Leukemia-initiating cells in human T-lymphoblastic leukemia exhibit glucocorticoid resistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
T-cell acute lymphoblastic leukemia (T-ALL) is associated with a significant risk of disease relapse, but the biological basis for relapse is poorly understood. Here, we identify leukemiainitiating cells (L-ICs) on the basis of functional assays and prospective isolation and report a role for L-ICs in T-ALL disease and relapse. Long-term proliferation in response to NOTCH1 activating signals in OP9-DL1 coculture system or capacity to initiate leukemia in xenografts by the CD7(+)CD1a(-) subset of primary T-ALL samples was superior to other subsets, refining the identity of T-ALL L-ICs. T-ALL engraftment was improved in nonobese diabetic/severe combined immunodeficiency (NOD/scid)IL2Rγ(null) (NSG) mice compared with NOD/scid with anti-CD122 treatment (NS122), but both showed changes in leukemia immunophenotype. Clonal analysis of xenografts using the TCRG locus revealed the presence of subclones of T-ALL L-ICs, some of which possess a selective growth advantage and correlated with the capacity of CD7(+)CD1a(+) xenograft cells to engraft secondary NSG mice. Treatment of high-risk T-ALL xenografts eliminated CD1a(+) T-ALL cells, but CD1a(-) cells were resistant and their number was increased. Our results establish that primary CD1a(-) T-ALL cells are functionally distinct from CD1a(+) cells and that the CD7(+)CD1a(-) subset is enriched for L-IC activity that may be involved in mediating disease relapse after therapy.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it