[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-358916-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-358916-en":131},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","prognostic-stratification-in-hepatocellular-carcinoma-using-a-telomerase-related-lncrna-signature-derived-from-tcga-database","Prognostic stratification in hepatocellular carcinoma using a telomerase-related lncRNA signature derived from TCGA database","","Hepatocellular carcinoma is marked by high recurrence and restricted treatment options, with limited understanding of how telomerase-related long non-coding RNAs shape prognosis and immune behavior. Using TCGA transcriptomic data, a telomerase-related lncRNA prognostic signature was constructed with LASSO-Cox regression and validated using time-dependent ROC analysis. Clinical utility was examined via nomogram calibration and decision-curve analysis, alongside tumor microenvironment assessment through immune profiling, TMB, drug sensitivity, and TIDE scores, with RT-qPCR validation in a pilot cohort.",{"@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/prognostic-stratification-in-hepatocellular-carcinoma-using-a-telomerase-related-lncrna-signature-derived-from-tcga-database/358916/",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/prognostic-stratification-in-hepatocellular-carcinoma-using-a-telomerase-related-lncrna-signature-derived-from-tcga-database/358916.png","ImageObject",300,407,{"name":42,"@type":43},"Riley","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-27","2026-09-23",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",14,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What clinical problem does the study address in hepatocellular carcinoma?","Question",{"text":63,"@type":64},"It addresses the high recurrence and poor outcomes of hepatocellular carcinoma, where therapeutic options remain limited and prognostic mechanisms are not well clarified, especially regarding telomerase-related lncRNAs.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How was the prognostic signature constructed and validated?",{"text":68,"@type":64},"The signature was built from TCGA transcriptomic data using LASSO-Cox regression, then validated with time-dependent ROC curves. Clinical utility was assessed using nomogram calibration and decision-curve analysis.",{"name":70,"@type":61,"acceptedAnswer":71},"How does the high-risk group differ in tumor immune features and immunotherapy-related scores?",{"text":72,"@type":64},"High-risk patients show increased immune cell presence, higher checkpoint expression, and elevated TIDE scores, suggesting a potential tendency toward poorer responses to immunotherapy.","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},358916,1790464108,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,115,120,123,127],{"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":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":145,"read_time":146},1374391975076,"https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051","OPEN ACCESS  \nCitation: Yang R, Xing L, Wang C, Zhang Y, Xie S, Yuan J (2026) Prognostic stratification in hepatocellular carcinoma using a telomeraserelated lncRNA signature derived from TCGA database. PLoS One 21(3): e0339415. [https://](https://)[ ](https://)[doi.org/10.1371/journal.pone.0339415](doi.org/10.1371/journal.pone.0339415)  \nEditor: Zhanzhan Li, Xiangya Hospital Central South University, CHINA  \nReceived: October 21, 2025  \nAccepted: December 4, 2025  \nPublished: March 6, 2026  \nPeer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0339415  \nCopyright: © 2026 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution,  \nRESEARCH ARTICLE  \nPrognostic stratification in hepatocellular carcinoma using a telomerase-related lncRNA signature derived from TCGA database  \nRunze Yang1, Luchao Xing1, Chenghao Wang1, Yunhao Zhang2, Songzhuang Xie2, Jianlei Yuan2*  \n1 Department of Graduate School, Chengde Medical University, Chengde, Hebei, China, 2 Department of Hepatobiliary and Pancreatic Surgery, Cangzhou People's Hospital, Cangzhou, Hebei, China  \n* [18103276691@163.com](18103276691@163.com)  \nAbstract  \nBackground  \nCharacterized by high recurrence rates and limited therapeutic options, hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. Notwithstanding the fact that telomerase-related long non-coding RNAs (TRLs) have been implicated in tumorigenesis, it remains poorly understood about their prognostic and immunological roles in HCC.  \nMethods  \nFor the purpose of identifying telomerase-related genes (TRGs) and TRLs, we used transcriptomic data from The Cancer Genome Atlas (TCGA) . We built a prognostic signature using LASSO-Cox regression. Then, we validated it with time-dependent ROC curves. We assessed the model's clinical utility with nomogram calibration and DCA. We also evaluated immune profiling, tumor mutation burden, drug sensitivity and TIDE scores to characterize the tumor microenvironment. Using a pilot cohort of clinical samples, initial experimental validation was completed with RT-qPCR.  \nResults  \nBy using a 4-TRLs signature, HCC patients can be divided into Low-risk (L-R) and High-risk (H-R) groups. The signature acted as an independent prognostic factor. It provided a highly accurate prediction of patient survival at 1, 3, and 5 years (AUC:  \n0.744–0.770) . H-R patients had more immune cells in their tumors. They also showed higher levels of checkpoint expression. Besides, their TIDE (tumor immune dysfunction and exclusion) scores were also higher. All these things mean they might not respond well to immunotherapy. Subtype-specific therapeutic vulnerabilities can be read from drug sensitivity analysis. By carrying out reverse transcription quantitative  \nPLOS One | [https://doi.org/10.1371/journal.pone.0339415](https://doi.org/10.1371/journal.pone.0339415) March 6, 2026 1 / 33  \nand reproduction in any medium, provided the original author and source are credited.  \nData availability statement: All relevant data are within the paper and its Supporting  Information files. The public data analyzed in this study are available from the TCGA database and GEO database (accession number GSE242889) . The data underlying this study have been uploaded to Zenodo and are accessible using the following: [https://doi](https://doi). org/10 .5281/zenodo.17752944.  \nFunding: The author(s) received no specific funding for this work.  \nCompeting interests: The authors have declared that no competing interests exist.  \npolymerase chain reaction (RT-qPCR), consistent dysregulation patterns ","cbCaijo0SzovLDyv","https://ap.wps.com/l/cbCaijo0SzovLDyv","pdf",8736976,33,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusion\n# Introduction","[{\"question\":\"What clinical problem does the study address in hepatocellular carcinoma?\",\"answer\":\"It addresses the high recurrence and poor outcomes of hepatocellular carcinoma, where therapeutic options remain limited and prognostic mechanisms are not well clarified, especially regarding telomerase-related lncRNAs.\"},{\"question\":\"How was the prognostic signature constructed and validated?\",\"answer\":\"The signature was built from TCGA transcriptomic data using LASSO-Cox regression, then validated with time-dependent ROC curves. Clinical utility was assessed using nomogram calibration and decision-curve analysis.\"},{\"question\":\"How does the high-risk group differ in tumor immune features and immunotherapy-related scores?\",\"answer\":\"High-risk patients show increased immune cell presence, higher checkpoint expression, and elevated TIDE scores, suggesting a potential tendency toward poorer responses to immunotherapy.\"}]","Prognostic stratification in hepatocellular carcinoma using a telomerase-related lncRNA signature derived from TCGA database | PDF",1790135631,83]