Characterization of a Long Non-Coding RNA, the Antisense RNA of Na/K-ATPase α1 in Human Kidney Cells

LncRNA ATP1A1-AS1 inhibits cell proliferation and promotes cell apoptosis in thyroid carcinoma by regulating the miR-620/IRF2BP2 axis

BACKGROUND

Thyroid carcinoma (THCA) is a common malignancy of the endocrine system. Further understanding of the molecular mechanism underlying THCA is crucial to develop effective diagnostic therapy and improve its treatments. In this study, we intended to provide novel direction for THCA targeted therapy from the aspect of lncRNA-miRNA-mRNA interaction. We aimed to investigate the function and molecular mechanism of lncRNA ATP1A1-AS1 in THCA.

METHODS

Gene expression was assessed by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Cell growth was detected by CCK-8 and EdU assays. Flow cytometry was applied for analyzing cell apoptosis. The binding of ATP1A1-AS1 or IRF2BP2 to miR-620 was validated by RNA pulldown and luciferase reporter assays. The protein levels were examined by western blotting.

RESULTS

ATP1A1-AS1 was decreased in THCA cells and tissues. ATP1A1-AS1 overexpression attenuated cell growth and promoted apoptosis. MiR-620, which was upregulated in THCA, was identified as a direct target of ATP1A1-AS1. Furthermore, IRF2BP2 was discovered to be a target of miR-620, which displayed low expression in THCA cells and tissues. Importantly, IRF2BP2 knockdown reversed the influence of ATP1A1-AS1 overexpression on THCA cell proliferation and apoptosis.

CONCLUSIONS

LncRNA ATP1A1-AS1 inhibited cell growth and promotes apoptosis in THCA via the miR-620/IRF2BP2 axis.

Identifying 4 Novel lncRNAs as Potential Biomarkers for Acute Rejection and Graft Loss of Renal Allograft

Acute rejection (AR) after kidney transplant is one of the major obstacles to obtain ideal graft survival. Reliable molecular biomarkers for AR and renal allograft loss are lacking. This study was performed to identify novel long noncoding RNAs (lncRNAs) for diagnosing AR and predicting the risk of graft loss. The several microarray datasets with AR and nonrejection specimens of renal allograft downloaded from Gene Expression Omnibus database were analyzed to screen differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). Univariate and multivariate Cox regression analyses were used to identify optimal prognosis-related DElncRNAs for constructing a risk score model. 39 common DElncRNAs and 185 common DEmRNAs were identified to construct a lncRNA-mRNA regulatory relationship network. DElncRNAs were revealed to regulate immune cell activation and proliferation. Then, 4 optimal DElncRNAs, ATP1A1-AS1, CTD-3080P12.3, EMX2OS, and LINC00645, were selected from 17 prognostic DElncRNAs to establish the 4-lncRNA risk score model. In the training set, the high-risk patients were more inclined to graft loss than the low-risk patients. Time-dependent receiver operating characteristics analysis revealed the model had good sensitivity and specificity in prediction of 1-, 2-, and 3-year graft survival after biopsy (AUC = 0.891, 0.836, and 0.733, respectively). The internal testing set verified the result well. Gene set enrichment analysis which expounded NOD-like receptor, the Toll-like receptor signaling pathways, and other else playing important role in immune response was enriched by the 4 lncRNAs. Allograft-infiltrating immune cells analysis elucidated the expression of 4 lncRNAs correlated with gamma delta T cells and eosinophils, etc. Our study identified 4 novel lncRNAs as potential biomarkers for AR of renal allograft and constructed a lncRNA-based model for predicting the risk of graft loss, which would provide new insights into mechanisms of AR.