Transcriptomic and proteomic analyses in bone tumor cells: Deciphering parathyroid hormone-related protein regulation of the cell cycle and 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 works in our laboratory, including functional assays, have shown that neutralization of parathyroid hormone-related protein (PTHrP) in the cell environment inhibits cell proliferation and induces cell death in GCT stromal cells, indicating a role for PTHrP in cell propagation and survival. The objective of this study was to investigate the global gene and protein expression patterns of GCT cells in order to identify the underlying pathways and mechanisms of neoplastic proliferation provided by PTHrP in the bone microenvironment. Primary stromal cell cultures from 10 patients with GCT were used in this study. Cells were exposed to optimized concentrations of either PTHrP peptide or anti-PTHrP neutralizing antiserum and were analyzed with both cDNA microarray and proteomic microarray assays in triplicate. Hierarchical clustering and principal component analyses confirmed that counteraction of PTHrP in GCT stromal cells results in a clear-cut gene expression pattern distinct from all other treatment groups and the control cell line human fetal osteoblast (hFOB). Multiple bioinformatics tools were used to analyze changes in gene/protein expression and identify important gene ontologies and pathways common to this anti-PTHrP-induced regulatory gene network. PTHrP neutralization interferes with multiple cell survival and apoptosis signaling pathways by triggering both death receptors and cell cycle-mediated apoptosis, particularly via the caspase pathway, TRAIL pathway, JAK-STAT signaling pathway, and cyclin E/CDK2-associated G1/S cell cycle progression. These findings indicate that PTHrP neutralization exhibits anticancer potential by regulating cell-cycle progression and apoptosis in bone tumor cells, with the corollary being that PTHrP is a pro-neoplastic factor that can be targeted in the treatment of bone tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 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".