Gene Expression Signatures Predict Overall Survial in Diffuse Large B Cell Lymphoma Treated with Rituximab and Chop-Like Chemotherapy.
Bibliographic record
Abstract
Abstract Gene expression profiling has been used to distinguish two major subtypes of diffuse large B cell lymphoma (DLBCL), termed germinal center B cell-like (GCB) DLBCL and activated B cell-like (ABC) DLBCL. Following CHOP-like chemotherapy, GCB and ABC DLBCLs had distinct 5-year survival rates of ∼60% and ∼30%, respectively. Prognostic gene expression signatures in CHOP-treated DLBCL include the lymph node signature, which reflects a non-malignant host response, the MHC class II signature, both favorable when expressed and the proliferation signature which is adverse when expressed. The addition of rituximab to CHOP chemotherapy (R-CHOP) has significantly improved the outcome for DLBCL patients. We therefore investigated, if gene expression signatures that predicted survival among DLBCL patients treated with CHOP remained predictive for DLBCL patients treated with R-CHOP. Gene expression profiling was performed on 156 samples from previously untreated patients with DLBCL using Affymetrix U133 plus arrays. All patients received rituximab and CHOP-like chemotherapy. Samples were classified as GCB DLBCL, ABC DLBCL, or unclassified, and were assessed for expression of the lymph node and proliferation signatures. A Cox-proportional hazards model was used to determine the association of these gene expression features with overall survival (OS). 71 DLBCL samples were classified as GCB DLBCL, 63 as ABC DLBCL, and 22 were unclassified. The addition of rituximab improved OS for both GCB and ABC DLBCL compared to historical controls treated with CHOP-like chemotherapy alone. After a median follow-up of 2.3 years, GCB DLBCL had a more favorable OS than ABC DLBCL, with 3-year OS rates of 86% vs. 68% (p = 0.014). The 3-year OS rate of unclassified DLBCLs was 69%. The lymph node signature was associated with favorable OS (p = 0.023) and the proliferation signature with inferior OS (p = 0.009), whereas the MHC class II signature was not associated with OS (p = 0.44). In summary, addition of rituximab to CHOP-like chemotherapy improved OS for both GCB and ABC DLBCL but ABC DLBCL remained inferior to GCB DLBCL. The prognostic value of the lymph node and proliferation signatures were maintained in the context of R-CHOP therapy. An understanding of the biological attributes of DLBCL tumors that are reflected in these gene expression signatures remains critical to our ability to improve survival of these patients.
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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 | 0.000 | 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 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".