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

Abstract

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. Three independent genome-wide miRNA expression profiling datasets were used for biomarker discovery ( = 158) and validation ( = 109 and = 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 ( = 127, cohort 1) and formalin-fixed paraffin-embedded (FFPE; = 165, cohort 2 and = 139, cohort 3) specimens. We identified an 8-miRNA signature that significantly predicted recurrence-free interval (RFI) in the discovery ( = 0.002) and two independent publicly available datasets ( = 0.00006 and = 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), = 0.001; cohort 2: HR, 6.15 (3.33-11.35), = 0.001; and cohort 3: HR, 4.23 (2.26-7.92), = 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). 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. .

Integrated Analysis Identifies a Nine-microRNA Signature Biomarker for Diagnosis and Prognosis in Colorectal Cancer

“…A number of miRNAs have been detected to predict the survival of patients with CRC (Balaguer et al, 2011;Zhang et al, 2013;Hur et al, 2015;Vychytilova-Faltejskova et al, 2016;Pettit et al, 2017;Toiyama et al, 2017;Ji et al, 2018;Kandimalla et al, 2018). Particularly,, and miR-92a have proven to be correlated with the prognosis or therapeutic outcome of patients with CRC (Gaedcke et al, 2012;Kuo et al, 2012;Schee et al, 2012;Tsai et al, 2013;Yong et al, 2013;Kim et al, 2014;Pichler et al, 2014;Sun et al, 2014;Xue et al, 2014;Fu et al, 2018;Igder et al, 2019).…”

“…MicroRNAs (miRNAs) have been developed as novel biomarkers for early non-invasive or minimally invasive diagnosis of CRC (Gangadhar and Schilsky, 2010;Chen et al, 2015). Expression profiles of miRNAs in human colon cancer were utilized to determine the potential clinical relevance in several studies (Smits et al, 2011;Ma et al, 2012;Manceau et al, 2014;Wu et al, 2014;Kandimalla et al, 2018). A single model incorporating multiple biomarkers demonstrates improved performance and stability of prognostic value (Agesen et al, 2012;Marisa et al, 2013).…”

Adjuvant Therapy for Colon Cancer: Genes, Genes… and the Patient in the Center

“…See related article by Kandimalla et al,p. 3867 In this issue of Clinical Cancer Research, Kandimalla and colleagues present an 8-miRNA signature, validated in independent clinical cohorts, that reliably identifies stage II/III colon cancer patients' risk of relapse (1). This novel recurrence classifier, obtained from formalin-fixed paraffin-embedded specimens, outperformed some widely used prognostic clinicopathologic features and consensus molecular subtypes (CMS).…”

“…More recently, data generated from different genomic platforms have defined several molecular subtypes with clinical relevance in stage III colon cancer, such as the poor prognosis CMS4/CDX2 subset or the differential benefit from oxaliplatin between enterocyte and stem-like subtypes. However, as suggested by Kandimalla and colleagues (1), clinical translation of a gene expression panel-based approach may be challenging. Diverse clinical cohorts, different sources from clinical sample acquisition, stromal-derived intratumoral heterogeneity, experimental methodologic differences, different data processing algorithms, inaccuracy to reliably classify patient subtype from biopsy tissue, and spatial and temporal heterogeneity within primary tumor tissue remain major obstacles to its wide implementation.…”

Genome‐wide identification of a novel miRNA‐based signature to predict recurrence in patients with gastric cancer

“…The Cancer Genome Atlas (TCGA) provides a foundation for systematic analysis of large-scale miRNA expression data. Most recently, a comprehensive study based on the TCGA and other data platforms has successfully identified an 8-miRNA signature that significantly predicted recurrence-free interval in stage II and III colorectal cancer (Kandimalla et al, 2018). In the present study, we employed a large cohort of GC patients from the TCGA project and identified a novel miRNA-based signature for predicting recurrence-free survival (RFS) in patients with GC, followed by validation of its clinical significance in an independent clinical cohort.…”