Genome-wide discovery and identification of a novel miRNA signature for recurrence prediction in stage II and III colorectal cancer

Purpose The current TNM (Tumor Node Metastasis) staging system is inadequate at identifying high-risk colorectal cancer (CRC) patients. Using a systematic and comprehensive-biomarker discovery and validation approach, we aimed to identify a miRNA-recurrence classifier (MRC) that can improve upon the current TNM-staging as well as superior to currently offered molecular assays. Experimental Design Three independent genome-wide miRNA-expression profiling datasets were used for biomarker discovery (N=158) and in-silico validation (N=109 and N=40) to identify a miRNA signature for predicting tumor recurrence in CRC patients. Subsequently, this signature was analytically trained and validated in retrospectively collected independent patient cohorts of fresh frozen (N=127, cohort 1) and FFPE (N=165, cohort 2 and N=139, cohort 3) specimens. Results We identified an 8-miRNA signature that significantly predicted recurrence free interval (RFI) in the discovery (p=0.002) and two independent publicly available datasets (p=0.00006 and p=0.002). The RT-PCR based validation in independent clinical cohorts revealed that MRC-derived high-risk patients succumb to significantly poor RFI in stage II and III CRC patients [cohort 1: HR: 3.44 (1.56-7.45), P=0.001, cohort 2: HR: 6.15 (3.33-11.35), P=0.001 and cohort 3: HR: 4.23 (2.26-7.92), P=0.0003]. In multivariate analyses, MRC emerged as an independent predictor of tumor recurrence, and achieved superior predictive accuracy than the currently available molecular assays. Conclusions This novel miRNA-recurrence classifier works superior to currently used clinicopathological features, as well as NCCN criteria, and works independent of adjuvant chemotherapy status in identifying high-risk stage II and III CRC patients. This can be deployed in clinical practice with FFPE specimens.

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