ReviewInternational journal of molecular sciences2025
Micro RNA in Colorectal Cancer-Potential Diagnostic and Prognostic Markers-An Updated Review.
Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Review
- Expression ofInternational journal of molecular sciences · 2026Article
- Liquid Biopsy in Colorectal Cancer: Future Perspectives Through the Lens of Artificial Intelligence-A Comprehensive Review of Novel Literature.International journal of molecular sciences · 2026Review
- ProVenTL: a transfer-learning framework for predicting peptide-protein interactions derived from snake venom for cancer therapeutics.Journal of computer-aided molecular design · 2026Article
- MicroRNAs in Breast Cancer: Diagnostic and Prognostic Potential, Challenges, and Clinical Reliability.Biomedicines · 2026Review
- Diet-Driven Epigenetic Alterations in Colorectal Cancer: From DNA Methylation and microRNA Expression to Liquid Biopsy Readouts.Biomedicines · 2026Review
- Targeted Inhibition of Oncogenic microRNAs miR-21, miR-17, and miR-155 Suppresses Tumor Growth and Modulates Immune Response in Colorectal Cancer.Pharmaceutics · 2026Article
- Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.Journal of personalized medicine · 2026Review
- Unravelling the nexus of non-coding RNAs in cancer stemness and therapeutic drug resistance.Frontiers in cell and developmental biology · 2026Review
- Navigating the molecular landscape: integrated multiomics liquid biopsy for biomarker discovery in early detection and monitoring of colorectal cancer.Frontiers in molecular biosciences · 2026Review
- RNA-based therapies for colorectal cancer: targeting the β-catenin pathway via microbiota -modulated miRNAs.Frontiers in molecular biosciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is one of the deadliest and most frequently occurring cancers worldwide. Often diagnosed in advanced stages, it requires more challenging treatment. However, emerging studies highlight the possible role of microRNAs (miRNAs) in the screening, diagnosis, and prognosis of CRC. MiRNAs modulate gene expression and can play both roles in tumor suppressors and oncogenes. In CRC, they influence epithelial-mesenchymal transition (EMT), cell proliferation and migration, apoptosis, autophagy, and patients' treatment response. In clinical applications, they can be used as predictive and prognostic biomarkers as well as for matching the most suitable treatments. Despite its growing popularity, there is still much to discover about their potential usage in medicine.
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.