RNA-binding protein NOVA1 promotes acute T-lymphocyte leukemia progression by stabilizing USP44 mRNA
Bibliographic record
Abstract
Acute T-lymphocyte leukemia (T-ALL) is a malignant tumor disease. RNA-binding protein neotumor ventral antigen-1 (NOVA1) is highly expressed in bone marrow mononuclear cells of T-ALL patients, while the role of NOVA1 in T-ALL progression remains unknown. The gain- and loss-of-function studies for NOVA1 were performed in Jurkat and CCRF-CEM cells. NOVA1 overexpression promoted cell proliferation and cell cycle progression. NOVA1 knockdown increased the apoptosis rate of T-ALL cells. Ubiquitin-specific protease 44 (USP44), a nuclear protein with deubiquitinase catalytic activity, has been reported to play an oncogene role in human T-cell leukemia. USP44 expression was positively associated with NOVA1, and RNA immunoprecipitation assay verified the binding of NOVA1 to the mRNA of USP44. USP44 knockdown partially abolished NOVA1-induced cell proliferation and inhibition of apoptosis. The in vivo xenograft experiment was performed by injection of T-ALL tumor cells into the tail vein of NOD/SCID mice. The knockdown of NOVA1 had lower tumorigenicity. NOVA1 knockdown alleviated pathological changes in lung and spleen tissues, and increased the overall survival period and the weight of T-ALL mice. Thus, NOVA1 acts as an accelerator in T-ALL, and its function might be achieved by binding to and stabilizing USP44 mRNA.
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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".