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Targeting FGFR3 in t(4;14) Mutiple Myeloma: Pre-Clinical Studies of PRO-001, a Novel Anti-FGFR3 Neutralizing Antibody.

2004· article· en· W2582502952 on OpenAlexaff
Suzanne Trudel, Ellen Wei, Zhihua Li, Eran Rom, Ira Chumakov, Yossi Singer, Christopher S. Chen, Donna Reece, Joseph Mıkhael, A. Keith Stewart, Avner Yayon

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsChromosomal translocationCancer researchBiologyAntibodyMultiple myelomaMolecular biologyFibroblast growth factor receptor 3Cyclin D1Phage displayReceptor tyrosine kinaseReceptorCancerFibroblast growth factorGeneGeneticsImmunologyCell cycle

Abstract

fetched live from OpenAlex

Abstract As with other B-cell malignancies, chromosomal translocations to the immunoglobulin heavy-chain (IgH) locus on chromosome 14q32 are believed to be a hallmark of multiple myeloma (MM), occurring in approximately 50% of patients. Identification of these chromosomal translocations has resulted in the discovery of powerful prognostic tools and novel molecular targets that promise to revolutionize the treatment of this malignancy. Five recurrent translocation partners have been defined, resulting in the dysregulation of the genes encoding cyclin D1 and D3, c-maf, mafB and Fibroblast Growth Factor Receptor 3 (FGFR3) together with MMSET. Genetic analysis of 14q32 translocations in MM has identified distinct groups of patients with separate clinical outcomes supporting a biological correlation of these genes in MM. In particular, the t(4;14) translocation portends a particularly bad prognosis. The association of FGFR3 expression with t(4;14) myeloma and the demonstration of the transforming potential of this receptor tyrosine kinase (RTK), make this a particularly attractive target for drug development for this poor prognosis group. We report here the development of a novel and highly specific anti-FGFR3 neutralizing antibody (PRO-001) isolated from a phage display human combinatorial antibody library. PRO-001 binds with high affinity (Kd=1.3 nM) to FGFR3 in in vitro binding assays and blocks ligand-dependent and independent FGFR3 phosphorylation and signal transduction in cell-based assays. Furthermore, PRO-001 potently inhibits FGFR3-dependent solid tumor growth in mouse xenograft models. We found that PRO-001 bound to, and competed with FGF binding to the surface of FGFR3 on human myeloma cell lines. PRO-001 inhibited FGF-induced phosphorylation of wild-type FGFR3 and downstream ERK phosphorylation in stable B9 cell transfectants (B9-WT) and FGFR3 expressing human myeloma cell lines. The antibody inhibited FGF-mediated growth of B9-WT with an IC50 of 3 μg/ml as determined by MTT proliferation assay. Growth of these cells could be rescued by IL-6 demonstrating selectivity of PRO-001 for FGFR3. PRO-001 inhibited the viability of the FGFR3 expressing, human myeloma cell line, UTMC2. Inhibition of viability was still observed when cells were co-cultured with stroma or in the presence of IL-6, a potent growth factor for MM cells. Several myeloma cell lines lacking FGFR3, showed minimal growth inhibition demonstrating selectivity and lack of non-specific toxic at effective dose concentrations. Finally, PRO-001 bound to FGFR3 on the cell surface, inhibited ERK phosphorylation, and induced cytotoxic responses in primary MM samples derived from t(4;14) positive patients. A xenograft mouse model has been established and studies assessing in vivo activity of PRO-001 are planned and will be reported. Taken together, the data demonstrate that PRO-001 is a specific and potent inhibitor of FGFR3 and that it deserves further study for targeted therapy in MM.

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)0.001
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.083
GPT teacher head0.414
Teacher spread0.330 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

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