Targeting the bHLH Transcriptional Networks by Mutated E Proteins in Experimental Glioma
Bibliographic record
Abstract
Glioblastomas (GB) are aggressive primary brain tumors. Helix-loop-helix (HLH, ID proteins) and basic HLH (bHLH, e.g., Olig2) proteins are transcription factors that regulate stem cell proliferation and differentiation throughout development and into adulthood. Their convergence on many oncogenic signaling pathways combined with the observation that their overexpression in GB correlates with poor clinical outcome identifies these transcription factors as promising therapeutic targets. Important dimerization partners of HLH/bHLH proteins are E proteins that are necessary for nuclear translocation and DNA binding. Here, we overexpressed a wild type or a dominant negative form of E47 (dnE47) that lacks its nuclear localization signal thus preventing nuclear translocation of bHLH proteins in long-term glioma cell lines and in glioma-initiating cell lines and analyzed the effects in vitro and in vivo. While overexpression of E47 was sufficient to induce apoptosis in absence of bHLH proteins, dnE47 was necessary to prevent nuclear translocation of Olig2 and to achieve similar proapoptotic responses. Transcriptional analyses revealed downregulation of the antiapoptotic gene BCL2L1 and the proproliferative gene CDC25A as underlying mechanisms. Overexpression of dnE47 in glioma-initiating cell lines with high HLH and bHLH protein levels reduced sphere formation capacities and expression levels of Nestin, BCL2L1, and CDC25A. Finally, the in vivo induction of dnE47 expression in established xenografts prolonged survival. In conclusion, our data introduce a novel approach to jointly neutralize HLH and bHLH transcriptional networks activities, and identify these transcription factors as potential targets in glioma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".