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Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC

OBJECTIVES: The exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustaine...

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Autores principales: Shi, Jihang, Li, Guangya, Liu, Lulu, Yuan, Xiandun, Wang, Yafei, Gong, Ming, Li, Chonghui, Ge, Xinlan, Lu, Shichun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106715/
https://www.ncbi.nlm.nih.gov/pubmed/37077914
http://dx.doi.org/10.3389/fimmu.2023.1166052
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author Shi, Jihang
Li, Guangya
Liu, Lulu
Yuan, Xiandun
Wang, Yafei
Gong, Ming
Li, Chonghui
Ge, Xinlan
Lu, Shichun
author_facet Shi, Jihang
Li, Guangya
Liu, Lulu
Yuan, Xiandun
Wang, Yafei
Gong, Ming
Li, Chonghui
Ge, Xinlan
Lu, Shichun
author_sort Shi, Jihang
collection PubMed
description OBJECTIVES: The exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustained high expression of inhibitory receptors including PD-1, TIGIT, TIM-3, and LAG-3, and always accompanied by metabolic and epigenetic reprogramming. Tex cells are getting more and more attention in researching immune-related diseases and tumor immunotherapy. However, studies on Tex-related models for tumor prognosis are still lacking. We hope to establish a risk model based on Tex-related genes for HCC prognosis. METHODS: Tex-related GEO datasets from different pathologic factors (chronic HBV, chronic HCV, and telomere shortening) were analyzed respectively to acquire differentially expressed genes (DEGs) by the ‘limma’ package of R. Genes with at least one intersection were incorporated into Tex-related gene set. GO, KEGG, and GSEA enrichment analyses were produced. Hub genes and the PPI network were established and visualized by the STRING website and Cytoscape software. Transcription factors and targeting small molecules were predicted by the TRUST and CLUE websites. The Tex-related HCC prognostic model was built by Cox regression and verified based on different datasets. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms tested immunotherapy sensitivity. Finally, qRT-PCR and Flow Cytometry was used to confirm the bioinformatic results. RESULTS: Hub genes such as AKT1, CDC6, TNF and their upstream transcription factor ILF3, Regulatory factor X-associated protein, STAT3, JUN, and RELA/NFKB1 were identified as potential motivators for Tex. Tex-related genes SLC16A11, CACYBP, HSF2, and ATG10 built the HCC prognostic model and helped with Immunotherapy sensitivity prediction. CONCLUSION: Our study demonstrated that Tex-related genes might provide accurate prediction for HCC patients in clinical decision-making, prognostic assessment, and immunotherapy. In addition, targeting the hub genes or transcription factors may help to reverse T cell function and enhance the effect of tumor immunotherapy.
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spelling pubmed-101067152023-04-18 Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC Shi, Jihang Li, Guangya Liu, Lulu Yuan, Xiandun Wang, Yafei Gong, Ming Li, Chonghui Ge, Xinlan Lu, Shichun Front Immunol Immunology OBJECTIVES: The exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustained high expression of inhibitory receptors including PD-1, TIGIT, TIM-3, and LAG-3, and always accompanied by metabolic and epigenetic reprogramming. Tex cells are getting more and more attention in researching immune-related diseases and tumor immunotherapy. However, studies on Tex-related models for tumor prognosis are still lacking. We hope to establish a risk model based on Tex-related genes for HCC prognosis. METHODS: Tex-related GEO datasets from different pathologic factors (chronic HBV, chronic HCV, and telomere shortening) were analyzed respectively to acquire differentially expressed genes (DEGs) by the ‘limma’ package of R. Genes with at least one intersection were incorporated into Tex-related gene set. GO, KEGG, and GSEA enrichment analyses were produced. Hub genes and the PPI network were established and visualized by the STRING website and Cytoscape software. Transcription factors and targeting small molecules were predicted by the TRUST and CLUE websites. The Tex-related HCC prognostic model was built by Cox regression and verified based on different datasets. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms tested immunotherapy sensitivity. Finally, qRT-PCR and Flow Cytometry was used to confirm the bioinformatic results. RESULTS: Hub genes such as AKT1, CDC6, TNF and their upstream transcription factor ILF3, Regulatory factor X-associated protein, STAT3, JUN, and RELA/NFKB1 were identified as potential motivators for Tex. Tex-related genes SLC16A11, CACYBP, HSF2, and ATG10 built the HCC prognostic model and helped with Immunotherapy sensitivity prediction. CONCLUSION: Our study demonstrated that Tex-related genes might provide accurate prediction for HCC patients in clinical decision-making, prognostic assessment, and immunotherapy. In addition, targeting the hub genes or transcription factors may help to reverse T cell function and enhance the effect of tumor immunotherapy. Frontiers Media S.A. 2023-04-03 /pmc/articles/PMC10106715/ /pubmed/37077914 http://dx.doi.org/10.3389/fimmu.2023.1166052 Text en Copyright © 2023 Shi, Li, Liu, Yuan, Wang, Gong, Li, Ge and Lu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Shi, Jihang
Li, Guangya
Liu, Lulu
Yuan, Xiandun
Wang, Yafei
Gong, Ming
Li, Chonghui
Ge, Xinlan
Lu, Shichun
Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title_full Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title_fullStr Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title_full_unstemmed Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title_short Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC
title_sort establishment and validation of exhausted cd8+ t cell feature as a prognostic model of hcc
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106715/
https://www.ncbi.nlm.nih.gov/pubmed/37077914
http://dx.doi.org/10.3389/fimmu.2023.1166052
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