Targeting Leukemia Stem Cells: Which Pathways Drive Self-Renewal Activity in T-Cell Acute Lymphoblastic Leukemia?
Bibliographic record
Abstract
T-Cell acute lymphoblastic leukemia (t-all) is a malignancy of white blood cells, characterized by an uncontrolled accumulation of T-cell progenitors. During leukemic progression, immature T cells grow abnormally and crowd into the bone marrow, preventing it from making normal blood cells and spilling out into the bloodstream. Recent studies suggest that only discrete cell populations that possess the ability to recreate the entire tumour might be responsible for the initiation and propagation of t-all. Those unique cells are commonly called "cancer stem cells" or, in the case of hematopoietic malignancies, "leukemia stem cells" (lscs). Like normal hematopoietic stem cells, lscs are thought to be capable of self-renewal, during which, by asymmetrical division, they give rise to an identical copy of themselves as well as to a daughter cell that is no longer capable of self-renewal activity and represents a more "differentiated" progeny. Here, we review the main pathways of self-renewal activity in lscs, focusing on their involvement in the maintenance and development of t-all. New stem cell-directed therapies and lsc-targeted agents are also discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".