Immune cell infiltration and immunotherapy in hepatocellular carcinoma
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Published:2022
Issue:7
Volume:19
Page:7178-7200
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ISSN:1551-0018
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Container-title:Mathematical Biosciences and Engineering
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language:
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Short-container-title:MBE
Author:
Jiang Yu,Lin Lijuan,Lv Huiming,Zhang He,Jiang Lili,Ma Fenfen,Wang Qiuyue,Ma Xue,Yu Shengjin
Abstract
<abstract><p>Hepatocellular carcinoma is a highly malignant tumor and patients yield limited benefits from the existing treatments. The application of immune checkpoint inhibitors is promising but the results described in the literature are not favorable. It is therefore urgent to systematically analyze the immune microenvironment of HCC and screen the population best suited for the application of immune checkpoint inhibitors to provide a basis for clinical treatment. In this study, we collected The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC)-related data sets to evaluate the immune microenvironment and immune cell infiltration (ICI) in HCC. Three independent ICI subtypes showing significant differences in survival were identified. Further, TCGA-LIHC immunophenoscore (IPS) was used to identify the differentially expressed genes between high- and low-IPS in HCC, so as to identify the immune gene subtypes in HCC tumors. The ICI score model for HCC was constructed, whereby we divided HCC samples into high- and low-score groups based on the median ICI score. The differences between these groups in genomic mutation load and immunotherapy benefit in HCC were examined in detail to provide theoretical support for accurate immunotherapy strategy in HCC. Finally, four genes were screened, which could accurately predict the subtype based on the tumor immune infiltration score. The findings may provide a basis and simplify the process for screening clinical drugs suitable for relevant subgroups.</p></abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine
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