TNF-α is the dominant cytokine in inflammatory osteolysis. Using mice whose BM stromal cells and osteoclast precursors are chimeric for the presence of TNF receptors, we found that both cell types mediated the cytokine’s osteoclastogenic properties. The greater contribution was made, however, by stromal cells that express the osteoclastogenic cytokine M-CSF. TNF-α stimulated M-CSF gene expression, in vivo, only in the presence of TNF-responsive stromal cells. M-CSF, in turn, induced the key osteoclastogenic cytokine receptor, receptor activator of NF-κB (RANK), in osteoclast precursors. In keeping with the proproliferative and survival properties of M-CSF, TNF-α enhanced osteoclast precursor number only in the presence of stromal cells bearing TNF receptors. To determine the clinical relevance of these observations, we induced inflammatory arthritis in wild-type mice and treated them with a mAb directed against the M-CSF receptor, c-Fms. Anti–c-Fms mAb selectively and completely arrested the profound pathological osteoclastogenesis attending this condition, the significance of which is reflected by similar blunting of the in vivo bone resorption marker tartrate-resistant acid phosphatase 5b (TRACP 5b). Confirming that inhibition of the M-CSF signaling pathway targets TNF-α, anti–c-Fms also completely arrested osteolysis in TNF-injected mice with nominal effect on macrophage number. M-CSF and its receptor, c-Fms, therefore present as candidate therapeutic targets in states of inflammatory bone erosion.
Hideki Kitaura, Ping Zhou, Hyun-Ju Kim, Deborah V. Novack, F. Patrick Ross, Steven L. Teitelbaum
Usage data is cumulative from April 2024 through April 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 796 | 78 |
90 | 44 | |
Figure | 471 | 8 |
Supplemental data | 48 | 1 |
Citation downloads | 85 | 0 |
Totals | 1,490 | 131 |
Total Views | 1,621 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.