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Record W2563072979 · doi:10.1016/s1525-0016(16)33457-8

649. Developing FGFR4 Chimeric Antigen Receptor CAR T Cell Therapy Against Rhabdomyosarcoma

2016· article· en· W2563072979 on OpenAlexaff
Nityashree Shivaprasad, Ying Xiong, Marielle E. Yohe, Dina Schneider, Jack F. Shern, Sivasubramanian Baskar, Dimiter S. Dimitrov, Paul Sorenson, Rimas J. Orentas, Javed Khan

Bibliographic record

VenueMolecular Therapy · 2016
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsFibroblast growth factor receptor 4ImmunohistochemistryMolecular biologyCancer researchBiologyFusion proteinAntibodyReceptorFibroblast growth factor receptorRecombinant DNAImmunologyFibroblast growth factorGene

Abstract

fetched live from OpenAlex

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in pediatrics with an annual incidence of 4.5 cases per 1 million. Patients with high-risk metastatic disease have dismal prognosis and newer treatments are needed. We identified, fibroblast growth factor receptor 4 (FGFR4) as an overexpressed cell surface protein in RMS by mRNA expression analysis. Furthermore, activating mutations in FGFR4 are associated with metastatic disease. FGFR4 protein overexpression in RMS provides a specific target for immune-based therapy of RMS. We are developing T cells genetically modified to express chimeric antigen receptors (CARs) that target FGFR4. To verify FGFR4 RNA expression at the protein level we performed both immunohistochemistry (IHC) and electrochemillumescence (ECL) ELISA assays. Using IHC analysis we measured FGFR4 protein levels on tissue microarrays (TMA) of normal tissue and primary tumor from RMS patients, increased staining for FGFR4 protein on RMS primary tumors, compared to normal tissues was demonstrated. FGFR4 expression measured using ECL ELISA assay, shows a range of 300 - 800pg FGFR4 per 1mg of total lysate in RMS cell lines. The range for normal tissues was 30 - 40 pg/mg for all tissues with the exception of liver, which expressed 70 pg/mg. A single-chain variable fragment (scFv) cDNA library derived from a human B cells was screened, and clones that showed binding to recombinant FGFR4 extracellular domain (ECD) selected. We identified ten specific human anti-FGFR4 scFv binders. The scFvs were cloned into prokaryotic expression vector containing the human IgG1 Fc region. Anti-FGFR4 scFv-Fc were expressed in 293FT cells by transient transfection and purified using Protein A affinity chromatography. The binding of scFv-Fcs to recombinant FGFR4 ECD was verified by ELISA. scFv-Fc binders were then assayed for binding to cell surface FGFR4 on RMS cell lines using flow cytometry. Anti-FGFR4 scFv-Fc bound to 293T cells transfected to express FGFR4 but not 293T control cells. Anti-FGFR4 scFv-Fc also bound FGFR4 on three RMS cell lines. The first two anti-FGFR4 scFv binder sequences evaluated, M410 and M412, were used to make short (S, extracellular scFv only) and long format (L, scFv with a CH2CH3 domain of IgG1) CAR constructs. Activated T cells were transduced with lentiviral CAR expression vector (LV) encoding M410-L, M412-S and M412-L CAR constructs and cell surface expression of FGFR4 CAR on transduced T cells was measured using flow cytometry. The M410 and M412 FGFR4 CARs, both short and long constructs, were tested for cell-mediated cytotoxicity against RMS cell lines. M410-L showed higher cytotoxic activity compared to M412-L. M412-S showed greater cytotoxic activity compared to M412-L CAR. Thus, overall CAR structure format may be important for its functional activity. The remaining scFv will be further analyzed in various CAR formats for its functional activity including cytotoxicity and interferon-gamma production. In summary, the overexpression of FGFR4 protein in RMS versus normal cell lines demonstrates that FGFR4 may be a suitable target for immune-based therapy. FGFR4 CAR-T cell therapy offers the potential of a novel therapeutic intervention for high-risk, refractory and relapsed RMS.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.310
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.293
Teacher spread0.266 · 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.

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

Citations11
Published2016
Admission routes1
Has abstractyes

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