Detailed Characterization of Mesenchymal Stem/Stromal Cells from a Large Cohort of AML Patients Demonstrates a Definitive Link to Treatment Outcomes
Bibliographic record
Abstract
Bone marrow mesenchymal stem/stromal cells (BM-MSCs) are key components of the hematopoietic niche thought to have a direct role in leukemia pathogenesis. BM-MSCs from patients with acute myeloid leukemia (AML) have been poorly characterized due to disease heterogeneity. We report a functional, genetic, and immunological characterization of BM-MSC cultures from 46 AML patients, stratified by molecular/cytogenetics into low-risk (LR), intermediate-risk (IR), and high-risk (HR) subgroups. Stable MSC cultures were successfully established and characterized from 40 of 46 AML patients irrespective of the risk subgroup. AML-derived BM-MSCs never harbored tumor-specific cytogenetic/molecular alterations present in blasts, but displayed higher clonogenic potential than healthy donor (HD)-derived BM-MSCs. Although HD- and AML-derived BM-MSCs equally provided chemoprotection to AML cells in vitro, AML-derived BM-MSCs were more immunosuppressive/anti-inflammatory, enhanced suppression of lymphocyte proliferation, and diminished secretion of pro-inflammatory cytokines. Multivariate analysis revealed that the level of interleukin-10 produced by AML-derived BM-MSCs as an independent prognostic factor negatively affected overall survival. Collectively our data show that AML-derived BM-MSCs are not tumor related, but display functional differences contributing to therapy resistance and disease evolution.
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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 | 0.001 | 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 | 0.000 |
| 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".