iScienceDevelopmental BiologyPeer-reviewed journal article
Drosophila RASopathy Models Identify Disease Subtype Differences and Biomarkers of Drug Efficacy
Tirtha K. DasiD, Jared Gatto, Rupa Mirmira, Ethan HourizadehiD, Dalia S. KaufmaniD, Bruce D. GelbiD, Ross Leigh CaganiD
Abstract
RASopathies represent a family of mostly autosomal dominant diseases that are caused by missense variants in the RAS/MAPK pathway. In aggregate, they are among the more common Mendelian disorders. They share overlapping pathologies that include structural birth and developmental defects that affect the heart, craniofacial and skeletal, lymphatic, and nervous systems. Variants in different genes--including those encoding KRAS, NRAS, BRAF, RAF1, and SHP2--are associated with overlapping but distinct phenotypes. Here, we report an analysis of 13 Drosophila transgenic lines, each expressing a different human disease isoform associated with a form of RASopathy. Similar to their human counterparts, each Drosophila line has common aspects but also important phenotypic distinctions including signaling pathways as well as response to therapeutics. For some lines, these differences represent activation of pathways outside the core RAS signaling pathway including the Hippo and SAPK/JNK signaling networks. We identified two classes of clinically relevant drugs, statins and histone deacetylase inhibitors, that improved viability across most RASopathy lines; in contrast, several canonical RAS pathway inhibitors proved poorly effective against, e.g., SHP2-expressing lines encoded by PTPN11. Our study provides a whole animal platform for comparison of a large number of RASopathy-associated variants. Among these variants we have identified differences in tissue phenotypes, in activation signaling pathways in biomarkers of disease progression and drug efficacy, and suggest drug classes that can be tolerated over long treatment periods for consideration in broad RASopathy trials.
- organism: Drosophila
- research focus: drug response / drug discovery
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 31
- FWCI
- 2.12
- Field percentile
- top 11%
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