| 1. |
- Canzian, Federico, et al.
(författare)
-
Comprehensive analysis of common genetic variation in 61 genes related to steroid hormone and insulin-like growth factor-I metabolism and breast cancer risk in the NCI breast and prostate cancer cohort consortium.
- 2010
-
Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 19:19, s. 3873-84
-
Tidskriftsartikel (refereegranskat)abstract
- There is extensive evidence that increases in blood and tissue concentrations of steroid hormones and of insulin-like growth factor I (IGF-I) are associated with breast cancer risk. However, studies of common variation in genes involved in steroid hormone and IGF-I metabolism have yet to provide convincing evidence that such variants predict breast cancer risk. The Breast and Prostate Cancer Cohort Consortium (BPC3) is a collaboration of large US and European cohorts. We genotyped 1416 tagging single nucleotide polymorphisms (SNPs) in 37 steroid hormone metabolism genes and 24 IGF-I pathway genes in 6292 cases of breast cancer and 8135 controls, mostly Caucasian, postmenopausal women from the BPC3. We also imputed 3921 additional SNPs in the regions of interest. None of the SNPs tested was significantly associated with breast cancer risk, after correction for multiple comparisons. The results remained null when cases and controls were stratified by age at diagnosis/recruitment, advanced or nonadvanced disease, body mass index, with or without in situ cases; or restricted to Caucasians. Among 770 estrogen receptor-negative cases, an SNP located 3' of growth hormone receptor (GHR) was marginally associated with increased risk after correction for multiple testing (P(trend) = 1.5 × 10(-4)). We found no significant overall associations between breast cancer and common germline variation in 61 genes involved in steroid hormone and IGF-I metabolism in this large, comprehensive study. Although previous studies have shown that variations in these genes can influence endogenous hormone levels, the magnitude of the effect of single SNPs does not appear to be sufficient to alter breast cancer risk.
|
|
| 2. |
- Gu, Fangyi, et al.
(författare)
-
Eighteen insulin-like growth factor pathway genes, circulating levels of IGF-I and its binding protein, and risk of prostate and breast cancer
- 2010
-
Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 19:11, s. 2877-2887
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Circulating levels of insulin-like growth factor I (IGF-I) and its main binding protein, IGF binding protein 3 (IGFBP-3), have been associated with risk of several types of cancer. Heritable factors explain up to 60% of the variation in IGF-I and IGFBP-3 in studies of adult twins.Methods: We systematically examined common genetic variation in 18 genes in the IGF signaling pathway for associations with circulating levels of IGF-I and IGFBP-3. A total of 302 single nucleotide polymorphisms (SNP) were genotyped in >5,500 Caucasian men and 5,500 Caucasian women from the Breast and Prostate Cancer Cohort Consortium.Results: After adjusting for multiple testing, SNPs in the IGF1 and SSTR5 genes were significantly associated with circulating IGF-I (P < 2.1 × 10−4); SNPs in the IGFBP3 and IGFALS genes were significantly associated with circulating IGFBP-3. Multi-SNP models explained R2 = 0.62% of the variation in circulating IGF-I and 3.9% of the variation in circulating IGFBP-3. We saw no significant association between these multi-SNP predictors of circulating IGF-I or IGFBP-3 and risk of prostate or breast cancers.Conclusion: Common genetic variation in the IGF1 and SSTR5 genes seems to influence circulating IGF-I levels, and variation in IGFBP3 and IGFALS seems to influence circulating IGFBP-3. However, these variants explain only a small percentage of the variation in circulating IGF-I and IGFBP-3 in Caucasian men and women.Impact: Further studies are needed to explore contributions from other genetic factors such as rare variants in these genes and variation outside of these genes.
|
|
| 3. |
- Huesing, Anika, et al.
(författare)
-
Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
-
Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
-
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.
|
|
| 4. |
- Wang, Zhaoming, et al.
(författare)
-
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
-
Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
-
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.
|
|
