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25.09.2018 | Original Research | Ausgabe 6/2018 Open Access

Diabetes Therapy 6/2018

Association of Pioglitazone with Increased Risk of Prostate Cancer and Pancreatic Cancer: A Functional Network Study

Zeitschrift:
Diabetes Therapy > Ausgabe 6/2018
Autoren:
Weiheng Wen, Peili Wu, Jinru Gong, Min Zhao, Zhen Zhang, Rongping Chen, Hong Chen, Jia Sun
Wichtige Hinweise
Weiheng Wen, Peili Wu and Jinru Gong contributed equally to this work.

Enhanced Digital Features

To view enhanced digital features for this article go to https://​doi.​org/​10.​6084/​m9.​figshare.​7043330.

Abstract

Introduction

The question of whether pioglitazone, an antidiabetic drug, increases the risk of cancer has been debated for some time. Recent studies have shown that pioglitazone use can increase the risk of prostate cancer as well as pancreatic cancer. However, it is unclear whether pioglitazone is a causal risk factor for these cancers.

Methods

In this study, we aimed to explore the direct targets of pioglitazone and genes associated with this drug by querying open platforms in order to construct a biological function network, and then to further evaluate the relationships of pioglitazone with prostate cancer and pancreatic cancer.

Results

We first tested our hypothesis using DrugBank and STRING. We identified four direct targets of pioglitazone and 50 pioglitazone-associated genes, which were then selected for KEGG pathway analysis using STRING and WebGestalt. This analysis generated the top 25 KEGG pathways, among which four pathways were related to site-specific cancers, including prostate cancer and pancreatic cancer. Finally, a genomic study using cBioPortal indicated that genomic alterations of two gene sets related to the prostate cancer and pancreatic cancer pathways, respectively, are associated with the acceleration of carcinogenesis.

Conclusions

Pioglitazone is likely to be a causal risk factor for prostate cancer and pancreatic cancer, so this drug should be used with caution. The present research also demonstrates the use of biological function network analysis to effectively explore drug interactions and drug safety profiles.
Literatur
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