CCND2 and CCND3 hijack immunoglobulin light-chain enhancers in cyclin D1− mantle cell lymphoma
Bibliographic record
Abstract
Abstract Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) translocation resulting in overexpression of cyclin D1. However, a small subset of cyclin D1− MCL has been recognized, and approximately one-half of them harbor CCND2 translocations while the primary event in cyclin D1−/D2− MCL remains elusive. To identify other potential mechanisms driving MCL pathogenesis, we investigated 56 cyclin D1−/SOX11+ MCL by fluorescence in situ hybridization (FISH), whole-genome/exome sequencing, and gene-expression and copy-number arrays. FISH with break-apart probes identified CCND2 rearrangements in 39 cases (70%) but not CCND3 rearrangements. We analyzed 3 of these negative cases by whole-genome/exome sequencing and identified IGK (n = 2) and IGL (n = 1) enhancer hijackings near CCND3 that were associated with cyclin D3 overexpression. By specific FISH probes, including the IGK enhancer region, we detected 10 additional cryptic IGK juxtapositions to CCND3 (6 cases) and CCND2 (4 cases) in MCL that overexpressed, respectively, these cyclins. A minor subset of 4 cyclin D1− MCL cases lacked cyclin D rearrangements and showed upregulation of CCNE1 and CCNE2. These cases had blastoid morphology, high genomic complexity, and CDKN2A and RB1 deletions. Both genomic and gene-expression profiles of cyclin D1− MCL cases were indistinguishable from cyclin D1+ MCL. In conclusion, virtually all cyclin D1− MCLs carry CCND2/CCND3 rearrangements with immunoglobulin genes, including a novel IGK/L enhancer hijacking mechanism. A subset of cyclin D1−/D2−/D3− MCL with aggressive features has cyclin E dysregulation. Specific FISH probes may allow the molecular identification and diagnosis of cyclin D1− MCL.
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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".