Genome-wide Discovery and Identification of a Novel miRNA Signature for Recurrence Prediction in Stage II and III Colorectal Cancer

Abstract

Purpose: The current tumor-node-metastasis (TNM) staging system is inadequate at identifying patients with high-risk colorectal cancer. Using a systematic and comprehensive biomarker discovery and validation approach, we aimed to identify an miRNA recurrence classifier (MRC) that can improve upon the current TNM staging as well as is 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 an miRNA signature for predicting tumor recurrence in patients with colorectal cancer. Subsequently, this signature was analytically trained and validated in retrospectively collected independent patient cohorts of fresh-frozen (N = 127, cohort 1) and formalin-fixed paraffin-embedded (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 patients with stage II and III colorectal cancer [cohort 1: hazard ratio (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 over 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 MRC is superior to currently used clinicopathologic features, as well as National Comprehensive Cancer Network (NCCN) criteria, and works regardless of adjuvant chemotherapy status in identifying patients with high-risk stage II and III colorectal cancer. This can be readily deployed in clinical practice with FFPE specimens for decision-making pending further model testing and validation. Clin Cancer Res; 24(16); 3867-77. ©2018 AACRSee related commentary by Rodriguez et al., p. 3787.

Figure 1

Study Design

Figure 2

A miRNA classifier Volcano plot and KM curves predicting recurrence-free interval in the TCGA discovery, validation and GSE validation cohorts. A) Volcano plot showing the significant and differentially regulated miRNAs selected in the TCGA discovery cohort. Selected miRNAs are depicted in the figure. The Kaplan Meier survival plots for recurrence-free interval stratified by MRC scores in the: B) TCGA discovery cohort (N=158), C) TCGA validation cohort (N=109), and D) the GSE29623 validation cohort (N=40). E) and F) The Kaplan Meier plots illustrating that both CMS4 and non-CMS4 patients with high miRNA risk scores exhibited shorter recurrence-free interval in the TCGA discovery and validation cohorts, respectively.

Figure 3

Stage-wise survival curves predicting recurrence-free interval in fresh-frozen specimens in clinical cohort-1. The Kaplan Meier survival plots for recurrence-free interval stratified by MRC scores in: A) combined stage II and III CRC patients, B) stage II patients, C) stage III CRC patients, and D) Hazard Ratios of the miRNA classifier, NCCN risk classification and other clinicopathological variables presented for stage II CRC patients.

Figure 4

Training and validation of the miRNA recurrence classifier in the FFPE specimens in clinical cohorts 2 and 3. A and G) Depict MRC risk score violin plots from Cox regression model of the 8-miRNA signature in the training and validation cohorts, respectively. B, C, D and H, I, J) Stage-wise Kaplan Meier plots for the recurrence-free interval in the training (N=165) and validation (N=139) cohorts, stratified based on the MRC risk scores and E and K) Receiver Operating Characteristic (ROC) curves achieved with MRC risk-scores as well as its combination with the tumor stage and lymphatic invasion in the training and validation cohorts, respectively. F and L) Hazard Ratios of the miRNA classifier, NCCN risk classification and other clinicopathological variables presented for stage II CRC from both cohorts.