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Large-scale cancer genomics efforts are identifying hundreds of somatic genomic alterations in glioblastoma (GBM). Distinguishing between active driver and neutral passenger alterations requires functional assessment of each gene; therefore, integrating biological weight of evidence with statistical significance for each genomic alteration will enable better prioritization for downstream studies. Here, we demonstrate the feasibility and potential of in vitro functional genomic screens to rapidly and systematically prioritize high-probability candidate genes for in vivo validation. Integration of low-complexity gain- and loss-of-function screens designed on the basis of genomic data identified 6 candidate GBM oncogenes, and RINT1 was validated as a novel GBM oncogene based on its ability to confer tumorigenicity to primary nontransformed murine astrocytes in vivo. Cancer genomics-guided low-complexity genomic screens can quickly provide a functional filter to prioritize high-value targets for further downstream mechanistic and translational studies.