SCAR

SCAR integrates spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from over 11 million cells across 395 cancer subtypes to enable systematic analysis of tumor heterogeneity, tumor microenvironment interactions, and multi-omics features.

Key Features:

• Integrated data coverage: Combines spatial transcriptomic and single-cell transcriptomic profiling across 21 tumor tissues, organoids, and cell lines, totaling over 11 million cells across 395 cancer subtypes.
• Spatial and single-cell modalities: Retains spatial transcriptomics and single-cell transcriptomics to resolve cellular localization and transcriptomic heterogeneity within tumors.
• Functional analysis modules: Provides modules for screening tumor cell types, analyzing metabolic features, examining cell communication pathways, and interrogating gene expression patterns within the tumor microenvironment.
• Biomarker and trajectory analysis: Enables profiling of biomarker expression patterns and analysis of cell developmental trajectories within tumor contexts.
• Multi-dimensional omics integration: Supports integrated analyses across 34 state-of-the-art omics techniques to investigate cell heterogeneity and spatial location.

Scientific Applications:

• Basic cancer biology: Facilitates analysis of cellular diversity and interactions using single-cell and spatial transcriptomics across diverse cancer subtypes.
• Immunotherapy development: Supports identification of immune-evasion mechanisms and candidate therapeutic targets within the tumor microenvironment.
• Tumor microenvironment analysis: Enables study of cell–cell communication, metabolic states, and spatial gene expression patterns in tumors.
• Biomarker and trajectory discovery: Allows discovery and characterization of biomarkers and cell developmental trajectories across tissues, organoids, and cell lines.

Methodology:

Integrates spatial transcriptomic and single-cell transcriptomic datasets and implements modules for tumor cell-type screening, metabolic feature analysis, cell communication analysis, spatial gene expression interrogation, biomarker profiling, trajectory analysis, and multi-omics integration across 34 omics techniques.