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

• Published in: Genomics, proteomics & bioinformatics Vol. 23; no. 1
• Main Authors: He, Jinhua, Luo (罗海涛), Haitao, Wang (王伟), Wei, Bu (卜德超), Dechao, Zou (邹正楷), Zhengkai, Wang (王浩霖), Haolin, Tang, Hongzhen, Han, Zeping, Luo, Wenfeng, Shen, Jian, Xie, Fangmei, Zhao (赵屹), Yi, Xiang, Zhiming
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 10.05.2025
• Subjects: Algorithms; Databases, Genetic; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Neoplasms - genetics; Neoplasms - immunology; Neoplasms - pathology; Software; Transcriptome; Web Server; Cancer single-cell data; Expression map; Enrichment analysis; Cross-tissue analysis; Immune cell
• ISSN: 1672-0229; 2210-3244
• DOI: 10.1093/gpbjnl/qzae067

Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell types or states. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell type/state map for each context, and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell types/states. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar gene detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer–immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.