Evaluation of MicroRNA Expression Profiles That May Predict Recurrence of Localized Stage I Non–Small Cell Lung Cancer after Surgical Resection

Authors:
Publisher website
Google Scholar
Abstract
Prognostic markers that can predict the relapse of localized non–small cell lung cancer (NSCLC) have yet to be defined. We surveyed expression profiles of microRNA (miRNA) in stage I NSCLC to identify patterns that might predict recurrence after surgical resection of this common deadly cancer. Small RNAs extracted from formalin-fixed and paraffin-embedded tissues were hybridized to locked nucleic acid probes against 752 human miRNAs (representing 82% of the miRNAs in the miRBase 13.0 database) to obtain expression profiles for 37 cases with recurrence and 40 cases without recurrence (with clinical follow-up for at least 32 months). Differential expression between the two case groups was detected for 49% of the miRNAs (Wilcoxon rank sum test; P < 0.01). The performance of expression profiles at differentiating the two case groups was assessed by leave-one-out and Monte Carlo cross-validations. In leave-one-out cross-validation using support vector machines- or top-scoring gene pair classifier methods, which looked for six- or two-miRNA-based classifiers, the identified miRNA expression pattern predicted recurrence with an accuracy of 70% and 83%, and hazard ratio of 3.6 [95% confidence interval (95% CI), 1.8–7.1] and 9.0 (95% CI, 4.4–18.2), respectively. Mean accuracy in Monte Carlo cross-validation using 1,000 random 60–17 splits was 69% (95% CI, 68–70) and 72% (95% CI, 71–72), respectively. The specific miRNAs mir-200b*, mir-30c-1*, mir-510, mir-630, mir-657, and mir-146b-3p and mir-124*, mir-585, and mir-708, respectively, represented most commonly among the 1,000 classifiers identified in Monte Carlo cross-validation by the two methods. MiRNAs mir-488, mir-503, and mir-647 were identified as potential reference miRNAs for future studies, based on the stability of their expression patterns across the 77 cases and the two case-groups. Our findings reinforce efforts to profile miRNA expression patterns for better prognostication of stage I NSCLC. Cancer Res; 70(1); 36–45

This publication has 36 references indexed in Scilit: