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

Abstract 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 c...

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Main Authors: Jingsheng Liao, Qi Liu, Jingtang Chen, Zhibin Lu, Huiting Mo, Jun Jia
Format: Article
Language:English
Published: BMC 2022-06-01
Series:Proteome Science
Subjects:
Online Access:https://doi.org/10.1186/s12953-022-00192-4
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author Jingsheng Liao
Qi Liu
Jingtang Chen
Zhibin Lu
Huiting Mo
Jun Jia
author_facet Jingsheng Liao
Qi Liu
Jingtang Chen
Zhibin Lu
Huiting Mo
Jun Jia
author_sort Jingsheng Liao
collection DOAJ
description Abstract 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.
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spelling doaj.art-9f2ba313f7174a29a7b3928ec6fc710a2022-12-22T00:19:49ZengBMCProteome Science1477-59562022-06-0120111310.1186/s12953-022-00192-4A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinomaJingsheng Liao0Qi Liu1Jingtang Chen2Zhibin Lu3Huiting Mo4Jun Jia5Department of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityDepartment of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityDepartment of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityDepartment of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityDepartment of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityDepartment of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical UniversityAbstract 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.https://doi.org/10.1186/s12953-022-00192-4TGF-β signaling pathwayLiver hepatocellular carcinomaTumor microenvironmentPrognosis, immunotherapy
spellingShingle Jingsheng Liao
Qi Liu
Jingtang Chen
Zhibin Lu
Huiting Mo
Jun Jia
A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma
Proteome Science
TGF-β signaling pathway
Liver hepatocellular carcinoma
Tumor microenvironment
Prognosis, immunotherapy
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 TGF-β signaling pathway
Liver hepatocellular carcinoma
Tumor microenvironment
Prognosis, immunotherapy
url https://doi.org/10.1186/s12953-022-00192-4
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