Dynamic landscape of m6A modifications and related post-transcriptional events in muscle-invasive bladder cancer.
Humans
Urinary Bladder Neoplasms
/ genetics
Adenosine
/ analogs & derivatives
Neoplasm Invasiveness
RNA Processing, Post-Transcriptional
/ genetics
Methylation
Male
Gene Expression Regulation, Neoplastic
RNA, Messenger
/ genetics
Machine Learning
Muscles
/ pathology
Female
Middle Aged
Prognosis
Aged
3' Untranslated Regions
/ genetics
Muscle-invasive bladder cancer
Nanopore sequencing
Transcriptional events
m6A modification
Journal
Journal of translational medicine
ISSN: 1479-5876
Titre abrégé: J Transl Med
Pays: England
ID NLM: 101190741
Informations de publication
Date de publication:
08 Oct 2024
08 Oct 2024
Historique:
received:
05
08
2024
accepted:
23
09
2024
medline:
9
10
2024
pubmed:
9
10
2024
entrez:
8
10
2024
Statut:
epublish
Résumé
Muscle-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. Paired 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. The 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 ). The 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.
Sections du résumé
BACKGROUND
BACKGROUND
Muscle-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.
METHODS
METHODS
Paired 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.
RESULTS
RESULTS
The 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 ).
CONCLUSIONS
CONCLUSIONS
The 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.
Identifiants
pubmed: 39380003
doi: 10.1186/s12967-024-05701-x
pii: 10.1186/s12967-024-05701-x
doi:
Substances chimiques
Adenosine
K72T3FS567
N-methyladenosine
CLE6G00625
RNA, Messenger
0
3' Untranslated Regions
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
912Subventions
Organisme : Bethune Charitable Foundation
ID : mnzl202009
Organisme : National High Level Hospital Clinical Research Funding
ID : BJ-2022-144
Organisme : National High Level Hospital Clinical Research Funding
ID : BJ-2022-174
Organisme : National High Level Hospital Clinical Research Funding
ID : BJ-2023-198
Organisme : National High Level Hospital Clinical Research Funding
ID : BJ-2024-153
Informations de copyright
© 2024. The Author(s).
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