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Fig. 9 | Journal of Translational Medicine

Fig. 9

From: Architecting the metabolic reprogramming survival risk framework in LUAD through single-cell landscape analysis: three-stage ensemble learning with genetic algorithm optimization

Fig. 9

In silico identification of targets and drugs for high 3 S-MMR score patients. (A-D) Volcano plot (A) and scatter plots (B-D) of the correlation coefficients derived from Spearman’s rank correlation analysis between 3 S-MMR score and druggable mRNA expression in the TCGA-LUAD cohort. Red dots indicate the significant positive correlations (P < 0.05, and Spearman’s r > 0.2). (E-H) Volcano plot (E) and scatter plots (F-H) of the correlations and significance between 3 S-MMR score and CERES score of drug targets. Green dots indicate the significant negative correlations (P < 0.05, and Spearman’s r < -0.2). (I-L) The comparison of IC50 values between high and low 3 S-MMR score groups of Paclitaxel (I), Gemcitabine (J), Gefitinib (K), and Cisplatin (L). (M) The composition of chemical compounds selected by CMap analysis. Only the top 10 drug categories are displayed. (N, P) The result of Spearman’s correlation analysis of CTRP-derived compounds (N) and PRISM-derived compounds (P). (O, Q) The results of differential drug response analysis of CTRP-derived compounds (O) and PRISM-derived compounds (Q), the lower values on the y-axis of boxplots imply greater drug sensitivity. Abbreviation: *P < 0.05; **P < 0.01; *** P < 0.001

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