Fig. 3

Hotspots of viral integration at gene loci and their mRNA expression. A–C Unsupervised hierarchical clustering of normalized integration data by samples (columns) and genes (rows) are shown. Data normalization was scaled using the built-in R function (scale). Lentiviral and γ-retroviral vectors showed different integration hotspots. A Heatmap showing the top 50 genes with the most enrichment of integration events at the promoter (genes with integration events from higher enrichment to lower enrichment are marked from red to green). B This heatmap shows the top 50 genes with the most enrichment of integration sites at the untranslated region (genes with integration events from higher enrichment to lower enrichment are marked from dark red to purple). C The 50 genes with the most enrichment in the exon region are shown (genes with integration events from higher enrichment to lower enrichment are marked from bittersweet to sky-blue). The bars at the top of each heatmap indicate CAR (CD22: bittersweet; CD19/22: vivid violet; BCMA: yellow; SLAMF7: jungle green) and viral vector type (lenti-vector: orange; Retro-vector: light blue). D–G) Gene expression showed no differences among transduced (TR) vs. non-transduced (UTR) cells for hot spot genes that integrated into the promoter (D, E) or the untranslated region (utr, F and G). Differential expression analysis was performed using the built-in function from limma package in Rstudio with custom scripts. Wald’s test was used to calculate the adjusted p-value or significance that a gene is differentially expressed. Genes with | FoldChange | >=2 and adj.P.value < 0.05 were considered significantly expressed