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Enhancer landscapes from normal ovary and subtype-specific disease states are profiled using publicly available data, with an H3K27ac-focused computational pipeline that predicts drug compound activity via epigenomic stratification. Recurrent enhancer patterns and differential transcription-factor enrichment are identified, highlighting SNS-032 and EHMT2-related inhibitors BIX-01294 and UNC0646 as candidate therapies.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/in-silico-enhancer-mining-reveals-sns-032-and-ehmt2-inhibitors-as-therapeutic-candidates-in-high-grade-serous-ovarian-cancer/376953/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/in-silico-enhancer-mining-reveals-sns-032-and-ehmt2-inhibitors-as-therapeutic-candidates-in-high-grade-serous-ovarian-cancer/376953.png","ImageObject",300,407,{"name":92,"@type":93},"\tCallum ","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-01","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main goal of the study?","Question",{"text":112,"@type":113},"To exploit ovarian cancer epigenomic enhancer landscapes to identify therapeutic candidates and improve drug discovery strategies for high-grade serous ovarian cancer.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What data and computational focus are used in the methods?",{"text":117,"@type":113},"The study interrogates enhancer landscapes of normal ovary and ovarian cancer subtypes using publicly available data, initially focusing on the H3K27ac histone mark and building a computational pipeline to predict drug activity.",{"name":119,"@type":110,"acceptedAnswer":120},"Which inhibitors are highlighted as therapeutic candidates?",{"text":121,"@type":113},"SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 are identified as therapeutic candidates in high-grade serous carcinoma, with additional in vitro probing of inhibitor efficacy.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},376953,1790852893,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":41},137451211410,"https://ap-avatar.wpscdn.com/avatar/2000bb0a9246f588df?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786362646172706240","British Journal of Cancer [www.nature.com/bjc](www.nature.com/bjc)  \nARTICLE OPEN   \nTranslational Therapeutics  \nIn silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer  \nMarcos Quintela 1,6, David W. James1,6, Jetzabel Garcia1, Kadie Edwards 1, Lavinia Margarit1,2, Nagindra Das3, Kerryn Lutchman-Singh3, Amy L. Beynon4, Inmaculada Rioja5, Rab K. Prinjha5, Nicola R. Harker5, Deyarina Gonzalez 1, R. Steven Conlan 1 and Lewis W. Francis 1 ✉  \n© The Author(s) 2023  \n\n|  | BACKGROUND: Epigenomic dysregulation has been linked to solid tumour malignancies, including ovarian cancers. Profiling of reprogrammed enhancer locations associated with disease has the potential to improve stratification and thus therapeutic choices. Ovarian cancers are subdivided into histological subtypes that have significant molecular and clinical differences, with high-grade serous carcinoma representing the most common and aggressive subtype.\u003Cbr>METHODS: We interrogated the enhancer landscape(s) of normal ovary and subtype-specific ovarian cancer states using publicly available data. With an initial focus on H3K27ac histone mark, we developed a computational pipeline to predict drug compound activity based on epigenomic stratification. Lastly, we substantiated our predictions in vitro using patient-derived clinical samples and cell lines.\u003Cbr>RESULTS: Using our in silico approach, we highlighted recurrent and privative enhancer landscapes and identified the differential enrichment of a total of 164 transcription factors involved in 201 protein complexes across the subtypes. We pinpointed SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 as therapeutic candidates in high-grade serous carcinoma, as well as probed the efficacy of specific inhibitors in vitro.\u003Cbr>CONCLUSION: Here, we report the first attempt to exploit ovarian cancer epigenomic landscapes for drug discovery This |  |\n| --- | --- | --- |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n| .\u003Cbr>computational pipeline holds enormous potential for translating epigenomic profiling into therapeutic leads. |  |  |\n|  | British Journal of Cancer (2023) 129:163–174; [https://doi.org/10.1038/s41416-023-02274-2](https://doi.org/10.1038/s41416-023-02274-2) |  |\n|  |  |  |\n\nINTRODUCTION  \nThe last decades have witnessed a significant increase in functional genomic approaches, high-throughput data availability and innovative computational methodologies [1] . Thriving in this data-intensive environment, in silico strategies have been widely used for drug development, discovery and repositioning [2] . Insilico approaches take advantage of vast genomic datasets tostratify patients into distinguishable molecular sub-groups, enabling the delivery of more accurate personalised care to patients [3, 4] . To date, this field has largely been driven by genomics, whereas now there is a surge in the exploitation of epigenomics, which offers a more dynamic view of disease, and therefore personalised treatment options [5, 6] .  \nIn contrast to genomics, epigenomics encompasses a set of covalent modifications that occur at chromatin level with no alteration to the underlying DNA sequence [7] . Different patterns of epigenetic alterations have fundamental effects on cancer progression, providing cancer cells with a degree of plasticity that allows them to adapt to their environment [8] . The precise temporal and spatial epigenomic regulation of gene transcription  \nis orchestrated by cis-acting regulatory elements that include promoter regions surrounding the transcriptional start site of genes, and enhancers, generally located many kilobases away from the gene body [9] . Active enhancers are highlighted by acetylated histone 3 at lysine 27 (H3K27ac), an epigenetic mark commonly associated with open chromatin regions [10] . Enhancers play a central role in regulating transcription wher","cbCaiexqZiFPYn7X","https://ap.wps.com/l/cbCaiexqZiFPYn7X","pdf",2426767,12,"English","# Background\n# Methods\n# Results\n# Conclusion\n# Introduction","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To exploit ovarian cancer epigenomic enhancer landscapes to identify therapeutic candidates and improve drug discovery strategies for high-grade serous ovarian cancer.\"},{\"question\":\"What data and computational focus are used in the methods?\",\"answer\":\"The study interrogates enhancer landscapes of normal ovary and ovarian cancer subtypes using publicly available data, initially focusing on the H3K27ac histone mark and building a computational pipeline to predict drug activity.\"},{\"question\":\"Which inhibitors are highlighted as therapeutic candidates?\",\"answer\":\"SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 are identified as therapeutic candidates in high-grade serous carcinoma, with additional in vitro probing of inhibitor efficacy.\"}]","In silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer | PDF",1790222309]