4.4 Article

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

期刊

DIABETES THERAPY
卷 9, 期 6, 页码 2229-2243

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s13300-018-0509-y

关键词

Bioinformatics; Cancer risk; Connectivity; Diabetic treatment; Drug safety; Functional network study; Pancreatic cancer; Pioglitazone; Prostate cancer; Side effect

资金

  1. National Natural Science Foundation of China [81670783, 81570716, 81770835]
  2. Natural Science Foundation of Guangdong Province [2017A030313473, 2016A030313633]
  3. National Undergraduate Training Programs for Innovation and Entrepreneurship [201712121049]

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IntroductionThe 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.MethodsIn 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.ResultsWe 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.ConclusionsPioglitazone 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.

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