Gene-environment interactions in 7610 women with breast cancer: prospective evidence from the Million Women Study

A gap analysis of UK biobank publications reveals SNPs associated with intrinsic subtypes of breast cancer

Breast cancer is a multifaceted disease and a leading cause of cancer morbidity and mortality in females across the globe. In 2020 alone, 2.3 million women were diagnosed and 685,000 died of breast cancer worldwide. With the number of diagnoses projected to increase to 3 million per year by 2040 it is essential that new methods of detection and disease stratification are sought to decrease this global cancer burden. Although significant improvements have been made in breast cancer diagnosis and treatment, the prognosis of breast cancer remains poor in some patient groups (i.e. triple negative breast cancer), necessitating research into better patient stratification, diagnosis and drug discovery. The UK Biobank, a comprehensive biomedical and epidemiological database with a wide variety of multiomics data (genomics, proteomics, metabolomics) offers huge potential to uncover groundbreaking discoveries in breast cancer research leading to improved patient stratification. Combining genomic, proteomic, and metabolic profiles of breast cancer in combination with histological classification, can aid treatment decisions through accurate diagnosis and prognosis prediction of tumor behaviour. Here, we systematically reviewed PubMed publications reporting the analysis of UK Biobank data in breast cancer research. Our analysis of UK Biobank studies in the past five years identified 125 publications, of which 76 focussed on genomic data analysis. Interestingly, only two studies reported the analysis of metabolomics and proteomics data, with none performing multiomics analysis of breast cancer. A meta-analysis of the 76 publications identified 2870 genetic variants associated with breast cancer across 445 genes. Subtype analysis revealed differential genetic alteration in 13 of the 445 genes and the identification of 59 well-established breast cancer genes. in differential pathways. Pathway interaction analyses illuminated their involvement in general cancer biomolecular pathways (e.g. DNA damage repair, Gene expression). While our meta-analysis only measured genetic differences in breast cancer due to current usage of UK Biobank data, minimal multi-omics analyses have been performed and the potential for harnessing multi-omics strategies within the UK Biobank cohort holds promise for unravelling the biological signatures of distinct breast cancer subtypes further in the future.

Association of the bitter taste genes TAS2R38 and CA6 and breast cancer risk; a case-control study of Polish women in Poland and Polish immigrants in USA

It is known that the perception of bitterness is mediated by type 2 bitter taste receptors (TAS2Rs). However, recent reports have suggested that the carbonic anhydrase 6 (CA6) gene may also influence bitterness sensing. Genetic variants in these genes could influence dietary intake of brassica vegetables, whose increased consumption has been observed in the literature, though inconsistently, to decrease breast cancer (BC) risk. We hypothesized that the estimated odds ratios (ORs) for the association between BC and taster diplotype (PAV/PAV) and/or genotype A/A, will be in the direction of increased BC risk, potentially due to reduced consumption of brassica vegetables. Using a case-control study of BC in Polish women in Poland (210 cases and 262 controls) and Polish immigrant women to USA (78 cases and 170 controls) we evaluated the association of the taster diplotypes in TAS2R38 gene and genotypes in the CA6 gene and BC risk in these two populations individually and jointly. No significant increase in risk was observed for the TAS2R38 PAV/PAV diplotype (tasters) in each population individually or in the joint population. For the CA6 gene, in the joint population, we observed an increased BC risk for the combined G/A and G/G genotypes (non-tasters) vs A/A (tasters), OR = 1.41 (95% CI 1.04-1.90, p = 0.026) which after adjustment for False Discovery Rate (FDR), was not significant at p≤0.05 level. However, for the joint population and for the combined genotype of the two genes AVI/AVI+G* (non-tasters) vs. PAV/*+A/A (tasters), we observed a significant increase in BC risk, OR = 1.77 (95%CI 1.47-2.74, p = 0.01), for the non-tasters, which remained significant after FDR adjustment. In conclusion for the joint population and the joint effect for the two bitter sensing genes, we observed an increase in BC risk for the bitterness non-tasters, association which is in the opposite direction to our original hypothesis.

Influence of alcohol consumption and alcohol metabolism variants on breast cancer risk among Black women: results from the AMBER consortium

BACKGROUND

Moderate to heavy alcohol consumption is associated with an increased risk of breast cancer. The etiologic role of genetic variation in genes involved in ethanol metabolism has not been established, with little information available among women of African ancestry.

METHODS

Our analysis from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium included 2889 U.S. Black women who were current drinkers at the time of breast cancer diagnosis (N cases = 715) and had available genetic data for four ethanol metabolism genomic regions (ADH, ALDH, CYP2E1, and ALDH2). We used generalized estimating equations to calculate genetic effects, gene* alcohol consumption (≥ 7drinks/week vs. < 7/week) interactions, and joint main plus interaction effects of up to 23,247 variants in ethanol metabolism genomic regions on odds of breast cancer.

RESULTS

Among current drinkers, 21% of cases and 14% of controls reported consuming ≥ 7 drinks per week. We identified statistically significant genetic effects for rs79865122-C in CYP2E1 with odds of ER- breast cancer and odds of triple negative breast cancer, as well as a significant joint effect with odds of ER- breast cancer (≥ 7drinks per week OR = 3.92, < 7 drinks per week OR = 0.24, p_joint = 3.74 × 10^-6). In addition, there was a statistically significant interaction of rs3858704-A in ALDH2 with consumption of ≥ 7 drinks/week on odds of triple negative breast cancer (≥ 7drinks per week OR = 4.41, < 7 drinks per week OR = 0.57, p_int = 8.97 × 10^-5).

CONCLUSIONS

There is a paucity of information on the impact of genetic variation in alcohol metabolism genes on odds of breast cancer among Black women. Our analysis of variants in four genomic regions harboring ethanol metabolism genes in a large consortium of U.S. Black women identified significant associations between rs79865122-C in CYP2E1 and odds of ER- and triple negative breast cancer. Replication of these findings is warranted.

Incorporating Alternative Polygenic Risk Scores into the BOADICEA Breast Cancer Risk Prediction Model

BACKGROUND

The multifactorial risk prediction model BOADICEA enables identification of women at higher or lower risk of developing breast cancer. BOADICEA models genetic susceptibility in terms of the effects of rare variants in breast cancer susceptibility genes and a polygenic component, decomposed into an unmeasured and a measured component - the polygenic risk score (PRS). The current version was developed using a 313 SNP PRS. Here, we evaluated approaches to incorporating this PRS and alternative PRS in BOADICEA.

METHODS

The mean, SD, and proportion of the overall polygenic component explained by the PRS (α2) need to be estimated. $\alpha $ was estimated using logistic regression, where the age-specific log-OR is constrained to be a function of the age-dependent polygenic relative risk in BOADICEA; and using a retrospective likelihood (RL) approach that models, in addition, the unmeasured polygenic component.

RESULTS

Parameters were computed for 11 PRS, including 6 variations of the 313 SNP PRS used in clinical trials and implementation studies. The logistic regression approach underestimates $\alpha $, as compared with the RL estimates. The RL $\alpha $ estimates were very close to those obtained by assuming proportionality to the OR per 1 SD, with the constant of proportionality estimated using the 313 SNP PRS. Small variations in the SNPs included in the PRS can lead to large differences in the mean.

CONCLUSIONS

BOADICEA can be readily adapted to different PRS in a manner that maintains consistency of the model.

IMPACT

: The methods described facilitate comprehensive breast cancer risk assessment.

Long Non-Coding RNA LINC00052 Targets miR-548p/Notch2/Pyk2 to Modulate Tumor Budding and Metastasis of Human Breast Cancer

Abnormal expression of long non-coding RNAs (lncRNAs) is involved in many pathological processes of cancers. However, the role of lncRNA LINC00052 in breast cancer progression is still unclear. Here, LINC00052 expression was detected by in situ hybridization and quantitative real-time PCR assays. Cell Counting Kit-8, wound healing, and transwell assays were used to investigate changes in the proliferation, migration, and invasion of breast cancer cells. MiR-548p was found associated with LINC00052 or Notch2 by RNA pull-down, dual-luciferase reporter, and qRT-PCR assays. The effect of LINC00052 on lung metastasis was explored through in vivo experiments. High LINC00052 expression was observed in breast cancer tissues and cells. LINC00052 silencing inhibited the proliferation, migration, and invasion of MCF7 cells, and LINC00052 overexpression produced the opposite results. MiR-548p, a target gene of LINC00052, partially rescued the effects of LINC00052 on proliferation, migration, and invasion of MCF7. Notch2 was the target of miR-548p and LINC00052 could promote Notch2 expression. Moreover, the phosphorylation of proline-rich tyrosine kinase 2 (Pyk2), a downstream factor of Notch2, was increased by LINC00052, and a Pyk2 mutant could inhibit the cell migration and invasion induced by LINC00052 overexpression in MDA-MB-468 cells, which was similar to the function of the miR-548p mimic. We further demonstrated that LINC00052 exacerbated the metastases of breast cancer cells in vivo. Our research demonstrated that LINC00052 is highly expressed in breast cancer and promotes breast cancer proliferation, migration, and invasion via the miR-548p/Notch2/Pyk2 axis. LINC00052 could serve as a potential therapeutic target for breast cancer.

Interindividual variation contributes to differential PCB 126 induced gene expression in primary breast epithelial cells and tissues

PCB 126 is a pervasive, dioxin-like chemical pollutant which can activate the aryl hydrocarbon receptor (AhR). Despite being banned from the market, PCB 126 can be detected in breast milk to this day. The extent to which interindividual variation impacts the adverse responses to this chemical in the breast tissue remains unclear. This study aimed to investigate the impact of 3 nM PCB 126 on gene expression in a panel of genetically diverse benign human breast epithelial cell (HBEC) cultures and patient derived breast tissues. Six patient derived HBEC cultures were treated with 3 nM PCB 126. RNAseq was used to interrogate the impact of exposure on differential gene expression. Gene expression changes from the top critical pathways were confirmed via qRT-PCR in a larger panel of benign patient derived HBEC cultures, as well as in patient-derived breast tissue explant cultures. RNAseq analysis of HBEC cultures revealed a signature of 144 genes significantly altered by 3 nM PCB 126 treatment. Confirmation of 8 targets using a panel of 12 HBEC cultures and commercially available breast cell lines demonstrated that while the induction of canonical downstream target gene, CYP1A1, was consistent across our primary HBECs, other genes including AREG, S100A8, IL1A, IL1B, MMP7, and CCL28 exhibited significant variability across individuals. The dependence on the activity of the aryl hydrocarbon receptor was confirmed using inhibitors. PCB 126 can induce significant and consistent changes in gene expression associated with xenobiotic metabolism in benign breast epithelial cells. Although the induction of most genes was reliant on the AhR, significant variability was noted between genes and individuals. These data suggest that there is a bifurcation of the pathway following AhR activation that contributes to the variation in interindividual responses.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

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.

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.

Genetic Factors, Adherence to Healthy Lifestyle Behavior, and Risk of Invasive Breast Cancer Among Women in the UK Biobank

BACKGROUND

Breast cancer is considered to result from a combination of genetic and lifestyle-related factors, but the degree to which an overall healthy lifestyle may attenuate the impact of multiple genetic variants on invasive breast cancer risk remains equivocal.

METHODS

Using Cox proportional hazards regression models, we examined the association of a modified healthy lifestyle index (HLI) with risk of invasive breast cancer by genetic risk group among 146 326 women from the UK Biobank. We generated an HLI score based on a combination of diet, physical activity, smoking, alcohol consumption and anthropometry, and a polygenic risk score (PRS) using 304 breast cancer-associated genetic loci.

RESULTS

Among premenopausal and postmenopausal women, a favorable lifestyle (highest tertile) was associated with 22% and 31% reductions in invasive breast cancer risk, respectively (hazard ratio [HR]high vs low = 0.78, 95% confidence interval [CI] = 0.64 to 0.94; HRhigh vs low = 0.69, 95% CI = 0.63 to 0.77, respectively), whereas a high PRS (highest tertile) was associated with more than a doubling in the risk in both groups. For premenopausal women, the greatest risk reduction in association with the HLI was seen among those with a high PRS (HRhigh vs low = 0.73, 95% CI = 0.75 to 0.95). In postmenopausal women, those with a favorable lifestyle had 30%, 29%, and 32% reductions in risk of invasive breast cancer in the low, intermediate, and high PRS groups, respectively (HRhigh vs low = 0.70, 95% CI = 0.56 to 0.88; HRhigh vs low = 0.71, 95% CI = 0.59 to 0.84; and HRhigh vs low = 0.68, 95% CI = 0.59 to 0.78, respectively). There was an additive but not multiplicative interaction between the HLI score and PRS for postmenopausal and, to a lesser extent, premenopausal women.

CONCLUSION

Our findings support the view that an overall healthy lifestyle may attenuate the impact of genetic factors on invasive breast cancer risk among women of European ancestry.

Predicting breast cancer risk using interacting genetic and demographic factors and machine learning

Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially factors related to both familial history (Group 1) and oestrogen metabolism (Group 2), for predicting BC risk. This approach identifies the best combinations of interacting genetic and demographic risk factors that yield the highest BC risk prediction accuracy. In tests on the Kuopio Breast Cancer Project (KBCP) dataset, our approach achieves a mean average precision (mAP) of 77.78 in predicting BC risk by using interacting genetic and Group 1 features, which is better than the mAPs of 74.19 and 73.65 achieved using only Group 1 features and interacting SNPs, respectively. Similarly, using interacting genetic and Group 2 features yields a mAP of 78.00, which outperforms the system based on only Group 2 features, which has a mAP of 72.57. Furthermore, the gene interaction maps built from genes associated with SNPs that interact with demographic risk factors indicate important BC-related biological entities, such as angiogenesis, apoptosis and oestrogen-related networks. The results also show that demographic risk factors are individually more important than genetic variants in predicting BC risk.

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.

The disparities in gastrointestinal cancer incidence among Chinese populations in Shanghai compared to Chinese immigrants and indigenous non-Hispanic white populations in Los Angeles, USA

Gastrointestinal cancer patterns are distinct among populations. Our study aims to compare the incidence and risk of gastrointestinal cancers between Chinese American and non-Hispanic whites in Los Angeles, CA, USA, to those of people indigenous to Shanghai to elucidate the changing patterns of gastrointestinal cancers. Cancer incidence data from 1988 to 2012 were extracted from the Cancer Incidence in Five Continents plus database. The age standardized incidence and estimated annual percentage change were calculated to estimate the temporal trends of gastrointestinal cancers. Traditional Poisson regression models and three-factor constrained Poisson regression models were applied to compare the gastrointestinal cancer risk across populations. The incidences of oesophageal, stomach, liver and gall bladder cancers were higher among indigenous Chinese residents of Shanghai than among the other two populations in Los Angeles. While the incidences of colorectal and pancreatic cancer were higher among non-Hispanic whites, Chinese American immigrants were considered to be at an intermediate level for most gastrointestinal cancers. The gender-specific gastrointestinal cancer disparities across populations, especially between Shanghai Chinese and non-Hispanic US whites, were significant regardless of age, period or cohort scale. However, the regional differences in gastrointestinal cancer rates decreased over time. Most gastrointestinal cancer patterns in Chinese American immigrants were more aligned to those of their new country of residence than to those of their original country. The disparities in gastrointestinal cancers across populations indicate that environmental factors might play a key role in cancer genesis. Shift in environmental exposures may result in significant changes in gastrointestinal cancer incidence.

A novel metadherinΔ7 splice variant enhances triple negative breast cancer aggressiveness by modulating mitochondrial function via NFĸB-SIRT3 axis

Metadherin (MTDH) expression inversely correlates with prognosis of several cancers including mammary carcinomas. In this work, we identified a novel splice variant of MTDH with exon7 skipping (MTDHΔ7) and its levels were found significantly high in triple negative breast cancer (TNBC) cells and in patients diagnosed with TNBC. Selective overexpression of MTDHΔ7 in MDA-MB-231 and BT-549 cells enhanced proliferation, invasion, and epithelial-to-mesenchymal (EMT) transition markers in comparison to its wildtype counterpart. In contrast, knockdown of MTDHΔ7 induced antiproliferative/antiinvasive effects. Mechanistically, MTDH-NFĸB-p65 complex activated SIRT3 transcription by binding to its promoter that in turn enhanced MnSOD levels and promoted EMT in TNBC cells. Intriguingly, mitochondrial OCR through Complex-I and -IV, and glycolytic rate (ECAR) were significantly high in MDA-MB-231 cells stably expressing MTDHΔ7. While depletion of SIRT3 inhibited MTDH-Wt/Δ7-induced OCR and ECAR, knockdown of MnSOD inhibited only ECAR. In addition, MTDH-Wt/Δ7-mediated pro-proliferative/-invasive effects were greatly obviated with either siSIRT3 or siMnSOD in these cells. The functional relevance of MTDHΔ7 was further proved under in vivo conditions in an orthotopic mouse model of breast cancer. Mice bearing labeled MDA-MB-231 cells stably expressing MTDHΔ7 showed significantly more tumor growth and metastatic ability to various organs in comparison to MTDH-Wt bearing mice. Taken together, MTDHΔ7 promotes TNBC aggressiveness through enhanced mitochondrial biogenesis/function, which perhaps serves as a biomarker.

Marked increase in breast cancer incidence in young women: A 10-year study from Northern Iran, 2004-2013

INTRODUCTION

Breast cancer is the most frequent cancer among women worldwide. Breast cancer incidence in young women is a health issue of concern, especially in middle-income countries such as Iran. The aim of this study is to report the breast cancer incidence variations in Golestan province, Iran, over a 10-year period (2004-2013).

METHODS

We analyzed data from the Golestan Population-based Cancer Registry (GPCR), which is a high-quality cancer registry collecting data on primary cancers based on standard protocols throughout the Golestan province. Age-standardized incidence rates (ASRs) and age-specific incidence rates per 100,000 person-years were calculated. Time trends in ASRs and age-specific rates were evaluated using Joinpoint regressions. The average annual percentage change (AAPC) with correspondence 95% confidence intervals (95%CIs) were calculated.

RESULTS

A total of 2106 new breast cancer cases were diagnosed during the study period. Most cases occurred in women living in urban areas: 1449 cases (68%) versus 657 cases (31%) in rural areas. Statistically significant increasing trends were observed over the 10-year study period amongst women of all ages (AAPC = 4.4; 95%CI: 1.2-7.8) as well as amongst women in the age groups 20-29 years (AAPC = 10.0; 95%CI: 1.7-19.0) and 30-39 years (AAPC = 5.1; 95%CI: 1.4-9.0).

CONCLUSION

The incidence of breast cancer increased between 2004 and 2013 in Golestan province amongst all age groups, and in particular amongst women aged 20-39 years. Breast cancer should be considered a high priority for health policy making in our community.

AA genotype of cyclin D1 G870A polymorphism increases breast cancer risk: Findings of a case-control study and meta-analysis

BACKGROUND

Cyclin D1 (CCND1) polymorphisms, a regulator of the cell cycle progress from G1 to the S phase, may lead to uncontrolled cell proliferation and lack of apoptosis. G870A, a common single-nucleotide polymorphism in CCND1 influences breast cancer risk. However, the association between G870A polymorphism and breast cancer risk is ambiguous so far.

MATERIALS AND METHODS

In this case-control study, we analyzed the role of G870A polymorphism with breast cancer risk in Indian women. A meta-analysis of 18 studies was also performed to elucidate this association by increasing statistical power.

RESULTS

In our case-control study, significant risk association of the CCND1 G870A AA genotype with breast cancer in total cohort (odds ratio [OR], 2.98; 95% confidence interval [CI], 1.64-5.42; P value, 4.96e-04) and premenopausal women (OR, 3.31; 95% CI, 1.54-7.08; P value, .003) was found. The results of the meta-analysis showed that AA genotype of the CCND1 G870A polymorphism significantly increases breast cancer risk in total pooled data (AA vs GG+GA: OR = 1.20; 95% CI = 1.03 to 1.39; P value, 0.016*) and Caucasian (AA vs GG+GA: OR = 1.22; 95% CI = 0.99 to 1.51; P value, .056*) but not in Asian population. Further, a significant protective association with breast cancer was also found in the GA vs AA comparison model in pooled data (OR = 0.73; 95% CI = 0.58 to 0.92; P value, .007*) as well as in Caucasian subgroup (OR = 0.62; 95% CI = 0.49 to 0.94; P value, .022*).

CONCLUSION

CCND1 G870A AA genotype was found associated with breast cancer risk. Future association studies considering the environmental impact on gene expression are required to validate/explore this association.

LINC00673 rs11655237 Polymorphism Is Associated With Increased Risk of Cervical Cancer in a Chinese Population

Cervical cancer is the fourth most commonly diagnosed cancer and the fourth leading cause of cancer deaths in women worldwide. Few single-nucleotide polymorphisms associated with risk of cervical cancer have been identified, yet genetic predisposition contributes significantly to this malignancy. Long noncoding RNA LINC00673 has been widely explored for its role in the development and prognosis of many tumors, and 2 genome-wide association studies identified that LINC00673 rs11655237 was associated with susceptibility to pancreatic cancer. In the current study, using a case–control study design, we found rs11655237 significantly increased susceptibility of cervical cancer in a Chinese population (odds ratio = 1.27; 95% confidence interval = 1.08-1.50; P = .005). Expression of LINC00673 was significantly higher in adjacent normal tissues than in paired cancer tissues (P < .01) and significantly lower in the cancer or paired adjacent normal tissues of patients with cervical cancer having rs11655237 allele A than in those having rs11655237 allele G (P < .001). Our results indicate that LINC00673 rs11655237 is associated with increased risk of cervical cancer, possibly by downregulating LINC00673 expression in cervical tissues.

Involvement of a mouse mammary tumor virus (MMTV) homologue in human breast cancer: Evidence for, against and possible causes of controversies

Breast cancer (BC) is a complex and heterogeneous disease whose evolution depends on the tumor-host interaction. This type of cancer occurs when the mammary cells begin to grow wildly and become able to invade nearby tissues and/or promote metastases. Mouse mammary tumor virus (MMTV) is the accepted etiological agent of mammary tumors in mice. The identification of MMTV-like sequences and antigens in human mammary carcinoma has supported the theory that a virus homologous to MMTV (namely, HMTV) may be involved in human BC, but the role of retroviral elements in this disease remains elusive, as results from different research groups were contradictory. In the present review we present works for and against the involvement of HMTV in BC and discuss possible causes of divergences among studies. In the final section we fit current data regarding this issue to stablished causality criteria. We conclude that there is convincing data supporting the association of HMTV with BC, however there is still a need for epidemiological and basic research studies focusing on carcinogenic mechanisms for this virus in humans to fully understand its role in BC. This knowledge may open the way for the development of new preventive and therapeutic approaches in human BC.

The LSP1 rs3817198 T > C polymorphism contributes to increased breast cancer risk: a meta-analysis of twelve studies

The association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk has been widely investigated, but remains controversial. We therefore undertook a comprehensive meta-analysis to provide a high-quality evaluation of this association. A literature search was performed among Pubmed, EMBASE and Chinese National Knowledge Infrastructure (CNKI) databases prior to July 31, 2016, and the strength of the association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk was assessed based on odds ratio (OR) and 95% confidence interval (95% CI). In total, 12 studies with 50,525 cases and 54,302 controls were included. Pooled risk estimates indicated a significant association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk. Analysis of cases stratified based on ethnicity suggested that the association was significant in both Caucasian and Asian populations. Stratification based on source of controls revealed an association only in population-based studies. These findings indicate the LSP1 rs3817198 T > C polymorphism is associated with increased risk of breast cancer, especially in Caucasian and Asian populations. Large, well-designed studies with different ethnicities are still needed to verify our findings.

A systematic analysis of the association studies between CASP8 D302H polymorphisms and breast cancer risk

Caspase 8 (CASP8) is a regulator of apoptosis, whose genetic variation has been reported to be associated with the risk of various cancers. Especially, the single-nucleotide polymorphism (SNP) rs1045485, which generates the substitution D302H in CASP8, is likely to be associated with breast cancer. Several previous studies have reported the association of CASP8 D302H polymorphism with breast cancer; however, the results are inconsistent. To validate the association between CASP8 D302H polymorphism and breast cancer risk, we performed an updated meta-analysis of 18 studies including 27,807 cases and 32,332 controls. We tested the overall association between this SNP and breast cancer susceptibility and stratified subgroups based on countries where cases are from. We confirmed a significant correlation between CASP8 D302H polymorphism and the reduced breast cancer susceptibility in population from UK, Germany and Poland, but no significant association was observed in other countries, such as Finland or USA. Our findings indicate the relationship of SNP CASP8 D302H and breast cancer would not be universal but only be sensitive in some particular European countries. The genetic difference for diverse countries may be useful in individual and precision medicine or health.

Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium

Background

Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.

Methods

Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.

Results

The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).

Conclusions

The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future

Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Large intergenic non-coding RNA-ROR reverses gemcitabine-induced autophagy and apoptosis in breast cancer cells

The purpose of this study was to elucidate the potential role of long intergenic non-protein coding RNA, regulator of reprogramming (linc-ROR) in gemcitabine (Gem)-induced autophagy and apoptosis in breast cancer cells. MDA-MB-231 cells were treated with short hairpin RNA (shRNA) to knockdown Linc-ROR expression in the presence of Gem. Gem treatment alone decreased cell survival and increased both apoptosis and autophagy. Gem treatment also increased the expression of LC3-II, Beclin 1, NOTCH1 and Bcl-2, but decreased expression of p62 and p53. Untreated MDA-MB-231 cell lines strongly expressed linc-ROR, but linc-ROR knockdown decreased cell viability and expression of p62 and p53 while increasing apoptosis. Linc-ROR knockdown also increased LC3-II/β-actin, Beclin 1, NOTCH1, and Bcl-2 expression, as well as the number of autophagic vesicles in MDA-MB-231 cells. Linc-ROR negatively regulated miR-34a expression by inhibiting histone H3 acetylation in the miR-34a promoter. We conclude that linc-ROR suppresses Gem-induced autophagy and apoptosis in breast cancer cells by silencing miR-34a expression.

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.

Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) is a membrane-spanning tyrosine kinase that mediates signaling for FGFs. Recent studies detected various point mutations of FGFR2 in multiple types of cancers, including breast cancer, lung cancer, gastric cancer, uterine cancer and ovarian cancer, yet the casual relationship between these mutations and tumorigenesis is unclear. Here we will discuss possible interactions between FGFR2 signaling and several major pathways through which the aberrantly activated FGFR2 signaling may result in breast cancer development. We will also discuss some recent developments in the discovery and application of therapies and strategies for breast cancers by inhibiting FGFR2 activities.

Gene-Environment Interactions in Preventive Medicine: Current Status and Expectations for the Future

The progression of many common disorders involves a complex interplay of multiple factors, including numerous different genes and environmental factors. Gene-environmental cohort studies focus on the identification of risk factors that cannot be discovered by conventional epidemiological methodologies. Such epidemiological methodologies preclude precise predictions, because the exact risk factors can be revealed only after detailed analyses of the interactions among multiple factors, that is, between genes and environmental factors. To date, these cohort studies have reported some promising results. However, the findings do not yet have sufficient clinical significance for the development of precise, personalized preventive medicine. Especially, some promising preliminary studies have been conducted in terms of the prevention of obesity. Large-scale validation studies of those preliminary studies, using a prospective cohort design and long follow-ups, will produce useful and practical evidence for the development of preventive medicine in the future.

Effects of long noncoding RNA-ROR on tamoxifen resistance of breast cancer cells by regulating microRNA-205

PURPOSE

To explore how long noncoding RNA-ROR (lncRNA-ROR) affects the tamoxifen resistance of breast cancer cells.

METHODS

Breast epithelial (MCF10A), breast cancer (MCF7), and natural tamoxifen-resistant breast cancer (MDA-MB-231) cell lines were selected, and the relative lncRNA-ROR expressions were detected using quantitative real-time polymerase chain reaction (qRT-PCR). In vitro induction of TR5 cell line was performed. There were six groups: MCF7, MCF7/TR5, MDA-MB-231, MCF7-ROR, MCF7/TR5 ROR-siRNA, and the MDA-MB-231 ROR-siRNA groups. CCK-8 assay was conducted to assess the changes in drug resistance of each group. The expression of the epithelial mesenchymal transition (EMT) marker was detected using Western blotting. Transwell was selected to test the invasive ability of the cells. Expressions of microRNA-205 (miR-205) and ZEB1/2 were detected using qRT-PCR .

RESULTS

Compared with the MCF7 cells, the proliferation rates of the MCF7/TR5 and MDA-MB-231 cells were significantly increased. Compared with the MCF7 cells, the MCF7-ROR cells had remarkably higher proliferation rates, down-regulated E-cadherin and miR-205 expressions, as well as increased vimentin, invasive ability, and mRNA expression of ZEB1 and ZEB2. Compared with the MCF7/TR5 and MDA-MB-231 cells, up-regulated E-cadherin and miR-205 expression, down-regulated expression of vimentin, ZEB1, and ZEB2 mRNA, and decreased invasive ability were observed in the MCF7/TR5 ROR-siRNA and MDA-MB-231 ROR-siRNA cells.

CONCLUSION

In MDA-MB-231 cells, down-regulated lncRNA-ROR could inhibit the EMT of breast cancer cells and enhance the sensibility of breast cancer cells to tamoxifen by increasing miR-205 expression and suppressing the expressions of ZEB1 and ZEB2.

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.

Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes

The genome is often the conduit through which environmental exposures convey their effects on health and disease. Whilst not all diseases act by directly perturbing the genome, the phenotypic responses are often genetically determined. Hence, whilst diseases are often defined has having differing degrees of genetic determination, genetic and environmental factors are, with few exceptions, inseparable features of most diseases, not least type 2 diabetes. It follows that to optimize diabetes, prevention and treatment will require that the etiological roles of genetic and environmental risk factors be jointly considered. As we discuss here, studies focused on quantifying gene-environment and gene-treatment interactions are gathering momentum and may eventually yield data that helps guide health-related choices and medical interventions for type 2 diabetes and other complex diseases.

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.

Breastfeeding and Immunohistochemical Expression of ki-67, p53 and BCL2 in Infiltrating Lobular Breast Carcinoma

Background/Aim

Invasive lobular breast carcinoma is the second most common type of breast cancer after invasive ductal carcinoma. According to the American Cancer Society, more than 180,000 women in the United States find out they have invasive breast cancer each year. Personal history of breast cancer and certain changes in the breast are correlated with an increased breast cancer risk. The aim of this work was to analyze breastfeeding in patients with infiltrating lobular breast carcinoma, in relation with: 1) clinicopathological parameters, 2) hormonal receptors and 3) tissue-based tumor markers

Materials and Methods

The study included 80 women with ILC, 46 of which had breastfeed their children. Analyzed parameters were: age, tumor size, axillary lymph node (N), distant metastasis (M), histological grade (HG), estrogen receptor (ER), progesterone receptor (PR), androgen receptor (AR), Ki-67, p53 and BCL2

Results

ILC of non-lactating women showed a larger (p = 0.009), lymph node involvement (p = 0.051) and distant metastasis (p = 0.060). They were also more proliferative tumors measured by Ki-67 (p = 0.053). Breastfeeding history did not influence the subsequent behavior of the tumor regardless of histological subtype

Conclusion

Lactation seems to influence the biological characteristics of ILC defining a subgroup with more tumor size, axillary lymph node involvement, distant metastasis and higher proliferation measured by ki-67 expression.

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.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

METHODS

We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

RESULTS

There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

CONCLUSIONS

The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Gene analysis techniques and susceptibility gene discovery in non-BRCA1/BRCA2 familial breast cancer

Breast cancer is the leading cause of cancer deaths in females worldwide occurring in both hereditary and sporadic forms. Women with inherited pathogenic mutations in the BRCA1 or BRCA2 genes have up to an 85% risk of developing breast cancer in their lifetimes. These patients are candidates for risk-reduction measures such as intensive radiological screening, prophylactic surgery or chemoprevention. However, only about 20% of familial breast cancer cases are attributed to mutations in BRCA1 and BRCA2, while a further 5-10% are attributed to mutations in other rare susceptibility genes such as TP53, STK11, PTEN, ATM and CHEK2. A multitude of genome wide association studies (GWAS) have been conducted confirming low-risk common variants associated with breast cancer in excess of 90 loci, which may contribute to a further 23% of the heritability. We currently find ourselves in "the next generation", with technologies offering deep sequencing at a fraction of the cost. Starting off primarily in a research setting, multi-gene panel testing is now utilized in the clinic to sequence multiple predisposing genes simultaneously (otherwise known as multi-gene panel testing). In this review, we focus on the hereditary breast cancer discoveries, techniques and the challenges we face in this complex disease, especially in the light of the vast amount of data we now have at hand. It has been 20 years since the first breast cancer susceptibility gene has been discovered and there has been substantial progress in unraveling the genetic component of the disease. However, hereditary breast cancer remains a challenging topic subject to common debate.

Molecular epidemiology, and possible real-world applications in breast cancer

Gene-environment interaction, a key idea in molecular epidemiology, has enabled the development of personalized medicine. This concept includes personalized prevention. While genome-wide association studies have identified a number of genetic susceptibility loci in breast cancer risk, however, the application of this knowledge to practical prevention is still underway. Here, we briefly review the history of molecular epidemiology and its progress in breast cancer epidemiology. We then introduce our experience with the trial combination of GWAS-identified loci and well-established lifestyle and reproductive risk factors in the risk prediction of breast cancer. Finally, we report our exploration of the cumulative risk of breast cancer based on this risk prediction model as a potential tool for individual risk communication, including genetic risk factors and gene-environment interaction with obesity.

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.

TGF-β Regulates Survivin to Affect Cell Cycle and the Expression of EGFR and MMP9 in Glioblastoma

Transforming growth factor beta (TGF-β) is suggestive of a molecular target for cancer therapy due to its involvement in cell cycle, differentiation, and morphogenesis. Meanwhile, survivin is identified as an apoptosis inhibitor and involved in tumorgenesis. Here, we aimed to investigate the potential associations between TGF-β and survivin in glioblastoma U87 cell line. Survivin small interfering RNA (siRNA), Western blotting, and cell cycle analysis were introduced to detect relevant proteins in TGF-β pathways. In this study, we observed a concentration- and time-dependent increase of survivin expression after treatment with TGF-β1. However, the kinase inhibitors U0126 and LY294002 inhibited the upregulation of survivin in comparison with DMSO. In addition, survivin siRNA effectively abrogated survivin expression in U87 cells, therefore affected cells' entry into the S phase of cell cycle, and then repressed the expression of epidermal growth factor receptor (EGFR) and matrix metalloproteinase 9 (MMP9) in comparison with non-transfection. In conclusion, the present study shows that TGF-β upregulates survivin expression via ERK and PI3K/AKT pathway, leading to glioblastoma cell cycle progression. Thus, the blockade of survivin will allow for the treatment of glioblastoma, partially attributing to the inhibition of EGFR and MMP9 expression.

Alcohol and breast cancer: reconciling epidemiological and molecular data

Breast cancer is the most diagnosed cancer in women worldwide. Epidemiological studies have suggested a possible causative role of alcohol consumption as a risk factor for breast cancer. However, such conclusions should be interpreted with considerable caution for several reasons. While epidemiological studies can help identify the roots of health problems and disease incidence in a community, they are by necessity associative and cannot determine cause and effect relationships. In addition, all these studies rely on self-reporting to determine the amount and type of alcoholic beverage consumed, which introduces recall bias. This is documented in a recent study which stated that the apparent increased risk of cancer among light-moderate drinkers may be "substantially due to underreporting of intake." Another meta-analysis about alcohol and breast cancer declared "the modest size of the association and variation in results across studies leave the causal role of alcohol in question." Furthermore, breast cancer develops over decades; thus, correlations between alcohol consumption and breast cancer cannot be determined in epidemiological studies with windows of alcohol exposure that captures current or recent alcohol intake, after clinical diagnosis. Numerous risk factors are involved in breast carcinogenesis; some are genetic and beyond the control of a woman; others are influenced by lifestyle factors. Breast cancer is a heterogeneous and polygenic disease which is further influenced by epigenetic mechanisms that affect the transciptomes, proteomes and metabolomes, and ultimately breast cancer evolution. Environmental factors add another layer of complexity by their interactions with the susceptibility genes for breast cancer and metabolic diseases. The current state-of-knowledge about alcohol and breast cancer association is ambiguous and confusing to both a woman and her physician. Confronting the huge global breast cancer issue should be addressed by sound science. It is advised that women with or without a high risk for breast cancer should avoid overconsumption of alcohol and should consult with their physician about risk factors involved in breast cancer. Since studies associating moderate alcohol consumption and breast cancer are contradictory, a woman and her physician should weigh the risks and benefits of moderate alcohol consumption.

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.