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Image-based profiling of patient-derived pancreatic tumor–stromal cell interactions within a micropatterned tumor model

Shilpaa Mukundan, Kriti Sharma, Kim Honselmann, Amy Singleton, Andrew Liss, Biju Parekkadan*

*Corresponding author for this work

Abstract

Pancreatic cancer is one of the most aggressive cancers with a 5-year patient survival rate of 8.2% and limited availability of therapeutic agents to target metastatic disease. Pancreatic cancer is characterized by a dense stromal cell population with unknown contribution to the progression or suppression of tumor growth. In this study, we describe a microengineered tumor stromal assay of patient-derived pancreatic cancer cells to study the heterotypic interactions of patient pancreatic cancer cells with different types of stromal fibroblasts under basal and drug-treated conditions. The population dynamics of tumor cells in terms of migration and viability were visualized as a functional end point. Coculture with cancer-associated fibroblasts increased the migration of cancer cells when compared to dermal fibroblasts. Finally, we imaged the response of a bromodomain and extraterminal inhibitor on the viability of pancreatic cancer clusters surrounding by stroma in microengineered tumor stromal assay. We visualized a codynamic reduction in both cancer and stromal cells with bromodomain and extraterminal treatment compared to the dimethyl sulfoxide-treated group. This study demonstrates the ability to engineer tumor–stromal assays with patient-derived cells, study the role of diverse types of stromal cells on cancer progression, and precisely visualize a coculture during the screening of therapeutic compounds.

Original languageEnglish
JournalTechnology in Cancer Research and Treatment
Volume17
ISSN1533-0346
DOIs
Publication statusPublished - 01.01.2018

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by the Shriners Hospitals for Children (BP), and National Institutes of Health grant R01EB012521 (BP).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Areas and Centers

  • Research Area: Luebeck Integrated Oncology Network (LION)

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