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Record W4282983643 · doi:10.1158/1538-7445.am2022-385

Abstract 385: iRGD mediated delivery of neoantigens to enable immunotherapy in integrin b5-rich tumors

2022· article· en· W4282983643 on OpenAlexaff
Tatiana Hurtado de Mendoza, Evangeline Mose, Gregory P. Botta, Gary B. Braun, Venkata Ramana Kotamraju, Randall P. French, Kodai Suzuki, Norio Miyamura, Siming Sun, Jay Patel, Tambet Teesalu, Erkki Ruoslahti, Kazuki N. Sugahara, Andrew M. Lowy

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsStemcell Technologies
Fundersnot available
KeywordsCancer researchPancreatic cancerImmunotherapyTumor microenvironmentIntegrinStromal cellStromaImmune systemImmunosurveillanceMedicineImmunologyCancerImmunohistochemistryInternal medicineReceptor

Abstract

fetched live from OpenAlex

Abstract Pancreatic duct adenocarcinomas are known for their abundant desmoplastic stroma that acts as a barrier for drug penetration and reduces treatment efficacy. iRGD is a tumor-penetrating peptide that initially targets αv integrins expressed on tumor vasculature with its RGD motif and then is proteolytically processed to expose a CendR motif (R/KXXR/K) that interacts with neuropilin-1 (NRP-1), leading to extravasation. We investigated the mechanism of iRGD tissue penetration and found that iRGD initially targets Carcinoma Associated Fibroblasts (CAFs) and then spreads to the tumor cells in a time dependent manner. CAF targeting was dependent on integrin β5 expression and CAFs induced upregulation of integrin β5 in the adjacent tumor cells in a TGF- β dependent manner. Drugs conjugated or co-administered with iRGD can penetrate deep into tumor tissue, significantly increasing the efficacy of chemotherapeutic agents in a variety of solid tumors. Our recent data shows that KrasLSL-G12D/+ Trp53LSL-R172H/+ Pdx1-Cre (KPC) mice treated with iRGD co-administered with Gemcitabine increased survival compared to drug alone. In addition, we are using iRGD to deliver neoantigens to breast and pancreatic cancers to enable immunotherapy. These tumors have a low mutational burden and a very immunosuppressive microenvironment, rendering them resistant to such therapies. We have used iRGD, to deliver the ovalbumin 257-264 (OVAI) peptide to triple negative breast tumors, followed by adoptive T cell transfer of OT1 CD8 T cells, in order to elicit an antitumor immune response. Our preliminary data showed tumor regression in 70%, and complete response in 42% of the mice treated with iRGD plus OVA1. We are now working on adapting this strategy to pancreatic cancer. Citation Format: Tatiana Hurtado de Mendoza, Evangeline S. Mose, Gregory P. Botta, Gary B. Braun, Venkata R. Kotamraju, Randall P. French, Kodai Suzuki, Norio Miyamura, Siming Sun, Jay Patel, Tambet Teesalu, Erkki Ruoslahti, Kazuki N. Sugahara, Andrew M. Lowy. iRGD mediated delivery of neoantigens to enable immunotherapy in integrin b5-rich tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 385.

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 head0.080
GPT teacher head0.407
Teacher spread0.327 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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