Lymphoid enhancer binding factor 1 (LEF1) expression is significantly higher in Hodgkin lymphoma associated with Richter syndrome relative to de novo classic Hodgkin lymphoma
Bibliographic record
Abstract
Lymphoid enhancer binding factor 1 (LEF1) is consistently upregulated in chronic lymphocytic leukemia (CLL) and in a subset of large B cell lymphoma. Knowledge of LEF1 expression in Hodgkin lymphoma is limited. In this study, we used immunohistochemistry to survey LEF1 expression in various subsets of Hodgkin lymphoma, de novo classic Hodgkin lymphoma (CHL) (n = 43), Hodgkin lymphoma associated with Richter syndrome (HL-RS) (n = 20), and nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) (n = 9). LEF1 expression was significantly higher in HL-RS compared with de novo CHL (12/20, 60% vs. 12/43, 28%; p = 0.0248). Only a single case (1/9; 11%) of NLPHL showed LEF1 expression. Epstein-Barr virus encoded RNA (EBER) was detected in 17 (40%) cases of de novo CHL and 14 (70%) HL-RS. Notably, we identified a correlation between LEF1 expression and EBER positivity (p = 0.0488). We concluded that LEF1 is commonly positive in CHL but not in NLPHL, and such a distinction may be helpful in this differential diagnosis. The higher frequency of LEF1 upregulation in HL-RS relative to de novo CHL suggests that these neoplasms might have different underlying pathogenic mechanisms and warrants further investigation.
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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".