MicroRNA profiles of t(14;18)–negative follicular lymphoma support a late germinal center B-cell phenotype
Bibliographic record
Abstract
A total of 90% of follicular lymphomas (FLs) harbor the translocation t(14;18) leading to deregulated BCL2 expression. Conversely, 10% of FLs lack the t(14;18), and the majority of these FLs do not express BCL2. The molecular features of t(14;18)-negative FLs remain largely unknown. We performed microRNA expression analysis in 32 FL grades 1 to 3A, including 17 t(14;18)-positive FLs, 9 t(14;18)-negative FLs without BCL2 expression, and 6 t(14;18)-negative FLs with BCL2 expression. MicroRNA profiles were correlated with corresponding mRNA expression patterns, and potential targets were investigated by quantitative PCR and immunohistochemistry in an independent validation series of 83 FLs. Statistical analysis identified 17 microRNAs that were differentially expressed between t(14;18)-positive FLs and t(14;18)-negative FLs. The down-regulation of miR-16, miR-26a, miR-101, miR-29c, and miR138 in the t(14;18)-negative FL subset was associated with profound mRNA expression changes of potential target genes involving cell cycle control, apoptosis, and B-cell differentiation. miR-16 target CHEK1 showed increased expression in t(14;18)-negative FLs, whereas TCL1A expression was reduced, in line with a partial loss of the germinal center B-cell phenotype in this FL subset. In conclusion, t(14;18)-negative FL have distinct microRNA profiles that are associated with an increased proliferative capacity and a "late" germinal center B-cell phenotype.
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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) | 0.001 | 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".