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RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer
PURPOSE: To investigate the prognostic value of N6-methyladenosine (m6A)-, 5-methylcytosine (m5C)-, and N1-methyladenosine (m1A)-related genes in cervical cancer (CESC) and predicting immunotherapy response. METHODS: We downloaded cervical cancer mRNA expression profiles, clinical data, and m6A, m5C...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101678/ https://www.ncbi.nlm.nih.gov/pubmed/37042849 http://dx.doi.org/10.1080/07853890.2023.2190618 |
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author | Wang, Yan Mao, Yiwen Wang, Caizhi Jiang, Xuefeng Tang, Qionglan Wang, Lingling Zhu, Jialei Zhao, Mengqiu |
author_facet | Wang, Yan Mao, Yiwen Wang, Caizhi Jiang, Xuefeng Tang, Qionglan Wang, Lingling Zhu, Jialei Zhao, Mengqiu |
author_sort | Wang, Yan |
collection | PubMed |
description | PURPOSE: To investigate the prognostic value of N6-methyladenosine (m6A)-, 5-methylcytosine (m5C)-, and N1-methyladenosine (m1A)-related genes in cervical cancer (CESC) and predicting immunotherapy response. METHODS: We downloaded cervical cancer mRNA expression profiles, clinical data, and m6A, m5C, m1A-related genes from public databases, and subjected them to serial bioinformatics analysis and clinical sample validation. RESULTS: Differential analysis revealed 106 methylation-related differential genes (MEDs), including 44 differentially downregulated and 62 upregulated genes. We then obtained methylation models containing 10 genes by univariate and multifactorial COX analysis. High risk genes with HR > 1 include IQGAP3, PTBP1, STAC3, CUX1, SLC2A1, and CA2, and low risk genes with HR < 1 include IGBP1, DUOX1, CHAF1A, and STAC3. We verified the accuracy of the model from inside TCGA and outside GSE39001 (AUC = 0.729). K-M analysis showed shorter survival times in the High-risk group, and Immunocytic infiltration analysis showed model genes closely associated with six immune cells. The high-risk group may benefit more effectively from immunosuppressive therapy, especially anti-CTLA-4 therapy (p < .05). We also screened nine drugs for potential treatment and verified the expression of three key genes SLC2A1, CUX1, and CA2 using immunohistochemistry and RT-qPCR experiments with clinical samples. CONCLUSION: We identified a prognostic model using m6A/m5C/m1A-related genes in cervical cancer, which can predict survival time and correlate with immune cell infiltration. Additionally, anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer. KEY MESSAGES: Cervical cancer still has a high mortality rate, we aim to establish a strong prognostic index and new treatment goals for improving patient survival. The role of three types of RNA methylation modifications, m6A, m5C, and m1A, in cervical cancer, remains unknown. Therefore, it is essential to explore the potential molecular mechanisms of m6A, m5C, and m1A methylation regulation in cervical cancer. We also screened nine drugs for potential treatment and anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer. We verified the expression of three key genes SLC2A1, CUX1, and CA2. |
format | Online Article Text |
id | pubmed-10101678 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-101016782023-04-14 RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer Wang, Yan Mao, Yiwen Wang, Caizhi Jiang, Xuefeng Tang, Qionglan Wang, Lingling Zhu, Jialei Zhao, Mengqiu Ann Med Oncology PURPOSE: To investigate the prognostic value of N6-methyladenosine (m6A)-, 5-methylcytosine (m5C)-, and N1-methyladenosine (m1A)-related genes in cervical cancer (CESC) and predicting immunotherapy response. METHODS: We downloaded cervical cancer mRNA expression profiles, clinical data, and m6A, m5C, m1A-related genes from public databases, and subjected them to serial bioinformatics analysis and clinical sample validation. RESULTS: Differential analysis revealed 106 methylation-related differential genes (MEDs), including 44 differentially downregulated and 62 upregulated genes. We then obtained methylation models containing 10 genes by univariate and multifactorial COX analysis. High risk genes with HR > 1 include IQGAP3, PTBP1, STAC3, CUX1, SLC2A1, and CA2, and low risk genes with HR < 1 include IGBP1, DUOX1, CHAF1A, and STAC3. We verified the accuracy of the model from inside TCGA and outside GSE39001 (AUC = 0.729). K-M analysis showed shorter survival times in the High-risk group, and Immunocytic infiltration analysis showed model genes closely associated with six immune cells. The high-risk group may benefit more effectively from immunosuppressive therapy, especially anti-CTLA-4 therapy (p < .05). We also screened nine drugs for potential treatment and verified the expression of three key genes SLC2A1, CUX1, and CA2 using immunohistochemistry and RT-qPCR experiments with clinical samples. CONCLUSION: We identified a prognostic model using m6A/m5C/m1A-related genes in cervical cancer, which can predict survival time and correlate with immune cell infiltration. Additionally, anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer. KEY MESSAGES: Cervical cancer still has a high mortality rate, we aim to establish a strong prognostic index and new treatment goals for improving patient survival. The role of three types of RNA methylation modifications, m6A, m5C, and m1A, in cervical cancer, remains unknown. Therefore, it is essential to explore the potential molecular mechanisms of m6A, m5C, and m1A methylation regulation in cervical cancer. We also screened nine drugs for potential treatment and anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer. We verified the expression of three key genes SLC2A1, CUX1, and CA2. Taylor & Francis 2023-04-12 /pmc/articles/PMC10101678/ /pubmed/37042849 http://dx.doi.org/10.1080/07853890.2023.2190618 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
spellingShingle | Oncology Wang, Yan Mao, Yiwen Wang, Caizhi Jiang, Xuefeng Tang, Qionglan Wang, Lingling Zhu, Jialei Zhao, Mengqiu RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title | RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title_full | RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title_fullStr | RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title_full_unstemmed | RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title_short | RNA methylation-related genes of m6A, m5C, and m1A predict prognosis and immunotherapy response in cervical cancer |
title_sort | rna methylation-related genes of m6a, m5c, and m1a predict prognosis and immunotherapy response in cervical cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101678/ https://www.ncbi.nlm.nih.gov/pubmed/37042849 http://dx.doi.org/10.1080/07853890.2023.2190618 |
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