ArticlePeerJ2016
A molecular classification of human mesenchymal stromal cells.
Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 51 citations in OpenAlex.
- Integrated workflow for univariate and multivariate evaluation of batch correction reliability.Metabolomics : Official journal of the Metabolomic Society · 2026Article
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- Computational comparative analysis identifies potential stemness-related markers for mesenchymal stromal/stem cells.Frontiers in cell and developmental biology · 2023Article
- Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts.Frontiers in immunology · 2023Article
- CD317-Positive Immune Stromal Cells in Human "Mesenchymal Stem Cell" Populations.Frontiers in immunology · 2022Article
- Identification and characterisation of maternal perivascular SUSD2Cell and tissue research · 2021Article
- Pulmonary mesenchymal stem cells are engaged in distinct steps of host response to respiratory syncytial virus infection.PLoS pathogens · 2021Article
- Osteogenic differentiation of human mesenchymal stromal cells and fibroblasts differs depending on tissue origin and replicative senescence.Scientific reports · 2021Article
- Allogenic Use of Human Placenta-Derived Stromal Cells as a Highly Active Subtype of Mesenchymal Stromal Cells for Cell-Based Therapies.International journal of molecular sciences · 2021Review
- Transcriptome comparisons of in vitro intestinal epithelia grown under static and microfluidic gut-on-chip conditions with in vivo human epithelia.Scientific reports · 2021Article
- A simple, scalable approach to building a cross-platform transcriptome atlas.PLoS computational biology · 2020Article
- Direct conversion of human fibroblasts into therapeutically active vascular wall-typical mesenchymal stem cells.Cellular and molecular life sciences : CMLS · 2020Article
- Transcriptome profiles acquired during cell expansion and licensing validate mesenchymal stromal cell lineage genes.Stem cell research & therapy · 2020Article
- Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms.Stem cell reports · 2019Review
- Chondrogenic, hypertrophic, and osteochondral differentiation of human mesenchymal stem cells on three-dimensionally woven scaffolds.Journal of tissue engineering and regenerative medicine · 2019Article
- Stemformatics: visualize and download curated stem cell data.Nucleic acids research · 2019Article
- Mesenchymal stem cell perspective: cell biology to clinical progress.NPJ Regenerative medicine · 2019Review
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonly used to describe and compare different cell types; however, efforts to identify specific markers of rare cellular subsets may be confounded by the small sample sizes of most studies. Consequently, it is difficult to derive reproducible, and therefore useful markers. We addressed the question of MSC classification with a large integrative analysis of many public MSC datasets. We derived a sparse classifier (The Rohart MSC test) that accurately distinguished MSC from non-MSC samples with >97% accuracy on an internal training set of 635 samples from 41 studies derived on 10 different microarray platforms. The classifier was validated on an external test set of 1,291 samples from 65 studies derived on 15 different platforms, with >95% accuracy. The genes that contribute to the MSC classifier formed a protein-interaction network that included known MSC markers. Further evidence of the relevance of this new MSC panel came from the high number of Mendelian disorders associated with mutations in more than 65% of the network. These result in mesenchymal defects, particularly impacting on skeletal growth and function. The Rohart MSC test is a simple in silico test that accurately discriminates MSC from fibroblasts, other adult stem/progenitor cell types or differentiated stromal cells. It has been implemented in the www.stemformatics.org resource, to assist researchers wishing to benchmark their own MSC datasets or data from the public domain. The code is available from the CRAN repository and all data used to generate the MSC test is available to download via the Gene Expression Omnibus or the Stemformatics resource.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.