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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.

BACKGROUND Breast Cancer is the most common cancer type in women, second among the all cancers, and inherited with autosomal dominant pattern. The clinical diagnosis of BC relies on the published diagnostic criteria, and two genes have been identified as the main causative for breast cancer which are BRCA1 and BRCA2. OBJECTIVE We aimed to compare the index cases with the diagnostic features to describe the genotype/demographic information association in breast cancer. METHODS We performed mutational analyses for the BRCA1 and BRCA2 genes on 2475 individuals from collobrative centers across Turkey, whom 1444 of them were ascertained index cases. RESULTS We identified mutations in 17% (421/2475) of all individuals while its almost the same 16.6% (239/1444) in 1444 index cases. Mutations in BRCA1/BRCA2 genes were detected in 17.8% (131/737) of familial cases and 12% (78/549) of sporadic breast cancer, with 4.9% of mutations in the BRCA1 and 12% in the BRCA2. CONCLUSIONS Genotype variation and demographic information patterns were analyzed of all observed breast cancer findings in probands. We showed that patients with BRCA2 mutations have significantly been identified more than BRCA1 mutations. We also observed that sporadic breast cancer cases without familial history have less mutation positivity in BRCA1/BRCA2 genes, and the results were consistent with other studies in the Mediterranean region. On performing meta-analyses of our data and the other limited studies of the Mediterranean region in the literature, we found significant correlations that individual studies did not have sufficient power to conclude. Correlating genotypes with demographic information should facilitate the disease management of BC both the familial and non-familial cases.

Recent studies have focused on the early detection of ovarian cancer (OC) using tumor materials by liquid biopsy. The mechanisms of microRNAs (miRNAs) to impact OC and signaling pathways are still unknown. This study aims to reliably perform functional analysis of previously validated circulating miRNAs' target genes by using pathfindR. Also, overall survival and pathological stage analyses were evaluated with miRNAs' target genes which are common in the The Cancer Genome Atlas and GTEx datasets. Our previous studies have validated three downregulated miRNAs (hsa-miR-885-5p, hsa-miR-1909-5p, and hsa-let7d-3p) having a diagnostic value in OC patients' sera, with high-throughput techniques. The predicted target genes of these miRNAs were retrieved from the miRDB database (v6.0). Active-subnetwork-oriented Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by pathfindR using the target genes. Enrichment of KEGG pathways assessed by the analysis of pathfindR indicated that 24 pathways were related to the target genes. Ubiquitin-mediated proteolysis, spliceosome and Notch signaling pathway were the top three pathways with the lowest p-values (p < 0.001). Ninety-three common genes were found to be differentially expressed (p < 0.05) in the datasets. No significant genes were found to be significant in the analysis of overall survival analyses, but 24 genes were found to be significant with pathological stages analysis (p < 0.05). The findings of our study provide in-silico evidence that validated circulating miRNAs' target genes and enriched pathways are related to OC and have potential roles in theranostics applications. Further experimental investigations are required to validate our results which will ultimately provide a new perspective for translational applications in OC management.

Artificial intelligence provides modelling on machines by simulating the human brain using learning and decision-making abilities. Early diagnosis is highly effective in reducing mortality in cancer. This study aimed to combine cancer-associated risk factors including genetic variations and design an artificial intelligence system for risk assessment. Data from a total of 268 breast cancer patients have been analysed for 16 different risk factors including genetic variant classifications. In total, 61 BRCA1, 128 BRCA2 and 11 both BRCA1 and BRCA2 genes associated breast cancer patients’ data were used to train the system using Mamdani’s Fuzzy Inference Method and Feed-Forward Neural Network Method as the model softwares on MATLAB. Sixteen different tests were performed on twelve different subjects who had not been introduced to the system before. The rates for neural network were 99.9% for training success, 99.6% for validation success and 99.7% for test success. Despite neural network’s overall success was slightly higher than fuzzy logic accuracy, the results from developed systems were similar (99.9% and 95.5%, respectively). The developed models make predictions from a wider perspective using more risk factors including genetic variation data compared with similar studies in the literature. Overall, this artificial intelligence models present promising results for BRCA variations’ risk assessment in breast cancers as well as a unique tool for personalized medicine software.

Aim: Dietary miRNAs in foods were recently suggested to be absorbed into the human circulation and engage in human gene regulation. This started a debate on their possible impacts on human diseases which need further investigation. In this study, we aimed to identify the putative functions and possible implications of selected Xeno-miRs in human diseases by using bioinformatic tools. Methods: Seventy-five human absorbable Xeno-miR candidates were selected from literature and narrowed down the list to miRNAs that share sequence homologies with human miRNAs. Sixteen distinct Xeno-miRs of animal species (cow, pig, chicken) were identified to have homologs in human and they were subsequently analyzed with target prediction, functional and pathway analysis tools. Results and Conclusion: Thirteen human genes were common targets of the miRNA sets grouped by species and shown evidence of associations with various cancer categories, specifically in large intestine adenocarcinoma by Ingenuity Pathway Analysis. miRNA functional enrichment analyses also highlighted the putative involvements of the dietary miRNAs in cancer pathways. Our effort provides "in silico" evidence for implications of animal-derived dietary miRNAs in cancer-associated pathways, and this shed on light the necessities of future translational research design to investigate the roles of dietary Xeno-miRs in cancer pathophysiology and nutrition-based interventions towards cancer management.

Coronary artery disease (CAD) is still the preliminary cause of mortality and morbidity in the developed world. Identification of novel predictive and therapeutic biomarkers is crucial for accurate diagnosis, prognosis and treatment of the CAD. The aim of this study was to detect novel candidate miRNA biomarker that may be used in the management of CAD. We performed miRNA profiling in whole blood samples of angiographically confirmed Turkish men with CAD and non-CAD controls with insignificant coronary stenosis. Validation of microarray results was performed by qRT-PCR in a larger cohort of 62 samples. We subsequently assessed the diagnostic value of the miRNA and correlations of miRNA with clinical parameters. miRNA-target identification and network analyses were conducted by Ingenuity Pathway Analysis (IPA) software. Hsa-miR-584-5p was one of the top significantly dysregulated miRNA observed in miRNA microarray. Men-specific down-regulation (p = 0.040) of hsa-miR-584-5p was confirmed by qRT-PCR. ROC curve analysis highlighted the potential diagnostic value of hsa-miR-584-5p with a power area under the curve (AUC) of 0.714 and 0.643 in men and in total sample, respectively. The expression levels of hsa-miR-584-5p showed inverse correlation with stenosis and Gensini scores. IPA revealed CDH13 as the only CAD related predicted target for the miRNA with biological evidence of its involvement in CAD. This study suggests that hsa-miR-584-5p, known to be tumor suppressor miRNA, as a candidate biomarker for CAD and highlighted its putative role in the CAD pathogenesis. The validation of results in larger samples incorporating functional studies warrant further research.

Çevik, Nazife (Arel Author), PurposeOvarian 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.MethodsIn 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((R)) (v.11.4.0.8).ResultsThe expression of hsa-miR-1273g-3p was found to be significantly down-regulated by t test Bonferroni FWER corrected p2, 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.ConclusionThis 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.

Aim of the Study: The purpose of this study was to identify specific circulating microRNAs (miRNAs) and investigate expression level of their target genes for evaluation of pathogenesis of epithelial ovarian cancer (EOC). Materials and Methods: In this study, we have studied on EOC patients' serum and whole blood, healthy control (HC) serum, and whole blood samples. Sixteen serum samples were collected to compare miRNA expression analysis through microarray. According to microarray results, one of the dysregulated miRNA in serum, hsa-let-7d-3p, was validated by RT-qPCR for discriminate two groups. The hsa-let-7d-3p is one of the tumor suppressive let-7d family members. Let-7d is downregulated in numerous types of cancer, including ovarian cancer and directly targets various oncogenes. We analyzed the let-7d targets, which are High Mobility Group A2 (HMGA2) and (Kirsten Rat Sarcoma Viral Oncogene Homolog), as the oncogenes that are associated with EOC. The relation between target genes of hsa-let-7d-3p and EOC has been examined by Pathway Studio. Twenty serum and whole blood samples collected to analyze expression level of target genes were analyzed by real-time PCR. Results: 31 significantly dysregulated miRNAs were identified by microarray in serum. Hsa-let-7d-3p has been selected for the validation, according to P-value and dysregulated level. RT-qPCR results showed that hsa-let-7d-3p could discriminate EOC patients from HC (P = 0.0484, AUC = 0.7). Furthermore, we identified hsa-let-7d-3p's target genes (HMGA2, KRAS) by bioinformatic analysis. The expression level of genes could discriminate patients with EOC from HC, with a power area under the ROC curves (AUC) of 62 and 64.2, respectively. Conclusion: HMGA2 and KRAS could be translationally downregulated by the hsa-let-7d-3p, and the loss of hsa-let-7d-3p expression led to the progression of EOC related to the tumorigenesis, invasion, and metastasis.