Abstract 4851: Disrupting redox homeostasis in pancreatic ductal adenocarcinoma initiates anti-tumor immune responses
Bibliographic record
Abstract
Abstract Immunotherapy has improved cancer treatment by ameliorating outcomes for patients with aggressive cancers. However, pancreatic ductal adenocarcinoma (PDAC) remains resistant to various immunotherapies. This resistance can be attributed to the immunosuppressive PDAC tumor microenvironment. Immunosuppressive cells populate the tumor microenvironment in the early neoplastic stages of the disease, suggesting that neoadjuvant therapies may be needed to overcome immune suppression. New therapeutic strategies that prime the immune response against PDAC are needed to improve the efficacy of immunotherapy. We aim to overcome immune suppression by leveraging redox vulnerabilities in PDAC. Our lab identified the antioxidant protein peroxiredoxin-4 (PRDX4) as essential for PDAC cell survival but dispensable in normal tissue, making it a promising therapeutic target. PRDX4 neutralizes reactive oxygen species in the endoplasmic reticulum and its depletion leads to decreased tumor growth and substantial DNA damage. From this, we hypothesize that PRDX4 depletion causes immunogenic DNA damage and initiates immune responses against PDAC. We generated stable doxycycline-inducible PRDX4 knockdown in the human PANC-1 and mouse KPC (LSL-KrasG12D;LSL-p53R172H;Pdx1-CreER) PDAC cell lines. Using immunofluorescence imaging, we show that PRDX4 depletion leads to cytosolic DNA in the form of micronuclei and dispersed DNA. We also show using RT-qPCR and ELISA that PRDX4 depletion leads to an increase in chemokine production, like CCL5, CXCL10 and CCL20. Using siRNA targeting both NF-κB and the DNA sensor cGAS, we show that this chemokine production is activated through the cGAS-STING pathway. Finally, using DNase to clear the cytosolic DNA, we show that cGAS-STING activation and chemokine production can be attributed to PRDX4 depletion-induced cytosolic DNA. To extend these findings in vivo, we created an immunocompetent KPC-PRDX4 mouse model by crossing KPC mice with PRDX4KO mice. This model develops spontaneous and staged cancer progression, from neoplastic lesions to PDAC. It also recapitulates the immune infiltrate seen in the human disease, making it a good model to study immune dynamics in the tumor microenvironment. Based on the strong chemokine response seen in vitro, we are now measuring the effects of PRDX4 depletion on the immune cell composition in the tumor microenvironment. Ongoing studies include immunofluorescence imaging and flow cytometry using tumor samples from our model. The aggressive growth and treatment resistance of PDAC demand research towards novel treatment strategies. This project contributes supporting evidence for targeting cancer metabolism, particularly PRDX4, to enhance immune responses in PDAC. Citation Format: Vishal Pandya, Lucie Malbeteau, Emily Poulton, Marianne Koritainsky. Disrupting redox homeostasis in pancreatic ductal adenocarcinoma initiates anti-tumor immune responses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4851.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".