[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-351685-105":59,"doc-detail-351685-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","identification-and-comprehensive-analysis-of-gene-characteristics-related-to-chromatin-remodeling-in-thyroid-cancer-patients","Identification and Comprehensive Analysis of Gene Characteristics Related to Chromatin Remodeling in Thyroid Cancer Patients","","Thyroid cancer (THCA) is a leading endocrine malignancy worldwide, yet its etiology and mechanisms remain incompletely defined. This observational study used THCA-related datasets and chromatin remodeling genes to screen candidate biomarkers through differential expression, two machine-learning approaches, and receiver operating characteristic evaluation. Prognostic relevance was assessed by Kaplan–Meier survival analysis, followed by weighted gene co-expression network analysis to define biomarker-associated key genes. Immune infiltration differences were characterized between THCA and controls, with biomarker expression validated in clinical samples by RT-qPCR. Five biomarkers were identified.",{"@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/identification-and-comprehensive-analysis-of-gene-characteristics-related-to-chromatin-remodeling-in-thyroid-cancer-patients/351685/",{"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/identification-and-comprehensive-analysis-of-gene-characteristics-related-to-chromatin-remodeling-in-thyroid-cancer-patients/351685.png","ImageObject",300,407,{"name":92,"@type":93},"Adam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What was the main goal of the study in thyroid cancer patients?","Question",{"text":112,"@type":113},"To identify biomarkers associated with chromatin remodeling in thyroid cancer patients using integrated bioinformatics and machine-learning analyses, then evaluate prognostic value and validate expression experimentally.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were candidate biomarkers selected and validated?",{"text":117,"@type":113},"Differential expression analysis and two machine learning algorithms were used to identify candidate genes, then ROC curve analysis selected biomarkers. Clinical samples were used to validate biomarker expression using reverse transcription quantitative polymerase chain reaction (RT-qPCR).",{"name":119,"@type":110,"acceptedAnswer":120},"Which biomarkers were found to be most associated with chromatin remodeling in THCA, and how did they relate to prognosis?",{"text":121,"@type":113},"Five biomarkers—CHD4, SMARCA2, CHD3, ATAD2, and SMARCA4—were screened. Kaplan–Meier analysis indicated higher expression of SMARCA4, CHD4, and ATAD2 corresponded to higher survival, while lower expression of CHD3 and SMARCA2 corresponded to worse survival.","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},351685,1790193594,{"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":8,"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},1374404737137,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","®  \n Observational Study   \nIdentification and comprehensive analysis of gene characteristics related to chromatin remodeling in thyroid cancer patients  \nShigui Wang, MDa , Shuangshuang Sun, MDb , Xiangzhong Wang, MDa , Xiang Chen, BDa ,*  \n\n| Abstract\u003Cbr>Thyroid cancer (THCA) is the 9th most common endocrine tumor worldwide. However, its etiology and pathogenesis are not fully understood. Therefore, this study aimed to identify the biomarkers associated with chromatin remodeling in patients with THCA. THCA-related datasets and chromatin remodeling related genes were included in this study. Differential expression analysis and 2 machine learning algorithms were employed to identify candidate genes. Biomarkers were identified by receiver operating characteristic curve analysis. The prognostic potential of the biomarkers was explored using Kaplan–Meier (KM) survival analysis. Key genes linked to biomarkers were identified using weighted gene co-expression network analysis. Immune infiltration analysis was performed to explore differences in immune infiltration between THCA and control groups. Finally, the expression for biomarker was validated in clinical samples using reverse transcription quantitative polymerase chain reaction. Five biomarkers (CHD4, SMARCA2, CHD3, ATAD2, and SMARCA4) were screened. KM survival analysis revealed that patients with higher expression of SMARCA4, CHD4, and ATAD2 had a higher survival rate, whereas in the lower expression groups of CHD3 and SMARCA2, the survival rate of THCA patients was lower. A total of 98 genes related to biomarkers were identified using weighted gene co-expression network analysis. In addition, a total of 20 immune cells infiltrated differentially in THCA and controls, with the largest positive correlation between immature dendritic cells and ATAD2, with a correlation coefficient of 0.54, and a large positive correlation between CD56dim natural killer cells and SMARCA4, which was 0.5. Reverse transcription quantitative polymerase chain reaction revealed that the expression of biomarkers was consistent with the results of the bioinformatics analysis. In summary, SMARCA4, CHD4, and ATAD2 were overexpressed, whereas CHD3 and SMARCA2 were downregulated in THCA samples. This study identified 5 biomarkers (CHD4, SMARCA2, CHD3, ATAD2, and SMARCA4) associated with chromatin remodeling in THCA. Current reference points for the prevention and treatment. |\n| --- |\n| Abbreviations: AUC = area under curve, CRRGs = chromatin remodeling related genes, CT = cycle threshold , DEGs = differentially expressed genes, KEGG = Kyoto encyclopedia of genes and genomes, KM = Kaplan–Meier, PTC = papillary thyroid carcinoma, SVM-RFE = Support vector machine-recursive feature elimination, SWI/SNF = SWItch/sucrose nonfermentable, TCGA = The Cancer Genome Atlas, THCA = thyroid cancer, TRβ = thyroid receptor beta, WGCNA = weighted gene co-expression network analysis. |\n| Keywords: bioinformatics, biomarkers, chromatin remodeling, thyroid cancer |\n\n1. Introduction  \nThyroid cancer (THCA) is the most common endocrine tumor and the 9th most common cancer worldwide. The incidence of common tumors has steadily increased over the past few decades. [1] With the incidence of THCA, its treatment of THCAis becoming increasingly standardized. Although most cases of early-stage thyroid carcinoma (THCA) can be cured by conventional treatments, including surgical resection, radioactive  \nSWand SS contributed to this article equally.  \nThe authors have no funding and conflicts of interest to disclose. The datasets generated during and/or analyzed during the current study are publicly available.  \nThis study was approved in accordance with the Ethical Standards of the Institutional Ethics Committee of Jurong Hospital Affiliated to Jiangsu University, and the ethics approval number is JRH-IEC-2024018. All patients’ written informed consent was obtained.  \na Department of General Surgery, Jurong Hospital Affiliated to Jiangs","cbCailHpM5bvoenr","https://ap.wps.com/l/cbCailHpM5bvoenr","pdf",2744900,11,"English","# Abstract\n# Introduction","[{\"question\":\"What was the main goal of the study in thyroid cancer patients?\",\"answer\":\"To identify biomarkers associated with chromatin remodeling in thyroid cancer patients using integrated bioinformatics and machine-learning analyses, then evaluate prognostic value and validate expression experimentally.\"},{\"question\":\"How were candidate biomarkers selected and validated?\",\"answer\":\"Differential expression analysis and two machine learning algorithms were used to identify candidate genes, then ROC curve analysis selected biomarkers. Clinical samples were used to validate biomarker expression using reverse transcription quantitative polymerase chain reaction (RT-qPCR).\"},{\"question\":\"Which biomarkers were found to be most associated with chromatin remodeling in THCA, and how did they relate to prognosis?\",\"answer\":\"Five biomarkers—CHD4, SMARCA2, CHD3, ATAD2, and SMARCA4—were screened. Kaplan–Meier analysis indicated higher expression of SMARCA4, CHD4, and ATAD2 corresponded to higher survival, while lower expression of CHD3 and SMARCA2 corresponded to worse survival.\"}]","Identification and Comprehensive Analysis of Gene Characteristics Related to Chromatin Remodeling in Thyroid Cancer Patients | PDF",1790095310,28]