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A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma

BACKGROUND: Exosomes play an important role in the tumor microenvironment (TME) and the mechanisms of tumor immune escape in hepatocellular carcinoma (HCC). It is known that immunosuppressive genes, involved in the processes of tumor immunosuppression, are associated with cancer progression. This st...

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Autores principales: Yang, Zhan, Li, Xinmiao, Pan, Chaoran, Li, Yifei, Lin, Lifan, Jin, Yan, Zheng, Jianjian, Yu, Zhengping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773453/
https://www.ncbi.nlm.nih.gov/pubmed/36550445
http://dx.doi.org/10.1186/s12885-022-10463-0
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author Yang, Zhan
Li, Xinmiao
Pan, Chaoran
Li, Yifei
Lin, Lifan
Jin, Yan
Zheng, Jianjian
Yu, Zhengping
author_facet Yang, Zhan
Li, Xinmiao
Pan, Chaoran
Li, Yifei
Lin, Lifan
Jin, Yan
Zheng, Jianjian
Yu, Zhengping
author_sort Yang, Zhan
collection PubMed
description BACKGROUND: Exosomes play an important role in the tumor microenvironment (TME) and the mechanisms of tumor immune escape in hepatocellular carcinoma (HCC). It is known that immunosuppressive genes, involved in the processes of tumor immunosuppression, are associated with cancer progression. This study aimed to explore the prognostic values of exosome-related immunosuppression genes (ERIGs) in HCC. METHODS: The RNA-seq transcriptome data of 374 HCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The TCGA cohort was randomly divided into the training cohort and validation cohort in a 1:1 ratio. WGCNA analysis and Pearson correlation analysis were used to identify ERIGs. The Lasso regression method was used to construct a 5-ERIG signature. The prognostic value of our signature was examined in the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort. RESULTS: Univariate Cox regression analysis was used to screen prognostic ERIGs. Subsequently, these prognostic ERIGs were included in Lasso regression analyses to identify 5 key ERIGs (ASAP1, IARS1, GTF3C2, TPD5L2 and SLC52A2) and construct a 5-ERIG signature. The patients in the low-risk group had better prognosis than those in the high-risk group. Univariate and multivariate cox regression revealed that risk score was an independent prognostic risk factor of HCC. Gene set enrichment analysis (GSEA) showed that this signature was highly associated with TME-related pathways. Subsequent analyses revealed the potential role of the signature in regulating the TME in HCC. In addition, a lower immunotherapy score was found in patients with high risk-score. Of note, this signature was confirmed to have a good performance in predicting HCC prognosis in the FAHWMU cohort. Moreover, knockdown of 5 ERIGs of this signature contributed to the suppression the Hep3B cell proliferation. CONCLUSIONS: We generated a novel prognostic 5-ERIG signature to accurately predict the prognosis of patients with HCC, and this signature may serve as an indicator of immunotherapy for HCC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10463-0.
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spelling pubmed-97734532022-12-23 A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma Yang, Zhan Li, Xinmiao Pan, Chaoran Li, Yifei Lin, Lifan Jin, Yan Zheng, Jianjian Yu, Zhengping BMC Cancer Research BACKGROUND: Exosomes play an important role in the tumor microenvironment (TME) and the mechanisms of tumor immune escape in hepatocellular carcinoma (HCC). It is known that immunosuppressive genes, involved in the processes of tumor immunosuppression, are associated with cancer progression. This study aimed to explore the prognostic values of exosome-related immunosuppression genes (ERIGs) in HCC. METHODS: The RNA-seq transcriptome data of 374 HCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The TCGA cohort was randomly divided into the training cohort and validation cohort in a 1:1 ratio. WGCNA analysis and Pearson correlation analysis were used to identify ERIGs. The Lasso regression method was used to construct a 5-ERIG signature. The prognostic value of our signature was examined in the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort. RESULTS: Univariate Cox regression analysis was used to screen prognostic ERIGs. Subsequently, these prognostic ERIGs were included in Lasso regression analyses to identify 5 key ERIGs (ASAP1, IARS1, GTF3C2, TPD5L2 and SLC52A2) and construct a 5-ERIG signature. The patients in the low-risk group had better prognosis than those in the high-risk group. Univariate and multivariate cox regression revealed that risk score was an independent prognostic risk factor of HCC. Gene set enrichment analysis (GSEA) showed that this signature was highly associated with TME-related pathways. Subsequent analyses revealed the potential role of the signature in regulating the TME in HCC. In addition, a lower immunotherapy score was found in patients with high risk-score. Of note, this signature was confirmed to have a good performance in predicting HCC prognosis in the FAHWMU cohort. Moreover, knockdown of 5 ERIGs of this signature contributed to the suppression the Hep3B cell proliferation. CONCLUSIONS: We generated a novel prognostic 5-ERIG signature to accurately predict the prognosis of patients with HCC, and this signature may serve as an indicator of immunotherapy for HCC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10463-0. BioMed Central 2022-12-22 /pmc/articles/PMC9773453/ /pubmed/36550445 http://dx.doi.org/10.1186/s12885-022-10463-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yang, Zhan
Li, Xinmiao
Pan, Chaoran
Li, Yifei
Lin, Lifan
Jin, Yan
Zheng, Jianjian
Yu, Zhengping
A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title_full A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title_fullStr A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title_full_unstemmed A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title_short A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
title_sort comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773453/
https://www.ncbi.nlm.nih.gov/pubmed/36550445
http://dx.doi.org/10.1186/s12885-022-10463-0
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