<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
Journal article(2026)
-
Judith Veldman, Mauricio N.Ferrao Blanco, Eric Farrell, Gerjo J.V.M. van Osch, Nicole Kops, Wendy J.L.M. Koevoet, Eric M.J. Bindels, Gregory van Beek, Remco M. Hoogenboezem, Kavitha Sivasubramaniyan, Jeroen van Rooij, Andrea Lolli
The authors regret that the original data availability statement of our manuscript was not included in the final submission and this oversight was not identified during proofreading. In the context of open-access publication, it is essential that the correct data availability information is provided. The correct statement is as follows: The data generated and analysed during the current study can be found in the Supplementary Data file with the exception of the single cell RNA sequencing data. The count matrices derived from the raw single cell RNA sequencing data have been uploaded to Gene Expression Omnibus under accession number GSE290973. Due to privacy considerations, the raw sequencing files have not been deposited in the Gene Expression Omnibus but can be obtained from the corresponding author upon reasonable request and completion of a Data Use Agreement. The authors would like to apologise for any inconvenience caused.
...
The authors regret that the original data availability statement of our manuscript was not included in the final submission and this oversight was not identified during proofreading. In the context of open-access publication, it is essential that the correct data availability information is provided. The correct statement is as follows: The data generated and analysed during the current study can be found in the Supplementary Data file with the exception of the single cell RNA sequencing data. The count matrices derived from the raw single cell RNA sequencing data have been uploaded to Gene Expression Omnibus under accession number GSE290973. Due to privacy considerations, the raw sequencing files have not been deposited in the Gene Expression Omnibus but can be obtained from the corresponding author upon reasonable request and completion of a Data Use Agreement. The authors would like to apologise for any inconvenience caused.
Journal article(2025)
-
Judith Veldman, Mauricio N. Ferrao Blanco, Eric Farrell, Gerjo J.V.M. van Osch, Nicole Kops, Wendy J.L.M. Koevoet, Eric M.J. Bindels, Gregory van Beek, Remco M. Hoogenboezem, Kavitha Sivasubramaniyan, Jeroen van Rooij, Andrea Lolli
Osteoarthritis (OA) is a common disabling disease for which no effective pharmacological therapy exists. The progression of osteoarthritis is characterized by the loss of homeostasis in the cartilage. Since in the early stages of the disease, a phenotypic switch is seen in which articular chondrocytes become hypertrophic and promote degradation of the cartilage extracellular matrix, targeting this phenomenon might be the key to developing an effective therapy. To accelerate the identification of potential therapy, drug repurposing strategies are used. In this study we have used a novel approach by combining this with the signature reversing principle on single cell transcriptomics data aimed to reverse the hypertrophic phenotype of chondrocytes in osteoarthritic cartilage of patients. We identified 6 drugs predicted to reverse the hypertrophic phenotype of chondrocytes. Subsequent in vitro evaluation in human chondrocytes and cartilage explants demonstrated that Cobimetinib, a MEK1/2 inhibitor, indeed reduced chondrocyte hypertrophy-related and catabolic gene expression, such as SPP1 , COL10A1 , MMP13 and ADAMTS5 , while promoting collagen type 2 and aggrecan gene expression. Finally, single-cell RNA sequencing performed on osteoarthritic cartilage explants exposed to Cobimetinib ex vivo confirmed the anti-hypertrophic effect of the identified drug on hypertrophy-related gene expression and velocity analysis shows that cells are diverting toward a homeostatic cartilage cluster. This study is a proof of concept that open-access single cell omics data together with a drug repurposing strategy can identify drugs that target a specific cellular phenotype in diseases like osteoarthritis and could accelerate the drug discovery process.
...
Osteoarthritis (OA) is a common disabling disease for which no effective pharmacological therapy exists. The progression of osteoarthritis is characterized by the loss of homeostasis in the cartilage. Since in the early stages of the disease, a phenotypic switch is seen in which articular chondrocytes become hypertrophic and promote degradation of the cartilage extracellular matrix, targeting this phenomenon might be the key to developing an effective therapy. To accelerate the identification of potential therapy, drug repurposing strategies are used. In this study we have used a novel approach by combining this with the signature reversing principle on single cell transcriptomics data aimed to reverse the hypertrophic phenotype of chondrocytes in osteoarthritic cartilage of patients. We identified 6 drugs predicted to reverse the hypertrophic phenotype of chondrocytes. Subsequent in vitro evaluation in human chondrocytes and cartilage explants demonstrated that Cobimetinib, a MEK1/2 inhibitor, indeed reduced chondrocyte hypertrophy-related and catabolic gene expression, such as SPP1 , COL10A1 , MMP13 and ADAMTS5 , while promoting collagen type 2 and aggrecan gene expression. Finally, single-cell RNA sequencing performed on osteoarthritic cartilage explants exposed to Cobimetinib ex vivo confirmed the anti-hypertrophic effect of the identified drug on hypertrophy-related gene expression and velocity analysis shows that cells are diverting toward a homeostatic cartilage cluster. This study is a proof of concept that open-access single cell omics data together with a drug repurposing strategy can identify drugs that target a specific cellular phenotype in diseases like osteoarthritis and could accelerate the drug discovery process.