Transcriptome analysis and artificial intelligence for predicting lymph node metastasis of esophageal squamous cell carcinoma.

Journal: Journal of thoracic disease
Published Date: May 28, 2025

Abstract

BACKGROUND: Lymph node metastasis (LNM) is the most common route of metastasis in esophageal squamous cell carcinoma (ESCC), and the treatment of patients with ESCC largely depends on the LNM status. The methods for diagnosing LNM in ESCC are still not accurate enough, and accurate LNM staging is crucial for clinical practice. The purpose of this study was to investigate the value of combining transcriptome analysis with artificial intelligence (AI) in predicting LNM and to construct an effective predictive model for LNM in ESCC.

Authors

  • Zhengang Zhao
    Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
  • Yujie Xie
    Lung Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
  • Dongmei Lai
    Department of Oncology, Gaozhou People's Hospital Affiliated to Guangdong Medical University, Maoming, China.
  • Jin Liang
    College of Tea & Food Science, Anhui Agricultural University, Hefei, China.
  • Ikenna C Okereke
    Department of Surgery, Henry Ford Health, Detroit, MI, USA.
  • Wanli Lin
    Department of Thoracic Surgery, Gaozhou People's Hospital Affiliated to Guangdong Medical University, Maoming, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals