bioRxivCell Biology
Disruption of DLL4/NOTCH1 Causes Dysregulated PPARγ/AKT Signaling in Pulmonary Arterial Hypertension
Keytam S. AwadiD, Shuibang WangiD, Edward J. Dougherty, Ali Keshavarz, Cumhur Y. Demirkale, Zu Xi Yu, Latonia Miller, Jason M. ElinoffiD, Robert L. DanneriD
Abstract
Pulmonary arterial hypertension (PAH) is a progressive cardiopulmonary disease characterized by vascular remodeling of small pulmonary arteries. Endothelial dysfunction in advanced PAH is associated with proliferation, apoptosis resistance, and endothelial to mesenchymal transition (EndoMT) due to aberrant signaling. DLL4, a cell membrane associated NOTCH ligand, activates NOTCH1 signaling and plays a pivotal role maintaining vascular integrity. Inhibition of DLL4 has been associated with the development of pulmonary hypertension, but the mechanism is incompletely understood. Here we report that BMPR2 silencing in PAECs activated AKT and decreased DLL4 expression. DLL4 loss was also seen in lungs of patients with IPAH and HPAH. Over-expression of DLL4 in PAECs induced BMPR2 promoter activity and exogenous DLL4 increased BMPR2 mRNA through NOTCH1 activation. Furthermore, DLL4/NOTCH1 signaling blocked AKT activation, decreased proliferation and reversed EndoMT in BMPR2- silenced PAECs and ECs from IPAH patients. PPAR{gamma}, suppressed by BMPR2 loss, was induced and activated by DLL4/NOTCH1 signaling in both BMPR2-silenced and IPAH PAECs, reversing aberrant phenotypic changes, in part through AKT inhibition. Finally, leniolisib, a well-tolerated oral PI3K8/AKT inhibitor, decreased cell proliferation, induced apoptosis and reversed markers of EndoMT in BMPR2-silenced PAECs. Restoring DLL4/NOTCH1/PPAR{gamma} signaling and/or suppressing AKT activation may be beneficial in preventing or reversing the pathologic vascular remodeling of PAH.
- organism: human
- assay: bulk RNA-seq
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell signaling & trafficking
- research focus: cancer & tumor microenvironment
- approach: experimental assay
- approach: statistical model
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