Inferences of individual differences in response to tripterysium glycosides across patients with Rheumatoid arthritis using a novel ceRNA regulatory axis.
Clin Transl Med
; 10(6): e185, 2020 Oct.
Article
in En
| MEDLINE
| ID: mdl-33135351
BACKGROUND: To identify biomarkers for guiding therapy and predicting clinical response of Tripterysium Glycosides Tablets (TGT) treatment is an urgent task due to individual differences in TGT response across rheumatoid arthritis (RA) patients. Competing endogenous RNA (ceRNA) regulatory system may influence drug response with involvement in diverse biological processes. Herein, we aimed to identify a TGT response-related ceRNA axis. METHODS: A TGT response-related ceRNA axis was screened according to clinical cohort-based RNA expression profiling, lncRNA-mRNA coexpression, and ceRNA network analyses. Its clinical relevance was evaluated by computational modeling. Regulatory mechanisms of ceRNA axis were also experimentally investigated. RESULTS: The ceRNA regulatory axis combined with lncRNA ENST00000494760, miR-654-5p, and C1QC was identified as a candidate biomarker for RA patients' response to TGT. Both ENST00000494760 and C1QC mRNA expression were significantly lower, while miR-654-5p expression was dramatically higher in TGT responders than nonresponders. Its clinical relevance was verified by computational modeling based on both independent clinical validation cohort and collagen-induced arthritis (CIA) mice. Mechanistically, miR-654-5p directly bound to the 3'-untranslated region of both ENST00000494760 and C1QC mRNA to inhibit their expression. Moreover, miR-654-5p suppressed C1QC mRNA expression, but ENST00000494760 bound to miR-654-5p and relieved its repression on C1QC mRNA, leading to RA aggressive progression and weak TGT response. CONCLUSIONS: LncRNA ENST00000494760 overexpression may sponge miR-654-5p to promote C1QC expression in RA patients. This novel ceRNA axis may serve as a biomarker for screening the responsive RA patients to TGT treatment, which will allow improved personalized healthcare.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
Language:
En
Journal:
Clin Transl Med
Year:
2020
Document type:
Article
Country of publication: