This study showed that tDC therapy in a preclinical model of MI was potentially translatable into an antiremodeling therapy for ischemic tissue repair.

Transforming growth factor-β (TGF-β) is a pluripotent cytokine that regulates cell fate and plasticity in normal tissues and tumors. The multifunctional cellular responses evoked by TGF-β are mediated by the canonical SMAD pathway and by noncanonical pathways, including mitogen-activated protein kinase (MAPK) pathways and the phosphatidylinositol 3'-kinase (PI3K)-protein kinase B (AKT) pathway. We found that TGF-β activated PI3K in a manner dependent on the activity of the E3 ubiquitin ligase tumor necrosis factor receptor-associated factor 6 (TRAF6). TRAF6 polyubiquitylated the PI3K regulatory subunit p85α and promoted the formation of a complex between the TGF-β type I receptor (TβRI) and p85α, which led to the activation of PI3K and AKT. Lys-linked polyubiquitylation of p85α on Lys and Lys in the iSH2 (inter-Src homology 2) domain was required for TGF-β-induced activation of PI3K-AKT signaling and cell motility in prostate cancer cells and activated macrophages. Unlike the activation of SMAD pathways, the TRAF6-mediated activation of PI3K and AKT was not dependent on the kinase activity of TβRI. In situ proximity ligation assays revealed that polyubiquitylation of p85α was evident in aggressive prostate cancer tissues. Thus, our data reveal a molecular mechanism by which TGF-β activates the PI3K-AKT pathway to drive cell migration.

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Subjective methods have been reported to adapt a general-purpose ontology for a specific application. For example, Gene Ontology (GO) Slim was created from GO to generate a highly aggregated report of the human-genome annotation. We propose statistical methods to adapt the general purpose, OBO Foundry Disease Ontology (DO) for the identification of gene-disease associations. Thus, we need a simplified definition of disease categories derived from implicated genes. On the basis of the assumption that the DO terms having similar associated genes are closely related, we group the DO terms based on the similarity of gene-to-DO mapping profiles. Two types of binary distance metrics are defined to measure the overall and subset similarity between DO terms. A compactness-scalable fuzzy clustering method is then applied to group similar DO terms. To reduce false clustering, the semantic similarities between DO terms are also used to constrain clustering results. As such, the DO terms are aggregated and the redundant DO terms are largely removed. Using these methods, we constructed a simplified vocabulary list from the DO called Disease Ontology Lite (DOLite). We demonstrated that DOLite results in more interpretable results than DO for gene-disease association tests. The resultant DOLite has been used in the Functional Disease Ontology (FunDO) Web application at http://www.projects.bioinformatics.northwestern.edu/fundo.Contact: s-lin2@northwestern.edu