Machine learning reveals glycolytic key gene in gastric cancer prognosis.

Journal: Scientific reports
PMID: 40082583

Abstract

Glycolysis is recognized as a central metabolic pathway in the neoplastic evolution of gastric cancer, exerting profound effects on the tumor microenvironment and the neoplastic growth trajectory. However, the identification of key glycolytic genes that significantly affect gastric cancer prognosis remains underexplored. In this work, five machine-learning algorithms were used to elucidate the intimate association between the glycolysis-associated gene phosphofructokinase fructose-bisphosphate 3 (PFKFB3) and the prognosis of gastric cancer patients. Validation across multiple independent datasets confirmed the prognostic significance of PFKFB3. Further, we delved into the functional implications of PFKFB3 in modulating immune responses and biological processes within gastric cancer patients, as well as its broader relevance across multiple cancer types. Results underscore the potential of PFKFB3 as a prognostic biomarker and therapeutic target in gastric cancer. Our project can be found at https://github.com/PiPiNam/ML-GCP .

Authors

  • Nan Li
    School of Basic Medical Sciences, Jiamusi University No. 258, Xuefu Street, Xiangyang District, Jiamusi 154007, Heilongjiang, China.
  • Yuzhe Zhang
    School of Environmental Science and Engineering, Changzhou University, Changzhou, China.
  • Qianyue Zhang
    China Academy of Electronics and Information Technology, National Engineering Research Center for Public Safety Risk Perception and Control by Big Data (RPP), Beijing, China.
  • Hao Jin
    School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China.
  • Mengfei Han
    China Academy of Electronics and Information Technology, National Engineering Research Center for Public Safety Risk Perception and Control by Big Data (RPP), Beijing, China.
  • Junhan Guo
    Center for Reproductive Medicine, Henan Key Laboratory of Reproduction and Genetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Ye Zhang
    Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

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