Genomic profiling reveals different genetic aberrations in systemic ALK‐positive and ALK‐negative anaplastic large cell lymphomas
Bibliographic record
Abstract
Anaplastic large cell lymphoma (ALCL) is a T/null-cell neoplasm characterized by chromosomal translocations involving the anaplastic lymphoma kinase (ALK) gene (ALK). Tumours with similar morphology and phenotype but negative for ALK have been also recognized. The secondary chromosomal imbalances of these lymphomas are not well known. We have examined 74 ALCL, 43 ALK-positive and 31 ALK-negative, cases by comparative genomic hybridization (CGH), and locus-specific alterations for TP53 and ATM were examined by fluorescence in situ hybridization and real-time quantitative polymerase chain reaction. Chromosomal imbalances were detected in 25 (58%) ALK-positive and 20 (65%) ALK-negative ALCL. ALK-positive ALCL with NPM-ALK or other ALK variant translocations showed a similar profile of secondary genetic alterations. Gains of 17p and 17q24-qter and losses of 4q13-q21, and 11q14 were associated with ALK-positive cases (P = 0.05), whereas gains of 1q and 6p21 were more frequent in ALK-negative tumours (P = 0.03). Gains of chromosome 7 and 6q and 13q losses were seen in both types of tumours. ALCL-negative tumours had a significantly worse prognosis than ALK-positive. However no specific chromosomal alterations were associated with survival. In conclusion, ALK-positive and negative ALCL have different secondary genomic aberrations, suggesting they correspond to different genetic entities.
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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".