The expression ofMet/hepatocyte growth factor receptor gene in giant cell tumors of bone and other benign musculoskeletal tumors
Bibliographic record
Abstract
Overexpression of the hepatocyte growth factor receptor (Met/HGF receptor), a transmembrane tyrosine kinase encoded by the MET proto-oncogene, is involved in transformation and invasive behavior of human carcinomas and sarcomas. We have previously found that bone sarcomas express high levels of Met/HGF receptor while in some cases the ligand HGF is co-expressed with the receptor, activating an autocrine loop. In this study, we analyzed 40 biopsy samples of a collection of giant cell tumors and other rare benign tumors of bone for expression of the MET proto-oncogene. These included nonossifying fibromas, osteoblastomas, desmoplastic fibromas of bone, chondroblastomas, and giant cell tumors of bone. Snap frozen samples were tested for the MET and HGF gene expression by immuno-histochemistry and Western blotting with anti-MET antibodies and RT-PCR. Over 50% of all cases scored positive for MET expression being constantly positive in recurrent or locally aggressive lesions. Sporadic co-expression of the Met/HGF receptor and ligand is also demonstrated. Met/HGF receptor expression in benign bone neoplasms suggests its early involvement in sarcomagenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".