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| 2. |
- Hendrickson, Sara J., et al.
(author)
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Plasma Carotenoid- and Retinol-Weighted Multi-SNP Scores and Risk of Breast Cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2013
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In: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia, PA, USA : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 22:5, s. 927-936
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Journal article (peer-reviewed)abstract
- Background: Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in beta-carotene 15,15'-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium. Methods: We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations. Results: Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for beta-carotene, 1.08 (0.98-1.20) for alpha-carotene, 1.04 (0.94-1.16) for beta-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited. Conclusions: Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk. Impact: Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer. (C) 2013 AACR.
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| 3. |
- Klein, Alison P., et al.
(author)
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An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.
- 2013
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In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 8:9
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Journal article (peer-reviewed)abstract
- PURPOSE: We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer.PATIENTS AND METHODS: Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates.RESULTS: Our risk model included current smoking (multivariable adjusted odds ratio (OR) and 95% confidence interval: 2.20 [1.84-2.62]), heavy alcohol use (>3 drinks/day) (OR: 1.45 [1.19-1.76]), obesity (body mass index >30 kg/m(2)) (OR: 1.26 [1.09-1.45]), diabetes >3 years (nested case-control OR: 1.57 [1.13-2.18], case-control OR: 1.80 [1.40-2.32]), family history of pancreatic cancer (OR: 1.60 [1.20-2.12]), non-O ABO genotype (AO vs. OO genotype) (OR: 1.23 [1.10-1.37]) to (BB vs. OO genotype) (OR 1.58 [0.97-2.59]), rs3790844(chr1q32.1) (OR: 1.29 [1.19-1.40]), rs401681(5p15.33) (OR: 1.18 [1.10-1.26]) and rs9543325(13q22.1) (OR: 1.27 [1.18-1.36]). The areas under the ROC curve for risk models including only non-genetic factors, only genetic factors, and both non-genetic and genetic factors were 58%, 57% and 61%, respectively. We estimate that fewer than 3/1,000 U.S. non-Hispanic whites have more than a 5% predicted lifetime absolute risk.CONCLUSION: Although absolute risk modeling using established risk factors may help to identify a group of individuals at higher than average risk of pancreatic cancer, the immediate clinical utility of our model is limited. However, a risk model can increase awareness of the various risk factors for pancreatic cancer, including modifiable behaviors.
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| 4. |
- Barrdahl, Myrto, et al.
(author)
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A comprehensive analysis of polymorphic variants in steroid hormone and insulin-like growth factor-1 metabolism and risk of in situ breast cancer : Results from the Breast and Prostate Cancer Cohort Consortium
- 2018
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In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 142:6, s. 1182-1188
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Journal article (peer-reviewed)abstract
- We assessed the association between 1,414 single nucleotide polymorphisms (SNPs) in genes involved in synthesis and metabolism of steroid hormones and insulin-like growth factor 1, and risk of breast cancer in situ (BCIS), with the aim of determining whether any of these were disease specific. This was carried out using 1,062 BCIS cases and 10,126 controls as well as 6,113 invasive breast cancer cases from the Breast and Prostate Cancer Cohort Consortium (BPC3). Three SNPs showed at least one nominally significant association in homozygous minor versus homozygous major models. ACVR2A-rs2382112 (ORhom=3.05, 95%CI=1.72-5.44, Phom=1.47 × 10-4), MAST2-rs12124649 (ORhom=1.73, 95% CI =1.18-2.54, Phom=5.24 × 10-3), and INSR-rs10500204 (ORhom=1.96, 95% CI=1.44-2.67, Phom=1.68 × 10-5) were associated with increased risk of BCIS; however, only the latter association was significant after correcting for multiple testing. Furthermore, INSR-rs10500204 was more strongly associated with the risk of BCIS than invasive disease in case-only analyses using the homozygous minor versus homozygous major model (ORhom=1.78, 95% CI=1.30-2.44, Phom=3.23 × 10-4). The SNP INSR-rs10500204 is located in an intron of the INSR gene and is likely to affect binding of the promyelocytic leukemia (PML) protein. The PML gene is known as a tumor suppressor and growth regulator in cancer. However, it is not clear on what pathway the A-allele of rs10500204 could operate to influence the binding of the protein. Hence, functional studies are warranted to investigate this further.
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| 5. |
- Barrdahl, Myrto, et al.
(author)
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Association of breast cancer risk loci with breast cancer survival
- 2015
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In: International Journal of Cancer. - : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 137:12, s. 2837-2845
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Journal article (peer-reviewed)abstract
- The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele=0.70; 95% CI: 0.58-0.85; ptrend=2.84 x 10-4; HRheterozygotes=0.71; 95% CI: 0.55-0.92; HRhomozygotes=0.48; 95% CI: 0.31-0.76; p2DF=1.45 x 10-3). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend=6.6 x 10-4; HRheterozygotes=0.96 95% CI: 0.90-1.03; HRhomozygotes=1.21; 95% CI: 1.09-1.35; p2DF=1.25 x 10-4). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.What's new? Genetic factors are known to influence the risk of breast cancer, but inherited genetic variation may also affect disease prognosis and response to treatment. In this study, the we investigated whether single nucleotide polymorphisms (SNPs) that are known to be associated with breast cancer risk might also influence the survival of breast-cancer patients. While two of the investigated SNPs may influence survival, there was otherwise no indication that SNP alleles related to breast cancer risk also play a role in the survival of breast cancer patients.
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| 6. |
- Cao, Yin, et al.
(author)
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Insulin-like growth factor pathway genetic polymorphisms, circulating IGF1 and IGFBP3, and prostate cancer survival
- 2014
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 106:5
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Journal article (peer-reviewed)abstract
- BACKGROUND: The insulin-like growth factor (IGF) signaling pathway has been implicated in prostate cancer (PCa) initiation, but its role in progression remains unknown.METHODS: Among 5887 PCa patients (704 PCa deaths) of European ancestry from seven cohorts in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium, we conducted Cox kernel machine pathway analysis to evaluate whether 530 tagging single nucleotide polymorphisms (SNPs) in 26 IGF pathway-related genes were collectively associated with PCa mortality. We also conducted SNP-specific analysis using stratified Cox models adjusting for multiple testing. In 2424 patients (313 PCa deaths), we evaluated the association of prediagnostic circulating IGF1 and IGFBP3 levels and PCa mortality. All statistical tests were two-sided.RESULTS: The IGF signaling pathway was associated with PCa mortality (P = .03), and IGF2-AS and SSTR2 were the main contributors (both P = .04). In SNP-specific analysis, 36 SNPs were associated with PCa mortality with P-trend less than .05, but only three SNPs in the IGF2-AS remained statistically significant after gene-based corrections. Two were in linkage disequilibrium (r(2) = 1 for rs1004446 and rs3741211), whereas the third, rs4366464, was independent (r(2) = 0.03). The hazard ratios (HRs) per each additional risk allele were 1.19 (95% confidence interval [CI] = 1.06 to 1.34; P-trend = .003) for rs3741211 and 1.44 (95% CI = 1.20 to 1.73; P-trend < .001) for rs4366464. rs4366464 remained statistically significant after correction for all SNPs (P-trend.corr = .04). Prediagnostic IGF1 (HRhighest (vs lowest quartile) = 0.71; 95% CI = 0.48 to 1.04) and IGFBP3 (HR = 0.93; 95% Cl = 0.65 to 1.34) levels were not associated with PCa mortality.CONCLUSIONS: The IGF signaling pathway, primarily IGF2-AS and SSTR2 genes, may be important in PCa survival.
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| 7. |
- Chen, Hongjie, et al.
(author)
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Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals
- 2021
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In: Human Genetics and Genomics Advances. - : Cell Press. - 2666-2477. ; 2:3
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.
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| 8. |
- Dimitrakopoulou, Vasiliki I., et al.
(author)
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Interactions between genome-wide significant genetic variants and circulating concentrations of 25-Hydroxyvitamin D in relation to prostate cancer risk in the National Cancer Institute BPC3
- 2017
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In: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 185:6, s. 452-464
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified over 100 single nucleotide polymorphisms (SNPs) associated with prostate cancer. However, information on the mechanistic basis for some associations is limited. Recent research has been directed towards the potential association of Vitamin D concentrations and prostate cancer, but little is known about whether the aforementioned genetic associations are modified by Vitamin D. We investigated the associations of 46 GWAS-identified SNPs, circulating concentrations of 25-hydroxyVitamin D (25 (OH)D), and prostate cancer (3,811 cases, 511 of whom died from the disease, compared with 2,980 controls- from 5 cohort studies that recruited participants over several periods beginning in the 1980s). We used logistic regression models with data from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) to evaluate interactions on the multiplicative and additive scales. After allowing for multiple testing, none of the SNPs examined was significantly associated with 25(OH)D concentration, and the SNP-prostate cancer associations did not differ by these concentrations. A statistically significant interaction was observed for each of 2 SNPs in the 8q24 region (rs620861 and rs16902094), 25(OH)D concentration, and fatal prostate cancer on both multiplicative and additive scales (P ≥ 0.001). We did not find strong evidence that associations between GWASidentified SNPs and prostate cancer are modified by circulating concentrations of 25(OH)D. The intriguing interactions between rs620861 and rs16902094, 25(OH)D concentration, and fatal prostate cancer warrant replication.
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| 9. |
- Joshi, Amit D., et al.
(author)
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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
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In: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
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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.
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| 10. |
- Kapoor, Pooja Middha, et al.
(author)
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Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium
- 2020
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In: International Journal of Epidemiology. - : Oxford University Press (OUP). - 0300-5771 .- 1464-3685. ; 49:1, s. 216-232
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Journal article (peer-reviewed)abstract
- Background: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. Methods: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. Results: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. Conclusions: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
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