Primary Cell 3D Pancreatic Cancer Organoid Models for Phenotypic High-throughput Therapeutic Screening

Recorded On: 02/05/2018

Pancreatic cancer remains a leading cause of cancer-associated death, with a median survival of ~ 6 months and 5-year survival rate less than 8%. The tumor microenvironment promotes tumor initiation and progression, and is associated to cancer metastasis and drug resistance. Traditional high throughput screening (HTS) assays for drug discovery use lab adapted 2D monolayer cancer cell models, which inadequately recapitulate the physiologic context of cancer. Primary cell 3D cell culture models have recently received renewed recognition not only due to their ability to better mimic the complexity of in vivo tumors but, are now cost effective and efficient. Here we describe phenotypically relevant 3D cell culture in ultra-low-attachment high density 384 and 1536 well plates using a magnetic force-based bioprinting technology. We have validated HTS amenable 2D and 3D spheroid/organoid-based cytotoxicity assays using 4 pancreatic cancer-associated cell lines against 5 known anti-cancer agents, and thereby screened ~3,400 drugs from Approved Drug and National Cancer Institute (NCI) collections. Assay quality was notable with Z’ averaging >0.8 across all assays and cell lines. As anticipated, results from the 3D screen were significantly different from the parallel screen performed on 2D cell monolayers. Collectively, these data indicate that a complex 3D cell culture can be adapted for quantitative HTS and may improve the disease relevance of assays used for therapeutic screening. Further analysis provides a basis for expedited translation into clinical study due to their well-known pharmacology in humans.

Shurong Hou

The Scripps Research Institute - FL

Shurong Hou is a postdoctoral fellow in The Scripps Research Institute Molecular Screening Center, who has dedicated herself to early drug discovery. She is interested in assay development of biochemical and cell-based assays for high throughput screening, especially developing physiologically relevant 3D tumor models for cancer drug discovery.

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