A Blood-based Noninvasive MiRNA Signature for Predicting Survival Outcomes in Patients with Intrahepatic Cholangiocarcinoma

Background: 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.

Methods: 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.

Results: 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).

Conclusions: 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.