The study presents an extensive functional genomic analysis of acute myeloid leukemia (AML) using a cohort of 672 tumor specimens from 562 patients. Whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses were conducted to assess mutational patterns, gene expression signatures, and drug responses. Key findings include: 1. **Genomic Landscape**: The cohort revealed a range of somatic variants per patient, with a median of 13 somatic variants. There were significant differences in mutation frequencies between Beat AML and The Cancer Genome Atlas (TCGA) data, particularly in genes like RSF2. Divergent mutational events were observed in 221 genes, with some mutations unique to Beat AML. 2. **Drug Response and Gene Expression**: RNA sequencing identified gene expression signatures associated with various AML subtypes. Ex vivo drug sensitivity assays showed that transformed cases generally had less sensitivity to most drugs compared to *de novo* cases. Drug sensitivity patterns were correlated with clinical and genetic features, and specific mutations like TP53, ASXL1, NRAS, KRAS, IDH2, RUNX1, U2AF1, and ZRSR2 were linked to drug resistance or sensitivity. 3. **Gene Signatures of Drug Response**: Correlation analysis between drug sensitivity and mutational events or gene expression levels identified novel associations. For example, mutation of FLT3, NPM1, and DNMT3A correlated with sensitivity to ibrutinib, while mutation of BCOR and RUNX1 correlated with increased sensitivity to JAK kinase inhibitors. 4. **Integrated Analysis**: Multivariate modeling integrated mutation data with gene expression clusters, revealing novel co-occurrences of mutations and expression clusters associated with drug sensitivity or resistance. The study provides a comprehensive dataset and analytical tools (available at www.vizome.org) to advance understanding and treatment of AML, highlighting the importance of integrating genomic and transcriptomic data to identify new markers and mechanisms of drug sensitivity and resistance.The study presents an extensive functional genomic analysis of acute myeloid leukemia (AML) using a cohort of 672 tumor specimens from 562 patients. Whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses were conducted to assess mutational patterns, gene expression signatures, and drug responses. Key findings include: 1. **Genomic Landscape**: The cohort revealed a range of somatic variants per patient, with a median of 13 somatic variants. There were significant differences in mutation frequencies between Beat AML and The Cancer Genome Atlas (TCGA) data, particularly in genes like RSF2. Divergent mutational events were observed in 221 genes, with some mutations unique to Beat AML. 2. **Drug Response and Gene Expression**: RNA sequencing identified gene expression signatures associated with various AML subtypes. Ex vivo drug sensitivity assays showed that transformed cases generally had less sensitivity to most drugs compared to *de novo* cases. Drug sensitivity patterns were correlated with clinical and genetic features, and specific mutations like TP53, ASXL1, NRAS, KRAS, IDH2, RUNX1, U2AF1, and ZRSR2 were linked to drug resistance or sensitivity. 3. **Gene Signatures of Drug Response**: Correlation analysis between drug sensitivity and mutational events or gene expression levels identified novel associations. For example, mutation of FLT3, NPM1, and DNMT3A correlated with sensitivity to ibrutinib, while mutation of BCOR and RUNX1 correlated with increased sensitivity to JAK kinase inhibitors. 4. **Integrated Analysis**: Multivariate modeling integrated mutation data with gene expression clusters, revealing novel co-occurrences of mutations and expression clusters associated with drug sensitivity or resistance. The study provides a comprehensive dataset and analytical tools (available at www.vizome.org) to advance understanding and treatment of AML, highlighting the importance of integrating genomic and transcriptomic data to identify new markers and mechanisms of drug sensitivity and resistance.