Extended Data Fig. 11: RNA-sequencing analysis of the combination treatment of lenvatinib and gefitinib in EGFRhigh liver cancer cells. | Nature

Extended Data Fig. 11: RNA-sequencing analysis of the combination treatment of lenvatinib and gefitinib in EGFRhigh liver cancer cells.

From: EGFR activation limits the response of liver cancer to lenvatinib

Extended Data Fig. 11

ad, Heat-map representations of the log2-transformed gene expression changes (log2FC) in liver cancer cells SNU449 (a), JHH1 (b), Huh6 (c) and SNU182 (d) treated with DMSO, 2.5 μM gefitinib, 5 μM lenvatinib, or the two drugs for 24 h. Differential expression of the whole genome is shown on the basis of each treatment versus DMSO using RNA-sequencing analysis. To show robust changes, only genes that have a mean read count over all samples equal or greater than 100 were included. To prevent too much dilution of the colour-coding, the log2-transformed fold-change values were truncated in that lower than −2 were set to −2 and higher than 2 were set to 2. Heat maps depicting all three treatments were then generated by unsupervised hierarchical clustering. One replicate was used for each sample. e, For the genes with a mean read count over all samples greater than 100 per line, the top 25% highest and 25% lowest synergy scores were determined and shown as heat maps. These lists were merged and an unsupervised hierarchical clustering was performed. f, GSEA analysis of the gene set of Kobayashi ‘EGFR signalling down’ in each comparison. Unsupervised hierarchical clustering of normalized enrichment scores (NES) was used to generate a comprehensive heat-map visualization of the functional transcriptional outputs of the four cell lines. *P < 0.001. g, GSEA analysis of curated gene sets was performed, Kobayashi ‘EGFR signalling down’ and Schuhmacher ‘MYC targets up’ were identified as two of the highest-ranking downregulated gene sets in the combination-treated cells in all four liver cancer cell lines based on additional gene alterations in combination group. hk, A fold change preranked list of each treatment versus DMSO was used to run GSEA against the Hallmark gene sets in SNU449 (h), JHH1 (i), Huh6 (j) and SNU182 (k) cells. Unsupervised hierarchical clustering of normalized enrichment scores was used to generate a comprehensive heat-map visualization of the functional transcriptional outputs of each treatment (FDR < 0.1). ln, GSEA indicates that the gene sets of Hallmark ‘MYC targets v1’ (l), Hallmark ‘MYC targets v2’ (m) and Hallmark ‘KRAS signalling up’ (n) were negatively enriched in the combination group based on additional gene alterations.

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