miR-18a has been reported to be upregulated in nasopharyngeal carcinoma (NPC) tissues by microarray assays. However, the roles and the underlying mechanisms of miR-18a in NPC remain poorly understood. Here we demonstrated by real-time RT-PCR that miR-18a expression is upregulated in NPC tissues, and positively correlated with tumor size and TNM stage. Moreover, miR-18a expression could be upregulated by NF-κB activation or Epstein-Barr virus encoded latent membrane protein 1 expression. The ectopic expression of miR-18a promoted NPC cell proliferation, migration and invasion, while the repression of miR-18a had opposite effects. Candidate genes under regulation by miR-18a were screened out through a whole-genome microarray assay, further identified by a reporter assay and verified in clinical samples. SMG1, a member of the phosphoinositide 3-kinase-related kinases family and an mTOR antagonist, was identified as functional target of miR-18a. Our results confirmed that miR-18a exerts its oncogenic role through suppression of SMG1 and activation of mTOR pathway in NPC cells. Importantly, in vivo xenograft tumor growth in nude mice was effectively inhibited by intratumor injection of miR-18a antagomir. Our data support an oncogenic role of miR-18a through a novel miR-18a/SMG1/mTOR axis and suggest that the antitumor effects of antagomir-18a may make it suitable for NPC therapy.

MicroRNAs (miRNAs) are short noncoding RNAs that play critical roles in human malignancies and can be used as biomarkers for cancer. Until now, a number of biomarkers for prognosis of glioblastoma (GBM) have been reported in tumor tissues but only a few biomarkers in circulating fluid. Using a custom microarray, we previously identified 19 differentially expressed miRNAs in serum of patients with GBM. In this study, we investigated whether 3 of the 19 miRNAs in serum could be used as prognostic biomarkers for patients with GBM. We first validated the serum levels of 3 candidate miRNAs in an independent cohort of 24 GBM patients and 12 healthy volunteers by real-time quantitative reverse transcription PCR (qRT-PCR), and then evaluated the prognostic value of these miRNAs in a total of 36 GBM patients. The results show that the serum levels of the 3 miRNAs (miR-451a, miR-485-3p and miR-4298) determined by qRT-PCR are significantly different between 24 GBM patients and 12 healthy volunteers (all P <0.05) and are in concordance with the results of microarray analysis. High serum level of miR-451a is correlated with positive tumor O(6)-methylguanine-DNA methyltransferase (MGMT) expression (P = 0.040). Survival analysis showed that low serum miR-485-3p level is associated with poor progression-free survival (PFS) (P < 0.004) and overall survival (OS) (P < 0.023). Furthermore, univariate and multivariate Cox analyses demonstrated that that serum miR-485-3p expression is a significant independent prognostic factor for PFS and OS in GBM patients. In conclusion, serum miR-485-3p level is reduced and might be a potential prognostic biomarker in GBM patients.

Background Long non-coding RNAs (lncRNAs) have been reported to be prognostic biomarkers in many types of cancer. We aimed to identify a lncRNA signature that can predict the prognosis in patients with esophageal squamous cell carcinoma (ESCC). Methods Using a custom microarray, we retrospectively analyzed lncRNA expression profiles in 141 samples of ESCC and 81 paired non-cancer specimens from Sun Yat-Sen University Cancer Center (Guangzhou, China), which were used as a training cohort to identify a signature associated with clinical outcomes. Then we conducted quantitative RT-PCR in another 103 samples of ESCC from the same cancer center as an independent cohort to verify the signature. Results Microarray analysis showed that there were 338 lncRNAs significantly differentially expressed between ESCC and non-cancer esophagus tissues in the training cohort. From these differentially expressed lncRNAs, we found 16 lncRNAs associated with overall survival (OS) of ESCC patients using Cox regression analysis. Then a 7-lncRNA signature for predicting survival was identified from the 16 lncRNAs, which classified ESCC patients into high-risk and low-risk groups. Patients with high-risk have shorter OS (HR: 3.555, 95% CI 2.195–5.757, p < 0.001) and disease-free survival (DFS) (HR: 2.537, 95% CI 1.646–3.909, p < 0.001) when compared with patients with low-risk in the training cohort. In the independent cohort, the 7 lncRNAs were detected by qRT-PCR and used to compute risk score for the patients. The result indicates that patients with high risk also have significantly worse OS (HR = 2.662, 95% CI 1.588–4.464, p < 0.001) and DFS (HR 2.389, 95% CI 1.447–3.946, p < 0.001). The univariate and multivariate Cox regression analyses indicate that the signature is an independent factor for predicting survival of patients with ESCC. Combination of the signature and TNM staging was more powerful in predicting OS than TNM staging alone in both the training (AUC: 0.772 vs 0.681, p = 0.002) and independent cohorts (AUC: 0.772 vs 0.660, p = 0.003). Conclusions The 7-lncRNA signature is a potential prognostic biomarker in patients with ESCC and may help in treatment decision when combined with the TNM staging system.