Massively parallel pooled screening reveals genomic determinants of nanoparticle delivery

Abstract

To accelerate the translation of cancer nanomedicine, we used an integrated genomic approach to improve our understanding of the cellular processes that govern nanoparticle trafficking. We developed a massively parallel screen that leverages barcoded, pooled cancer cell lines annotated with multiomic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. We identified both materials properties and cell-intrinsic features that mediate nanoparticle-cell association. Using machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers. We validated one such biomarker: gene expression of SLC46A3 , which inversely predicts lipid-based nanoparticle uptake in vitro and in vivo. Our work establishes the power of integrated screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations.

Identification of 5-Carboxyfluorescein as a Probe Substrate of SLC46A3 and Its Application in a Fluorescence-Based In Vitro Assay Evaluating the Interaction with SLC46A3

“…We demonstrated that 5-CF uptake was significantly inhibited by steroid conjugates, bile acids, DM1 compounds, macrolides, and rifabutin, consistent with previous findings . SLC46A3 was recently implicated as a biomarker for T-DM1 therapy and functional lipid NP delivery. , Therefore, rapid screening of potent SLC46A3 inhibitors using these fluorescent probes could predict T-DM1-drug interactions and uncover compounds with the potential to improve the efficacy of NPs.…”

“…12 SLC46A3 was recently implicated as a biomarker for T-DM1 therapy and functional lipid NP delivery. 11,14 Therefore, rapid screening of potent SLC46A3 inhibitors using these fluorescent probes could predict T-DM1-drug interactions and uncover compounds with the potential to improve the efficacy of NPs. Little information is available regarding exogenous substrates of SLC46A3, excluding DM1 and Lys-SMCC-DM1, the active catabolite of T-DM1 in lysosomes.…”

A Nanomedicine Structure–Activity Framework for Research, Development, and Regulation of Future Cancer Therapies

“…Most recently, Boehnke et al , combined ML and high-throughput screening to evaluate the influence of biological heterogeneity on NP delivery, an important consideration for the development of targeted and personalized nanomedicines. Using this approach, the authors were able to construct genomic and protein–protein interaction networks to identify several cellular biomarkers for NP uptake and subcellular trafficking . While further work is still needed to improve the training and validation of these models, these early results are key steps to improving nanomedicine development.…”

CRISPR nuclease off-target activity and mitigation strategies

“…Toward this end, many groups are working to improve specificity of the delivery modalities themselves. This includes screening for vectors or nanoparticles that have specific tissue tropisms, such as those optimized to cross the blood-brain-barrier, to transduce vascular tissue, and more ( White et al, 2004 ; Choudhury et al, 2016 ; Sago et al, 2018 ; Boehnke et al, 2022 ). There also are efforts to conjugate cell type-specific antibodies to delivery vectors to improve targeted in vivo delivery ( Tombácz et al, 2021 ).…”