Title
New Drug Candidates For Osteosarcoma: Drug Repurposing Based On Gene Expression Signature
Abstract
Osteosarcoma (OS) is an aggressive bone malignancy and the third most common cancer in adolescence. Since the late 1970s, OS therapy and prognosis had only modest improvements, making it appealing to explore new tools that could help ameliorate the treatment. We present a meta-analysis of the gene expression signature of primary OS, and propose small molecules that could reverse this signature. The meta-analysis was performed using GEO microarray series. We first compared gene expression from eleven primary OS against osteoblasts to obtain the differentially expressed genes (DEGs). We later filtered those DEGs by verifying which ones had a concordant direction of differential expression in a validation group of 82 OS samples versus 30 bone marrow mesenchymal stem cells (BM-MSC) samples. A final gene expression signature of 266 genes (98 up and 168 down regulated) was obtained. The L1000CDS(2) engine was used for drug repurposing. The top molecules predicted to reverse the signature were afatinib (PubChem CID 10184653), BRD-K95196255 (PubChem CID 3242434), DG-041 (PubChem CID 11296282) and CA-074 Me (PubChem CID 23760717). Afatinib (Gilotrif (TM)) is currently used for metastatic non-small-cell lung cancer with EGFR mutations, and in vitro evidence shows antineoplastic potential in OS cells. The other three molecules have reports of antineoplastic effects, but are not currently FDA-approved. Further studies are necessary to establish the potential of these drugs in OS treatment. We believe our results can be an important contribution for the investigation of new therapeutic genetic targets and for selecting new drugs to be tested for OS.
Year
DOI
Venue
2021
10.1016/j.compbiomed.2021.104470
COMPUTERS IN BIOLOGY AND MEDICINE
Keywords
DocType
Volume
Osteosarcoma, Microarray expression data, Gene expression signature, Drug repurposing, Afatinib
Journal
134
ISSN
Citations 
PageRank 
0010-4825
0
0.34
References 
Authors
0
4