Abstract 2431: Inhibition of metastasis through therapeutic targeting of focal adhesion kinase (FAK) in pancreatic cancer
Bibliographic record
Abstract
Abstract BACKGROUND: Cancer mortality is primarily caused by metastatic disease; it has therefore been suggested that the preclinical evaluation of novel therapies should include testing in metastatic models of disease. This is especially relevant in light of recent reports of both conventional and targeted therapies being associated with accelerated metastases despite maintenance of primary tumor control. Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase which also acts as molecular scaffold, and localizes to focal adhesions, contact points between the cell and the extra-cellular matrix. Downstream of integrins and transmembrane receptors, FAK acts as a signaling hub, participating in processes integral to tumor progression including cell survival, proliferation, angiogenesis, migration and invasion. In this ongoing study, we explore the efficacy of selective genetic and pharmacologic FAK inhibition in preclinical models of human pancreatic cancer, including spontaneously metastasizing, cell-line derived and primary xenografts. METHODS & RESULTS: We constructed modified pancreatic cancer cell lines using retroviral over-expression of the dominant negative FRNK (FAK related non-kinase). Pharmacologic inhibition of FAK was performed with PF-562271 (Pfizer), a selective FAK/Pyk2 inhibitor which recently completed Phase I testing. Adhesion, invasion and migration in vitro assays were conducted using the xCELLigence RTCA system. In vivo efficacy of FAK inhibition was evaluated in orthotopic xenograft models. In vitro studies demonstrated that both modalities of FAK inhibition resulted in impaired adhesion, invasion and migration and 3D colony formation, without comparable effects on viability, proliferation or colony formation in 2D. Expression of dominant-negative FRNK resulted in 49% smaller xenograft tumors (p=0.003), a 78% reduction in metastatic disease (p< 0.001) and longer overall survival (p < 0.001). There was a similar, 46% trend to reduction of metastatic burden (p=0.089) in orthotopic cell line xenograft models treated with PF-562271, despite a lack of significant primary tumor growth delay. CONCLUSIONS: Our data suggest a potential utility of selective FAK inhibition in delaying metastatic progression of pancreatic cancer. This is particularly relevant clinically since patients frequently present with locally advanced, unresectable disease and subsequently develop metastases. Pharmacologic FAK inhibition (in combination with conventional therapies) is currently being evaluated in neo/adjuvant models of this disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2431. doi:10.1158/1538-7445.AM2011-2431
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".