Human DDR2 (Discoidin domain-containing receptor 2) ELISA Kit

Introduction The periosteum has a bilayered structure that surrounds cortical bone. The outer layer is rich in connective tissue and fibroblasts, while the inner layer in contact with the cortical surface of the bone predominantly consists of osteoblasts and osteoblast progenitors. The identification of cell-specific surface markers of the bilayered structure of the periosteum is important for the purpose of tissue regeneration. Materials and methods We investigated the expression of the discoidin domain tyrosine kinase receptor DDR2, fibroblast specific protein-1 (FSP-1) and alkaline phosphatase (ALP) in the periosteum of cortical bone by immunohistochemistry. Osteogenic differentiation was compared between DDR2- and FSP-1-expressing cells flow-sorted from the periosteum. Results We showed that DDR2 predominantly labeled osteogenic cells residing in the inner layer of the periosteum and that Pearson's coefficient of colocalization indicated a significant correlation with the expression of ALP. The mineralization of DDR2-expressing osteogenic cells isolated from the periosteum was significantly induced. In contrast, FSP-1 predominantly labeled the outer layer of periosteal fibroblasts, and Pearson's coefficient of colocalization indicated that FSP-1 was poorly correlated with the expression of DDR2 and ALP. FSP-1-expressing periosteal fibroblasts did not exhibit osteogenic differentiation for the induction of bone mineralization. Conclusion DDR2 is a novel potential cell surface marker for identifying and isolating osteoblasts and osteoblast progenitors within the periosteum that can be used for musculoskeletal regenerative therapies.

BACKGROUND & AIMS: No targeted therapies have been found to be effective against hepatocellular carcinoma (HCC), possibly due to the large degree of intratumor heterogeneity. We performed genetic analyses of different regions of HCCs to evaluate levels of intratumor heterogeneity and associate alterations with responses to different pharmacologic agents. METHODS: We obtained samples of HCCs (associated with hepatitis B virus infection) from 10 patients undergoing curative resection, before adjuvant therapy, at hospitals in China. We collected 4-9 spatially distinct samples from each tumor (55 regions total), performed histologic analyses, isolated cancer cells, and carried them low-passage culture. We performed whole-exome sequencing, copy-number analysis, and high-throughput screening of the cultured primary cancer cells. We tested responses of an additional 105 liver cancer cell lines to a fibroblast growth factor receptor (FGFR) 4 inhibitor. RESULTS: We identified a total of 3670 non-silent mutations (3192 missense, 94 splice-site variants, and 222 insertions or deletions) in the tumor samples. We observed considerable intratumor heterogeneity and branched evolution in all 10 tumors; the mean percentage of heterogeneous mutations in each tumor was 39.7% (range, 12.9%-68.5%). We found significant mutation shifts toward C>T and C>G substitutions in branches of phylogenetic trees among samples from each tumor (P <.0001). Of note, 14 of the 26 oncogenic alterations (53.8%) varied among subclones that mapped to different branches. Genetic alterations that can be targeted by existing pharmacologic agents (such as those in FGF19, DDR2, PDGFRA, and TOP1) were identified in intratumor subregions from 4 HCCs and were associated with sensitivity to these agents. However, cells from the remaining subregions, which did not have these alterations, were not sensitive to these drugs. High-throughput screening identified pharmacologic agents to which these cells were sensitive, however. Overexpression of FGF19 correlated with sensitivity of cells to an inhibitor of FGFR 4; this observation was validated in 105 liver cancer cell lines ( P = .0024). CONCLUSIONS: By analyzing genetic alterations in different tumor regions of 10 HCCs, we observed extensive intratumor heterogeneity. Our patient-derived cell line-based model, integrating genetic and pharmacologic data from multiregional cancer samples, provides a platform to elucidate how intratumor heterogeneity affects sensitivity to different therapeutic agents.