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Dysregulated Expression of Circular RNAs Serve as Prognostic and Clinicopathological Markers in Cancer.

ABSTRACT: Purpose: Circular RNAs (circRNAs) as prognostic biomarkers have spurred considerable interest in several types of tumors. In the present study, we aimed to elucidate the clinicopathological and prognostic values of circRNAs in human cancer. Methods: We systematically searched PubMed Central (PMC), PubMed, Web of Science, EMBASE, Scopus, CBM and the Cochrane Library databases up to Nov 29, 2018. Eligible studies reporting on the association between circRNAs expression and clinicopathological and prognostic outcomes in cancer were incorporated. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess clinicopathological parameters, and hazard ratios (HRs) and 95% CIs to estimate overall survival (OS). Results: Thirty-two studies involving 4529 patients were incorporated into our meta-analysis. Pooled results showed that high expression of oncogenic circRNAs was significantly associated with poor clinicopathological characteristics (tumor size: OR=1.29, 95%Cl: 1.10-1.51; TNM stage: OR=1.62, 95%Cl: 1.41-1.87; differentiation grade: OR=1.41, 95%Cl: 1.11-1.78; lymph node metastasis: OR=1.69; 95%Cl: 1.34-2.13; distant metastasis: OR=2.75; 95%Cl: 1.92-3.95) and a poor prognosis (OS: HR=2.75; 95%Cl: 2.34-3.15). Furthermore, we found that high expression of tumor-suppressor circRNAs was correlated with improved clinical characteristics (tumor size: OR=0.72; 95%Cl: 0.56-0.92; TNM stage: OR=0.77, 95%Cl: 0.68-0.88) and longer survival times (OS: HR=0.49; 95%Cl: 0.42-0.56). Subgroup analyses based on cancer types and circRNA types were also performed. Conclusion: Our study indicates that circRNAs may serve as important biomarkers for clinicopathologic features and prognosis in human cancer.

SUBMITTER: Huang X

PROVIDER: S-EPMC6547981 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Pancreatic cancer (PC) is a highly aggressive malignant tumor with a high mortality rate. It is urgent to find optimal molecular targets for the early diagnosis and treatment of PC. Here, we aimed to systematically analyze the prognostic, diagnostic, and clinicopathological significance of circular RNAs (circRNAs) in PC. Relevant studies were screened through PubMed, Web of Science, and other databases. The prognostic value of PC-associated circRNAs was assessed using the composite hazard ratio (HR), the diagnostic performance was assessed using the area under the summary receiver operator characteristic (SROC) curve (AUC), and the correlation with clinicopathological characteristics using the composite odds ratio (OR) was explored. In our study, 48 studies were included: 34 for prognosis, 11 for diagnosis, and 30 for correlation with clinicopathological characteristics. For prognosis, upregulated circRNAs were associated with poorer overall survival (OS) (HR = 2.02) and disease-free survival/progression-free survival (HR = 1.84) while downregulated circRNAs were associated with longer OS (HR = 0.55). Notably, the combination of circRNAs, including hsa_circ_0064288, hsa_circ_0000234, hsa_circ_0004680, hsa_circ_0071036, hsa_circ_0000677, and hsa_circ_0001460, was associated with worse OS (HR = 2.35). For diagnosis, the AUC was 0.83, and the pooled sensitivity and specificity were 0.79 and 0.73, respectively. For clinicopathologic characteristics, upregulated circRNAs were associated with poorer tumor differentiation, more nerve and vascular invasion, higher T stage, lymphatic metastasis, distant metastasis, advanced TNM stage, and higher preoperative CA19-9 level. In contrast, downregulated circRNAs were negatively associated with PC differentiation and lymphatic metastasis. Overall, our results showed that circRNAs are closely related to the prognosis and clinicopathological characteristics of PC patients and could be utilized for early diagnosis; thus, they are promising biomarkers for clinical application in PC.

Project description:BackgroundWhile most differential coexpression (DC) methods are bound to quantify a single correlation value for a gene pair across multiple samples, a newly devised approach under the name Correlation by Individual Level Product (CILP) revolutionarily projects the summary correlation value to individual product correlation values for separate samples. CILP greatly widened DC analysis opportunities by allowing integration of non-compromised statistical methods.MethodsHere, we performed a study to verify our hypothesis that conditional relationships, i.e., gene pairs of remarkable differential coexpression, may be sought as quantitative prognostic markers for human cancers. Alongside the seeking of prognostic gene links in a pan-cancer setting, we also examined whether a trend of global expression correlation loss appeared in a wide panel of cancer types and revisited the controversial subject of mutual relationship between the DE approach and the DC approach.ResultsBy integrating CILP with classical univariate survival analysis, we identified up to 244 conditional gene links as potential prognostic markers in five cancer types. In particular, five prognostic gene links for kidney renal papillary cell carcinoma tended to condense around cancer gene ESPL1, and the transcriptional synchrony between ESPL1 and PTTG1 tended to be elevated in patients of adverse prognosis. In addition, we extended the observation of global trend of correlation loss in more than ten cancer types and empirically proved DC analysis results were independent of gene differential expression in five cancer types.ConclusionsCombining the power of CILP and the classical survival analysis, we successfully fetched conditional transcriptional relationships that conferred prognosis power for five cancer types. Despite a general trend of global correlation loss in tumor transcriptomes, most of these prognosis conditional links demonstrated stronger expression correlation in tumors, and their stronger coexpression was associated with poor survival.

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Dysregulated Expression of Circular RNAs Serve as Prognostic and Clinicopathological Markers in Cancer.

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