Inferring Cell-type-specific Genes of Lung Cancer Based on Deep Learning.

Journal: Current gene therapy
Published Date:

Abstract

BACKGROUND: Lung cancer is cancer with the highest incidence in the world, and there is obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology allows researchers to obtain cell-type-specific expression genes at the single-cell level, thereby obtaining information regarding the cell status and subpopulation distribution, as well as the communication behavior between cells. Many researchers have applied this technology to lung cancer research, but due to the shortcomings of insufficient sequencing depth, only a small part of the gene expression can be detected. Researchers can only roughly compare whether a few thousand genes are significant in different cell types.

Authors

  • Nitao Cheng
    Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
  • Chen Chen
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Changsheng Li
  • Jingyu Huang
    Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.