Journal of Shandong University (Health Sciences) ›› 2025, Vol. 63 ›› Issue (9): 31-39.doi: 10.6040/j.issn.1671-7554.0.2024.1401

• Special Issue on “Big DataEnabled, AI Foundation ModelDriven Multimodal Cohort Design and Analysis” • Previous Articles    

Pan-cancer cell type-specific gene-gene co-expression pattern

LI Jing1,2, JU Weihang1,2, LIU Ke1,2   

  1. 1. Department of Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. National Institute of Health and Medicine Big Data, Jinan 250003, Shandong, China
  • Published:2025-09-08

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Abstract: Objective To investigate the gene co-expression patterns across diverse cell types within multiple cancer tissues using single-cell omics data. Methods Utilizing large-scale public single-cell transcriptomics data and the CS-CORE method, cell type-specific gene co-expression profiles were generated for six common cell types across five distinct cancers. Results A total of 30 high-quality gene co-expression maps were obtained. Among the analyzed cell types, malignant cells exhibited the highest number of co-expressed gene pairs, suggesting a relatively complex gene regulatory mechanism. Hierarchical clustering across cancer types revealed that the regulatory breadth of transcription factors tended to be conserved within the same cell type. Additionally, macrophages displayed the most differentially co-expressed gene pairs, suggesting that the gene regulatory network of macrophages might be susceptible to the influence of the tumor microenvironment. Conclusion This study systematically constructs a cell type-specific gene co-expression map in cancer tissues, uncovering several gene co-expression patterns from a pan-cancer perspective.

Key words: Cell type specificity, Gene co-expression, Cancer, Single-cell transcriptome, Pan-cancer

CLC Number: 

  • R730.2
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