CanCellCap: robust cancer cell capture across tissue types on single-cell RNA-seq data by multi-domain learning.

Journal: BMC biology
Published Date: Jul 30, 2025

Abstract

BACKGROUND: The advent of single-cell RNA sequencing (scRNA-seq) has provided unprecedented insights into cancer cellular diversity, enabling a comprehensive understanding of cancer at the single-cell level. However, identifying cancer cells remains challenging due to gene expression variability caused by tumor or tissue heterogeneity, which negatively impacts generalization and robustness.

Authors

  • Jiaxing Bai
    Department of Automation, National Institute for Data Science in Health and Medicine, State Key Laboratory of Mariculture Breeding, Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen University, Xiamen, Fujian, China.
  • Yichun Gao
    Department of Automation, National Institute for Data Science in Health and Medicine, State Key Laboratory of Mariculture Breeding, Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen University, Xiamen, Fujian, China.
  • Feng Zhou
    Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Yushuang He
    Department of Ultrasound and West China Biomedical Big Data Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan, 610000, China.
  • Chen Lin
    Faculty of Business and Economics, University of Hong Kong, Hong Kong SAR 999077, China.
  • Xiaobing Huang
    Research Center for Ageing Society of Jiangxi Provincial Association of Social Science, Gannan Normal University, Ganzhou, China.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.

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