Abstract B009: Targeting PAR-2 improves tumor antigen presentation and primes the immune system for anti-PD-1 immunotherapy
Bibliographic record
Abstract
Abstract Identifying mechanisms of resistance to immune checkpoint inhibitors (ICIs) has become a major focus in cancer immunotherapy. Our previous work identified F2RL1 expression in tumors, encoding the G protein-coupled receptor Protease-Activated Receptor-2 (PAR-2), as a negative biomarker for ICI responsiveness. In this study, we evaluated the potential of PAR-2 as a therapeutic target to enhance anti-PD-1 treatment efficacy. Using a sensitive protein-based assay, we observed that systemic PAR-2 activation was significantly elevated across multiple tumor types and correlated with reduced survival of lung cancer patients treated with pembrolizumab and platinum-based chemotherapy. Global PAR-2 deletion in mice significantly increased anti-PD-1 activity and pharmacologic inhibition of PAR-2 using a novel negative allosteric modulator, I-117, significantly potentiated anti-PD-1 therapy in preclinical studies. Mechanistically, PAR-2 inhibition reshaped the tumor microenvironment (TME), notably by reducing the frequency of putative immunosuppressive myeloid cells, as evidenced by flow cytometry using the CD206 marker and by bulk RNA sequencing of MHCII+ CD19- tumor-infiltrating cells, which revealed a downregulation of genes associated with protumorigenic M2-like macrophages. In parallel, PAR-2 inhibition led to a marked enrichment of effector CD8+ T cells within tumors, as well as an increased frequency of CD8+ T cells in tumor-draining lymph nodes (tdLNs), a change not observed with anti–PD-1 monotherapy at the same time point. In contrast, the combination therapy significantly increased the accumulation of central memory CD8+ T cells within the tdLNs, as detected by flow cytometry. These cellular changes were accompanied by a shift in the cytokine milieu, with a trend toward increased Th1-type cytokines and decreased immunosuppressive cytokines, as measured by multiplex ELISA. Finally, using ex vivo co-culture assays with naïve antigen-specific T cells, we demonstrated that PAR-2 inhibition with I-117 significantly enhanced the antigen-presenting capacity of CD11c+ dendritic cells present in tumors and tdLNs. Altogether, these results support a model in which PAR-2 inhibition primes the immune system for optimal tumor antigen presentation, thereby enhancing the effectiveness of PD-1 blockade. Our study provides a compelling rationale for combined use of PAR-2 and PD-1 blockade for cancer immunotherapy. Citation Format: Samya Aouad, Maleck Kadiri, Lucie Giraud, Emma Skora, Thibaut Brugat, Anne-Laure Blayo, Stephan Schann, John Satgg. Targeting PAR-2 improves tumor antigen presentation and primes the immune system for anti-PD-1 immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr B009.
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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) | 0.007 | 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".