Development and Validation of a 6-miRNA Prognostic Signature in Spinal Chordoma

Wei Huang; Yi-Guo Yan; Wen-Jun Wang; Zhi-Hua Ouyang; Xue-Lin Li; Tao-Lan Zhang; Xiao-Bin Wang; Bing Wang; Guo-Hua Lv; Jing Li; Ming-Xiang Zou

doi:10.3389/fonc.2020.556902

Development and Validation of a 6-miRNA Prognostic Signature in Spinal Chordoma

Front Oncol. 2020 Oct 27:10:556902. doi: 10.3389/fonc.2020.556902. eCollection 2020.

Authors

Wei Huang^{1

2}, Yi-Guo Yan¹, Wen-Jun Wang¹, Zhi-Hua Ouyang¹, Xue-Lin Li¹, Tao-Lan Zhang³, Xiao-Bin Wang⁴, Bing Wang⁴, Guo-Hua Lv⁴, Jing Li⁴, Ming-Xiang Zou^{1

4}

Affiliations

¹ Department of Spine Surgery, The First Affiliated Hospital, University of South China, Hengyang, China.
² Health Management Center, The First Affiliated Hospital, University of South China, Hengyang, China.
³ Department of Cancer Biology, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States.
⁴ Department of Spine Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.

Abstract

Background: Published data have suggested a critical role for microRNA (miRNA) expression in chordoma progression. However, most of these studies focus on single miRNA and no multi-miRNA prognostic signature has been currently established for chordoma. In this study, we sought to develop and validate a 6-miRNA risk score (miRscore) model for survival prediction.

Methods: Medline, Embase, and Google scholar searches (from inception to July 20, 2018) were conducted to identify candidate miRNAs with prognostic value as per predefined criteria. Quantitative RT-PCR was used to measure miRNA levels in 114 spinal chordoma (54 in the training and 60 in the validation cohort) and 20 control specimens. Subsequently, the miRscore was built based on miRNAs data.

Results: Literature searches identified six prognostic miRNAs (miR-574-3p, miR-1237-3p, miR-140-3p, miR-1, miR-155, and miR-1290) with differential expression in tumor tissues. Bioinformatical analysis revealed an important regulatory role for miR-574-3p/EGFR signaling in chordoma and showed that the target genes of these prognostic miRNAs were mainly enriched in transcription regulation, protein binding and cancer-related pathways. In both cohorts, the miRscore was associated with surrounding muscle invasion by tumor and/or other aggressive features. The miRscore model well predicted local recurrence-free survival and overall survival, which remained after adjusting for other relevant covariates. Further time-dependent receiver operating characteristics analysis in the two cohorts found that the miRscore classifier had stronger prognostic power than known clinical predictors and improved the ability of Enneking staging to predict outcomes. Importantly, recursive-partitioning analysis of both samples combined separated patients into four prognostically distinct risk subgroups for recurrence and survival (both P < 0.001).

Conclusions: These data suggest the miRscore as a useful prognostic stratification tool in spinal chordoma and may represent an important step toward future personalized treatment of patients.

Keywords: decision tree; miRNA; miRNA risk score; miRNA signature; prognostic biomarkers; spinal chordoma; survival analysis.