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1166 Avidity engineered multifunctional antibodies that strongly activate and expand anti-tumor immunity in situ, turning cold patient tumor tissue hot and exerting durable tumor control in mice

2025· article· W4416076231 on OpenAlexaff
Robert H. Friesen, Sophie M. Poznanski, André Simoes, Leila Vahedi, Loreto Parga‐Vidal, Erik Slinger, Jarek Juraszek, André Kunert, Ali A. Ashkar

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2025
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmunityAntibodyAvidityImmune systemHumoral immunityTumor cellsImmunotherapy

Abstract

fetched live from OpenAlex

Background Antibodies and ADCs are mainstays in the treatment of cancer. However, given difficulties in achieving a deep and sustained response, significant improvements are desirable. We report on first in class ‘Booster’ molecules, based on clinically validated ADCC-competent antibodies, equipped with two immunomodulatory domains that uniquely combine co-stimulation and cytokine signaling, and are affinity engineered to be functional only when in contact with a tumor cell. We see strong and durable expansion without exhaustion and increased cytotoxicity of immune cells in the presence of cancer cells in vitro, broad activation of anti-tumor immune cell types in patient tumors ex vivo, and durable reduction of tumor burden in vivo, with significantly better activity than adoptive cell therapy or control antibody without fusion domains.Methods NRG mice were engrafted with luciferase expressing tumor cells via intraperitoneal injection 7 days prior to treatment. Mice received 1 million NK cells freshly isolated from healthy donors. Compounds were administered biweekly, and low dose IL2 thrice weekly. NK cell expansion was quantified in blood and tumor burden monitored monitored via bioluminescence. ex vivo: in situ activation of tumor-resident immune populations was evaluated by nanostring in freshly isolated tumor tissue. in vitro: long-term cytotoxicity was measured by quantifying live tumor cells using automated microscopy with regular co-culture re-sets. Expansion was performed by stimulating NK cells weekly with tumor cells that were opsonized with Booster or antibody.Results Mice treated with Her2, TROP2, or EGFR Boosters demonstrated superior tumor control than trastuzumab, sacituzumab, or cetuximab analogue treated mice respectively. Boosters induced superior and sustained NK cell expansion in mice, with up to 5000x higher NK numbers compared to the relevant control antibody analogue. Our Boosters reprogram the full immune microenvironment ex vivo in freshly isolated patient tumor tissue, transforming a cold tumor into a hot tumor. They activate multiple cytotoxic pathways in three different tumor types. In separate in vitro assays we saw sustained expansion and enhanced long-term cytotoxicity of NK cells for at least 6 weeks.Conclusions In correlation with extensive in vitro and ex vivo data, we observe a prolonged and significant improvement in tumor control in mice treated with Boosters compared to mice treated with parent antibody analogues. Work is ongoing to develop these molecules, with preparations ongoing to bring them to the clinic.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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".

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Citations0
Published2025
Admission routes1
Has abstractno

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