Evidence map›Paper›PMID 41694387›Full record

ReviewFrontiers in immunology2026

Rewriting the RNA code: an m

Yi Sun, Jinliang Wu, Guanhao Chen, Haojun Ma, Wenshuya Li, Hongyu Tan, Kerong Yang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

7 authors.

Yi SunDepartment of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Jinliang WuDepartment of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Guanhao ChenDepartment of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Haojun MaThe First Clinical School of Medicine, Zhengzhou University, Zhengzhou, Henan, China.
Wenshuya LiDepartment of the Plastic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Hongyu TanDepartment of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Kerong YangDepartment of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The epitranscriptome, particularly N Methods: We synthesized current evidence through systematic reviews of primary research and high-impact papers from PubMed and Google Scholar, focusing on the mechanistic role of m Results: We classify tumors into Writer-Dominant (METTL3/14-high, Eraser-High (FTO/ALKBH5-high), Reader-Amplified (IGF2BP/YTHDF-high), and Immune-Modulatory subtypes, each with distinct oncogenic programs, therapy resistance mechanisms, and, crucially, actionable therapeutic vulnerabilities. We provide explicit, evidence-based molecular and functional inclusion criteria for each subtype and acknowledge that tumors can exhibit hybrid features, which directly inform rational combination strategies. Furthermore, we detail a diagnostic-therapeutic roadmap that integrates liquid biopsy-based m Conclusion: Targeting the m

Indexed as

AdenosineNeoplasmsAnimalsBiomarkers, TumorEpitranscriptomeEpitranscriptomicsGene Expression Regulation, NeoplasticHumansRNA MethylationAdenosineBiomarkers, TumorN-methyladenosinecancer immunotherapyepitranscriptomeN6-methylAdenosine (m6A)RNA modificationtargeted therapytherapeutic resistance

Identifiers

PMID41694387
PMCPMC12901410

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.