Characterization of the Impact of the <i>MYBBP1A</i> Gene and rs3809849 on Asparaginase Sensitivity and Cellular Functions
Bibliographic record
Abstract
Aims: To investigate the role of MYBBP1A gene and rs3809849 in pancreatic cancer (PANC1) and lymphoblastic leukemia (NALM6) cell lines and their response to asparaginase treatment. Materials & methods: The authors applied CRISPR-Cas9 to produce MYBBP1A knock-out (KO) and rs3809849 knock-in (KI) cell lines. The authors also interrogated rs3809849's impact on PANC1 cells through allele-specific overexpression. Results: PANC1 MYBBP1A KO cells exhibited lower proliferation capacity (p ≤ 0.05), higher asparaginase sensitivity (p = 0.01), reduced colony-forming potential (p = 0.001), cell cycle blockage in S phase, induction of apoptosis and remarkable morphology changes suggestive of an epithelial–mesenchymal transition. Overexpression of the wild-type (but not the mutant) allele of MYBBP1A-rs3809849 in PANC1 cells increased asparaginase sensitivity. NALM6 MYBBP1A KO displayed resistance to asparaginase (p < 0.0001), whereas no effect for rs3809849 KI was noted. Conclusions: MYBBP1A is important for regulating various cellular functions, and it plays, along with its rs3809849 polymorphism, a tissue-specific role in asparaginase treatment response.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".