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Abstract B092: Therapeutic targeting of tumorigenic EphA2+/EphA3+ brain tumor initiating cells with bi-specific antibody in glioblastoma

2016· article· en· W2547018141 on OpenAlexaff
Parvez Vora, Maleeha Qazi, Chirayu Chokshi, Chitra Venugopal, Max London, Amy Hu, Nicole McFarlane, Minomi Subapanditha, Mohini Singh, Sujeivan Mahendram, Jarrett Adams, Jason Moffat, Sachdev S. Sidhu, Sheila K. Singh

Bibliographic record

VenueCancer Immunology Research · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsCancer researchErythropoietin-producing hepatocellular (Eph) receptorEPH receptor A2SOX2PopulationBiologyBrain tumorGliomaMedicineImmunologyReceptorPathologyInternal medicineEmbryonic stem cellReceptor tyrosine kinase

Abstract

fetched live from OpenAlex

Abstract Glioblastoma (GBM), the most aggressive primary human brain tumor, carrier a dismal prognosis and is increasingly characterized by cellular and genetic intra-tumoral heterogeneity (ITH). Many of the 14 members of the erythropoietin-producing hepatocellular carcinoma receptor (EphR) family and their ephrin ligands are expressed in GBM cells and constitute potential molecular targets for novel therapeutic agents. We hypothesize that multiple members of the EphR family play a critical role in orchestrating the clonal evolution of GBM progression. Individual Eph receptor targeting strategies have shown only modest pre-clinical success, likely because single agent therapy cannot target the degree of ITH in GBM. Using a highly specific human Eph receptor monoclonal antibody (mAb) panel (EphR profiler), we identified five Eph receptors with dysregulated expression in recurrent GBM as compared to primary GBM. With our unique chemoradiotherapy-adapted, patient-derived xenograft model of GBM, we identified EphA2 and EphA3 expression to be upregulated after therapy. Here we show that EphA2 and EphA3 co-expression marks a highly tumorigenic cell population in recurrent GBM with higher in vitro and in vivo self-renewal and proliferation capacity as compared to EphA2+/EphA3-, EphA2-/EphA3+ or EphA2-/EphA3- cells. Lentiviral mediated knockdown of EphA2 and EphA3 blocks this self-renewal and proliferation capacity in recurrent GBM. Through further characterization using mass cytometry (CyTOF) assay, we find that EphA2 and EphA3 is co-expressed with multiple brain tumor initiating cell (BTIC) markers (CD133, CD15, Bmi1, Sox2, Integrin α6 and FoxG1). Considering the important role of EphA2+/EphA3+ cells in GBM tumorigenesis and recurrence, we generated a bi-specific antibody (bsIgG) that co-targets EphA2 and EphA3. In vitro treatment of GBM with bsEphA2/A3 IgG led to pharmacological blockade of phosphorylated EphA2. We then assessed the in vivo efficacy of the bsEphA2/A3 IgG to block GBM tumor growth in our PDX model, and found that treatment with intracranial bsIgG resulted in non-invasive and significantly smaller lesions. The striking reduction in tumor burden in recurrent GBM after co-targeting of EphA2 and EphA3 validates the premise of our therapeutic strategy of targeting multiple EphRs. Discovering the clonal composition of recurrent GBM will enable us to target cellular subpopulations, and this ITH, with selective compounds that inhibit BTIC and Eph receptor activity with minimal off-target effects. Comprehensive Eph receptor profiling of individual patient-derived GBM will allow us to develop a therapeutic strategy for each patient's tumor, employing polytherapy with mAbs against Eph receptors expressed at recurrence. Citation Format: Parvez Vora, Maleeha Qazi, Chirayu Chokshi, Chitra Venugopal, Max London, Amy Hu, Nicole McFarlane, Minomi Subapanditha, Mohini Singh, Sujeivan Mahendram, Jarrett Adams, Jason Moffat, Sachdev Sidhu, Sheila Singh. Therapeutic targeting of tumorigenic EphA2+/EphA3+ brain tumor initiating cells with bi-specific antibody in glioblastoma [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr B092.

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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 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 score0.007
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.086
GPT teacher head0.380
Teacher spread0.294 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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