Identification of tumor antigens and anoikis-based molecular subtypes in the hepatocellular carcinoma immune microenvironment: implications for mRNA vaccine development and precision treatment

Journal of Big Data

Research

Zhiyuan Zheng¹  Zhiping Yan²  Xiaolin Wang²  Lingxiao Liu²  Feng Zhou³  Hantao Yang⁴  Yang Shi⁵ 

[1] Department of Interventional Radiology, Zhongshan Hospital Fudan University and Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, 200032, Shanghai, China;Faculty of Medicine, Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074, Aachen, Germany;National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, China;Department of Interventional Radiology, Zhongshan Hospital Fudan University and Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, 200032, Shanghai, China;National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, China;Department of Neurosurgery, Baoji Central Hospital, 8 Jiangtan Road, 721008, Baoji, Shaanxi Province, China;Department of Neurosurgery, Zhongshan Hospital Fudan University, 180 Fenglin Road, 200032, Shanghai, China;Faculty of Medicine, Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074, Aachen, Germany;

关键词: HCC;    Anoikis;    Prognosis;    Subtype;    TCGA;    GEO;    Machine learning;    Hepatocellular carcinoma;    Anoikis;    Tumor antigen;    mRNA vaccine;    Tumor immune microenvironment;   

DOI  :  10.1186/s40537-023-00803-7

 received in 2023-03-12, accepted in 2023-07-16,  发布年份 2023

来源: Springer

【 摘 要 】

Hepatocellular carcinoma (HCC) represents a formidable malignancy with a high lethality. Nonetheless, the development of vaccine and the establishment of prognostic models for precise and personalized treatment of HCC still encounter big challenges. Thus, the aim of this study was to develop HCC vaccines and explore anoikis-based prognostic models based on RNA sequencing data in GEO datasets (GSE10143, GSE76427) and the TCGA-LIHC cohort. Potential HCC antigens were identified using GEPIA2, cBioPortal, and TIMER2. Anoikis-related subtypes and gene clusters were defined by consensus clustering of 566 liver cancer samples based on 28 anoikis regulators, and we further analyzed their relationship with the immune microenvironment of HCC. A predictive model based on anoikis-related long noncoding RNAs (lncRNAs) was developed to accurately predict HCC prognosis. Seven overexpressed genes associated with HCC prognosis and tumor-infiltrating antigen-presenting cells were identified as potential tumor antigens for the development of HCC mRNA vaccines. Two subtypes based on anoikis-related genes (ARGs) and two gene clusters with different characteristics were identified and validated in defined cohorts. The tumor immune microenvironment between the two subtypes showed different cell infiltration and molecular characteristics. Furthermore, a prognostic score based on seven lncRNAs identified by LASSO regression was constructed, with the low-risk group having favorable prognosis, a “hot” immune microenvironment, and better response to immunotherapy. CCNB1, CDK1, DNASE1L3, KPNA2, PRC1, PTTG, and UBE2S were first identified as promising tumor antigens for mRNA vaccine development in HCC. Besides, we innovatively propose anoikis-based molecular subtypes, which not only enable personalized prognostic stratification of HCC patients but also provide a blueprint for identifying optimal candidates for tumor vaccines, enhancing immunotherapeutic strategies.

【 授权许可】

CC BY   
© Springer Nature Switzerland AG 2023

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