TAZ-CAMTA1 and YAP-TFE3 modulate the basal TAZ/YAP transcriptional program by recruiting the ATAC histone acetyltransferase complex
Bibliographic record
Abstract
Abstract Epithelioid hemangioendothelioma (EHE) is a vascular sarcoma that metastasizes early and lacks an effective medical therapy. The TAZ-CAMTA1 and YAP-TFE3 fusion proteins are chimeric transcription factors and initiating oncogenic drivers of EHE. A combined proteomic/genetic screen identified YEATS2 and ZZZ3, components of the A da 2a - c ontaining histone acetyltransferase (ATAC) complex, as key interactors of both TAZ-CAMTA1 and YAP-TFE3 despite the dissimilarity of the C terminal fusion partners CAMTA1 and TFE3. An integrative next generation sequencing approach showed the fusion proteins drive expression of a unique transcriptome distinct from TAZ and YAP by simultaneously hyperactivating a TEAD-based transcriptional program and modulating the chromatin environment via interaction with the ATAC complex. Interaction of the ATAC complex with both TAZ-CAMTA1 and YAP-TFE3 indicates the histone acetyltransferase complex is an oncogenic driver in EHE and potentially other sarcomas. Furthermore, the ATAC complex is an enzymatic transcriptional cofactor required for both fusion proteins in EHE, representing a unifying therapeutic target for this sarcoma. Gene fusions are the most common genetic alterations activating TAZ and YAP in cancer, and this study serves as a template for identifying epigenetic modifiers recruited by the C terminal fusion partners of other TAZ/YAP gene fusions occurring in gliomas, carcinomas, and other sarcomas. Summary TAZ-CAMTA1 and YAP-TFE3 alter the TAZ/YAP transcriptional program by recruiting the ATAC complex and modifying the chromatin landscape.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".