Combinatorial Drug Testing in 3D Microtumors Derived from GBM Patient-Derived Xenografts Reveals Cytotoxic Synergy in Pharmacokinomics-informed Pathway Interactions
SCIENTIFIC REPORTS(2018)
Abstract
Glioblastoma multiforme (GBM), the most common form of primary malignant brain cancer in adults, is a devastating disease for which effective treatment has remained elusive for over 75 years. One reason for the minimal progress during this time is the lack of accurate preclinical models to represent the patient’s tumor’s in vivo environment, causing a disconnect in drug therapy effectiveness between the laboratory and clinic. While patient-derived xenografts (PDX’s or xenolines) are excellent human tumor representations, they are not amenable to high throughput testing. Therefore, we developed a miniaturized xenoline system (microtumors) for drug testing. Nineteen GBM xenolines were profiled for global kinase (kinomic) activity revealing actionable kinase targets associated with intracranial tumor growth rate. Kinase inhibitors for these targets (WP1066, selumetinib, crizotinib, and cediranib) were selected for single and combination therapy using a fully human-derived three-dimensional (3D) microtumor model of GBM xenoline cells embedded in HuBiogel for subsequent molecular and phenotype assays. GBM microtumors closely resembled orthotopically-implanted tumors based on immunohistochemical analysis and displayed kinomic and morphological diversity. Drug response testing could be reproducibly performed in a 96-well format identifying several synergistic combinations. Our findings indicate that 3D microtumors can provide a suitable high-throughput model for combination drug testing.
MoreTranslated text
Key words
Cancer models,CNS cancer,Science,Humanities and Social Sciences,multidisciplinary
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined