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Cellular Dynamics Upon Immune Checkpoint Inhibition

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet most patients experience limited or no clinical benefit. To elucidate the mechanisms of response and resistance, we analyzed single-cell RNA-sequencing data from 141 patients across multiple cancer types and ICI treatment modalities, with longitudinally paired samples. Using a robust, integration-free deep phenotyping framework, we annotated 876,410 cells into 80 granular states. We identified consistent compositional changes in 17 cell subtypes following ICI treatment, including enhanced adaptive immune responses and reduced interferon-responsive cells. Co-regulated cell communities within the tumor microenvironment (TME) highlighted coordinated interplay between immune and non-immune components. Importantly, we discovered two distinct patient groups with divergent TME dynamics post-treatment: responders showed expansion of naive lymphocytes, while non-responders exhibited increased immune-experienced/suppressive cells. This dichotomy offers a potential predictive biomarker for patient stratification. Our comprehensive analysis of TME dynamics during ICI treatment advances understanding of response mechanisms and personalized cancer immunotherapy.

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Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD50000000665 Illumina NovaSeq 6000 13