A Multicenter Study of Genotype Variation/Demographic Patterns in 2475 Individuals Including 1444 Cases With Breast Cancer in Turkey.

Objective: Breast cancer (BC) is the most common cancer type in women and may be inherited, mostly in an autosomal dominant pattern. The clinical diagnosis of BC relies on the published diagnostic criteria, and analysis of two genes, BRCA1 and BRCA2, which are strongly associated with BC, are included in these criteria. The aim of this study was to compare BC index cases with non-BC individuals in terms of genotype and diagnostic features to investigate the genotype/demographic information association. Materials and Methods: Mutational analyses for the BRCA1/BRCA2 genes was performed in 2475 individuals between 2013-2022 from collaborative centers across Turkey, of whom 1444 with BC were designated as index cases. Results: Overall, mutations were identified in 17% (421/2475), while the percentage of mutation carriers in cases of BC was similar, 16.6% (239/1444). BRCA1/BRCA2 gene mutations were detected in 17.8% (131/737) of familial cases and 12% (78/549) of sporadic cases. Mutations in BRCA1 were found in 4.9%, whereas 12% were in BRCA2 (p<0.05). Meta-analyses were performed to compare these results with other studies of Mediterranean-region populations. Conclusion: Patients with BRCA2 mutations were significantly more common than those with BRCA1 mutations. In sporadic cases, there was a lower proportion with BRCA1/BRCA2 variants, as expected, and these results were consistent with the data of Mediterranean-region populations. However, the present study, because of the large sample size, revealed more robust findings than previous studies. These findings may be helpful in facilitating the clinical management of BC for both familial and non-familial cases.

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.

Investigation of putative roles of smoking-associated salivary microbiome alterations on carcinogenesis by integrative in silico analysis.

Growing evidence suggests that cigarette smoking alters the salivary microbiome composition and affects the risk of various complex diseases including cancer. However, the potential role of the smoking-associated microbiome in cancer development remains unexplained. Here, the putative roles of smoking-related microbiome alterations in carcinogenesis were investigated by in silico analysis and suggested evidence can be further explored by experimental methodologies. The Disbiome database was used to extract smoking-associated microbial taxa in saliva and taxon set enrichment analysis (TSEA) was conducted to identify the gene sets associated with extracted microbial taxa. We further analyzed the expression profiles of identified genes by using RNA-sequencing data from TCGA and GTEx projects. Associations of the genes with smoking-related phenotypes in cancer datasets were analyzed to prioritize genes for their interplay between smoking-related microbiome and carcinogenesis. Thirty-eight microbial taxa associated with smoking were included in the TSEA and this revealed sixteen genes that were significantly associated with smoking-associated microbial taxa. All genes were found to be differentially expressed in at least one cancer dataset, yet the ELF3 and CTSH were the most common differentially expressed genes giving significant results for several cancer types. Moreover, C2CD3, CTSH, DSC3, ELF3, RHOT2, and WSB2 showed statistically significant associations with smoking-related phenotypes in cancer datasets. This study provides in silico evidence for the potential roles of the salivary microbiome on carcinogenesis. The results shed light on the importance of smoking cessation strategies for cancer management and interventions to stratify smokers for their risk of smoking-induced carcinogenesis.

Different perspectives on translational genomics in personalized medicine

Personalized medicine is a relatively new and interesting concept in the medical and healthcare industries. New approaches in current research have supported the search for biomarkers, based on the genomic, epigenomic and proteomic profile of individuals, using new technological tools. This perspective involves the potential to determine optimal medical interventions and provide the optimal benefit-risk balance for treatment, whilst it also takes a patient's personal situation into consideration. Translational genomics, a subfield of personalized medicine, is changing medical practice, by facilitating clinical or non-clinical screening tests, informing diagnoses and therapeutics, and routinely offering personalized health-risk assessments and personalized treatments. Further research into translational genomics will play a critical role in creating a new approach to cancer, pharmacogenomics, and women's health. Our current knowledge may be used to develop new solutions that can be used to minimize, improve, manage, and delay the symptoms of diseases in real-time and maintain a healthy lifestyle. In this review, we define and discuss the current status of translational genomics in some special areas including integration into research and health care.

Integrated bioinformatics analysis of validated and circulating miRNAs in ovarian cancer.

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 hsalet7d-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.

Germline landscape of BRCAs by 7-site collaborations as a BRCA consortium in Turkey.

BRCA1/2 mutations play a significant role in cancer pathogenesis and predisposition particularly in breast, ovarian and prostate cancers. Thus, germline analysis of BRCA1 and BRCA2 is essential for clinical management strategies aiming at the identification of recurrent and novel mutations that could be used as a first screening approach. We analyzed germline variants of BRCA1/2 genes for 2168 individuals who had cancer diagnosis or high risk assessment due to BRCAs related cancers, referred to 10 health care centers distributed across 7 regions covering the Turkish landscape. Overall, 68 and 157 distinct mutations were identified in BRCA1 and BRCA2, respectively. Twenty-two novel variants were reported from both genes while BRCA2 showed higher mutational heterogeneity. We herein report the collective data as BRCA Turkish consortium that confirm the molecular heterogeneity in BRCAs among Turkish population, and also as the first study presenting the both geographical, demographical and gene based landscape of all recurrent and novel mutations which some might be a founder effect in comparison to global databases. This wider perspective leads to the most accurate variant interpretations which pave the way for the more precise and efficient management affecting the clinical and molecular aspects.

BRCA Variations Risk Assessment in Breast Cancers Using Different Artificial Intelligence Models.

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.

In silico identification of putative roles of food-derived xeno-mirs on diet-associated cancer.

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.

Hsa-miR-584-5p as a novel candidate biomarker in Turkish men with severe coronary artery disease.

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.

Regulation of HMGA2 and KRAS genes in epithelial ovarian cancer by miRNA hsa-let-7d-3p.

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.

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.