Extensive analysis of 59 sarcoma-related fusion genes identified pazopanib as a potential inhibitor to COL1A1-PDGFB fusion gene.
Takeshi HiroseMasachika IkegamiShinya KojimaAkihiko YoshidaMakoto EndoEijiro ShimadaMasaya KanahoriRyunosuke OyamaYoshihiro MatsumotoYasuharu NakashimaAkira KawaiHiroyuki ManoShinji KohsakaPublished in: Cancer science (2023)
Sarcomas are malignant mesenchymal tumors that are extremely rare and divergent. Fusion genes are involved in approximately 30% of sarcomas as driver oncogenes; however, their detailed functions are not fully understood. In this study, we determined the functional significance of 59 sarcoma-related fusion genes. The transforming potential and drug sensitivities of these fusion genes were evaluated using a focus formation assay (FFA) and the mixed-all-nominated-in-one (MANO) method, respectively. The transcriptome was also examined using RNA sequencing of 3T3 cells transduced with each fusion gene. Approximately half (28/59, 47%) of the fusion genes exhibited transformation in the FFA assay, which was classified into five types based on the resulting phenotype. The sensitivity to 12 drugs including multityrosine kinase inhibitors was assessed using the MANO method and pazopanib was found to be more effective against cells expressing the COL1A1-PDGFB fusion gene compared with the others. The downstream MAPK/AKT pathway was suppressed at the protein level following pazopanib treatment. The fusion genes were classified into four subgroups by cluster analysis of the gene expression data and gene set enrichment analysis. In summary, the oncogenicity and drug sensitivity of 59 fusion genes were simultaneously evaluated using a high-throughput strategy. Pazopanib was selected as a candidate drug for sarcomas harboring the COL1A1-PDGFB fusion gene. This assessment could be useful as a screening platform and provides a database to evaluate customized therapy for fusion gene-associated sarcomas.
Keyphrases
- genome wide
- genome wide identification
- high throughput
- gene expression
- genome wide analysis
- dna methylation
- signaling pathway
- stem cells
- bioinformatics analysis
- single cell
- cell proliferation
- rna seq
- emergency department
- bone marrow
- machine learning
- electronic health record
- oxidative stress
- risk assessment
- small molecule
- drug induced
- induced apoptosis
- protein protein
- amino acid