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Analysis of distinct long noncoding RNA transcriptional fingerprints in pancreatic ductal adenocarcinoma.


ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal malignancies with the worst prognosis. Recent studies have demonstrated that long noncoding RNAs (lncRNAs) play critical roles in tumorigenesis and cancer progression. However, the expression pattern and roles of lncRNAs in the development of PDAC remain unknown. Herein, we globally analyzed the lncRNA expression profile in human PDAC and non-tumor tissues using four independent public microarray datasets from Gene Expression Omnibus (GEO). The analysis of GEO datasets by repurposing microarray probes confirmed that hundreds of lncRNAs are differentially expressed in PDAC tissues compared with normal tissues. We selected four lncRNAs including LINC00152, CASC9, LINC00226 and F11-AS1 for validation in PDAC cell lines and normal cells. Loss of function assays were performed to investigate the roles of LINC00152 and CASC9 in PDAC cell proliferation and invasion. Taken together, our findings demonstrate lncRNA expression alterations in PDAC and may provide new potential molecular markers for PDAC patient diagnosis and treatment.

SUBMITTER: Yu X 

PROVIDER: S-EPMC5345666 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Analysis of distinct long noncoding RNA transcriptional fingerprints in pancreatic ductal adenocarcinoma.

Yu Xiang X   Lin Yang Y   Sui Wu W   Zou Yanfen Y   Lv Zhongchuan Z  

Cancer medicine 20170221 3


Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal malignancies with the worst prognosis. Recent studies have demonstrated that long noncoding RNAs (lncRNAs) play critical roles in tumorigenesis and cancer progression. However, the expression pattern and roles of lncRNAs in the development of PDAC remain unknown. Herein, we globally analyzed the lncRNA expression profile in human PDAC and non-tumor tissues using four independent public microarray datasets from Gene  ...[more]

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