Duodenal follicular lymphoma: Comprehensive gene expression analysis with insights into pathogenesis
Bibliographic record
Abstract
Follicular lymphoma (FL) of the gastrointestinal tract, particularly duodenal follicular lymphoma (DFL), is a rare variant of FL with indolent clinical behavior, and this disease is included in the 2008 World Health Organization classification system. In contrast to nodal follicular lymphoma (NFL), DFL occurs most frequently in the second part of the duodenum, lacks follicular dendritic cell meshworks and has memory B-cell characteristics. However, its molecular pathogenesis is still unclear. In the present study, we examined 10 DFL, 18 NFL and 10 gastric MALT lymphoma samples using gene expression analysis. Quantitative RT-PCR experiments and immunohistochemical analysis for 72 formalin-fixed, paraffin-embedded tissues from an independent series, including 32 DFL, 19 gastric MALT lymphoma and 27 NFL samples, were performed for validation of microarray data. Gene expression profiles of the three lymphoma types were compared using 2918 differentially expressed genes (DEG) and results suggested that DFL shares characteristics of MALT lymphoma. Among these DEG, CCL20 and MAdCAM-1 were upregulated in DFL and MALT but downregulated in NFL. In contrast, protocadherin gamma subfamily genes were upregulated in DFL and NFL. Quantitative RT-PCR and immunohistochemical studies demonstrated concordant results. Double immunofluorescence studies revealed that CCL20 and CCR6 were co-expressed in both DFL and MALT. We hypothesize that increased expression of CCL20 and MAdCAM-1 and co-expression of CCL20 and CCR6 may play an important role in tumorigenesis.
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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 | 0.001 |
| 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) | 0.000 | 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".