ReviewDiscover oncology2025
The functions of circular RNAs and long noncoding RNAs in cholangiocarcinoma.
Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
8 authors.
Funding
Abstract
Cholangiocarcinoma (CCA) is a highly aggressive malignancy with an extremely poor prognosis. The rising incidence of cholangiocarcinoma in recent years underscores the need for new diagnostic biomarkers and therapeutic targets. Circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) have become important research focuses in oncology, including in CCA. The specific expression patterns of circRNAs and lncRNAs has been associated with unfavorable clinicopathological features in CCA. CircRNAs and lncRNAs play crucial roles in the occurrence, development, and drug resistance of CCA through various mechanisms. This review primarily focuses on exploring the biological roles and pathways of these non-coding RNAs in CCA. Additionally, we examine the practical implications and feasibility of using circRNAs and lncRNAs as diagnostic and prognostic markers, while also exploring their potential as therapeutic targets for CCA.
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Registered trials
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.