Multiparametric Analysis of Oncology Drug Screening with Aqueous Two-Phase Tumor Spheroids.

Abstract

Spheroids present a biologically relevant three-dimensional model of avascular tumors and a unique tool for discovery of anticancer drugs. Despite being used in research laboratories for several decades, spheroids are not routinely used in the mainstream drug discovery pipeline primarily due to the difficulty of mass-producing uniformly sized spheroids and intense labor involved in handling, drug treatment, and analyzing spheroids. We overcome this barrier using a polymeric aqueous two-phase microtechnology to robotically microprint spheroids of well-defined size in standard 384-microwell plates. We use different cancer cells and show that resulting spheroids grow over time and display characteristic features of solid tumors. We demonstrate the feasibility of robotic, high-throughput screening of 25 standard chemotherapeutics and molecular inhibitors against tumor spheroids of three different cancer cell lines. This screening uses over 7000 spheroids to elicit high quality dose-dependent drug responses from spheroids. To quantitatively compare performance of different drugs, we employ a multiparametric scoring system using half-maximum inhibitory concentration (IC50), maximum inhibition (Emax), and area under the dose-response curve (AUC) to take into account both potency and efficacy parameters. This approach allows us to identify several compounds that effectively inhibit growth of spheroids and compromise cellular viability, and distinguish them from moderately effective and ineffective drugs. Using protein expression analysis, we demonstrate that spheroids generated with the aqueous two-phase microtechnology reliably resolve molecular targets of drug compounds. Incorporating this low-cost and convenient-to-use tumor spheroid technology in preclinical drug discovery will make compound screening with realistic tumor models a routine laboratory technique prior to expensive and tedious animal tests to dramatically improve testing throughput and efficiency and reduce costs of drug discovery.