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Methods: eccDNA was sequenced and annotated using Circle_seq, intersected with TCGA overexpression genes, and assessed via univariate Cox regression. LASSO and Cox models built a prognostic signature, evaluated by ROC, nomogram, risk stratification, and ssGSEA immune infiltration. Results: A 9-gene eccDNA signature distinguished high- vs low-risk cohorts.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/a-novel-extrachromosomal-circular-dna-related-genes-signature-for-overall-survival-prediction-in-patients-with-ovarian-cancer/405798/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/a-novel-extrachromosomal-circular-dna-related-genes-signature-for-overall-survival-prediction-in-patients-with-ovarian-cancer/405798.png","ImageObject",300,407,{"name":42,"@type":43},"Connor ","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-28",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",9,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What was the main objective of this study on ovarian cancer?","Question",{"text":63,"@type":64},"To analyze eccDNA in the UACC-1598–4 cell line and determine how eccDNA-related genes are associated with ovarian cancer prognosis.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How were eccDNA-related genes selected for the prognostic model?",{"text":68,"@type":64},"Annotated eccDNA genes from UACC-1598–4 were intersected with TCGA ovarian cancer overexpression genes, then genes linked to prognosis were identified using univariate Cox regression.",{"name":70,"@type":61,"acceptedAnswer":71},"What genes and model characteristics were reported in the results?",{"text":72,"@type":64},"The study built a prognostic model based on a 9-gene signature, discriminating high- and low-risk individuals across TCGA training and ICGC validation cohorts, with immune infiltration differences and an ROC AUC reported as 0.67.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},405798,1790816516,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,115,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":108,"slug":109},7,40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},8,"Research & Report",30,"research-report",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145,"preview_page_count":4},687207022233,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Zhang et al. BMC Medical Genomics (2023) 16:140 [https://doi.org/10.1186/s12920-023-01576-x](https://doi.org/10.1186/s12920-023-01576-x)  \nBMC Medical Genomics  \n RESEARCH Open Access  \nA novel extrachromosomal circular DNA   related genes signature for overall survival prediction in patients with ovarian cancer  \nYing Zhang1,2†, Kexian Dong1,2†, Xueyuan Jia1,2†, Shuomeng Du1,2, Dong Wang3, Liqiang Wang1,2, Han Qu1,2, Shihao Zhu1,2, Yang Wang1,2, Zhao Wang4, Shuopeng Zhang1,2, Wenjing Sun1,2 and Songbin Fu 1,2*  \nAbstract  \nObjective Ovarian cancer (OV) has a high mortality rate all over the world, and extrachromosomal circular DNA (eccDNA) plays a key role in carcinogenesis. We wish to study more about the molecular structure of eccDNA in the UACC-1598–4 cell line and how its genes are associated with ovarian cancer prognosis.  \nMethods We sequenced and annotated the eccDNA by Circle_seq of the OV cell line UACC-1598–4 . To acquire the amplified genes of OV on eccDNA, the annotated eccDNA genes were intersected with the overexpression genes of OV in TCGA. Univariate Cox regression was used to find the genes on eccDNA that were linked to OV prognosis. The least absolute shrinkage and selection operator (LASSO) and cox regression models were used to create the OV prognostic model, as well as the receiver operating characteristic curve (ROC) curve and nomogram of the prediction model. By applying the median value of the risk score, the samples were separated into high-risk and low-risk groups, and the differences in immune infiltration between the two groups were examined using ssGSEA.  \nResults EccDNA in UACC-1598–4 has a length of 0-2000 bp, and some of them include the whole genes or gene fragments. These eccDNA originated from various parts of chromosomes, especially enriched in repeatmasker, introns, and coding regions. They were annotated with 2188 genes by Circle_seq. Notably, theTCGA database revealed that a total of 198 of these eccDNA genes were overexpressed in OV (p \u003C 0. 05) . They were mostly enriched in pathways associated with cell adhesion, ECM receptors, and actin cytoskeleton. Univariate Cox analysis showed 13 genes associated with OV prognosis. LASSO and Cox regression analysis were used to create a risk model based on remained 9 genes. In both the training (TCGA database) and validation (International Cancer Genome Consortium, ICGC) cohorts, a 9-gene signature could successfully discriminate high-risk individuals (all p \u003C 0. 01) . Immune infiltration differed significantly between the high-risk and low-risk groups. The model’s area under the ROC curve was 0 . 67, and a nomograph was created to assist clinician.  \nConclusion EccDNA is found in UACC-1598–4, and part of its genes linked to OV prognosis. Patients with OV maybe efficiently evaluated using a prognostic model based on eccDNA genes, including SLC7A1, NTN1, ADORA1, PADI2, SULT2B1, LINC00665, CILP2, EFNA5, TOMM.  \nKeywords Ovarian cancer, eccDNA, TCGA, Prognostic model, Immune infiltration  \n†Ying Zhang, Kexian Dong and Xueyuan Jia contributed equally to this work.  \n*Correspondence: Songbin Fu [fusb@ems.hrbmu.edu.cn](fusb@ems.hrbmu.edu.cn)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permissio","cbCaidhfx7Vx2dp7","https://ap.wps.com/l/cbCaidhfx7Vx2dp7","pdf",6208361,15,"English","# Abstract\n## Objective\n## Methods\n## Results\n## Conclusion\n# Introduction","[{\"question\":\"What was the main objective of this study on ovarian cancer?\",\"answer\":\"To analyze eccDNA in the UACC-1598–4 cell line and determine how eccDNA-related genes are associated with ovarian cancer prognosis.\"},{\"question\":\"How were eccDNA-related genes selected for the prognostic model?\",\"answer\":\"Annotated eccDNA genes from UACC-1598–4 were intersected with TCGA ovarian cancer overexpression genes, then genes linked to prognosis were identified using univariate Cox regression.\"},{\"question\":\"What genes and model characteristics were reported in the results?\",\"answer\":\"The study built a prognostic model based on a 9-gene signature, discriminating high- and low-risk individuals across TCGA training and ICGC validation cohorts, with immune infiltration differences and an ROC AUC reported as 0.67.\"}]","A novel extrachromosomal circular DNA related genes signature for overall survival prediction in patients with ovarian cancer | PDF",1790561876,38]