Gene-gene interactions in breast cancer susceptibility.
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ABSTRACT:
SUBMITTER: Turnbull C
PROVIDER: S-EPMC4125627 | biostudies-literature | 2012 Feb
REPOSITORIES: biostudies-literature
Publications
Gene-gene interactions in breast cancer susceptibility.
Turnbull Clare C Seal Sheila S Renwick Anthony A Warren-Perry Margaret M Hughes Deborah D Elliott Anna A Pernet David D Peock Susan S Adlard Julian W JW Barwell Julian J Berg Jonathan J Brady Angela F AF Brewer Carole C Brice Glen G Chapman Cyril C Cook Jackie J Davidson Rosemarie R Donaldson Alan A Douglas Fiona F Greenhalgh Lynn L Henderson Alex A Izatt Louise L Kumar Ajith A Lalloo Fiona F Miedzybrodzka Zosia Z Morrison Patrick J PJ Paterson Joan J Porteous Mary M Rogers Mark T MT Shanley Susan S Walker Lisa L Ahmed Munaza M Eccles Diana D Evans D Gareth DG Donnelly Peter P Easton Douglas F DF Stratton Michael R MR Rahman Nazneen N
Human molecular genetics 20111109 4
There have been few definitive examples of gene-gene interactions in humans. Through mutational analyses in 7325 individuals, we report four interactions (defined as departures from a multiplicative model) between mutations in the breast cancer susceptibility genes ATM and CHEK2 with BRCA1 and BRCA2 (case-only interaction between ATM and BRCA1/BRCA2 combined, P = 5.9 × 10(-4); ATM and BRCA1, P= 0.01; ATM and BRCA2, P= 0.02; CHEK2 and BRCA1/BRCA2 combined, P = 2.1 × 10(-4); CHEK2 and BRCA1, P= 0. ...[more]
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Project description:BackgroundBreast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination.MethodsIn an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle.ResultsNone of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways.ConclusionThe importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described. The strategy used here has the potential to identify complex biological links among breast cancer genes and processes. This will provide novel biological information, which will ultimately improve breast cancer risk management.
| S-EPMC1522021 | biostudies-literature
Project description:Cancer arises from complex, multi-layer interactions between diverse genetic and environmental factors. Genetic studies have identified multiple loci associated with tumor susceptibility. However, little is known about how germline polymorphisms interact with one another and with somatic mutations within a tumor to mediate acquisition of cancer traits. Here, we survey recent studies showing gene-gene interactions, also known as epistases, affecting genetic susceptibility in colorectal, gastric and esophageal cancers. We also catalog epistasis types and cancer hallmarks with respect to the interacting genes. A total of 22 gene variation pairs displayed all levels of statistical epistasis, including synergistic, redundant, suppressive and co-suppressive interactions. Five genes primarily involved in base excision repair formed a linear topology in the interaction network, MUTYH-OGG1-XRCC1-PARP1-MMP2, and three genes in mTOR cell-proliferation pathway formed another linear network, PRKAG2-RPS6KB1-PIK3CA. Discrete pairwise epistasis was also found in nucleotide excision repair, detoxification, proliferation, TP53, TGF-β and other pathways. We propose that three modes of biological interaction underlie the molecular mechanisms for statistical epistasis. The direct binding, linear pathway and convergence modes can exhibit any level of statistical epistasis in susceptibility to gastrointestinal cancers, and this is likely true for other complex diseases as well. This review highlights the link between cancer hallmarks and susceptibility genes.
| S-EPMC5341900 | biostudies-literature
Project description:BackgroundThere is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs) may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development.MethodsIn this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART), and the multifactor dimensionality reduction (MDR) method.ResultsOur analyses show evidence for several simple (two-way) and complex (multi-way) SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082)A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach) rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns.ConclusionThe strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.
| S-EPMC1976420 | biostudies-literature
Project description:Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(-07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15-1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72-1.11, P for interaction = 3.2 × 10(-05)). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.
| S-EPMC3995140 | biostudies-literature
Project description:BackgroundIt is unclear whether germline breast cancer susceptibility gene mutations affect breast cancer related outcomes. We wanted to evaluate mutation patterns in 20 breast cancer susceptibility genes and correlate the mutations with clinical characteristics to determine the effects of these germline mutations on breast cancer prognosis.MethodsThe study cohort included 480 ethnic Chinese individuals in Taiwan with at least one of the six clinical risk factors for hereditary breast cancer: family history of breast or ovarian cancer, young age of onset for breast cancer, bilateral breast cancer, triple negative breast cancer, both breast and ovarian cancer, and male breast cancer. PCR-enriched amplicon-sequencing on a next generation sequencing platform was used to determine the germline DNA sequences of all exons and exon-flanking regions of the 20 genes. Protein-truncating variants were identified as pathogenic.ResultsWe detected a 13.5% carrier rate of pathogenic germline mutations, with BRCA2 being the most prevalent and the non-BRCA genes accounting for 38.5% of the mutation carriers. BRCA mutation carriers were more likely to be diagnosed of breast cancer with lymph node involvement (66.7% vs 42.6%; P = 0.011), and had significantly worse breast cancer specific outcomes. The 5-year disease-free survival was 73.3% for BRCA mutation carriers and 91.1% for non-carriers (hazard ratio for recurrence or death 2.42, 95% CI 1.29-4.53; P = 0.013). After adjusting for clinical prognostic factors, BRCA mutation remained an independent poor prognostic factor for cancer recurrence or death (adjusted hazard ratio 3.04, 95% CI 1.40-6.58; P = 0.005). Non-BRCA gene mutation carriers did not exhibit any significant difference in cancer characteristics or outcomes compared to those without detected mutations. Among the risk factors for hereditary breast cancer, the odds of detecting a germline mutation increased significantly with having bilateral breast cancer (adjusted odds ratio 3.27, 95% CI 1.64-6.51; P = 0.0008) or having more than one risk factor (odds ratio 2.07, 95% CI 1.22-3.51; P = 0.007).ConclusionsWithout prior knowledge of the mutation status, BRCA mutation carriers had more advanced breast cancer on initial diagnosis and worse cancer-related outcomes. Optimal approach to breast cancer treatment for BRCA mutation carriers warrants further investigation.
| S-EPMC5863855 | biostudies-literature
Project description:Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors (age at menarche, parity, breastfeeding, body mass index, height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, physical activity) in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene-environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between LSP1-rs3817198 and parity (Pinteraction = 2.4 × 10(-6)) and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1 × 10(-4)). Overall, the per-allele odds ratio (95% confidence interval) for LSP1-rs3817198 was 1.08 (1.01-1.16) in nulliparous women and ranged from 1.03 (0.96-1.10) in parous women with one birth to 1.26 (1.16-1.37) in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85-0.98) in those with an alcohol intake of <20 g/day and 1.45 (1.14-1.85) in those who drank ? 20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3 × 10(-5)), with a per-allele OR of 1.14 (1.11-1.17) in parous women and 0.98 (0.92-1.05) in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.
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Project description: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.
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Project description:The roles of many environmental contaminants in increasing breast cancer risk remain controversial. Arsenic (As) is a major global environmental contaminant and carcinogen. We conducted a systematic review of the role of As and gene-arsenic interactions in susceptibility to breast cancer. Following a systematic literature search using well-defined inclusion/exclusion criteria, a total of 15 epidemiologic studies (two meta-analyses, three systematic reviews, three cohort studies, two case-control studies, and five cross-sectional studies) were reviewed. In addition, several animal, in vitro, in vivo, and in silico (i.e., computer modeling) studies provided mechanistic insights into the association between As and breast cancer. Our review suggests a possible overall main effect of As on breast cancer risk. The evidence for an effect of gene-As interactions on breast cancer risk is strong. Studies that measured levels of As metabolites among participants and/or evaluated interactions between As exposure and genetic or epigenetic factors generally reported positive associations with breast cancer risk. Our analysis of the Comparative Toxicogenomics and the Ingenuity Pathway Analysis Databases provided further evidence for As-gene interactions and their effects on breast cancer-related biologic pathways. Our findings provide potential leads for future epidemiologic studies of As-associated cancer risks and interventions to reduce population exposure.
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Project description: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.
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Project description:Breast cancer (BC) is a major problem for civilization, manifested by continuously increasing morbidity and mortality among women worldwide. Core circadian genes may play an important role in cancer development and progression. To evaluate the effects of single nucleotide polymorphism (SNP) in circadian genes in BC risk, 16 functional SNPs were genotyped in 321 BC patients and 364 healthy women using the TaqMan fluorescence-labelled probes or High-Resolution Melt Curve technique in the Real-Time PCR system. The selected SNPs were analyzed for the risk of BC, progression, and the influence on gene expression in BC tissue pairs to demonstrate the functionality of genetic variants. The study showed a relationship between an increased BC risk under the dominant genetic model of CRY2 rs10838524, PER2 rs934945, and recessive genetic model of PER1 rs2735611. A protective effect of BMAL1 rs2279287 was observed among carriers with at least one variant allele. Moreover, we found an increased risk of estrogen-/progesterone-positive tumors under the dominant genetic model of PER2 rs934945 and estrogen negative tumors under the variant genotype of CRY2 rs10838524, PER1 rs2735611. We demonstrated significantly altered gene expression of BMAL1, CRY2, PER1, PER2, PER3 according to particular genotypes in the BC tissue pairs. Our findings support the hypothesized role of circadian genes in breast carcinogenesis and indicate probable biomarkers for breast cancer susceptibility.
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