ReviewGenes & genomics2025
The diverse landscape of RNA modifications in cancer development and progression.
Review in Genes & genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Bioinformatic characterization of SLC25A39 across cancers with validation in hepatocellular carcinoma.Discover oncology · 2026Article
- RNA modifications: molecular orchestrators of wound healing.Burns & trauma · 2026Article
- Metabolomics-Based Liquid Biopsy for Predicting Clinically Significant Prostate Cancer.Cancers · 2025Review
- Multidimensional analysis reveals the potential of ACSL3 as a cancer biomarker: from pan-cancer exploration to functional validation in hepatocellular carcinoma.Clinical and experimental medicine · 2025Article
- Multidimensional pan-cancer analysis reveals the impact of PPIA on tumor epigenetic modifications and immune regulation.Scientific reports · 2025Article
- Identification and Characterization of the RNA Modifying Factors PUS7 and WTAP as Key Components for the Control of Tumor Biological Processes in Renal Cell Carcinomas.Current issues in molecular biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundRNA modifications, a central aspect of epitranscriptomics, add a regulatory layer to gene expression by modifying RNA function without altering nucleotide sequences. These modifications play vital roles across RNA species, influencing RNA stability, translation, and interaction dynamics, and are regulated by specific enzymes that add, remove, and interpret these chemical marks.
objectiveThis review examines the role of aberrant RNA modifications in cancer progression, exploring their potential as diagnostic and prognostic biomarkers and as therapeutic targets. We focus on how altered RNA modification patterns impact oncogenes, tumor suppressor genes, and overall tumor behavior.
methodsWe performed an in-depth analysis of recent studies and advances in RNA modification research, highlighting key types and functions of RNA modifications and their roles in cancer biology. Studies involving preclinical models targeting RNA-modifying enzymes were reviewed to assess therapeutic efficacy and potential clinical applications.
resultsAberrant RNA modifications were found to significantly influence cancer initiation, growth, and metastasis. Dysregulation of RNA-modifying enzymes led to altered gene expression profiles in oncogenes and tumor suppressors, correlating with tumor aggressiveness, patient outcomes, and response to immunotherapy. Notably, inhibitors of these enzymes demonstrated potential in preclinical models by reducing tumor growth and enhancing the efficacy of existing cancer treatments.
conclusionsRNA modifications present promising avenues for cancer diagnosis, prognosis, and therapy. Understanding the mechanisms of RNA modification dysregulation is essential for developing targeted treatments that improve patient outcomes. Further research will deepen insights into these pathways and support the clinical translation of RNA modification-targeted therapies.
Indexed as
Identifiers
39643826What 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.