Purpose: Epigenetic dysregulation is a common characteristic of cancers, including gastric cancer (GC), and contributes to cancer development and progression. Although the efficacy of BET (an epigenetic regulator) inhibition has been demonstrated in various cancer types, predictive genetic markers of its efficacy in GC are currently lacking. Therefore, we aimed to identify markers that predict the response of BET inhibition in GC and, suggest an effective treatment regimen through combined therapy. Methods: The effect of BET inhibition was evaluated using iBET-151, a small-molecule inhibitor of BET proteins, in a large panel (n = 49) of GC cell lines and xenograft mouse models. Comprehensive genetic information was used to identify cell lines sensitive to iBET-151. Flow cytometry, Western blotting, and colony-formation and migration assays were used to evaluate the effects of iBET-151 and/or paclitaxel. The synergistic effect of iBET-151 and paclitaxel was evaluated using an organoid model. Results: We found that iBET-151 showed a modest growth-inhibitory effect in GC cells (73%, 36/49). iBET-151 inhibited tumorigenicity in vitro and significantly promoted cell cycle arrest and apoptosis. Based on comprehensive genetic information analysis in relation to BET family expression, we found that BRD4 was highly expressed in the iBET-151-sensitive cell lines. We also identified WNT5B and IRS2 as potential biomarkers that are predictive for sensitivity to iBET-151. In GC xenograft model mice, iBET-151 significantly decreased tumor volumes and Ki-67 and BRD4 expression. Combination treatment showed that iBET-151 increased the sensitivity of GC cells to paclitaxel in approximately 70% of the cell lines (34/49) tested. iBET-151 plus paclitaxel significantly promoted cell cycle arrest and apoptosis and suppressed c-Myc, Bcl-2 and Bcl-xL expression. In GC organoids, iBET-151 and paclitaxel showed a synergistic effect. Conclusions: Collectively, our data suggest that iBET-151 is a potential therapeutic agent for GC, especially in combination with paclitaxel, and that WNT5B and IRS2 may predict iBET-151 sensitivity.
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All Science Journal Classification (ASJC) codes
- Molecular Medicine
- Cancer Research