Cancer Discovery · 2025 · 33 citations · 63 references
Life SciencesImmunologyOncologyCancer ImmunologyImmunotherapyTumor ImmunologyCancer ImmunotherapyCheckpoint Inhibitor TherapyImmune Checkpoint InhibitorsKidney CancerT Cell ExhaustionTumor-infiltrating LymphocytesCd8 Positive T CellsImmune Checkpoint Inhibitor ResponseImmune Checkpoint Inhibitor TherapyImmune Checkpoint ResistanceProgrammed Cell Death Protein 1 (Pd-1) PathwayResistance To Checkpoint InhibitorsTertiary Lymphoid StructuresTumor Microenvironment Characterization
Abstract Immune checkpoint inhibitors targeting the PD-1 pathway have transformed treatment of advanced renal cell carcinoma (RCC), but mechanisms underlying the therapeutic response remain largely unknown. In this study, we perform transcriptomic analysis on RCC biospecimens from 102 patients enrolled in a phase II clinical trial of first-line nivolumab (NCT03117309) to investigate determinants of response to anti–PD-1 monotherapy. Through bulk analysis, we identify an enrichment of genes associated with tertiary lymphoid structures (TLS) in responding patients. Using single-cell transcriptomics and external cohort validation, we identify a population of tissue-resident (ZNF683+SLAMF7+) exhausted CD8+ T cells enriched in patients with poor clinical outcomes. Integrating these findings, we find tumors with high TLS and low tissue-resident exhausted CD8+ T cells that have superior clinical outcomes with nivolumab. Altogether, these analyses contribute to a growing understanding of how the tumor microenvironment drives immune checkpoint inhibitor resistance and propose possible therapeutic targets to rationally overcome resistance to anti–PD-1 monotherapy. Significance: We describe a paradigm wherein combined high TLS and low tissue-resident exhausted CD8+ T cells are required for optimal response to PD-1 blockade in RCC. This analysis identifies key determinants of response to PD-1 blockade in advanced RCC and suggests avenues for future immune modulation through rational combination therapy strategies.
63
STAR: ultrafast universal RNA-seq aligner
Alexander Dobin, Carrie Davis, Felix Schlesinger et al. · Bioinformatics · 2012 · 56.2K citations · Full text
Classification and Regression by randomForest
Andy Liaw, Matthew C. Wiener · 2007 · 18.4K citations