CSIG-16. CIC-FUSION ONCOPROTEINS COOPERATE WITH JAK/STAT1/3 SIGNALING TO DRIVE CIC-REARRANGED SARCOMA
Bibliographic record
Abstract
Abstract CIC-rearranged sarcoma (CRS) is a rare disease driven by a specific fusion protein involving the CIC gene. The occurrence in the brain is 3% in all CRS patients, and these tumors frequently metastasize to the brain. The most common rearrangement is with the double homeobox 4 (DUX4) transcription factor (CIC-DUX4), and others, such as CIC-NUTM1 fusions, have been identified in a subset of pediatric primitive neuroectodermal tumors. However, the molecular mechanisms by which CIC-fusions drive CRS remain unknown. Preliminary data show that CIC-DUX4/NUTM1 fusions activate JAK and its downstream effector STAT1/3. We hypothesize that JAK/STAT1/3 signaling cooperates with CIC-fusions to drive CIC-sarcomas by inducing ETV1/4/5 expression. Patient-derived CRS cell lines showed elevated levels of JAK1/STAT1/3 activation compared to fusion-negative sarcoma lines. Inhibition of JAK1 using Ruxolitinib and Solicitinib reduced STAT1/3 phosphorylation, downregulated ETV1/4/5 expression at both mRNA and protein levels, and diminished ETV5 promoter activity, cell proliferation, and tumorigenicity. Although the mechanism by which CIC-fusions activate oncogenic targets is still under investigation, histone acetylation appears to play a central role. STAT1/3 interacts with p300/CBP to enhance transcription, and STAT1 is necessary for p300 acetyltransferase activity. Ruxolitinib significantly reduced histone acetylation at ETV1/4/5 promoters in hMSC cells expressing CIC-DUX4/NUTM1, as well as in CRS cell lines. Unlike the p300 inhibitor C646, which causes global hypoacetylation, Ruxolitinib’s effects were promoter-specific, indicating its potential as a more targeted and less toxic therapeutic option. Importantly, we found that STAT1/3 binds to ETV1/4/5 promoters only in the presence of CIC-fusions. Luciferase assays confirmed that STAT1/3 alone cannot activate ETV5 transcription without CIC-fusions, revealing a novel cooperative mechanism. In vivo, Ruxolitinib treatment of CRS xenografts led to significant reductions in tumor volume, STAT1/3 activation, and ETV1/4/5 expression. These findings support JAK1/STAT1/3 inhibition as a promising therapeutic strategy for CRS and warrant further preclinical investigation.
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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) | 0.002 | 0.001 |
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".