Acute Myeloid Leukemia (AML): Upregulation of BAALC/MN1/MLLT11/EVI1 Gene Cluster Relate With Poor Overall Survival and a Possible Linkage With Coexpression of MYC/BCL2 Proteins
Bibliographic record
Abstract
BACKGROUND: Molecular heterogeneity accounts for the variable and often poor prognosis in acute myeloid leukemia (AML). The current risk stratification strategy in clinical practice is limited to karyotyping and limited molecular studies screening for genetic mutations such as FLT-3 and NPM1. There is opportunity to identify further molecular prognostic markers, which may also lay the groundwork for the development of novel targeted therapies. Complex molecular technologies require transition into widely available laboratory platforms, for better integration into routine clinical practice. METHOD: In a defined subset (MYC/BCL2 or MYC/BCL2) of AML patients (n=20), we examined expression signature of several genes (n=12) of established prognostic value in AML. RNA expression and MYC/BCL2 protein pattern was correlated with 3 cytogenetic risk groups and overall survival. RESULTS: K-means++ unsupervised clustering defined 2 distinct groups with high and low transcript levels of BAALC/MN1/MLLT11/EVI1/SOCS2 genes (>2.5-fold difference; P<0.001). This mRNA signature trended with higher prevalence of MYC/BCL2 coexpression (P<0.057) and poor overall survival (P<0.036), but did not correlate with conventional cytogenetic risk groups (P<0.084). CONCLUSIONS: This pilot study provides useful data, which may help further refine the prognostic scheme of AML patients outside conventional cytogenetic risk groups. It also presents some biological rationale for future studies to explore the use of novel agents targeting MYC and/or BCL2 genes in combination with conventional chemotherapy protocols for AML.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".