Integral Analyses of Competing Endogenous RNA Mechanisms and DNA Methylation Reveal Regulatory Mechanisms in Osteosarcoma

Research progress on the role of lncRNA, circular RNA, and microRNA networks in regulating ferroptosis in osteosarcoma

Noncoding RNAs (ncRNAs) do not participate in protein-coding. Ferroptosis is a newly discovered form of cell death mediated by reactive oxygen species and lipid peroxidation. Recent studies have shown that ncRNAs such as microRNAs, long noncoding RNAs, circular RNAs, and ferroptosis are involved in the occurrence and development of osteosarcoma (OS). Studies have confirmed that ncRNAs participate in the development of OS by regulating the ferroptosis. However, systematic summary on this topic are still lacking. This review summarises the potential role of ncRNAs in the diagnosis, treatment, drug resistance, and prognosis of OS and the basis for diagnosing, preventing, and treating clinical OS and developing effective drugs. This review summarises the latest research progress on ncRNAs that regulate ferroptosis in OS, attempts to clarify the molecular mechanisms by which ncRNAs regulate ferroptosis in the pathogenesis of OS, and elaborates on the involvement of ferroptosis in OS from the perspective of ncRNAs.

Weighted correlation network analysis identifies multiple susceptibility loci for low-grade glioma

BACKGROUND

The current molecular classifications cannot completely explain the polarized malignant biological behavior of low-grade gliomas (LGGs), especially for tumor recurrence. Therefore, we tried to identify suspicious hub genes related to tumor recurrence in LGGs.

METHODS

In this study, we constructed a gene-miRNA-lncRNA co-expression network for LGGs by a weighted gene co-expression network analysis (WGCNA). GDCRNATools and the WGCNA R package were mainly used in data analysis.

RESULTS

Sequencing data from 502 LGG patients were analyzed in this study. Compared with recurrent glioma tissues, we identified 774 differentially expressed (DE) mRNAs, 49 DE miRNAs, and 129 DE lncRNAs in primary LGGs and ultimately determined that the expression of MKLN1 was related to tumor recurrence in LGG.

CONCLUSION

This study identified the potential biomarkers for the pathogenesis and recurrence of LGGs and proposed that MKLN1 could be a potential therapeutic target.

DNMT3A Regulates miR-149 DNA Methylation to Activate NOTCH1/Hedgehog Pathway to Promote the Development of Junctional Osteosarcoma

Purpose. To investigate the DNMT3A/miR-149/NOTCH1/Hedgehog axis regulating the development of osteosarcoma. Methods. First, microRNA and mRNA expression microarrays were downloaded from the GEO database for osteosarcoma and differentially expressed microRNAs were analyzed. Subsequently, we collected cancerous tissues and corresponding paracancerous tissues from 42 osteosarcoma patients and examined the expression levels of miR-149, DNMT3A, and NOTCH1 in the samples. Subsequently, miR-149 was overexpressed in osteosarcoma cells to detect cell proliferation and metastatic ability changes. We then queried the methylation level of the miR-149 promoter on the bioinformatics website and verified it by experiment. We further demonstrated the expression level of miR-149 with NOTCH1 using a dual luciferase assay and confirmed the role of NOTCH1 on osteosarcoma cell growth and metastasis by functional rescue assay. Finally, we detected the activation level of the Hedgehog/catenin signaling pathway by WB and immunofluorescence. Results. miR-149 was significantly low expressed in osteosarcoma tissues and cells, while DNMT3A and NOTCH1 were highly expressed in osteosarcoma tissues and cells, and negatively correlated with miR-149 expression levels. Overexpression of miR-149 significantly inhibited the growth and metastasis of osteosarcoma cells in vitro and in vivo, and we found that DNMT3A could promote the methylation modification of the miR-149 promoter, thereby inhibiting the expression of miR-149. Subsequently, the experimental results showed that miR-149 could target negative regulation of NOTCH1, and further overexpression of NOTCH1 in cells with high miR-149 expression could promote the growth and metastasis of osteosarcoma cells in vitro. Conclusion. The methyltransferase DNMT3A suppresses miR-149 expression by promoting methylation modification of the miR-149 promoter, resulting in elevated expression levels of NOTCH1 in cells, therefore exacerbating activation of the Hedgehog signaling pathway and therefore exacerbating the development and progression of osteosarcoma.

Epidemiological Evidence for Associations Between Genetic Variants and Osteosarcoma Susceptibility: A Meta-Analysis

BACKGROUND

Previous studies have showed that single nucleotide polymorphisms (SNPs) might be implicated in the pathogenesis of osteosarcoma (OS). Numerous studies involving SNPs with OS risk have been reported; these results, however, remain controversial and no comprehensive research synopsis has been performed till now.

OBJECTIVE

This study seeks to clarify the relationships between SNPs and OS risk using a comprehensive meta-analysis, and assess epidemiological evidence of significant associations.

METHODS

The PubMed, Web of Science, and Medline were used to screen for articles that evaluated the association between SNP and OS susceptibility in humans before 24 December 2021. Furthermore, we used Venice Criteria and a false positive report probability (FPRP) test to assess the grades of epidemiological evidence for the statistical relationships.

RESULTS

We extracted useful data based on 43 articles, including 10,255 cases and 13,733 controls. Our results presented that 25 SNPs in 17 genes were significantly associated with OS risk. Finally, we graded strong evidence for 17 SNPs in 14 genes with OS risk (APE1 rs1760944, BCAS1 rs3787547, CTLA4 rs231775, ERCC3 rs4150506, HOTAIR rs7958904, IL6 rs1800795, IL8 rs4073, MTAP rs7023329 and rs7027989, PRKCG rs454006, RECQL5 rs820196, TP53 rs1042522, VEGF rs3025039, rs699947 and rs2010963, VMP1 rs1295925, XRCC3 rs861539), moderate for 14 SNPs in 12 genes and weak for 14 SNPs in 11 genes.

CONCLUSION

In summary, this study offered a comprehensive meta-analysis between SNPs and OS susceptibility, then evaluated the credibility of statistical relationships, and provided useful information to identify the appropriate candidate SNPs and design future studies to evaluate SNP factors for OS risk.