Promiscuity of translocation partners in multiple myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is characterized by karyotypic instability, including chromosomal translocations involving the IGH locus. MM cells display a promiscuity of translocation partners, only some of which are recurrent. We propose that several factors, including temporal and spatial nuclear positioning of potential partner loci, "off-target" IGH diversification mechanisms, and aberrant repair pathways contribute to the promiscuity of translocation partners in MM. We speculate that in MM, IGH diversification processes [V(D)J recombination, somatic hypermutation, and class switch recombination] in B cells may not be restricted to specific stages of B-cell development or within specific immune tissues, but may occur in different temporal "windows." Before or during MM evolution, off-target activities of the enzymes involved in IGH modification processes may contribute to the generation of double-strand breaks (DSB) in translocation partner loci. In the parent B cells from which MM originates, spatial proximity within the nucleus of IGH and potential translocation partners contributes to the selection of a translocation partner and the clinical frequency at which a specific translocation occurs. The spatial proximity of IGH and specific translocation partners may be temporal and contribute not only to partner selection but also to the promiscuity of partners seen in MM. Lastly, aberrant repair mechanisms in MM progenitors (including the possibility that a Ku 86 variant allows for positional instability at DSBs) may also contribute to the promiscuity of chromosome translocation partners in MM.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".