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Record W4297387081 · doi:10.1136/jitc-2022-005187

GD2-targeting CAR-T cells enhanced by transgenic IL-15 expression are an effective and clinically feasible therapy for glioblastoma

2022· article· en· W4297387081 on OpenAlexaff
Tessa Gargett, Lisa M. Ebert, Nga Truong, Paris M. Kollis, Kristýna Šediváková, Wenbo Yu, Erica C. F. Yeo, Nicole L. Wittwer, Briony L. Gliddon, Melinda N. Tea, Rebecca J. Ormsby, Santosh Poonnoose, Jake Nowicki, Orazio Vittorio, David S. Ziegler, Stuart M. Pitson, Michael P. Brown

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2022
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsOccupational Cancer Research Centre
FundersMark Hughes FoundationMedical Research CouncilFlinders FoundationTour de CureAustralian Cancer Research FoundationFay Fuller FoundationCancer AustraliaCancer Council South AustraliaNeurosurgical Research FoundationNational Health and Medical Research CouncilHospital Research Foundation
KeywordsChimeric antigen receptorMedicineGliomaFlow cytometryCancer researchBrain tumorAntigenImmune systemImmunotherapyTumor antigenPathologyOncologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Aggressive primary brain tumors such as glioblastoma are uniquely challenging to treat. The intracranial location poses barriers to therapy, and the potential for severe toxicity. Effective treatments for primary brain tumors are limited, and 5-year survival rates remain poor. Immune checkpoint inhibitor therapy has transformed treatment of some other cancers but has yet to significantly benefit patients with glioblastoma. Early phase trials of chimeric antigen receptor (CAR) T-cell therapy in patients with glioblastoma have demonstrated that this approach is safe and feasible, but with limited evidence of its effectiveness. The choices of appropriate target antigens for CAR-T-cell therapy also remain limited. METHODS: We profiled an extensive biobank of patients' biopsy tissues and patient-derived early passage glioma neural stem cell lines for GD2 expression using immunomicroscopy and flow cytometry. We then employed an approved clinical manufacturing process to make CAR- T cells from patients with peripheral blood of glioblastoma and diffuse midline glioma and characterized their phenotype and function in vitro. Finally, we tested intravenously administered CAR-T cells in an aggressive intracranial xenograft model of glioblastoma and used multicolor flow cytometry, multicolor whole-tissue immunofluorescence and next-generation RNA sequencing to uncover markers associated with effective tumor control. RESULTS: Here we show that the tumor-associated antigen GD2 is highly and consistently expressed in primary glioblastoma tissue removed at surgery. Moreover, despite patients with glioblastoma having perturbations in their immune system, highly functional GD2-specific CAR-T cells can be produced from their peripheral T cells using an approved clinical manufacturing process. Finally, after intravenous administration, GD2-CAR-T cells effectively infiltrated the brain and controlled tumor growth in an aggressive orthotopic xenograft model of glioblastoma. Tumor control was further improved using CAR-T cells manufactured with a clinical retroviral vector encoding an interleukin-15 transgene alongside the GD2-specific CAR. These CAR-T cells achieved a striking 50% complete response rate by bioluminescence imaging in established intracranial tumors. CONCLUSIONS: Targeting GD2 using a clinically deployed CAR-T-cell therapy has a sound scientific and clinical rationale as a treatment for glioblastoma and other aggressive primary brain tumors.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.021
GPT teacher head0.371
Teacher spread0.350 · 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

Citations105
Published2022
Admission routes1
Has abstractyes

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