Machine learning model reveals roles of interferon­stimulated genes in sorafenib­resistant liver cancer.

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.