A systematic analysis of FDA-approved anticancer drugs

Jingchun Sun,Qiang Wei,Hua Xu,Jingqi Wang,Yubo Zhou,Qi Liu

doi:10.1186/s12918-017-0464-7

Abstract

BackgroundThe discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment. Repurposing existing drugs that may have unanticipated effects as potential candidates is one way to meet this important goal. Systematic investigation of efficient anticancer drugs could provide valuable insights into trends in the discovery of anticancer drugs, which may contribute to the systematic discovery of new anticancer drugs.ResultsIn this study, we collected and analyzed 150 anticancer drugs approved by the US Food and Drug Administration (FDA). Based on drug mechanism of action, these agents are divided into two groups: 61 cytotoxic-based drugs and 89 target-based drugs. We found that in the recent years, the proportion of targeted agents tended to be increasing, and the targeted drugs tended to be delivered as signal drugs. For 89 target-based drugs, we collected 102 effect-mediating drug targets in the human genome and found that most targets located on the plasma membrane and most of them belonged to the enzyme, especially tyrosine kinase. From above 150 drugs, we built a drug-cancer network, which contained 183 nodes (150 drugs and 33 cancer types) and 248 drug-cancer associations. The network indicated that the cytotoxic drugs tended to be used to treat more cancer types than targeted drugs. From 89 targeted drugs, we built a cancer-drug-target network, which contained 214 nodes (23 cancer types, 89 drugs, and 102 targets) and 313 edges (118 drug-cancer associations and 195 drug-target associations). Starting from the network, we discovered 133 novel drug-cancer associations among 52 drugs and 16 cancer types by applying the common target-based approach. Most novel drug-cancer associations (116, 87%) are supported by at least one clinical trial study.ConclusionsIn this study, we provided a comprehensive data source, including anticancer drugs and their targets and performed a detailed analysis in term of historical tendency and networks. Its application to identify novel drug-cancer associations demonstrated that the data collected in this study is promising to serve as a fundamental for anticancer drug repurposing and development.

Highlights

The discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment
The increasing cost of new drug development and decreasing number of truly efficient medicines approved by the US Food and Drug Administration (FDA) present unprecedented challenges for the pharmaceutical industry and patient healthcare, including the oncology [1, 2]
Collection of FDA-approved anticancer drugs and their relation information We have collected anticancer drugs approved by FDA since 1949 to the end of 2014 from multiple data sources

Summary

Introduction

The discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment. Repurposing existing drugs that may have unanticipated effects as potential candidates is one way to meet this important goal. The increasing cost of new drug development and decreasing number of truly efficient medicines approved by the US Food and Drug Administration (FDA) present unprecedented challenges for the pharmaceutical industry and patient healthcare, including the oncology [1, 2]. As the increasing availability of FDA-approved drugs and quantitative biological data from the human genome project, multiple strategies have been proposed to shorten the drug development process and significantly lower costs, including drug repurposing [3, 4] and network pharmacology [5, 6]

Methods

Results

Conclusion