Identifying functional cancer-specific miRNA–mRNA interactions in testicular germ cell tumor. (7th September 2016)

• Record Type: Journal Article
• Authors: Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali
• Is Part Of: Journal of theoretical biology. Volume 404(2016)
• Page Start: 82
• Page End: 96
• Publication Date: 2016-09-07
• Subjects: MiRNA–mRNA interaction -- Testicular germ cell tumor -- Gene ontology -- KEGG pathways -- Disease ontology; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2016.05.026
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA–mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA–mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA–mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA–mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA–mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Abstract : Highlights: This study investigates functional cancer-specific miRNA–mRNA interactions in TGCT. A new algorithm is proposed for identifying functional miRNA–mRNA interactions. The algorithm includes several steps to refine sequence-based interactions. Identified interactions are then assessed for functional enrichment in TGCT. 13 candidate functional TGCT interactions are nominated for follow-up experiments.