An In Vitro Model for Acute Myeloid Leukemia Relapse Using the SORE6 Reporter
Bibliographic record
Abstract
Many patients diagnosed with acute myeloid leukemia (AML) relapse within two years of the initial remission. The biology of AML relapse is incompletely understood, although cancer stem-like (CSL) cells have been hypothesized to be important. To test this hypothesis, we employed SORE6, a reporter designed to detect the transcriptional activity of the embryonic stem cell proteins Oct4 and Sox2, to identify/purify CSL cells in two FLT3-mutated AML cell lines. Both cell lines contained ~10% of SORE6+ cells in the steady state. Compared to SORE6− cells, SORE6+ cells exhibited more characteristics of CSL cells, with significantly higher chemoresistance and rates of spheroid formation. SORE6+ cells had substantially higher expression of Myc and FLT3 proteins, which are drivers of SORE6 activity. Using a mixture of SORE6−/SORE6+ cells that were molecularly barcoded, we generated an in vitro study model for AML relapse. Specifically, after ‘in vitro remission’ induced by Ara-C, both cell lines regenerated after 13 ± 3 days. Barcode analysis revealed that most of the regenerated cells were derived from the original SORE6+ cells. Regenerated cells exhibited more CSL features than did the original SORE6+ cells, even though a proportion of them lost SORE6 activity. In bone marrow samples from a patient cohort, we found that relapsed blasts expressed significantly higher levels of Myc, a surrogate marker of SORE6 activity, compared to pre-treatment blasts. To conclude, using our in vitro model, we have provided evidence that CSL cells contribute to AML relapse.
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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 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".