A computational model to predict bone metastasis in breast cancer by integrating the dysregulated pathways.

ABSTRACT:

Background

Although there are a lot of researches focusing on cancer prognosis or prediction of cancer metastases, it is still a big challenge to predict the risks of cancer metastasizing to a specific organ such as bone. In fact, little work has been published for such a purpose nowadays.

Methods

In this work, we propose a Dysregulated Pathway Based prediction Model (DPBM) built on a merged data set with 855 samples. First, we use bootstrapping strategy to select bone metastasis related genes. Based on the selected genes, we then detect out the dysregulated pathways involved in the process of bone metastasis via enrichment analysis. And then we use the discriminative genes in each dysregulated pathway, called as dysregulated genes, to construct a sub-model to forecast the r

SUBMITTER: Zhou X 

PROVIDER: S-EPMC4161863 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature