Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer
Background. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with th...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Mediators of Inflammation |
| Online Access: | http://dx.doi.org/10.1155/2023/1400267 |
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| author | Yibin Liu Shouze Liu Lu Yan Qianqian Zhang Wenhua Liu Xianghua Huang Shikai Liu |
| author_facet | Yibin Liu Shouze Liu Lu Yan Qianqian Zhang Wenhua Liu Xianghua Huang Shikai Liu |
| author_sort | Yibin Liu |
| collection | DOAJ |
| description | Background. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods. Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan–Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results. Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions. Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients. |
| format | Article |
| id | doaj-art-3ca5b425301c4927ad62946be417dd43 |
| institution | Kabale University |
| issn | 1466-1861 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Mediators of Inflammation |
| spelling | doaj-art-3ca5b425301c4927ad62946be417dd432025-02-03T05:57:01ZengWileyMediators of Inflammation1466-18612023-01-01202310.1155/2023/1400267Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian CancerYibin Liu0Shouze Liu1Lu Yan2Qianqian Zhang3Wenhua Liu4Xianghua Huang5Shikai Liu6Department of GynecologyDepartment of GynecologyDepartment of GynecologyDepartment of Gynecology and ObstetricsDepartment of PainDepartment of GynecologyDepartment of Gynecology IIIBackground. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods. Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan–Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results. Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions. Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.http://dx.doi.org/10.1155/2023/1400267 |
| spellingShingle | Yibin Liu Shouze Liu Lu Yan Qianqian Zhang Wenhua Liu Xianghua Huang Shikai Liu Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer Mediators of Inflammation |
| title | Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer |
| title_full | Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer |
| title_fullStr | Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer |
| title_full_unstemmed | Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer |
| title_short | Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer |
| title_sort | contribution of m5c rna modification related genes to prognosis and immunotherapy prediction in patients with ovarian cancer |
| url | http://dx.doi.org/10.1155/2023/1400267 |
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