A blood-based noninvasive miRNA signature for predicting survival outcomes in patients with intrahepatic cholangiocarcinoma.

Abstract

The prognosis in patients with intrahepatic cholangiocarcinoma (ICC) is generally poor. To improve treatment selection, we sought to identify microRNA (miRNA) signature associated with survival outcomes in ICC. We first analysed the miRNA expression profiles of primary ICC from two public datasets to identify a miRNA panel to detect patients for short-term survival. We then analysed 309 specimens, including 241 FFPE samples from two clinical cohorts (training: n = 177; validation: n = 64) and matched plasma samples (n = 68), and developed a risk-stratification model incorporating the panel and CA 19-9 levels to predict survival outcomes in ICC. We identified a 7-miRNA panel that robustly classified patients with poor outcomes in the discovery cohorts (AUC = 0.80 and 0.88, respectively). We subsequently trained this miRNA panel in a clinical cohort (AUC = 0.83) and evaluated its performance in an independent validation cohort (AUC = 0.82) and plasma samples from the additional validation cohort (AUC = 0.78). Patients in both clinical cohorts who were classified as high-risk had significantly worse prognosis (p < 0.01). The risk-stratification model demonstrated superior performance compared to models (AUC = 0.85). We established a novel miRNA signature that could robustly predict survival outcomes in resected tissues and liquid biopsies to improve the clinical management of patients with ICC.