In Vitro and In Vivo Drug-Response Profiling Using Patient-Derived High-Grade Glioma.

BACKGROUND: Genomic profiling cannot solely predict the complexity of how tumor cells behave in their in vivo microenvironment and their susceptibility to therapies. The aim of the study was to establish a functional drug prediction model utilizing patient-derived GBM tumor samples for in vitro testing of drug efficacy followed by in vivo validation to overcome the disadvantages of a strict pharmacogenomics approach. METHODS: High-throughput in vitro pharmacologic testing of patient-derived GBM tumors cultured as 3D organoids offered a cost-effective, clinically and phenotypically relevant model, inclusive of tumor plasticity and stroma. RNAseq analysis supplemented this 128-compound screening to predict more efficacious and patient-specific drug combinations with additional tumor stemness evaluated using flow cytometry. In vivo PDX mouse models rapidly validated (50 days) and determined mutational influence alongside of drug efficacy. We present a representative GBM case of three tumors resected at initial presentation, at first recurrence without any treatment, and at a second recurrence following radiation and chemotherapy, all from the same patient. RESULTS: Molecular and in vitro screening helped identify effective drug targets against several pathways as well as synergistic drug combinations of cobimetinib and vemurafenib for this patient, supported in part by in vivo tumor growth assessment. Each tumor iteration showed significantly varying stemness and drug resistance. CONCLUSIONS: Our integrative model utilizing molecular, in vitro, and in vivo approaches provides direct evidence of a patient's tumor response drifting with treatment and time, as demonstrated by dynamic changes in their tumor profile, which may affect how one would address that drift pharmacologically.

Lead identification using 3D models of pancreatic cancer.

Recent technological advances have enabled 3D tissue culture models for fast and affordable HTS. We are no longer bound to 2D models for anti-cancer agent discovery, and it is clear that 3D tumor models provide more predictive data for translation of preclinical studies. In a previous study, we validated a microplate 3D spheroid-based technology for its compatibility with HTS automation. Small-scale screens using approved drugs have demonstrated that drug responses tend to differ between 2D and 3D cancer cell proliferation models. Here, we applied this 3D technology to the first ever large-scale screening effort completing HTS on over 150K molecules against primary pancreatic cancer cells. It is the first demonstration that a screening campaign of this magnitude using clinically relevant, ex-vivo 3D pancreatic tumor models established directly from biopsy, can be readily achieved in a fashion like traditional drug screen using 2D cell models. We identified four unique series of compounds with sub micromolar and even low nanomolar potency against a panel of patient derived pancreatic organoids. We also applied the 3D technology to test lead efficacy in autologous cancer associated fibroblasts and found a favorable profile for better efficacy in the cancer over wild type primary cells, an important milestone towards better leads. Importantly, the initial leads have been further validated in across multiple institutes with concordant outcomes. The work presented here represents the genesis of new small molecule leads found using 3D models of primary pancreas tumor cells.

Automating a Magnetic 3D Spheroid Model Technology for High-Throughput Screening.

Affordable and physiologically relevant three-dimensional (3D) cell-based assays used in high-throughput screening (HTS) are on the rise in early drug discovery. These technologies have been aided by the recent adaptation of novel microplate treatments and spheroid culturing techniques. One such technology involves the use of nanoparticle (NanoShuttle-PL) labeled cells and custom magnetic drives to assist in cell aggregation to ensure rapid 3D structure formation after the cells have been dispensed into microtiter plates. Transitioning this technology from a low-throughput manual benchtop application, as previously published by our lab, into a robotically enabled format achieves orders of magnitude greater throughput but required the development of specialized support hardware. This effort included in-house development, fabrication, and testing of ancillary devices that assist robotic handing and high-precision placement of microtiter plates into an incubator embedded with magnetic drives. Utilizing a "rapid prototyping" approach facilitated by cloud-based computer-aided design software, we built the necessary components using hobby-grade 3D printers with turnaround times that rival those of traditional manufacturing/development practices at a substantially reduced cost. This approach culminated in a first-in-class HTS-compatible 3D system in which we have coupled 3D bioprinting to a fully automated HTS robotic platform utilizing our novel magnetic incubator shelf assemblies.

Advanced Development of Primary Pancreatic Organoid Tumor Models for High-Throughput Phenotypic Drug Screening.

Traditional high-throughput drug screening in oncology routinely relies on two-dimensional (2D) cell models, which inadequately recapitulate the physiologic context of cancer. Three-dimensional (3D) cell models are thought to better mimic the complexity of in vivo tumors. Numerous methods to culture 3D organoids have been described, but most are nonhomogeneous and expensive, and hence impractical for high-throughput screening (HTS) purposes. Here we describe an HTS-compatible method that enables the consistent production of organoids in standard flat-bottom 384- and 1536-well plates by combining the use of a cell-repellent surface with a bioprinting technology incorporating magnetic force. We validated this homogeneous process by evaluating the effects of well-characterized anticancer agents against four patient-derived pancreatic cancer KRAS mutant-associated primary cells, including cancer-associated fibroblasts. This technology was tested for its compatibility with HTS automation by completing a cytotoxicity pilot screen of ~3300 approved drugs. To highlight the benefits of the 3D format, we performed this pilot screen in parallel in both the 2D and 3D assays. These data indicate that this technique can be readily applied to support large-scale drug screening relying on clinically relevant, ex vivo 3D tumor models directly harvested from patients, an important milestone toward personalized medicine.