Genome-wide methylation profiles in monozygotic twins with discordance for ovarian carcinoma

Ovarian cancer is a disease that is generally diagnosed at an advanced stage, and has poor survival. Monozygotic (MZ) twins are considered to be good research models for investigating the epigenetic changes associated with diseases. In the present study, the involvement of epigenetic mechanisms in ovarian cancer etiology were evaluated using the MZ twin model. Whole-genome methylation patterns were investigated in a BRCA1 gene mutation-carrying family comprising MZ twins, only one of whom had ovarian cancer, and other healthy siblings. Whole-genome methylation patterns were assessed in peripheral blood DNA using Infinium MethylationEPIC BeadChips on an Illumina iScan device. The hypermethylated and hypomethylated genes were detected between cases and controls in four different comparison groups in order to evaluate the differences in methylation levels according to cancer diagnosis and BRCA mutation status. The obtained results showed that the differential methylations in 12 different genes, namely PR/SET domain 6, cytochrome B5 reductase 4, ZNF714, OR52M1, SEMA4D, CHD1L, CAPZB, clustered mitochondria homolog, RB-binding protein 7, chromatin repair factor, ankyrin repeat domain 23, RIB43A domain with coiled-coils 1 and C6orf227, were associated with ovarian cancer. Biological functional analysis of the genes detected in the study using the PANTHER classification system revealed that they have roles in biological processes including 'biologic adhesion', 'regulation', 'cellular components organization', 'biogenesis', 'immune system functioning', 'metabolic functioning' and 'localization'. Overall, the present study suggested that epigenetic differences, such as methylation status, could be used as a non-invasive biological markers for the early diagnosis and follow-up of ovarian cancer

miRNA expression profile changes in the peripheral blood of monozygotic discordant twins for epithelial ovarian carcinoma: potential new biomarkers for early diagnosis and prognosis of ovarian carcinoma

Background Ovarian cancer is the second most common gynecologic cancer with high mortality rate and generally diagnosed in advanced stages. The 5-year disease-free survival is below 40%. MicroRNAs, subset of the non-coding RNA molecules, regulate the translation in post transcriptional level by binding to specific mRNAs to promote or degrade the target oncogenes or tumor suppressor genes. Abnormal expression of miRNAs were found in numerous human cancer, including ovarian cancer. Investigating the miRNAs derived from the peripheral blood samples can be used as a marker in the diagnose, treatment and prognosis of ovarian cancer. We aimed to find biological markers for early diagnosis of ovarian cancer by investigating BRCA1 gene mutation carrier monozygotic discordant twins and their high risk healthy family individual's miRNAs. Methods The study was conducted on monozygotic twins discordant for ovarian cancer, and the liquid biopsy exploration of miRNAs was performed on mononuclear cells that were isolated from the peripheral blood samples. The miRNA expression profile changes in the study were found by using microarray analysis. miRNA isolation procedure performed from the lymphocyte in accordance with the kit protocol. The presence and quality of the isolated miRNAs screened by electrophoresis. Raw data logarithmic analysis was studied by identifying the threshold, normalization, correlation, mean and median values. Target proteins were detected for each miRNA by using different algorithms. Results After the comparison of monozygotic discordant twins for epithelial ovarian carcinoma upregulation of the 4 miRNAs, miR-6131, miR-1305, miR-197-3p, miR-3651 and downregulation of 4 miRNAs, miR-3135b, miR-4430, miR-664b-5p, miR-766-3p were found statically significant. Conclusions The detected 99 miRNAs out of 2549 miRNAs might be used in the clinic as new biological indicators in the diagnosis and follow up of epithelial ovarian cancer with complementary studies. ThemiRNA expressionprofiles were identified to be statistically significant in the evaluation of ovarian cancer etiology, BRCA1 mutation status, and ovarian cancer risk in accordance with the obtained data. There is a need for validation of the miRNAs which were particularly detected between monozygotic twins and its association with ovarian cancer was emphasized in our study in wider cohorts including ovarian cancer patients, and healthy individuals

New Approach for Risk Estimation Algorithms of BRCA1/2 Negativeness Detection with Modelling Supervised Machine Learning Techniques

BRCA1/2 gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the BRCA1/2 gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to develop an algorithm considering all the clinical, demographic, and genetic features of patients for identifying the BRCA1/2 negativity in the present study. An experimental dataset was created with the collection of the all clinical, demographic, and genetic features of breast cancer patients for 20 years. This dataset consisted of 125 features of 2070 high-risk breast cancer patients. All data were numeralized and normalized for detection of the BRCA1/2 negativity in the machine learning algorithm. The performance of the algorithm was identified by studying the machine learning model with the test data. k nearest neighbours (KNN) and decision tree (DT) accuracy rates of 9 features involving Dataset 2 were found to be the most effective. The removal of the unnecessary data in the dataset by reducing the number of features was shown to increase the accuracy rate of algorithm compared with the DT. BRCA1/2 negativity was identified without performing the BRCA1/2 gene test with 92.88% accuracy within minutes in high-risk breast cancer patients with this algorithm, and the test associated result waiting stress, time, and money loss were prevented. That algorithm is suggested be useful in fast performing of the treatment plans of patients and accurately in addition to speeding up the clinical practice

The Association of Pancreatic Cancer and PALB2 Gene Mutations in the Turkish Population

OBJECTIV

Downregulation of Forkhead Transcription Factor (FOXO3a) Contributes to Tumorigenesis of Acute Myeloid Leukemia and Chronic Myeloid Leukemia

The expression of the FOXO3a gene, and its role in acute myeloid leukemia and chronic myeloid leukemia were investigated in the present study. We analyzed 101 patients diagnosed with AML, and CML, and 34 healthy individuals. The cDNAs obtained from the blood samples of patients, and healthy controls were analyzed by the Real-Time PCR using specific primers, and probes for the FOXO3a and ACTB genes. A 50-fold decrease in FOXO3a expression levels was detected in CML patients, and 8-fold decrease was detected in AML patients compared with the levels in the healthy controls. Significant difference was detected between the patients, and healthy controls (p= 0.000). However, there was no statistically significant difference between the CML and AML patient groups for FOXO3a expression level. The decrease in FOXO3a gene expression in all CML (51/51), and AML patients (50/50) was remarkable. The FOXO3a gene expression was downregulated in 91.8% (124/135) of all individuals included in the study. The present study might be an important report on emphasizing the expression profiles of FOXO3a gene in AML, and CML patents. Whether the FOXO3a gene is a valuable biomarker for early diagnosis and prognosis in CML and AML patients need to be investigated in larger study groups

New Approach for Risk Estimation Algorithms of BRCA1/2 Negativeness Detection with Modelling Supervised Machine Learning Techniques

BRCA1/2 gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the BRCA1/2 gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to develop an algorithm considering all the clinical, demographic, and genetic features of patients for identifying the BRCA1/2 negativity in the present study. An experimental dataset was created with the collection of the all clinical, demographic, and genetic features of breast cancer patients for 20 years. This dataset consisted of 125 features of 2070 high-risk breast cancer patients. All data were numeralized and normalized for detection of the BRCA1/2 negativity in the machine learning algorithm. The performance of the algorithm was identified by studying the machine learning model with the test data. k nearest neighbours (KNN) and decision tree (DT) accuracy rates of 9 features involving Dataset 2 were found to be the most effective. The removal of the unnecessary data in the dataset by reducing the number of features was shown to increase the accuracy rate of algorithm compared with the DT. BRCA1/2 negativity was identified without performing the BRCA1/2 gene test with 92.88% accuracy within minutes in high-risk breast cancer patients with this algorithm, and the test associated result waiting stress, time, and money loss were prevented. That algorithm is suggested be useful in fast performing of the treatment plans of patients and accurately in addition to speeding up the clinical practice

RB1 GENE MUTATIONS IN TURKISH PATIENTS WITH RETINOBLASTOMA

RB1 GENE MUTATIONS IN TURKISH PATIENTS WITH RETINOBLASTOM

FGFR4 c.1162G > A (p.Gly388Arg) Polymorphism Analysis in Turkish Patients with Retinoblastoma

Purpose. Various molecular variations are known to result in different gene variants in the FGFR4 gene, known for its oncogenic transformation activity. The goal of this study was to investigate the FGFR4 p.Gly388Arg variant that plays role in the progression of cancer and retinal growth and may be an effective candidate variant in the Turkish population in retinoblastoma patients with no RB1 gene mutation. Methods. Using the Sanger sequencing methods, the FGFR4 p.Gly388Arg variant was bidirectionally sequenced in 49 patients with non-RB1 gene mutation in retinoblastoma patients and 13 healthy first-degree relatives and 146 individuals matched by sex and age in the control group. Results. In Turkish population-specific study, the FGFR4 p.Gly388Arg variant was found in 27 (55.1 percent) of 49 patients; mutation was found in 7 (53.8 percent) of these patients’ 13 healthy relatives screened. When FGFR4 p.Gly388Arg mutation status is evaluated in terms of 146 healthy controls, in 70 (47.9 percent) individuals, mutation was observed. Our analysis showed that the FGFR4 p.Gly388Arg allele frequency, which according to different databases is seen as 30 percent in the general population, is 50 percent common in the Turkish population. Conclusions. In patients with advanced retinoblastoma who were diagnosed with retinoblastoma prior to 24 months, the FGFR4 p.Gly388Arg allele was found to be significantly higher. As a result, these results indicate that the polymorphism of FGFR4 p.Gly388Arg may play a role in both the development of tumors and the progression of aggressive tumors

FGFR4 c.1162G > A (p.Gly388Arg) Polymorphism Analysis in Turkish Patients with Retinoblastoma

Purpose. Various molecular variations are known to result in different gene variants in the FGFR4 gene, known for its oncogenic transformation activity. The goal of this study was to investigate the FGFR4 p.Gly388Arg variant that plays role in the progression of cancer and retinal growth and may be an effective candidate variant in the Turkish population in retinoblastoma patients with no RB1 gene mutation. Methods. Using the Sanger sequencing methods, the FGFR4 p.Gly388Arg variant was bidirectionally sequenced in 49 patients with non-RB1 gene mutation in retinoblastoma patients and 13 healthy first-degree relatives and 146 individuals matched by sex and age in the control group. Results. In Turkish population-specific study, the FGFR4 p.Gly388Arg variant was found in 27 (55.1 percent) of 49 patients; mutation was found in 7 (53.8 percent) of these patients' 13 healthy relatives screened. When FGFR4 p.Gly388Arg mutation status is evaluated in terms of 146 healthy controls, in 70 (47.9 percent) individuals, mutation was observed. Our analysis showed that the FGFR4 p.Gly388Arg allele frequency, which according to different databases is seen as 30 percent in the general population, is 50 percent common in the Turkish population. Conclusions. In patients with advanced retinoblastoma who were diagnosed with retinoblastoma prior to 24 months, the FGFR4 p.Gly388Arg allele was found to be significantly higher. As a result, these results indicate that the polymorphism of FGFR4 p.Gly388Arg may play a role in both the development of tumors and the progression of aggressive tumors