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Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

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NATURE CANCER
卷 4, 期 4, 页码 502-+

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NATURE PORTFOLIO
DOI: 10.1038/s43018-023-00534-x

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This study conducted an exploratory biomarker analysis of refractory tumors in pediatric patients before atezolizumab therapy. Elevated levels of CD8+T cells and PD-L1 were associated with improved progression-free survival, while a diverse baseline infiltrating T-cell receptor repertoire was prognostic. The differential gene expression analysis identified CALCA and CCDC183 as potential contributors to immune response, and elevated Iga2 expression was correlated with T-and B-cell infiltration. Consensus gene co-expression network analysis revealed core cellular pathways in antitumor immunity. These findings provide insights for future clinical trials and biomarker profiling.
We report herein an exploratory biomarker analysis of refractory tumors collected from pediatric patients before atezolizumab therapy (iMATRIX-atezolizumab, NCT02541604). Elevated levels of CD8+T cells and PD-L1 were associated with progression-free survival and a diverse baseline infiltrating T-cell receptor repertoire was prognostic. Differential gene expression analysis revealed elevated expression of CALCA (preprocalcitonin) and CCDC183 (highly expressed in testes) in patients who experienced clinical activity, suggesting that tumor neoantigens from these genes may contribute to immune response. In patients who experienced partial response or stable disease, elevated Iga2 expression correlated with T-and B-cell infiltration, suggesting that tertiary lymphoid structures existed in these patients' tumors. Consensus gene co-expression network analysis identified core cellular pathways that may play a role in antitumor immunity. Our study uncovers features associated with response to immune-checkpoint inhibition in pediatric patients with cancer and provides biological and translational insights to guide prospective biomarker profiling in future clinical trials.

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