Transcriptomic profiling reveals an enhancer RNA signature for recurrence prediction in colorectal cancer

Background: Colorectal cancer (CRC) is one of the most fatal malignancies worldwide, and this is in part due to high rates of tumor recurrence in these patients. Currently, TNM staging remains the gold standard for predicting prognosis and recurrence in CRC patients; however, this approach is inadequate for the identification of high-risk patients who have the highest likelihood of disease recurrence. Recent evidence has revealed that enhancer RNAs (eRNAs) represent a higher level of cellular regulation and their expression is frequently dysregulated in several cancers including CRC. However, the clinical significance of eRNAs as recurrence predictor biomarkers in CRC remains unexplored, which was the primary aim of this study. Results We performed a systematic analysis of eRNA expression profiles in colon cancer (CC) and rectal cancer (RC) patients, from the TCGA dataset. By using rigorous biomarker discovery approaches, by splitting the entire dataset into a training and the testing cohort, we identified a 22-eRNA panel in CC, and a 19-eRNA panel in RC for predicting tumor recurrence. The Kaplan-Meier analysis showed that biomarker panels robustly stratified low and high-risk CC ( P  = 7.29e-05) and RC ( P  = 6.81e-03) patients with recurrence. Multivariate and LASSO Cox regression models indicated that both biomarker panels were independent predictors of recurrence, and significantly superior to TNM staging in CC (HR = 11.89, P  = 9.54e-04) and RC (HR = 3.91, P  = 3.52e-02). Importantly, the ROC curves demonstrated that both panels exhibited excellent recurrence prediction accuracy in CC (AUC = 0.833; 95% CI: 0.74–0.93) and RC (AUC = 0.834; 95% CI: 0.72–0.92) patients. Subsequently, a combination signature which included the eRNA panels along with TNM staging achieved an even greater predictive accuracy in patients with CC (AUC = 0.85). Conclusion Herein, we report a novel eRNA signature for predicting recurrence in patients with CRC. Further experimental validation in independent clinical cohorts, these biomarkers have the potential to improve current risk stratification approaches for guiding precision oncology treatments in patients suffering from this lethal malignancy.