Dataset Information

LncRNA MSC-AS1 Is a Diagnostic Biomarker and Predicts Poor Prognosis in Patients With Gastric Cancer by Integrated Bioinformatics Analysis.

ABSTRACT: Numerous studies have shown that long uncoded RNA (lncRNA) MSC-AS1 may play an important role in the occurrence and development of some types of cancer. However, its role in gastric cancer has rarely been discussed. This study aimed to clarify the association between lncRNA MSC-AS1 and gastric cancer using The Cancer Genome Atlas (TCGA) database. We determined the expression of MSC-AS1 using the Wilcoxon rank sum test; in addition, logistic regression was applied to evaluate the association between MSC-AS1 and clinicopathological characteristics. Also, Kaplan-Meier and Cox regression were used to evaluate the relationship between MSC-AS1 and survival. A nomogram was conducted to predict the impact of MSC-AS1 on prognosis. Moreover, Gene Set enrichment analysis (GSEA) was performed to annotate the biological function of MSC-AS1. Quantitative analysis of immune infiltration was carried out by single-set GSEA (ssGSEA). The MSC-AS1 level was elevated in gastric cancer tissues. An increased MSC-AS1 level was significantly correlated with T stage (odds ratio [OR] = 2.55 for T3 and T4 vs. T1 and T2), histological type (OR = 5.28 for diffuse type vs. tubular type), histological grade (OR = 3.09 for grade 3 vs. grades 1 and 2), TP53 status (OR = 0.55 for mutated vs. wild type), and PIK3CA status (OR = 0.55 for mutated vs. wild type) (all p < 0.05) by univariate logistic regression. Kaplan-Meier survival analysis showed high MSC-AS1 expression had a poor overall survival [hazard ratio (HR) = 1.75; 95% confidence interval (CI): 1.25-2.45; p = 0.001] and progression-free interval (HR = 1.47; 95% CI: 1.03-2.10; p = 0.034). Multivariate survival analysis revealed that MSC-AS1 expression (HR = 1.681; 95% CI: 1.057-2.673; p = 0.028) was independently correlated with overall survival. GSEA demonstrated that the P38/MAPK pathway, the VEGF pathway, the cell adhesion molecules cams, the NOD-like receptor signaling pathway were differentially enriched in the high MSC-AS1 expression phenotype. SsGSEA and Spearman correlation revealed the relationships between MSC-AS1 and macrophages, NK cells, and Tems were the strongest. Coregulatory proteins were included in the PPI network. Upregulated lncRNA MSC-AS1 might be a potential biomarker for the diagnosis and prognosis of gastric cancer.

SUBMITTER: Yang W

PROVIDER: S-EPMC8674534 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background Glioma is characterized by high morbidity, high mortality, and poor prognosis. Despite tremendous advances in the treatment of glioma, the prognosis of patients with glioma is still unsatisfactory. There is an urgent need to discover novel molecular markers that effectively predict prognosis in patients with glioma. The investigation of the role of WEE2-AS1 in various tumors is an emerging research field, but the biological function and prognostic value of WEE2-AS1 in glioma have rarely been reported. This study aimed to assess the value of WEE2-AS1 as a potential prognostic marker of glioma. Methods Gene expression (RNA-Seq) data of patients with glioma were extracted from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. The Wilcoxon rank sum test was used to analyze the expression of WEE2-AS1 in the cells and tissues of glioma. The Kruskal–Wallis rank sum test, Wilcoxon rank sum test, and logistic regression were used to evaluate the relationship between clinical variables and expression of WEE2-AS1. Cox regression analysis and the Kaplan–Meier method were used to evaluate the prognostic factors in glioma. A nomogram based on Cox multivariate analysis was used to predict the impact of WEE2-AS1 on glioma prognosis. Gene Set Enrichment Analysis (GSEA) was used to identify key WEE2-AS1-associated signaling pathways. Spearman’s rank correlation was used to elucidate the association between WEE2-AS1 expression and immune cell infiltration levels. Results We found that WEE2-AS1 was overexpressed in a variety of cancers, including glioma. High expression of WEE2-AS1 was associated with glioma progression. We determined that the expression of WEE2-AS1 might be an independent risk factor for the survival and prognosis of patients with glioma. We further observed that the mechanism of WEE2-AS1-mediated tumorigenesis involved neuroactive ligand-receptor interaction, cell cycle, and the infiltration of immune cells into the glioma microenvironment. Conclusion These findings demonstrate that WEE2-AS1 is a promising biomarker for the diagnosis and prognosis of patients with glioma. An increased understanding of its effects on the regulation of cell growth may lead to the development of clinical applications that improve the prognostic status of patients with glioma. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-023-10594-y.

Project description:Long non-coding (lnc)RNAs have been recognized as important regulators in gastric cancer. lncRNA GAS8-AS1 is considered a tumor suppressor in multiple types of cancer, such as papillary thyroid carcinoma, ovarian cancer and colorectal cancer. However, the specific role of GAS8-AS1 in gastric cancer remains to be fully elucidated. The aim of the present study was to investigate the role of GAS8-AS1 in gastric cancer and its potential underlying mechanisms of action. The expression levels of GAS8-AS1, microRNA (miR)-21-3p, PTEN and pyruvate dehydrogenase (E1) alpha subunit gene (PDHA1) in gastric cancer and non-cancerous tissues, as well as in gastric cancer cell lines, were detected using reverse transcription-quantitative PCR. Cell proliferation was detected by using a Cell Counting Kit-8 assay. Cell migration and invasion were detected using a Transwell assay. Results of the present study demonstrated that the expression levels of GAS8-AS1 in gastric cancer tissues were significantly decreased, whereas its expression did not differ among cancer tissues at different clinical stages. Low expression levels of GAS8-AS1 predicted poor 5-year survival rates for 70 patients with gastric adenocarcinoma from the Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) during patient follow-up. In addition, the expression levels of miR-21-3p were markedly increased in cancer tissues, and miR-21-3p expression was negatively associated with the expression of GAS8-AS1. The direct interaction between GAS8-AS1 and miR-21-3p was predicted using the starBase database and was confirmed by using an RNA pull-down assay. In gastric cell lines, the overexpression of GAS8-AS1 reduced the expression levels of mature miR-21-3p but did not affect the expression of miR-21-3p precursor, while the overexpression of miR-21-3p did not, in turn, affect the expression of GAS8-AS1. In addition, the overexpression of GAS8-AS1 inhibited cancer cell proliferation, while the overexpression of miR-21-3p promoted cancer cell proliferation and attenuated the effects of GAS8-AS1. Overexpression of miR-21-3p promoted cancer cell migration and invasion, whereas overexpression of GAS8-AS1 did not affect cell migration or invasion. In summary, results of the present study have demonstrated that GAS8-AS1 acts as a tumor suppressor in gastric cancer, and it may inhibit cancer cell proliferation by downregulating miR-21-3p.

Project description:Background: Knowledge about the prognostic role of long noncoding RNA (lncRNA) in colorectal cancer (CRC) is limited. Therefore, we constructed a lncRNA-related prognostic model based on data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Materials and Methods: CRC transcriptome and clinical data were downloaded from the GSE20916 dataset and the TCGA database, respectively. R software was used for data processing and analysis. The differential lncRNA expression within the two datasets was first screened, and then intersections were measured. Cox regression and the Kaplan-Meier method were used to evaluate the effects of various factors on prognosis. The area under the curve (AUC) of the receiver operating characteristic curve and a nomogram based on multivariate Cox analysis were used to estimate the prognostic value of the lncRNA-related model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to elucidate the significantly involved biological functions and pathways. Results: A total of 11 lncRNAs were crossed. The univariate Cox analysis screened out two lncRNAs, which were analyzed in the multivariate Cox analysis. A nomogram based on the two lncRNAs and other clinicopathological risk factors was constructed. The AUC of the nomogram was 0.56 at 3 years and 0.71 at 5 years. The 3-year nomogram model was compared with the ideal model, which showed that some indices of the 3-year model were consistent with the ideal model, suggesting that our model was highly accurate. The GO and KEGG enrichment analyses showed that positive regulation of secretion by cells, positive regulation of secretion, positive regulation of exocytosis, endocytosis, and the calcium signaling pathway were differentially enriched in the two-lncRNA-associated phenotype. Conclusions: A two-lncRNA prognostic model of CRC was constructed by bioinformatics analysis. The model had moderate prediction accuracy. LncRNA BBOX1-AS1 and lncRNA FOXP4-AS1 were identified as prognostic biomarkers.

Project description:BackgroundGastric cancer (GC) is a malignant tumour that originates in the gastric mucosal epithelium and is associated with high mortality rates worldwide. Long noncoding RNAs (lncRNAs) have been identified to play an important role in the development of various tumours, including GC. Yet, lncRNA biomarkers in a competing endogenous RNA network (ceRNA network) that are used to predict survival prognosis remain lacking. The aim of this study was to construct a ceRNA network and identify the lncRNA signature as prognostic factors for survival prediction.MethodsThe lncRNAs with overall survival significance were used to construct the ceRNA network. Function enrichment, protein-protein interaction, and cluster analysis were performed for dysregulated mRNAs. Multivariate Cox proportional hazards regression was performed to screen the potential prognostic lncRNAs. RT-qPCR was used to measure the relative expression levels of lncRNAs in cell lines. CCK8 assay was used to assess the proliferation of GC cells transfected with sh-lncRNAs.ResultsDifferentially expressed genes were identified including 585 lncRNAs, 144 miRNAs, and 2794 mRNAs. The ceRNA network was constructed using 35 DElncRNAs associated with overall survival of GC patients. Functional analysis revealed that these dysregulated mRNAs were enriched in cancer-related pathways, including TGF-beta, Rap 1, calcium, and the cGMP-PKG signalling pathway. A multivariate Cox regression analysis and cumulative risk score suggested that two of those lncRNAs (LINC01644 and LINC01697) had significant prognostic value. Furthermore, the results indicate that LINC01644 and LINC01697 were upregulated in GC cells. Knockdown of LINC01644 or LINC01697 suppressed the proliferation of GC cells.ConclusionsThe authors identified 2-lncRNA signature in ceRNA regulatory network as prognostic biomarkers for the prediction of GC patient survival and revealed that silencing LINC01644 or LINC01697 inhibited the proliferation of GC cells.

Dataset Information

LncRNA MSC-AS1 Is a Diagnostic Biomarker and Predicts Poor Prognosis in Patients With Gastric Cancer by Integrated Bioinformatics Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets