Fig. 7

Drug sensitivities analysis based on m6A models. A, Network diagram displaying drugs with significant correlations between sensitivity and m6A.ES.harm or m6A.ES.benefit across 24 datasets through pRRophetic method. The gene node size represents the cumulative correlation between the corresponding drug sensitivity and m6A.ES.harm or m6A.ES.benefit. B, Correlation of m6A.ES.harm with sensitivity of 12 anti-cancer drugs through pRRophetic method. C–D, Relationship of m6A.ES.harm with gemcitabine and sorafenib sensitivity in GSE36376. E, Validation of the correlation between m6A.ES.harm and sensitivity of 12 anti-cancer drugs through oncoPredict method among 7 datasets. F–G, Association of m6A.ES.harm with gemcitabine and sorafenib sensitivity in TCGA. H, Relationship between m6A.ES.benefit and sensitivity of 4 anti-cancer drugs through pRRophetic method. I–J, Correlation of m6A.ES.benefit with paclitaxel and bortezomib sensitivity in GSE25097. K, Validation of the correlation between m6A.ES.benefit and sensitivity of 4 anti-cancer drugs through oncoPredict method. L–M, Association of m6A.ES.benefit with paclitaxel and bortezomib sensitivity in GSE114564. N–O, Differences of m6A.ES.harm and m6A.ES.benefit among TACE subgroups. Negative, negative correlation. Positive, positive correlation. Cor, correlation coefficient. TACE, trans-catheter arterial chemoembolization. ***P < 0.001