Angioimmunoblastic T‐cell lymphoma: more than a disease of T follicular helper cells
Bibliographic record
Abstract
Abstract Angioimmunoblastic T‐cell lymphoma (AITL) is one of the most frequent entities of peripheral T‐cell lymphoma. An AITL has two components: the AITL tumour cells, which have a T follicular helper (TFH) cell phenotype, and a surrounding and extensive tumour microenvironment that is populated with various reactive cell types, including B cells. Recurrent TET2 mutations have been described in 50–80% of AITLs, possibly occurring in a haematopoietic progenitor cell. An article published recently in the Journal of Pathology describes the use of microdissection to isolate PD1+ AITL tumour cells and CD20+ B cells from the AITL microenvironment, and to show that TET2 mutations are actually more frequent in these diseases than previously thought. Whereas TET2 mutations were detected in only six of 13 AITLs, 12 of 13 samples of microdissected PD1+ AITL tumour cells possessed this mutation. Moreover, TET2 mutations were detected in CD20+ B cells from the AITL microenvironment in six of nine informative cases. These results confirm that TET2 mutation is an early event in the majority of AITL cases, and that the driving molecular anomalies are not restricted to the T lineage tumour cells. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".