[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-450376-105":59,"doc-detail-450376-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","construction-and-validation-of-risk-models-of-prognostic-genes-associated-with-parthanatos-in-papillary-thyroid-carcinoma-based-on-bioinformatics","Construction and validation of risk models of prognostic genes associated with parthanatos in papillary thyroid carcinoma based on bioinformatics","","Study objectives focus on clarifying the role of parthanatos-related genes (PRGs) in papillary thyroid carcinoma and building a prognostic risk model to support personalized treatment decisions. Differentially expressed PRGs were identified from the GSE33630 dataset, followed by weighted gene co-expression network analysis (WGCNA) to define key module genes. Seven prognostic genes were selected for the regression-based model, which was validated and paired with a nomogram for survival prediction, including correlations with clinical features, immune infiltration, drug sensitivity, and GSEA, plus RT-qPCR experimental validation.",{"@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":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/construction-and-validation-of-risk-models-of-prognostic-genes-associated-with-parthanatos-in-papillary-thyroid-carcinoma-based-on-bioinformatics/450376/",{"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/construction-and-validation-of-risk-models-of-prognostic-genes-associated-with-parthanatos-in-papillary-thyroid-carcinoma-based-on-bioinformatics/450376.png","ImageObject",300,407,{"name":92,"@type":93},"\tJames","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-07","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main purpose of this study in papillary thyroid carcinoma?","Question",{"text":112,"@type":113},"To elucidate the role of parthanatos-related genes (PRGs) and construct a validated prognostic risk model that can guide personalized treatment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were prognostic genes selected for the risk model?",{"text":117,"@type":113},"Differentially expressed PRGs were identified using the GSE33630 dataset, key module genes were determined by WGCNA, and regression analysis selected seven prognostic genes for model construction.",{"name":119,"@type":110,"acceptedAnswer":120},"What evidence was used to validate the model and support survival prediction?",{"text":121,"@type":113},"The model’s predictive performance was validated, a nomogram was developed for survival prediction, and additional analyses included clinical feature correlations, immune infiltration, drug sensitivity screening, and GSEA, with experimental validation via RT-qPCR.","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},450376,1790947571,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"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":145},2336474466412,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Wang et al. Discover Oncology (2026) 17:32 [https://doi.org/10.1007/s12672-025-04202-7](https://doi.org/10.1007/s12672-025-04202-7)  \nDiscover Oncology  \nANALYSIS Open Access  \nConstruction and validation    \nof risk models of prognostic genes associated with parthanatos in papillary thyroid carcinoma based on bioinformatics  \nRui Wang 1,2, Li Zhang3 and Shuxin Wen 1,2*  \n*Correspondence: Shuxin Wen [wensxsx@163.com](wensxsx@163.com)  \n1Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan 030032, China  \n2Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology,  \nWuhan 430030, China 3Department of Head and Neck Surgery, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences (Cancer Hospital Affiliated to Shanxi Medical University), Taiyuan 030001, China  \nAbstract  \nObject This study aimed to elucidate the role of parthanatos-related genes (PRGs) in papillary thyroid carcinoma (PTC) and construct a prognostic risk model to guide personalized treatment.  \nMethods Using the GSE33630 dataset, differential ly expressed PRGs were identified and analyzed via weighted gene co-expression network analysis (WGCNA) to pinpoint key module genes. Regression analysis selected seven prognostic genes for risk model construction. The model’s performance was validated, and a nomogram was developed for survival prediction. Further analyses included clinical feature correlations, immune infiltration, drug sensitivity, gene set enrichment analysis (GSEA), and experimental validation via RT-qPCR.  \nResults Seven prognostic genes (TSHZ3, SERGEF, AKAP12, SGPP2, ASGR1, AK1, PELI2) were identified. The risk model demonstrated robust predictive accuracy, stratifying patients into high-and low-risk groups with significant survival differences. GSEA revealed 29 enriched pathways (e. g., ribosome, focal adhesion), while immune infiltration analysis highlighted CD56 + NK cells and AK1 as key immune correlates. Drug sensitivity screening identified 111 differential therapeutics. Functional analysis indicated AKAP12 had the strongest functional similarity among prognostic genes. Conclusion This study comprehensively mapped PRGs in PTC, established a validated risk model, and provided insights into immune-microenvironment interactions and therapeutic targets, advancing precision oncology for PTC.  \nKeywords Papillary thyroid carcinoma, Parthanatos, Prognostic gene, Risk model, Immune checkpoint inhibitors  \n1 Introduction  \nThyroid cancer is a malignant tumor originating from the follicular epithelium or parafollicular epithelial cells of the thyroid gland, and is the most common malignant tumor in the head and neck. In recent years, the incidence of thyroid cancer in the world has  \n© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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 permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/l](http://creativecommons.org/l)icenses/by-nc-nd/4.0/.  \nWang et al. Discover Oncology (2026) 17:32 Page 2 of 21  \nincreased rapidly, a","cbCaihkufIbSkspS","https://ap.wps.com/l/cbCaihkufIbSkspS","pdf",4927151,21,"English","# Abstract\n## Methods and validation\n## Results\n## Conclusion\n# Introduction","[{\"question\":\"What is the main purpose of this study in papillary thyroid carcinoma?\",\"answer\":\"To elucidate the role of parthanatos-related genes (PRGs) and construct a validated prognostic risk model that can guide personalized treatment.\"},{\"question\":\"How were prognostic genes selected for the risk model?\",\"answer\":\"Differentially expressed PRGs were identified using the GSE33630 dataset, key module genes were determined by WGCNA, and regression analysis selected seven prognostic genes for model construction.\"},{\"question\":\"What evidence was used to validate the model and support survival prediction?\",\"answer\":\"The model’s predictive performance was validated, a nomogram was developed for survival prediction, and additional analyses included clinical feature correlations, immune infiltration, drug sensitivity screening, and GSEA, with experimental validation via RT-qPCR.\"}]","Construction and validation of risk models of prognostic genes associated with parthanatos in papillary thyroid carcinoma based on bioinformatics | PDF",1790733015,53]