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  • American Association for Cancer Research (AACR)  (3)
  • Chang-Claude, Jenny  (3)
  • 2015-2019  (3)
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Publisher
  • American Association for Cancer Research (AACR)  (3)
Person/Organisation
Language
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  • 2015-2019  (3)
Year
Subjects(RVK)
  • 1
    Online Resource
    Online Resource
    A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk
    American Association for Cancer Research (AACR) ; 2018
    In:  Cancer Research Vol. 78, No. 18 ( 2018-09-15), p. 5419-5430
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 18 ( 2018-09-15), p. 5419-5430
    Abstract: 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 cis-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 P & lt; 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, 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 (P & lt; 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/0008-5472.CAN-18-0951
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 3 ( 2019-02-01), p. 505-517
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 3 ( 2019-02-01), p. 505-517
    Abstract: 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 × 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.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/0008-5472.CAN-18-2726
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 17 ( 2016-09-01), p. 5103-5114
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 17 ( 2016-09-01), p. 5103-5114
    Abstract: Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/0008-5472.CAN-15-2980
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
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