Somatic mutation detection from liquid biopsy-derived cellular aggregates formed by magnetic 3D bioprinting.

Abstract

291 Background: A challenge in the analysis of circulating tumor cells (CTC) is their scarcity, and the inability to expand them for further analysis. To overcome this obstacle, we used magnetic 3D bioprinting to form CTC spheroids that could grow. The principle of magnetic 3D bioprinting is the magnetization of cells with nanoparticles and their subsequent printing into spheroids. For this project, CTCs can be aggregated into close contact to interact and grow in culture. In this study, we demonstrated the ability to aggregate CTCs and perform next generation sequencing (NGS) to detect somatic mutations from renal and prostate cancers. Methods: Blood samples from prostate and kidney cancer patients were enriched for CTCs (Isoflux, Fluxion), from a starting blood volume of 7.5-14 mL. CTCs were isolated immunomagnetically for EpCAM+ EGFR+ cells, then enumerated for CK+ CD45-. The cells were then removed of microbeads, then magnetized by incubation with NanoShuttle (NS, Nano3D), a magnetic nanoparticle assembly, and printed into spheroids in 384-well plates. After 4 d of growth, the cells were lysed and DNA was amplified by whole genome amplificaiton (WGA) with the NGS kit (Fluxion) and quantified via qPCR. Targeted libraries were sequenced using the PGM (ThermoFisher) sequencing instrument; data was analyzed using a customized variant calling/filtering pipeline based on standard Ion Reporter alignment tools and VarSeq for variant filtering and functional interpretation. Results: CTCs were successfully aggregated using magnetic 3D bioprinting, and grew over 4 d. We then demonstrated the detection of somatic variants within a majority of the samples, for both prostate and renal cancers. Using the commercial Oncomine, we found a median of 5 COSMIC variants (32 total) per sample using cell cultures. Conclusions: We successfully developed methods to aggregate CTCs with magnetic 3D bioprinting, expanded them, and then detected somatic mutations using NGS.