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Single-Cell RNA Sequencing of Baseline PBMCs Predicts ICI efficacy and irAE Severity in NSCLC Patients

GSE285888 Homo sapiens Expression profiling by high throughput sequencing 1 samples Submitted 2025/05/19 Platform GPL16791
Summary
Immune checkpoint inhibitors (ICIs) have revolutionized by offering remarkable clinical benefits and durable responses for patients with advanced non-small cell lung cancer (NSCLC). However, a very small percentage of patients responded to ICI treatment, and immune-related adverse events (irAEs) leading to treatment discontinuation remain challenges. Despite the recognized need for biomarkers that can predict both the efficacy of ICIs and the risk of irAEs, such biomarkers have yet to be clearly identified. In this study, we performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMC) from NSCLC patients prior to treatment with ICIs. We found that the immune response is generally reduced in patients with poor prognosis. However, the hypoxic environment is particularly more prominent in patients with primary resistance compared to those with acquired resistance. Meanwhile, granzyme and perforin are closely associated with favorable prognosis. We also identified IL1B and CXCL8 as key predictors of irAEs, with their activation linked to inflammation. Moreover, we found that PRF1 in CD8+ T cells and NK cells plays a critical mediator of complete responses and reduced irAE to ICI therapy. These findings deepen our understanding of the mechanisms of ICI efficacy and provide valuable information for optimizing immunotherapy strategies. By identifying biomarkers for both better prognosis and irAEs, this research lays the foundation for personalized immunotherapy approaches that aim to improve clinical outcomes while minimizing the risks associated with ICI treatment.
Published in
Single-cell RNA sequencing of baseline PBMCs predicts ICI efficacy and irAE severity in patients with NSCLC
Kim GD, Shin SI, Sun P et al. · Journal for immunotherapy of cancer 2025 · PMID 40404203 · doi:10.1136/jitc-2025-011636
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Also filed as BioProject PRJNA1206711. Searching any of these in the dataset finder brings you back here.

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