Frequency of <i>MYD88</i> and <i>CD79B</i> mutations, and <i>MGMT</i> methylation in primary central nervous system diffuse large <scp>B</scp>‐cell lymphoma
Bibliographic record
Abstract
Primary CNS diffuse large B-cell lymphoma (PCNS-DLBCL) and systemic DLBCL harbor mutations in MYD88 and CD79B. DNA methyltransferase (MGMT) is methylated in some DLBCL. Our goal was to investigate the frequencies of these events, which have not been previously reported within the same series of patients with PCNS-DLBCL. Fifty-four cases of PCNS-DLBCL from two institutions were analyzed by Sanger sequencing for MYD88 and CD79B, and pyrosequencing for MGMT. MYD88 mutations were identified in 68.8% (35 of 51 cases), with L265P being the most frequent mutation. Mutations other than L265P were identified in 21.6% of cases, of which eight novel MYD88 mutations were identified. Of mutated cases, 17.6% had homozygous/hemizygous MYD88 mutations, which has not been previously reported in PCNS-DLBCL. CD79B mutations were found in six of 19 cases (31.6%), all in the Y196 mutation hotspot. MGMT methylation was observed in 37% (20 of 54 cases). There was no significant difference in median overall survival (OS) between the wild type and mutated MYD88 cases, or between methylated and unmethylated MGMT cases. However, a significant difference (P = 0.028) was noted in median OS between the wild type and mutated CD79B cases.
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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 | 0.001 |
| 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 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".