Developing μSpherePlatform Using a Commercial Hairbrush: An Agarose 3D Culture Platform for Deep-Tissue Imaging of Prostate Cancer.

Abstract

Prostate-specific membrane antigen (PSMA) is a viable diagnostic biomarker for the detection and treatment of prostate cancer. Although numerous imaging techniques and fluorescent probes have been developed, targeted imaging and intraoperative surgery continue to remain as a proof-of-concept with a severe lack of tools having high affinity and penetrative capacity. In vitro three-dimensional cell culture has gained immense interest in cancer research and drug discovery programs as it yields important physiological information and serves an excellent model for bioimaging and penetration analysis studies. Current techniques employed in spheroid formation include liquid overlay and hanging drop methods, both of which are low-yielding and technically demanding. We describe for the first time a simple-to-use platform, μSpherePlatform, an inexpensive, high-throughput method yielding morphologically homogeneous spheroids in bulk for analyzing penetrative capacity and imaging ability of PCa diagnostics. Microwell arrays made of agarose have been fabricated using a commercial hairbrush as a master template. This procedure has been described in detail, and arrays of spheroids (100-120 spheroids/6-well plate) with >95% success rates have been produced from PCa cell lines (LNCaP and DU-145). A PSMA-targeted fluorescent conjugate was synthesized and evaluated in the spheroids developed using μSpherePlatform by multiphoton imaging. A synthetic 3D scaffold strategy is reported herein, which (1) correlates perfectly with the in vivo model, (2) is amenable for automated analysis, (3) shows a negligible lot to lot variation, (4) is simplistic, (5) is useful for high-throughput assays, (6) is extremely compatible with imaging techniques, (7) generates PCa spheroids within 48 h, and (8) forms large size-controllable spheroids of diameter 500-1300 μm. The μSpherePlatform thus provides a significant contribution to multimodal analyses of cancer diagnostics and deep-tissue imaging studies.