Survival of Del17p CLL Depends on Genomic Complexity and Somatic Mutation
Bibliographic record
Abstract
PURPOSE: Chronic lymphocytic leukemia (CLL) with 17p deletion typically progresses quickly and is refractory to most conventional therapies. However, some del(17p) patients do not progress for years, suggesting that del(17p) is not the only driving event in CLL progression. We hypothesize that other concomitant genetic abnormalities underlie the clinical heterogeneity of del(17p) CLL. EXPERIMENTAL DESIGN: We profiled the somatic mutations and copy number alterations (CNA) in a large group of del(17p) CLLs as well as wild-type CLL and analyzed the genetic basis of their clinical heterogeneity. RESULTS: We found that increased somatic mutation number associates with poor overall survival independent of 17p deletion (P = 0.003). TP53 mutation was present in 81% of del(17p) CLL, mostly clonal (82%), and clonal mutations with del(17p) exhibit shorter overall survival than subclonal mutations with del(17p) (P = 0.019). Del(17p) CLL has a unique driver mutation profile, including NOTCH1 (15%), RPS15 (12%), DDX3X (8%), and GPS2 (6%). We found that about half of del(17p) CLL cases have recurrent deletions at 3p, 4p, or 9p and that any of these deletions significantly predicts shorter overall survival. In addition, the number of CNAs, but not somatic mutations, predicts shorter time to treatment among patients untreated at sampling. Indolent del(17p) CLLs were characterized by absent or subclonal TP53 mutation and few CNAs, with no difference in somatic mutation number. CONCLUSIONS: We conclude that del(17p) has a unique genomic profile and that clonal TP53 mutations, 3p, 4p, or 9p deletions, and genomic complexity are associated with shorter overall survival. Clin Cancer Res; 23(3); 735-45. ©2016 AACR.
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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 | 0.001 |
| 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) | 0.002 | 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".