Combination bortezomib and rituximab treatment affects multiple survival and death pathways to promote apoptosis in mantle cell lymphoma
Bibliographic record
Abstract
Mantle cell lymphoma (MCL) is a distinct histologic subtype of B cell non-Hodgkins lymphoma (NHL) associated with an aggressive clinical course. Inhibition of the ubiquitin-proteasome pathway modulates survival and proliferation signals in MCL and has shown clinical benefit in this disease. This has provided rationale for exploring combination regimens with B-cell selective immunotherapies such as rituximab. In this study, we examined the effects of combined treatment with bortezomib and rituximab on patient-derived MCL cell lines (Jeko, Mino, SP53) and tumor samples from patients with MCL where we validate reversible proteasome inhibition concurrent with cell cycle arrest and additive induction of apoptosis. When MCL cells were exposed to single agent bortezomib or combination bortezomib/rituximab, caspase dependent and independent apoptosis was observed. Single agent bortezomib or rituximab treatment of Mino and Jeko cell lines and patient samples resulted in decreased levels of nuclear NFkappaB complex(es) capable of binding p65 consensus oligonucleotides, and this decrease was enhanced by the combination. Constitutive activation of the Akt pathway was also diminished with bortezomib alone or in combination with rituximab. On the basis of in vitro data demonstrating additive apoptosis and enhanced NFkappaB and phosphorylated Akt depletion in MCL with combination bortezomib plus rituximab, a phase II trial of bortezomib-rituximab in patients with relapsed/refractory MCL is underway.
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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 | 0.001 |
| 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".