Intermittent Exposure of Primitive Quiescent Chronic Myeloid Leukemia Cells to Granulocyte-Colony Stimulating Factor <i>In vitro</i> Promotes their Elimination by Imatinib Mesylate
Bibliographic record
Abstract
PURPOSE: Primitive quiescent chronic myeloid leukemia (CML) cells are biologically resistant to imatinib mesylate, an inhibitor of the p210(BCR-ABL) kinase. The present study was designed to investigate whether either continuous or intermittent exposure of these cells to granulocyte-colony stimulating factor (G-CSF) in vitro can overcome this limitation to the effectiveness of imatinib mesylate therapy. EXPERIMENTAL DESIGN: CD34(+) leukemic cells were isolated from six newly diagnosed chronic phase CML patients and cultured for 12 days in serum-free medium with or without G-CSF and/or imatinib mesylate present either continuously or intermittently (three cycles of G-CSF for 0, 1, or 4 days +/- imatinib mesylate for 0, 3, or 4 days). Every 4 days, the number of residual undivided viable cells and the total number of viable cells present were measured. RESULTS: Intermittent but not continuous exposure to G-CSF significantly accelerated the disappearance in vitro of initially quiescent CD34(+) CML cells. This resulted in 3- and 5-fold fewer of these cells remaining after 8 and 12 days, respectively, relative to continuous imatinib mesylate alone (P < 0.04). Cultures containing imatinib mesylate and intermittently added G-CSF also showed the greatest reduction in the total number of cells present after 12 days (5-fold more than imatinib mesylate alone). CONCLUSION: Intermittent exposure to G-CSF can enhance the effect of imatinib mesylate on CML cells by specifically targeting the primitive quiescent leukemic elements. A protocol for treating chronic-phase CML patients with imatinib mesylate that incorporates intermittent G-CSF exposure may offer a novel strategy for obtaining improved responses in vivo.
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".