OBJECTIVE: To identify markers associated with the chondrogenic capacity of expanded human articular chondrocytes and to use these markers for sorting of more highly chondrogenic subpopulations. METHODS: The chondrogenic capacity of chondrocyte populations derived from different donors (n = 21) or different clonal strains from the same cartilage biopsy specimen (n = 21) was defined based on the glycosaminoglycan (GAG) content of tissues generated using a pellet culture model. Selected cell populations were analyzed by microarray and flow cytometry. In some experiments, cells were sorted using antibodies against molecules found to be associated with differential chondrogenic capacity and again assessed in pellet cultures. RESULTS: Significance Analysis of Microarrays indicated that chondrocytes with low chondrogenic capacity expressed higher levels of insulin-like growth factor 1 and of catabolic genes (e.g., matrix metalloproteinase 2, aggrecanase 2), while chondrocytes with high chondrogenic capacity expressed higher levels of genes involved in cell-cell or cell-matrix interactions (e.g., CD49c, CD49f). Flow cytometry analysis showed that CD44, CD151, and CD49c were expressed at significantly higher levels in chondrocytes with higher chondrogenic capacity. Flow cytometry analysis of clonal chondrocyte strains indicated that CD44 and CD151 could also identify more chondrogenic clones. Chondrocytes sorted for brighter CD49c or CD44 signal expression produced tissues with higher levels of GAG per DNA (up to 1.4-fold) and type II collagen messenger RNA (up to 3.4-fold) than did unsorted cells. CONCLUSION: We identified markers that allow characterization of the capacity of monolayer-expanded chondrocytes to form in vitro cartilaginous tissue and enable enrichment for subpopulations with higher chondrogenic capacity. These markers might be used as a means to predict and possibly improve the outcome of cell-based cartilage repair techniques.
OBJECTIVE: To identify markers associated with the chondrogenic capacity of expanded human articular chondrocytes and to use these markers for sorting of more highly chondrogenic subpopulations. METHODS: The chondrogenic capacity of chondrocyte populations derived from different donors (n = 21) or different clonal strains from the same cartilage biopsy specimen (n = 21) was defined based on the glycosaminoglycan (GAG) content of tissues generated using a pellet culture model. Selected cell populations were analyzed by microarray and flow cytometry. In some experiments, cells were sorted using antibodies against molecules found to be associated with differential chondrogenic capacity and again assessed in pellet cultures. RESULTS: Significance Analysis of Microarrays indicated that chondrocytes with low chondrogenic capacity expressed higher levels of insulin-like growth factor 1 and of catabolic genes (e.g., matrix metalloproteinase 2, aggrecanase 2), while chondrocytes with high chondrogenic capacity expressed higher levels of genes involved in cell-cell or cell-matrix interactions (e.g., CD49c, CD49f). Flow cytometry analysis showed that CD44, CD151, and CD49c were expressed at significantly higher levels in chondrocytes with higher chondrogenic capacity. Flow cytometry analysis of clonal chondrocyte strains indicated that CD44 and CD151 could also identify more chondrogenic clones. Chondrocytes sorted for brighter CD49c or CD44 signal expression produced tissues with higher levels of GAG per DNA (up to 1.4-fold) and type II collagen messenger RNA (up to 3.4-fold) than did unsorted cells. CONCLUSION: We identified markers that allow characterization of the capacity of monolayer-expanded chondrocytes to form in vitro cartilaginous tissue and enable enrichment for subpopulations with higher chondrogenic capacity. These markers might be used as a means to predict and possibly improve the outcome of cell-based cartilage repair techniques.
Authors: Tsaiwei Olee; Shawn P Grogan; Martin K Lotz; Clifford W Colwell; Darryl D D'Lima; Evan Y Snyder Journal: Tissue Eng Part A Date: 2013-10-19 Impact factor: 3.845
Authors: Hagen Schmal; Alexander T Mehlhorn; David Dovi-Akue; Jan M Pestka; Norbert P Südkamp; Philipp Niemeyer Journal: Eur J Orthop Surg Traumatol Date: 2014-12
Authors: A R Tan; E Alegre-Aguarón; G D O'Connell; C D VandenBerg; R K Aaron; G Vunjak-Novakovic; J Chloe Bulinski; G A Ateshian; C T Hung Journal: Osteoarthritis Cartilage Date: 2014-10-17 Impact factor: 6.576
Authors: Karsten Schrobback; Jana Wrobel; Dietmar W Hutmacher; Tim B F Woodfield; Travis J Klein Journal: Tissue Eng Part A Date: 2013-02-19 Impact factor: 3.845
Authors: Shawn P Grogan; Xian Chen; Sujata Sovani; Noboru Taniguchi; Clifford W Colwell; Martin K Lotz; Darryl D D'Lima Journal: Tissue Eng Part A Date: 2013-09-25 Impact factor: 3.845