SNPs for breast cancer risk assessment
نویسندگان
چکیده
منابع مشابه
Association of Obesity Related Genetic Variants (FTO and MC4R) with Breast Cancer Risk:a population-based case-control study in Iran
Background: The heterogeneous breast cancer is the most common cause of cancer-related mortality. Obesity defined by BMI is known as a major risk factor for breast cancer. Objective: The purpose of this study was to explore the role of obesity related-polymorphisms rs9939609 FTO and rs17782313 MC4R in breast cancer development. Materials and Methods: We obtained matched peripheral blood, serum ...
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Background: Breast Cancer (BC), the second leading cause of cancer mortality after lung cancer and varied across the world due to genetic and environmental factors. In this study, we evaluated the interaction between the polymorphisms in genes encoding enzymes of folate metabolism: methylenetetrahydrofolate reductase (MTHFR), methionine synthesis reductase (MTR) with the BC prognostic factors. ...
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Background: Prediction of breast cancer risk and identifying women who are at high risk of breast cancer, would be a great help for planning and conducting screening programs. The aim of this study was to estimate the 5-year breast cancer risk among women in Isfahan. Methods: This cross-sectional study was conducted on 9674 women aged 35-69 years who referred to the Breast Cancer Screening Cen...
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Breast cancer is the most common cancer worldwide and is the second leading cause of death in women after lung cancer. Micro RNAs (miRNAs) are among endogenous factors which are involved in many types of cancers, including breast cancer. Single nucleotide polymorphism (SNP) in the miRNAs, might change their biological activities such as their effects on oncogenes and tumor suppressor genes. The...
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Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
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