessments should be carried out to shed light on the etiology of BC. DATA AVAILABILITY: Not applicable.

Human Papillomavirus in Breast Carcinogenesis: A Passenger, a Cofactor, or a Causal Agent?

Simple Summary

Breast cancer (BC) is the most frequent tumor in women worldwide. A minority of BC patients have a family history of the disease, suggesting the importance of environmental and lifestyle factors. Human papillomavirus (HPV) infection has been detected in a subset of tumors, suggesting a potential role in BC. In this review, we summarized relevant information in respect to this topic and we propose a model of HPV-mediated breast carcinogenesis. Evidence suggests that breast tissue is accessible to HPV, which may be a causal agent of BC in a subset of cases.

Abstract

Breast cancer (BC) is the most commonly diagnosed malignancy in women worldwide as well as the leading cause of cancer-related death in this gender. Studies have identified that human papillomavirus (HPV) is a potential risk factor for BC development. While vaccines that protect against oncogenic HPVs infection have been commercially available, global disparities persist due to their high cost. Interestingly, numerous authors have detected an increased high risk (HR)-HPV infection in BC specimens when compared with non-tumor tissues. Therefore, it was suggested that HR-HPV infection could play a role in breast carcinogenesis in a subset of cases. Additional epidemiological and experimental evidence is still needed regarding the role of HR-HPV infection in the development and progression of BC.

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.

A streamlined model for use in clinical breast cancer risk assessment maintains predictive power and is further improved with inclusion of a polygenic risk score

Five-year absolute breast cancer risk prediction models are required to comply with national guidelines regarding risk reduction regimens. Models including the Gail model are under-utilized in the general population for various reasons, including difficulty in accurately completing some clinical fields. The purpose of this study was to determine if a streamlined risk model could be designed without substantial loss in performance. Only the clinical risk factors that were easily answered by women will be retained and combined with an objective validated polygenic risk score (PRS) to ultimately improve overall compliance with professional recommendations. We first undertook a review of a series of 2,339 Caucasian, African American and Hispanic women from the USA who underwent clinical testing. We first used deidentified test request forms to identify the clinical risk factors that were best answered by women in a clinical setting and then compared the 5-year risks for the full model and the streamlined model in this clinical series. We used OPERA analysis on previously published case-control data from 11,924 Gail model samples to determine clinical risk factors to include in a streamlined model: first degree family history and age that could then be combined with the PRS. Next, to ensure that the addition of PRS to the streamlined model was indeed beneficial, we compared risk stratification using the Streamlined model with and without PRS for the existing case-control datasets comprising 1,313 cases and 10,611 controls of African-American (n = 7421), Caucasian (n = 1155) and Hispanic (n = 3348) women, using the area under the curve to determine model performance. The improvement in risk discrimination from adding the PRS risk score to the Streamlined model was 52%, 46% and 62% for African-American, Caucasian and Hispanic women, respectively, based on changes in log OPERA. There was no statistically significant difference in mean risk scores between the Gail model plus risk PRS compared to the Streamlined model plus PRS. This study demonstrates that validated PRS can be used to streamline a clinical test for primary care practice without diminishing test performance. Importantly, by eliminating risk factors that women find hard to recall or that require obtaining medical records, this model may facilitate increased clinical adoption of 5-year risk breast cancer risk prediction test in keeping with national standards and guidelines for breast cancer risk reduction.

Interactions between a Polygenic Risk Score and Non-genetic Risk Factors in Young-Onset Breast Cancer

Most gene-environmental studies have focused on breast cancers generally, the preponderance of which occur after age 50. Young-onset breast cancers (YOBC) tend to be aggressive and may be etiologically different. The goal of this analysis was to assess interactions between an established 77-SNP polygenic risk score (PRS) and non-genetic risk factors for YOBC. We constructed the PRS using a family-based study of 1,291 women diagnosed with breast cancer before age 50 and their parents and unaffected sisters. We used conditional logistic regression to analyze interactions between the PRS and 14 established risk factors. In further analyses we assessed the same interactions, but for invasive cancer, estrogen receptor (ER) positive cancer and with broader inclusion of racial/ethnic groups. Results showed a decreased association between the PRS and YOBC risk for women who had ever used hormonal birth control (odds ratio [OR] = 2.20 versus 3.89) and a stronger association between the PRS and YOBC risk in pre-menopausal women (OR = 2.46 versus 1.23). Restricting the analysis to ER+ cancers or invasive cancers or using samples from all ethnic groups produced similar results. In conclusion, the PRS may interact with hormonal birth control use and with menopausal status on risk of YOBC.

Characterization of lncRNA LINC00520 and functional polymorphisms associated with breast cancer susceptibility in Chinese Han population

Background

The aim was to evaluate the association between the LINC00520 genetic polymorphisms and breast cancer (BC) susceptibility.

Methods

Nine single‐nucleotide polymorphisms (SNPs) on LINC00520 genotyping were performed in 504 BC patients and 505 cancer‐free controls in Chinese Han population to study the relationship between LINC00520 polymorphism and BC susceptibility. qRT‐PCR and luciferase tests were used to explore how rs12880540 affected the expression of LINC00520.

Results

The genotype GG (OR:3.58, 95%CI:1.32‐9.69) in rs8012083 increased the risk of triple‐negative BC. The genotype GG (OR:0.31, 95%CI:0.14‐0.69) in rs8012083, the genotype AA (OR:2.74, 95%CI:1.01‐7.42) in rs2152275, and genotype TG (OR:1.62, 95%CI:1.04‐2.52) in rs12880540 were associated with HER‐2 status. The dominant (OR:0.65, 95%CI:0.45‐0.95) and overdominant genetic model (OR:0.67, 95%CI:0.46‐0.98) consistently showed that rs11622641 T was significantly associated with lower risk of BC. Similarly, the recessive genetic model (OR:1.57, 95%CI:1.07‐2.30) of rs12880540 and the dominant (OR:1.62, 95%CI:1.24‐2.11) and overdominant (OR:1.56, 95%CI:1.19‐2.03) genetic model of rs2152278 may increase the risk of BC. The relative expression of LINC00520 increased linearly with the increase in the number of rs12880540 mutations. rs12880540 alleles were due to the interaction between LINC00520 and miR‐3122 at T, but the mutation of rs12880540 G > T had no effect on the binding ability of LINC00520 and miR‐3122.

Conclusion

A genetic variant of rs8012083 in LINC00520 may be used as a biomarker for triple‐negative BC after further evaluation of diagnostic tests. The genetic variant of LINC00520 was related to the susceptibility of BC, and rs12880540 might affect the corresponding mRNA expression of lncRNA LINC00520.

Update Breast Cancer 2019 Part 4 - Diagnostic and Therapeutic Challenges of New, Personalised Therapies for Patients with Early Breast Cancer

The further development of therapies for women with early breast cancer is progressing far more slowly than in the case of patients with advanced breast cancer and is additionally delayed compared to developments in metastatic breast cancer. Nonetheless, significant advancements have been able to be recorded recently. This review summarises the latest developments in view of the most recent publications and professional conferences. For hormone-receptor-positive patients, new aspects for the duration of antihormone therapy and with regard to the benefits of multigene tests have been published. In the case of HER2-positive patients, the value of post-neoadjuvant therapy and de-escalation of the therapy is discussed. In patients with triple-negative breast cancer, there is a question of whether the knowledge of the biological background of a homologous recombination deficiency (HRD) helps develop new therapies for this subtype. In particular the "use" of a BRCA1/2 mutation or the biological characteristic HRD as a potential motive for therapy plays a role here in specifying the significance of platinum therapy and therapy with PARP inhibitors.

Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC)

BACKGROUND

The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk.

METHODS

We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline.

RESULTS

The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk.

CONCLUSIONS

The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.

Functional Variants in Linc-ROR are Associated with mRNA Expression of Linc-ROR and Breast Cancer Susceptibility

Functional polymorphisms in Linc-ROR may change its ability of regulation by regulating Linc-ROR expression. However, these functional polymorphisms in Linc-ROR and their associations with breast cancer (BC) susceptibility were scarcely reported. In this molecular epidemiological study, four SNPs (rs6420545, rs4801078, rs1942348 and rs9636089) were selected in Linc-ROR by bioinformatics method. Unconditional logistic regression model was performed to analyze the associations between four SNPs and BC susceptibility adjusted for reproductive factors. Quantitative real-time (qRT) PCR was used to evaluate relative expression of Linc-ROR in plasma. The interactions of gene reproductive factors were assessed by Multifactor Dimensionality Reduction (MDR) method. A novel finding showed TT (OR: 1.79; 95%CI: 1.20-2.68) genotype of rs4801078 in Linc-ROR had a significant association with the higher risk of BC and the expression of Linc-ROR mRNA was closely related with the alleles of rs4801078. In addition, we found the interaction of rs4801078, number of pregnancy and menopausal status might increase BC risk (OR: 2.78; 95%CI: 2.74-3.61). Our results suggest that interactions of SNPs in Linc-ROR and reproductive factors might contribute to BC risk, and alleles of rs4801078 might affect Linc-ROR expression level.

Screening for gene-environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction

Identifying gene-environment interactions is a central challenge in the quest to understand susceptibility to complex, multi-factorial diseases. Developing an understanding of how inter-individual variability in inherited genetic variation alters the effects of environmental exposures will enhance our knowledge of disease mechanisms and improve our ability to predict disease and target interventions to high-risk sub-populations. Limited progress has been made identifying gene-environment interactions in the epidemiological setting using existing statistical approaches for genome-wide searches for interaction. In this paper, we describe a novel two-step approach using omics data to conduct genome-wide searches for gene-environment interactions. Using existing genome-wide SNP data from a large Bangladeshi cohort study specifically designed to assess the effect of arsenic exposure on health, we evaluated gene-arsenic interactions by first conducting genome-wide searches for SNPs that modify the effect of arsenic on molecular phenotypes (gene expression and DNA methylation features). Using this set of SNPs showing evidence of interaction with arsenic in relation to molecular phenotypes, we then tested SNP-arsenic interactions in relation to skin lesions, a hallmark characteristic of arsenic toxicity. With the emergence of additional omics data in the epidemiologic setting, our approach may have the potential to boost power for genome-wide interaction research, enabling the identification of interactions that will enhance our understanding of disease etiology and our ability to develop interventions targeted at susceptible sub-populations.

Screening for gene-environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction

Identifying gene-environment interactions is a central challenge in the quest to understand susceptibility to complex, multi-factorial diseases. Developing an understanding of how inter-individual variability in inherited genetic variation alters the effects of environmental exposures will enhance our knowledge of disease mechanisms and improve our ability to predict disease and target interventions to high-risk sub-populations. Limited progress has been made identifying gene-environment interactions in the epidemiological setting using existing statistical approaches for genome-wide searches for interaction. In this paper, we describe a novel two-step approach using omics data to conduct genome-wide searches for gene-environment interactions. Using existing genome-wide SNP data from a large Bangladeshi cohort study specifically designed to assess the effect of arsenic exposure on health, we evaluated gene-arsenic interactions by first conducting genome-wide searches for SNPs that modify the effect of arsenic on molecular phenotypes (gene expression and DNA methylation features). Using this set of SNPs showing evidence of interaction with arsenic in relation to molecular phenotypes, we then tested SNP-arsenic interactions in relation to skin lesions, a hallmark characteristic of arsenic toxicity. With the emergence of additional omics data in the epidemiologic setting, our approach may have the potential to boost power for genome-wide interaction research, enabling the identification of interactions that will enhance our understanding of disease etiology and our ability to develop interventions targeted at susceptible sub-populations.

Genetic variants in lncRNA SRA and risk of breast cancer

Long non-coding RNA (lncRNA) steroid receptor RNA activator (SRA) has been identified to activate steroid receptor transcriptional activity and participate in tumor pathogenesis. This case-control study evaluated the association between two haplotype tagging SNPs (htSNPs) (rs10463297, rs801460) of the whole SRA sequence and breast cancer risk. We found that rs10463297 TC genotype significantly increased BC risk compared with CC genotype in both the codominant (TC vs. TT: OR=1.43, 95 % CI=1.02–2.00) and recessive (TC+CC vs. TT: OR=1.39, 95 % CI=1.01–1.92) genetic models. Both TC, TC + CC genotypes of rs10463297 and GA, AA, GA+AA genotypes of rs801460 were significantly associated with estrogen receptor (ER) positivity status. rs10463297 TC (2.09 ± 0.41), CC (2.42 ± 0.51) and TC + CC (2.20 ± 0.47) genotypes were associated with higher blood plasma SRA mRNA levels compared with the TT genotype(1.45 ± 0.34). Gene–reproductive interaction analysis presented a best model consisted of four factors (rs10463297, age, post-menopausal, No. of pregnancy), which could increase the BC risk with 1.58-fold (OR=1.58, 95 % CI=1.23–2.03). These findings suggest that SRA genetic variants may contribute to BC risk and have apparent interaction with reproductive factors in BC progression.

Association analyses of genetic variants in long non-coding RNA MALAT1 with breast cancer susceptibility and mRNA expression of MALAT1 in Chinese Han population

The long non-coding RNA (lncRNA) Metastasis-associated lung adenocarcinoma transcript 1(MALAT1) has been implicated in breast cancer (BC). Polymorphisms in MALAT1 may play a vital role in the progress of breast cancer by its regulation function. However, potential genetic variants in MALAT1 affecting the development of BC is rarely explored. In our current molecular epidemiology study, all three tagging SNPs (rs3200401, rs619586 and rs7927113) in lncRNA MALAT1 were selected for genotyping in 487BCE patients and 489 cancer-free controls in Chinese Han population, and futher experiment of quantitative real-time (qRT) PCR was conducted to examine the relative expression of MALAT1. The results showed that individuals with genotype AG of rs619586 has a decreased risk of BC in codominant model (OR: 0.684, 95%CI: 0.478-0.979), dominant mode (OR: 0.675, 95%CI: 0.479-0.951) and over-dominant model (OR: 0.692, 95%CI: 0484-0.989). Also, qRT-PCR results revealed that the expression for MALAT1 with AG (0.827±0.490), GG (0.511±0.149) and AG+GG genotypes (0.743±0.447) of rs619586 was significantly lower than that with genotype AA (1.511±0.737). In addition, females with genotype CT of rs3200401 had a lower risk of BC in the codominant model (OR: 0.75, 95%CI: 0.559-1.007) and over-dominant model (OR: 0.741, 95%CI: 0.552-0.993). In summary, our results implied that the genetic variants of lncRNA MALAT1 were associated with the susceptibility of BC, and meaningful genetic alteration might affect the corresponding mRNA expression of lncRNA MALAT1.

Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint  = 0.77, 95% CI: 0.67-0.88, pint  = 1.8 × 10-4 ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10-5 ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10-4 ) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint  = 0.89, 95% CI: 0.83-0.95, pint  = 5.2 × 10-4 ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

The precision relationships between eight GWAS-identified genetic variants and breast cancer in a Chinese population

Some of the new breast cancer susceptibility loci discovered in recent Genome-wide association studies (GWASs) have not been confirmed in Chinese populations. To determine whether eight novel Single-Nucleotide Polymorphisms (SNPs) have associations with breast cancer risk in women from southeast China, we conducted a case-control study of 1,156 breast cancer patients and 1,256 healthy controls. We first validated that the SNPs rs12922061, rs2290203, and rs2981578 were associated with overall breast cancer risk in southeast Chinese women, with the per-allele OR of 1.209 (95%CI: 1.064-1.372), 1.176 (95%CI: 1.048-1.320), and 0.852 (95%CI: 0.759-0.956), respectively. Rs12922061 and rs2290203 even passed the threshold for Bonferroni correction (P value: 0.00625). In stratified analysis, we found another three SNPs were significantly associated within different subgroups. However, after Bonferroni correction (P value: 0.000446), there were no statistically significant was observed. In gene-environment interaction analysis, we observed gene-environment interactions played a potential role of in the risk of breast cancer. These findings provide new insight into the associations between the genetic susceptibility and fine classifications of breast cancer. Based on these results, we encourage further large series studies and functional research to confirm these finding.

MiRNA-binding site functional polymorphisms in DNA repair genes RAD51, RAD52, and XRCC2 and breast cancer risk in Chinese population

RAD51, RAD52, and XRCC2 are all involved in DNA homologous recombinational repair, and there are interactions among those genes. Polymorphisms in 3'-UTR of DNA repair genes may change DNA repair capacity by regulating gene expression. However, potential regulatory variants affecting their expression remain largely unexplored. Five miRNA-binding site SNPs (rs7180135 and rs45549040 in RAD51, rs1051669 and rs7963551 in RAD52 and rs3218550 in XRCC2) selected by bioinformatics method were genotyped in 498 breast cancer (BC) patients and 498 matched controls in Chinese population. Association between SNPs and BC risk was analyzed by adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) in unconditional logistic regression model. Quantitative real-time (qRT) PCR and Western Blot assays were used to calculate the relative expression of RAD52 in recombinant plasmid-pGenesil-1-let-7b group and let-7b-inhibitor group. Gene-reproductive factors interactions were evaluated by multifactor dimensionality reduction (MDR) method. We found that individuals with AC (OR 0.684, 95%CI 0.492-0.951) and CC (OR 0.317, 95%CI 0.200-0.503) genotypes of rs7963551 had a significantly lower risk of breast cancer and qRT-PCR and Western Blot revealed that let-7b might downregulate the expression of RAD52 in MCF-7 and SKBR-3 cells. A significant interaction between the number of pregnancy (≥2) and rs7963551 (Ars7963551) was found to increase breast cancer risk by 2.63-fold (OR 2.63; 95%CI 2.03-3.42). In summary, the miRNA-binding SNPs in DNA repair genes RAD51, RAD52, and XRCC2 and their interaction with reproductive factors might play important roles in the development of BC, and let-7b might downregulate RAD52 expression in MCF-7 and SKBR-3 cells.

Modifiers of breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers

Pathogenic mutations in BRCA1 and BRCA2 are associated with high risks of breast and ovarian cancer. However, penetrance estimates for mutation carriers have been found to vary substantially between studies, and the observed differences in risk are consistent with the hypothesis that genetic and environmental factors modify cancer risks for women with these mutations. Direct evidence that this is the case has emerged in the past decade, through large-scale international collaborative efforts. Here, we describe the methodological challenges in the identification and characterisation of these risk-modifying factors, review the latest evidence on genetic and lifestyle/hormonal risk factors that modify breast and ovarian cancer risks for women with BRCA1 and BRCA2 mutations and outline the implications of these findings for cancer risk prediction. We also review the unresolved issues in this area of research and identify strategies of clinical implementation so that women with BRCA1 and BRCA2 mutations are no longer counselled on the basis of 'average' risk estimates.

Mammalian mitochondrial ribosomal small subunit (MRPS) genes: A putative role in human disease

Mitochondria are prominently understood as power houses producing ATP the primary energy currency of the cell. However, mitochondria are also known to play an important role in apoptosis and autophagy, and mitochondrial dysregulation can lead to pathological outcomes. Mitochondria are known to contain 1500 proteins of which only 13 are coded by mitochondrial DNA and the rest are coded by nuclear genes. Protein synthesis in mitochondria involves mitochondrial ribosomes which are 55-60S particles and are composed of small 28S and large 39S subunits. A feature of mammalian mitoribosome which differentiate it from bacterial ribosomes is the increased protein content. The human mitochondrial ribosomal protein (MRP) gene family comprises of 30 genes which code for mitochondrial ribosomal small subunit and 50 genes for the large subunit. The present review focuses on the mitochondrial ribosomal small subunit genes (MRPS), presents an overview of the literature and data gleaned from publicly available gene and protein expression databases. The survey revealed aberrations in MRPS gene expression patterns in varied human diseases indicating a putative role in their etiology.

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

BACKGROUND

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature.

METHODS

To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed.

RESULTS

A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest.

CONCLUSION

Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings.

Interactions between breast cancer susceptibility loci and menopausal hormone therapy in relationship to breast cancer in the Breast and Prostate Cancer Cohort Consortium

Current use of menopausal hormone therapy (MHT) has important implications for postmenopausal breast cancer risk, and observed associations might be modified by known breast cancer susceptibility loci. To provide the most comprehensive assessment of interactions of prospectively collected data on MHT and 17 confirmed susceptibility loci with invasive breast cancer risk, a nested case-control design among eight cohorts within the NCI Breast and Prostate Cancer Cohort Consortium was used. Based on data from 13,304 cases and 15,622 controls, multivariable-adjusted logistic regression analyses were used to estimate odds ratios (OR) and 95 % confidence intervals (CI). Effect modification of current and past use was evaluated on the multiplicative scale. P values <1.5 × 10(-3) were considered statistically significant. The strongest evidence of effect modification was observed for current MHT by 9q31-rs865686. Compared to never users of MHT with the rs865686 GG genotype, the association between current MHT use and breast cancer risk for the TT genotype (OR 1.79, 95 % CI 1.43-2.24; P interaction = 1.2 × 10(-4)) was less than expected on the multiplicative scale. There are no biological implications of the sub-multiplicative interaction between MHT and rs865686. Menopausal hormone therapy is unlikely to have a strong interaction with the common genetic variants associated with invasive breast cancer.

Gene-environment interaction and risk of breast cancer

Hereditary, genetic factors as well as lifestyle and environmental factors, for example, parity and body mass index, predict breast cancer development. Gene-environment interaction studies may help to identify subgroups of women at high-risk of breast cancer and can be leveraged to discover new genetic risk factors. A few interesting results in studies including over 30,000 breast cancer cases and healthy controls indicate that such interactions exist. Explorative gene-environment interaction studies aiming to identify new genetic or environmental factors are scarce and still underpowered. Gene-environment interactions might be stronger for rare genetic variants, but data are lacking. Ongoing initiatives to genotype larger sample sets in combination with comprehensive epidemiologic databases will provide further opportunities to study gene-environment interactions in breast cancer. However, based on the available evidence, we conclude that associations between the common genetic variants known today and breast cancer risk are only weakly modified by environmental factors, if at all.

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.

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.

Cation-coupled bicarbonate transporters

Cation-coupled HCO3(-) transport was initially identified in the mid-1970s when pioneering studies showed that acid extrusion from cells is stimulated by CO2/HCO3(-) and associated with Na(+) and Cl(-) movement. The first Na(+)-coupled bicarbonate transporter (NCBT) was expression-cloned in the late 1990s. There are currently five mammalian NCBTs in the SLC4-family: the electrogenic Na,HCO3-cotransporters NBCe1 and NBCe2 (SLC4A4 and SLC4A5 gene products); the electroneutral Na,HCO3-cotransporter NBCn1 (SLC4A7 gene product); the Na(+)-driven Cl,HCO3-exchanger NDCBE (SLC4A8 gene product); and NBCn2/NCBE (SLC4A10 gene product), which has been characterized as an electroneutral Na,HCO3-cotransporter or a Na(+)-driven Cl,HCO3-exchanger. Despite the similarity in amino acid sequence and predicted structure among the NCBTs of the SLC4-family, they exhibit distinct differences in ion dependency, transport function, pharmacological properties, and interactions with other proteins. In epithelia, NCBTs are involved in transcellular movement of acid-base equivalents and intracellular pH control. In nonepithelial tissues, NCBTs contribute to intracellular pH regulation; and hence, they are crucial for diverse tissue functions including neuronal discharge, sensory neuron development, performance of the heart, and vascular tone regulation. The function and expression levels of the NCBTs are generally sensitive to intracellular and systemic pH. Animal models have revealed pathophysiological roles of the transporters in disease states including metabolic acidosis, hypertension, visual defects, and epileptic seizures. Studies are being conducted to understand the physiological consequences of genetic polymorphisms in the SLC4-members, which are associated with cancer, hypertension, and drug addiction. Here, we describe the current knowledge regarding the function, structure, and regulation of the mammalian cation-coupled HCO3(-) transporters of the SLC4-family.

Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.

Contrast-enhanced ultrasonography in differential diagnosis of benign and malignant ovarian tumors

Objective

To evaluate the accuracy of contrast-enhanced ultrasonography (CEUS) in differential diagnosis of benign and malignant ovarian tumors.

Methods

The scientific literature databases PubMed, Cochrane Library and CNKI were comprehensively searched for studies relevant to the use of CEUS technique for differential diagnosis of benign and malignant ovarian cancer. Pooled summary statistics for specificity (Spe), sensitivity (Sen), positive and negative likelihood ratios (LR⁺/LR⁻), and diagnostic odds ratio (DOR) and their 95%CIs were calculated. Software for statistical analysis included STATA version 12.0 (Stata Corp, College Station, TX, USA) and Meta-Disc version 1.4 (Universidad Complutense, Madrid, Spain).

Results

Following a stringent selection process, seven high quality clinical trials were found suitable for inclusion in the present meta-analysis. The 7 studies contained a combined total of 375 ovarian cancer patients (198 malignant and 177 benign). Statistical analysis revealed that CEUS was associated with the following performance measures in differential diagnosis of ovarian tumors: pooled Sen was 0.96 (95%CI = 0.92∼0.98); the summary Spe was 0.91 (95%CI = 0.86∼0.94); the pooled LR⁺ was 10.63 (95%CI = 6.59∼17.17); the pooled LR− was 0.04 (95%CI = 0.02∼0.09); and the pooled DOR was 241.04 (95% CI = 92.61∼627.37). The area under the SROC curve was 0.98 (95% CI = 0.20∼1.00). Lastly, publication bias was not detected (t = −0.52, P = 0.626) in the meta-analysis.

Conclusions

Our results revealed the high clinical value of CEUS in differential diagnosis of benign and malignant ovarian tumors. Further, CEUS may also prove to be useful in differential diagnosis at early stages of this disease.

MAPK genes interact with diet and lifestyle factors to alter risk of breast cancer: the Breast Cancer Health Disparities Study

Mitogen-activated protein kinases (MAPK) are integration points for multiple biochemical signals. We evaluated 13 MAPK genes with breast cancer risk and determined if diet and lifestyle factors mediated risk. Data from 3 population-based case-control studies conducted in Southwestern United States, California, and Mexico included 4183 controls and 3592 cases. Percent Indigenous American (IA) ancestry was determined from 104 ancestry informative markers. The adaptive rank truncated product (ARTP) was used to determine the significance of each gene and the pathway with breast cancer risk, by menopausal status, genetic ancestry level, and estrogen receptor (ER)/progesterone receptor (PR) strata. MAP3K9 was associated with breast cancer overall (P(ARTP) = 0.02) with strongest association among women with the highest IA ancestry (P(ARTP) = 0.04). Several SNPs in MAP3K9 were associated with ER+/PR+ tumors and interacted with dietary oxidative balance score (DOBS), dietary folate, body mass index (BMI), alcohol consumption, cigarette smoking, and a history of diabetes. DUSP4 and MAPK8 interacted with calories to alter breast cancer risk; MAPK1 interacted with DOBS, dietary fiber, folate, and BMI; MAP3K2 interacted with dietary fat; and MAPK14 interacted with dietary folate and BMI. The patterns of association across diet and lifestyle factors with similar biological properties for the same SNPs within genes provide support for associations.

Germline DNA variations in breast cancer predisposition and prognosis: a systematic review of the literature

Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented.

Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium

Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 × 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.

Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer

Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.

Candidate gene-environment interactions in breast cancer

Gene-environment interactions have the potential to shed light on biological processes leading to disease, identify individuals for whom risk factors are most relevant, and improve the accuracy of epidemiological risk models. We review the progress that has been made in investigating gene-environment interactions in the field of breast cancer. Although several large-scale analyses have been carried out, only a few significant interactions have been reported. One of these, an interaction between CASP8-rs1045485 and alcohol consumption has been replicated, but others have not, including LSP1- rs3817198 and parity, and 1p11.2-rs11249433 and ever being parous. False positive interactions may arise if the gene and environment are correlated and the causal variant is less frequent than the tag SNP. We conclude that while much progress has been made in this area it is still too soon to tell whether gene-environment interactions will fulfil their promise. Before we can make this assessment we will need to replicate (or refute) the reported interactions, identify the causal variants that underlie tag-SNP associations and validate the next generation of epidemiological risk models.

Post-GWAS gene-environment interplay in breast cancer: results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79,000 women

We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNM stage, tumor grade, tumor size, age at diagnosis, estrogen receptor status and progesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (Pinteraction = 8.84 × 10(-4)) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hits and the epidemiologic risk factors taken into consideration, but we propose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.

Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases

Rheumatic diseases offer distinct challenges to researchers because of heterogeneity in disease phenotypes, low disease incidence, and geographic variation in genetic and environmental factors. Emerging research areas, including epigenetics, metabolomics, and the microbiome, may provide additional links between genetic and environmental risk factors in the pathogenesis of rheumatic disease. This article reviews the methods used to establish genetic and environmental risk factors and studies gene-environment interactions in rheumatic diseases, and provides specific examples of successes and challenges in identifying gene-environment interactions in rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Emerging research strategies and future challenges are discussed.

Reproductive windows, genetic loci, and breast cancer risk

PURPOSE

The reproductive windows between age at menarche and age at first birth (standardized age at first birth) and from menarche to menopause (reproductive lifespan) may interact with genetic variants in association with breast cancer risk.

METHODS

We assessed this hypothesis in 6131 breast cancer cases and 7274 controls who participated in the population-based Collaborative Breast Cancer Study. Risk factor information was collected through telephone interviews, and DNA samples were collected on a subsample (N= 1484 cases, 1307 controls) to genotype for 13 genome-wide association study-identified loci. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and P values for the interaction between reproductive windows and genotypes were obtained by adding cross-product terms to statistical models.

RESULTS

For standardized age at first birth, the OR was 1.52 (CI, 1.36-1.71) comparing the highest quintile with the lowest quintile. Carrier status for rs10941679 (5p12) and rs10483813 (RAD51B) appeared to modify this relationship (P = .04 and P = .02, respectively). For reproductive lifespan, the OR comparing the highest quintile with the lowest quintiles was 1.62 (CI, 1.35-1.95). No interactions were detected between genotype and reproductive lifespan (all P > .05). All results were similar regardless of ductal versus lobular breast cancer subtype.

CONCLUSIONS

Our results suggest that the reproductive windows are associated with breast cancer risk and that associations may vary by genetic variants.

Human MCS5A1 candidate breast cancer susceptibility gene FBXO10 is induced by cellular stress and correlated with lens epithelium-derived growth factor (LEDGF)

Genetic variation and candidate genes associated with breast cancer susceptibility have been identified. Identifying molecular interactions between associated genetic variation and cellular proteins may help to better understand environmental risk. Human MCS5A1 breast cancer susceptibility associated SNP rs7042509 is located in F-box protein 10 (FBXO10). An orthologous Rattus norvegicus DNA-sequence that contains SNV ss262858675 is located in rat Mcs5a1, which is part of a mammary carcinoma susceptibility locus controlling tumor development in a non-mammary cell-autonomous manner via an immune cell-mediated mechanism. Higher Fbxo10 expression in T cells is associated with Mcs5a increased susceptibility alleles. A common DNA-protein complex bound human and rat sequences containing MCS5A1/Mcs5a1 rs7042509/ss262858675 in electrophoretic mobility shift assays (EMSAs). Lens epithelium-derived growth factor (LEDGF), a stress-response protein, was identified as a candidate to bind both human and rat sequences using DNA-pulldown and mass spectrometry. LEDGF binding was confirmed by LEDGF-antibody EMSA and chromatin immunoprecipitation (ChIP). Ectopic expression of LEDGF/p75 increased luciferase activities of co-transfected reporters containing both human and rat orthologs. Over-expressed LEDGF/p75 increased endogenous FBXO10 mRNA levels in Jurkat cells, a human T-cell line, implying LEDGF may be involved in increasing FBXO10 transcript levels. Oxidative and thermal stress of Jurkat cells increased FBXO10 and LEDGF expression, further supporting a hypothesis that LEDGF binds to a regulatory region of FBXO10 and increases expression during conditions favoring carcinogenesis. We conclude that FBXO10, a candidate breast cancer susceptibility associated gene, is induced by cellular stress and LEDGF may play a role in expression of this gene.

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

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.