SCAR: Single-cell and Spatially-resolved Cancer Resources

Abstract Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to compreh...

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Veröffentlicht in:Nucleic acids research 2024-01, Vol.52 (D1), p.D1407-D1417
Hauptverfasser: Deng, Yushan, Chen, Peixin, Xiao, Jiedan, Li, Mengrou, Shen, Jiayi, Qin, Siying, Jia, Tengfei, Li, Changxiao, Chang, Ashley, Zhang, Wensheng, Liu, Hebin, Xue, Ruidong, Zhang, Ning, Wang, Xiangdong, Huang, Li, Chen, Dongsheng
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Sprache:eng
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Zusammenfassung:Abstract Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development. Graphical Abstract Graphical Abstract
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gkad753