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Jin Z, Sheng J, Hu Y, Zhang Y, Wang X, Huang Y. Shining a spotlight on m6A and the vital role of RNA modification in endometrial cancer: a review. Front Genet 2023; 14:1247309. [PMID: 37886684 PMCID: PMC10598767 DOI: 10.3389/fgene.2023.1247309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/19/2023] [Indexed: 10/28/2023] Open
Abstract
RNA modifications are mostly dynamically reversible post-transcriptional modifications, of which m6A is the most prevalent in eukaryotic mRNAs. A growing number of studies indicate that RNA modification can finely tune gene expression and modulate RNA metabolic homeostasis, which in turn affects the self-renewal, proliferation, apoptosis, migration, and invasion of tumor cells. Endometrial carcinoma (EC) is the most common gynecologic tumor in developed countries. Although it can be diagnosed early in the onset and have a preferable prognosis, some cases might develop and become metastatic or recurrent, with a worse prognosis. Fortunately, immunotherapy and targeted therapy are promising methods of treating endometrial cancer patients. Gene modifications may also contribute to these treatments, as is especially the case with recent developments of new targeted therapeutic genes and diagnostic biomarkers for EC, even though current findings on the relationship between RNA modification and EC are still very limited, especially m6A. For example, what is the elaborate mechanism by which RNA modification affects EC progression? Taking m6A modification as an example, what is the conversion mode of methylation and demethylation for RNAs, and how to achieve selective recognition of specific RNA? Understanding how they cope with various stimuli as part of in vivo and in vitro biological development, disease or tumor occurrence and development, and other processes is valuable and RNA modifications provide a distinctive insight into genetic information. The roles of these processes in coping with various stimuli, biological development, disease, or tumor development in vivo and in vitro are self-evident and may become a new direction for cancer in the future. In this review, we summarize the category, characteristics, and therapeutic precis of RNA modification, m6A in particular, with the purpose of seeking the systematic regulation axis related to RNA modification to provide a better solution for the treatment of EC.
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Affiliation(s)
- Zujian Jin
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Jingjing Sheng
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Yingying Hu
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Yu Zhang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Xiaoxia Wang
- Reproductive Medicine Center, School of Medicine, The Fourth Affiliated Hospital, Zhejiang University, Yiwu, Zhejiang, China
| | - Yiping Huang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
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Yu L, Zhang Y, Xue L, Liu F, Jing R, Luo J. Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy. Front Microbiol 2023; 14:1175925. [PMID: 37275146 PMCID: PMC10232852 DOI: 10.3389/fmicb.2023.1175925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/27/2023] [Indexed: 06/07/2023] Open
Abstract
Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m5U). To fill this knowledge gap, we first performed a comparative evaluation of various commonly used DL models for epigenetic studies with the help of autoBioSeqpy. We identified optimal architectural variations for m5U site classification, optimizing the layer depth and neuron width. Second, we used this knowledge to develop Deepm5U, an improved convolutional-recurrent neural network that accurately predicts m5U sites from RNA sequences. We successfully applied Deepm5U to transcriptomewide m5U profiling data across different sequencing technologies and cell types. Third, we showed that the techniques for interpreting deep neural networks, including LayerUMAP and DeepSHAP, can provide important insights into the internal operation and behavior of models. Overall, we offered practical guidance for the development, benchmark, and analysis of deep learning models when designing new algorithms for RNA modifications.
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Affiliation(s)
- Lezheng Yu
- School of Chemistry and Materials Science, Guizhou Education University, Guiyang, China
| | - Yonglin Zhang
- Department of Pharmacy, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Li Xue
- School of Public Health, Southwest Medical University, Luzhou, China
| | - Fengjuan Liu
- School of Geography and Resources, Guizhou Education University, Guiyang, China
| | - Runyu Jing
- School of Cyber Science and Engineering, Sichuan University, Chengdu, China
| | - Jiesi Luo
- Basic Medical College, Southwest Medical University, Luzhou, China
- Sichuan Key Medical Laboratory of New Drug Discovery and Druggability Evaluation, Luzhou Key Laboratory of Activity Screening and Druggability Evaluation for Chinese Materia Medica, Southwest Medical University, Luzhou, China
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