Distribution and clinical impact of molecular subtypes with dark zone signature of DLBCL in a Japanese real-world study
Bibliographic record
Abstract
The distribution and clinical impact of cell-of-origin (COO) subtypes of diffuse large B-cell lymphoma (DLBCL) outside Western countries remain unknown. Recent literature also suggests that there is an additional COO subtype associated with the germinal center dark zone (DZ) that warrants wider validation to generalize clinical relevance. Here, we assembled a cohort of Japanese patients with untreated DLBCL and determined the refined COO subtypes, which include the DZ signature (DZsig), using the NanoString DLBCL90 assay. To compare the distribution and clinical characteristics of the molecular subtypes, we used a data set from the cohort of British Columbia Cancer (BCC) (n = 804). Through the 1050 patient samples on which DLBCL90 assay was successfully performed in our cohort, 35%, 45%, and 6% of patients were identified to have germinal center B-cell-like (GCB) DLBCL, activated B-cell-like (ABC) DLBCL, and DZsig-positive (DZsigpos) DLBCL, respectively, with the highest prevalence of ABC-DLBCL, differing significantly from the BCC result (P < .001). GCB-DLBCL, ABC-DLBCL, and DZsigpos-DLBCL were associated with 2-year overall survival rates of 88%, 75%, and 66%, respectively (P < .0001), with patients with DZsigpos-DLBCL having the poorest prognosis. In contrast, GCB-DLBCL without DZsig showed excellent outcomes after rituximab-containing immunochemotherapy. DZsigpos-DLBCL was associated with the significant enrichment of tumors with CD10 expression, concurrent MYC/BCL2 expression, and depletion of microenvironmental components (all, P < .05). These results provide evidence of the distinct distribution of clinically relevant molecular subtypes in Japanese DLBCL and that refined COO, as measured by the DLBCL90 assay, is a robust prognostic biomarker that is consistent across geographical areas.
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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".