High-resolution whole genome tiling path array CGH analysis of CD34+ cells from patients with low-risk myelodysplastic syndromes reveals cryptic copy number alterations and predicts overall and leukemia-free survival
Bibliographic record
Abstract
Myelodysplastic syndromes (MDSs) pose an important diagnostic and treatment challenge because of the genetic heterogeneity and poorly understood biology of the disease. To investigate initiating genomic alterations and the potential prognostic significance of cryptic genomic changes in low-risk MDS, we performed whole genome tiling path array comparative genomic hybridization (aCGH) on CD34(+) cells from 44 patients with an International Prognostic Scoring System score less than or equal to 1.0. Clonal copy number differences were detected in cells from 36 of 44 patients. In contrast, cells from only 16 of the 44 patients displayed karyotypic abnormalities. Although most patients had normal karyotype, aCGH identified 21 recurring copy number alterations. Examples of frequent cryptic alterations included gains at 11q24.2-qter, 17q11.2, and 17q12 and losses at 2q33.1-q33.2, 5q13.1-q13.2, and 10q21.3. Maintenance of genomic integrity defined as less than 3 Mb total disruption of the genome correlated with better overall survival (P = .002) and was less frequently associated with transformation to acute myeloid leukemia (P = .033). This study suggests a potential role for the use of aCGH in the clinical workup of MDS patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".