BackgroundThe expression of circular RNA (circRNA) may affect tumor progression. However, there have been no systemic meta-analysis for cancer diagnosis by using circRNAs in clinical till now. Herein, we aimed to collect and examined all the evidence on the potential role of circRNA as novel biomarker in human cancers.MethodsA comprehensive search strategy was used to search relevant literatures in the databases of PubMed, Embase, and the Web of Science from 2015 to August 2017. The correlation between circRNA expression and the diagnostic accuracy of tumor markers was analyzed. The methodological quality of each study was assessed by quality assessment for the diagnostic accuracies of the eligible studies (QUADAS-2). Statistical analysis was performed by applying the STATA (version 12.0) software.ResultsThe present meta-analysis included 1752 patients with circRNA expression data of tumor and paired adjacent non-tumorous tissues from 17 publications (19 studies). The pooled sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic OR (DOR) with their 95% confidential intervals (95%CIs), and AUC values were 0.72 (0.67–0.76), 0.74 (0.69–0.78), 2.80 (2.40–3.10), 0.38 (0.33–0.44), 7.00 (6.00–9.00), and 0.79, respectively. Subgroup analyses showed that the expression of circRNA in tissues of hepatocellular carcinoma (HCC) group was more prone to be detected than other tumor types, with a high values of the specificity, DOR, and AUC.ConclusionscircRNAs might be suitable as diagnostic biomarkers for tumors, especially in HCC diagnosis. Further prospective studies on the diagnostic value of circRNAs from the different tumors are needed in the future.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4213-0) contains supplementary material, which is available to authorized users.

Surface-enhanced Raman scattering (SERS), owing to its high sensitivity based on localized surface plasmon resonance of nanostructured metals, is recently attracting much attention to be used for biotechnology, such as cell imaging and tumor therapy. On the other hand, the trace detection of bio-molecules with large molecular weight is still challenging because the troublesome treatment of SERS substrate using coupling or cross-linking agents is required. In this paper, we apply liquid interface assisted SERS (LI-SERS) method, which provides unique features of collection and self-immobilization of analyte molecules on the SERS substrate, to realize the label-free trace detection of bio-molecules with detection limits of pM ~ fM. Specifically, deoxyribonucleic acid (DNA) discrimination and quantitative detection of β-Amyloid (Aβ) in trace-concentration are demonstrated to illustrate the ultrahigh sensitivity and versatility of the LI-SERS method. The results suggest LI-SERS is promising for the early-stage diagnosis of diseases such as virus infection and Alzheimer's disease.

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