Abstract 385: iRGD mediated delivery of neoantigens to enable immunotherapy in integrin b5-rich tumors
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".