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eISSN: 1643-3750

Experimental Study of Somatic Variants of Osteosarcoma by Whole-Exome Sequencing

Jingyu Hou, Guoqing Liu, Peng Zhang, Bangmin Wang, Qiang Yan, Pin Wu, Chuchu Wang, Weitao Yao

Department of Bone and Soft Tissue Oncology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China (mainland)

Med Sci Monit 2020; 26:e920826

DOI: 10.12659/MSM.920826

Available online: 2020-01-24

Published: 2020-03-20


#920826

BACKGROUND: This study aimed to investigate the role of gene mutation site distribution, biological function, pathway enrichment, and gene association analysis in the occurrence, development, and migration of osteosarcoma.
MATERIAL AND METHODS: Somatic mutation screening was performed using the whole-exome sequencing of osteosarcoma samples, and the distribution of mutations was demonstrated by Circos diagrams. Metascape was used to analyze the GO and KEGG signal pathway enrichment of the genes harboring protein coding alterations, and GeneMANIA was used to analyze the interaction of mutated genes.
RESULTS: The results showed that the protein coding alterations were found throughout the whole genome in 3 osteosarcoma samples. A large number of identical or related biological processes and pathways were found in osteosarcoma samples. The GeneMANIA analysis of the 10 mutations shared by 3 samples showed that the target gene minichromosome maintenance complex component 4 (MCM4) and 3 lateral genes were most functional, and were all related to DNA replication. The analysis of GO and KEGG signal pathway enrichment showed that the mutated genes were involved mainly in tumor-related metabolic pathways. Three mutated genes were involved in the cell process, and 2 mutated genes were involved in the metabolic process. Known driver gene mutations were also observed in the samples.
CONCLUSIONS: The gene analysis confirmed that patients with osteosarcoma had a wide range of common gene mutations related to each other, which are involved in tumor-related metabolic pathways. These findings provide a basis for further gene-targeted therapy and pathway research.

Keywords: Biological Processes, Drive, High-Throughput Nucleotide Sequencing



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