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MDNA109: Effect of an interleukin-2 superkine on CD8 T-cell properties in the tumor microenvironment.

2019· article· en· W2947005140 on OpenAlexaff
Moutih Rafei, Shafique Fidai, Rosemina Merchant, Fahar Merchant

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPharma Medica Research (Canada)Université de Montréal
Fundersnot available
KeywordsIL-2 receptorCytotoxic T cellCancer researchCD8Interleukin 2CytokineImmunotherapyTumor microenvironmentMedicineT cellIn vivoImmune systemImmunologyMolecular biologyBiologyIn vitroBiochemistry

Abstract

fetched live from OpenAlex

e14220 Background: Proleukin (a cysteine-modified variant of interleukin (IL)-2) is the only common-γc cytokine approved for the treatment of metastatic melanoma and renal cell carcinoma. Its therapeutic use is however hampered by its short half-life and severe toxicity. At low doses, Proleukin administration leads to preferential activation of regulatory T cells (Tregs) due to their expression of the high affinity trimeric IL-2 receptor (IL-2R) consisting of CD25, CD122 and CD132 instead of cytotoxic CD8 T cells expressing the intermediate affinity IL-2R (CD122 and CD132). Methods: To bypass these limitations, we evaluated engineered variants of IL-2 (MDNA109 superkine) exhibiting enhanced affinity towards CD122 including their long-acting and bispecific superkine fusions. This approach allows preferential activation of CD8 T cells while displaying reduced adverse effects in vivo. Results: Both Biacore analysis and signaling studies on human peripheral blood mononuclear cells confirmed enhanced binding of MDNA109 to CD122 and STAT5 activation, respectively. When tested in vivo, MDNA109 co-administration with the immune-checkpoint blockers anti-programmed cell death (PD)-1 or anti-cytotoxic T-Lymphocyte-Associated Protein (CTLA)4 cured mice with pre-established MC38 or CT26 colon cancers respectively. In addition, bi-weekly administration of the long-acting MDNA109-Fc fusion led to similar therapeutic outcomes in the B16F10 model when compared to MDNA109 administered daily. Finally, in vitro and in-vivo results using (a) MDNA109 muteins with completely impaired CD25 binding activity and (b) novel bispecific superkine fusions consisting of MDNA109 and a dual IL-4/IL-13 super-antagonist capable of selective CD8 T-cell activation while mitigating the suppressive functions of myeloid-derived suppressor cells and tumor-associated macrophages will be presented. Conclusions: Altogether, these data demonstrate that both MDNA109 and MDNA109-Fc are therapeutically superior to Proleukin. Furthermore, use of MDNA109-based strategies will not only ensure complete abrogation of adverse effects, but will in addition eliminate immunosuppression caused by both Tregs and myeloid cells.

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 score0.004

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 head0.085
GPT teacher head0.436
Teacher spread0.351 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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