The goal of this K99/R00 proposal is to develop a new translational research framework whereby the role of the mechanical properties in tumor growth and molecular response are specifically exploited to design new photodynamic therapy (PDT) combination treatments for pancreatic cancer. Previous studies have shown that while the rigidity of the extracellular matrix surrounding cells directly impacts growth, development and signaling, the relevance of this crucial factor to treatment response has not yet been explored. This is particularly relevant for tumors of the pancreas which are characterized by a profound growth of dense fibrous tissue around the tumor (called desomplasia). In order to overcome this limitation in our scientific knowledge, this proposal introduces a highly interdisciplinary approach combining 1) fluorescence laser tracking microrheometry (FLTM) a novel optical technology to measure the mechanical properties (microrheology) in and around tumors, 2) a customizable three-dimensional (3D) tumor model system using a synthetic nanofiber scaffold called PuraMatrix"""""""" with tunable matrix mechanics, 3) a high-throughput quantitative imaging approach to report tumor growth properties and treatment response in relation to matrix mechanical properties. Dr. Celli will first optimize the 3D model system informed by studies on ex vivo tumors from orthotopic PanCa mice, to assess the impact of matrix rheology (measured by FLTM and traditional bulk rheology) on growth and development of 3D in vitro tumors. He will conduct PDT treatments and specific survival factors as potential targets for mechanism based combination treatments that are customized to each synthetic mechanical microenvironment. He will then evaluate the efficacy of the most promising combination treatments to test the hypothesis that only a treatment customized for the appropriate mechanical microenvironment will in fact achieve a synergistically enhanced efficacy in that environment. The research will culminate in testing of the most promising strategies in a mouse model of pancreatic cancer. If successful, this research will not only produce urgently needed new treatments for a deadly disease, but will also add a new level of understanding to guide the design of future treatments which could be applied to the study of other tumors. A mentoring committee has been assembled to guide the research in the K99 phase and facilitate Dr. Celli's training. Dr. Tayyaba Hasan, who is an expert in PDT treatment of cancer will provide primary mentorship and guidance in the overall study design. Co-Mentor, Dr. Peter So is a world expert in novel imaging technologies. He will guide Dr. Celli in FLTM measurements (which was developed in his laboratory) and help interpret results. Training in the molecular biology and treatment of pancreatic cancer will be provided by Dr. Nabeel Bardeesy and Dr. Stephen Pereira. Dr. Gareth McKinley will provide additional mentorship in rheology and microrheology. The opportunities provided by this award will not only allow Dr. Celli to pursue potentially ground-breaking research, but will also provide him with valuable mentorship and training to his career as an independent investigator.

Public Health Relevance

The proposed research is directly relevant to the treatment of pancreatic cancer with potentially broader application to other solid tumors. This work will shed new light on how the mechanical properties of the tumor stroma can guide the design of more effective therapeutic strategies. In the present study this concept will specifically be leveraged to design enhanced photodynamic therapy combination treatments which, upon translation into the clinic, could have a direct impact on survival and quality of life for patients with this lethal form of cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Career Transition Award (K99)
Project #
5K99CA155045-03
Application #
8310211
Study Section
Subcommittee G - Education (NCI)
Program Officer
Schmidt, Michael K
Project Start
2012-02-01
Project End
2013-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
3
Fiscal Year
2012
Total Cost
$144,019
Indirect Cost
$10,668
Name
University of Massachusetts Boston
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
808008122
City
Boston
State
MA
Country
United States
Zip Code
02125
Broekgaarden, Mans; Rizvi, Imran; Bulin, Anne-Laure et al. (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009-13022
Cramer, Gwendolyn M; Jones, Dustin P; El-Hamidi, Hamid et al. (2017) ECM Composition and Rheology Regulate Growth, Motility, and Response to Photodynamic Therapy in 3D Models of Pancreatic Ductal Adenocarcinoma. Mol Cancer Res 15:15-25
Jones, Dustin P; Hanna, William; El-Hamidi, Hamid et al. (2014) Longitudinal measurement of extracellular matrix rigidity in 3D tumor models using particle-tracking microrheology. J Vis Exp :
Celli, Jonathan P; Rizvi, Imran; Blanden, Adam R et al. (2014) An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci Rep 4:3751
Rizvi, Imran; Anbil, Sriram; Alagic, Nermina et al. (2013) PDT dose parameters impact tumoricidal durability and cell death pathways in a 3D ovarian cancer model. Photochem Photobiol 89:942-52
Rizvi, Imran; Gurkan, Umut A; Tasoglu, Savas et al. (2013) Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules. Proc Natl Acad Sci U S A 110:E1974-83
Bonfert-Taylor, Petra; Leblond, Frederic; Holt, Robert W et al. (2012) Information loss and reconstruction in diffuse fluorescence tomography. J Opt Soc Am A Opt Image Sci Vis 29:321-30
Celli, Jonathan P (2012) Stromal interactions as regulators of tumor growth and therapeutic response: A potential target for photodynamic therapy? Isr J Chem 52:757-766
Glidden, Michael D; Celli, Jonathan P; Massodi, Iqbal et al. (2012) Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters. Theranostics 2:827-39