Identification of Fasudil as a collaborator to promote the anti-tumor effect of lenvatinib in hepatocellular carcinoma by inhibiting GLI2-mediated hedgehog signaling pathway

Abstract

Lenvatinib is a frontline tyrosine kinase inhibitor for patients with advanced hepatocellular carcinoma (HCC). However, just 25% of patients benefit from the treatment, and acquired resistance always develops. To date, there are neither effective medications to combat lenvatinib resistance nor accurate markers that might predict how well a patient would respond to the lenvatinib treatment. Thus, novel strategies to recognize and deal with lenvatinib resistance are desperately needed. In the current study, a robust Lenvatinib Resistance index (LRi) model to predict lenvatinib response status in HCC was first established. Subsequently, five candidate drugs (Mercaptopurine, AACOCF3, NU1025, Fasudil, and Exisulind) that were capable of reversing lenvatinib resistance signature were initially selected by performing the connectivity map (CMap) analysis, and fasudil finally stood out by conducting a series of cellular functional assays in vitro and xenograft mouse model. Transcriptomics revealed that the co-administration of lenvatinib and fasudil overcame lenvatinib resistance by remodeling the hedgehog signaling pathway. Mechanistically, the feedback activation of EGFR by lenvatinib led to the activation of the GLI2-ABCC1 pathway, which supported the HCC cell's survival and proliferation. Notably, co-administration of lenvatinib and fasudil significantly inhibited IHH, the upstream switch of the hedgehog pathway, to counteract GLI2 activation and finally enhance the effectiveness of lenvatinib. These findings elucidated a novel EGFR-mediated mechanism of lenvatinib resistance and provided a practical approach to overcoming drug resistance in HCC through meaningful drug repurposing strategies.

Keywords

• Lenvatinib resistance
• Fasudil
• Hedgehog signaling pathway
• Drug repurposing
• Machine learning