Fig. 2

Transcriptome analyses of SK-UT1 cells xenografts tissue from selinexor, eribulin, and selinexor + eribulin treatment groups. (A) The volcano plot of the DEGs obtained from global transcriptome analyses in each treatment group relative to vehicle-treated SK-UT1 tumor is shown (n = 3/group). (B) Venn diagrams representing the overlap of DEGs among different treatment groups. The upregulated and downregulated genes were analyzed and represented separately. (C) Top canonical pathways enriched by differentially expressed genes by Ingenuity Pathway Analysis (IPA). Pathways were ranked based on p-value, where the bars represent the inverse log of the p-value (x-axis). A p-value < 0.05 by Fisher’s exact test was considered to select statistically significant pathway annotation. (D). Comparative heatmap of the differentially expressed genes in different treatment groups, as determined by heat mapper. (E) Validation of selected genes that showed significant differential expression following selinexor + eribulin combination treatment. qPCR validation of selected cancer-related genes obtained from RNA-sequencing. Results are represented as the mean ± SEM. (*P < 0.05; n = 3/group). (F) Western blotting validation of selected cancer-related genes. (G) Selinexor treatment showed minimal nuclear entrapment of IκB-α, but combined treatment with selinexor and eribulin further increased nuclear retention of IκB-α (H) Bar graphs show the IPA tool predicted a list of significantly activated and inhibited upstream transcription regulators in each treatment group. A z-score greater than 2.0 defines significant activation of the node, whereas a z-score less than 2.0 defines inhibition. HIF1A, MYB and SOX4 are several transcription regulators predicted to be inhibited by selinexor + eribulin treatment