Acute myeloid leukemia is a clinically and genetically heterogenous disease characterized by bone marrow infiltration with immature leukemic blasts that cause bone marrow failure. Patient age, comorbidities and genomic disease characteristics have a profound impact on patient outcome. Here, we present an integrated Multi-Omics analysis of protein and gene expression as well as cytogenetics and mutations to capture the rewiring of intracellular protein networks that is most likely caused by genomic aberrations. Because protein networks are downstream of genomic aberrations, we hypothesized that our Multi-Omics approach may add to the current AML classification by identifying proteomic AML subtypes with specific clinical and molecular features that could identify therapeutic vulnerabilities and aid in the identification of predictive biomarkers.