Evidence mapPaperPMID 41736103Full record

ReviewHuman genomics2026

Therapeutic rewiring of ceRNA networks: a computational pipeline for drug repurposing in acute kidney injury via circRNA-miRNA-mRNA axis disruption.

Ming Wang, Feng Gao

Abstract readReview
In one paragraph

Review in Human genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ming WangDepartment of Urology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, Zhejiang, P.R. China.
Feng GaoDepartment of Urology, Hangzhou Hospital of Traditional Chinese Medicine, 453 Stadium Road, Hangzhou, 310000, Zhejiang, P.R. China. friendgao@yeah.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review synthesizes current evidence on competing endogenous RNA (ceRNA) regulation in acute kidney injury (AKI) and proposes a practical, reproducible framework for computationally guided drug repurposing that aims to rewire pathogenic circRNA–miRNA–mRNA axes. We summarize the ceRNA concept and its biological rationale in renal injury, anchored to foundational descriptions of the ceRNA hypothesis. Building on curated circRNA resources and drug–gene mapping platforms, we present and critically evaluate a five-stage computational framework: (1) multi-omics data mining and ceRNA triplet inference, (2) network pharmacology mapping to drug–gene resources, (3) RNA-aware molecular docking to candidate structured RNA motifs, (4) molecular dynamics (MD) refinement and rescoring, and (5) integrative prioritization with explicit experimental filters for renal safety and tractability. We synthesize methodological best practices and limitations for each stage, with particular attention to the emerging field of RNA-targeted small molecules and their experimental validation. Three illustrative case studies demonstrate how distinct repurposing logics (direct RNA engagement, network/miRNA modulation, pathway-level modulation) can be mapped onto this pipeline and what orthogonal assays are required to progress candidates from in silico nomination to biochemical and in vivo testing. The review concludes with a pragmatic experimental roadmap, clear caveats (RNA structural dynamics, cellular context dependency, miRNA redundancy), and proposals to integrate single-cell and systems-pharmacology approaches to improve replicability and translational potential. By collating the literature and proposing a transparent, stepwise framework with validation benchmarks, this review aims to generate testable, prioritized in-silico hypotheses for RNA-aware repurposing in AKI that require rigorous biochemical and preclinical validation before any consideration of clinical testing. Because AKI arises from multiple, biologically distinct etiologies (for example ischemia–reperfusion injury, sepsis, nephrotoxic injury such as cisplatin exposure, and obstructive causes), candidate drugs and circRNA/miRNA targets must be evaluated in etiology-matched cellular and animal models; the pipeline therefore explicitly recommends etiology-aware filtering and model selection to avoid overgeneralizing findings across all AKI types.

Indexed as

Acute Kidney InjuryComputational BiologyDrug RepositioningMicroRNAsRNA, CircularRNA, MessengerAnimalsGene Regulatory NetworksHumansRNA, Competitive EndogenousMicroRNAsRNA, CircularRNA, Competitive EndogenousRNA, MessengerAcute kidney injuryceRNA networkscircRNA–miRNA–mRNA axisComputational pharmacologyDrug repurposing

Identifiers

PMID41736103
PMCPMC13041499

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.