FB2026_01 , released March 12, 2026
FB2026_01 , released March 12, 2026
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Citation
Housden, B.E., Valvezan, A.J., Kelley, C., Sopko, R., Hu, Y., Roesel, C., Lin, S., Buckner, M., Tao, R., Yilmazel, B., Mohr, S.E., Manning, B.D., Perrimon, N. (2015). Identification of potential drug targets for tuberous sclerosis complex by synthetic screens combining CRISPR-based knockouts with RNAi.  Sci. Signal. 8(393): rs9.
FlyBase ID
FBrf0229582
Publication Type
Research paper
Abstract
The tuberous sclerosis complex (TSC) family of tumor suppressors, TSC1 and TSC2, function together in an evolutionarily conserved protein complex that is a point of convergence for major cell signaling pathways that regulate mTOR complex 1 (mTORC1). Mutation or aberrant inhibition of the TSC complex is common in various human tumor syndromes and cancers. The discovery of novel therapeutic strategies to selectively target cells with functional loss of this complex is therefore of clinical relevance to patients with nonmalignant TSC and those with sporadic cancers. We developed a CRISPR-based method to generate homogeneous mutant Drosophila cell lines. By combining TSC1 or TSC2 mutant cell lines with RNAi screens against all kinases and phosphatases, we identified synthetic interactions with TSC1 and TSC2. Individual knockdown of three candidate genes (mRNA-cap, Pitslre, and CycT; orthologs of RNGTT, CDK11, and CCNT1 in humans) reduced the population growth rate of Drosophila cells lacking either TSC1 or TSC2 but not that of wild-type cells. Moreover, individual knockdown of these three genes had similar growth-inhibiting effects in mammalian TSC2-deficient cell lines, including human tumor-derived cells, illustrating the power of this cross-species screening strategy to identify potential drug targets.
PubMed ID
PubMed Central ID
PMC4642709 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Sci. Signal.
    Title
    Science signaling
    ISBN/ISSN
    1937-9145 1945-0877
    Data From Reference
    Genes (7)
    Human Disease Models (3)
    Cell Lines (2)