Metabolic pathways of potential miRNA biomarkers derived from liquid biopsy in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is the type of OC with the highest mortality rate. Due to the asymptomatic nature of the disease and few available diagnostic tests, it is mostly diagnosed at the advanced stage. Therefore, the present study aimed to discover predictive and/or early diagnostic novel circulating microRNAs (miRNAs or miRs) for EOC. Firstly, microarray analysis of miRNA expression levels was performed on 32 samples of female individuals: Eight plasma samples from patients with pathologically confirmed EOC (mean age, 45 (30-54) years), eight plasma samples from matched healthy individuals (HIs) (mean age, 44 (30-65) years), eight EOC tissue samples (mean age, 45 (30-54) years) and eight benign ovarian (mean age, 35 (17-70) years) neoplastic tissue samples A total of 31 significantly dysregulated miRNAs in serum and three miRNAs in tissue were identified by microarray. The results were validated using reverse transcription-quantitative PCR on samples from 10 patients with pathologically confirmed EOC (mean age, 47(30-54) years), 10 matched His (mean age, 40(26-65) years], 10 EOC tissue samples (mean age, 47(30-54) years) and 10 benign ovarian neoplastic tissue samples (mean age, 40(17-70) years). The 'Kyoto Encyclopedia of Genes and Genomes' (KEGG) database was used for target gene and pathway analysis. A total of three miRNAs from EOC serum (hsa-miR-1909-5p, hsa-miR-885-5p and hsa-let-7d-3p) and one microRNA from tissue samples (hsa-miR-200c-3p) were validated as significant to distinguish patients with EOC from HIs. KEGG pathway enrichment analysis showed seven significant pathways, which included 'prion diseases', 'proteoglycans in cancer', 'oxytocin signaling pathway', 'hippo signaling pathway', 'adrenergic signaling in cardiomyocytes', 'oocyte meiosis' and 'thyroid hormone signaling pathway', in which the validated miRNAs served a role. This supports the hypothesis that four validated miRNAs, have the potential to be a biomarker of EOC diagnosis and target for treatment.

The role of the serum exosomal and endometrial microRNAs in recurrent implantation failure.

OBJECTIVE: It has been identified that endometrium specific microRNAs have different expression levels in endometrial tissues and maternal serum during endometrial cycle. The aim of this study was to analyze microRNA expression levels in recurrent implantation failure patients and healthy controls endometrial samples for enlightening the aetiopathogenesis of the disease. The second aim was to search for a potential noninvasive molecular biomarker in early diagnosis and treatment of Recurrent Implantation Failure (RIF) patients. METHODS: Endometrium and serum samples in two different phases (PP; proliferative phase and SP; secretory phase) from the same cases (RIF; n = 12 and Control; n = 8) were obtained. The expression levels of the microRNA by RT-qPCR method were measured. The expression levels of the healthy controls and study group were compared. Lastly performed target genes analysis of significantly dysregulated miRNA by target analyze databases for obtained related biological pathways. RESULTS: This study showed that has-miR-145, has-miR-23b, has-miR-31 and has-miR-30b were significantly up-regulated in PP and down-regulated in SP endometrium samples. In serum samples, has-miR-145 and hsa-miR-23b were significantly down-regulated in both of PP and SP. Target gene and pathway analysis for dysregulated miRNAs identified important, validated and predicted genes for the implantation process. CONCLUSIONS: This study is the first study to obtain endometrium and serum samples in two different phases from the same cases and measure the candidate miRNAs expression. Our finding suggests that expression level of four candidate miRNAs may be involved in RIF development in women. Furthermore, these miRNAs can be potential biomarker for early diagnosis of RIF patients.

Potential biomarker of circulating hsa-miR-1273g-3p level for detection of recurrent epithelial ovarian cancer.

PURPOSE: Ovarian cancer (OC) is first gynaecologic cancer that causes women death and epithelial ovarian cancer (EOC) is the most lethal ovarian cancer type. While treatment is commonly successful, some cases (10-20%) show resistance to chemotherapy which is followed by recurrence. MicroRNA (miRNA) based diagnosis methods are slightly important for recurrent ovarian cancer diagnosis. We aimed to detect novel circulating miRNAs to be used as an early diagnosis and prediction tools for recurrent EOC. METHODS: In this study, recurrent EOC serum samples and healthy control serum samples were compared for miRNA expression analysis by microarray. Microarray results were analyzed by bioinformatics tools and differentially expressed hsa-miR-1273g-3p was obtained. After microarray analysis, differentially expressed hsa-miR-1273g-3p was validated by Real-Time PCR (RT-qPCR). The relation between target genes of hsa-miR-1273g-3p and ovarian cancer were examined by Pathway Studio® (v.11.4.0.8). RESULTS: The expression of hsa-miR-1273g-3p was found to be significantly down-regulated by t test Bonferroni FWER corrected p < 0.05 and fold change > 2, in recurrence EOC compare with healthy controls groups. The RT-qPCR results confirmed that relative expressions of the serum hsa-miR-1273g-3p were significantly down-regulated in patients with recurrent EOC (p = 0.0275). Serum hsa-miR-1273g-3p levels could discriminate patients with recurrent EOC from healthy controls, with a power area under the curve (AUC) of 0.7. CONCLUSION: This study suggested that hsa-miR-1273g-3p plays a significant role in regulation of related genes, which are TNF-alfa, COL1A1, MMP-2, MMP-9, with recurrent EOC outcome. hsa-miR-1273g-3p may be used as a prognostic marker for recurrent EOC after chemotherapy.

Analysis of shared miRNAs of different species using ensemble CCA and genetic distance.

MicroRNA is a type of single stranded RNA molecule and has an important role for gene expression. Although there have been a number of computational methodologies in bioinformatics research for miRNA classification and target prediction tasks, analysis of shared miRNAs among different species has not yet been addressed. In this article, we analyzed miRNAs that have the same name and function but have different sequences and belong to different (but closely related) species which are constructed from the online miRBase database. We used sequence-driven features and performed the standard and the ensemble versions of Canonical Correlation Analysis (CCA). However, due to its sensitivity to noise and outliers, we extended it using an ensemble approach. Using linear combinations of dimer features, the proposed Ensemble CCA (ECCA) method has identified higher test-set-correlations than CCA. Moreover, our analysis reveals that the Redundancy Index of ECCA applied to a pair of species has correlation with their genetic distance.