Cytogenetic abnormalities in MALT lymphomas and their precursor lesions from different organs. A fluorescence <i>in situ</i> hybridization (FISH) study
Bibliographic record
Abstract
AIMS: To analyse the possible activation of distinct molecular pathways in mucosa-associated lymphoid tissue (MALT) lymphoma, we determined the prevalence of trisomies 3, 12, 18 in MALT lymphomas from different organs, as well as the prevalence of translocations of the MALT1 gene in a subset of primary breast MALT lymphomas. We compared the numerical cytogenetic alterations in lymphomas, precursor lesions and in normal non-haematolymphoid tissue from the same organs. METHODS AND RESULTS: Forty-two samples of paraffin-embedded tissue (29 MALT lymphomas from stomach, breast, parotid and thyroid; two Sjögren's syndrome; two Hashimoto's thyroiditis and nine reactive samples) were studied by fluorescence in situ hybridization (FISH). Analysed together, the cases of gastric, parotid and thyroid MALT lymphomas presented trisomy 3 in 46%, trisomy 12 in 28% and trisomy 18 in 21% of the cases. In contrast to other locations, trisomy 3 was not present in the majority of the cases of primary breast MALT lymphomas. None of the nine breast cases presented MALT1 gene rearrangements. Half of the cases of preneoplastic lesions exhibited trisomy 3 and trisomy 12; none exhibited trisomy 18. CONCLUSIONS: Trisomy 3 is the most frequent numerical abnormality in gastric, parotid and thyroid but not in primary breast MALT lymphomas. MALT1 gene rearrangements are also rare in this location, suggesting that distinct molecular pathways may be activated in breast cases.
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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) | 0.002 | 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".