REFINEMENT OF MUM1 EXPRESSION THRESHOLD FOR DOUBLE POSITIVE CD10+ MUM1+ DIFFUSE LARGE B CELL LYMPHOMA ALLOWS A BETTER CELL OF ORIGIN CLASSIFICATION FOR GCB SUBTYPE
Bibliographic record
Abstract
The cell-of-origin (COO) determination of diffuse large B cell lymphoma (DLBCL) into germinal center B-cell like (GCB) and activated B-cell like (ABC) by immunohistochemistry based on the most commonly used Hans’ algorithm, has at most 86% (Meyer et al, JCO, 2011) to 91% of concordance (Petrella et al, Annals Oncol, 2017) compared with the gold standard gene-expression profiling approach. Among those discrepancies, the algorithm is giving to CD10 positivity a priority over MUM1 for assigning GCB subtype, whatever the level of expression of MUM1 above 30%. Indeed, a substantial number of cases featuring a double positive (DP) CD10+ MUM1+ phenotype are classified as GCB according to Hans’ algorithm whereas ABC on gene expression profiling. The aim of this study was to evaluate whether the expression level of MUM1 assessed by immunohistochemistry could predict the molecular classification of DP in GCB or ABC. For that purpose, we used 2 independent cohorts of patients: one with 1608 DLBCLs from LYSA trials (GHEDI Cohort, GAINED, REMARC, RT3), the other with 255 DLBCLs treated in Nantes University Hospital (CHU Nantes) between 2006 and 2016. One hundred twenty two and 22 DP DLBCLs respectively were identified in these 2 cohorts, representing 8% of DLBCLs. RNA extracted from FFPE tissues was available for 91 DP DLBCLs, tested for gene expression profiling by the RT-MLPA assay, a sensitive method validated on archival paraffin-embedded formalin-fixed (FFPE) tissues for the GCB/ABC classification (Bobee et al, J Mol Diagn, 2017). The level of MUM1 expression by 10% increments was evaluated on those 91 cases by three pathologists on multihead microscope. Among the 81 DP DLBCLs with available results (5 failures, 2 DLBCL EBV+ and 3 PMBL) for GCB/ABC classification by RT-MLPA, 48 cases (59.2%) were classified in GCB molecular subtype, 25 (30.8%) in ABC and 8 were unclassified (9.8%). In order to correctly identify GCB molecular DP DLBCLs based on Hans’ algorithm, depending on MUM1+ tumor cells, we tested different MUM1 thresholds (Table 1). A MUM1 threshold ≤ 50% correctly identified 19/48 molecular GCB and misclassified only 1 ABC (specificity 95%), while higher thresholds could not reliably identify GCB or ABC DLBCL. Overall, our study clearly demonstrates that Hans’ algorithm cannot be used to accurately identify molecular GCB and ABC DLBCL within the DP CD10+MUM1+ except when MUM1+ tumor cells do not exceed 50%. This new threshold could be included in the Hans’ algorithm to identify GCB DLBCLs among DP DLBCLs. Above this threshold, targeted gene expression tests should be used to correctly classify these subgroups of DLBCLs for COO. Keywords: diffuse large B-cell lymphoma (DLBCL).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 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".