Apoptotic Blocks in Primary Non-Hodgkin B Cell Lymphomas Identified by BH3 Profiling
Bibliographic record
Abstract
To determine causes of apoptotic resistance, we analyzed 124 primary B cell NHL samples using BH3 profiling, a technique that measures the mitochondrial permeabilization upon exposure to synthetic BH3 peptides. Our cohort included samples from chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), high-grade B cell lymphoma with translocations in MYC and BCL2 (HGBL-DH), mantle cell lymphoma (MCL) and marginal zone lymphoma (MZL). While a large number of our samples displayed appropriate responses to apoptosis-inducing peptides, pro-apoptotic functional defects, implicating BAX, BAK, BIM or BID, were seen in 32.4% of high-grade NHLs (12/37) and in 3.4% of low-grade NHLs (3/87, p < 0.0001). The inhibition of single anti-apoptotic proteins induced apoptosis in only a few samples, however, the dual inhibition of BCL2 and MCL1 was effective in 83% of samples, indicating MCL1 was the most common cause of lack of response to the BCL2 inhibitor, venetoclax. We then profiled Toledo and OCI-Ly8 high-grade lymphoma cell lines to determine which drugs could reduce MCL1 expression and potentiate venetoclax responses. Doxorubicin and vincristine decreased levels of MCL1 and increased venetoclax-induced apoptosis (all p < 0.05). Overall, in primary NHLs expressing BCL2 that have no defects in pro-apoptotic signaling, a poor response to venetoclax is primarily due to the presence of MCL1, which may be overcome by combining venetoclax with doxorubicin and vincristine-based chemotherapy or with other anti-microtubule inhibitors.
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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 | 0.000 |
| 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) | 0.001 | 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".