Multipathway kinase signatures of multipotent stromal cells are predictive for osteogenic differentiation: tissue-specific stem cells.
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ABSTRACT: Bone marrow-derived multipotent stromal cells (MSCs) offer great promise for regenerating tissue. Although certain transcription factors have been identified in association with tendency toward particular MSC differentiation phenotypes, the regulatory network of key receptor-mediated signaling pathways activated by extracellular ligands that induce various differentiation responses remains poorly understood. Attempts to predict differentiation fate tendencies from individual pathways in isolation are problematic due to the complex pathway interactions inherent in signaling networks. Accordingly, we have undertaken a multivariate systems approach integrating experimental measurement of multiple kinase pathway activities and osteogenic differentiation in MSCs, together with computational analysis to elucidate quantitative combinations of kinase signals predictive of cell behavior across diverse contexts. In particular, for culture on polymeric biomaterial surfaces presenting tethered epidermal growth factor, type I collagen, neither, or both, we have found that a partial least-squares regression model yields successful prediction of phenotypic behavior on the basis of two principal components comprising the weighted sums of eight intracellular phosphoproteins: phospho-epidermal growth factor receptor, phospho-Akt, phospho-extracellular signal-related kinase 1/2, phospho-heat shock protein 27, phospho-c-Jun, phospho-glycogen synthase kinase 3alpha/beta, phospho-p38, and phospho-signal transducer and activator of transcription 3. This combination provides the strongest predictive capability for 21-day differentiated phenotype status when calculated from day-7 signal measurements; day-4 and day-14 signal measurements are also significantly predictive, indicating a broad time frame during MSC osteogenesis wherein multiple pathways and states of the kinase signaling network are quantitatively integrated to regulate gene expression, cell processes, and ultimately, cell fate.
SUBMITTER: Platt MO
PROVIDER: S-EPMC2976759 | biostudies-literature | 2009 Nov
REPOSITORIES: biostudies-literature
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