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Abstract PR15: A novel NK cell-targeted therapeutic strategy against pancreatic cancer

2020· article· en· W3047711886 on OpenAlexaff
Kamiya Mehla, Thomas C. Caffrey, Kelly A. O'Connel, Raghupathy Madiyalakan, Christopher F. Nicodemus, Michael A. Hollingsworth

Bibliographic record

VenueCancer Immunology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsPancreatic cancerCancer researchImmunotherapyCytotoxic T cellTumor microenvironmentImmune systemImmunologyCancer immunotherapyCD8Memory T cellMedicineBiologyCancerInternal medicineIn vitro

Abstract

fetched live from OpenAlex

Abstract Recent years have witnessed an increased incidence of pancreatic adenocarcinoma (PDAC). Pancreatic tumors are poorly immunogenic; current immunotherapeutic strategies largely focus on boosting adaptive immunity while ignoring immunosuppressed innate immune players such as natural killer cells (NKs). NK cells respond to tumor insults by generating IFN-γ for T-cell activation. Multiple studies suggest that tumor cells evade NK cell-mediated killing by 1) developing “escape variants” and 2) regulating inhibitory and activating receptors on NK cells, imparting anergic/exhaustive phenotype inside the pancreatic tumor microenvironment. We posit that a therapeutic combination that not only overturns tumor-mediated NKs dysfunction but also boosts cytotoxic CD8 T cells will provide long-lasting therapeutic benefits in PDAC. Given this, we explored the efficacy of a unique therapeutic combination, tumor antigen-targeted IgE antibody (humanized anti-MUC1.IgE) in combination of anti-PD-L1 (for relieving T-cell exhaustion) and PolyICLC (for dendritic cell maturation) in a preclinical model of pancreatic cancer using mice transgenic for human MUC1 and FcϵRI (hMUC1/hFcϵRI). This therapeutic combination induced MUC1 specific rejection of two different human MUC1-expressing pancreatic tumor cell lines (Panc02.MUC1, KPC.MUC1) and prolonged the overall survival of mice challenged with subcutaneous and orthotopic tumors as compared to control counterparts. Additionally, this combination generated CD8 T-cell memory response as evidenced by MUC1 specific rejection/delays of tumors in mice rechallenged with MUC1-expressing tumors. Cytokine/chemokine profiling of anti-MUC1.IgE+anti-PD-L1+PolyICLC treated tumors further demonstrates a reduction in proinflammatory cytokines as compared to control counterparts. Most importantly, NK and CD8 T cells were involved in cell-mediated antitumor responses, as in vivo depletion of these subtypes abrogated the tumor-protective benefits in mice bearing orthotopic tumors. Anti-MUC1.IgE+anti-PD-L1+PolyICLC combination appears to increase circulating NKs and reverse NK cell exhaustion inside pancreatic tumor microenvironment. Additional data suggest that this therapeutic combination boosts tumor cell killing by NK cells in antibody-dependent cell cytotoxicity assays (ADCC). In sum, this is the first study to show that specific stimulation of IgE/FcϵRI axis in combination with PolyICLC and anti-PD-L1 can activate both CD8 T and NK cell effector pathways and provide long-lasting tumor-protective benefits against pancreatic cancer. This abstract is also being presented as Poster A48. Citation Format: Kamiya Mehla, Thomas C. Caffrey, Kelly A. O'Connel, Raghupathy Madiyalakan, Christopher F. Nicodemus, Michael A. Hollingsworth. A novel NK cell-targeted therapeutic strategy against pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr PR15.

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), Research integrity, 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 score0.282
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0190.000

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 head0.149
GPT teacher head0.414
Teacher spread0.265 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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