| 1. |
- Garcia-Closas, Montserrat, et al.
(författare)
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Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics
- 2008
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Ingår i: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 4:4, s. e1000054-
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Tidskriftsartikel (refereegranskat)abstract
- A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
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| 2. |
- Huesing, Anika, et al.
(författare)
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Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
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Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
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Tidskriftsartikel (refereegranskat)abstract
- Objective There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Material and methods Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. Results We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Discussion and conclusions Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
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| 3. |
- Wang, Zhaoming, et al.
(författare)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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