Cargando…

Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set

BACKGROUND: Mesenchymal stem cells (MSCs) play a crucial role in osteosarcoma (OS) growth and progression. This study conducted a bioinformatics analysis of a single-cell ribonucleic acid sequencing data set and explored the MSC-specific differentially expressed genes (DEGs) in advanced OS. METHODS:...

Descripción completa

Detalles Bibliográficos
Autores principales: Jiang, Haoli, Du, Haoyuan, Liu, Yingnan, Tian, Xiao, Xia, Jinquan, Yang, Shucai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641133/
https://www.ncbi.nlm.nih.gov/pubmed/36388032
http://dx.doi.org/10.21037/tcr-22-2370
Descripción
Sumario:BACKGROUND: Mesenchymal stem cells (MSCs) play a crucial role in osteosarcoma (OS) growth and progression. This study conducted a bioinformatics analysis of a single-cell ribonucleic acid sequencing data set and explored the MSC-specific differentially expressed genes (DEGs) in advanced OS. METHODS: MSC-specific DEGs from GSE152048 was extracted using Seurat R package. These DEGs were then subjected to the functional analysis, and several key genes were further identified and underwent a prognosis analysis. RESULTS: A total of 234 upregulated and 280 downregulated DEGs were identified between the MSCs and other cells, and a total of 188 upregulated and 158 downregulated DEGs were identified between the MSCs and osteoblastic cells. The Gene Ontology (GO) functional analysis showed that the specific DEGs between the MSCs and osteoblastic cells were enriched in GO terms such as “collagen catabolic process”, “positive regulation of pathway-restricted SMAD protein phosphorylation”, “osteoblast differentiation”, “regulation of release of cytochrome c from mitochondria” and “interleukin-1 production”. The specific DEGs between the MSCs and osteoblastic cells were subjected to a protein-protein interaction network analysis. Further, a survival analysis of 20 genes with combined scores >0.94 revealed that the low expression of ANXA1 (annexin A1) and TPM1 (tropomyosin 1) was associated with the shorter overall survival of OS patients, while the high expression of FDPS (farnesyl pyrophosphate synthase), IFITM5 (interferon-induced transmembrane protein 5), FKBP11 (FKBP prolyl isomerase 11), SP7, and SQLE (squalene epoxidase) was associated with the shorter overall survival of OS patients. In a further analysis, we compared the expression of ANXA1, FDPS, IFITM5, FKBP11, SP7, SQLE, and TPM1 between the MSCs and high-grade OS cells. Further validation studies using the GSE42352 data set revealed that ANXA1, FKBP11, SP7, and TPM1 were more upregulated in the MSCs than the high-grade OS cells, while FDPS, IFITM5, and SQLE were more downregulated in the MSCs than the high-grade OS cells. CONCLUSIONS: Our bioinformatics analysis revealed 7 hub genes derived from the specific DEGs between the MSCs and osteoblastic cells. The 7 hub genes may serve as potential prognostic biomarkers for patients with OS.