β-catenin promotes MTX resistance of leukemia cells by down-regulating FPGS expression via NF-κB
Bibliographic record
Abstract
BACKGROUND: Aberrant activation of β-catenin has been shown to play important roles in the chemoresistance of acute lymphoblastic leukemia (ALL), but the involvement and mechanism of β-catenin in methotrexate (MTX) resistance is poorly understood. In the present study, we demonstrate a critical role of β-catenin-NF-κB-FPGS pathway in MTX resistance in the human T-lineage ALL cell lines. METHODS: Lentivirus sh-β-catenin was used to silence the expression of β-catenin. Flow cytometry was performed to detect apoptosis after MTX treatment. Western blot, real-time PCR, Co-immunoprecipitation (Co-IP), Chromatin immunoprecipitation (ChIP), Re-ChIP, and Luciferase assay were utilized to investigate the relationship among β-catenin, nuclear factor (NF)-κB, and folypoly-γ-glutamate synthetase (FPGS). RESULTS: Depletion of β-catenin significantly increased the cytotoxicity of MTX. At the molecular level, knockdown of β-catenin caused the increase of the protein level of FPGS and NF-κB p65. Furthermore, β-catenin complexed with NF-κB p65 and directly bound to the FPGS promoter to regulate its expression. In addition, β-catenin repression prolonged the protein turnover of FPGS. CONCLUSIONS: Taken together, our results demonstrate that β-catenin may contribute to MTX resistance in leukemia cells via the β-catenin-NF-κB-FPGS pathway, posing β-catenin as a potential target for combination treatments during ALL therapy.
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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) | 0.001 | 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 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".