Brief Introduction

Cancer cell growth is strictly relied on the differential gene expression, such as the highly expression of EGFR and TOP2A in lung cancer. Previous studies showed that the differential cancer gene expression are caused by accumulative somatic mutations. Different cancer patients can carry distinct somatic mutations, thus the personalized cancer therapy is the trend of clinical oncology.

Our aim is to find the optimal personalized drug(s) to treatment cancer based on personalized genetic background. We thus constructed this web server to effectively predict the candidates from the patient genetic background.

Briefly, we firstly linked the somatic mutations and the differential cancer gene expression using the TCGA dataset, and then find drugs from DrugBank that can inhibit/agonist the function of up/down-regulated genes. Thus, different cancer patients can have their "own" different drugs based on the genetic background.