Using machine learning method to identify as a novel marker to predict biochemical recurrence in prostate cancer.

Journal: Biomarkers in medicine
Published Date: Jan 1, 2021

Abstract

This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. We identified as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that was a DNA methylation-driven gene. Additionally, had significant positive correlations with immune infiltrations. was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

Authors

  • Peng Qiao
    Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
  • Di Zhang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Song Zeng
    Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
  • Yicun Wang
    Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
  • Biao Wang
    School of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212100, China.
  • Xiaopeng Hu
    Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin University of Science and Technology, Tianjin, China.

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