PD‐L1 and PD‐1 expression in pediatric post‐transplant Burkitt lymphoma and other monomorphic post‐transplant lymphoproliferative disorders
Bibliographic record
Abstract
Abstract Background Post‐transplant lymphoproliferative disorders (PTLD) develop as a consequence of immune suppression. Programmed death protein 1 (PD‐1), a regulator of host immune activation, binds to programmed death‐ligand 1 (PD‐L1) to suppress the T‐cell immune response. PD‐1/PD‐L1 pathway may play a role in PTLD. The objective was to describe intratumoral expression of PD‐L1 and PD‐1 in pediatric monomorphic PTLD, and assess if density of these cells is associated with progression‐free survival (PFS) and overall survival (OS). Procedure Clinical variables and outcome data were collected on B‐cell monomorphic PTLD treated in Toronto, Canada between 2000 and 2017. Diagnostic area from tumor tissue was identified to count CD3‐positive or PD‐1‐positive cells and CD3‐negative lymphoma B cells or PD‐L1‐positive cells. CD3+, PD‐1+, and PD‐L1+ cell densities were compared between cases of PTLD. OS and PFS were analyzed. Results We identified 25 cases of B‐cell monomorphic PTLD; majority Burkitt lymphoma (32%) and diffuse large B‐cell lymphoma (56%). All cases had CD3+ cells infiltrating the tumor, and median percentage of CD3+ cells was 14% (interquartile range: 6.2%–25%). Twelve cases (48%) had PD‐1+ cell infiltrating (range: 1%–83%) and 13 cases (52%) had no PD‐1+ cells infiltrating. Sixteen cases (64%) had PD‐L1+ cells present; however, there was no PD‐L1 expression on any Burkitt lymphoma tissue. When comparing PD‐1 and PD‐L1 expression, there was no difference in OS or PFS. Conclusion Intratumoral presence of PD‐1+ and PD‐L1+ cells varied in pediatric patients with monomorphic PTLD; however, no relationship to OS and PFS was identified.
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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 | 0.001 |
| 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) | 0.001 | 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".