PTHrP Induces Autocrine/Paracrine Proliferation of Bone Tumor Cells through Inhibition of Apoptosis
Bibliographic record
Abstract
Giant Cell Tumor of Bone (GCT) is an aggressive skeletal tumor characterized by local bone destruction, high recurrence rates and metastatic potential. Previous work in our lab has shown that the neoplastic cell of GCT is a proliferating pre-osteoblastic stromal cell in which the transcription factor Runx2 plays a role in regulating protein expression. One of the proteins expressed by these cells is parathyroid hormone-related protein (PTHrP). The objectives of this study were to determine the role played by PTHrP in GCT of bone with a focus on cell proliferation and apoptosis. Primary stromal cell cultures from 5 patients with GCT of bone and one lung metastasis were used for cell-based experiments. Control cell lines included a renal cell carcinoma (RCC) cell line and a human fetal osteoblast cell line. Cells were exposed to optimized concentrations of a PTHrP neutralizing antibody and were analyzed with the use of cell proliferation and apoptosis assays including mitochondrial dehydrogenase assays, crystal violet assays, APO-1 ELISAs, caspase activity assays, flow cytometry and immunofluorescent immunohistochemistry. Neutralization of PTHrP in the cell environment inhibited cell proliferation in a consistent manner and induced apoptosis in the GCT stromal cells, with the exception of those obtained from a lung metastasis. Cell cycle progression was not significantly affected by PTHrP neutralization. These findings indicate that PTHrP plays an autocrine/paracrine neoplastic role in GCT by allowing the proliferating stromal cells to evade apoptosis, possibly through non-traditional caspase-independent pathways. Thus PTHrP neutralizing immunotherapy is an intriguing potential therapeutic strategy for this tumor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".