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The Classical Illegitimate Switch Translocation Model Is Unable To Account for at Least Half of the Translocation Breakpoints from t(4;14)(p16;q32) Multiple Myeloma.

2005· article· en· W2555050655 on OpenAlexaff
Jonathan J. Keats, Erin Strachan, Andrew R. Belch, Linda M. Pilarski

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBreakpointChromosomal translocationBiologyGeneticsDerivative chromosomeLocus (genetics)ChromosomeImmunoglobulin class switchingGeneMolecular biologyChromosome 22B cell

Abstract

fetched live from OpenAlex

Abstract Translocations involving the IgH locus are one of the most common genetic abnormalities observed in multiple myeloma (MM). Unlike several hematological malignancies, MM IgH translocations involve multiple partner chromosomes. Although IgH translocations are not unique to MM, the molecular anatomy of the translocations appears to be different from that observed in most B-cell malignancies. In general, the breakpoints occur within the switch regions of the IgH locus and the translocations appear to result from illegitimate class switch recombination (CSR) events. Previous analysis of the breakpoint junctions from t(4;14) samples suggested that the majority of these translocations result from illegitimate CSR events. These events were characterized by der(4) breakpoints containing Smu-chromosome 4 junctions and der(14) breakpoints with chromosome 4-downstream switch region junctions. However, not all t(4;14) breakpoints fit this “classical” model, as some derivative chromosomes were observed with hybrid switch regions. Unfortunately, the mechanism that generates these hybrid switch regions has been unclear. In general, only a single derivative was cloned from each patient or cell line. In the one case reported elsewhere in which both derivatives were cloned, the mechanism did not appear to be linked to the CSR process and thus represented a “non-classical” translocation. The poor prognostic impact of t(4;14) myeloma has been well established by several groups, including our own. In an attempt to identify recurrent breakpoint sites and to identify the potential mechanism(s) leading to t(4;14) translocations, we cloned the breakpoint junctions of both derivative chromosomes from 4 cell lines and 5 patients with MB4-2 and MB4-3 breakpoints. Furthermore, we cloned der(4) breakpoints from 4 additional patients, three of which are FGFR3 non-expressers for which we could not detect a der(14) breakpoint using our PCR based strategy. We defined the t(4;14) breakpoint region as encompassing 64.5 kb of chromosome 4, flanked by LETM1 exon 3 and MMSET exon 5, based on combining the previously published breakpoints with our newly cloned and sequenced breakpoints. Current dogma suggests that t(4;14) translocation events are randomly distributed throughout the defined breakpoint region, but this idea is not supported by our sequencing data. We identified two hotspots, which contain breakpoints from 9 of the 27 patients or cell lines with at least one cloned derivative. Interestingly, these regions only represent 1 kb of the entire breakpoint region. Therefore 33% of the cloned breakpoints exist within only 1.5% of the total breakpoint region. Moreover, for the 13 MM samples for which both derivatives are cloned, although 6/13 (46%) fit the classical model of CSR mediated switch translocations, surprisingly, 7/13 (54%) appear to be non-classical translocations. The non-classical translocations are defined by little to no loss of sequence from the involved switch region and the presence of a hybrid switch region on one of the two derivative chromosomes. Importantly, the non-classical translocations may not involve B-cell specific mechanisms and could potentially occur before or after a successful CSR event. Therefore, the classical illegitimate CSR event model can explain only half of the t (4; 14) breakpoints cloned to date.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.026
GPT teacher head0.285
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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