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Chemical Library Screening Identifies Novel Inhibitors of Cyclin D2 (CCND2) Transactivation That Selectively Induce Apoptosis in Multiple Myeloma Cells.

2006· article· en· W2549813000 on OpenAlexaff
Rodger E. Tiedemann, Xinliang Mao, Chng-Xin Shi, Yuan Xiao Zhang, Stephen Palmer, Craig B. Reeder, Aaron D. Schimmer, Keith Stewart

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicBioactive Compounds and Antitumor Agents
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsCyclin D2Cancer researchCell cycleBiologyChemistryCyclinMolecular biologyApoptosisBiochemistry

Abstract

fetched live from OpenAlex

Abstract Multiple myeloma tumors universally target one of the three human cyclin D genes (CCND1, CCND2 or CCND3) for dysregulation (Bergsagel et al., 2005, Blood, 106:296). Using a lentivirus expressing CCND2 RNAi we first tested the effects of selective cyclin D2 knock down on My5 and H929 myeloma cell lines and found G0/G1 phase arrest, increased apoptosis and significant selective disadvantage in transfected cells. By comparison, knockout mouse models indicate that most somatic tissues can develop in the total absence of cyclin D1, D2 and D3 (Kozar et al., 2004, Cell,118:477). Targeted inhibition of specific cyclin D expression is therefore a rational therapeutic strategy in myeloma. To identify novel pharmaceutical inhibitors of CCND2 transactivation we developed an assay employing NIH 3T3 cells stably co-expressing the CCND2 transactivator c-Maf and the cyclin D2 promoter driving firefly luciferase (luc) and screened the Lopac (n=1280), Prestwick (n=1120) and Spectrum (n=2000) libraries of drugs and natural compounds. In a parallel MTS assay, the effect of each compound on 3T3 viability was determined, allowing exclusion of compounds that caused secondary suppression of CCND2 due to non-specific cytotoxicity. From the screen we identified 10 c-Maf independent putative CCND2 inhibitors. These included monensin, patulin, β-lapachone, camptothecin, dihydrogambogic acid, gentian violet, thapsigargin, brefeldin A, pristimerin and kinetin riboside. Three of the 10 compounds (gentian violet, thapsigargin and patulin) were not studied further due to toxicity cited in the literature. Subsequent validation studies using selected compounds in human myeloma cell lines (HMCL) confirmed successful suppression of both cyclin D2 and D1 proteins. Each of these compounds was then shown to be cytotoxic to a genetically diverse and standardized panel of 14 HMCL in MTT assays: monensin (10–760 nM), camptothecin (5–700nM), dihydrogambogic acid (250–800 nM), pristimerin (150–500 nM) and kinetin riboside (2.5–20μM). Cell cycle analysis confirmed induction of G0/G1 phase arrest for most compounds, consistent with cyclin D inhibition. However, camptothecin and b-lapachone induced S-phase arrest, suggesting secondary suppression of cyclin D by virtue of S-phase activity. Unsorted myeloma patient bone marrow samples demonstrated selective activity for pristimerin, dihydrogambogic acid and kinetin riboside against CD138+ myeloma cells compared with non malignant hematopoietic cells; by contrast monensin showed almost equal toxicity for normal cells. The triterpenoid, pristimerin, showed potent anti-myeloma activity and was examined in greater detail. Studies confirm that pristimerin rapidly inhibits cyclin D1, D2 and D3 expression (<6 hours) at nanomolar concentrations and induces apoptosis of primary myeloma cells characterized by caspase 9 cleavage and Annexin V binding. While pristimerin is cytotoxic to HMCL and patient myeloma cells at 0.1–0.15 mg/L, toxicity studies in vivo indicate that the drug is tolerated in mice at 2.5 mg/kg i.p. daily. In vivo activity against a xenograft model is currently being determined. Overall this targeted chemical biology screen has identified several compounds, including the triterpenoid, pristimerin, that are being further characterized for promising preclinical anti-myeloma activity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.089
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.080
GPT teacher head0.324
Teacher spread0.244 · 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 teacher head, 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
Published2006
Admission routes1
Has abstractyes

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