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This study analyzes RNA sequencing, mutation, and clinical data from TCGA-LIHC, ICGC-LIRI, and GEO to discover tumor antigens and build immunophenotypes and immune landscapes. Weighted correlation network analysis identifies gene modules linked to mRNA vaccine efficacy. Six candidate antigen targets are validated, and immunophenotypes reveal likely patient subgroups and determinants of responsiveness.",{"@graph":69,"@context":127},[70,84,106],{"@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/preparation-of-hepatocellular-carcinoma-mrna-vaccines-based-on-potential-tumor-targets-and-immunophenotypes/331880/",{"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/preparation-of-hepatocellular-carcinoma-mrna-vaccines-based-on-potential-tumor-targets-and-immunophenotypes/331880.png","ImageObject",300,407,{"name":92,"@type":93},"Patrick","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119,123],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main purpose of this study on HCC mRNA vaccines?","Question",{"text":113,"@type":114},"To discover and validate effective tumor antigens for developing mRNA vaccines for hepatocellular carcinoma, and to construct immunophenotypes and immune landscapes that identify potential beneficiaries.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which datasets and tools are used to derive candidate tumor targets?",{"text":118,"@type":114},"RNA sequencing, mutation, and clinical information are collected from TCGA-LIHC, ICGC-LIRI, and GEO, and multiple analysis resources (e.g., GEPIA2.0, cBioPortal, TIMER2.0, and IHC) are used to discover tumor antigens.",{"name":120,"@type":111,"acceptedAnswer":121},"What antigen targets are reported as potential candidates for HCC mRNA vaccines?",{"text":122,"@type":114},"Six antigen targets are identified in the TCGA cohort: AURKA, CDC25C, KPNA2, MCM3, NEK2, and TUBG1, associated with antigen-presenting cell infiltration and poor prognosis.",{"name":124,"@type":111,"acceptedAnswer":125},"How do immunophenotypes and immune gene modules relate to vaccine responsiveness?",{"text":126,"@type":114},"Five immunophenotypes are consistent across cohorts, and increased expression of blue and black immune gene modules may reduce mRNA vaccine responsiveness, helping stratify potential beneficiaries.","https://schema.org",{"og:url":83,"og:type":129,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":131,"canonical":83},"index,follow",{"doc_id":133,"site_id":62},331880,1790193075,{"code":4,"msg":5,"data":136},{"doc_id":133,"user_id":137,"nickname":92,"user_avatar":138,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":139,"file_id":140,"file_url":141,"file_type":142,"file_size":143,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":144,"language":145,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":146,"faqs":147,"seo_title":148,"seo_description":67,"update_tm":149,"read_time":150,"preview_page_count":4},549758146520,"https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470","Preparation of hepatocellular carcinoma mRNA vaccines based on potential tumor targets and immunophenotypes  \nHai-Kuo Wang1\\#, Xuan-Hao Xu2\\#, Si-Ming Wang1, He-Yun Zhang1  \n1Department of Hepatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; 2Department of Cardiology, the Eighth Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China  \nContributions: (I) Conception and design: HK Wang, XH Xu; (II) Administrative support: HY Zhang; (III) Provision of study materials or patients: HK Wang, SM Wang, HY Zhang; (IV) Collection and assembly of data: HK Wang; (V) Data analysis and interpretation: HK Wang, XH Xu; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.  \n\\#These authors contributed equally to this work.  \nCorrespondence to: He-Yun Zhang, MD. Department of Hepatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107  \nYanjiang West Road, Yuexiu District, Guangzhou 510000, China. Email: [zhysums@163.com](zhysums@163.com).  \nBackground: With the development of messenger RNA (mRNA)-based therapeutics for malignant tumor, mRNA vaccines have shown considerable promise for tumor immunotherapy. Immunophenotypes can reflect the tumor microenvironment, which might have a significant influence on the effect of immunotherapy. This study seeks to discover and validate effective antigens that can be employed to develop mRNA vaccines for hepatocellular carcinoma (HCC) and to construct immunophenotypes and immune landscapes to identify  \npotential beneficiaries.  \nMethods: RNA sequencing (RNASeq) data, mutation information, and clinical information were obtained from HCC patients and control cases from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), International Cancer Genome Consortium-Liver Cancer (ICGC-LIRI) and Gene Expression Omnibus (GEO) cohorts. Gene Expression Profiling Interactive Analysis (GEPIA2.0), cBioPortal for Cancer Genomics (cBioPortal), Tumor IMmune Estimation Resource (TIMER2.0), and immunohistochemistry (IHC) were employed to discover tumor antigens. ConsensusClusterPlus was employed to perform consistency matrix building and immunophenotypic clustering. Single sample gene set enrichment analysis (ssGSEA), ESTIMATE and monocle2 were employed to map immune cell distribution.  \nWeighted correlation network analysis (WGCNA) was employed to identify potential gene modules that  \ninfluence the efficacy of mRNA vaccines.  \nResults: Six antigen targets were discovered in the TCGA cohort, including AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1, which were associated with antigen-presenting cell infiltration and poor prognosis. IHC scores ofAURKA, CDC25C and MCM3 were higher in tumor tissues, and high scores of AURKA and CDC25C indicated poor prognosis in the validation cohort. Five immunophenotypes derived from TCGA-LIHC and ICGC-LIRI cohorts were consistent. Furthermore, increased expression of blue and  \nblack modules may reduce vaccine responsiveness.  \nConclusions: AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1 may be potential targets formRNA vaccine development for HCC, especially AURKA and CDC25C. HCC patients with IS1 and IS5 subtypes perhaps present an autoimmunosuppressed state, then IS2 and IS3 subtypes perhaps the potential  \nbeneficiaries.  \nKeywords: mRNA vaccine; hepatocellular carcinoma (HCC); immunophenotype; tumor antigens  \nSubmitted Jul 16, 2023. Accepted for publication Nov 08, 2023. Published online Jan 23, 2024.  \ndoi: 10.21037/tcr-23-1237  \nView this article at: [https://dx.doi.org/10.21037/tcr-23-1237](https://dx.doi.org/10.21037/tcr-23-1237)  \n© Translational Cancer Research. All rights reserved. Transl Cancer Res 2024;13(1):173-190 | [https://dx.doi.org/10.21037/tcr-23-1237](https://dx.doi.org/10.21037/tcr-23-1237)  \n174 Wang et al. Research on mRNA vaccines for HCC  \nIntroduction  \nHepatocellular carcinoma (HCC) is the fourth most frequent cause of cance","cbCaioVa6ED4at8X","https://ap.wps.com/l/cbCaioVa6ED4at8X","pdf",6643945,18,"English","# Introduction\n## Tumor immunotherapy and mRNA vaccines for HCC\n# Methods\n## Data sources and antigen discovery\n## Immunophenotypic clustering and immune cell mapping\n## Gene module identification and vaccine efficacy modeling\n# Results\n## Candidate antigen targets and clinical associations\n## Immunophenotype consistency across cohorts\n## Immune gene modules and vaccine responsiveness\n# Conclusions","[{\"question\":\"What is the main purpose of this study on HCC mRNA vaccines?\",\"answer\":\"To discover and validate effective tumor antigens for developing mRNA vaccines for hepatocellular carcinoma, and to construct immunophenotypes and immune landscapes that identify potential beneficiaries.\"},{\"question\":\"Which datasets and tools are used to derive candidate tumor targets?\",\"answer\":\"RNA sequencing, mutation, and clinical information are collected from TCGA-LIHC, ICGC-LIRI, and GEO, and multiple analysis resources (e.g., GEPIA2.0, cBioPortal, TIMER2.0, and IHC) are used to discover tumor antigens.\"},{\"question\":\"What antigen targets are reported as potential candidates for HCC mRNA vaccines?\",\"answer\":\"Six antigen targets are identified in the TCGA cohort: AURKA, CDC25C, KPNA2, MCM3, NEK2, and TUBG1, associated with antigen-presenting cell infiltration and poor prognosis.\"},{\"question\":\"How do immunophenotypes and immune gene modules relate to vaccine responsiveness?\",\"answer\":\"Five immunophenotypes are consistent across cohorts, and increased expression of blue and black immune gene modules may reduce mRNA vaccine responsiveness, helping stratify potential beneficiaries.\"}]","Preparation of hepatocellular carcinoma mRNA vaccines based on potential tumor targets and immunophenotypes | PDF",1789995611,45]