These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Competing endogenous RNA network for esophageal cancer progression.
    Author: Chen S, Ju G, Gu J, Shi M, Wang Y, Wu X, Wang Q, Zheng L, Xiao T, Fan Y.
    Journal: Ann Transl Med; 2021 Sep; 9(18):1473. PubMed ID: 34734025.
    Abstract:
    BACKGROUND: Esophageal cancer (ESCA) constitutes one of the most common cancers worldwide. The identification of potential biomarkers is important to improving the diagnostic accuracy and treatment efficiency for patients with ESCA. In this study, we aimed to identify biomarkers related to ESCA progression through a comprehensive analysis of long non-coding RNAs (lncRNAs), microRNA (miRNAs), and mRNA expression profiles in ESCA. METHODS: Differentially expressed lncRNAs, miRNAs, and mRNAs (DElncRNAs, DEmiRNAs, and DEmRNAs, respectively) in ESCA samples compared with normal controls were obtained. A competing endogenous RNA (ceRNA) network consisting of interacting DElncRNAs, DEmiRNAs, and DEmRNAs was constructed using a combination of the miRCode and TargetScan databases. Relationships between RNAs in the ceRNA network and overall survival in patients with EC were explored through another independent ESCA dataset from The Cancer Genome Atlas. RESULTS: A total of 1,014 DElncRNAs, 3,677 DEmRNAs, and 35 DEmiRNAs were identified in ESCA samples compared with normal samples. Functional enrichment analysis indicated that the DEmRNAs were involved in cell activity, inflammatory response, and oxygen metabolism-related biological processes. A ceRNA network containing 5 DEmiRNAs, 582 DEmRNAs and 764 DElncRNAs was obtained. In the survival analysis, 39 genes were found to be significantly associated with overall survival in patients with EC, including GOLGA7, NFYB, TOP1, and TMTC3. CONCLUSIONS: Our study constructed a ceRNA network for ESCA for the first time, which will be helpful for the disease's diagnosis and treatment.
    [Abstract] [Full Text] [Related] [New Search]