Evidence map›Paper›PMID 40823093›Full record

ReviewFrontiers in oncology2025

Advances in research on RNA methylation and cancer radiotherapy resistance.

Hui Liu, Hui Luo, Ming Jin, Zhen Zheng, Yang Xi, Kaitai Liu

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2025. 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

6 authors.

Hui Liu *Department of Radiation Oncology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Hui Luo *Department of Radiation Oncology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Ming JinDepartment of Radiation Oncology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Zhen ZhengDepartment of Radiation Oncology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yang XiDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Health Science Center, Ningbo University, Ningbo, Zhejiang, China.
Kaitai LiuDepartment of Radiation Oncology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA methylation is a type of reversible chemical modification in epitranscriptomics that influences gene expression by dynamically regulating RNA functions. RNA methylation comprises N6-methyladenosine (m6A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), N1-methyladenosine (m1A), and 3-methylcytosine (m3C) modifications. These are dynamically controlled by a tripartite enzymatic system: methyltransferases ("writers") add methyl groups, demethylases ("erasers") remove them, and RNA-binding proteins ("readers") recognize and interpret the modifications to mediate downstream biological effects. Extensive research has shown the importance of RNA methylation in the onset and progression of cancer. RNA methylation contributes to radioresistance in cancer cells through various mechanisms, affecting therapeutic outcomes. To date, the precise functions of RNA methylation in cancer radioresistance remain unclear. This review summarizes recent advances in m6A, m5C, m7G, and m1A methylation in cancer radioresistance regulation and discusses the clinical potential of precision therapeutic strategies targeting these methylation modifications.

Indexed as

m1A methylationm5C methylationm6A methylationm7G methylationradioresistance

Identifiers

PMID40823093
PMCPMC12350144

What OpenQuestion holds

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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.