Dataset Information

Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis.

ABSTRACT: Background:Numerous studies have reported the relationship between Long non-coding RNAs (LncRNAs) expression and prognosis of osteosarcoma, but less consensus has been reached. Our meta-analysis was conducted to quantitatively assess the relationship between the expression of LncRNAs, prognosis and clinical pathology in osteosarcoma development. Methods:PubMed,Embase,Web of Science,The Cochrane Library,SionMed,CNKI and WanFang databases were carefully searched to identify eligible studies. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to evaluate the prognostic significance of LncRNAs expression in osteosarcoma. Moreover, meta-regression analysis and subgroup analysis were carried out to explore the potential sources of heterogeneity. Results:A total of 20 studies comprising 1749 patients were included in present meta-analysis. The results showed that the over-expression of LncRNA had a significant correlation with overall survival (OS) (HR?=?2.16, 95% CI:1.68-2.79), and was not related to disease free survival (DFS) (HR?=?0.71, 95% CI:0.05-9.53). Subgroup analysis further indicated that LncRNA transcription level was significantly associated with alkaline phosphatase (HR?=?2.13, 95% CI:1.58-2.88) , tumor size (?25:HR?=?1.01, 95% CI:0.78-1.3), gender(female/male: HR?=?1.15, 95% CI: 0.96-1.37), tumor site (femur,tibia/elsewhere:HR?=?1.15, 95% CI:0.94-1.4) and chemotherapy (yes/no: HR?=?1.45, 95% CI:0.46-4.63). Conclusions:This study demonstrated that abnormal LncRNAs expression might be potential prognostic markers to predict worse overall survival in osteosarcoma patients. However, the cut-off values may be the source of heterogeneity.

SUBMITTER: Chen D

PROVIDER: S-EPMC6303364 | biostudies-other | 2018 Nov

REPOSITORIES: biostudies-other

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Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis.

Chen Delong D Wang Haibin H Zhang Meng M Jiang Shan S Zhou Chi C Fang Bin B Chen Peng P

Journal of bone oncology 20180922

<h4>Background</h4>Numerous studies have reported the relationship between Long non-coding RNAs (LncRNAs) expression and prognosis of osteosarcoma, but less consensus has been reached. Our meta-analysis was conducted to quantitatively assess the relationship between the expression of LncRNAs, prognosis and clinical pathology in osteosarcoma development.<h4>Methods</h4>PubMed,Embase,Web of Science,The Cochrane Library,SionMed,CNKI and WanFang databases were carefully searched to identify eligible ...[more]

PMID: 30591861

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Project description:BACKGROUND:Long non-coding RNAs (lncRNAs) are key regulators of diverse cellular processes. Although a number of studies have reported the identification of bovine lncRNAs across many tissues, very little is known about the identity and characteristics of lncRNAs in bovine oocytes. METHODS:A bovine oocyte cDNA library was constructed and sequenced using the Illumina HiSeq 2000 sequencing system. The oocyte transcriptome was constructed using the ab initio assembly software Scripture and Cufflinks. The assembled transcripts were categorized to identify the novel intergenic transcripts, and the coding potential of these novel transcripts was assessed using CPAT and PhyloCSF. The resulting candidate long intergenic non-coding RNAs (lincRNAs) transcripts were further evaluated to determine if any of them contain any known protein coding domains in the Pfam database. RT-PCR was used to analyze the expression of oocyte-expressed lincRNAs in various bovine tissues. RESULTS:A total of 85 million raw reads were generated from sequencing of the bovine oocyte library. Transcriptome reconstruction resulted in the assembly of a total of 42,396 transcripts from 37,678 genomic loci. Analysis of the assembled transcripts using the step-wide pipeline resulted in the identification of 1535 oocyte lincRNAs corresponding to 1183 putative non-coding genes. A comparison of the oocyte lincRNAs with the lncRNAs reported in other bovine tissues indicated that 970 of the 1535 oocyte lincRNAs appear to be unique to bovine oocytes. RT-PCR analysis of 5 selected lincRNAs showed either specific or predominant expression of 4 lincRNAs in the fetal ovary. Functional prediction of the oocyte-expressed lincRNAs suggested their involvement in oogenesis through regulating their neighboring protein-coding genes. CONCLUSIONS:This study provides a starting point for future research aimed at understanding the roles of lncRNAs in controlling oocyte development and early embryogenesis in cattle.

Project description:Background: The role of N6-methyladenosine (m6A)-related long non-coding RNAs (lncRNAs) in osteosarcoma (OS) has not been fully studied yet. We aimed to identify m6A-related lncRNAs that could act as prognostic biomarkers for OS. Methods: Pearson correlation was performed to identify m6A-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct the risk model and assess whether the risk score was an independent prognostic factor for patients with OS. Gene Set Enrichment Analysis (GSEA) was performed to analyze the functions of genes in high-risk and low-risk groups. StarBase and Cytoscape were used to construct a competing endogenous RNA (ceRNA) network based on m6A-related prognostic lncRNA signature. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of genes involved in the ceRNA network. Results: We extracted 122 common lncRNAs from TCGA and Gene Expression Omnibus (GEO) databases. Pearson correlation results revealed 59 significant m6A-related lncRNAs in The Cancer Genome Atlas (TCGA) database, from which 2 were screened to construct a risk signature in TCGA dataset, which was then validated in the GEO dataset. A corresponding risk score was calculated and shown to be an independent prognostic factor for patients with OS. Enrichment analysis indicated that cell proliferation-related biological processes were more common in the high-risk group, while immune-related biological processes were more common in the low-risk group. Moreover, we established a nomogram that had a good ability to predict the overall survival of patients with OS. Additionally, a ceRNA network based on small nucleolar RNA host gene 7 (SNHG7) and small nucleolar RNA host gene 12 (SNHG12) was constructed, with genes that were enriched in hepatocellular carcinoma, gastric cancer, and non-small-cell lung cancer pathways. Conclusion: Our study revealed the prognostic role of m6A-related lncRNAs in OS and identified SNHG7 and SNHG12 as potential biomarkers for predicting the prognosis of patients with OS. These findings have enriched our understanding of the role of m6A modification in the dysregulation of lncRNAs in OS.

Dataset Information

Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis.

Publications

Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis.

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