Hammond, P. T. | Search bioRxiv

bioRxiv2021

A predictive microfluidic model of human glioblastoma to assess trafficking of blood-brain barrier penetrant nanoparticles

The blood-brain barrier represents a significant challenge for the treatment of high-grade gliomas, and our understanding of drug transport across this critical biointerface remains limited. To advance preclinical therapeutic development for gliomas, there is an urgent need for predictive in vitro models with realistic blood-brain barrier vasculature. Here, we report a vascularized human glioblastoma (GBM) model in a microfluidic device that accurately recapitulates brain tumor vasculature with self-assembled endothelial cells, astrocytes, and pericytes to investigate the transport of targeted nanotherapeutics across the blood-brain barrier and into GBM cells. Using modular layer-by-layer assembly, we functionalized the surface of nanoparticles with GBM-targeting motifs to improve trafficking to tumors. We directly compared nanoparticle transport in our in vitro platform with transport across mouse brain capillaries using intravital imaging, validating the ability of the platform to model in vivo blood-brain barrier transport. We investigated the therapeutic potential of functionalized nanoparticles by encapsulating cisplatin and showed improved efficacy of these GBM-targeted nanoparticles both in vitro and in an in vivo orthotopic xenograft model. Our vascularized GBM model represents a significant biomaterials advance, enabling in-depth investigation of brain tumor vasculature and accelerating the development of targeted nanotherapeutics. Significance StatementThe blood-brain barrier represents a major therapeutic challenge for the treatment of glioblastoma, and there is an unmet need for in vitro models that recapitulate human biology and are predictive of in vivo response. Here we present a new microfluidic model of vascularized glioblastoma featuring a tumor spheroid in direct contact with self-assembled vascular networks comprised of human endothelial cells, astrocytes, and pericytes. This model was designed to accelerate the development of targeted nanotherapeutics, and enabled rigorous assessment of a panel of surface-functionalized nanoparticles designed to exploit a receptor overexpressed in tumor-associated vasculature. Trafficking and efficacy data in the in vitro model compared favorably to parallel in vivo data, highlighting the utility of the vascularized glioblastoma model for therapeutic development.

bioengineering↗

bioRxiv2021

Massively parallel pooled screening reveals genomic determinants of nanoparticle-cell interactions

To accelerate the translation of cancer nanomedicine, we hypothesize that integrated genomic screens will improve understanding of the cellular processes governing nanoparticle trafficking. We developed a massively parallel high-throughput screening method leveraging barcoded, pooled cancer cell lines annotated with multi-omic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. This approach identified both the materials properties and cell-intrinsic features mediating nanoparticle-cell association. Coupling the data with machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers, including gene expression of SLC46A3. We engineered cell lines to validate SLC46A3 as a biomarker whose expression inversely predicts liposomal nanoparticle uptake both in vitro and in vivo. We further demonstrated the predictive capabilities extend beyond liposomal nanoparticles, regulating both uptake and transfection efficacy of solid lipid nanoparticles. Our work establishes the power of massively parallel pooled cell screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations for specific patient populations.

bioengineering↗