Prediction of BRCA Gene Mutation in Breast Cancer Based on Deep Learning and Histopathology Images.

ABSTRACT:

Background

Breast cancer is one of the most common cancers and the leading cause of death from cancer among women worldwide. The genetic predisposition to breast cancer may be associated with a mutation in particular genes such as gene BRCA1/2. Patients who carry a germline pathogenic mutation in BRCA1/2 genes have a significantly increased risk of developing breast cancer and might benefit from targeted therapy. However, genetic testing is time consuming and costly. This study aims to predict the risk of gBRCA mutation by using the whole-slide pathology features of breast cancer H&E stains and the patients' gBRCA mutation status.

Methods

In this study, we trained a deep convolutional neural network (CNN) of ResNet on whole-slide images (WSIs) to predict the gBRCA mutation i

SUBMITTER: Wang X 

PROVIDER: S-EPMC8329536 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature