SynthesisFrontiers in oncology2021
Exosome-Derived Long Non-Coding RNAs as Non-Invasive Biomarkers of Bladder Cancer.
Synthesis in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The diagnostic accuracy of urine-derived exosomes for bladder cancer: a systematic review and meta-analysis.World journal of surgical oncology · 2024Pooled it
- Exosomal noncoding RNAs as noninvasive biomarkers in bladder cancer: a diagnostic meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Pooled it
- Artificial intelligence and multi-omics integration in liquid biopsy for genitourinary cancers: a systematic scoping review.International urology and nephrology · 2026Article
- Beyond Visualization: Advanced Imaging, Theragnostics and Biomarker Integration in Urothelial Bladder Cancer.Cancers · 2025Review
- The emerging role of exosomal LncRNAs in chronic fatigue syndrome: from intercellular communication to disease biomarkers.Frontiers in molecular biosciences · 2025Review
- The identification of a NAging · 2024Article
- lncRNA BANCR promotes the colorectal cancer metastasis through accelerating exosomes-mediated M2 macrophage polarization via regulating RhoA/ROCK signaling.Molecular and cellular biochemistry · 2024Article
- Applications of Exosomes in Diagnosing Muscle Invasive Bladder Cancer.Pharmaceutics · 2022Review
- Transcriptional Regulation of NUPR1 by MYH11 Activates PI3 K/AKT and Promotes Bladder Cancer Progression Through Ferroptosis and M2 Polarization of Macrophages.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveAs a result of the inconsistency between reports, a meta-analysis was designed to appraise the clinical implications of long non-coding RNAs (lncRNAs) in exosomes for the diagnosis of bladder cancer.
methodsThe PubMed, EMBASE, and Cochrane library databases were searched to identify the relevant literature on lncRNAs in exosomes for bladder cancer diagnosis from database inception to May 2021. The literature was screened according to the inclusion and exclusion criteria, and the Quality Assessment of Diagnostic Accuracy Studies-2 entry tool was applied to evaluate the quality of the literature, and the sources of heterogeneity were explored using meta-regression and subgroup analysis. Stata 14.0 and RevMan 5.3 software were used for statistical analysis.
resultsA total of 23 studies described in 10 articles were included, with a total of 1883 patients with bladder cancer and 1721 patients in the non-cancerous control group. The exosome-derived lncRNAs performed better in the diagnosis of bladder cancer with a pooled sensitivity of 0.74 (95% CI, 0.69-0.77), specificity of 0.76 (95% CI, 0.72-0.80), and area under the curve of 0.83. The heterogeneity between studies was partly as a result of differences in specimen type, number of lncRNAs, lncRNA expression form, and reference gene type. Subgroup analysis showed that the detection efficacy based on the combination of multiple lncRNAs (0.86, 95% CI, 0.82-0.88) was higher than that based on a single lncRNA (0.81, 95% CI, 0.78-0.85), and exosomal lncRNAs with blood as the detection sample had a high diagnostic efficacy (0.86, 95% CI, 0.82-0.86).
conclusionsExosome-derived lncRNAs hold great promise as non-invasive diagnostic biomarkers of bladder cancer. However, their clinical value needs to be examined in further comprehensive prospective studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.