OLIG2 (BHLHB1), a bHLH Transcription Factor, Contributes to Leukemogenesis in Concert with LMO1
Bibliographic record
Abstract
OLIG2 (originally designated BHLHB1) encodes a transcription factor that contains the basic helix-loop-helix motif. Although expression of OLIG2 is normally restricted to neural tissues, overexpression of OLIG2 has been shown in patients with precursor T-cell lymphoblastic lymphoma/leukemia (pre-T LBL). In the current study, we found that overexpression of OLIG2 was not only found in oligodendroglioma samples and normal neural tissue but also in a wide spectrum of malignant cell lines including leukemia, non-small cell lung carcinoma, melanoma, and breast cancer cell lines. To investigate whether enforced expression of OLIG2 is oncogenic, we generated transgenic mice that overexpressed OLIG2 in the thymus. Ectopic OLIG2 expression in the thymus was only weakly oncogenic as only 2 of 85 mice developed pre-T LBL. However, almost 60% of transgenic mice that overexpressed both OLIG2 and LMO1 developed pre-T LBL with large thymic tumor masses. Gene expression profiling of thymic tumors that developed in OLIG2/LMO1 mice revealed up-regulation of Notch1 as well as Deltex1 (Dtx1) and pre T-cell antigen receptor alpha (Ptcra), two genes that are considered to be downstream of Notch1. Of note, we found mutations in the Notch1 heterodimerization or proline-, glutamic acid-, serine-, and threonine-rich domain in three of six primary thymic tumors. In addition, growth of leukemic cell lines established from OLIG2/LMO1 transgenic mice was suppressed by a gamma-secretase inhibitor, suggesting that Notch1 up-regulation is important for the proliferation of OLIG2-LMO1 leukemic cells.
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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".