EXPERIMENT_TITLE: GSM5847961: HECT_OVCAR3_3; Homo sapiens; Hi-C
EXPERIMENT_DESIGN_LIBRARY_DESCRIPTOR_LIBRARY_CONSTRUCTION_PROTOC: In situ Hi-C was performed as previously described (Rao et al. 2014); see assocaited paper by Kelly et al. for more detail (methods section)
STUDY_DESCRIPTOR_STUDY_ABSTRACT: Ovarian cancer is one of the deadliest cancers among women worldwide and is the leading cause of gynecologic-related cancer deaths in the U.S. Enhancers are often repurposed by the tumor cells for the regulation of genes that allow tumor cells to become more aggressive and resistant to therapy. Recent evidence suggests that exploiting transcriptional dependence by targeting oncogenic super-enhancers may be a viable therapeutic avenue. To this end, we leveraged genomic data such as H3K27ac, BRD4, and copy number information to identify putatively oncogenic super-enhancers. We found that copy number amplification of these super-enhancers is predictive of clinical outcome and that the targets genes associated to the copy number events via chromatin eQTL analysis are involved in numerous oncogenic processes. To systematically probe the functions these super-enhancers we designed a CRISPR interference screen (dCas9-KRAB) so specifically inhibit each super-enhancer and measure the consequences on gene expression via RNA-seq. These results show pervasive gene expression changes that underlie the biology of ovarian cancer. Finally, we select two salient super-enhancers for further analysis. CRISPR-based deletion of these two super-enhancers results in in dramatic changes in gene expression and decreased cell proliferation of ovarian cancer cells. Taken together these analyses highlight the importance of BRD4-bound and copy number amplified super-enhancers in ovarian cancer oncogenic regulation. Overall design: In this study, two super-enhancers were identified as being oncogenic in ovarian cancer. We wanted to determine if the DEGs detected from DESeq2 and the results of our biological assays were due to direct or indirect effects. Therefore, we performed Hi-C Seq to investigate interaction frequencies across the OVCAR3 genome.
SAMPLE_TITLE: HECT_OVCAR3_3
SAMPLE_SAMPLE_ATTRIBUTES_SAMPLE_ATTRIBUTE: [{"TAG": "source_name", "VALUE": "OVCAR 3 Cell Line"}, {"TAG": "cell line", "VALUE": "OVCAR 3"}, {"TAG": "genotype", "VALUE": "Wild Type"}, {"TAG": "replicate", "VALUE": "Replicate 3"}]
Pool_Member_@attributes_sample_title: HECT_OVCAR3_3
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