New Genetic Variants Improve Personalized Breast Cancer Diagnosis

نویسندگان

  • Jie Liu
  • David Page
  • Peggy Peissig
  • Catherine McCarty
  • Adedayo A. Onitilo
  • Amy Trentham-Dietz
  • Elizabeth Burnside
چکیده

Recent large-scale genome-wide association studies (GWAS) have identified a number of new genetic variants associated with breast cancer. However, the degree to which these genetic variants improve breast cancer diagnosis in concert with mammography remains unknown. We conducted a case-control study and collected mammography features and 77 genetic variants which reflect the state of the art GWAS findings on breast cancer. A naïve Bayes model was developed on the mammography features and these genetic variants. We observed that the incorporation of the genetic variants significantly improved breast cancer diagnosis based on mammographic findings.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Leveraging Interaction between Genetic Variants and Mammographic Findings for Personalized Breast Cancer Diagnosis

Recent large-scale genome-wide association studies (GWAS) have identified a number of genetic variants associated with breast cancer which showed great potential for clinical translation, especially in breast cancer diagnosis via mammograms. However, the amount of interaction between these genetic variants and mammographic features that can be leveraged for personalized diagnosis remains unknow...

متن کامل

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 ...

متن کامل

Diagnosis of Breast Cancer using a Combination of Genetic Algorithm and Artificial Neural Network in Medical Infrared Thermal Imaging

Introduction This study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. The medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. By analyzing this information, the best diagnostic parameters among the available parameters are selected and ...

متن کامل

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms

Several recent genome-wide association studies have identified genetic variants associated with breast cancer. However, how much these genetic variants may help advance breast cancer risk prediction based on other clinical features, like mammographic findings, is unknown. We conducted a retrospective case-control study, collecting mammographic findings and high-frequency/low-penetrance genetic ...

متن کامل

Feature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 2014  شماره 

صفحات  -

تاریخ انتشار 2014