Dataset Information

Mesenchymal-like stem cells in canine ovary show high differentiation potential.

ABSTRACT: OBJECTIVES:Recent studies have reported the existence of stem cells in ovarian tissue that show enhanced proliferative and differentiation potential compared to other adult tissues. Based on this evidence, we hypothesized that ovarian tissue contained mesenchymal-like stem cells (MSC) that could be isolated using a novel rapid plastic adhesion technique. MATERIALS AND METHODS:We established MSC lines derived from ovarian and adipose tissue based on their ability to rapidly adhere to plastic culture dishes in the first 3 hours after plating and studied their potentiality in terms of molecular markers and differentiation capacity. RESULTS:Morphological and kinetic properties of in vitro cultured ovarian MSC were similar to adipose-derived MSC, and both reached senescence after similar passage numbers. Ovarian-derived MSC expressed mesenchymal (CD90 and CD44) but not haematopoietic markers (CD34 and CD45), indicating similarity to adipose-derived MSC. Moreover, ovarian-derived MSC expressed NANOG, TERT, SOX2, OCT4 and showed extensive capacity to differentiate not only into adipogenic, osteogenic and chondrogenic tissue but also towards neurogenic and endodermal lineages and even precursors of primordial germ cells. CONCLUSION:These results show for the first time the derivation of ovarian cells with the molecular properties of MSC as well as wide differentiation potential. Canine ovarian tissue is accessible, expandable, multipotent and has high plasticity, holding promise for applications in regenerative medicine.

SUBMITTER: Trindade AB

PROVIDER: S-EPMC6529137 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Mesenchymal-like stem cells in canine ovary show high differentiation potential.

Trindade A B AB Therrien J J Garcia J M JM Smith L C LC

Cell proliferation 20171008 6

<h4>Objectives</h4>Recent studies have reported the existence of stem cells in ovarian tissue that show enhanced proliferative and differentiation potential compared to other adult tissues. Based on this evidence, we hypothesized that ovarian tissue contained mesenchymal-like stem cells (MSC) that could be isolated using a novel rapid plastic adhesion technique.<h4>Materials and methods</h4>We established MSC lines derived from ovarian and adipose tissue based on their ability to rapidly adhere ...[more]

PMID: 28990287

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Project description:Human bone marrow mesenchymal stem cells (hBMSCs) are widely used cell source for clinical bone regeneration. Achieving the greatest therapeutic effect is dependent on the osteogenic differentiation potential of the stem cells to be implanted. However, there are still no practical methods to characterize such potential non-invasively or previously. Monitoring cellular morphology is a practical and non-invasive approach for evaluating osteogenic potential. Unfortunately, such image-based approaches had been historically qualitative and requiring experienced interpretation. By combining the non-invasive attributes of microscopy with the latest technology allowing higher throughput and quantitative imaging metrics, we studied the applicability of morphometric features to quantitatively predict cellular osteogenic potential. We applied computational machine learning, combining cell morphology features with their corresponding biochemical osteogenic assay results, to develop prediction model of osteogenic differentiation. Using a dataset of 9,990 images automatically acquired by BioStation CT during osteogenic differentiation culture of hBMSCs, 666 morphometric features were extracted as parameters. Two commonly used osteogenic markers, alkaline phosphatase (ALP) activity and calcium deposition were measured experimentally, and used as the true biological differentiation status to validate the prediction accuracy. Using time-course morphological features throughout differentiation culture, the prediction results highly correlated with the experimentally defined differentiation marker values (R>0.89 for both marker predictions). The clinical applicability of our morphology-based prediction was further examined with two scenarios: one using only historical cell images and the other using both historical images together with the patient's own cell images to predict a new patient's cellular potential. The prediction accuracy was found to be greatly enhanced by incorporation of patients' own cell features in the modeling, indicating the practical strategy for clinical usage. Consequently, our results provide strong evidence for the feasibility of using a quantitative time series of phase-contrast cellular morphology for non-invasive cell quality prediction in regenerative medicine.

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Mesenchymal-like stem cells in canine ovary show high differentiation potential.

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Mesenchymal-like stem cells in canine ovary show high differentiation potential.

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