| 21. |
- Campa, Daniele, et al.
(author)
-
Genetic risk variants associated with in situ breast cancer
- 2015
-
In: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 17
-
Journal article (peer-reviewed)abstract
- Introduction: Breast cancer in situ (BCIS) diagnoses, a precursor lesion for invasive breast cancer, comprise about 20 % of all breast cancers (BC) in countries with screening programs. Family history of BC is considered one of the strongest risk factors for BCIS.Methods: To evaluate the association of BC susceptibility loci with BCIS risk, we genotyped 39 single nucleotide polymorphisms (SNPs), associated with risk of invasive BC, in 1317 BCIS cases, 10,645 invasive BC cases, and 14,006 healthy controls in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). Using unconditional logistic regression models adjusted for age and study, we estimated the association of SNPs with BCIS using two different comparison groups: healthy controls and invasive BC subjects to investigate whether BCIS and BC share a common genetic profile.Results: We found that five SNPs (CDKN2BAS-rs1011970, FGFR2-rs3750817, FGFR2-rs2981582, TNRC9-rs3803662, 5p12-rs10941679) were significantly associated with BCIS risk (P value adjusted for multiple comparisons <0.0016). Comparing invasive BC and BCIS, the largest difference was for CDKN2BAS-rs1011970, which showed a positive association with BCIS (OR = 1.24, 95 % CI: 1.11-1.38, P = 1.27 x 10(-4)) and no association with invasive BC (OR = 1.03, 95 % CI: 0.99-1.07, P = 0.06), with a P value for case-case comparison of 0.006. Subgroup analyses investigating associations with ductal carcinoma in situ (DCIS) found similar associations, albeit less significant (OR = 1.25, 95 % CI: 1.09-1.42, P = 1.07 x 10(-3)). Additional risk analyses showed significant associations with invasive disease at the 0.05 level for 28 of the alleles and the OR estimates were consistent with those reported by other studies.Conclusions: Our study adds to the knowledge that several of the known BC susceptibility loci are risk factors for both BCIS and invasive BC, with the possible exception of rs1011970, a putatively functional SNP situated in the CDKN2BAS gene that may be a specific BCIS susceptibility locus.
|
|
| 22. |
- Campa, Daniele, et al.
(author)
-
Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium
- 2011
-
In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 103:16, s. 1252-1263
-
Journal article (peer-reviewed)abstract
- Background Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer. Methods To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 x 10(-4)) was done. Casecase comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided. Results We confirmed the association of 14 SNPs with breast cancer risk (P(trend) = 2.57 x 10(-3) -3.96 x 10(-19)). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor-positive than estrogen receptor-negative breast cancer (P(heterogeneity) = .0016 for FGFR2-rs2981582 and P(heterogeneity) = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor-positive than progesterone receptor-negative breast cancer (P(heterogeneity) = .0028). Conclusion This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.
|
|
| 23. |
- Canzian, Federico, et al.
(author)
-
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
-
In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 19:19, s. 3873-84
-
Journal article (peer-reviewed)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.
|
|
| 24. |
- Figueroa, Jonine D., et al.
(author)
-
Genome-wide association study identifies multiple loci associated with bladder cancer risk
- 2014
-
In: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 23:5, s. 1387-1398
-
Journal article (peer-reviewed)abstract
- andidate gene and genome-wide association studies (GWAS) have identified 11 independent susceptibility loci associated with bladder cancer risk. To discover additional risk variants, we conducted a new GWAS of 2422 bladder cancer cases and 5751 controls, followed by a meta-analysis with two independently published bladder cancer GWAS, resulting in a combined analysis of 6911 cases and 11 814 controls of European descent. TaqMan genotyping of 13 promising single nucleotide polymorphisms with P < 1 × 10−5 was pursued in a follow-up set of 801 cases and 1307 controls. Two new loci achieved genome-wide statistical significance: rs10936599 on 3q26.2 (P = 4.53 × 10−9) and rs907611 on 11p15.5 (P = 4.11 × 10−8). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 × 10−7) and rs4510656 on 6p22.3 (P = 6.98 × 10−7); these require further studies for confirmation. In conclusion, our study has identified new susceptibility alleles for bladder cancer risk that require fine-mapping and laboratory investigation, which could further understanding into the biological underpinnings of bladder carcinogenesis.
|
|
| 25. |
- Fu, Yi-Ping, et al.
(author)
-
The 19q12 Bladder Cancer GWAS Signal : Association with Cyclin E Function and Aggressive Disease
- 2014
-
In: Cancer Research. - 0008-5472 .- 1538-7445. ; 74:20, s. 5808-5818
-
Journal article (peer-reviewed)abstract
- A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell-cycle protein. We performed genetic fine-mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r(2) >= 0.7) associated with increased bladder cancer risk. From this group, we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWASs, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele OR = 1.18 [95% confidence interval (CI), 1.09-1.27, P = 4.67 x 10(-5)] versus OR = 1.01 (95% CI, 0.93-1.10, P = 0.79) for nonaggressive disease, with P = 0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (P = 0.013) and, independently, with each rs7257330-A risk allele (P-trend = 0.024). Overexpression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E overexpression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models.
|
|
| 26. |
- Gaudet, Mia M, et al.
(author)
-
Blood Levels of Cadmium and Lead in Relation to Breast Cancer Risk in Three Prospective Cohorts.
- 2019
-
In: International Journal of Cancer. - : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 144:5, s. 1010-1016
-
Journal article (peer-reviewed)abstract
- Cadmium and lead have been classified as carcinogens by the International Agency for Research on Cancer. However, their associations with breast cancer risk are unknown despite their persistence in the environment and ubiquitous human exposure. We examined associations of circulating levels of cadmium and lead with breast cancer risk in three case-control studies nested within the Cancer Prevention Study-II (CPS-II) LifeLink Cohort, European Prospective Investigation into Cancer and Nutrition - Italy (EPIC-Italy), and the Northern Sweden Health and Disease Study (NSHDS) cohorts. Metal levels were measured in stored erythrocytes from 1,435 cases and 1,433 controls using inductively coupled plasma-mass spectrometry. Summary relative risks (RR) and 95% confidence intervals (CI) were calculated using random-effects models with each study result weighted by the within- and between-study variances. I2 values were calculated to estimate proportion of between study variation. Using common cut-points, cadmium levels were not associated with breast cancer risk in the CPS-II cohort (continuous RR=1.01, 95% CI 0.76 - 1.34), but were inversely associated with risk in the EPIC- Italy (continuous RR=0.80, 95% CI 0.61 - 1.03) and NSHDS cohorts (continuous RR=0.73, 95% CI 0.54 - 0.97). The inverse association was also evident in the meta-analysis (continuous RR=0.84, 95% CI 0.69 - 1.01) with low between-study heterogeneity. Large differences in lead level distributions precluded a meta-analysis of their association with breast cancer risk; no associations were found in the three studies. Adult cadmium and lead levels were not associated with higher risk of breast cancer in our large meta-analysis.
|
|
| 27. |
- Henrion, Marc Y R, et al.
(author)
-
Common variation at 1q24.1 (ALDH9A1) is a potential risk factor for renal cancer
- 2015
-
In: PLOS ONE. - : Public library science. - 1932-6203. ; 10:3
-
Journal article (peer-reviewed)abstract
- So far six susceptibility loci for renal cell carcinoma (RCC) have been discovered by genome-wide association studies (GWAS). To identify additional RCC common risk loci, we performed a meta-analysis of published GWAS (totalling 2,215 cases and 8,566 controls of Western-European background) with imputation using 1000 Genomes Project and UK10K Project data as reference panels and followed up the most significant association signals [22 single nucleotide polymorphisms (SNPs) and 3 indels in eight genomic regions] in 383 cases and 2,189 controls from The Cancer Genome Atlas (TCGA). A combined analysis identified a promising susceptibility locus mapping to 1q24.1 marked by the imputed SNP rs3845536 (Pcombined =2.30x10-8). Specifically, the signal maps to intron 4 of the ALDH9A1 gene (aldehyde dehydrogenase 9 family, member A1). We further evaluated this potential signal in 2,461 cases and 5,081 controls from the International Agency for Research on Cancer (IARC) GWAS of RCC cases and controls from multiple European regions. In contrast to earlier findings no association was shown in the IARC series (P=0.94; Pcombined =2.73x10-5). While variation at 1q24.1 represents a potential risk locus for RCC, future replication analyses are required to substantiate our observation.
|
|
| 28. |
- Huesing, Anika, et al.
(author)
-
Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
-
In: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
-
Journal article (peer-reviewed)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.
|
|
| 29. |
- Joshi, Amit D., et al.
(author)
-
Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium
- 2014
-
In: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
-
Journal article (peer-reviewed)abstract
- Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 x 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
|
|
| 30. |
- Lindstroem, Sara, et al.
(author)
-
Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
- 2012
-
In: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
-
Journal article (peer-reviewed)abstract
- Background: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age.Methods: We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data.Results: The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile).Conclusions: Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening.Impact: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
|
|
