Fig. 5: siRNA knockdown and drug inhibition of NOTCH signaling pathway reduces viability of H3.3-mutated glioma cells.

a Dose–response curves of DAPT treatment on our cell panel. Curves were fitted using the “log(inhibitor) versus response–variable slope” model and IC50s were calculated using the GraphPad Prism software. Arrows denote the direction of IC50 shift upon gene editing where applicable. b Dose–response curves of Panobinostat treatment on our cell panel. For a, b, p values comparing LogIC50s were calculated by unpaired t test using GraphPad QuickCalcs with n = 3 biologically independent samples. c Western blot of ASCL1 knockdown in subgroups of our panel of cells using siRNA for ASCL1, with quantification of ASCL1 levels exhibiting strong knockdown in XIII and XVII lines. siRNA targeting noncoding RNA from the same vendor as our targeting siRNA (Thermo) was used as control. d Cell viability measured using CellTiterGlo assay (Promega) of cells under siRNA knockdown of ASCL1 plotted as dot plot with mean ± sd; n = 4 biologically independent samples. e Western blot of ASCL1 levels with transient transfection of empty vector or pCS2-HA-ASCL1 plasmid leading to overexpression of ASCL1 in XIII-WT and XVII-WT cells. f Cell viability of XIII-WT and XVII-WT cells with overexpression of ASCL1, mean ± sd; n = 3 biologically independent samples. g Western blot of RBPJ knockdown in our panel of cell lines. RBPJ knockdown was the strongest in XIII and XVII cells, which exhibit higher RBPJ expression than the H3.3WT-reverted cells. h Cell viability of glioma cell lines under RBPJ knockdown, mean ± sd; n = 3 biologically independent samples. i Western blot of RBPJ levels across cell panel under RIN1 (RBPJ inhibitor 1) treatment (2 μM, 72 h). RIN1 does not significantly impact RBPJ protein levels. j Cell viability of glioma cells under RIN1 treatment, mean ± sd; n = 3 biologically independent samples. All p values were calculated by Student’s t test comparison of treated cells versus control or vehicle. *p < 0.05.