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

May 146, 1038

Authors

Kandimalla R†, Gao F†, Matsuyama T, Ishikawa T, Uetake H, Takahashi N, Yamada Y, Becerra C, Kopetz S, Wang X* and Goel A*.

Clin Cancer Res 2018

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 RTPCR 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. The RT-PCR based MRC risk score = (- 0.1218×miR-744) + (-3.7142×miR-429) + (-2.2051×miR-362) + (3.0564×miR-200b) + (2.4997×miR-191) + (-0.0065×miR-30c2) + (2.2224×miR-30b) + (-1.1162×miR-33a).

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 readily deployed in clinical practice with FFPE specimens for decision making pending further model testing and validation.