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Record W2885431388 · doi:10.1158/1538-7445.am2018-1759

Abstract 1759: AVID200, a highly potent TGF-beta trap, exhibits optimal isoform selectivity for enhancing anti-tumor T-cell activity, without promoting metastasis or cardiotoxicity

2018· article· en· W2885431388 on OpenAlexaff
Maureen D. O'Connor‐McCourt, Gilles Tremblay, Anne E.G. Lenferink, Traian Sulea, John C. Zwaagstra, James Koropatnick

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsLawson Health Research InstituteNational Research Council Canada
Fundersnot available
KeywordsCancer researchEctodomainMetastasisTGF beta signaling pathwayAntibodyCancer cellCancerTumor microenvironmentT cellBiologyTransforming growth factorTransforming growth factor betaImmune systemImmunologyMedicineReceptorCell biologyInternal medicine

Abstract

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Abstract The purpose of the studies presented here is to examine the ability of the novel TGF-β-neutralizing agent, AVID200, to reverse immunosuppression in the tumor microenvironment, and to determine the safety profile of AVID200 in non-human primates. TGF-β is a secreted protein that is aberrantly produced by tumors, and which promotes cancer progression primarily by suppressing both the innate and adaptive immune systems. AVID200 is a computationally-designed, avidity-enhanced, receptor ectodomain-based trap that binds and neutralizes TGF-β1 and -β3. We demonstrate, in tumor cell-based assays, that AVID200 potently neutralizes TGF-β1 and -β3 with low pM potency. Using a syngeneic 4T1 triple negative breast cancer (TNBC) model, we report that AVID200, in a dose-dependent manner, enhances the capacity of T-cells isolated from draining lymph nodes to specifically recognize and kill 4T1 tumor cells. The anti-tumor T-cell-activating potency of AVID200 was observed to be higher than that of the pan-neutralizing TGF-β antibody, 1D11. AVID200 was designed to have minimal activity against TGF-β2. This isoform specificity was chosen since it has been reported that inhibition of the TGF-β2 isoform can promote metastasis. We report that AVID200 does not increase the number of foci in a metastasis assay, whereas pan TGF-β neutralizing agents do. This supports the concept that blockade of TGF-β2 is undesirable. Also, it has been reported that pan-TGF-β blockers can exhibit cardiac toxicity in animal models and in humans. It has been proposed that this is due to TGF-β2 neutralization since this is the main isoform implicated in normal cardiac function. To determine if AVID200 exhibits cardiotoxicity, we tested AVID200 in a pilot non-human primate study. No adverse cardiac events were observed at doses of up to 30 mg/kg. An update on GLP toxicology studies will be presented at the meeting. In conclusion, AVID200 is a novel TGF-β trap that potently blocks TGF-β-1 and -3 isoforms, which results in reversal of immunosuppression in the tumor microenvironment. It has minimal activity against TGF-β2 and accordingly does not detectably promote cardiac toxicity and metastasis. Thus, AVID200 is a promising new immunotherapy that selectively inhibits the TGF-β1 and -3 isoforms, thereby enhancing desirable anti-tumor immunity, while avoiding the tumor-promoting and cardiotoxic effects resulting from TGF-β2 neutralization. Citation Format: Maureen D. O'Connor-McCourt, Gilles Tremblay, Anne Lenferink, Traian Sulea, John Zwaagstra, James Koropatnick. AVID200, a highly potent TGF-beta trap, exhibits optimal isoform selectivity for enhancing anti-tumor T-cell activity, without promoting metastasis or cardiotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1759.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.097
GPT teacher head0.412
Teacher spread0.315 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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