American Association for Cancer Research
10780432ccr173236-sup-191721_3_supp_4586214_pb1r7h.xlsx (112.62 kB)

Supplementary Table 2 from Genome-wide Discovery and Identification of a Novel miRNA Signature for Recurrence Prediction in Stage II and III Colorectal Cancer

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posted on 2023-03-31, 21:41 authored by Raju Kandimalla, Feng Gao, Takatoshi Matsuyama, Toshiaki Ishikawa, Hiroyuki Uetake, Naoki Takahashi, Yasuhide Yamada, Carlos Becerra, Scott Kopetz, Xin Wang, Ajay Goel

Supplementary Table 2: Data of miRNAs which are analyzed in the TCGA discovery cohort with associated statistical parameters.


National Cancer Institute


Cancer Prevention Research Institute of Texas

Baylor Foundation and Baylor Scott & White Research Institute

Research Grants Council of the Hong Kong Special Administrative Region, China

Science Technology and Innovation Committee of Shenzhen



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 AACR.See related commentary by Rodriguez et al., p. 3787

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