Aberrant immunoglobulin class switch recombination and switch translocations in activated B cell–like diffuse large B cell lymphoma
Bibliographic record
Abstract
To elucidate the mechanisms underlying chromosomal translocations in diffuse large B cell lymphoma (DLBCL), we investigated the nature and extent of immunoglobulin class switch recombination (CSR) in these tumors. We used Southern blotting to detect legitimate and illegitimate CSR events in tumor samples of the activated B cell-like (ABC), germinal center B cell-like (GCB), and primary mediastinal B cell lymphoma (PMBL) subgroups of DLBCL. The frequency of legitimate CSR was lower in ABC DLBCL than in GCB DLBCL and PMBL. In contrast, ABC DLBCL had a higher frequency of internal deletions within the switch mu (Smu) region compared with GCB DLBCL and PMBL. ABC DLBCLs also had frequent deletions within Sgamma and other illegitimate switch recombinations. Sequence analysis revealed ongoing Smu deletions within ABC DLBCL tumor clones, which were accompanied by ongoing duplications and activation-induced cytidine deaminase-dependent somatic mutations. Unexpectedly, short fragments derived from multiple chromosomes were interspersed within Smu in one case. These findings suggest that ABC DLBCLs have abnormalities in the regulation of CSR that could predispose to chromosomal translocations. Accordingly, aberrant switch recombination was responsible for translocations in ABC DLBCLs involving BCL6, MYC, and a novel translocation partner, SPIB.
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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 | 0.001 | 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".