Identification of a gene signature and prediction of overall survival of patients with stage IV colorectal cancer using a novel machine learning approach.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
PMID: 39987816

Abstract

OBJECTIVE: We sought to characterize unique gene signature patterns associated with worse overall survival (OS) among patients with stage IV colorectal cancer (CRC) using a machine learning (ML) approach.

Authors

  • Abdullah Altaf
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
  • Jun Kawashima
    Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, USA.
  • Mujtaba Khalil
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
  • Hunter Stecko
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
  • Zayed Rashid
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
  • Matthew Kalady
    Department of Surgery, Division of Colorectal Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
  • Timothy M Pawlik
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, Columbus, OH.

Keywords

External Resources

Popular Topics
Recent Journals