Supplementary Video 5 from The Role of Transforming Growth Factor-β–Mediated Tumor-Stroma Interactions in Prostate Cancer Progression: An Integrative Approach

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Supplementary Video 2 from The Role of Transforming Growth Factor-β–Mediated Tumor-Stroma Interactions in Prostate Cancer Progression: An Integrative Approach

Supplementary Video 3 from The Role of Transforming Growth Factor-β–Mediated Tumor-Stroma Interactions in Prostate Cancer Progression: An Integrative Approach

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The objective was to identify the usefulness of heparin level by anti-factor Xa (anti-Xa) assay vs activated partial thromboplastin time (PTT) or activated clotting time (ACT) in neonates undergoing extracorporeal membrane oxygenation (ECMO). A retrospective record review of 21 patients in the neonatal intensive care unit (mean ECMO initiation age, 2 days; range, 0-4 days; male/female ratio, 1:1) undergoing ECMO from 2006 to 2008 was performed. Linear regression correlations between anti-Xa, PTT, and ACT were determined by extrapolating PTT and ACT therapeutic ranges that corresponded with the ECMO heparin target range of 0.3 to 0.6 U/mL. Pearson correlation coefficients between heparin levels and PTT (-0.903 to 0.984), PTT less than 40 seconds after correction using PTT-heparinase (-0.903 to 1.000), and ACT (-0.951 to 0.891) in this patient population were widely variable. Inconsistency of PTT and ACT therapeutic ranges corresponding to heparin levels of 0.3 to 0.6 U/mL prompts a multifactorial approach to ECMO management because no single laboratory test can be used to determine appropriate anticoagulation management.

Abstract We have implemented a hybrid cellular automata model based on the structure of human prostate that recapitulates key interactions in nascent tumor foci between tumor cells and adjacent stroma. Model simulations show how stochastic interactions between tumor cells and stroma may lead to a structural suppression of tumor growth, modest proliferation, or unopposed tumor growth. The model incorporates key aspects of prostate tumor progression, including transforming growth factor-β (TGF-β), matrix-degrading enzyme activity, and stromal activation. It also examines the importance of TGF-β during tumor progression and the role of stromal cell density in regulating tumor growth. The validity of one of the key predictions of the model about the effect of epithelial TGF-β production on glandular stability was tested in vivo. These experimental results confirmed the ability of the model to generate testable biological predictions in addition to providing new avenues of experimental interest. This work underscores the need for more pathologically representative models to cooperatively drive computational and biological modeling, which together could eventually lead to more accurate diagnoses and treatments of prostate cancer. [Cancer Res 2009;69(17):7111–20]