Genome-wide analysis of long noncoding RNA (lncRNA) expression in hepatoblastoma tissues
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Rui Dong
PROVIDER: E-GEOD-51701 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We performed a genome-wide analysis of lncRNA expression in hepatoblastoma tissues to identify novel targets for further study of hepatoblastoma.We found that 2736 lncRNAs were differentially expressed in hepatoblastoma tissues.
2013-12-31 | GSE51701 | GEO
Project description:Recent studies show that long non-coding RNAs (lncRNAs) play crucial roles in human cancers. However, functional lncRNAs and their downstream mechanisms are largely unknown in the molecular pathogenesis of intrahepatic cholangiocarcinoma (ICC) and its progression. In the present study, we performed transcriptomic profiling of five ICC and paired adjacent noncancerous tissues (N) using lncRNA and mRNA microarrays to identify relevant biomarkers in ICC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the microarray results. We sought correlations between the expression levels of lncRNAs and those of target genes. Clinicopathological characteristics and overall survival were compared using the t-test and the Kaplan–Meier method, respectively. A total of 3,054 and 2,111 lncRNAs were significantly up- and down-regulated(fold change?2, p?0.05) in ICC tissues compared to the adjacent NT samples. Bioinformatic analysis indicated that most such genes were related to carcinogenesis, hepatic system disease, and signal transduction. Positive correlations were evident between four pairs of lncRNAs and target mRNAs (RNA43085 and SULF1, RNA47504 and KDM8, RNA58630 and PCSK6, and RNA40057 and CYP2D6). In addition, some lncRNAs and mRNAs were significantly associated with clinicopathological characteristics. The cumulative overall survival rate was significantly associated with low-level expression of CYP2D6 (p=0.005) and PCSK6 (p=0.038). And patients with high expression levels of CYP2D6 and RNA40057 have significant better prognosis (p=0.014). Our results suggested that lncRNA expression profile in ICC tissues is profoundly different from that in NT samples. The lncRNA signature could be used as a biomarker for the prognosis of patients with ICC. Furthermore, the combination of lncRNA and mRNA can reliably predict the survival. The lncRNA expression profiles of cancer and adjacent normal tissues form 5 ICC patients were studied by microarray and an combination of lncRNA and mRNA could be used as a biomarker for the prognosis of patients with ICC
2014-09-30 | E-GEOD-61850 | biostudies-arrayexpress
Project description:Long noncoding RNAs (lncRNAs) are a class of non-coding RNAs longer than 200 nt that function in endogenous gene regulation and tumorigenesis. Hepatocellular carcinoma (HCC) is a heterogeneous disease with different treatment outcome. It is a challenge to develop a prognostic marker to identify HCC patients who are at greatest risk for recurrence or death. In this study, we try to screen lncRNAs whose expression levels are associated with recurrence or death of HCC patients through an extensive lncRNA profiling study on a cohort of 59 HCC patients. For these experiments, we used RNA extracted from 59 HCC tissues and 20 normal livers. Total RNAs from the 20 normal livers were pooled and used as a reference for all microarray experiments. For each microarray experiment, Cy5-labeled probes derived from the DNase-treated total RNA from each HCC sample was hybridized against Cy3-labeled probes derived from common reference on Arraystar Human LncRNA Microarray (Arraystar, Rockville, USA). LncRNAs whose expression was significantly associated with disease-specific survival and time to recurrence were selected based on microarray data. The univariate Cox proportional hazards model was used to assess the association of lncRNAs with survival. We computed a statistical significance level (P value) for two endpointsM-bM-^@M-^Tthe time to cancer-related death and time to recurrence, based on univariate Cox proportional hazards models in BRB-ArrayTools version 4.2.0.
2012-08-16 | E-GEOD-40144 | biostudies-arrayexpress
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.
2014-03-07 | E-GEOD-53622 | biostudies-arrayexpress
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.
2014-03-07 | E-GEOD-53624 | biostudies-arrayexpress
Project description:This study aimed to further our understanding of the role that hypermethylatioted in cancer 1 (HIC1) plays in prostate cancer (PCa) development. Microarrays were searched for some genes that had correlated expression with HIC1 mRNA. Our data showed that HIC1 promoter hypermethylation was presented in cell lines, tissues and plasma of PCa patients. According to fold-change screening between restoring expression of HIC1 and its respective control cells, both up-regulated and down-regulated genes were commonly observed in PC3 and C4-2B cells. The restoring expression HIC1 in PCa lines were respectively noted as PC3-HIC1 and C4-2B-HIC1 cells, and the respective controls were noted as C4-2B-GFP and PC3-GFP cells.
2012-11-17 | E-GEOD-42336 | biostudies-arrayexpress
Project description:To further development of our lncRNA and mRNA expression approach to pancreatic ductal adenocarcinoma(PDAC), we have employed lncRNA and mRNA microarray expression profiling as a discovery platform to identify lncRNA and mRNA expression in pancreatic ductal adenocarcinoma.Human pancreatic ductal adenocarcinoma tissues and normal pancreatic tissues from PDAC donors and other duodenum diseases donors. analyze mRNA and lncRNA expression in pancreatic ductal adenocarcinoma (PDAC) by microarray platform
2014-11-18 | E-GEOD-57144 | biostudies-arrayexpress
Project description:Genome-wide analysis of long noncoding RNA (lncRNA) expression in hepatoblastoma tissues
| PRJNA225914 | ENA
Project description:Expression data from hepatoblastoma tissues
| PRJNA543290 | ENA
Project description:Investigation of lncRNA expression profile of laryngeal cancer A seven chip study using total RNA extracted from 7 squamous cell carcinoma tissues and paired adjacent normal tissues
2014-07-23 | E-GEOD-59652 | biostudies-arrayexpress