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Updated: Jan 21, 2026

Three-dimensional Alginate-bead Culture of Human Pituitary Adenoma Cells
Published on: February 18, 2016
Exosome-Transmitted lncRNA H19 Inhibits the Growth of Pituitary Adenoma
Yong Zhang1, Yan Ting Liu1,2, Hao Tang1
1Department of Neurosurgery, Center of Pituitary Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Context:
Our previous study demonstrated that the expression of long noncoding RNA (lncRNA) H19 was frequently downregulated in human primary pituitary adenomas and negatively correlated with tumor progression. However, the role of exosomal lncRNA H19 in the inhibition of pituitary tumor growth remains unclear.
Objective:
To investigate whether exosomal H19 could be transported across the cell membrane to exert its inhibitory effect on pituitary tumor growth.
Design:
Empty lentivirus GH3 cells with or without H19 overexpression were used to establish a xenograft model. Isolated exosomes were identified by transmission electron microscopy, nanoparticle tracking, and Western blotting. The expression levels of serum exosomal H19 from 200 healthy subjects and 206 patients with various subtypes of pituitary tumors were detected by ultracentrifugation and quantitative real-time PCR.
Results:
The growth of distal tumor cells was inhibited by transferring exosomal H19, which could be transported through cell membrane and exert its inhibitory effect. Cabergoline increased H19 expression and played a synergic therapeutic effect with exosomal H19. Exosomal H19 inhibited phosphorylation of the mTORC1 substrate 4E-BP1. Of note, the expression level of exosomal H19 in the patients with all subtypes of pituitary tumors was significantly lower than that in the healthy subjects. The change of plasma exosomal H19 level may be correlated with the prognosis or drug response of the patients.
Conclusion:
Exosomal H19 inhibits the growth of distal pituitary tumors through inhibiting 4E-BP1 phosphorylation. Plasma exosomal H19 may serve as an important biomarker for predicting medical responses of patients with prolactinomas.
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