High Levels of MicroRNA-126 Bioactivity Specify the LSC Compartment in AML
Bibliographic record
Abstract
Abstract Leukemia stem cells (LSCs) are a biologically distinct blast population positioned at the apex of the acute myeloid leukemia (AML) developmental hierarchy. A more complete understanding of the unique properties of LSCs is crucial for the identification of novel AML regulatory pathways and the subsequent development of innovative therapies that effectively target these cells in leukemia patients. However, most studies overlook the heterogeneity of AML and the existence of LSC, potentially masking important molecular pathways. MicroRNAs (miRNAs) are an emerging class of non-coding small RNAs that negatively regulate the expression of protein-encoding genes. Normal miRNA expression is tissue and developmental stage restricted, suggesting important roles in tissue specification and/or cell lineage determination. Several studies have already demonstrated that miRNA expression levels are dysregulated in AML. However, little is known of the contribution of miRNAs to the regulation of gene expression and maintenance of LSCs. In order to elucidate the role of miRNAs in the regulation and maintenance of the leukemic stem cell state and the leukemogenic process, primary AML patient samples were fractionated into sub-populations based on the expression of CD34 and CD38 cell surface expression and purified RNA was extracted for miRNA array profiling. Supervised analysis guided by the in vivo SCID leukemia initiating capacity of each sub-population identified a unique 2 miRNA signature associated with leukemia stem cell enriched fractions. Validation of top miRNA candidates was confirmed by standard RT-PCR. However, to confirm that our miRNA candidates were biologically active within the AML developmental hierarchy at a single cell level, we utilized bidirectional miRNA sensor lentivectors (Bd.LV). Bd.LVs co-express truncated NGFR and enhanced GFP (eGFP), and permit post-transcriptional regulation of eGFP when miRNA target sequences (miRT) are placed downstream. One week post-transduction of a unique primary AML patient sample (8227), which can maintain a phenotypic and functional hierarchy for over 200 days in serum-free in vitro culture conditions, multicolor flow cytometry analysis revealed that miR-126 strongly suppressed (17 fold eGFP repression vs. control vector) eGFP expression in CD34+CD38-cells, the sub-fraction of AML that is highly enriched in LSC, while miR-126 activity declined along a gradient of further “differentiation” of the cells. Knockdown of miR-126 activity in 8227 cells with antagomirs designed to target miR-126 resulted in an increase in eGFP expression within the CD34+CD38-population, confirming the specificity of the biosensor lentivector. Furthermore, this expression gradient of miR-126 was conserved in 2 primary patient AML samples after 10 weeks post-transplant into pre-conditioned NOD/SCID mice. These experiments demonstrate that mir-126, a miRNA candidate identified by miRNA array, is more abundantly expressed and biologically active within the leukemia stem cell compartment of the AML hierarchy. Moreover, these data demonstrate the utility of biosensor vector technology in discerning miRNA expression patterns at the single cell level and will be useful for the further refinement of LSC purification.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".