Dataset Information

T lymphocytes in hepatocellular carcinoma immune microenvironment: insights into human immunology and immunotherapy.

ABSTRACT: Hepatocellular carcinoma (HCC) is characterized by poor outcome and shows limited drug-response in clinical trials. Tumor immune microenvironment (TIME) exerts a strong selection pressure on HCC, leading to HCC evolvement and recurrence after multiple therapies. T cell-mediated immunoreaction during cancer surveillance and clearance is central in cancer immunity. Heterogenous T cell subsets play multiple roles in HCC development and progression. The re-educated T cells in TIME usually lead to deteriorated T cell response and tumor progression. Investigation into immune system dysregulation during HCC development will shed light on how to turn immune suppressive state to immune activation and induce more efficient immune response. Emerging T cell-based treatment such as cancer vaccines, CAR-T cell therapy, adoptive cell therapy, and immune checkpoint inhibitors (ICIs), have been proved to cause tumor regression in some clinical and preclinical trials. In this review, we focused on recent studies that explored T cells involved in HCC and how they affect the course of disease. We also briefly outlined current T cell-based immunotherapies in HCC.

SUBMITTER: Bian J

PROVIDER: S-EPMC7783774 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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T lymphocytes in hepatocellular carcinoma immune microenvironment: insights into human immunology and immunotherapy.

Bian Jin J Lin Jianzhen J Long Junyu J Yang Xu X Yang Xiaobo X Lu Xin X Sang Xinting X Zhao Haitao H

American journal of cancer research 20201201 12

Hepatocellular carcinoma (HCC) is characterized by poor outcome and shows limited drug-response in clinical trials. Tumor immune microenvironment (TIME) exerts a strong selection pressure on HCC, leading to HCC evolvement and recurrence after multiple therapies. T cell-mediated immunoreaction during cancer surveillance and clearance is central in cancer immunity. Heterogenous T cell subsets play multiple roles in HCC development and progression. The re-educated T cells in TIME usually lead to de ...[more]

PMID: 33415021

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Project description:Introduction: Tremendous evidence indicates that N6-methyladenosine (m6A) epigenetic modification and m6A-related enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of the m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive. Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value was compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Four independent algorithms (ssGSEA, xCell, MCP-counter, and TIMER) were used to calculate the ratio of tumor cells and non-tumor cells to evaluate the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs was performed using TIDE and SubMap. Results: A total of 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. The m6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways, and immune cell infiltration abundance under distinct m6A patterns. As expected, the m6A gene cluster confirmed the aforementioned results. The m6Ascore model further found that patients in the high-m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, upregulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low-m6Ascore patients were associated with adverse outcomes. Notably, low-m6Ascore patients might be more sensitive to anti-PD-L1 therapy. Conclusion: This study found that a classification model based on the m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision-making.

Dataset Information

T lymphocytes in hepatocellular carcinoma immune microenvironment: insights into human immunology and immunotherapy.

Publications

T lymphocytes in hepatocellular carcinoma immune microenvironment: insights into human immunology and immunotherapy.

Similar Datasets

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