EBV+ nodal T/NK-cell lymphoma associated with clonal hematopoiesis and structural variations of the viral genome
Bibliographic record
Abstract
ABSTRACT: Epstein-Barr virus (EBV)-positive (EBV+) nodal T- and natural killer (NK)-cell lymphoma is a peripheral T-cell lymphoma (EBV+ nPTCL) that presents as a primary nodal disease with T-cell phenotype and EBV-harboring tumor cells. To date, the genetic aspect of EBV+ nPTCL has not been fully investigated. In this study, whole-exome and/or whole-genome sequencing was performed on 22 cases of EBV+ nPTCL. TET2 (68%) and DNMT3A (32%) were observed to be the most frequently mutated genes whose presence was associated with poor overall survival (P = .004). The RHOA p.Gly17Val mutation was identified in 2 patients who had TET2 and/or DNMT3A mutations. In 4 patients with TET2/DNMT3A alterations, blood cell-rich tissues (the bone marrow [BM] or spleen) were available as paired normal samples. Of 4 cases, 3 had at least 1 identical TET2/DNMT3A mutation in the BM or spleen. Additionally, the whole part of the EBV genome was sequenced and structural variations (SVs) were found frequent among the EBV genomes (63%). The most frequently identified type of SV was deletion. In 1 patient, 4 pieces of human chromosome 9, including programmed death-ligand 1 gene (PD-L1) were identified to be tandemly incorporated into the EBV genome. The 3' untranslated region of PD-L1 was truncated, causing a high-level of PD-L1 protein expression. Overall, the frequent TET2 and DNMT3A mutations in EBV+ nPTCL seem to be closely associated with clonal hematopoiesis and, together with the EBV genome deletions, may contribute to the pathogenesis of this intractable lymphoma.
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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 | 0.000 |
| 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) | 0.000 | 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".