Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE)
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA321449 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE)
| PRJNA321450 | ENA
Project description:Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) - Meta-Analysis
| PRJNA314164 | ENA
Project description:Susceptibility loci for IgA nephropathy
| PRJNA80299 | ENA
Project description:Fine Mapping of Eight Psoriasis Susceptibility Loci
| PRJNA375837 | ENA
Project description:Elucidating the oncogenic role of Menin in prostate cancer progression
| PRJNA549240 | ENA
Project description:Analysis of chromatin looping identies gene promoters that interact with enhancers and HIF-binding sites at kidney cancer-associated susceptibility loci
2019-12-31 | GSE130988 | GEO
Project description:Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single nucleotide polymorphisms (SNPs) associated with cancer risk lie in non protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs), and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared to normal human mammary epithelial cells (HMECs) and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissues specific regulatory signatures to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P=3.8x10-30) OSECs (P=2.4x10-23) and HMECs (P=6.7x10-15) but not for EECs (P=0.45) or LNCaP cells (P=0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) indicating both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets germline genetic susceptibility variants for ovarian cancer FAIRE-Seq and ChIP-Seq of 2 different histone modifications in 5 cell types.
2015-04-22 | E-GEOD-68104 | biostudies-arrayexpress
Project description:Lupus susceptibility results from the combined effects of numerous genetic loci, but the contribution of these loci to disease pathogenesis has been difficult to study due to the large cellular heterogeneity of the autoimmune immune response. We performed single cell RNA, B cell receptor (BCR), and T cell receptor (TCR) sequencing of splenocytes from mice with multiple polymorphic lupus susceptibility loci. We not only observed lymphocyte and myeloid expansion, but also characterized changes in subset frequencies and gene expression, such as decreased CD8 and marginal zone B cells and increased Fcrl5 and Cd5l expressing macrophages. Clonotypic analyses revealed expansion of B and CD4 clones, and TCR repertoires from lupus prone mice were distinguishable by algorithmic specificity prediction and unsupervised machine learning classification. Myeloid differential gene expression, metabolism, and altered ligand-receptor interaction were associated with decreased antigen presentation. This dataset provides novel mechanistic insight into the pathophysiology of a spontaneous model of lupus, highlighting potential therapeutic targets for autoantibody mediated disease.
2022-03-14 | GSE192762 | GEO
Project description:Background: Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer. Results: We generated genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotated the regulatory potential of 2,181 fine-mapped PCa risk-associated SNPs and predicted a set of target genes that are regulated by PCa risk-related H3K27Ac-mediated loops. We next identified PCa risk-associated CTCF sites involved in long-range chromatin loops. We used CRISPR-mediated deletion to remove PCa risk-associated CTCF anchor regions and the CTCF anchor regions looped to the PCa risk-associated CTCF sites; we observed up to 100 fold increases in expression of genes within the loops when the PCa risk-associated CTCF anchor regions were deleted. Conclusions: We have identified GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer.
2018-08-15 | GSE118514 | GEO
Project description:In order to identify methylation changes in prostate cancer, we performed a genome-wide analysis of DNA methylation using Agilent human CpG island arrays. We then chose specific genes to validate methylation both in the same cases as were hybridized to the array (using quantitative EpiTYPER analysis) and in an independent series of prostate cancer samples (using MethyLight quantitative methylation specific PCR). We specifically chose low grade (Gleason score 6 cases) and high grade (Gleason score 8 cases) to discover methylated genes/loci that may be involved in the progression to a higher grade of prostate cancer.
2009-03-27 | GSE15298 | GEO