CIEC: Cross-tissue Immune Cell Type Enrichment and Expression Map Visualization for Cancer

Area of Science:

• Immunology
• Bioinformatics
• Genomics

Background:

• Single-cell transcriptome sequencing reveals immune cell functions in cancer immunity.
• Understanding immune cell heterogeneity across tissues is crucial for cancer research.

Purpose of the Study:

• To introduce Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), a web-based application.
• To provide a comprehensive resource for analyzing immune cell characteristics across multiple cancer-related tissues.

Main Methods:

• Integrative analysis of 480 samples from 323 cancer patients, covering various tissue types.
• Utilized the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm for enrichment analysis.
• Developed a user-friendly online interface for data exploration.

Main Results:

• Constructed an immune cell type/state map for different cancer contexts.
• Enabled estimation of enrichment for context-specific immune cell types/states.
• Provided tools for expression mapping, correlation analysis, and signature scoring.

Conclusions:

• CIEC is a valuable resource for exploring intrinsic immune cell characteristics in cancer patients.
• The tool can potentially guide the development of novel cancer-immune biomarkers and immunotherapy strategies.
• CIEC is freely accessible online for researchers worldwide.