Leukemia-Related Gene Expression of Bone Marrow Cells from Patients with Shwachman-Diamond Syndrome at the Pre-Leukemic Phase.
Bibliographic record
Abstract
Abstract Background: Shwachman-Diamond syndrome (SDS) is an inherited bone marrow failure disorder characterized by varying degrees of cytopenia and a high propensity for myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) in up to 36% of the patients by the age of 30 years. Although the gene associated with SDS, SBDS, has recently been identified, its function, the link with MDS/AML and the mechanism for the development of MDS/AML in SDS is unclear and the molecular events occurring during transformation haven’t been yet identified. It is likely that several events occur many years before overt transformation occurs, and might be identifiable by comprehensive analysis. Objectives: To use oligonucleotide microarray to identify leukemogenic gene expression before overt transformation, which can explain a propensity for MDS/AML. Methods: Total RNA from marrow cells from 9 SDS patients and 7 healthy age-matched donors of bone marrows for transplantation was extracted, labeled and hybridized to Affymetrix HG_U133_Plus2.0 GeneChip. Data were pre-processed using robust multichip analysis (RMA) and differentially expressed genes were identified with permutation-based methods. False discovery rate (FDR)-adjusted p-values were used to rank genes and cluster analysis grouped genes and samples. Real-time PCR was performed to confirm differential expression of genes found by microarray. Results: Of the 38,500 genes on the HG_133_Plus2.0 we analyzed 52 known leukemia-related genes. We identified several genes with small FDR-adjusted p-values. Clustering of arrays resulted in two clusters that clearly separated patients from controls. Interestingly among the leukemia-related genes, the most differentially expressed gene (T=4.2) was ARHGEF12, a member of the Rho GEF family. Rho GEFs are oncogenes; many of them can transform NIH 3T3 cells into a malignant phenotype by altering expression and activation of Rho GTPases. ARHGEF12 is mapped at 11q23, telomeric to MLL, and is a novel MLL fusion partner in acute myeloid leukemia. Real time PCR after normalization against beta-actin confirmed statistically higher expression of the ARHGEF12 (p=0.03) in SDS marrow cells. In addition to ARHGEF12, we have found striking expression changes in several other genes, related to MDS/AML including TAL1, whose differential expression was also confirmed by real-time PCR. Conclusions: SDS marrow cells exhibit abnormal gene expression pattern, which might results in continuous stimulation favoring evolution or progression of malignant clones. Additional molecular and cytogenetic events are likely necessary for the malignant process to be irreversible and complete. Although analysis of whole marrow cells may not enable the detection of genes with lower differential expression between SDS and normal, it may still assist identifying molecular pathways involved in leukemogenesis. This is critically important when studying marrow failure disorders as obtaining sufficient amount of RNA from purified cell population is largely impossible.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".