Anti-Human GSK3B (a.a. 1-420) Polyclonal antibody

Although humans with X-linked hypophosphatemia (XLH) and the Hyp mouse, a murine homolog of XLH, are known to develop degenerative joint disease, the exact mechanism that drives the osteoarthritis (OA) phenotype remains unclear. Mice that overexpress high-molecular-weight fibroblast growth factor (FGF) 2 isoforms (HMWTg mice) phenocopy both XLH and Hyp, including OA with increased FGF23 production in bone and serum. Because HMWTg cartilage also has increased FGF23 and there is cross-talk between FGF23-Wnt/beta-catenin signaling, the purpose of this study was to determine if OA observed in HMWTg mice is due to FGF23-mediated canonical Wnt signaling in chondrocytes, given that both pathways are implicated in OA pathogenesis. HMWTg OA joints had decreased Dkk1, Sost, and Lrp6 expression with increased Wnt5a, Wnt7b, Lrp5, Axin2, phospho-GSK3b, Lef1, and nuclear beta-catenin, as indicated by immunohistochemistry or quantitative PCR analysis. Chondrocytes from HMWTg mice had enhanced alcian blue and alkaline phosphatase staining as well as increased FGF23, Adamts5, Il-1 beta, Wnt7b, Wnt16, and Wisp1 gene expression and phospho-GSK3 beta protein expression as indicated by Western blot, compared with chondrocytes of vector control and chondrocytes from mice overexpressing the low-molecular-weight isoform, which were protected from OA. Canonical Wnt inhibitor treatment rescued some of those parameters in HMWTg chondrocytes, seemingly delaying the initially accelerated chondrogenic differentiation. FGF23 neutralizing antibody treatment was able to partly ameliorateOA abnormalities in subchondral bone and reduce degradative/hypertrophic chondrogenic marker expression in HMWTg joints in vivo. These results demonstrate that osteoarthropathy of HMWTg is at least partially due to FGF23modulated Wnt/beta-catenin signaling in chondrocytes.

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS(2). The L1000CDS(2) search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS(2) search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS(2) to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS(2), we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS(2) we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS(2) tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.