Identification of dysregulated miRNAs in triple negative breast cancer: A meta‐analysis approach. Issue 7 (29th November 2018)

• Record Type: Journal Article
• Authors: Naorem, Leimarembi Devi; Muthaiyan, Mathavan; Venkatesan, Amouda
• Is Part Of: Journal of cellular physiology. Volume 234:Issue 7(2019:Jul.)
• Page Start: 11768
• Page End: 11779
• Publication Date: 2018-11-29
• Subjects: gene ontology (GO) -- miRNA -- Naïve Bayes -- robust rank aggregation (RRA) -- triple negative breast cancer (TNBC); Physiology -- Periodicals; Cell physiology -- Periodicals; 571.6
• DOI: 10.1002/jcp.27839
• Languages: English
• ISSNs: 0021-9541

Abstract

Abstract: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor clinical outcomes and lack of approved targeted therapy. Dysregulated microRNAs (miRNAs) have been considered a promising biomarker, which plays an important role in the tumorigenesis of human cancer. Due to the increase in miRNA profiling datasets of TNBC, a proper analysis is required for studying. Therefore, this study used meta‐analysis to amalgamate ten miRNA profiling studies of TNBC. By the robust rank aggregation method, metasignatures of six miRNAs (4 upregulated: hsa‐miR‐135b‐5p, hsa‐miR‐18a‐5p, hsa‐miR‐9‐5p and hsa‐miR‐522‐3p; 2 downregulated: hsa‐miR‐190b and hsa‐miR‐449a) were obtained. The gene ontology analysis revealed that target genes regulated by miRNAs were associated with processes like the regulation of transcription, DNA dependent, and signal transduction. Also, it is noted from the pathway analysis that signaling and cancer pathways were associated with the progression of TNBC. A Naïve Bayes‐based classifier built with miRNA signatures discriminates TNBC and non‐TNBC samples in test data set with high diagnostic sensitivity and specificity. From the analysis carried out by the study, it is suggested that the identified miRNAs are of great importance in improving the diagnostics and therapeutics for TNBC. Abstract : The study adopted meta‐analysis using the robust rank aggregation method to integrate miRNA expression profiling datasets of triple negative breast cancer. A meta‐signatures of six significantly dysregulated miRNAs (hsa‐miR‐135b‐5p, hsa‐miR‐18a‐5p, hsa‐miR‐9‐5p, hsa‐miR‐522‐3p, hsa‐miR‐190b, and hsa‐miR‐449a) were identified from different studies and have high prediction accuracy.