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A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma

BACKGROUND: Transforming growth factor-beta (TGF-β) signal is an important pathway involved in all stages of liver hepatocellular carcinoma (LIHC) initiation and progression. Therefore, targeting TGF- β pathway may be a potential therapeutic strategy for LIHC. Prediction of patients’ tumor cells res...

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Autores principales: Liao, Jingsheng, Liu, Qi, Chen, Jingtang, Lu, Zhibin, Mo, Huiting, Jia, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9215003/
https://www.ncbi.nlm.nih.gov/pubmed/35733217
http://dx.doi.org/10.1186/s12953-022-00192-4
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author Liao, Jingsheng
Liu, Qi
Chen, Jingtang
Lu, Zhibin
Mo, Huiting
Jia, Jun
author_facet Liao, Jingsheng
Liu, Qi
Chen, Jingtang
Lu, Zhibin
Mo, Huiting
Jia, Jun
author_sort Liao, Jingsheng
collection PubMed
description BACKGROUND: Transforming growth factor-beta (TGF-β) signal is an important pathway involved in all stages of liver hepatocellular carcinoma (LIHC) initiation and progression. Therefore, targeting TGF- β pathway may be a potential therapeutic strategy for LIHC. Prediction of patients’ tumor cells response requires effective biomarkers. METHODS: From 54 TGF-β-related genes, this research determined the genes showing the greatest relation to LIHC prognosis, and developed a risk score model with 8 TGF-β-related genes. The model divided LIHC patients from different datasets and platforms into low- and high-risk groups. Multivariate Cox regression analysis confirmed that the model was an independent prognostic factor for LIHC. The differences in genetic mutation, immune cell infiltration, biological pathway, response to immunotherapy or chemotherapy, and tumor microenvironment in LIHC samples showing different risks were analyzed. RESULTS: Compared with low-risk group, in the training set and test set, high-risk group showed shorter survival, lower stromal score and higher M0 macrophages scores, regulatory T cells (Tregs), helper follicular T cells. Moreover, high-risk samples showed higher sensitivity to cisplatin, imatinib, sorafenib and salubrinal and pyrimethamine. High-risk group demonstrated a significantly higher Tumor Immune Dysfunction and Exclusion (TIDE) score, but would significantly benefit less from taking immunotherapy and was less likely to respond to immune checkpoint inhibitors. CONCLUSIONS: In general, this work provided a risk scoring model based on 8 TGF-β pathway-related genes, which might be a new potential tool for predicting LIHC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12953-022-00192-4.
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spelling pubmed-92150032022-06-23 A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma Liao, Jingsheng Liu, Qi Chen, Jingtang Lu, Zhibin Mo, Huiting Jia, Jun Proteome Sci Research BACKGROUND: Transforming growth factor-beta (TGF-β) signal is an important pathway involved in all stages of liver hepatocellular carcinoma (LIHC) initiation and progression. Therefore, targeting TGF- β pathway may be a potential therapeutic strategy for LIHC. Prediction of patients’ tumor cells response requires effective biomarkers. METHODS: From 54 TGF-β-related genes, this research determined the genes showing the greatest relation to LIHC prognosis, and developed a risk score model with 8 TGF-β-related genes. The model divided LIHC patients from different datasets and platforms into low- and high-risk groups. Multivariate Cox regression analysis confirmed that the model was an independent prognostic factor for LIHC. The differences in genetic mutation, immune cell infiltration, biological pathway, response to immunotherapy or chemotherapy, and tumor microenvironment in LIHC samples showing different risks were analyzed. RESULTS: Compared with low-risk group, in the training set and test set, high-risk group showed shorter survival, lower stromal score and higher M0 macrophages scores, regulatory T cells (Tregs), helper follicular T cells. Moreover, high-risk samples showed higher sensitivity to cisplatin, imatinib, sorafenib and salubrinal and pyrimethamine. High-risk group demonstrated a significantly higher Tumor Immune Dysfunction and Exclusion (TIDE) score, but would significantly benefit less from taking immunotherapy and was less likely to respond to immune checkpoint inhibitors. CONCLUSIONS: In general, this work provided a risk scoring model based on 8 TGF-β pathway-related genes, which might be a new potential tool for predicting LIHC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12953-022-00192-4. BioMed Central 2022-06-22 /pmc/articles/PMC9215003/ /pubmed/35733217 http://dx.doi.org/10.1186/s12953-022-00192-4 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
Liao, Jingsheng
Liu, Qi
Chen, Jingtang
Lu, Zhibin
Mo, Huiting
Jia, Jun
A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title_full A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title_fullStr A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title_full_unstemmed A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title_short A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
title_sort risk score model based on tgf-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9215003/
https://www.ncbi.nlm.nih.gov/pubmed/35733217
http://dx.doi.org/10.1186/s12953-022-00192-4
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