Drug repurposing against breast cancer by integrating drug-exposure expression profiles and drug-drug links based on graph neural network.

ABSTRACT:

Motivation

Breast cancer is one of the leading causes of cancer deaths among women worldwide. It is necessary to develop new breast cancer drugs because of the shortcomings of existing therapies. The traditional discovery process is time-consuming and expensive. Repositioning of clinically approved drugs has emerged as a novel approach for breast cancer therapy. However, serendipitous or experiential repurposing cannot be used as a routine method.

Results

In this study, we proposed a graph neural network model GraphRepur based on GraphSAGE for drug repurposing against breast cancer. GraphRepur integrated two major classes of computational methods, drug network-based and drug signature-based. The differentially expressed genes of disease, drug-exposure gene expression data an

SUBMITTER: Cui C 

PROVIDER: S-EPMC8479657 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature