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Träfflista för sökning "WFRF:(Huntsman David G.) "

Sökning: WFRF:(Huntsman David G.)

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1.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (<em>r</em><em>g</em> = 0.57, <em>p</em> = 4.6 × 10−8), breast and ovarian cancer (<em>r</em><em>g</em> = 0.24, <em>p</em> = 7 × 10−5), breast and lung cancer (<em>r</em><em>g</em> = 0.18, <em>p </em>=1.5 × 10−6) and breast and colorectal cancer (<em>r</em><em>g</em> = 0.15, <em>p</em> = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.</p>
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2.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.</p>
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3.
  • Phelan, Catherine M, et al. (författare)
  • Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.
  • 2017
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 49:5, s. 680-691
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.</p>
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4.
  • Siddiq, Afshan, et al. (författare)
  • A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11
  • 2012
  • Ingår i: Human Molecular Genetics. - 0964-6906 .- 1460-2083. ; 21:24, s. 5373-5384
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P 1 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR 1.16; P 1.1 10(8)) but showed a weaker association with overall breast cancer (OR 1.08, P 1.3 10(6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR 1.01, P 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR 1.12; P 1.1 10(9)), and with both ER-positive (OR 1.09; P 1.5 10(5)) and ER-negative (OR 1.16, P 2.5 10(7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.</p>
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5.
  • Yang, Yaohua, et al. (författare)
  • Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk
  • 2019
  • Ingår i: Cancer Research. - AMER ASSOC CANCER RESEARCH. - 0008-5472 .- 1538-7445. ; 79:3, s. 505-517
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P &lt; 7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.</p>
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6.
  • Lu, Yingchang, et al. (författare)
  • A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
  • 2018
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 78:18, s. 5419-5430
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>.</p><h2>Abstract</h2><p>Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their <em>cis</em>-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of <em>P</em> &lt; 2.2 × 10<sup>−6</sup>, we identified 35 genes, including <em>FZD4</em> at 11q14.2 (Z = 5.08, <em>P</em> = 3.83 × 10<sup>−7</sup>, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (<em>P</em> &lt; 1.47 × 10<sup>−3</sup>). These data identify one novel locus <em>(FZD4</em>) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.</p><p><strong>Significance:</strong> Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. <em>Cancer Res; 78(18); 5419–30. ©2018 AACR</em>.</p>
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