Gene profiling of Graffi murine leukemia virus-induced lymphoid leukemias: identification of leukemia markers and Fmn2 as a potential oncogene
Bibliographic record
Abstract
The Graffi murine leukemia virus induces a large spectrum of leukemias in mice and thus provides a good model to compare the transcriptome of all types of leukemias. We analyzed the gene expression profiles of both T and B leukemias induced by the virus with DNA microarrays. Given that we considered that a 4-fold change in expression level was significant, 388 probe sets were associated to B, to T, or common to both leukemias. Several of them were not yet associated with lymphoid leukemia. We confirmed specific deregulation of Fmn2, Arntl2, Bfsp2, Gfra2, Gpm6a, and Gpm6b in B leukemia, of Nln, Fbln1, and Bmp7 in T leukemias, and of Etv5 in both leukemias. More importantly, we show that the mouse Fmn2 induced an anchorage-independent growth, a drastic modification in cell shape with a concomitant disruption of the actin cytoskeleton. Interestingly, we found that human FMN2 is overexpressed in approximately 95% of pre-B acute lymphoblastic leukemia with the highest expression levels in patients with a TEL/AML1 rearrangement. These results, surely related to the role of FMN2 in meiotic spindle maintenance, suggest its important role in leukemogenesis. Finally, we propose a new panel of genes potentially involved in T and/or B leukemias.
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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) | 0.001 | 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".