Leukaemia‐related gene expression in bone marrow cells from patients with the preleukaemic disorder Shwachman–Diamond syndrome
Bibliographic record
Abstract
Shwachman-Diamond syndrome (SDS) is an inherited bone marrow failure disorder with cytopenia and a high propensity for myelodysplastic syndrome (MDS) and leukaemia, particularly acute myeloid leukaemia. The mechanism of leukaemogenesis in SDS is unknown. In accordance to the multi-hit theory of carcinogenesis, it is likely that several molecular and cellular hits occur before MDS/leukaemia become apparent. This study used oligonucleotide microarray to identify gene expression patterns, which were shown to be associated with leukaemogenesis, in marrow mononuclear cells of nine SDS patients without overt transformation compared to healthy controls. Among 154 known leukaemia-related genes, several oncogenes were found to be upregulated, including LARG, TAL1 and MLL, and of several tumour suppressor genes were downregulated, including DLEU1, RUNX1, FANCD2 and DKC1. Real time polymerase chain reaction confirmed statistically higher expression of LARG and TAL1 in SDS marrows. We conclude that SDS marrow mononuclear cells exhibit abnormal gene expression patterns, which might result in continuous stimulation favouring evolution or progression of malignant clones. Additional molecular and cytogenetic events are probably necessary for the malignant process to be irreversible and complete.
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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) | 0.001 | 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".