iPSC-derived venous endothelial cells for modeling vascular malformation and drug discovery

Published: 25 November 2024| Version 1 | DOI: 10.17632/s26782v3kg.1
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Venous malformations (VMs) represent prevalent vascular anomalies typically attributed to non-inherited somatic mutations within venous endothelial cells (VECs). The lack of robust disease models for VMs impeded the discovery of new drugs. Here, we implemented heterozygous mutation into iPSCs and devised a robust protocol for the generation of iVECs. This protocol involved the deliberate manipulation of cell cycle dynamics mediated through the retinoic signaling pathway. The mutated iVECs exhibited aberrant TIE2 signaling and formed dilated blood vessels in vivo, thereby recapitulating the phenotypic characteristics observed in VMs. Moreover, utilizing a deep neural network and a high-throughput DRUG-Seq approach, we performed drug screening and identified Bosutinib that effectively rescued the disease phenotype in vitro and in vivo. In summary, by leveraging genome editing and stem cell technology, we generated VM models that enabled the development of new potential therapeutics.

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Cultured cells were lysed in lysis buffer (Beyotime). The concentration of extracted protein was measured using BCA kit (Beyotime) and spectrophotometer (Thermo Fisher), according to its manufacturer’s protocol. Proteins of samples were separated by 10% SDS-PAGE and transferred to PVDF membrane. Membranes were incubated for 2 hours at room temperature with 5% fat-free milk in Tris buffered saline containing Tween 20, followed by incubation at 4℃ with primary antibodies overnight. The membranes were washed with TBS-T buffer for 3 times and then incubated with a horseradish peroxide-conjugated secondary antibody for 1 h at room temperature. After TBS-T buffer washing, the membrane was developed with ECL Reagent (Beyotime) and visualized using an enhanced chemiluminescence detection system. The density of the signals was quantified with Image J (NIH) software.

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Peking University

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