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Cancer Cell Line Screen Identifies Biomarkers Linked to Uptake of Therapeutic Nanoparticles

NEW YORK — Through a new cell line screening approach, researchers have identified biomarkers that indicate whether a cancer therapeutic nanoparticle may interact with a certain cell.

Therapeutic nanoparticles can be used to deliver small molecule, biologic, or nucleic acid-based treatments directly to particular cells in the body of a cancer patient. But their use has been stymied by a limited understanding of how they interact with their target delivery sites.

By screening a library of nearly three dozen types of nanoparticles against hundreds of cancer cell lines, researchers from the Massachusetts Institute of Technology and elsewhere identified those that interact more strongly with certain cancer cell lines. As they reported this week in Science, the researchers further identified biomarkers that affect nanoparticle delivery to cells. In particular, they found that expression of SLC46A3 inversely predicted uptake of lipid-based nanoparticles.

"Our work establishes the power of integrated screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations," senior author Paula Hammond from MIT and her colleagues wrote in their paper.

The researchers designed their nanoPRISM (profiling relative inhibition simultaneously in mixtures) assay to screen for nanoparticles associated with certain cell lines. For this, they cultured pooled cells containing DNA barcodes — using the PRISM approach — with fluorescently labeled nanoparticles and used fluorescence-activated cell sorting (FACS) to bin the cells based on the strength of their association with nanoparticles. The screen encompassed 488 cancer cell lines and 35 different nanoparticle formulations.

Through further analyses, the researchers found that the core composition of the nanoparticles — whether they were liposomal, polylactide-co-glycolide, or polystyrene — was the main driver of their association with cancer cell lines. This, the researchers noted, was unexpected, as cell surface chemistry had instead been assumed to be the main predictor of cell-nanoparticle interactions.

By folding in cell lineage, mRNA, missense mutations, and other data from the Cancer Cell Line Encyclopedia, the researchers searched for cell line features that could further predict nanoparticle interactions. They homed in on highly significant biomarkers in the solute carrier (SLC) transporter and the ATP-binding cassette (ABC) families. ABCA1, they found, has a positive relationship with liposomal nanoparticles, while members of the ABC multidrug resistant subfamily have a negative relationship with polylactide-co-glycolide nanoparticles.

The researchers generated an algorithm based on gene copy number, gene expression, and protein abundance to uncover predictive biomarkers. Through this, they additionally found a strong, negative relationship between SLC46A3 and uptake of liposomal nanoparticles. SLC46A3, the researchers noted, is an understudied member of the SLC family that has been linked to lipid catabolism.

In further cell line-based analyses, the researchers found that overexpression of SLC46A3 led to decreased uptake of liposomes and that its modulation could influence that uptake.

They tested the in vivo delivery of a US Food and Drug Administration-approved liposomal nanoparticle analog in mice with subcutaneous melanoma cell line LOXIMVI tumors and noted an inverse relationship between SLC46A3 expression and retention of the nanoparticle analogs, underscoring their screen's real-world applicability.

In a related commentary appearing in Science, Ohio State University's Jessica Winter wrote that SLC46A3 biomarker testing could be used to identify patients who are more likely to respond to lipid-based nanotherapeutics.

She added that the nanoPRISM method employed in this analysis is a "substantial advance" over early approaches used in the nanoparticle field and noted that the method could be expanded to microfluidic, organ-on-a-chip, or organoid experiments to examine other barriers to nanoparticle delivery. "Thus, the nanoPRISM approach could catalyze rapid materials optimization, accelerating nanocarrier design and bringing the promise of cancer nanomedicine closer to reality," she wrote.