Lef1 Is a Critical Mediator of Wnt/β-Catenin Signaling in T-Cell Acute Lymphoblastic Leukemia (T-ALL)
Bibliographic record
Abstract
Abstract T-cell acute lymphoblastic leukemia (T-ALL) is a malignancy characterized by an uncontrolled proliferation of immature T-cells. While current therapies cure ~80% of pediatric patients, adults fare more poorly with ~40% overall survival. Refractory cases and relapses are presumably due to the ineffective targeting of leukemia stem cells (LSC), previously described in human and in mouse models of T-ALL, and thought to be resistant to standard treatments. Recently, we have reported that active signaling through the Wnt/β-catenin pathway is a defining feature of LSC in T-ALL, and that interruption of this signaling pathway abrogates disease propagation in vivo. Using an integrated, real-time reporter of Wnt/β-catenin signaling (7TGC; composed of 7 Tcf/Lef-binding sites upstream of a minimal promoter and GFP marker), we identified leukemia-initiating cell (LIC) activity to reside asymmetrically within the minor proportion of Wnt-active, GFP+ cells in primary mouse NOTCH1-induced T-cell leukemias. Moreover, inducible deletion of β-catenin in this context eliminated LIC activity. Here, we report that LIC activity in this Wnt-active subpopulation is dependent on Lef1. Using Lef1loxP/loxP animals, we show that inducible Cre-mediated deletion of Lef1 in established leukemias extinguishes both Wnt/GFP reporter expression and LIC activity. To explore mechanisms underlying asymmetry of LIC activity within the tumor population, we have also investigated the differential expression of various Lef1 protein isoforms in Wnt-active (GFP+) vs. Wnt-inactive (GFP-) leukemic subsets and assessed their function in supporting LIC activity. These results suggest that β-catenin acts via Lef1 to support asymmetric LIC activity within the Wnt-active subset of leukemia cells. Disclosures No relevant conflicts of interest to declare.
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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) | 0.002 | 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".