Amplification of 2p as a genomic marker for transformation in lymphoma
Bibliographic record
Abstract
To outline further genetic mechanisms of transformation from follicular lymphoma (FL) to diffuse large B-cell lymphoma (DLBCL), we have performed whole genome array-CGH in 81 tumors from 60 patients [29 de novo DLBCL (dnDLBCL), 31 transformed DLBCL (tDLBCL), and 21 antecedent FL]. In 15 patients, paired tumor samples (primary FL and a subsequent tDLBCL) were available, among which three possessed more than two subsequent tumors, allowing us to follow specific genetic alterations acquired before, during, and after the transformation. Gain of 2p15-16.1 encompassing, among others, the REL, BCL11A, USP34, COMMD1, and OTX1 genes was found to be more common in the tDLBCL compared with dnDLBCL (P < 0.001). Furthermore, a high-level amplification of 2p15-16.1 was also detected in the FL stage prior to transformation, indicating its importance during the transformation event. Quantitative real-time PCR showed a higher level of amplification of REL, USP34, and COMMD1 (all involved in the NFκΒ-pathway) compared with BCL11A, which indicates that the altered genes disrupting the NFκΒ pathway may be the driver genes of transformation rather than the previously suggested BCL11A. Moreover, a 17q21.33 amplification was exclusively found in tDLBCL, never in FL (P < 0.04) or dnDLBCL, indicating an upregulation of genes of importance during the later phase of transformation. Taken together, our study demonstrates potential genomic markers for disease progression to clinically more aggressive forms. We also confirm the importance of the TP53-, CDKN2A-, and NFκΒ-pathways for the transformation from FL to DLBCL.
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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".