With the rapidly increasing availability of genomic data and ensuing identification of disease associated mutations, the determination of molecular mechanisms by which such mutations affect biochemical processes and phenotypes remains a major challenge. In this study we developed and applied a multilayered proteomic workflow to explore how genetic lesions modulate the modular proteome to alter functional phenotypes. Using this workflow we determined how expression of a panel of disease-associated mutations in the Dyrk2 protein kinase altered the composition, topology and activity of the multifunctional protein complex assembled around Dyrk2 and the phosphoproteomic state of the respective cells. We found that the selected cancer-related Dyrk2 mutations caused, to a differing extent, disassembly of the catalytic kinase core complex and caused disruption of interactions within the Dyrk2 core or with other cellular modules. This is exemplified by the nuclear pore associated Y-complex which we identified as new interactor of Dyrk2. We further found that the altered protein-protein interactions caused by the mutations are associated with topological changes and with changes in posttranslational modifications in the mutated kinase modules. Finally, we observed that the expression of each tested cancer-related mutation created a specific phosphoproteomic footprint including altered phosphorylation of known cancer-associated proteins, thus linking Dyrk2 mutations with cancer-related biochemical processes. Overall we developed an integrated, multilayered proteomic workflow to study how specific genomic mutations affect the modular proteome. Applying it to mutations in the Dyrk2 kinase we discover multiple mutation-specific, significant, pleiotropic and functionally relevant changes, highlighting the large plasticity of molecular responses to genomic lesions. The established workflow is generically applicable and will contribute to a better understanding of the molecular mechanisms that translate genomic alterations into (disease) phenotypes.