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SPP1 functions as an enhancer of cell growth in hepatocellular carcinoma targeted by miR-181c.


ABSTRACT: Patients diagnosed with hepatocellular carcinoma (HCC) suffered a high risk of recurrence and poor prognosis. Identification of differentially expressed genes (DEGs) in HCC provides potential biomarkers for evaluating prognosis and specific therapeutic treatments. In this study, DEGs over-expressed in HCC specimens with a fold change over 2.0 were collected through integrative bioinformatics analysis from GEO datasets. Gene ontology and KEGG pathway enrichment were conducted by applying DAVID database. We noticed Secreted phosphoprotein 1 (SPP1) as one of the signature genes up-regulated in HCC tissues with a close relation to the tumor process. Eighty-seven paired HCC specimens from our medical center were explored to verify the aberrant expression of SPP1 by IHC and qRT-PCR assay. Depletion of SPP1 in HCC Hep3B cells was established. The cell proliferation was impaired in SPP1 depleted cells, along with a resistance of cell apoptosis by down-regulating SPP1. Intriguingly, we further validated a direct interaction between miR-181c and SPP1, which indicated a post-transcriptional regulation mechanism of SPP1 in HCC. Thus, our results suggest that SPP1 may function as an enhancer of HCC growth targeted by miR-181c, and probably provide us an innovational target for HCC diagnose and therapeutic treatment.

SUBMITTER: Wang J 

PROVIDER: S-EPMC6895505 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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SPP1 functions as an enhancer of cell growth in hepatocellular carcinoma targeted by miR-181c.

Wang Junqing J   Hao Fengjie F   Fei Xiaochun X   Chen Yongjun Y  

American journal of translational research 20191115 11


Patients diagnosed with hepatocellular carcinoma (HCC) suffered a high risk of recurrence and poor prognosis. Identification of differentially expressed genes (DEGs) in HCC provides potential biomarkers for evaluating prognosis and specific therapeutic treatments. In this study, DEGs over-expressed in HCC specimens with a fold change over 2.0 were collected through integrative bioinformatics analysis from GEO datasets. Gene ontology and KEGG pathway enrichment were conducted by applying DAVID da  ...[more]

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