507 MRNA Challenge Predicts Brain Cancer Immunogenicity and Response to Checkpoint Inhibitors

INTRODUCTION: Pathogen recognition receptor (PRRs) activation is requisite for igniting the immune response and making the tumor microenvironment ‘hot’ during oncogenesis. We theorized that these PRRs would remain present in ICI responsive tumors and could be challenged using pan-PRR mimic to prospectively predict brain cancer immunogenicity and response to immune checkpoint inhibitors (ICIs) METHODS: By layering mRNA into multilamellar nanoparticles (ML RNA-NPs), multiple pathogen recognition receptors can be simultaneously activated in individualized cancer cells serving as a broad screen to test tumor immunogenicity. We challenged murine brain tumor lines known to respond (GL261 and SMA-560) or resist ICI treatment (KR158b and CT2A) with ML RNA-NPs and analyzed downstream production of proinflammatory cytokines as predictors of ICI response. RESULTS: We demonstrated that ML-RNA-NPs can activate multiple PRRs simultaneously. Following ML-RNA-NP challenge, ICI responsive tumors GL261 and SMA-560 (compared to more ICI resistant lines KR158b and CT2A) elicited increased production in pro-inflammatory cytokines such as IFN-β and IL-6 and in CCL4. To further develop this work into a commercially viable tool to predict ICI response, we developed 3D modeling of glial tumors for ML RNA-NP challenge and immunogenicity prediction. We enrolled canines with primary gliomas and began growing their tumoroids in 3D using liquid-like solid (LLS) technology. Using this pipeline, we successfully perfused 3D murine tumoroids with ML RNA-NP demonstrating ability to set up real-time patient derived explants to predict immunogenicity. We demonstrated that mRNA perfusion of 3D tumoroids elicited similar cytokine response observed with 2D culture of cell-lines. CONCLUSIONS: Our results indicate that cytokine signatures following ML RNA-NP challenge differ significantly from ICI responsive versus non-responsive brain tumors. These findings allow for creation of a diagnostic assay to quickly assess tumor immunogenicity, allowing for informed treatment with ICIs.

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Publication Details

Journal
Neurosurgery
Published
2025-03-14
DOI
https://doi.org/10.1227/neu.0000000000003360_507
Primary Topic
Radiopharmaceutical Chemistry and Applications
Type
article
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article

507 MRNA Challenge Predicts Brain Cancer Immunogenicity and Response to Checkpoint Inhibitors

Hilary Geffrard, Elizabeth Ogando‐Rivas, Dingpeng Zhang, Héctor Méndez-Gómez et al.
Neurosurgery
Radiopharmaceutical Chemistry and Applications
article

507 MRNA Challenge Predicts Brain Cancer Immunogenicity and Response to Checkpoint Inhibitors

Hilary Geffrard, Elizabeth Ogando‐Rivas, Dingpeng Zhang, Héctor Méndez-Gómez, John A. Ligon, Elias Sayour, Alfonso Pepe, Rachel Moor, Jianping Huang, Natalie L. Silver, Paul Castillo, Frances Weidert, Anna DeVries, Sadeem Qdaisat, Rowan J. Milner, Maryam Rahman, Ekkehard M. Kasper
article en

Abstract

INTRODUCTION: Pathogen recognition receptor (PRRs) activation is requisite for igniting the immune response and making the tumor microenvironment ‘hot’ during oncogenesis. We theorized that these PRRs would remain present in ICI responsive tumors and could be challenged using pan-PRR mimic to prospectively predict brain cancer immunogenicity and response to immune checkpoint inhibitors (ICIs) METHODS: By layering mRNA into multilamellar nanoparticles (ML RNA-NPs), multiple pathogen recognition receptors can be simultaneously activated in individualized cancer cells serving as a broad screen to test tumor immunogenicity. We challenged murine brain tumor lines known to respond (GL261 and SMA-560) or resist ICI treatment (KR158b and CT2A) with ML RNA-NPs and analyzed downstream production of proinflammatory cytokines as predictors of ICI response. RESULTS: We demonstrated that ML-RNA-NPs can activate multiple PRRs simultaneously. Following ML-RNA-NP challenge, ICI responsive tumors GL261 and SMA-560 (compared to more ICI resistant lines KR158b and CT2A) elicited increased production in pro-inflammatory cytokines such as IFN-β and IL-6 and in CCL4. To further develop this work into a commercially viable tool to predict ICI response, we developed 3D modeling of glial tumors for ML RNA-NP challenge and immunogenicity prediction. We enrolled canines with primary gliomas and began growing their tumoroids in 3D using liquid-like solid (LLS) technology. Using this pipeline, we successfully perfused 3D murine tumoroids with ML RNA-NP demonstrating ability to set up real-time patient derived explants to predict immunogenicity. We demonstrated that mRNA perfusion of 3D tumoroids elicited similar cytokine response observed with 2D culture of cell-lines. CONCLUSIONS: Our results indicate that cytokine signatures following ML RNA-NP challenge differ significantly from ICI responsive versus non-responsive brain tumors. These findings allow for creation of a diagnostic assay to quickly assess tumor immunogenicity, allowing for informed treatment with ICIs.

NeurosurgeryVol. 71(Supplement_1)
Openalex Percentile: Top 93%
Radiopharmaceutical Chemistry and Applications
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