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Immune-remodeling mRNAs expressing IRF8 or NIK generate durable anti-tumor immunity in multiple cancer models

GSE325843 Mus musculus Expression profiling by high throughput sequencing 4 samples Submitted 2026/03/29 Platform GPL24247Platform GPL34475
Summary
Although immunotherapy has a subset of cancer patients, its broader efficacy remains limited, primarily due to an immunosuppressive tumor microenvironment characterized by insufficient numbers of functional tumor-specific T cells, antigen-presenting cells (APCs) and tumor-infiltrating lymphocytes. Here we engineer immune cells in the tumor microenvironment using lipid nanoparticles (LNPs) to deliver immune remodeling mRNAs (IR-mRNAs) encoding NF-κB inducing kinase (NIK) or interferon regulatory factor 8 (IRF8). These IR-mRNAs activate APCs in tumors, significantly increasing activated type 1 conventional dendritic cells, immunostimulatory cytokines, and priming anti-tumor CD8+ T cells. IR-mRNAs encapsulated in LNPs elicited durable antitumor responses in multiple syngeneic mouse tumor models via both intratumoral and intravenous delivery. Co-administration of IR- and OVA-mRNA elicited ~10-fold increase of antigen-specific CD8⁺ T cell responses, sustained long-term memory, and effectively prevented tumor growth in vaccinated mice. Additionally, adjuvanting influenza vaccines with IR-mRNAs enhanced the humoral response by 5-fold and the cellular response by ~15-fold, underscoring their potential as adjuvants for boosting adaptive immunity.
Published in
Immune-remodeling mRNAs expressing IRF8 or NIK generate durable antitumor immunity in multiple cancer models
Gupta A, Das R, Reed K et al. · Nature biotechnology 2026 · PMID 42129506 · doi:10.1038/s41587-026-03115-2
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Direct links to NCBI, no account and no request form: the whole study as GSE325843_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1442052 and SRA study SRP686241. Searching any of these in the dataset finder brings you back here.

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