Long noncoding RNA (lncRNA) maternal-expressed gene 3 (MEG3) is associated with proliferation of various tumor cells and has decreased expression in many types of cancers. In this study, we aimed at demonstrating the association between MEG3 polymorphisms and the risk of lung cancer in northeast China. There were 526 lung cancer patients and 526 healthy controls included in this hospital-based case-control study. The genotyping of two polymorphisms, rs7158663 G > A and rs4081134 G>A, was performed by the Taqman allelic discrimination method. We found that MEG3 rs4081134-AA may be associated with the risk of lung cancer (AA vs. GG: adjusted odds ratio [OR] = 0.487, confidence interval [95% CI] = 0.257-0.897, p = 0.030; AA vs. AG+GG: adjusted OR = 0.522, 95% CI = 0.274-0.992, p = 0.047). Similar associations in several subgroups were found in subsequent stratified analysis. Further, there were no statistically significant interactions of rs4081134 polymorphism and smoking to lung cancer susceptibility. In addition, the associations between the MEG3 rs7158663 polymorphism and lung cancer susceptibility were not found. These results indicate that the MEG3 rs4081134 polymorphism was significantly associated with lung cancer susceptibility in the Chinese population.

Background Recently, accumulating evidence have revealed that circular RNA (circRNA) was deregulated in multiple types of cancer, suggesting that circRNA might serve as a novel candidate biomarker of cancer diagnosis. However, inconsistent results have become an obstacle in applying circRNAs to clinical practice. The aim of this study is to evaluate diagnostic value of circRNAs among cancers. Methods A literature search was systematically performed among PubMed, Sciencedirect, Cochrane Library, Web of Science, Wanfang, and Chinese National Knowledge Infrastructure databases up to February 15, 2019. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratios, negative likelihood ratios, diagnostic odds ratio, and area under the SROC curve (AUC) were applied to evaluate diagnostic performance of circRNAs. Results In total, the study included 64 studies with single circRNA and 13 studies with combined circRNAs. Overall, the study presented that a single circRNA had moderate diagnostic value, with a SEN of 0.75, a SPE of 0.76, and an AUC of 0.82. The plasma circRNAs had higher diagnostic accuracy than tissue (AUC: 0.87, 95% confidence interval [CI]: 0.83–0.89 for plasma/serum subgroup; AUC: 0.79, 95% CI: 0.75–0.82 for tissue subgroup). Furthermore, the combined circRNAs had good diagnostic efficacy for GC, with a SEN of 0.89, a SPE of 0.94, and an AUC of 0.97, respectively. Conclusion This study confirmed that circRNAs may be candidate biomarkers for cancer diagnosis. In particular, diagnosis of combined circRNAs will be a new alternative applied to clinical research and practice for cancer.

BackgroundThe aberrant regulation of MALAT1 has been indicated to be involved in various carcinogenic pathways contributing to the tumourigenesis and progression of cancers. The current meta-analysis summarized the research advances of MALAT1 functions and analyzed its prognostic value among multiple types of cancers.MethodsEligible studies were identified through retrieving the PubMed, Web of Science, and CNKI databases, up to Mar 1, 2018. 28 studies of 5436 patients and 36 studies of 3325 patients were enrolled in the meta-analysis to evaluate the association of MALAT1 expression with survival outcomes and clinical parameters.ResultsThe results demonstrated that over-expression of MALAT1 may predict lymph node metastasis (pooled OR = 2.335, 95% CI 1.606–3.395, P = 0.000) and distant metastasis (pooled OR = 2.456, 95% CI 1.407–4.286, P = 0.002). Moreover, MALAT1 was also related with tumour size (pooled OR = 1.875, 95% CI 1.257–2.795, P = 0.002) and TNM stage (pooled OR = 2.034, 95% CI 1.111–3.724, P = 0.021). Additionally, elevated MALAT1 expression could predict poor OS (pooled HR = 2.298, 95% CI 1.953–2.704, P = 0.000), DFS (pooled HR = 2.036, 95% CI 1.240–3.342, P = 0.005), RFS (pooled HR = 2.491, 95% CI 1.505–4.123, P = 0.000), DSS (pooled HR = 2.098, 95% CI 1.372–3.211, P = 0.001) and PFS (pooled HR = 1.842, 95% CI 1.138–2.983, P = 0.013) in multivariate model. Importantly, subgroup analyses disclosed that increased MALAT1 expression had a poor OS among different cancer types (Estrogen-dependent cancer: pooled HR = 2.656, 95% CI 1.560–4.523; urological cancer: pooled HR = 1.952, 95% CI 1.189–3.204; glioma: pooled HR = 2.315, 95% CI 1.643–3.263; digestive cancer: pooled HR = 2.451, 95% CI 1.862–3.227).ConclusionsThe present findings demonstrated that MALAT1 may be a novel biomarker for predicting survival outcome, lymph node metastasis and distant metastasis.Electronic supplementary materialThe online version of this article (10.1186/s12935-018-0606-z) contains supplementary material, which is available to authorized users.