fig2

Multi-omics classification of acute myeloid leukemia guides drug combinations to overcome Venetoclax resistance

Figure 2. Reproduction of AML molecular subtyping results in external cohorts. (A) Prediction and classification of patient samples using NTP in the BEAT AML cohort; (B) Kaplan-Meier survival curves illustrating differences in OS among patients with different clusters in the BEAT AML cohort (P = 0.011); (C) Comparison of CEBPA, FLT3, NPM1, and TP53 gene mutations with the three clusters; (D) Bar chart describing the relationship between clinical indicators such as ELN 2017 risk categories, patient responses to induction therapy and the three clusters in the BEAT AML cohort; (E) Simulation of patient differentiation trajectories in different clusters within the BEAT AML cohort; (F and H) Prediction and classification of patient samples using NTP in the GSE10358 and GSE71014 cohorts; (G and I) Kaplan-Meier survival curves showing differences in OS among patients with different subtypes in the GSE10358 cohort (P = 0.001) and GSE71014 cohort (P = 0.003). Log-rank tests were used to calculate P-values for Kaplan-Meier survival curves, and categorical variables were analyzed using the chi-square test or Fisher’s exact test. AML: Acute myeloid leukemia; NTP: nearest template prediction; OS: overall survival; CEBPA: CCAAT/enhancer-binding protein alpha; FLT3: FMS-like tyrosine kinase 3; NPM1: nucleophosmin 1; TP53: tumor protein 53; ELN: European LeukemiaNet.

Cancer Drug Resistance
ISSN 2578-532X (Online)

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