Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response
Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to de...
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.991162/full |
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| author | Jin Cao Yichen Liang Yichen Liang J. Juan Gu J. Juan Gu J. Juan Gu Yuxiang Huang Yuxiang Huang Buhai Wang Buhai Wang Buhai Wang |
| author_facet | Jin Cao Yichen Liang Yichen Liang J. Juan Gu J. Juan Gu J. Juan Gu Yuxiang Huang Yuxiang Huang Buhai Wang Buhai Wang Buhai Wang |
| author_sort | Jin Cao |
| collection | DOAJ |
| description | Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients.Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature’s usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups.Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients’ immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy.Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients’ customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy. |
| first_indexed | 2024-04-11T19:42:41Z |
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| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T19:42:41Z |
| publishDate | 2022-10-01 |
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| spelling | doaj.art-5800640698394aadab72993e5cd7cc3e2022-12-22T04:06:40ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-10-011310.3389/fgene.2022.991162991162Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune responseJin Cao0Yichen Liang1Yichen Liang2J. Juan Gu3J. Juan Gu4J. Juan Gu5Yuxiang Huang6Yuxiang Huang7Buhai Wang8Buhai Wang9Buhai Wang10Medical College, Yangzhou University, Yangzhou, Jiangsu, ChinaInstitute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaDepartment of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaMedical College, Yangzhou University, Yangzhou, Jiangsu, ChinaInstitute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaDepartment of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaInstitute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaDepartment of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaMedical College, Yangzhou University, Yangzhou, Jiangsu, ChinaInstitute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaDepartment of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, ChinaBackground: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients.Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature’s usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups.Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients’ immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy.Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients’ customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy.https://www.frontiersin.org/articles/10.3389/fgene.2022.991162/fullN7-methylguanosine (m7G)long non-coding RNAbreast cancerprognostic modelimmune responsethe cancer genome atlas |
| spellingShingle | Jin Cao Yichen Liang Yichen Liang J. Juan Gu J. Juan Gu J. Juan Gu Yuxiang Huang Yuxiang Huang Buhai Wang Buhai Wang Buhai Wang Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response Frontiers in Genetics N7-methylguanosine (m7G) long non-coding RNA breast cancer prognostic model immune response the cancer genome atlas |
| title | Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response |
| title_full | Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response |
| title_fullStr | Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response |
| title_full_unstemmed | Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response |
| title_short | Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response |
| title_sort | construction of prognostic signature of breast cancer based on n7 methylguanosine related lncrnas and prediction of immune response |
| topic | N7-methylguanosine (m7G) long non-coding RNA breast cancer prognostic model immune response the cancer genome atlas |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.991162/full |
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