Title of article :
Integrated Genome-Wide Methylation and Expression Analyses Reveal Key Regulators in Osteosarcoma
Author/Authors :
Wang, Fei Department of Orthopedics - China-Japan union Hospital Jilin University - Changchun - Jilin, China , Qin, Guoqing Department of Orthopedics - Jilin Disabled Persons’ Rehabilitation Center - Jilin Chunguang Rehabilitation Hospital - Changchun - Jilin, China , Liu, Junzhi China-Japan union Hospital Jilin University - Changchun - Jilin, China , Wang, Xiunan Department of Orthopedics - The 964th Hospital of the PLA Joint Logistics Support Force - Lvyuan District, - Changchun City - Jilin Province, China , Ye, Baoguo Department of Anesthesiology - China-Japan union Hospital Jilin University - Changchun - Jilin, China
Abstract :
Osteosarcoma (OS) is one of the most common types of primary bone tumors in early adolescence with unsatisfied prognosis.
Aberrant DNA methylation had been demonstrated to be related to tumorigenesis and progression of multiple cancers and
could serve as the potential biomarkers for the prognosis of human cancers. In conclusion, this study identified 18
downregulated hypomethylation genes and 52 upregulated hypomethylation genes in OS by integrating the analysis the
GSE97529 and GSE42572 datasets. Bioinformatics analysis revealed that OS-specific methylated genes were involved in
regulating multiple biological processes, including chemical synaptic transmission, transcription, response to drug, and
regulating immune response. KEGG pathway analysis showed that OS-specific methylated genes were associated with the
regulation of Hippo, cAMP calcium, MAPK, and Wnt signaling pathways. By analyzing R2 datasets, this study showed that the
dysregulation of these OS-specific methylated genes was associated with the metastasis-free survival time in patients with OS,
including CBLN4, ANKMY1, BZW1, KRTCAP3, GZMB, KRTDAP, LY9, PFKFB2, PTPN22, and CLDN7. This study provided
a better understanding of the molecular mechanisms underlying the progression and OS and novel biomarkers for the prognosis
of OS.
Keywords :
Genome-Wide , Analyses , OS , DNA
Journal title :
Computational and Mathematical Methods in Medicine