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Campbell P.T.,Epidemiology Research Program | Newton C.C.,Epidemiology Research Program | Newcomb P.A.,Fred Hutchinson Cancer Research Center | Phipps A.I.,Fred Hutchinson Cancer Research Center | And 25 more authors.
Cancer Epidemiology Biomarkers and Prevention | Year: 2015

Background: Microsatellite instability (MSI) and BRAF mutation status are associated with colorectal cancer survival, whereas the role of body mass index (BMI) is less clear. We evaluated the association between BMI and colorectal cancer survival, overall and by strata of MSI, BRAF mutation, sex, and other factors. Methods: This study included 5,615 men and women diagnosed with invasive colorectal cancer who were followed for mortality (maximum: 14.7 years; mean: 5.9 years). Prediagnosis BMI was derived from self-reported weight approximately one year before diagnosis and height. Tumor MSI and BRAF mutation status were available for 4,131 and 4,414 persons, respectively. Multivariable hazard ratios (HR) and 95% confidence intervals (CI) were estimated from delayed-entry Cox proportional hazards models. Results: In multivariable models, high prediagnosis BMI was associated with higher risk of all-cause mortality in both sexes (per 5-kg/m2; HR, 1.10; 95% CI, 1.06-1.15), with similar associations stratified by sex (Pinteraction: 0.41), colon versus rectum (Pinteraction: 0.86), MSI status (Pinteraction: 0.84), and BRAF mutation status (Pinteraction: 0.28). In joint models, with MS-stable/MSI-low and normal BMI as the reference group, risk of death was higher for MS-stable/MSI-low and obese BMI (HR, 1.32; P value: 0.0002), not statistically significantly lower for MSI-high and normal BMI (HR, 0.86; P value: 0.29), and approximately the same for MSIhigh and obese BMI (HR, 1.00; P value: 0.98). Conclusions: High prediagnosis BMI was associated with increased mortality; this association was consistent across participant subgroups, including strata of tumor molecular phenotype. Impact: High BMI may attenuate the survival benefit otherwise observed with MSI-high tumors. © 2015 American Association for Cancer Research. Source

Agim Z.S.,Bogazici University | Esendal M.,Samuel Lunenfeld Research Institute | Briollais L.,Prosserman Center for Health Research | Uyan O.,Bogazici University | And 5 more authors.
PLoS ONE | Year: 2013

Schizophrenia is one of the most common and complex neuropsychiatric disorders, which is contributed both by genetic and environmental exposures. Recently, it is shown that NRG1-mediated ErbB4 signalling regulates many important cellular and molecular processes such as cellular growth, differentiation and death, particularly in myelin-producing cells, glia and neurons. Recent association studies have revealed genomic regions of NRG1 and ERBB4, which are significantly associated with risk of developing schizophrenia; however, inconsistencies exist in terms of validation of findings between distinct populations. In this study, we aim to validate the previously identified regions and to discover novel haplotypes of NRG1 and ERBB4 using logistic regression models and Haploview analyses in three independent datasets from GWAS conducted on European subjects, namely, CATIE, GAIN and nonGAIN. We identified a significant 6-kb block in ERBB4 between chromosome locations 212,156,823 and 212,162,848 in CATIE and GAIN datasets (p = 0.0206 and 0.0095, respectively). In NRG1, a significant 25-kb block, between 32,291,552 and 32,317,192, was associated with risk of schizophrenia in all CATIE, GAIN, and nonGAIN datasets (p = 0.0005, 0.0589, and 0.0143, respectively). Fine mapping and FastSNP analysis of genetic variation located within significantly associated regions proved the presence of binding sites for several transcription factors such as SRY, SOX5, CEPB, and ETS1. In this study, we have discovered and validated haplotypes of ERBB4 and NRG1 in three independent European populations. These findings suggest that these haplotypes play an important role in the development of schizophrenia by affecting transcription factor binding affinity. © 2013 Agim et al. Source

Schoeps A.,German Cancer Research Center | Schoeps A.,University of Heidelberg | Rudolph A.,German Cancer Research Center | Seibold P.,German Cancer Research Center | And 87 more authors.
Genetic Epidemiology | Year: 2014

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. © 2013 WILEY PERIODICALS, INC. Source

Savas S.,Samuel Lunenfeld Research Institute | Savas S.,University of Toronto | Savas S.,Memorial University of Newfoundland | Azorsa D.O.,Translational Genomics Research Institute TGen | And 13 more authors.
PLoS ONE | Year: 2011

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells. © 2011 Savas et al. Source

Kar S.P.,University of Cambridge | Tyrer J.P.,University of Cambridge | Li Q.,Dana-Farber Cancer Institute | Lawrenson K.,University of Southern California | And 163 more authors.
Cancer Epidemiology Biomarkers and Prevention | Year: 2015

Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. © 2015 American Association for Cancer Research. Source

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