Detection of <i>CSF1</i> rearrangements deleting the 3′ UTR in tenosynovial giant cell tumors
Bibliographic record
Abstract
Tenosynovial giant cell tumors (TGCTs) are characterized by rearrangements of CSF1, thought to drive overexpression of macrophage colony-stimulating factor (CSF1), thereby promoting tumor growth and recruitment of non-neoplastic mononuclear and multinucleated inflammatory cells. While fusions to collagen promoters have been described, the mechanism of CSF1 overexpression has been unclear in a majority of cases. Two cohorts of TGCT were investigated for CSF1 rearrangements using fluorescence in situ hybridization (FISH) and either RNA-seq or DNA-seq with Sanger validation. The study comprised 39 patients, including 13 localized TGCT, 21 diffuse TGCT, and five of unspecified type. CSF1 rearrangements were identified by FISH in 30 cases: 13 translocations, 17 3' deletions. Sequencing confirmed CSF1 breakpoints in 28 cases; in all 28 the breakpoint was found to be downstream of exon 5, replacing or deleting a long 3' UTR containing known miRNA and AU-rich element negative regulatory sequences. We also confirmed the presence of CBL exon 8-9 mutations in six of 21 cases. In conclusion, TGCT in our large cohort were characterized by variable alterations, all of which led to truncation of the 3' end of CSF1, instead of the COL6A3-CSF1 fusions previously reported in some TGCTs. The diversity of fusion partners but consistent integrity of CSF1 functional domains encoded by exons 1-5 support a hypothesis that CSF1 overexpression results from transcription of a truncated form of CSF1 lacking 3' negative regulatory sequences. The presence of CBL mutations affecting the linker and RING finger domain suggests an alternative mechanism for increased CSF1/CSF1R signaling in some cases.
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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".