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

Abstract

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlasdatabase, Gene Expression Omnibusdatabase and Cancer Cell Line Encyclopediadatabase were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK 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 MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion:MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.