ReviewCancers2023
Circulating and Endometrial Tissue microRNA Markers Associated with Endometrial Cancer Diagnosis, Prognosis, and Response to Treatment.
Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed, 9 citations in OpenAlex.
- Review
- Epigenetics, Oxidative Stress, and the Microbiome in Endometriosis: Toward an Integrated Mechanistic Framework for Precision Medicine.Journal of personalized medicine · 2026Review
- Review
- miRNA Signatures in Endometrial Cancer: Implications for Oncogenesis and Polymerase Epsilon (POLE) Mutation Status.International journal of molecular sciences · 2025Article
- Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.Frontiers in immunology · 2025Article
- Utilization of miRNAs as Biomarkers for the Diagnosis, Prognosis, and Metastasis in Gynecological Malignancies.International journal of molecular sciences · 2024Review
- Landscape of Endometrial Cancer: Molecular Mechanisms, Biomarkers, and Target Therapy.Cancers · 2024Review
- Interplay between LncRNA/miRNA and TGF-β Signaling in the Tumorigenesis of Gynecological Cancer.Current pharmaceutical design · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In developed countries, endometrial cancer (EC) is one of the most common neoplasms of the female reproductive system. MicroRNAs (miRs) are a class of single-stranded noncoding RNA molecules with lengths of 19-25 nucleotides that bind to target messenger RNA (mRNA) to regulate post-transcriptional gene expression. Although there is a large amount of research focused on identifying miRs with a diagnostic, prognostic, or response to treatment capacity in EC, these studies differ in terms of experimental methodology, types of samples used, selection criteria, and results obtained. Hence, there is a large amount of heterogeneous information that makes it difficult to identify potential miR biomarkers. We aimed to summarize the current knowledge on miRs that have been shown to be the most suitable potential markers for EC. We searched PubMed and Google Scholar without date restrictions or filters. We described 138 miRs with potential diagnostic, prognostic, or treatment response potential in EC. Seven diagnostic panels showed higher sensitivity and specificity for the diagnosis of EC than individual miRs. We further identified miRs up- or downregulated depending on the FIGO stage, precursor lesions, and staging after surgery, which provides insight into which miRs are expressed chronologically depending on the disease stage and/or that are modulated depending on the tumor grade based on histopathological evaluation.
Indexed as
Identifiers
What OpenQuestion holds
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.