503 research outputs found
Heterogeneity of Breast Cancer Associations with Five
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 = 10213). This SNP was also more strongly related to PR-positive, low grade and node positive tumors
(P = 1025, 1028, 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 1024, 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
Genetic and Non-genetic Predictors of LINE-1 Methylation in Leukocyte DNA.
Background: Altered DNA methylation has been associated with various diseases. Objective: We evaluated the association between levels of methylation in leukocyte DNA at long interspersed nuclear element 1 (LINE-1) and genetic and non-genetic characteristics of 892 control participants from the Spanish Bladder Cancer/EPICURO study. Methods: We determined LINE-1 methylation levels by pyrosequencing. Individual data included demographics, smoking status, nutrient intake, toenail concentrations of 12 trace elements, xenobiotic metabolism gene variants, and 515 polymorphisms among 24 genes in the one-carbon metabolism pathway. To assess the association between LINE-1 methylation levels (percentage of methylated cytosines) and potential determinants, we estimated beta coefficients (βs) by robust linear regression. Results: Women had lower levels of LINE-1 methylation than men (β = –0.7, p = 0.02). Persons who smoked blond tobacco showed lower methylation than nonsmokers (β = –0.7, p = 0.03). Arsenic toenail concentration was inversely associated with LINE-1 methylation (β = –3.6, p = 0.003). By contrast, iron (β = 0.002, p = 0.009) and nickel (β = 0.02, p = 0.004) were positively associated with LINE-1 methylation. Single nucleotide polymorphisms (SNPs) in DNMT3A (rs7581217-per allele, β = 0.3, p = 0.002), TCN2 (rs9606756-GG, β = 1.9, p = 0.008; rs4820887-AA, β = 4.0, p = 4.8 × 10–7; rs9621049-TT, β = 4.2, p = 4.7 × 10–9), AS3MT (rs7085104-GG, β = 0.7, p = 0.001), SLC19A1 (rs914238, TC vs. TT: β = 0.5 and CC vs. TT: β = –0.3, global p = 0.0007) and MTHFS (rs1380642, CT vs. CC: β = 0.3 and TT vs. CC; β = –0.8, global p = 0.05) were associated with LINE-1 methylation. Conclusions: We identified several characteristics, environmental factors, and common genetic variants that predicted DNA methylation among study participants.This work was partially supported by the Association for International Cancer Research (AICR; grant 09-0780, and a doctoral scholarship awarded to S.M.T.); Fondo de Investigaciones Sanitarias, Instituto de Salud Carlos III, MINECO, Spain (grants 00/0745, PI051436, PI061614, PI09-02102, and G03/174); Red Temática de Investigación Cooperativa en Cáncer (grant RD06/0020-RTICC); the U.S. National Institutes of Health (grant RO1-CA089715); a postdoctoral fellowship awarded to A.F.S.A. from the Fundación Científica de la AECC; Fundació Marató TV3; and The Johns Hopkins University Vredenburg Scholarship awarded to A.L.C
Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models
Objective: Absolute risk models estimate an individual's future disease risk
over a specified time interval. Applications utilizing server-side risk
tooling, such as the R-based iCARE (R-iCARE), to build, validate, and apply
absolute risk models, face serious limitations in portability and privacy due
to their need for circulating user data in remote servers for operation. Our
objective was to overcome these limitations.
Materials and Methods: We refactored R-iCARE into a Python package (Py-iCARE)
then compiled it to WebAssembly (Wasm-iCARE): a portable web module, which
operates entirely within the privacy of the user's device.
Results: We showcase the portability and privacy of Wasm-iCARE through two
applications: for researchers to statistically validate risk models, and to
deliver them to end-users. Both applications run entirely on the client-side,
requiring no downloads or installations, and keeps user data on-device during
risk calculation.
Conclusions: Wasm-iCARE fosters accessible and privacy-preserving risk tools,
accelerating their validation and delivery.Comment: 10 pages, 2 figure
Large-Scale Evaluation of Candidate Genes Identifies Associations between VEGF Polymorphisms and Bladder Cancer Risk
Common genetic variation could alter the risk for developing bladder cancer. We conducted a large-scale evaluation of single nucleotide polymorphisms (SNPs) in candidate genes for cancer to identify common variants that influence bladder cancer risk. An Illumina GoldenGate assay was used to genotype 1,433 SNPs within or near 386 genes in 1,086 cases and 1,033 controls in Spain. The most significant finding was in the 5′ UTR of VEGF (rs25648, p for likelihood ratio test, 2 degrees of freedom = 1 × 10(−5)). To further investigate the region, we analyzed 29 additional SNPs in VEGF, selected to saturate the promoter and 5′ UTR and to tag common genetic variation in this gene. Three additional SNPs in the promoter region (rs833052, rs1109324, and rs1547651) were associated with increased risk for bladder cancer: odds ratio (95% confidence interval): 2.52 (1.06–5.97), 2.74 (1.26–5.98), and 3.02 (1.36–6.63), respectively; and a polymorphism in intron 2 (rs3024994) was associated with reduced risk: 0.65 (0.46–0.91). Two of the promoter SNPs and the intron 2 SNP showed linkage disequilibrium with rs25648. Haplotype analyses revealed three blocks of linkage disequilibrium with significant associations for two blocks including the promoter and 5′ UTR (global p = 0.02 and 0.009, respectively). These findings are biologically plausible since VEGF is critical in angiogenesis, which is important for tumor growth, its elevated expression in bladder tumors correlates with tumor progression, and specific 5′ UTR haplotypes have been shown to influence promoter activity. Associations between bladder cancer risk and other genes in this report were not robust based on false discovery rate calculations. In conclusion, this large-scale evaluation of candidate cancer genes has identified common genetic variants in the regulatory regions of VEGF that could be associated with bladder cancer risk
A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.
We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis
Patient survival and tumor characteristics associated with CHEK2:p.I157T – findings from the Breast Cancer Association Consortium
Abstract
Background
P.I157T is a CHEK2 missense mutation associated with a modest increase in breast cancer risk. Previously, another CHEK2 mutation, the protein truncating c.1100delC has been associated with poor prognosis of breast cancer patients. Here, we have investigated patient survival and characteristics of breast tumors of germ line p.I157T carriers.
Methods
We included in the analyses 26,801 European female breast cancer patients from 15 studies participating in the Breast Cancer Association Consortium. We analyzed the association between p.I157T and the clinico-pathological breast cancer characteristics by comparing the p.I157T carrier tumors to non-carrier and c.1100delC carrier tumors. Similarly, we investigated the p.I157T associated risk of early death, breast cancer-associated death, distant metastasis, locoregional relapse and second breast cancer using Cox proportional hazards models.
Additionally, we explored the p.I157T-associated genomic gene expression profile using data from breast tumors of 183 Finnish female breast cancer patients (ten p.I157T carriers) (GEO: GSE24450). Differential gene expression analysis was performed using a moderated t test. Functional enrichment was investigated using the DAVID functional annotation tool and gene set enrichment analysis (GSEA). The tumors were classified into molecular subtypes according to the St Gallen 2013 criteria and the PAM50 gene expression signature.
Results
P.I157T was not associated with increased risk of early death, breast cancer-associated death or distant metastasis relapse, and there was a significant difference in prognosis associated with the two CHEK2 mutations, p.I157T and c.1100delC. Furthermore, p.I157T was associated with lobular histological type and clinico-pathological markers of good prognosis, such as ER and PR expression, low TP53 expression and low grade. Gene expression analysis suggested luminal A to be the most common subtype for p.I157T carriers and CDH1 (cadherin 1) target genes to be significantly enriched among genes, whose expression differed between p.I157T and non-carrier tumors.
Conclusions
Our analyses suggest that there are fundamental differences in breast tumors of CHEK2:p.I157T and c.1100delC carriers. The poor prognosis associated with c.1100delC cannot be generalized to other CHEK2 mutations
BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers
Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers.
Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided.
Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed.
Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations
Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.
Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition
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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.
Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis
Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk
The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We
performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988
controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate
logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two
more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold
LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches
explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with
bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the
total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed.
The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the
effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was
detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer
risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.The work was partially supported by the Fondo de Investigacion Sanitaria, Instituto de Salud Carlos III (G03/174, 00/0745, PI051436, PI061614, PI09-02102, G03/174 and Sara Borrell fellowship to ELM) and Ministry of Science and Innovation (MTM2008-06747-C02-02 and FPU fellowship award to VU), Spain; AGAUR-Generalitat de Catalunya (Grant 2009SGR-581); Fundaciola Maratode TV3; Red Tematica de Investigacion Cooperativa en Cancer (RTICC); Asociacion Espanola Contra el Cancer (AECC); EU-FP7-201663; and RO1-CA089715 and CA34627; the Spanish National Institute for Bioinformatics (www.inab.org); and by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, USA. MD Anderson support for this project included U01 CA 127615 (XW); R01 CA 74880 (XW); P50 CA 91846 (XW, CPD); Betty B. Marcus Chair fund in Cancer Prevention (XW); UT Research Trust fund (XW) and R01 CA 131335 (JG)
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