Expression and Prognostic Value of MCM Family Genes in Osteosarcoma

Zhou, Jian; Wang, Mingyong; Zhou, Zhen; Wang, Wanchun; Duan, Juan; Wu, Gen Sheng

doi:10.3389/fmolb.2021.668402

Cited by 26 publications

(22 citation statements)

References 35 publications

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“…Jian Zhou et al reported that MCMs were generally upregulated in various of tumors. Consistent with our research, most of MCM members were highly expressed in tumor tissues, except for MCM8 and MCM9 in sarcoma (32). The proliferation of osteosarcoma cells could be restrained by the inhibition of MCM2.…”

Section: Discussionsupporting

confidence: 91%

Identification of Mesenchymal stem cells Functions in the development of osteosarcoma：A bioinformatics analysis

Cui,

Li,

et al. 2022

Preprint

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Background：Mesenchymal stem cells can promote osteosarcoma cell proliferation and migration, while the underlying mechanism remains unknown. The aim of the study was to identify the crucial genes between mesenchymal stem cells (MSC) and osteosarcoma cells (OS) to investigate the potential molecular mechanism of osteosarcoma.Methods：GSE42352 and GSE39262 were downloaded from Gene Expression Omnibus (GEO) database. The GEO2R calculation method was used to analyze these two gene profiles. Differentially expressed genes (DEGs) were identified between mesenchymal stem cells and osteosarcoma cells. Moreover, FunRich was utilized to conduct functional enrichment analysis. These DEGs were mapped to STRING database to construct a protein-protein interaction (PPI) network, and hub genes were identified by Cytoscape plug-in CytoHubba and CytoNCA. Furthermore, the expression of identified hub genes was validated by the GEPIA database. The correlations between microRNA (miRNA) and hub genes were analyzed by the online website StarBase. The correlation among microRNA (miRNA), transcription factors (TFs) and hub genes were analyzed by Cytoscape plug-in iRegulon and TRRUST database. Cytoscape was used to establish a regulatory network of TF‐miRNA‐target gene. Finally, the TCGA clinical data was used to verify the clinical pathological features of CCNA2.Results: A total of 225 markedly robust DEGs were identified (101 upregulated and 124 downregulated). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that these DEGs were related to various cancer-related biological pathways and functions. A PPI network was constructed including 225 nodes and 1695 edges, and 9 hub genes were found in the PPI networks. Re-analysing a PPI network of all cell cycle genes showed CCNA2 is the most important node in biological networks. Analysis of human samples confirmed that miR-381 and CCNA2 exhibited an inverse pattern of expression in human osteosarcomas. Analysis of the original patients data from TCGA Website confirmed that CCNA2 expression increased in patients was associated with metastatic. Investigating the relationship between CCNA2 and tumour immunity showed CCNA2 was involved in the infiltration of CD4+ T cells in SARC and had a significant coexpression relationship with CD274 and TOX.Conclusions: CCNA2 is a promising prognostic biomarker and potential therapeutic target for OS patients. In particular, miR-381 may inhibit the proliferation of OS by specifically targeting CCNA2.

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Section: Discussionsupporting

confidence: 91%

Identification of Mesenchymal stem cells Functions in the development of osteosarcoma：A bioinformatics analysis

Cui,

Li,

et al. 2022

Preprint

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“…Moreover, the hypermethylation state was significantly correlated with MCM3overexpression. Previous studies also reported that MCM3 hypomethylation could increase its expression in hepatocellular carcinoma ( Hua et al, 2020 ) and osteosarcoma ( Zhou et al, 2021 ), and was negatively associated with prognosis. We also identified that “double-strand break repair via break-induced replication” might be the most affected biological processes in GSEA of MCM3 correlated and differential genes between the high and low MCM3 expression groups ( Figure 3B ).…”

Section: Discussionmentioning

confidence: 87%

Systematic analysis of MCM3 in pediatric medulloblastoma via multi-omics analysis

Cao

Zhao

Liang

et al. 2022

Front. Mol. Biosci.

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Minichromosome maintenance proteins are DNA-dependent ATPases that bind to replication origins and allow a single round of DNA replication. One member of this family, MCM3, is reportedly active in most cancers. To systematically elucidate the mechanisms affected by aberrant MCM3 expression and evaluate its clinical significance, we analyzed multi-omics data from the GEO database and validated them in cell lines and tumor samples. First, we showed the upregulation of MCM3 in medulloblastoma (MB) at bulk and single-cell RNA sequence levels and revealed the potential role of MCM3 via DNA replication. Then we found the dysregulation of MCM3 might result from abnormal methylation of MCM3. Moreover, we discovered that MCM3 might affect varied biological processes such as apoptosis, autophagy, and ferroptosis and that MCM3 was correlated with immune components such as fibroblast and neutrophils, which were associated with overall survival in different medulloblastoma subtypes. Furthermore, we found that MCM3 expression was correlated with the IC50 values of cisplatin and etoposide. The nomogram of MCM3-related genes showed the reliable and better prediction of 1- and 5-year survival compared to current histological and molecular classifications. Overall, the results of our study demonstrated that MCM3 might serve as a potential biomarker with clinical significance and better guidance than current histological and molecular classifications for clinical decision-making.

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“…Many studies have clarified the molecular mechanism and prognostic markers of various subtypes of sarcoma from the perspective of gene expression. 10–12 , 14 , 26 , 27 However, the prognostic value of the differential expressed genes in the integrated subtypes of sarcoma remains to be reported. In this study, we obtained three GSE series profiles from the GEO database, and differentially expressed genes were selected.…”

Section: Discussionmentioning

confidence: 99%

“… 13 Similarly, minichromosome maintenance family proteins were found to widely participate in the tumor progress and prognosis in patients with osteosarcoma. 14 However, the role of common differential expression genes (CDEGs) among diverse subtypes of SARC has not been reported. In the current study, we obtained several CDEGs from three GEO series (GSE) profiles and identified several genes that interacted the most.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics Analysis Identified Five Widely Expressed Genes Associated with Prognosis in Sarcoma

Tu¹,

Jia²,

Qian³

2022

IJGM

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Background Human sarcomas (SARC) are a group of malignant tumors that originated from mesenchymal lineages with more than 60 subtypes. However, potential biomarkers for the diagnosis and prognosis of SARC remain to be investigated. Methods We obtained three GSE raw matrix files (GSE39262, GSE21122, GSE48418) that related to various subtypes of sarcoma from the public GEO database and explored the widely differential expression genes in three obtained GSE files. Then common differential expression genes (CDGEs) were identified. We analyzed the correlation between the expression of the top five interacted genes of CDEGs and genome-wide differences, prognosis, genetic mutation, functional enrichment, immune infiltration, immune checkpoint, and marker genes’ expression of N6-methyladenosine (m 6 A) modification in SARC patients. Besides, a prognostic nomogram was constructed to predict the survival of SARC patients. Results Among the three GSE files, 42 CDGEs were identified, and the top five interacted genes were ASPM, CCNB2, PRC1, AURKA, and SCM2. The expression levels of the five genes were higher in the SARC group than that in the normal group. The transcriptional level of CCNB2, PRC, and SCM2 was correlated to the worse survival of SARC. The constructed nomogram that combined CNB2, PRC1, and SCM2 showed a fairly good incredibility in predicting the survival of SARC (C-index: 0.711). Furthermore, the five genes were widely involved in immune infiltration, immune checkpoint, and m 6 A modification. In addition, we found a minor survival-related mutation rate (9%) of the five identified genes in SARC patients (p < 0.05). Conclusion The results suggested the five identified genes widely participated in the prognosis, immune infiltration, immune checkpoint, and m 6 A modification of SARC patients. This study provided a theoretical basis for the research about the correlation between the level of five identified genes and sarcoma, but the further mechanism needs to be verified by experiments.

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Expression and Prognostic Value of MCM Family Genes in Osteosarcoma

Cited by 26 publications

References 35 publications

Identification of Mesenchymal stem cells Functions in the development of osteosarcoma：A bioinformatics analysis

Identification of Mesenchymal stem cells Functions in the development of osteosarcoma：A bioinformatics analysis

Systematic analysis of MCM3 in pediatric medulloblastoma via multi-omics analysis

Bioinformatics Analysis Identified Five Widely Expressed Genes Associated with Prognosis in Sarcoma

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