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Updated: Sep 7, 2025

A Biomimetic Model for Liver Cancer to Study Tumor-Stroma Interactions in a 3D Environment with Tunable Bio-Physical Properties
Published on: August 7, 2020
A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy
Jingsheng Liao1,2, Qi Liu1,2, Jingtang Chen1,2
1Department of Medical Oncology, Affiliated Dongguan Hospital, Southern Medical University, 78 Wandao Road, Dongguan City, 523000, Guangdong Province, China.
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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