Proteins rarely work in isolation but rather function in combinations and complexes. Considering diseases driven by changes at the network level, rather than at the individual protein level has driven the recent development of the strategy of drugging “networks.” My research focuses on gene fusions, which are induced by aberrant chromosomal rearrangements or splicing dysregulation and can drive neoplasia across diverse tissues. We have generated the interactomes for 24 oncofusions and their parent proteins. With our unique combination of analysis methods and experimental design, I present interactors gained and lost as a result of the fusion event. To demonstrate the utility of this novel combination of experimental and computational methods, I highlight the interactome of the driver of the well-characterized Ewing’s sarcoma (EwS): EWSR1-FLI1. We show gains and losses caused by the oncoprotein formation fall in line with the dysregulations attributed to EwS. Not only that, but the characteristics of the gains and losses reveal a consistent pattern: gained interactions are subunits of the chromatin remodeling BAF complex, and losses are overwhelmingly related to mRNA splicing, stability, and stress granules—effectively recapitulating the known dysregulations of EwS. I highlight the robustness and adaptability of our methods by focusing on the interactomes of a morphologically similar cancer, synovial sarcoma caused by SS18-SSX1, and of a dissimilar cancer, driven by NCOA4-RET. As expected, the interactomes of SS18-SSX1 show significant overlap to EWSR1-FLI1’s, while NCOA4-RET has almost no overlap. We expect that our approach can provide valuable insights into not only other fusion-driven diseases, but also into complex basic biological questions. To highlight this flexibility, I will discuss my contribution to determining how the interactome of RNA polymerase II changes during distinct phases of transcription.