Molecular Signaling Pathways Mediating Osteoclastogenesis Induced by Prostate Cancer Cells
Bibliographic record
Abstract
BACKGROUND: Advanced prostate cancer commonly metastasizes to bone leading to osteoblastic and osteolytic lesions. Although an osteolytic component governed by activation of bone resorbing osteoclasts is prominent in prostate cancer metastasis, the molecular mechanisms of prostate cancer-induced osteoclastogenesis are not well-understood. METHODS: We studied the effect of soluble mediators released from human prostate carcinoma cells on osteoclast formation from mouse bone marrow and RAW 264.7 monocytes. RESULTS: Soluble factors released from human prostate carcinoma cells significantly increased viability of naïve bone marrow monocytes, as well as osteoclastogenesis from precursors primed with receptor activator of nuclear factor κ-B ligand (RANKL). The prostate cancer-induced osteoclastogenesis was not mediated by RANKL as it was not inhibited by osteoprotegerin (OPG). However inhibition of TGFβ receptor I (TβRI), or macrophage-colony stimulating factor (MCSF) resulted in attenuation of prostate cancer-induced osteoclastogenesis. We characterized the signaling pathways induced in osteoclast precursors by soluble mediators released from human prostate carcinoma cells. Prostate cancer factors increased basal calcium levels and calcium fluctuations, induced nuclear localization of nuclear factor of activated t-cells (NFAT)c1, and activated prolonged phosphorylation of ERK1/2 in RANKL-primed osteoclast precursors. Inhibition of calcium signaling, NFATc1 activation, and ERK1/2 phosphorylation significantly reduced the ability of prostate cancer mediators to stimulate osteoclastogenesis. CONCLUSIONS: This study reveals the molecular mechanisms underlying the direct osteoclastogenic effect of prostate cancer derived factors, which may be beneficial in developing novel osteoclast-targeting therapeutic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".