Detection of Chromosome 13q Deletions and IgH Translocations in Patients with Multiple Myeloma by FISH: Comparison with Karyotype Analysis
Bibliographic record
Abstract
Multiple myeloma (MM) is a plasma cell dyscrasia characterized by frequent 13q deletions and IgH translocations that have clinical prognostic significance. We evaluated clonal plasma cells by interphase fluorescence in situ hybridization (FISH) and combined with immunofluorescence detection of cytoplasmic light chain (cIg-FISH) for the presence of 13q deletions and IgH translocations. The FISH results were compared with conventional cytogenetic analysis. Of the 25 bone marrow specimens from MM patients, 11 (44%) had 13q deletions. IgH translocations involving cyclin D1 (t(11;14)) and FGFR3 (t(4;14)) were found in 32 and 36%, respectively. P53 deletions were detected in 20% of the cases. One patient had coexistence of t(ll;14) and t(4;14), which has not been previously reported. Conventional cytogenetic analysis was performed in 15 cases and revealed complex numerical and structural changes in 7. Karyotype analysis failed to detect 3 of 6 cases with 13q deletions, and also missed most of the IgH translocations and p53 deletions detected by cIg-FISH. On the other hand, the complex numerical and structural changes shown by conventional cytogenetics were not demonstrated by interphase FISH. Since 13q deletions, IgH translocations and a hypodiploid karyotype are significant prognostic factors for MM, our study illustrates the importance of combining conventional cytogenetics with interphase FISH analysis in patients with 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".