Gene expression changes were assessed in tumor cells treated with epigenetic inhibitors and after drug withdrawal

Sequential therapy is a promising strategy to enhance antitumor efficacy; however, the rational design of sequential drug treatments remains challenging. Here, we introduce an AI framework, AlphaTherapy, which can design sequential drug combinations for cancer treatment. Analysis of AlphaTherapy-predicted combinations and large-scale in vitro validation revealed that the first drug in effective anti-tumor combinations often targets transcription, particularly epigenetic inhibitors. To investigate how epigenetic drugs enhance the efficacy of subsequent treatments, RNA-seq was performed on tumor cells treated with epigenetic inhibitors followed by drug withdrawal to assess gene expression changes. Overall design: RNA-seq was performed on the following cell lines under specified treatment conditions: A375 cells: untreated control (DMSO), treatment (2 µM I-BET151 for 72 h), and withdrawal treatment (2 µM I-BET151 for 72 h followed by 72 h without drug). MDA-MB-231 cells: untreated control (DMSO), treatment (2 µM OTX-015, 5 µM GSK126, 5 µM UNC1999, 10 µM CCS1477, and 5 µM A485 for 72 h), and withdrawal treatment (drug treatment for 72 h followed by 72 h without drug). MCF7 cells: untreated control (DMSO), treatment (10 µM CCS1477 for 72 h), and withdrawal treatment (drug treatment for 72 h followed by 72 h without drug).