Abstract 502P
Background
Esophageal squamous cell carcinoma (ESCC) is a widespread malignant tumor in Asia. Despite neoadjuvant chemoradiotherapy (NCRT) reshaping ESCC treatment landscape, its efficacy varies across individuals. Although several miRNA biomarkers have been constructed to forecast the efficacy of NCRT, these predictors may lack generalizability and comparability due to batch effects arising from miRNA absolute expression values. Therefore, we aim to identify a specific miRNA pair based on pairwise-comparison analysis for predicting NCRT benefits of ESCCs.
Methods
Endoscopic samples of 215 ESCC patients before NCRT were enrolled from multiple centers in China. MiRNA expression profiles of 102 patients in the discovery cohort were explored by sequencing. 6215 miRNA pair scores were generated based on their relative expression levels, assigned as 1 if miRNA-1 expressed more than miRNA-2; otherwise, assigned as 0. MiRNA pairs significantly associated with prognosis were identified by Cox regression. The selected miRNA pair was validated in internal (N=80) and external (N=33) verification cohorts by RT-qPCR, and its prognostic value was evaluated in all three cohorts.
Results
Six miRNA pairs significantly correlated with prognosis (P < 0.001) were identified, and miR-1180-3p|miR-505-3p showed the highest efficacy in distinguishing patients with different survival outcomes. In the discovery cohort, it achieved impressive accuracy with an area under the receiver operating characteristic curve (AUC) of 0.76 (95%CI: 0.66-0.86) for overall survival (OS) and 0.75 (95%CI: 0.65-0.85) for recurrence-free survival. Its expression patterns were assessed in both internal and external verification cohorts, and its performance was evaluated for OS in both cohorts, with AUC values of 0.58 (95%CI: 0.43-0.71) and 0.62 (95%CI: 0.43-0.80), respectively.
Conclusions
We identified a novel miRNA pair miR-1180-3p|miR-505-3p of survival prediction for ESCC with NCRT, which suggests potential research directions for tumor-miRNA interaction mechanisms. Further validation through prospective clinical trials could facilitate its application on personalized treatment.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
J. He.
Funding
The National Natural Science Foundation of China (82203025).
Disclosure
All authors have declared no conflicts of interest.