ReviewMolecular therapy. Oncology2026
Multi-omics dissection of R-loop dynamics in tumorigenesis: From transcription-replication conflict to therapeutic targets.
Review in Molecular therapy. Oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- R-loops in colorectal cancer: mechanisms, mapping strategies, and therapeutic opportunities.Molecular biology reports · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
R-loops, three-stranded nucleic acid structures comprising an RNA-DNA hybrid and a displaced single-stranded DNA strand, play context-dependent roles in cancer-serving essential physiological functions while also driving tumorigenesis when dysregulated. Their pathological effects are mediated through replication stress, genomic instability, transcriptional disruption, and defective RNA processing. This review highlights the emerging potential of targeting R-loops as a therapeutic strategy in oncology. We survey advanced methodologies for R-loop mapping, addressing technical limitations of current approaches, and advocate for multi-omics integration to elucidate R-loop dynamics and functional networks in cancers such as lung, bladder, and prostate malignancies. Critically, we explore two promising therapeutic avenues: (1) direct inhibition of R-loop resolvers to trigger excessive R-loop accumulation and replication catastrophe, and (2) synthetic lethality strategies that capitalize on cancer-specific R-loop handling defects. Clinical evidence supporting these approaches is discussed, along with challenges including tumor heterogeneity, detection limitations, and adaptive resistance. We argue that a multi-omics-driven understanding of R-loop biology will accelerate the translation of R-loop-directed therapies into precision oncology.
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Registered trials
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