A pan-cancer single-cell RNA-seq atlas of intratumoral B cells

Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large...

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Veröffentlicht in:Cancer cell 2024-10, Vol.42 (10), p.1784-1797.e4
Hauptverfasser: Fitzsimons, Evelyn, Qian, Danwen, Enica, Andrei, Thakkar, Krupa, Augustine, Marcellus, Gamble, Samuel, Reading, James L., Litchfield, Kevin
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Sprache:eng
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Zusammenfassung:Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large sample cohort. We identify key B cell subset signatures, revealing distinct subpopulations and highlighting the heterogeneity and functional diversity of these cells in the tumor microenvironment. We explore associations between B cell subsets and checkpoint inhibitor therapy responses, finding subset-specific effects on overall response. Additionally, we examine B and T cell crosstalk, identifying unique ligand-receptor pairs for specific B cell subsets, spatially validated. This comprehensive dataset serves as a valuable resource, providing a detailed atlas that enhances the understanding of B cell complexity in tumors and opens new avenues for research and therapeutic strategies. [Display omitted] •A scRNA-seq atlas identifies ten clusters of intratumoral B and plasma cells•Specific B cell subsets are associated with checkpoint inhibitor therapy responses•Atlas-derived B cell gene signatures validated in spatial analyses•Publicly available Shiny tool enables users to interactively explore the atlas Fitzsimons et al. present a comprehensive pan-cancer single-cell RNA-seq atlas of intratumoral B cells, identifying ten distinct B and plasma cell clusters. They uncover associations with checkpoint inhibitor therapy response, explore B-T cell crosstalk, validate findings with spatial data, and offer an interactive tool for further research.
ISSN:1535-6108
1878-3686
1878-3686
DOI:10.1016/j.ccell.2024.09.011