17 research outputs found
Identification of candidate genes in a family with cancer overload by whole-exome sequencing
Background. Approximately 120 out of every 1 million children in the world develop cancer each year. In Turkey, 2500-3000 children are diagnosed with new cancer each year. The causes of childhood cancer have been studied for many years. It is known that many cancers in children, as in adults, cause uncontrolled cell growth, and develop as a result of mutations in genes that cause cancer. Methods. The investigation of family history within this context in the study, a total of 13 individuals consisting of all children and adults in the family were examined using the whole-exome sequencing (WES) with the individuals who were diagnosed with cancer in the family, who were detected to have different cancer profiles, and defined as high risk and to determine the gene or genes through which the disease has developed. Results. At the end of the study, a total of 30 variants with a pathogenic record in the family were identified. A total of 10 pathogenic variants belonging to 8 different genes from these variants have been associated with various cancer risks. Conclusions. A significant scientific contribution has been made to the mechanism of disease formation by studying a family with a high cancer burden and by finding the genes associated with the disease. In addition, by the results obtained, family members with cancer predisposition were selected after a risk analysis conducted in this family, and the necessary examinations and scans were recommended to provide an early diagnostic advantage. © 2022, Turkish National Pediatric Society. All rights reserved
Türk toplumunda meme kanserli hastalarda BRCA mutasyonlarının dağılımı ve sağkalımla ilişkisi
Clinicopathological characteristics and survival rate in patients with BRCA1/2 linked ovarian cancer in Turkey
Aberrant miR-3135b and miR-1273g-3p expression in the peripheral blood samples of BRCA1/2 (±) ovarian cancer patients
Ovarian cancer (OC) ranks as the eighth most prevalent malignancy among women globally. The short non-coding RNA molecules, microRNAs (miRNAs) target multiple mRNAs and regulate the gene expression. Here in this study, we aimed to validate miR-3135b and miR-1273g-3p as novel biomarkers for prognostic and diagnostic factor OC. After RNA isolation, we analyzed the miR-3135b and miR-1273g-3p expression in peripheral blood samples derived from 150 OC patients. Subsequently, we compared their expression levels with 100 healthy controls. The differences of miR-3135b and miR-1273g-3p expression were detected using the Quantitative Real Time-PCR (qRT-PCR) technique following miRNA-specific cDNA synthesis pursing miRNA separation. The miR-3135b and miR-1273g-3p were higher in OC patients who tested positive for BRCA1/2 compared to BRCA-negative patients, and healthy cases. The level of miR-3135b demonstrated a roughly 4.82-fold increase in OC patients in comparison to the healthy cases, while miR-1273g-3p expression exhibited a roughly 6.77-fold increase. The receiver operating characteristic (ROC) analysis has demonstrated the potential of miR-3135b and miR-1273g-3p as markers for distinguishing between OC patients and healthy controls. The higher expressions of miR-3135b and miR-1273g-3p could be associated with OC development. Moreover, miR-3135b may have a diagnostic potential and miR-1273g-3p may have both diagnostic and prognostic potential in OC cell differentiation. The string analysis has revealed an association between miR-1273g-3p and the MDM2 gene, suggesting a potential link to tumor formation through the proteasomal degradation of the TP53 tumor suppressor gene. Additionally, the analysis indicates an association of miR-1273g-3p with CHEK1, a gene involved in checkpoint-mediated cell cycle arrest. String analysis also indicates that miR-3135b is associated with the MAPK1 gene, causing activation of the oncogenesis cascade. In conclusion, miR-1273g-3p, and miR-3135b exhibit significant potential as diagnostic markers. However, further research is needed to comprehensively investigate these miRNAs diagnostic and predictive characteristics in a larger cohort
2008-2012 yılları arasında kanser genetiği polikliniğine başvuran yüksek riskli meme/over kanser sendromlu vakaların dağılımı
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
Methylation Changes of Primary Tumors, Monolayer, and Spheroid Tissue Culture Environments in Malignant Melanoma and Breast Carcinoma
Epigenetic changes have major role in the normal development and programming of gene expression. Aberrant methylation results in carcinogenesis. The primary objective of our study is to determine whether primary tumor tissue and cultured tumor cells in 2D and 3D tissue culture systems have the same methylation signature for PAX5, TMPRSS2, and SBDS. These findings will play an important role in developing in vitro model system to understand the effect of methylation inhibitors on primary tumor tissue. In a previous study PAX5, TMPRSS2, and SBDS genes that we are investigating were reported to be methylated more than 60% in breast cancer and malignant melanoma cell lines. However, these genes have never been studied in primary tumor tissues. Thus, primary tumor tissues of breast cancer and malignant melanoma were first grown in 2D and 3D cultures. Then these two types of tumor tissues and their 2D and 3D cultures were investigated for changes considering methylation levels in PAX5, TMPRSS2, and SBDS genes using real-time polymerase chain reaction. No differences were observed in the primary tissues and culture systems for both PAX5 and TMPRSS2 in malignant melanoma tissues. We found that PAX5 gene was an efficient marker to measure the effects of methylation inhibitors for in vitro systems for malignant melanoma tissue
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