A major barrier to treating advanced-stage cancers is heterogeneity in the responsiveness of metastatic disease to conventional therapies leading to resistance and treatment failure. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Developing PDT-based combinations that target resistant tumor populations and cooperate mechanistically with conventional agents is an increasingly promising approach to improve therapeutic efficacy while minimizing toxicity, particularly in complex disease sites. Identifying the molecular, cellular, and microenvironmental cues that lead to heterogeneity and treatment resistance is critical to developing strategies to target unresponsive regions of stubborn disease. Cell-based research platforms that integrate key microenvironmental cues are emerging as increasingly important tools to improve the translational efficiency of new agents, and to design combination regimens. Among the challenges associated with developing and scaling complex cell-based screening platforms is the need to integrate, and balance, biological relevance with appropriate, high-content imaging routines that provide meaningful quantitative readouts of therapeutic response. The benefits and challenges associated with deriving meaningful insights from complex cell-based models will be presented, with a particular emphasis on overcoming chemoresistance mediated by physical stress and communication with stromal partners (e.g. tumor endothelial cells, which are emerging as dynamic regulators of treatment resistance) using PDT-based combinations.

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Imran Rizvi, Emma A. Briars, Anne-Laure Bulin, Sriram Anbil, Daniela Vecchio, Ahmed Alkhateeb, William R. Hanna, Jonathan P. Celli, and Tayyaba Hasan, "Designing PDT-based combinations to overcome chemoresistance in heterocellular 3D tumor models (Conference Presentation)," Proc. SPIE 9694, Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXV, 969404 (Presented at SPIE BiOS: February 13, 2016; Published: 26 April 2016); https://doi.org/10.1117/12.2213436.4848635773001.