Different characteristics identified by single nucleotide polymorphism array analysis in leukemia suggest the need for different application strategies depending on disease category
Bibliographic record
Abstract
The purpose of this study was to evaluate the detection rate of chromosomal rearrangements in leukemia using single nucleotide polymorphism array (SNP-A) in combination with metaphase cytogenetics (MC), with the aim of proposing a practical approach for clinical karyotyping applications of SNP-A. The Genome-Wide Human SNP Array 6.0 (Affymetrix, Santa Clara, CA) was applied in 469 patients with a variety of hematologic malignancies. Combined use of SNP-A with MC improved the detection rate in comparison with MC alone: acute myeloid leukemia (AML) with normal karyotype (NK), 32% versus 0%; core binding factor (CBF)-AML 40% versus 29%; myelodysplastic syndrome (MDS), 54% versus 39%; chronic myeloid leukemia (CML), 24% versus 3%; and acute lymphoblastic leukemia (ALL), 88% versus 63%. Different patterns of abnormalities (especially the type, size, and location) were noted in the leukemia subtypes. Copy neutral loss of heterozygosity lesions was detected in 23% of AML-NK, 3% of CBF-AML, 25% of MDS, 2% of CML, and 20% of ALL. SNP-A also provided information on cryptic deletions and a variety of aneuploidies in ALL, while the benefit was minimal in CML. In conclusion, different patterns of abnormal lesions were presented according to the disease category, thus requiring a different approach of adopting SNP-A-based karyotyping among different leukemia subtypes.
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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) | 0.000 | 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) | 0.000 | 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".