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Record W2564655741 · doi:10.1016/s1525-0016(16)33216-6

407. A Novel Rabbit Antibody-Derived, Anti-CD123 LV/CAR Construct for AML Immunotherapy

2016· article· en· W2564655741 on OpenAlexaff
Robyn A. A. Oldham, Elliot Berinstein, Jeffrey A. Medin

Bibliographic record

VenueMolecular Therapy · 2016
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsInterleukin-3 receptorChimeric antigen receptorMyelopoiesisCancer researchImmunotherapyHaematopoiesisImmunologyImmunotoxinAntibodyMyeloid leukemiaBiologyAntigenCytotoxic T cellProgenitor cellCancer immunotherapyMonoclonal antibodyStem cellImmune systemCell biologyIn vitro

Abstract

fetched live from OpenAlex

Chimeric antigen receptors (CARs) have emerged in the immunotherapy field as an exciting new option for cancer treatment, with clinical trials of CD19-directed CARs having already demonstrated long-lasting responses in patients with ALL and CLL. As a hematological malignancy, acute myeloid leukemia (AML) may be another viable target for CAR-mediated therapy. Furthermore, with a 5-year survival rate of just 5.5% for patients over 65, new treatments for AML are very much needed. CD123 (the IL-3 receptor α-chain) is upregulated on AML blasts/stem cells and plays a role in proliferation and apoptotic resistance. This antigen demonstrates much lower expression levels on normal hematopoietic cells, where its expression is restricted to the myeloid progenitor subpopulation. Previous attempts to target CD123 in AML through several forms of immunotherapy have had variable success. Specifically, results of previous CD123 murine antibody-derived CARs have been mixed, with some results showing CAR-mediated eradication of normal myelopoiesis via targeting of HSCs with low CD123 expression. We have developed a CD123 CAR, derived from a novel rabbit anti-CD123 mAb that we generated. Rabbit antibodies are reported to have a broader avidity and higher range of affinities than mouse mAbs; this may lead to a CAR with a unique binding profile. We will determine whether such a rabbit-derived CD123 CAR will lead to more specific binding, resulting in optimized killing of AML cells, while minimizing cytotoxic effects on HSCs. To generate our CAR, human CD123 was purified as a GST-tagged protein and used for immunization of rabbits. Hybridoma cell lines were developed from the spleen cells of rabbits with positive immune responses, and novel antibodies were purified and screened for specificity to CD123 using a combination of ELISA, flow cytometry, and ADCC. A candidate antibody was selected, and the VL and VH chains were subcloned, sequenced, and assembled into an scFv. A second generation CAR was then designed that includes a CD8 hinge and transmembrane region, a 4-1BB costimulatory domain, and a CD3ζ signaling domain. This construct was then subcloned into a lentiviral backbone to facilitate expression in immune effector cells. Our CD123 CAR has been transduced into primary T cells and the NK-92 cell line for in vitro testing. Flow cytometry demonstrates that our CARs are expressed at the cell surface. Furthermore, the expression of the CD123 CAR has been shown to be stable in the NK-92 cell line. Cytotoxicity assays are being performed in vitro in order to confirm binding specificity and cytotoxic potential of the CD123 CARs in both NK-92 and T cells. Future work will compare CAR T and CAR NK killing in vivo using NSG mouse models of AML. AML may be an ideal target for CAR therapy, and we will exploit our novel CD123 CARs as therapeutic entities. We will examine whether the use of a novel rabbit anti-CD123 scFv in our LV/CAR construct will optimize the killing of AML cells while minimizing HSC eradication. This novel second-generation CAR has the potential to greatly impact the treatment of AML patients in the future.

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 score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.328
Teacher spread0.301 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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