Drug screening at single-organoid resolution via bioprinting and interferometry

Abstract

There is increasing interest in leveraging tumor organoids for high-throughput drug screenings to investigate tumor biology and identify therapeutic leads. However, functional precision medicine platforms are limited by the difficulties of creating, scaling, and analyzing physiological disease models. Most systems use manually seeded organoids and take advantage of destructive endpoint assays to rapidly characterize response to treatment. These approaches fail to capture transitory changes and intra-sample heterogeneity that underlies much of the clinically observed resistance to therapy. We therefore developed bioprinted tumor organoids linked to real-time growth pattern quantitation via high-speed live cell interferometry (HSLCI). We demonstrate that bioprinting gives rise to 3D organoid structures that preserve histology and gene expression. These are suitable for imaging with HSLCI, enabling accurate parallel mass measurements for thousands of bioprinted organoids. In drug screening experiments, HSLCI rapidly identifies organoids transiently or persistently sensitive or resistant to specific therapies. We show that our approach can provide detailed, actionable information to guide rapid therapy selection.

Organoids

“…Technical challenges to rapid and high-throughput screening of 3D organoids have been addressed in recent years and surpassed by different means, including alternative plate design or seeding geometries 15,150,151 .…”

A rapid platform for 3D patient-derived cutaneous neurofibroma organoid establishment and screening

“…We can leverage this system to screen several tens ( Figure 5 ) to hundreds of compounds 23,24 and interrogate a broad range of biological pathways 24 . Given the heterogenous cellular composition of cNFs, it will be important to incorporate assays that distinguish cell types so to determine the effects that drugs have on each distinct population 45,48 .…”

“…Given the established growth conditions, we determine feasibility to perform medium-to high-throughput drug screening on cNF benign tumor organoids. Using our established organoid screening paradigm and mini-ring platform [23][24][25]45 , we tested n=43 targeted kinase inhibitors on cNF organoids established from two patients (Figure 5). NF0009 were tested in StemPro with cytokines while NF0012 was tested in StemPro with cytokines and forskolin.…”

“…We performed RNA-seq on primary tumor samples together with organoids grown in Mammocult, StemPro, and DMEM to measure the transcriptional changes that occur in the various environments. RNA was extracted from 100K cells after a 6-day growth period as organoids according to our established protocol 45 . Index-tagged sequencing libraries were prepared and sequenced by the UCLA Technology Center for Genomics & Bioinformatics (TCGB) Facility using a NovaSeq 6000 S4.…”

Machine learning boosts three-dimensional bioprinting

“…Experimental results showed that the method could 346 effectively detect quality errors during 3D bioprinting, and a bigger error signified that a higher detection accuracy was reached. Tebon et al [ 91 ] utilized a conventional neural network to detect high-throughput drug screening problems in 3D-bioprinted organs. A quantitative phase imaging technology was employed to obtain relevant images.…”