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N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer

BACKGROUND: N6-methyladenosine (m(6)A) modification has been widely studied in various cancers, and m(6)A regulators, such as METTL3, METTL14, WTAP, and YTHDF1, play crucial roles in breast cancer. However, a comprehensive study of m(6)A regulators in breast cancer is still lacking. MATERIAL/METHODS...

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Autores principales: Song, Yanni, Zheng, Chaojing, Tao, Yangbao, Huang, Rui, Zhang, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353996/
https://www.ncbi.nlm.nih.gov/pubmed/34349094
http://dx.doi.org/10.12659/MSM.929615
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author Song, Yanni
Zheng, Chaojing
Tao, Yangbao
Huang, Rui
Zhang, Qian
author_facet Song, Yanni
Zheng, Chaojing
Tao, Yangbao
Huang, Rui
Zhang, Qian
author_sort Song, Yanni
collection PubMed
description BACKGROUND: N6-methyladenosine (m(6)A) modification has been widely studied in various cancers, and m(6)A regulators, such as METTL3, METTL14, WTAP, and YTHDF1, play crucial roles in breast cancer. However, a comprehensive study of m(6)A regulators in breast cancer is still lacking. MATERIAL/METHODS: Expression data of m(6)A regulators and clinicopathological information were acquired from The Cancer Genome Atlas (TCGA) program. Protein interaction was collected from the STRING database. Data on tumor purity and correlation among m(6)A regulators were obtained from the TIMER database. LASSO, consensus clustering, and gene set enrichment analysis (GSEA) were used to evaluate the role of m(6)A regulators. Moreover, the prognostic value of m(6)A-related genomic targets in breast cancer was analyzed by Kaplan-Meier analysis and Cox regression models. RESULTS: We found most m(6)A regulators were associated with key clinicopathological parameters, such as tumor staging, Nottingham prognostic index (NPI), and cellularity. Also, consensus clustering analysis-based grouping could effectively predict patients’ overall survival. Correlation analysis also showed that these regulators interacted with each other. Patients were further split into a high-risk group and low-risk group based on Cox and LASSO analysis. High-risk patients had a significantly worse overall survival than did low-risk patients. Moreover, AKT1 and MYC were enriched in patients in the high-risk group, according to GSEA analysis. The patients in the high-risk group also displayed resistance to chemoradiotherapy or hormone therapy. CONCLUSIONS: The m(6)A regulators are critical participants in the development and progression of breast cancer and are likely to be used to predict prognosis and develop treatment strategies.
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spelling pubmed-83539962021-08-23 N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer Song, Yanni Zheng, Chaojing Tao, Yangbao Huang, Rui Zhang, Qian Med Sci Monit Database Analysis BACKGROUND: N6-methyladenosine (m(6)A) modification has been widely studied in various cancers, and m(6)A regulators, such as METTL3, METTL14, WTAP, and YTHDF1, play crucial roles in breast cancer. However, a comprehensive study of m(6)A regulators in breast cancer is still lacking. MATERIAL/METHODS: Expression data of m(6)A regulators and clinicopathological information were acquired from The Cancer Genome Atlas (TCGA) program. Protein interaction was collected from the STRING database. Data on tumor purity and correlation among m(6)A regulators were obtained from the TIMER database. LASSO, consensus clustering, and gene set enrichment analysis (GSEA) were used to evaluate the role of m(6)A regulators. Moreover, the prognostic value of m(6)A-related genomic targets in breast cancer was analyzed by Kaplan-Meier analysis and Cox regression models. RESULTS: We found most m(6)A regulators were associated with key clinicopathological parameters, such as tumor staging, Nottingham prognostic index (NPI), and cellularity. Also, consensus clustering analysis-based grouping could effectively predict patients’ overall survival. Correlation analysis also showed that these regulators interacted with each other. Patients were further split into a high-risk group and low-risk group based on Cox and LASSO analysis. High-risk patients had a significantly worse overall survival than did low-risk patients. Moreover, AKT1 and MYC were enriched in patients in the high-risk group, according to GSEA analysis. The patients in the high-risk group also displayed resistance to chemoradiotherapy or hormone therapy. CONCLUSIONS: The m(6)A regulators are critical participants in the development and progression of breast cancer and are likely to be used to predict prognosis and develop treatment strategies. International Scientific Literature, Inc. 2021-08-05 /pmc/articles/PMC8353996/ /pubmed/34349094 http://dx.doi.org/10.12659/MSM.929615 Text en © Med Sci Monit, 2021 https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Database Analysis
Song, Yanni
Zheng, Chaojing
Tao, Yangbao
Huang, Rui
Zhang, Qian
N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title_full N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title_fullStr N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title_full_unstemmed N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title_short N6-Methyladenosine Regulators Are Involved in the Progression of and Have Clinical Impact on Breast Cancer
title_sort n6-methyladenosine regulators are involved in the progression of and have clinical impact on breast cancer
topic Database Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353996/
https://www.ncbi.nlm.nih.gov/pubmed/34349094
http://dx.doi.org/10.12659/MSM.929615
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