A panel of eight microRNAs is a good predictive parameter for triple-negative breast cancer relapse

• Published in: Theranostics Vol. 10; no. 19; pp. 8771 - 8789
• Main Authors: Hong, Hsiao-Chin, Chuang, Cheng-Hsun, Huang, Wei-Chih, Weng, Shun-Long, Chen, Chia-Hung, Chang, Kuang-Hsin, Liao, Kuang-Wen, Huang, Hsien-Da
• Format: Journal Article
• Language: English
• Published: Australia Ivyspring International Publisher Pty Ltd 01.01.2020; Ivyspring International Publisher
• Subjects: Adult; Bioinformatics; Biomarkers; Biomarkers, Tumor - genetics; Breast cancer; Cancer therapies; Cell Line, Tumor; Chemotherapy; Datasets; Disease; Female; Gene expression; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic; Humans; Logistic Models; Metastasis; MicroRNAs; MicroRNAs - genetics; Middle Aged; Neoplasm Recurrence, Local - diagnosis; Neoplasm Recurrence, Local - genetics; Precision Medicine; Prognosis; Research Paper; Signal transduction; Software; Triple Negative Breast Neoplasms - diagnosis; Triple Negative Breast Neoplasms - genetics; miRNA signature; prediction; triple-negative breast cancer; relapse; prognosis
• ISSN: 1838-7640; 1838-7640
• DOI: 10.7150/thno.46142

Triple-negative breast cancer (TNBC), which has the highest recurrence rate and shortest survival time of all breast cancers, is in urgent need of a risk assessment method to determine an accurate treatment course. Recently, miRNA expression patterns have been identified as potential biomarkers for diagnosis, prognosis, and personalized therapy. Here, we investigate a combination of candidate miRNAs as a clinically applicable signature that can precisely predict relapse in TNBC patients after surgery. Four total cohorts of training (TCGA_TNBC and GEOD-40525) and validation (GSE40049 and GSE19783) datasets were analyzed with logistic regression and Gaussian mixture analyses. We established a miRNA signature risk model and identified an 8-miRNA signature for the prediction of TNBC relapse. The miRNA signature risk model identified ten candidate miRNAs in the training set. By combining 8 of the 10 miRNAs (miR-139-5p, miR-10b-5p, miR-486-5p, miR-455-3p, miR-107, miR-146b-5p, miR-324-5p and miR-20a-5p), an accurate predictive model of relapse in TNBC patients was established and was highly correlated with prognosis (AUC of 0.80). Subsequently, this 8-miRNA signature prognosticated relapse in the two validation sets with AUCs of 0.89 and 0.90. The 8-miRNA signature predictive model may help clinicians provide a prognosis for TNBC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.