Elizabeth M. Azzato

Genome-Wide Meta-Analysis Identifies Regions on 7p21 (AHR) and 15q24 (CYP1A2) As Determinants of Habitual Caffeine Consumption

We report the first genome-wide association study of habitual caffeine intake. We included 47,341 individuals of European descent based on five population-based studies within the United States. In a meta-analysis adjusted for age, sex, smoking, and eigenvectors of population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4×10−19), near AHR, and 15q24 (P = 5.2×10−14), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer

IntroductionThe aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK.MethodsUsing the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation.ResultsDifferences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75).ConclusionsWe have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

A population-based validation of the prognostic model PREDICT for early breast cancer

INTRODUCTION Predict (www.predict.nhs.uk) is a prognostication and treatment benefit tool developed using UK cancer registry data. The aim of this study was to compare the 10-year survival estimates from Predict with observed 10-year outcome from a British Columbia dataset and to compare the estimates with those generated by Adjuvant! (www.adjuvantonline.com). METHOD The analysis was based on data from 3140 patients with early invasive breast cancer diagnosed in British Columbia, Canada, from 1989-1993. Demographic, pathologic, staging and treatment data were used to predict 10-year overall survival (OS) and breast cancer specific survival (BCSS) using Adjuvant! and Predict models. Predicted outcomes from both models were then compared with observed outcomes. RESULTS Calibration of both models was excellent. The difference in total number of deaths estimated by Predict was 4.1 percent of observed compared to 0.7 percent for Adjuvant!. The total number of breast cancer specific deaths estimated by Predict was 3.4 percent of observed compared to 6.7 percent for Adjuvant! Both models also discriminate well with similar AUC for Predict and Adjuvant! respectively for both OS (0.709 vs 0.712) and BCSS (0.723 vs 0.727). Neither model performed well in women aged 20-35. CONCLUSION In summary Predict provided accurate overall and breast cancer specific survival estimates in the British Columbia dataset that are comparable with outcome estimates from Adjuvant! Both models appear well calibrated with similar model discrimination. This study provides further validation of Predict as an effective predictive tool following surgery for invasive breast cancer.

Prevalent cases in observational studies of cancer survival: do they bias hazard ratio estimates?

Observational epidemiological studies often include prevalent cases recruited at various times past diagnosis. This left truncation can be dealt with in non-parametric (Kaplan–Meier) and semi-parametric (Cox) time-to-event analyses, theoretically generating an unbiased hazard ratio (HR) when the proportional hazards (PH) assumption holds. However, concern remains that inclusion of prevalent cases in survival analysis results inevitably in HR bias. We used data on three well-established breast cancer prognosticators – clinical stage, histopathological grade and oestrogen receptor (ER) status – from the SEARCH study, a population-based study including 4470 invasive breast cancer cases (incident and prevalent), to evaluate empirically the effectiveness of allowing for left truncation in limiting HR bias. We found that HRs of prognostic factors changed over time and used extended Cox models incorporating time-dependent covariates. When comparing Cox models restricted to subjects ascertained within six months of diagnosis (incident cases) to models based on the full data set allowing for left truncation, we found no difference in parameter estimates (P=0.90, 0.32 and 0.95, for stage, grade and ER status respectively). Our results show that use of prevalent cases in an observational epidemiological study of breast cancer does not bias the HR in a left truncation Cox survival analysis, provided the PH assumption holds true.

Common germline polymorphisms in COMT, CYP19A1, ESR1, PGR, SULT1E1 and STS and survival after a diagnosis of breast cancer

Although preliminary evidence suggests that germline variation in genes involved in steroid hormone metabolism may alter breast cancer prognosis, this has not been systematically evaluated. We examined associations between germline polymorphisms in 6 genes involved in the steroid hormone metabolism and signaling pathway (COMT, CYP19A1, ESR1, PGR, SULT1E1, STS) and survival among women with breast cancer participating in SEARCH, a population‐based case–control study. Blood samples from up to 4,470 women were genotyped for 4 possible functional SNPs in CYP19A1 and 106 SNPs tagging the common variation in the remainder of the genes. The genotypes of each polymorphism were tested for association with survival after breast cancer diagnosis using Cox regression analysis. Significant evidence of an association was observed for a COMT polymorphism (rs4818 p = 0.016) under the codominant model. This SNP appeared to fit a dominant model better (HR = 0.80 95% CI: 0.69–0.95, p = 0.009); however, the result was only marginally significant after permutation analysis adjustment for multiple hypothesis tests (p = 0.047). To further evaluate this finding, somatic expression microarray data from 8 publicly available datasets were used to test the association between survival and tumor COMT gene expression; no statistically significant associations were observed. A correlated SNP in COMT, rs4860, has recently been associated with breast cancer prognosis in Chinese women in a dominant model. These results suggest that COMT rs4818, or a variant it tags, is associated with breast cancer prognosis. Further study of COMT and its putative association with breast cancer prognosis is warranted.

Common single-nucleotide polymorphisms in DNA double-strand break repair genes and breast cancer risk.

The proteins involved in homologous recombination are instrumental in the error-free repair of dsDNA breakages, and common germ-line variations in these genes are, therefore, potential candidates for involvement in breast cancer development and progression. We carried out a search for common, low-penetrance susceptibility alleles by tagging the common variation in 13 genes in this pathway in a two-stage case-control study. We genotyped 100 single-nucleotide polymorphisms (SNP), tagging the 655 common SNPs in these genes, in up to 4,470 cases and 4,560 controls from the SEARCH study. None of these tagging SNPs was associated with breast cancer risk, with the exception of XRCC2 rs3218536, R188H, which showed some evidence of a protective association for the rare allele [per allele odds ratio, 0.89; 95% confidence intervals (95% CI), 0.80-0.99; P trend = 0.03]. Further analyses showed that this effect was confined to a risk of progesterone receptor positive tumors (per rare allele odds ratio, 0.78; 95% CI, 0.66-0.91; P trend = 0.002). Several other SNPs also showed receptor status-specific susceptibility and evidence of roles in long-term survival, with the rare allele of BRIP1 rs2191249 showing evidence of association with a poorer prognosis (hazard ratio per minor allele, 1.20; 95% CI, 1.07-1.36; P trend = 0.002). In summary, there was little evidence of breast cancer susceptibility with any of the SNPs studied, but larger studies would be needed to confirm subgroup effects. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3482–9)

Effects of common germline genetic variation in cell cycle control genes on breast cancer survival: results from a population-based cohort

IntroductionSomatic alterations have been shown to correlate with breast cancer prognosis and survival, but less is known about the effects of common inherited genetic variation. Of particular interest are genes involved in cell cycle pathways, which regulate cell division.MethodsWe examined associations between common germline genetic variation in 13 genes involved in cell cycle control (CCND1, CCND2, CCND3, CCNE1, CDK2 [p33], CDK4, CDK6, CDKN1A [p21, Cip1], CDKN1B [p27, Kip1], CDKN2A [p16], CDKN2B [p15], CDKN2C [p18], and CDKN2D [p19]) and survival among women diagnosed with invasive breast cancer participating in the SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity) breast cancer study. DNA from up to 4,470 women was genotyped for 85 polymorphisms that tag the known common polymorphisms (minor allele frequency > 0.05) in the genes. The genotypes of each polymorphism were tested for association with survival using Cox regression analysis.ResultsThe rare allele of the tagging single nucleotide polymorphism (SNP) rs2479717 is associated with an increased risk of death (hazard ratio = 1.26 per rare allele carried, 95% confidence interval: 1.12 to 1.42; P = 0.0001), which was not attenuated after adjusting for tumour stage, grade, and treatment. This SNP is part of a large linkage disequilibrium block, which contains CCND3, BYSL, TRFP, USP49, C6ofr49, FRS3, and PGC. We evaluated the association of survival and somatic expression of these genes in breast tumours using expression microarray data from seven published datasets. Elevated expression of the C6orf49 transcript was associated with breast cancer survival, adding biological interest to the finding.ConclusionIt is possible that CCND3 rs2479717, or another variant it tags, is associated with prognosis after a diagnosis of breast cancer. Further study is required to validate this finding.

Maternal EPHX1 polymorphisms and risk of phenytoin-induced congenital malformations.

Objectives The teratogenic effects of the anti-epileptic drug phenytoin have been linked to genetic differences in phenytoin disposition. The goal of this study was to assess the effect of maternal genotype of functional polymorphisms in two genes involved in phenytoin metabolism, CYP2C9 (R144C, I395L) and EPHX1 (Y113H, H139R), on the presence of major craniofacial abnormalities (CFAs) in the child. Methods We used data from the Collaborative Perinatal Project (1959–1974), a study involving 42 000 mothers and 55 000 children to assess the effect of maternal genotype. We studied 174 pregnancies in 155 women who used phenytoin throughout their pregnancy, gave birth to a live child and had available stored blood specimens suitable for DNA extraction. Results Nineteen children had CFA. In a logistic regression model adjusted for history of phenytoin use during the first trimester and maternal epilepsy (N=157 pregnancies), the maternal EPHX1 113 H [per rare allele odds ratio (OR): 2.43, 95% confidence interval (CI): 1.16–5.10, P=0.02] and 139 R (per rare allele OR: 2.33, 95% CI: 1.09–5.00, P=0.03) alleles were associated with CFAs in the child. The maternal EPHX1 Y113/H139 (common) haplotype showed a significant protective association with CFAs in the child (OR: 0.29, 95% CI: 0.12–0.68, P=0.004), when compared to other haplotypes. CYP2C9 genotype was not related to fetal endpoints. Conclusion Maternal EPHX1 genotype may be associated with risk of fetal anomalies among pregnant women taking phenytoin. Future study is required to confirm these results in larger, independent populations.

Common germline variation in mismatch repair genes and survival after a diagnosis of colorectal cancer

The mismatch repair (MMR) genes are involved in the maintenance of genomic integrity. Recently, we showed that common variants in these genes are unlikely to contribute significantly to colorectal cancer risk. The aim of this study was to investigate the role of common variants in the mismatch repair pathway as prognostic markers in colorectal cancer patients. We genotyped 2,060 patients for 68 SNPs in 7 mismatch repair genes (MLH1, MLH3, MSH2, MSH3, MSH6, PMS1 and PMS2), using a single nucleotide polymorphism (SNP) tagging approach. Genotypes at the tag SNPs and multi‐SNP haplotypes were tested for association with overall survival (OS) and disease specific survival (DSS) using a Cox regression model. Eight SNPs and 10 haplotypes were significant at a nominal p < 0.05 in the univariate analyses. Stepwise analysis showed that haplotype effects were mainly due to associated SNPs carried by these haplotypes. After adjustment for sex, age at diagnosis and stage when using overall survival and stage only when using disease specific survival, prognostic values were unattenuated. The most significant SNP associated with disease specific survival after adjustment was rs863221, located in MSH3 (HR: 0.59, 95% confidence interval (CI) 0.42–0.82, p‐value: 0.001). In conclusion, we find some evidence that common variants in mismatch repair genes may contribute to survival of patients with colorectal cancer.

Common germ-line polymorphism of C1QA and breast cancer survival

Background:A synonymous single nucleotide polymorphism (SNP) rs172378 (A>G, Gly−>Gly) in the complement component C1QA has been proposed to be associated with distant breast cancer metastasis. We previously reported overexpression of this gene to be significantly associated with better prognosis in oestrogen-receptor-negative tumours. The purpose of this study was to investigate the association of rs172378 with expression of C1QA and breast cancer survival.Methods:We analysed the gene expression pattern of rs172378 in normal and tumour tissue samples, and further explored its involvement in relation to mortality in 2270 women with breast cancer participating in Studies of Epidemiology and Risk factors in Cancer Heredity, a population-based case–control study.Results:We found that although rs172378 showed differential allelic expression significantly different between normal (preferentially expressing the G allele) and tumour tissue samples (preferentially expressing the A allele), there was no significant difference in survival by rs172378 genotype (per allele hazard ratio (HR) 1.02, 95% CI: 0.88–1.19, P=0.78 for all-cause mortality; HR 1.03, 95% CI: 0.87–1.22, P=0.72 for breast-cancer-specific mortality).Conclusion:Our study results show that rs172378 is linked to a cis-regulatory element affecting gene expression and that allelic preferential expression is altered in tumour samples, but do not support an association between genetic variation in C1QA and breast cancer survival.