Martinez, J. E. | Search bioRxiv

bioRxiv2025

Rapamycin can revert CCM phenotype in brain endothelial cells and ameliorates chronic cavernoma development in combination with lapatinib

This study investigates the impact of rapamycin and propranolol on cerebral cavernous malformations (CCMs). Employing an unbiased transcriptomic analysis, we aimed to comprehensively elucidate the molecular mechanisms underlying these drug effects in Mouse Brain Microvascular Endothelial Cells (mBMEC) deficient in Ccm3. While propranolol shows limited efficacy in modulating the CCM transcriptomic phenotype in mBMEC, rapamycin demonstrates a higher impact. Rapamycin reverses gene expression changes induced by Ccm3 deficiency, restoring Klf2/4-dependent genes like Nos3, Adamts1, and Thbs1. Notably, we observed a reduction in KLF2 protein levels in Ccm3 KO cells treated with rapamycin. Critically, in vivo experiments demonstrate that a combination of rapamycin and lapatinib effectively reduces lesion volume in a chronic CCM model. This finding is particularly noteworthy as it suggests a potential treatment strategy for existing lesions. In summary, our work describes a new mechanism for the effects of rapamycin in Ccm3- deficient cells and identifies a new drug combination in the treatment of cavernomas.

cell biology↗

bioRxiv2020

Automated generation of context-specific Gene Regulatory Networks with a weighted approach in D. melanogaster

MotivationThe regulation of gene expression is a key factor in the development and maintenance of life in all organisms. This process is carried out mainly through the action of transcription factors (TFs), although other actors such as ncRNAs are involved. In this work, we propose a new method to construct Gene Regulatory Networks (GRNs) depicting regulatory events in a certain context for Drosophila melanogaster. Our approach is based on known relationships between epigenetics and the activity of transcription factors. ResultsWe developed method, Tool for Weighted Epigenomic Networks in D. melanogaster (Fly T-WEoN), which generates GRNs starting from a reference network that contains all known gene regulations in the fly. Regulations that are unlikely taking place are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications, and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from literature. Experimental data files can be generated with several standard procedures and used solely when and if available.Fly T-WEoN is available as a Cytoscape application that permits integration with other tools, and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster. AvailabilityFly T-WEoN, together with its step-by-step guide is available at https://weon.readthedocs.io Contactalberto.martin@umayor.cl

bioinformatics↗