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  • GENE  (20)
  • susceptibility loci  (14)
  • 1
    Keywords: CANCER ; EXPRESSION ; SURVIVAL ; neoplasms ; PATHWAY ; RISK ; GENE ; ASSOCIATION ; SUSCEPTIBILITY ; BREAST ; BREAST-CANCER ; METASTASIS ; POOR-PROGNOSIS ; HIGH-FREQUENCY ; GENETIC SUSCEPTIBILITY ; OVARIAN ; association study ; CORRELATE ; germline variation ; PIK3CA MUTATIONS ; PTEN LOSS
    Abstract: Background:Somatic mutations in phosphoinositide-3-kinase catalytic subunit alpha (PIK3CA) are frequent in breast tumours and have been associated with oestrogen receptor (ER) expression, human epidermal growth factor receptor-2 overexpression, lymph node metastasis and poor survival. The goal of this study was to evaluate the association between inherited variation in this oncogene and risk of breast cancer.Methods:A single-nucleotide polymorphism from the PIK3CA locus that was associated with breast cancer in a study of Caucasian breast cancer cases and controls from the Mayo Clinic (MCBCS) was genotyped in 5436 cases and 5280 controls from the Cancer Genetic Markers of Susceptibility (CGEMS) study and in 30 949 cases and 29 788 controls from the Breast Cancer Association Consortium (BCAC).Results:Rs1607237 was significantly associated with a decreased risk of breast cancer in MCBCS, CGEMS and all studies of white Europeans combined (odds ratio (OR)=0.97, 95% confidence interval (CI) 0.95-0.99, P=4.6 x 10(-3)), but did not reach significance in the BCAC replication study alone (OR=0.98, 95% CI 0.96-1.01, P=0.139).Conclusion:Common germline variation in PIK3CA does not have a strong influence on the risk of breast cancer.
    Type of Publication: Journal article published
    PubMed ID: 22033276
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  • 2
    Keywords: CANCER ; EXPRESSION ; RISK ; GENE ; SUSCEPTIBILITY ; breast cancer ; PATTERNS ; risk factors ; ESTROGEN-RECEPTOR ; ALLELES ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; PROGESTERONE-RECEPTOR ; BRCA2 MUTATION CARRIERS ; Risk prediction
    Abstract: Breast cancers demonstrate substantial biological, clinical and etiological heterogeneity. We investigated breast cancer risk associations of eight susceptibility loci identified in GWAS and two putative susceptibility loci in candidate genes in relation to specific breast tumor subtypes. Subtypes were defined by five markers (ER, PR, HER2, CK5/6, EGFR) and other pathological and clinical features. Analyses included up to 30 040 invasive breast cancer cases and 53 692 controls from 31 studies within the Breast Cancer Association Consortium. We confirmed previous reports of stronger associations with ER+ than ER- tumors for six of the eight loci identified in GWAS: rs2981582 (10q26) (P-heterogeneity = 6.1 x 10(-18)), rs3803662 (16q12) (P = 3.7 x 10(-5)), rs13281615 (8q24) (P = 0.002), rs13387042 (2q35) (P = 0.006), rs4973768 (3p24) (P = 0.003) and rs6504950 (17q23) (P = 0.002). The two candidate loci, CASP8 (rs1045485, rs17468277) and TGFB1 (rs1982073), were most strongly related with the risk of PR negative tumors (P = 5.1 x 10(-6) and P = 4.1 x 10(-4), respectively), as previously suggested. Four of the eight loci identified in GWAS were associated with triple negative tumors (P 〈= 0.016): rs3803662 (16q12), rs889312 (5q11), rs3817198 (11p15) and rs13387042 (2q35); however, only two of them (16q12 and 2q35) were associated with tumors with the core basal phenotype (P 〈= 0.002). These analyses are consistent with different biological origins of breast cancers, and indicate that tumor stratification might help in the identification and characterization of novel risk factors for breast cancer subtypes. This may eventually result in further improvements in prevention, early detection and treatment
    Type of Publication: Journal article published
    PubMed ID: 21596841
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  • 3
    Keywords: ENVIRONMENT ; Germany ; MODEL ; MODELS ; ALGORITHM ; INFORMATION ; EPIDEMIOLOGY ; GENE ; SAMPLE ; MARKER ; ASSOCIATION ; LINKAGE ; polymorphism ; single nucleotide polymorphism ; statistics ; smoking ; MARKERS ; REGION ; REGIONS ; LINKAGE DISEQUILIBRIUM ; HLA ; PREDICTORS ; LOCATION ; SINGLE ; REGRESSION ; RHEUMATOID-ARTHRITIS ; interaction ; analysis ; methods ; GENOTYPE ; single-nucleotide ; single-nucleotide polymorphism ; mantel statistics ; POWER ; PREDICTOR ; LINKAGE-DISEQUILIBRIUM ; SET ; ENVIRONMENTAL-FACTORS ; case control ; LOGISTIC-REGRESSION ; comparison ; case-control ; association study ; sex ; genetic analysis
    Abstract: Accounting for interactions with environmental factors in association studies may improve the power to detect genetic effects and may help identifying important environmental effect modifiers. The power of unphased genotype-versus haplotype-based methods in regions with high linkage disequilibrium (LD), as measured by D', for analyzing gene x environment (gene x sex) interactions was compared using the Genetic Analysis Workshop 15 (GAW15) simulated data on rheumatoid arthritis with prior knowledge of the answers. Stepwise and regular conditional logistic regression (CLR) was performed using a matched case-control sample for a HLA region interacting with sex. Haplotype-based analyses were performed using a haplotype-sharing-based Mantel statistic and a test for haplotype-trait association in a general linear model framework. A step-down minP algorithm was applied to derive adjusted p-values and to allow for power comparisons. These methods were also applied to the GAW15 real data set for PTPN22.For markers in strong LD, stepwise CLR performed poorly because of the correlation/collinearity between the predictors in the model. The power was high for detecting genetic main effects using simple CLR models and haplotype-based methods and for detecting joint effects using CLR and Mantel statistics. Only the haplotype-trait association test had high power to detect the gene x sex interaction.In the PTPN22 region with markers characterized by strong LD, all methods indicated a significant genotype x sex interaction in a sample of about 1000 subjects. The previously reported R620W single-nucleotide polymorphism was identified using logistic regression, but the haplotype-based methods did not provide any precise location information.
    Type of Publication: Journal article published
    PubMed ID: 18466575
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  • 4
    Keywords: CANCER ; MODEL ; POPULATION ; RISK ; SITE ; SITES ; GENE ; GENES ; BIOMARKERS ; ASSOCIATION ; polymorphism ; POLYMORPHISMS ; single nucleotide polymorphism ; SUSCEPTIBILITY ; VARIANTS ; HEALTH ; ovarian cancer ; OVARIAN-CANCER ; WOMEN ; REPLICATION ; glycosylation ; ONCOLOGY ; SINGLE NUCLEOTIDE POLYMORPHISMS ; biomarker ; CANCER-RISK ; Genetic ; single nucleotide
    Abstract: Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for hetero geneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies. Cancer Epidemiol Biomarkers Prev; 19(2); 600-4. (C) 2010 AACR
    Type of Publication: Journal article published
    PubMed ID: 20142253
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  • 5
    Keywords: CANCER ; SURVIVAL ; RISK ; FAMILY ; ASSOCIATION ; SUSCEPTIBILITY ; BREAST-CANCER ; MUTATIONS ; MUTATION CARRIERS ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; CONSORTIUM
    Abstract: Purpose: An assay for the single-nucleotide polymorphism (SNP), rs61764370, has recently been commercially marketed as a clinical test to aid ovarian cancer risk evaluation in women with family histories of the disease. rs67164370 is in a 3'-UTR miRNA binding site of the KRAS oncogene and is a candidate for epithelial ovarian cancer (EOC) susceptibility. However, only one published article, analyzing fewer than 1,000 subjects in total, has examined this association. Experimental Design: Risk association was evaluated in 8,669 cases of invasive EOC and 10,012 controls from 19 studies participating in the Ovarian Cancer Association Consortium, and in 683 cases and 2,044 controls carrying BRCA1 mutations from studies in the Consortium of Investigators of Modifiers of BRCA1/2. Prognosis association was also examined in a subset of five studies with progression-free survival (PFS) data and 18 studies with all-cause mortality data. Results: No evidence of association was observed between genotype and risk of unselected EOC (OR = 1.02, 95% CI: 0.95-1.10), serous EOC (OR = 1.08, 95% CI: 0.98-1.18), familial EOC (OR = 1.09, 95% CI: 0.78-1.54), or among women carrying deleterious mutations in BRCA1 (OR = 1.09, 95% CI: 0.88-1.36). There was little evidence for association with survival time among unselected cases (HR = 1.10, 95% CI: 0.99-1.22), among serous cases (HR = 1.12, 95% CI = 0.99-1.28), or with PFS in 540 cases treated with carboplatin and paclitaxel (HR = 1.18, 95% CI: 0.93-1.52). Conclusions: These data exclude the possibility of an association between rs61764370 and a clinically significant risk of ovarian cancer or of familial ovarian cancer. Use of this SNP for ovarian cancer clinical risk prediction, therefore, seems unwarranted.
    Type of Publication: Journal article published
    PubMed ID: 21385923
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  • 6
    Keywords: carcinoma ; POPULATION ; GENE-EXPRESSION ; MARKER ; OVARIAN-CANCER ; PROSTATE-CANCER ; METAANALYSIS ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; PLATFORM
    Abstract: Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 x 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.
    Type of Publication: Journal article published
    PubMed ID: 25378557
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  • 7
    Keywords: EXPRESSION ; REDUCED RISK ; HUMAN GENES ; SINGLE-NUCLEOTIDE POLYMORPHISMS ; BINDING-SITES ; COMMON VARIANT ; CASP8 GENE ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; IDENTIFIES 3
    Abstract: Genetic variations, such as single nucleotide polymorphisms (SNPs) in microRNAs (miRNA) or in the miRNA binding sites may affect the miRNA dependent gene expression regulation, which has been implicated in various cancers, including breast cancer, and may alter individual susceptibility to cancer. We investigated associations between miRNA related SNPs and breast cancer risk. First we evaluated 2,196 SNPs in a case-control study combining nine genome wide association studies (GWAS). Second, we further investigated 42 SNPs with suggestive evidence for association using 41,785 cases and 41,880 controls from 41 studies included in the Breast Cancer Association Consortium (BCAC). Combining the GWAS and BCAC data within a meta-analysis, we estimated main effects on breast cancer risk as well as risks for estrogen receptor (ER) and age defined subgroups. Five miRNA binding site SNPs associated significantly with breast cancer risk: rs1045494 (odds ratio (OR) 0.92; 95% confidence interval (CI): 0.88-0.96), rs1052532 (OR 0.97; 95% CI: 0.95-0.99), rs10719 (OR 0.97; 95% CI: 0.94-0.99), rs4687554 (OR 0.97; 95% CI: 0.95-0.99, and rs3134615 (OR 1.03; 95% CI: 1.01-1.05) located in the 3' UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively. DROSHA belongs to miRNA machinery genes and has a central role in initial miRNA processing. The remaining genes are involved in different molecular functions, including apoptosis and gene expression regulation. Further studies are warranted to elucidate whether the miRNA binding site SNPs are the causative variants for the observed risk effects.
    Type of Publication: Journal article published
    PubMed ID: 25390939
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  • 8
    Keywords: EXPRESSION ; GENE ; BREAST-CANCER ; OVARIAN-CANCER ; PROSTATE-CANCER ; telomere length ; COMMON VARIANT ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; FUNCTIONAL VARIATION
    Abstract: Several studies have reported associations between multiple cancer types and single-nucleotide polymorphisms (SNPs) on chromosome 5p15, which harbours TERT and CLPTM1L, but no such association has been reported with endometrial cancer. To evaluate the role of genetic variants at the TERT-CLPTM1L region in endometrial cancer risk, we carried out comprehensive fine-mapping analyses of genotyped and imputed SNPs using a custom Illumina iSelect array which includes dense SNP coverage of this region. We examined 396 SNPs (113 genotyped, 283 imputed) in 4,401 endometrial cancer cases and 28,758 controls. Single-SNP and forward/backward logistic regression models suggested evidence for three variants independently associated with endometrial cancer risk (P = 4.9 x 10(-6) to P = 7.7 x 10(-5)). Only one falls into a haplotype previously associated with other cancer types (rs7705526, in TERT intron 1), and this SNP has been shown to alter TERT promoter activity. One of the novel associations (rs13174814) maps to a second region in the TERT promoter and the other (rs62329728) is in the promoter region of CLPTM1L; neither are correlated with previously reported cancer-associated SNPs. Using TCGA RNASeq data, we found significantly increased expression of both TERT and CLPTM1L in endometrial cancer tissue compared with normal tissue (TERT P = 1.5 x 10(-18), CLPTM1L P = 1.5 x 10(-19)). Our study thus reports a novel endometrial cancer risk locus and expands the spectrum of cancer types associated with genetic variation at 5p15, further highlighting the importance of this region for cancer susceptibility.
    Type of Publication: Journal article published
    PubMed ID: 25487306
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  • 9
    Keywords: carcinoma ; MODELS ; POPULATION ; VARIANTS ; BREAST-CANCER ; TRANSCRIPTION FACTORS ; PROFILES ; SET ; susceptibility loci ; GENOME-WIDE ASSOCIATION
    Abstract: 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 co-expression 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 co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set 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 data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.
    Type of Publication: Journal article published
    PubMed ID: 26209509
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  • 10
    Keywords: Germany ; ALGORITHM ; DISEASE ; DISEASES ; EXPOSURE ; GENE ; GENES ; SAMPLE ; MARKER ; ASSOCIATION ; VARIANTS ; HEALTH ; genetics ; MARKERS ; LINKAGE DISEQUILIBRIUM ; gene-environment interaction ; PREVALENCE ; heredity ; case-control study ; RE ; VARIANT ; interaction ; analysis ; POWER ; TECHNOLOGY ; USA ; VARIABLES ; genetic association ; association study ; interactions ; DETECT ; GENE-ENVIRONMENT INTERACTIONS ; indirect association ; gene-environment interaction effect
    Abstract: Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily, inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only
    Type of Publication: Journal article published
    PubMed ID: 18163529
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