Identification of cooperative genes for NUP98-HOXA9 in myeloid leukemogenesis using a mouse model
Bibliographic record
Abstract
The chromosomal translocation t(7; 11)(p15;p15), observed in human myeloid leukemia, results in a NUP98 and HOXA9 gene fusion. We generated a transgenic mouse line that specifically expressed the chimeric NUP98-HOXA9 gene in the myeloid lineage. While only 20% of the transgenic mice progressed to leukemia after a latency period, myeloid progenitor cells from nonleukemic transgenic mice still exhibited increased proliferative potential. This suggested that the NUP98-HOXA9 fusion induced a preleukemic phase, and other factors were required for complete leukemogenesis. NUP98-HOXA9 expression promoted the onset of retrovirus-induced BXH2 myeloid leukemia. This phenomenon was used to identify cooperative disease genes as common integration sites (CISs). Meis1, a known HOX cofactor, was identified as a CIS with a higher integration frequency in transgenic than in wild-type BXH2 mice. By the same means we identified further 4 candidate cooperative genes, Dnalc4, Fcgr2b, Fcrl, and Con1. These genes cooperated with NUP98-HOXA9 in transforming NIH 3T3 cells. The system described here is a powerful tool to identify cooperative oncogenes and will assist in the clarification of the multistep process of carcinogenesis.
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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 | 0.001 | 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 | 0.001 |
| 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".