MicroRNA-Target Identification: A Combinatorial In Silico Approach.

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA-target prediction.

Genetic Association Analysis Implicates Six MicroRNA-Related SNPs With Increased Risk of Breast Cancer in Australian Caucasian Women.

INTRODUCTION: Breast cancer (BC), a heterogeneous disease, features microRNA-related single nucleotide polymorphisms (miRSNPs) as underlying factors of BC development, thus providing targets for novel diagnostic and therapeutic strategies. This study investigated miRSNPs in BC susceptibility in Australian Caucasian women. PATIENTS AND METHODS: The study population included patients 33 to 80 years of age stratified by molecular subtypes of breast tumors (luminal A, 47.59%), stage (stage I, 36.96%), tumor-type (ductal, 44.95%), grading (intermediate, 35.52%), size (10.1-25 mm, 31.14%), and lymph node (sentinel negative, 38.93%). Sixty-five miRSNPs underwent allelic analysis in two independent case-control cohorts (GU-CCQ-BB, 377 cases and 521 controls; GRC-BC, 267 cases and 201 controls) using a MassARRAY platform. GU-CCQ-BB, GRC-BC, and the combined populations (BC-CA) (644 cases and 722 controls) underwent independent statistical analysis. RESULTS: In the GU-CCQ-BB population, miRSNPs TET2-rs7670522, ESR1-rs2046210, FGFR2-rs1219648, MIR210-rs1062099, HIF1A-rs2057482, and CASC16-rs4784227 were found to be associated with increased BC risk (P ≤ .05). Only ESR1-rs2046210 was also significantly associated (P ≤ .05) when replicated in the GRC-BC and BC-CA populations. No significant association was correlated with BC-clinical features (pathological types and ER/PR/HER2 status); however, MIR210-rs1062099 was found to be significantly associated (P ≤ .05) with age (>50 years) in the GU-CCQ-BB cohort. CONCLUSION: This is the first study to demonstrate the association of MIR210-rs1062099 and TET2-rs7670522 with increased BC risk. Additionally, four previously reported SNPs (ESR1-rs2046210, FGFR2-rs1219648, HIF1A-rs2057482, and CASC16-rs4784227) were confirmed as BC risk variants. Replication and functional studies in larger Caucasian cohorts are necessary to elucidate the role of these miRSNPS in the development of BC.

Regulatory Mechanisms of Epigenetic miRNA Relationships in Human Cancer and Potential as Therapeutic Targets.

Initiation and progression of cancer are under both genetic and epigenetic regulation. Epigenetic modifications including alterations in DNA methylation, RNA and histone modifications can lead to microRNA (miRNA) gene dysregulation and malignant cellular transformation and are hereditary and reversible. miRNAs are small non-coding RNAs which regulate the expression of specific target genes through degradation or inhibition of translation of the target mRNA. miRNAs can target epigenetic modifier enzymes involved in epigenetic modulation, establishing a trilateral regulatory "epi-miR-epi" feedback circuit. The intricate association between miRNAs and the epigenetic architecture is an important feature through which to monitor gene expression profiles in cancer. This review summarises the involvement of epigenetically regulated miRNAs and miRNA-mediated epigenetic modulations in various cancers. In addition, the application of bioinformatics tools to study these networks and the use of therapeutic miRNAs for the treatment of cancer are also reviewed. A comprehensive interpretation of these mechanisms and the interwoven bond between miRNAs and epigenetics is crucial for understanding how the human epigenome is maintained, how aberrant miRNA expression can contribute to tumorigenesis and how knowledge of these factors can be translated into diagnostic and therapeutic tool development.