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Exploring targeted therapy of osteosarcoma using proteomics data

Authors Chaiyawat P, Settakorn J, Sangsin A, Teeyakasem P, Klangjorhor J, Soongkhaw A, Pruksakorn D

Received 17 August 2016

Accepted for publication 3 December 2016

Published 1 February 2017 Volume 2017:10 Pages 565—577

DOI https://doi.org/10.2147/OTT.S119993

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Ru Chen

Peer reviewer comments 3

Editor who approved publication: Dr Jianmin Xu

Parunya Chaiyawat,1 Jongkolnee Settakorn,2 Apiruk Sangsin,1 Pimpisa Teeyakasem,1 Jeerawan Klangjorhor,1 Aungsumalee Soongkhaw,2 Dumnoensun Pruksakorn1,3

1Orthopedic Laboratory and Research Netting Center, Department of Orthopedics, 2Department of Pathology, Faculty of Medicine, 3Excellence Center in Osteology Research and Training Center, Chiang Mai University, Chiang Mai, Thailand

Abstract: Despite multimodal therapeutic treatments of osteosarcoma (OS), some patients develop resistance to currently available regimens and eventually end up with recurrent or metastatic outcomes. Many attempts have been made to discover effective drugs for improving outcome; however, due to the heterogeneity of the disease, new therapeutic options have not yet been identified. This study aims to explore potential targeted therapy related to protein profiles of OS. In this review of proteomics studies, we extracted data on differentially expressed proteins (DEPs) from archived literature in PubMed and our in-house repository. The data were divided into three experimental groups, DEPs in 1) OS/OB: OS vs osteoblastic (OB) cells, 2) metastasis: metastatic vs non-metastatic sublines plus fresh tissues from primary OS with and without pulmonary metastasis, and 3) chemoresistance: spheroid (higher chemoresistance) vs monolayer cells plus fresh tissues from biopsies from good and poor responders. All up-regulated protein entities in the list of DEPs were sorted and cross-referenced with identifiers of targets of US Food and Drug Administration (FDA)-approved agents and chemical inhibitors. We found that many targets of FDA-approved antineoplastic agents, mainly a group of epigenetic regulators, kinases, and proteasomes, were highly expressed in OS cells. Additionally, some overexpressed proteins were targets of FDA-approved non-cancer drugs, including immunosuppressive and antiarrhythmic drugs. The resulting list of chemical agents showed that some transferase enzyme inhibitors might have anticancer activity. We also explored common targets of OS/OB and metastasis groups, including amidophosphoribosyltransferase (PPAT), l-lactate dehydrogenase B chain (LDHB), and pyruvate kinase M2 (PKM2) as well as the common target of all categories, cathepsin D (CTSD). This study demonstrates the benefits of a text mining approach to exploring therapeutic targets related to protein expression patterns. These results suggest possible repurposing of some FDA-approved medicines for the treatment of OS and using chemical inhibitors in drug screening tests.

Keywords: osteosarcoma, proteomics, targeted therapy, text mining, FDA-approved drugs

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