Noncanonical β-catenin interactions promote leukemia-initiating activity in early T-cell acute lymphoblastic leukemia
Bibliographic record
Abstract
T-cell acute lymphoblastic leukemia (T-ALL) is a T-cell malignancy characterized by cell subsets and enriched with leukemia-initiating cells (LICs). β-Catenin modulates LIC activity in T-ALL. However, its role in maintaining established leukemia stem cells remains largely unknown. To identify functionally relevant protein interactions of β-catenin in T-ALL, we performed coimmunoprecipitation followed by liquid chromatography-mass spectrometry. Here, we report that a noncanonical functional interaction of β-catenin with the Forkhead box O3 (FOXO3) transcription factor positively regulates LIC-related genes, including the cyclin-dependent kinase 4, which is a crucial modulator of cell cycle and tumor maintenance. We also confirm the relevance of these findings using stably integrated fluorescent reporters of β-catenin and FOXO3 activity in patient-derived xenografts, which identify minor subpopulations with enriched LIC activity. In addition, gene expression data at the single-cell level of leukemic cells of primary patients at the time of diagnosis and minimal residual disease (MRD) up to 30 days after the standard treatments reveal that the expression of β-catenin- and FOXO3-dependent genes is present in the CD82+CD117+ cell fraction, which is substantially enriched with LICs in MRD as well as in early T-cell precursor ALL. These findings highlight key functional roles for β-catenin and FOXO3 and suggest novel therapeutic strategies to eradicate aggressive cell subsets in T-ALL.
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 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".