Huiwen Mu1, Sujie Zhang1, Zhaoying Yao1, Yunxin Liu1,2, Kang Lin3, Zheng Zhao4,5, Yubing Zhu6,7. 1. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China. 2. Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. 3. Department of Clinical Laboratory, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. 4. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China. zhaozheng0322@126.com. 5. Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. zhaozheng0322@126.com. 6. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China. zyb86052002@163.com. 7. Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. zyb86052002@163.com.
Abstract
PURPOSE: Exosome-derived long non-coding RNAs (lncRNAs) as novel biomarkers are widely investigated in various cancers, yet results remain controversial. The aim of this meta-analysis was to clarify the diagnostic and prognostic value of exosome-derived lncRNAs in cancer. METHODS: PubMed, Web of Science, EMBASE, CNKI, and WanFang online databases were comprehensively searched for eligible studies up to January, 2020. To evaluate the diagnostic effect, sensitivity, specificity, and area under the curve (AUC) were pooled. Threshold effect, subgroup analysis, and meta-regression were applied to explore heterogeneity. Deeks' funnel plot and sensitivity analysis were used to examine publication bias and stability of meta-analysis, respectively. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and recurrence free survival (RFS) were calculated to assess the prognostic value. RESULTS: A total of 29 eligible studies involving 3882 patients were enrolled in the meta-analysis, which included 26 on diagnosis and 11 on prognosis. For diagnosis analysis, the pooled sensitivity, specificity, and AUC were 0.83 (95% CI 0.78-0.87), 0.80 (95% CI 0.75-0.84), and 0.88 (95% CI 0.85-0.91), respectively. Meta-regression revealed that the cancer type acted as the potential source of heterogeneity. Sensitivity analysis and Deeks' funnel plot indicated that results were relatively robust and had no publication bias. For the prognosis analysis, results suggested that overexpression of exosome-derived lncRNAs which upregulated in cancer showed a significant association with poor OS (HR 2.21, 95% CI 1.79-2.71, p < 0.001). Conversely, overexpression of exosome-derived lncRNAs which downregulated in cancer was markedly related to better OS (HR 0.28, 95% CI 0.14-0.55, p < 0.001). CONCLUSION: This meta-analysis reveals that exosome-derived lncRNAs might serve as promising diagnostic and prognostic biomarkers for cancer. However, the clinical value of exosome-derived lncRNAs needs to be further confirmed.
PURPOSE: Exosome-derived long non-coding RNAs (lncRNAs) as novel biomarkers are widely investigated in various cancers, yet results remain controversial. The aim of this meta-analysis was to clarify the diagnostic and prognostic value of exosome-derived lncRNAs in cancer. METHODS: PubMed, Web of Science, EMBASE, CNKI, and WanFang online databases were comprehensively searched for eligible studies up to January, 2020. To evaluate the diagnostic effect, sensitivity, specificity, and area under the curve (AUC) were pooled. Threshold effect, subgroup analysis, and meta-regression were applied to explore heterogeneity. Deeks' funnel plot and sensitivity analysis were used to examine publication bias and stability of meta-analysis, respectively. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and recurrence free survival (RFS) were calculated to assess the prognostic value. RESULTS: A total of 29 eligible studies involving 3882 patients were enrolled in the meta-analysis, which included 26 on diagnosis and 11 on prognosis. For diagnosis analysis, the pooled sensitivity, specificity, and AUC were 0.83 (95% CI 0.78-0.87), 0.80 (95% CI 0.75-0.84), and 0.88 (95% CI 0.85-0.91), respectively. Meta-regression revealed that the cancer type acted as the potential source of heterogeneity. Sensitivity analysis and Deeks' funnel plot indicated that results were relatively robust and had no publication bias. For the prognosis analysis, results suggested that overexpression of exosome-derived lncRNAs which upregulated in cancer showed a significant association with poor OS (HR 2.21, 95% CI 1.79-2.71, p < 0.001). Conversely, overexpression of exosome-derived lncRNAs which downregulated in cancer was markedly related to better OS (HR 0.28, 95% CI 0.14-0.55, p < 0.001). CONCLUSION: This meta-analysis reveals that exosome-derived lncRNAs might serve as promising diagnostic and prognostic biomarkers for cancer. However, the clinical value of exosome-derived lncRNAs needs to be further confirmed.
Entities:
Keywords:
Cancer; Diagnosis; Exosomes; Long non-coding RNAs; Meta-analysis; Prognosis