Dataset Information

The clinical value of lncRNA NEAT1 in digestive system malignancies: A comprehensive investigation based on 57 microarray and RNA-seq datasets.

ABSTRACT: This comprehensive investigation was performed to evaluate the expression level and potential clinical value of NEAT1 in digestive system malignancies. A total of 57 lncRNA datasets of microarray or RNA-seq and 5 publications were included. The pooled standard mean deviation (SMD) indicated that NEAT1 was down-regulated in esophageal carcinoma (ESCA, SMD = -0.35, 95% CI: -0.5~-0.20, P < 0.0001) and hepatocellular carcinoma (HCC, SMD = -0.47, 95% CI: -0.60~-0.34, P < 0.0001), while in pancreatic cancer (PC), NEAT1 was up-regulated (SMD = 0.45, 95% CI: 0.2~0.71, P = 0.001). However, NEAT1 expression in gastric cancer (GC), colorectal cancer (CRC), biliary tract cancer (BTC) and gallbladder carcinoma (GBC) showed no significant difference between cancer and control groups. The pooled area under the curve values for ESCA, GC, CRC, PC and HCC were 0.60, 0.89, 0.81, 0.77 and 0.69, respectively. Furthermore, our result demonstrated that a high expression of NEAT1 predicted an unfavorable prognosis in patients with digestive system malignancies (HR: 1.50, 95% CI: 1.28-1.76, P < 0.0001). Our study suggests that NEAT1 may play different roles in the initiation and progression of digestive system cancers and could be a potential diagnostic and prognostic biomarker in patients with digestive system carcinomas. Further and stricter studies with a larger number of cases are necessary to strengthen our conclusions.

SUBMITTER: Xiong DD

PROVIDER: S-EPMC5392277 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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The clinical value of lncRNA NEAT1 in digestive system malignancies: A comprehensive investigation based on 57 microarray and RNA-seq datasets.

Xiong Dan-Dan DD Feng Zhen-Bo ZB Cen Wei-Luan WL Zeng Jing-Jing JJ Liang Lu L Tang Rui-Xue RX Gan Xiao-Ning XN Liang Hai-Wei HW Li Zu-Yun ZY Chen Gang G Luo Dian-Zhong DZ

Oncotarget 20170301 11

This comprehensive investigation was performed to evaluate the expression level and potential clinical value of NEAT1 in digestive system malignancies. A total of 57 lncRNA datasets of microarray or RNA-seq and 5 publications were included. The pooled standard mean deviation (SMD) indicated that NEAT1 was down-regulated in esophageal carcinoma (ESCA, SMD = -0.35, 95% CI: -0.5~-0.20, P < 0.0001) and hepatocellular carcinoma (HCC, SMD = -0.47, 95% CI: -0.60~-0.34, P < 0.0001), while in pancreatic ...[more]

PMID: 28118609

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Project description:ObjectiveCoronavirus disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The clinical and epidemiological analysis reported the association between SARS-CoV-2 and neurological diseases. Among neurological diseases, Alzheimer's disease (AD) has developed as a crucial comorbidity of SARS-CoV-2. This study aimed to understand the common transcriptional signatures between SARS-CoV-2 and AD.Materials and methodsSystem biology approaches were used to compare the datasets of AD and COVID-19 to identify the genetic association. For this, we have integrated three human whole transcriptomic datasets for COVID-19 and five microarray datasets for AD. We have identified differentially expressed genes for all the datasets and constructed a protein-protein interaction (PPI) network. Hub genes were identified from the PPI network, and hub genes-associated regulatory molecules (transcription factors and miRNAs) were identified for further validation.ResultsA total of 9,500 differentially expressed genes (DEGs) were identified for AD and 7,000 DEGs for COVID-19. Gene ontology analysis resulted in 37 molecular functions, 79 cellular components, and 129 biological processes were found to be commonly enriched in AD and COVID-19. We identified 26 hub genes which includes AKT1, ALB, BDNF, CD4, CDH1, DLG4, EGF, EGFR, FN1, GAPDH, INS, ITGB1, ACTB, SRC, TP53, CDC42, RUNX2, HSPA8, PSMD2, GFAP, VAMP2, MAPK8, CAV1, GNB1, RBX1, and ITGA2B. Specific miRNA targets associated with Alzheimer's disease and COVID-19 were identified through miRNA target prediction. In addition, we found hub genes-transcription factor and hub genes-drugs interaction. We also performed pathway analysis for the hub genes and found that several cell signaling pathways are enriched, such as PI3K-AKT, Neurotrophin, Rap1, Ras, and JAK-STAT.ConclusionOur results suggest that the identified hub genes could be diagnostic biomarkers and potential therapeutic drug targets for COVID-19 patients with AD comorbidity.

Dataset Information

The clinical value of lncRNA NEAT1 in digestive system malignancies: A comprehensive investigation based on 57 microarray and RNA-seq datasets.

Publications

The clinical value of lncRNA NEAT1 in digestive system malignancies: A comprehensive investigation based on 57 microarray and RNA-seq datasets.

Similar Datasets

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