Long noncoding RNA PICSAR/miR-588/EIF6 axis regulates tumorigenesis of hepatocellular carcinoma by activating PI3K/AKT/mTOR signaling pathway.
Zhikui LiuHuanye MoLiankang SunLiang WangTianxiang ChenBowen YaoRunkun LiuYongshen NiuKangsheng TuQiuran XuNan YangPublished in: Cancer science (2020)
Accumulating evidence has identified long noncoding RNAs (lncRNAs) as regulators in tumor progression and development. Here, we elucidated the function and possible molecular mechanisms of the effect of lncRNA-PICSAR (p38 inhibited cutaneous squamous cell carcinoma associated lincRNA) on the biological behaviors of HCC. In the present study, we found that PICSAR was upregulated in HCC tissues and cells and correlated with progression and poor prognosis in HCC patients. Gain- and loss-of-function experiments indicated that PICSAR enhanced cell proliferation, colony formation, and cell cycle progression and inhibited apoptosis of HCC cells. PICSAR could function as a competing endogenous RNA by sponging microRNA (miR)-588 in HCC cells. Mechanically, miR-588 inhibited HCC progression and alternation of miR-588 reversed the promotive effects of PICSAR on HCC cells. In addition, we confirmed that eukaryotic initiation factor 6 (EIF6) was a direct target of miR-588 in HCC and mediated the biological effects of miR-588 and PICSAR in HCC, resulting in PI3K/AKT/mTOR pathway activation. Our data identified PICSAR as a novel oncogenic lncRNA associated with malignant clinical outcomes in HCC patients. PICSAR played an oncogenic role by targeting miR-588 and subsequently promoted EIF6 expression and PI3K/AKT/mTOR activation in HCC. Our results revealed that PICSAR could be a potential prognostic biomarker and therapeutic target for HCC.
Keyphrases
- cell proliferation
- long noncoding rna
- long non coding rna
- poor prognosis
- cell cycle
- cell cycle arrest
- induced apoptosis
- pi k akt
- signaling pathway
- squamous cell carcinoma
- end stage renal disease
- endoplasmic reticulum stress
- chronic kidney disease
- oxidative stress
- cell death
- ejection fraction
- gene expression
- machine learning
- transcription factor
- risk assessment
- lymph node metastasis
- locally advanced