Systemic Drug Effects in Vortioxetine-Induced Time-Series Datasets

This paper introduces an approach for inferring the gene regulatory networks in vortioxetine-induced glioblastoma cells to investigate vortioxetine's systemic effects. The approach uses an ordinary differential equation (ODE)-based inverse problem to evaluate the drug-induced gene interactions within the GLIOMA and ERBB pathways, which are deeply intertwined in cancers, by using time-series datasets. Time-series datasets were generated in triplicate at 0, 3, 6, 9, 12, and 24 h. The results of the ERBB pathway confirmed that PIK3R5 was commonly activated, while JUN, as a proto-oncogene in glioblastoma, was inhibited by genes across all three datasets. In particular, PIK3R5 was commonly activated by PAK6 in all three datasets. The results of the GLIOMA pathway confirmed that CALML6 was commonly activated, while CDK4 and CCND1, which are mostly overexpressed in human cancers, were inhibited across all three datasets. Additionally, an analysis of the independent datasets generated at 6 and 22 h after the vortioxetine injection identified the most distinct variable genes between the two time points: CRK (1.96) and JUN (-3.02) for the ERBB signaling pathway, and BRAF (1.30) and MAP2K2 (-1.92) for the GLIOMA pathway. We conclude that vortioxetine, an antidepressant, decreases JUN, a proto-oncogene involved in the ERBB signaling pathway, and CCND1, another proto-oncogene involved in the GLIOMA pathway, over time in glioblastoma cells.