Objective: To explore the therapeutic potential and the underlying mechanism of metformin, an adenosine monophosphate-activated kinase (AMPK) activator, in ocular melanoma.
Methods: CCK8, transwell, and colony formation assays were performed to detect the proliferation and migration ability of ocular melanoma cells. A mouse orthotopic xenograft model was built to detect ocular tumor growth in vivo. Western blot, immunofluorescence, and electron microscopy were adopted to evaluate the autophagy levels of ocular melanoma cells, and high-throughput proteomics and CUT & Tag assays were performed to analyze the candidate for autophagy alteration.
Results: Here, we revealed for the first time that a relatively low dose of metformin induced significant tumorspecific inhibition of the proliferation and migration of ocular melanoma cells both in vitro and in vivo. Intriguingly, we found that metformin significantly attenuated autophagic influx in ocular melanoma cells. Through high-throughput proteomics analysis, we revealed that optineurin (OPTN), which is a key candidate for autophagosome formation and maturation, was significantly downregulated after metformin treatment. Moreover, excessive OPTN expression was associated with an unfavorable prognosis of patients. Most importantly, we found that a histone deacetylase, SIRT1, was significantly upregulated after AMPK activation, resulting in histone deacetylation in the OPTN promoter.
Conclusions: Overall, we revealed for the first time that metformin significantly inhibited the progression of ocular melanoma, and verified that metformin acted as an autophagy inhibitor through histone deacetylation of OPTN. This study provides novel insights into metformin - guided suppression of ocular melanoma and the potential mechanism underlying the dual role of metformin in autophagy regulation.
Keywords: OPTN; autophagy; histone modification; metformin; ocular melanoma.
© 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.