Properties of CD34+ CML Cells That Predict Clinical Response to Tyrosine Kinase Inhibitors.
Bibliographic record
Abstract
Abstract Imatinib (IM) treatment causes remission in a majority of patients with chronic myeloid leukemia (CML) but relapses remain a problem. The frequent presence in relapsing cells of BCR-ABL kinase domain mutations suggests that their prior but undetected acquisition by rare CML stem cells may be a major contributor to IM treatment failures. We have recently demonstrated that enriched populations of CML stem cells (lin−CD34+CD38− cells) are relatively insensitive to IM and possess multiple unique features that would be expected to promote both innate and acquired mechanisms of resistance to BCR-ABL-targeted therapeutics. These include elevated BCR-ABL expression and tyrosine kinase activity, increased expression of ABCB1/MDR1 and ABCG2, decreased expression of OCT1, and a high degree of genetic instability, as demonstrated by a rapid accumulation of BCR-ABL mutations in vitro. To determine whether these parameters may be predictive of clinical responses to IM, immunomagnetically selected CD34+ stem/progenitor cells from 18 chronic phase CML patients’ samples obtained prior to IM therapy were evaluated and the results compared with subsequent clinical responses. Direct sequencing of transcripts cloned from extracts of freshly isolated CD34+ cells (10 clones/sample) detected a high frequency of pre-existing BCR-ABL kinase mutations in the CD34+ cells from 12 of 12 patients regardless of their subsequent IM responses (20–80%). Interestingly, a higher incidence of BCR-ABL kinase domain mutations was found in 5 IM-nonresponders (33–80% of transcripts showed ≥1 BCR-ABL kinase domain mutation) as compared to 5 IM-responders (values of 20-30%, P<0.02). A higher frequency of BCR-ABL kinase domain mutations was also detected in extracts of colonies generated from assays of cells harvested from 3-week suspension cultures initiated with the same starting CD34+ CML cells (21–68% vs 10–43%). A high incidence of BCR-ABL kinase domain mutations was also documented in freshly isolated or cultured CD34+ cells from 2 patients who developed sudden blast crisis (50–63% and 17–83%). Overall, 38 different mutations were identified from freshly isolated CD34+ CML cells and >50 additional mutations were identified in the progeny of CD34+ CML cells cultured ± IM. These included 15 point mutations frequently associated with clinical IM resistance (including G250, Q252, E255, T315, M351, F359 and H396) and >40 mutations not previously described. Furthermore, freshly isolated CD34+ cells from IM-nonresponders (including the 2 patients who developed blast crisis, n=10) showed a greater resistance to IM in vitro (∼2 fold, P< 0.001 with 5 μM and P<0.02 with 10 μM IM) as compared to CD34+ cells from IM-responders (n=8) in the presence of 5 and 10 μM IM, as determined by colony-forming cell (CFC) assays. Although more IM-resistant CFCs were obtained in the presence of IM from 3-week cultures initiated with CD34+ cells from the same IM-nonresponders than from IM responders, these latter differences were not significantly different (P= 0.28). These results suggest that the CD34+ leukemic cells from individual chronic phase CML patients harbor differences in their biologic properties that are predictive of how they will respond to IM therapy and that assessment of these differences may form the basis of rapid, practical and quantitative tests to assist in optimized patient management.
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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 | 0.001 |
| 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".