Machine learning model reveals roles of interferon‑stimulated genes in sorafenib‑resistant liver cancer
Deok Hwa Seo1, Ji Woo Park2, Hee Won Jung2
1Department of Biomedicine and Health Sciences, The Catholic University Liver Research Center, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Abstract:
HCC (Hepatocellular carcinoma) is the most common malignant tumor; however, the molecular pathogenesis of these tumors is not well understood. Sorafenib, an approved treatment for HCC, inhibits angiogenesis and tumor cell proliferation. However, only ~30% of patients are sensitive to sorafenib and most show disease progression, indicating resistance to sorafenib. The present study used machine learning to investigate several mechanisms related to sorafenib resistance in liver cancer cells. This revealed that unphosphorylated interferon-stimulated genes (U-ISGs) were upregulated in sorafenib-resistant liver cancer cells, and the unphosphorylated ISGF3 (U-ISGF3; unphosphorylated STAT1, unphosphorylated STAT2 and IRF9) complex was increased in sorafenib-resistant liver cancer cells. Further study revealed that the knockdown of the U-ISGF3 complex downregulated U-ISGs. In addition, inhibition of the U-ISGF3 complex downregulated cell viability in sorafenib-resistant liver cancer cells. These results suggest that U-ISGF3 induced sorafenib resistance in liver cancer cells. Also, this mechanism may also be relevant to patients with sorafenib resistance.
Insights
Unphosphorylated interferon-stimulated genes (U-ISGs) and the U-ISGF3 complex drive sorafenib resistance in liver cancer. Targeting this complex may overcome resistance in hepatocellular carcinoma (HCC) patients.
Area of Science:
- Oncology
- Molecular Biology
- Hepatocellular Carcinoma Research
Background:
- Hepatocellular carcinoma (HCC) is a prevalent malignancy with poorly understood molecular drivers.
- Sorafenib is a standard HCC treatment, but drug resistance limits its efficacy in most patients.
Purpose of the Study:
- To investigate molecular mechanisms underlying sorafenib resistance in liver cancer using machine learning.
- To identify novel therapeutic targets for overcoming sorafenib resistance in HCC.
Main Methods:
- Machine learning analysis of liver cancer cell lines.
- Investigation of unphosphorylated interferon-stimulated genes (U-ISGs) and the U-ISGF3 complex.
- Gene knockdown experiments to assess the role of U-ISGF3.
Main Results:
- Upregulation of U-ISGs and increased levels of the U-ISGF3 complex (unphosphorylated STAT1, unphosphorylated STAT2, and IRF9) in sorafenib-resistant HCC cells.
- Knockdown of the U-ISGF3 complex led to downregulation of U-ISGs.
- Inhibition of the U-ISGF3 complex reduced cell viability in sorafenib-resistant HCC cells.
Conclusions:
- The U-ISGF3 complex promotes sorafenib resistance in liver cancer.
- This mechanism is a potential therapeutic target for improving sorafenib treatment outcomes in HCC patients.
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