Evidence map›Paper›PMID 39380003›Full record

ArticleJournal of translational medicine2024

Dynamic landscape of m6A modifications and related post-transcriptional events in muscle-invasive bladder cancer.

Lili Zhang, Ziwei Chen, Gaoyuan Sun, Chang Li, Pengjie Wu, Wenrui Xu, Hui Zhu, Zaifeng Zhang, Yongbin Tang, Yayu Li and 7 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. The bladder cancer mEMBO reports · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. 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

17 authors.

Lili Zhang *Clinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Ziwei Chen *Clinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Gaoyuan SunClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Chang LiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Pengjie WuDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Wenrui XuDepartment of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Hui ZhuDepartment of Nuclear Medicine, Beijing Hospital, National Center of Gerontology, Beijing, China.
Zaifeng ZhangClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Yongbin TangGraduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yayu LiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Yifei LiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Siyuan XuClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Hexin LiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Meng ChenNational Clinical Research Center for Cancer/Cancer Hospital, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Fei XiaoClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. xiaofei3965@bjhmoh.cn.
Yaqun ZhangTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China. zhangyaqun@yeah.net.
Wei ZhangDepartment of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. zwigyl@hotmail.com.ORCID 0000-0003-1515-964X

Funding

Bethune Charitable Foundation mnzl202009National High Level Hospital Clinical Research Funding BJ-2022-144National High Level Hospital Clinical Research Funding BJ-2022-174National High Level Hospital Clinical Research Funding BJ-2023-198National High Level Hospital Clinical Research Funding BJ-2024-153
6 · The paper itself

Abstract

backgroundMuscle-invasive bladder carcinoma (MIBC) is a serious and more advanced stage of bladder carcinoma. N6-Methyladenosine (m6A) is a dynamic and reversible modifications that primarily affects RNA stability and alternative splicing. The dysregulation of m6A in MIBC can be potential target for clinical interventions, but there have been limited studies on m6A modifications in MIBC and their associations with post-transcriptional regulatory processes.

methodsPaired tumor and adjacent-normal tissues were obtained from three patients with MIBC following radical cystectomy. The additional paired tissues for validation were obtained from patients underwent transurethral resection. Utilizing Nanopore direct-RNA sequencing, we characterized the m6A RNA methylation landscape in MIBC, with a focus on identifying post-transcriptional events potentially affected by changes in m6A sites. This included an examination of differential transcript usage, polyadenylation signal sites, and variations in poly(A) tail length, providing insights into the broader impact of m6A alterations on RNA processing in MIBC.

resultsThe prognostic-related m6A genes and m6A-risk model constructed by machine learning enables the stratification of high and low-risk patients with precision. A novel m6A modification site in the 3' untranslated region (3'UTR) of IGLL5 gene were identified, characterized by a lower m6A methylation ratio, elongated poly(A) tails, and a notable bias in transcript usage. Furthermore, we discovered two particular transcripts, VWA1-203 and CEBPB-201. VWA1-203 displayed diminished m6A methylation levels, a truncated 3'UTR, and an elongated poly(A) tail, whereas CEBPB-201 showed opposite trends, highlighting the complex interplay between m6A modifications and RNA processing. Source code was provided on GitHub ( https://github.com/lelelililele/Nanopore-m6A-analysis ).

conclusionsThe state-of-the-art Nanopore direct-RNA sequencing and machine learning techniques enables comprehensive identification of m6A modification and provided insights into the potential post-transcriptional regulation mechanisms on the development and progression in MIBC.

Indexed as

AdenosineNeoplasm InvasivenessUrinary Bladder Neoplasms3' Untranslated RegionsAgedFemaleGene Expression Regulation, NeoplasticHumansMachine LearningMaleMethylationMiddle AgedMusclesPrognosisRNA, MessengerRNA Processing, Post-Transcriptional3' Untranslated RegionsAdenosineN-methyladenosineRNA, Messengerm6A modificationMuscle-invasive bladder cancerNanopore sequencingTranscriptional events

Identifiers

PMID39380003
PMCPMC11460118

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.