Acquired <i>TNFRSF14</i> Mutations in Follicular Lymphoma Are Associated with Worse Prognosis
Bibliographic record
Abstract
Clinical correlative studies have linked 1p36 deletions with worse prognosis in follicular lymphoma (FL). In this study, we sought to identify the critical gene(s) in this region that is responsible for conferring inferior prognosis. BAC array technology applied to 141 FL specimens detected a minimum region of deletion (MRD) of ∼97 kb within 1p36.32 in 20% of these cases. Frequent single-nucleotide polymorphism-detected copy-neutral loss of heterozygosity was also found in this region. Analysis of promoter CpGs in the MRD did not reveal differential patterns of DNA methylation in samples that differed in 1p36 status. Exon sequencing of MRD genes identified somatic alterations in the TNFRSF14 gene in 3 of 11 selected cases with matching normal DNA. An expanded cohort consisting of 251 specimens identified 46 cases (18.3%) with nonsynonymous mutations affecting TNFRSF14. Overall survival (OS) and disease-specific survival (DSS) were associated with the presence of TNFRSF14 mutation in patients whose overall treatment included rituximab. We further showed that inferior OS and DSS were most pronounced in patients whose lymphomas contained both TNFRSF14 mutations and 1p36 deletions after adjustment for the International Prognostic Index [hazard ratios of 3.65 (95% confidence interval, 1.35-9.878, P=0.011) and 3.19 (95% confidence interval, 1.06-9.57, P=0.039), respectively]. Our findings identify TNFRSF14 as a candidate gene associated with a subset of FL, based on frequent occurrence of acquired mutations and their correlation with inferior clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".