Presentation
19 April 2017 PDT-based combinations in overcoming chemoresistance from stromal and heterotypic cellular communication (Conference Presentation)
Imran Rizvi, Anne-Laure Bulin, Sriram R. Anbil, Emma A. Briars, Daniela Vecchio, Jonathan P. Celli, Mans Broekgaarden, Tayyaba Hasan
Author Affiliations +
Abstract
Targeting the molecular and cellular cues that influence treatment resistance in tumors is critical to effectively treating unresponsive populations of stubborn disease. The informed design of mechanism-based combinations is emerging as increasingly important to targeting resistance and improving the efficacy of conventional treatments, while minimizing toxicity. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Increasing evidence shows that PDT-based combinations cooperate mechanistically with, and improve the therapeutic index of, traditional chemotherapies. These and other findings emphasize the importance of including PDT as part of comprehensive treatment plans for cancer, particularly in complex disease sites. Identifying effective combinations requires a multi-faceted approach that includes the development of bioengineered cancer models and corresponding image analysis tools. The molecular and phenotypic basis of verteporfin-mediated PDT-based enhancement of chemotherapeutic efficacy and predictability in complex 3D models for ovarian cancer will be presented.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Imran Rizvi, Anne-Laure Bulin, Sriram R. Anbil, Emma A. Briars, Daniela Vecchio, Jonathan P. Celli, Mans Broekgaarden, and Tayyaba Hasan "PDT-based combinations in overcoming chemoresistance from stromal and heterotypic cellular communication (Conference Presentation)", Proc. SPIE 10047, Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXVI, 1004705 (19 April 2017); https://doi.org/10.1117/12.2252685
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KEYWORDS
Photodynamic therapy

3D modeling

Resistance

Tumor growth modeling

Cancer

Image analysis

Oncology

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