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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".