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The Role of Proteasome Inhibitors and the Trail Apoptotic Pathway in the Treatment of Chronic Lymphocytic Leukemia.

2005· article· en· W2513909258 on OpenAlexaff
Kristin McCrea, Albert F. Kaboré, James B. Johnston, Spencer B. Gibson

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChronic lymphocytic leukemiaApoptosisProteasomeProteasome inhibitorCancer researchCytotoxic T cellMonoclonal antibodyProgrammed cell deathLeukemiaCancer cellChlorambucilMultiple myelomaBiologyAntibodyImmunologyCancerCell biologyBiochemistryIn vitroChemotherapy

Abstract

fetched live from OpenAlex

Abstract TRAIL (tumour necrosis factor-related apoptosis-inducing ligand) triggers the TRAIL apoptotic pathway selectively in tumour cells by binding to two death receptors, DR4 and DR5, that are present on the surface of many cancer cells. It is effective at inducing apoptosis in a variety of haematological malignancies, such as multiple myeloma. However, chronic lymphocytic leukemia (CLL) cells are relatively resistant to TRAIL-induced apoptosis. We have previously shown that the chemotherapeutic drugs, fludarabine and chlorambucil, increase the cell surface expressions of DR4 and DR5, and give synergistic apoptotic responses when combined with TRAIL. Proteasome inhibitors, that are used in the treatment of multiple myeloma, also upregulate TRAIL and its death receptors in CLL cells but not in normal B cells. Herein we have determined that proteasome inhibitors are effective at inducing apoptosis in CLL cells, and that the activation of the TRAIL apoptotic pathway contributes significantly to proteasome inhibitor cytotoxicity. Combining proteasome inhibitors with TRAIL enhanced apoptosis in CLL cells by approximately 15% over treatment with the proteasome inhibitor alone. Another novel approach to trigger the TRAIL apoptotic pathway is to use activating monoclonal antibodies directed against DR4 and DR5. Similar to TRAIL, we demonstrated that when used alone, the monoclonal antibodies were minimally cytotoxic against CLL cells. Proteasome inhibitors in combination with activating monoclonal antibodies against DR4 or DR5 increased the amount of apoptosis in CLL cells. Cell death was enhanced by 23% and 17% when proteasome inhibitors were combined with monoclonal antibodies against DR4 and DR5, respectively. While proteasome inhibitors may have a potential role in CLL treatment as single therapy, they are also cytotoxic to normal B cells. However, when activating monoclonal antibodies against TRAIL death receptors are given in combination with proteasome inhibitors, that upregulate DR4 and DR5 expression, the anti-tumor specificity and cytotoxicity of these agents may be increased in CLL.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.197
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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