3D ex vivo platform for microfluidic drug screening of biopsy-derived multicellular spheroids


The use of three-dimensional (3D) ex vivo platforms as a tool for drug screening and profiling has rapidly increased in recent years due to the need of testing targeted drugs in mimicked tumour microenvironment conditions. However, developing physiologically relevant 3D tumour models for personalized medicine remain challenging due to the availability of limited amount of biopsy material. New microfluidic technologies are enabling new miniaturized screening solutions, allowing extensive testing of anticancer agents on human tumor tissue preparations in 3D. We have developed a microfluidic platform for drug screening and profiling utilizing  prostate cancer patient-derived tumor samples.

The biopsy tissue was dissociated into a single cell suspension consisting of tumor cells, stromal cells and immune cells. Cell samples were seeded in the microfluidics device and allowed to grow for 3-5 days during which the cells self-organized into multicellular spheroids. Subsequently, the spheroids were treated with a panel of standard-of-care drugs for prostate cancer. All readouts were obtained via bright-field and epifluorescence microscopy. The microfluidic platform has been designed to be operated entirely without the need of external equipment, such as syringe pumps, generating stable drug concentration gradients across arrays of 240 spheroids per device. Outcomes were generated as 8-point drug concentration response curves per device, with each drug concentration tested on at least 24 spheroids. Custom developed software was used to analyze bright-field and fluorescent images to provide clinically relevant end point measurements, such as spheroid growth and viability.

This study was carried out comparing standard prostate cancer cell lines with prostate biopsies from 2 different patients. Spheroids were sensitive to docetaxel, but resistant to enzalutamide, despite the presence of intact androgen receptors. This preliminary data outlines how this technology could become a useful tool to investigate patient-specific inherent or acquired drug resistance and to test novel anticancer agents in a cost-effective manner in a 3D format.

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