Genome-wide copy number analysis of Hodgkin Reed-Sternberg cells identifies recurrent imbalances with correlations to treatment outcome
Bibliographic record
Abstract
In classical Hodgkin lymphoma (cHL) the mechanisms underlying primary refractory disease and relapse remain unknown. To gain further insight into cHL pathogenesis and genomic changes linked to treatment response, we studied 53 cHL patients by array comparative genomic hybridization, including 23 patients whose primary treatment failed, using DNA from microdissected HRS cells. Copy number alterations found in more than 20% of cases included gains of 2p, 9p, 16p, 17q, 19q, 20q, and losses of 6q, 11q, and 13q. We identified at high resolution recurrent changes defining minimally gained and lost regions harboring genes involved in nuclear factor kappaB signaling, such as REL, IKBKB, CD40, and MAP3K14. Gains of chromosome 16p11.2-13.3 were significantly more frequent in pretreatment and relapse biopsies of unresponsive patients and were associated with shortened disease-specific survival (P = .028). In the therapy-resistant HL cell line KMH2, we found genomic gains and overexpression of the multidrug resistance gene ABCC1 mapping to cytoband 16p13.11. We show that doxorubicin exposure to KMH2 induces ABCC1 expression and that siRNA silencing of ABCC1 sensitizes KMH2 cells to doxorubicin toxicity in vitro, suggesting that overexpression of ABCC1 contributes to the drug resistance phenotype found in KMH2.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".