AUTHOR=Hong Wei-feng , Liu Mou-yuan , Liang Li , Zhang Yang , Li Zong-juan , Han Keqi , Du Shi-suo , Chen Yan-jie , Ma Li-heng 

TITLE=Molecular Characteristics of T Cell-Mediated Tumor Killing in Hepatocellular Carcinoma

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.868480

DOI=10.3389/fimmu.2022.868480

ISSN=1664-3224

ABSTRACT=Background: Although checkpoint blockade is a promising approach for the treatment of hepatocellular carcinoma (HCC), patient subsets expected to show a response are not clearly established. T cell-mediated tumor killing (TTK) is the fundamental principle of immune checkpoint inhibitor therapy; accordingly, we established subtypes based on genes related to sensitivity to TKK and evaluated their prognostic value in setting of immunotherapies. Methods: Genes regulating the sensitivity of tumor cells to T cell-mediated killing (referred to as GSTTKs) showing differential expression in HCC and correlations with prognosis were identified by high-throughput screening assays. Unsupervised clustering was applied to patients with HCC to reveal subtypes based on GSTTKs. The tumor microenvironment, metabolic properties, and genetic variation were compared among subgroups. An algorithm based prognostic GSTTKs, referred to as the TCscore, was developed; its clinical and predictive value for the response to immunotherapy were evaluated. Results: In total, 18 of 641 GSTTKs simultaneously showed differential expression and were correlated with prognosis in HCC. Patients were clustered into two subgroups based on the 18 GSTTKs, reflecting distinct TTK patterns in HCC. Tumor infiltrating-immune cells, immune-related gene expression, glycolipid metabolism, somatic mutations, and signaling pathways differed between the two subgroups. The TCscore effectively distinguished between populations with different responses to chemotherapeutics or immunotherapy and overall survival. Conclusions: TTK subtypes in HCC differ with respect to the tumor microenvironment, metabolic patterns, mutations, and signaling pathways. Accordingly, this clustering strategy can be used to predict the efficacy of checkpoint inhibitors and survival outcomes and reflects differences in the functionality of T cells in HCC.