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Record W2994178787 · doi:10.1182/blood.v108.11.847.847

Aurora Kinases as Therapeutic Targets in Multiple Myeloma.

2006· article· en· W2994178787 on OpenAlexaff
Tony Reiman, Robert P. Evans, Claudia Naber, Tara Steffler, Jonathan J. Keats, Troy Perry, Christopher A. Maxwell, Heidi Chau, Andrew R. Belch, Linda M. Pilarski

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAurora inhibitorAurora A kinaseAurora kinaseCancer researchBone marrowAurora B kinaseMultiple myelomaBiologyKinasePlasma cellCentrosomeMitosisGene knockdownPlasma Cell MyelomaCytokinesisCell cycleCell biologyCell cultureCellImmunologyCell divisionGenetics

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: We have previously found that in multiple myeloma there is amplification of the centrosome, the organelle that nucleates the mitotic spindle. We have reported that RHAMM is a component of the centrosome which interacts with TPX2, the protein that targets Aurora A kinase to the mitotic spindle. We have also shown that RHAMM expression and alternative splicing in myeloma correlate with centrosome amplification, aggressive disease and poor survival. These findings led us to speculate that Aurora A and possibly other Aurora kinases are potential therapeutic targets in myeloma. METHODS: We examined the expression of Aurora A, B and C kinases in 5 myeloma cell lines and autoMACS-purified CD138+ myeloma bone marrow plasma cells from 20 patients. We assessed the anti-proliferative and pro-apoptotic effects of Aurora A knockdown in myeloma cell lines with RNA interference. We investigated the anti-myeloma activity of two potent, selective Aurora kinase inhibitors, VE-465 (Merck/Vertex) and AZD1152 (AstraZeneca), in 5 myeloma cell lines, in CD138+ bone marrow plasma cells from 2 myeloma patients, and in a NOD/SCID murine xenograft model. RESULTS: Aurora A, B and C kinases are ubiquitously expressed in both myeloma cell lines and myeloma bone marrow plasma cells. Expression levels vary among patients. Aurora A and B are expressed in myeloma plasma cells at levels comparable to that seen in the CD138- cells from the same marrow sample, and comparable to the levels seen in normal marrow from control individuals. Aurora C, while expressed at low levels, is consistently ectopically overexpressed in myeloma plasma cells relative to coexisting CD138- cells and normal marrow. In myeloma cell lines, Aurora A knockdown with RNA interference induces apoptosis and cell killing. In all five myeloma cell lines tested, and in myeloma bone marrow plasma cells from two patients, both VE-465 and AZD1152 induce apoptosis and myeloma cell killing at nanomolar concentrations, to varying degrees (20–80% reduction in cell viability). VE-465 is known to inhibit all three Aurora kinases with comparable specificity, while AZD1152 is known to inhibit Aurora B and C more selectively than Aurora A. Despite these differences in activity, both compounds have comparable pre-clinical efficacy against myeloma. Myeloma cell lines treated with either agent demonstrate a phenotype consistent with target inhibition. Both drugs show additive effects on killing of cell lines and primary myeloma cells when combined with dexamethasone, even in dexamethasone-resistant cells. Anti-myeloma activity was seen with single agent Aurora kinase inhibition in the murine model, at well tolerated doses. CONCLUSIONS: Aurora kinases are potential therapeutic targets in myeloma. Aurora kinase inhibitors comprise an emerging class of anti-cancer drug therapy that deserves further evaluation for myeloma patients.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.217
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2006
Admission routes1
Has abstractyes

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