Helen Cramp

Identification of new genetic susceptibility Loci for breast cancer through consideration of gene-environment interactions

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/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 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.

Associations of ATR and CHEK1 Single Nucleotide Polymorphisms with Breast Cancer

DNA damage and replication checkpoints mediated by the ATR-CHEK1 pathway are key to the maintenance of genome stability, and both ATR and CHEK1 have been proposed as potential breast cancer susceptibility genes. Many novel variants recently identified by the large resequencing projects have not yet been thoroughly tested in genome-wide association studies for breast cancer susceptibility. We therefore used a tagging SNP (tagSNP) approach based on recent SNP data available from the 1000 genomes projects, to investigate the roles of ATR and CHEK1 in breast cancer risk and survival. ATR and CHEK1 tagSNPs were genotyped in the Sheffield Breast Cancer Study (SBCS; 1011 cases and 1024 controls) using Illumina GoldenGate assays. Untyped SNPs were imputed using IMPUTE2, and associations between genotype and breast cancer risk and survival were evaluated using logistic and Cox proportional hazard regression models respectively on a per allele basis. Significant associations were further examined in a meta-analysis of published data or confirmed in the Utah Breast Cancer Study (UBCS). The most significant associations for breast cancer risk in SBCS came from rs6805118 in ATR (p=7.6x10-5) and rs2155388 in CHEK1 (p=3.1x10-6), but neither remained significant after meta-analysis with other studies. However, meta-analysis of published data revealed a weak association between the ATR SNP rs1802904 (minor allele frequency is 12%) and breast cancer risk, with a summary odds ratio (confidence interval) of 0.90 (0.83-0.98) [p=0.0185] for the minor allele. Further replication of this SNP in larger studies is warranted since it is located in the target region of 2 microRNAs. No evidence of any survival effects of ATR or CHEK1 SNPs were identified. We conclude that common alleles of ATR and CHEK1 are not implicated in breast cancer risk or survival, but we cannot exclude effects of rare alleles and of common alleles with very small effect sizes.

Levels of DNA Methylation Vary at CpG Sites across the BRCA1 Promoter, and Differ According to Triple Negative and "BRCA-Like" Status, in Both Blood and Tumour DNA.

Triple negative breast cancer is typically an aggressive and difficult to treat subtype. It is often associated with loss of function of the BRCA1 gene, either through mutation, loss of heterozygosity or methylation. This study aimed to measure methylation of the BRCA1 gene promoter at individual CpG sites in blood, tumour and normal breast tissue, to assess whether levels were correlated between different tissues, and with triple negative receptor status, histopathological scoring for BRCA-like features and BRCA1 protein expression. Blood DNA methylation levels were significantly correlated with tumour methylation at 9 of 11 CpG sites examined (p<0.0007). The levels of tumour DNA methylation were significantly higher in triple negative tumours, and in tumours with high BRCA-like histopathological scores (10 of 11 CpG sites; p<0.01 and p<0.007 respectively). Similar results were observed in blood DNA (6 of 11 CpG sites; p<0.03 and 7 of 11 CpG sites; p<0.02 respectively). This study provides insight into the pattern of CpG methylation across the BRCA1 promoter, and supports previous studies suggesting that tumours with BRCA1 promoter methylation have similar features to those with BRCA1 mutations, and therefore may be suitable for the same targeted therapies.

Genome-Wide Analysis of Circulating Cell-Free DNA Copy Number Detects Active Melanoma and Predicts Survival

BACKGROUND A substantial number of melanoma patients develop local or metastatic recurrence, and early detection of these is vital to maximise benefit from new therapies such as inhibitors of BRAF and MEK, or immune checkpoints. This study explored the use of novel DNA copy-number profiles in circulating cell-free DNA (cfDNA) as a potential biomarker of active disease and survival. PATIENTS AND METHODS Melanoma patients were recruited from oncology and dermatology clinics in Sheffield, UK, and cfDNA was isolated from stored blood plasma. Using low-coverage whole-genome sequencing, we created copy-number profiles from cfDNA from 83 melanoma patients, 44 of whom had active disease. We used scoring algorithms to summarize copy-number aberrations and investigated their utility in multivariable logistic and Cox regression analyses. RESULTS The copy-number aberration score (CNAS) was a good discriminator of active disease (odds ratio, 3.1; 95% CI, 1.5-6.2; P = 0.002), and CNAS above or below the 75th percentile remained a significant discriminator in multivariable analysis for active disease (P = 0.019, with area under ROC curve of 0.90). Additionally, mortality was higher in those with CNASs above the 75th percentile than in those with lower scores (HR, 3.4; 95% CI, 1.5-7.9; P = 0.005), adjusting for stage of disease, disease status (active or resected), BRAF status, and cfDNA concentration. CONCLUSIONS This study demonstrates the potential of a de novo approach utilizing copy-number profiling of cfDNA as a biomarker of active disease and survival in melanoma. Longitudinal analysis of copy-number profiles as an early marker of relapsed disease is warranted.