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Predictive analysis of long non-coding RNA expression profiles in tumor and normal tissues from glioblastoma patients

ABSTRACT: We compared lncRNA expression data in tumor tissues from 9 patients and 3 healthy tissues by using an HlncOA 1.0 array. Data show that 185 lncRNAs, including 90 upregulated and 95 downregulated lncRNA transcripts, were significantly dysregulated in glioblastoma tissues. Then, 8 dysregulated lncRNAs were validated in another 50 samples of specimens using quantitative real-time polymerase chain reaction assays（qRT-PCR）. We predicted lncRNA-miRNA-mRNA networks by co-expressing lncRNA and mRNA with altered miRNA. Bioinformatic analysis was used to predict possible pathways in which these networks might be involved. Finally, we analyzed interactions between validated lncRNAs and their potential cancer-related miRNA targets to identify the potential roles of lncRNAs in glioblastomas.

ORGANISM(S): Homo sapiens

PROVIDER: GSE104267 | GEO | 2017/09/27

SECONDARY ACCESSION(S): PRJNA412196

REPOSITORIES: GEO

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Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.

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Predictive analysis of long non-coding RNA expression profiles in tumor and normal tissues from glioblastoma patients

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