4.6 Article

Applying Small Molecule Signal Transducer and Activator of Transcription-3 (STAT3) Protein Inhibitors as Pancreatic Cancer Therapeutics

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MOLECULAR CANCER THERAPEUTICS
卷 15, 期 5, 页码 794-805

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AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1535-7163.MCT-15-0003

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  1. NIH [NCI CA167291]
  2. IUSCC ITRAC basic science pilot funding mechanism, Indiana Clinical Translational Science Institute, Project Development Team within the ICTSI NIH/NCRR [UL1TR001108]
  3. Jeff Gordon Children's Foundation
  4. CIHR
  5. Leukemia and Lymphoma Society
  6. Canada Research Chair Program
  7. Alberta Innovates
  8. Canadian Foundation for Innovation
  9. MITACS post-doctoral fellowship

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Constitutively activated STAT3 protein has been found to be a key regulator of pancreatic cancer and a target for molecular therapeutic intervention. In this study, PG-S3-001, a small molecule derived from the SH-4-54 class of STAT3 inhibitors, was found to inhibit patient-derived pancreatic cancer cell proliferation in vitro and in vivo in the low micromolar range. PG-S3-001 binds the STAT3 protein potently, K-d = 324 nmol/L by surface plasmon resonance, and showed no effect in a kinome screen (>100 cancer-relevant kinases). In vitro studies demonstrated potent cell killing as well as inhibition of STAT3 activation in pancreatic cancer cells. To better model the tumor and its microenvironment, we utilized three-dimensional (3D) cultures of patient-derived pancreatic cancer cells in the absence and presence of cancer-associated fibroblasts (CAF). In this coculture model, inhibition of tumor growth is maintained following STAT3 inhibition in the presence of CAFs. Confocal microscopy was used to verify tumor cell death following treatment of 3D cocultures with PG-S3-001. The 3D model was predictive of in vivo efficacy as significant tumor growth inhibition was observed upon administration of PG-S3-001. These studies showed that the inhibition of STAT3 was able to impact the survival of tumor cells in a relevant 3D model, as well as in a xenograft model using patient-derived cells. (C)2016 AACR.

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