Wang Hai-Kuo, Xu Xuan-Hao, Wang Si-Ming, Zhang He-Yun
Department of Hepatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Department of Cardiology, the Eighth Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China.
Transl Cancer Res. 2024 Jan 31;13(1):173-190. doi: 10.21037/tcr-23-1237. Epub 2024 Jan 23.
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 potential beneficiaries.
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. Weighted correlation network analysis (WGCNA) was employed to identify potential gene modules that influence the efficacy of mRNA vaccines.
Six antigen targets were discovered in the TCGA cohort, including and , which were associated with antigen-presenting cell infiltration and poor prognosis. IHC scores of and were higher in tumor tissues, and high scores of 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 black modules may reduce vaccine responsiveness.
and may be potential targets for mRNA vaccine development for HCC, especially and . HCC patients with IS1 and IS5 subtypes perhaps present an autoimmunosuppressed state, then IS2 and IS3 subtypes perhaps the potential beneficiaries.
随着基于信使核糖核酸（mRNA）的恶性肿瘤治疗方法的发展，mRNA疫苗在肿瘤免疫治疗中显示出了巨大的潜力。免疫表型可以反映肿瘤微环境，这可能对免疫治疗的效果产生重大影响。本研究旨在发现和验证可用于开发肝细胞癌（HCC）mRNA疫苗的有效抗原，并构建免疫表型和免疫图谱以识别潜在的受益人群。
从癌症基因组图谱-肝细胞癌（TCGA-LIHC）、国际癌症基因组联盟-肝癌（ICGC-LIRI）和基因表达综合数据库（GEO）队列中的HCC患者及对照病例获取RNA测序（RNASeq）数据、突变信息和临床信息。利用基因表达谱交互分析（GEPIA2.0）、癌症基因组学cbioportal数据库（cBioPortal）、肿瘤免疫估计资源（TIMER2.0）和免疫组织化学（IHC）来发现肿瘤抗原。使用ConsensusClusterPlus进行一致性矩阵构建和免疫表型聚类。采用单样本基因集富集分析（ssGSEA）、ESTIMATE和monocle2来绘制免疫细胞分布图。利用加权基因共表达网络分析（WGCNA）来识别影响mRNA疫苗疗效的潜在基因模块。
在TCGA队列中发现了6个抗原靶点，包括[具体抗原名称1]和[具体抗原名称2]，它们与抗原呈递细胞浸润及预后不良相关。在肿瘤组织中，[具体抗原名称1]和[具体抗原名称2]的IHC评分较高，在验证队列中，[具体抗原名称1]的高分表明预后不良。源自TCGA-LIHC和ICGC-LIRI队列的5种免疫表型是一致的。此外，蓝色和黑色模块表达的增加可能会降低疫苗反应性。
[具体抗原名称1]和[具体抗原名称2]可能是HCC mRNA疫苗开发的潜在靶点，尤其是[具体抗原名称1]和[具体抗原名称2]。IS1和IS5亚型的HCC患者可能呈现自身免疫抑制状态，那么IS2和IS3亚型可能是潜在的受益人群。
