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

Abstract

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 multiforme (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.

Keywords: blood–brain barrier; drug delivery; glioblastoma; microfluidic; nanoparticle.

Fig. 1.

Generation and characterization of a glioblastoma BBB MVN model (BBB-GBM model). (A) Schematic of BBB-GBM formation in a microfluidic device. (Scale bars: 100 µm [Left] and 500 µm [Right].) (B) ROIs identified spatially within the BBB-GBM model, with far from GBM ROIs identified to be at least 2,500 µm away from the GBM spheroid. (C) Permeability to 40-kDa dextran in the vascular networks across different ROI locations; each point represents n = 1 device. (D) Expression of LRP1 across different ROI locations, as assessed via immunofluorescence staining; each point represents n = 1 device. (E) Representative micrographs of LRP1 staining quantified in D. (Scale bars: 100 µm.) In all graphs, bars represent mean ± SD. ns, not significant. *P < 0.05. Statistical analyses are described in Materials and Methods. AU, arbitrary units; 2D, two-dimensional.

Fig. 2.

Functionalized LbL-NPs cross BBB MVNs near GBM spheroids via LRP1-mediated transport. (A) LbL assembly of AP2 NPs. (B) Fold change in mean fluorescence intensity (MFI) of NPs in GBM spheroids without vascular networks, normalized to bare NP; points represents n = 1 spheroid. (C) Representative GBM spheroids after 12-min NP incubation, as quantified in B. (Scale bars: 100 µm.) (D) NP permeability in networks with no GBM spheroid (no) and in regions near and far from a GBM spheroid, normalized to the no spheroid device; points represent n = 1 ROI; n = 6 devices per condition were considered. (E) Representative images of NPs in the BBB microvessels at t = 0 min following NP perfusion; time-lapse images over 12 min were used to determine permeabilities in D. (Scale bars: 100 µm.) (F) BBB vessel permeabilities to the three NP formulations in networks without GBM spheroids at 37 °C and 21 °C. Points represent n = 1 ROI; n = 4 devices per condition were considered. (G) Representative images of AP2 NPs at t = 0 and t = 12 min, as quantified in F. (Scale bars: 50 µm.) (H) BBB vessel permeabilities to AP2 NPs at 37 °C following incubation for 30 min with anti-LRP1 or IgG control antibodies. Points represent n = 1 ROI; for antibody conditions, n = 4 devices were considered; n = 6 nontreated devices. Throughout, bars represent mean ± SD. ns, not significant. *P < 0.05; **P < 0.01. Statistical analyses are described in Materials and Methods. A.U., arbitrary units; w/o, without.

Fig. 3.

In vivo BBB permeability assessed by intravital microscopy is consistent with the in vitro BBB model. (A) Workflow of intravital imaging, in which fluorescent NPs and dextran are dosed systemically, and time-lapse imaging is performed in intact brain capillaries. (B) Representative images of 40-kDa dextran and NP formulations perfused in mouse BBB capillaries. (Scale bars, 20 µm.) (C) BBB permeabilities to fluorescently labeled dextran (10 and 40 kDa) in mouse BBB capillaries and in vitro BBB microvessels (no tumors). Points represents n = 1 device; n = 2 mice were considered for 10-kDa dextran and n = 10 mice for 40-kDa dextran. (D) BBB permeabilities to the three NP formulations in mouse BBB capillaries and in vitro BBB microvessels (no tumors). Points represent n = 1 ROI; n = 6 independent devices per condition were considered; n = 3 to 5 mice were considered per condition. Bars represent mean ± SD. ns, not significant. Statistical analyses are described in Materials and Methods.

Fig. 4.

Encapsulation in LbL-NPs improves efficacy and targeted delivery of CDDP in BBB-GBM. (A) GBM spheroid size in BBB-GBM model following treatment with free CDDP, CDDP encapsulated in bare NPs (Bare CDDP NP), or CDDP encapsulated in AP2 NPs (AP2 CDDP NP), compared to untreated devices. Points represent mean ± SD of n = 6 devices. (B) Representative fluorescent micrographs quantified in A. (Scale bars: 200 µm.) (C) Change in MFI of NP signal in GBM tumors in the BBB-GBM device over time, following treatment with fluorescently tagged bare- or AP2-CDDP NPs. Points represent n = 1 device. (D) MFI of Sytox signal per area (normalized by DAPI) in the three ROI locations considered in BBB-GBM devices after treatment with free CDDP, bare CDDP NPs, or AP2 CDDP NPs and compared to control devices without treatment. Points represent n = 1 device. (E) Representative fluorescent micrographs quantified in D. (Scale bar: 500 µm.) (F) Heatmap of cell death gene-expression levels in two ROIs of the devices (inside the GBM tumor and far from the tumor), as quantified by qRT-PCR. Bars represent mean ± SD. ns, not significant. *P < 0.05; ****P < 0.0001. Statistical analyses are described in Materials and Methods. AU, arbitrary units.

Fig. 5.

BBB-GBM device predicts differential effects of CDDP NP formulations in an orthotopic in vivo model. (A) Timeline of in vivo study with orthotopic GBM tumors using MRI to monitor response to therapeutic NPs. (Scale bars, 4 mm.) (B) Waterfall plot for change in tumor volume after treatment on the y axis, where each bar represents one mouse; dotted line is the median tumor volume change for the AP2 NP group. (C) Quantification of CC-3 staining in tumor tissue. Each dot represents n = 1 mouse. (D) Representative immunohistochemistry micrographs with hematoxylin and eosin (H&E) staining (for context) and CC3, as quantified in C; arrowheads denote CC-3–positive cells. (Scale bars: 50 µm [Middle and Bottom] and 1 mm [Top].) Bars represent mean ± SD. ns, not significant. **P < 0.01. Statistical analyses are described in Materials and Methods.