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Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy

N6-methyladenosine (m(6)A) is a common RNA modification in coding and non-coding RNAs and plays an important role in the occurrence and development of breast cancer (BC). However, the role of m(6)A-related lncRNAs in breast cancer prognosis is unclear. This study aimed to help verify the biological...

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Autores principales: Han, Xinwei, Chen, Yu, Xie, Jiaogui, Wang, Yichao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539557/
https://www.ncbi.nlm.nih.gov/pubmed/37781080
http://dx.doi.org/10.7150/jca.87079
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author Han, Xinwei
Chen, Yu
Xie, Jiaogui
Wang, Yichao
author_facet Han, Xinwei
Chen, Yu
Xie, Jiaogui
Wang, Yichao
author_sort Han, Xinwei
collection PubMed
description N6-methyladenosine (m(6)A) is a common RNA modification in coding and non-coding RNAs and plays an important role in the occurrence and development of breast cancer (BC). However, the role of m(6)A-related lncRNAs in breast cancer prognosis is unclear. This study aimed to help verify the biological function of m(6)A-related lncRNAs in breast cancer prognosis through bio-informatics techniques. First, we screened 18 m(6)A-related lncRNAs from the TCGA database: AL137847.1, AC137932.2, OTUD6B-AS1, MORF4L2-AS1, AC078846.1, AC012442.1, AL118556.1, AL138955.1, AC009754.1, AC024257.4, AL391095.1, AC024270.3, AC087392.1, LINC02649, AC090948.2, AL158212.1, ITGA6-AS1, AL133243.2 and constructed a risk-prognosis model based on this. Based on the model's median risk score, BC patients were divided into high-risk and low-risk groups. Then, the predictive value of the model was verified by Cox regression, Lasso regression, Kaplan-Meier curve and ROC curve analysis, and biological differences between the two groups were verified by GO enrichment analysis, tumor mutation burden, immune indications and in vitro tests. Importantly, the risk score of this prognostic model is an excellent independent prognostic factor, and m(6)A regulators are differentially expressed in patients with different risks. In addition, based on patients' different sensitivities to drugs, some drug candidates for different risk populations are screened to provide targets for breast cancer treatment. The difference in immune function between high-risk and low-risk patients also affected the sensitivity to immunotherapy. In the validation of clinical samples, we analyzed the expression of relevant lncRNAs in different risk groups and speculated the possible impact on the prognosis of breast cancer patients. The risk assessment tool built based on the full analysis of these m(6)A-related genes and m(6)A-related lncRNA libraries, as well as the m(6)A-related lncRNAs, has a high prognostic prediction ability, which may provide a supplementary screening method for accurately judging the prognosis of BC and a new perspective for personalized treatment of breast cancer patients.
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spelling pubmed-105395572023-09-30 Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy Han, Xinwei Chen, Yu Xie, Jiaogui Wang, Yichao J Cancer Research Paper N6-methyladenosine (m(6)A) is a common RNA modification in coding and non-coding RNAs and plays an important role in the occurrence and development of breast cancer (BC). However, the role of m(6)A-related lncRNAs in breast cancer prognosis is unclear. This study aimed to help verify the biological function of m(6)A-related lncRNAs in breast cancer prognosis through bio-informatics techniques. First, we screened 18 m(6)A-related lncRNAs from the TCGA database: AL137847.1, AC137932.2, OTUD6B-AS1, MORF4L2-AS1, AC078846.1, AC012442.1, AL118556.1, AL138955.1, AC009754.1, AC024257.4, AL391095.1, AC024270.3, AC087392.1, LINC02649, AC090948.2, AL158212.1, ITGA6-AS1, AL133243.2 and constructed a risk-prognosis model based on this. Based on the model's median risk score, BC patients were divided into high-risk and low-risk groups. Then, the predictive value of the model was verified by Cox regression, Lasso regression, Kaplan-Meier curve and ROC curve analysis, and biological differences between the two groups were verified by GO enrichment analysis, tumor mutation burden, immune indications and in vitro tests. Importantly, the risk score of this prognostic model is an excellent independent prognostic factor, and m(6)A regulators are differentially expressed in patients with different risks. In addition, based on patients' different sensitivities to drugs, some drug candidates for different risk populations are screened to provide targets for breast cancer treatment. The difference in immune function between high-risk and low-risk patients also affected the sensitivity to immunotherapy. In the validation of clinical samples, we analyzed the expression of relevant lncRNAs in different risk groups and speculated the possible impact on the prognosis of breast cancer patients. The risk assessment tool built based on the full analysis of these m(6)A-related genes and m(6)A-related lncRNA libraries, as well as the m(6)A-related lncRNAs, has a high prognostic prediction ability, which may provide a supplementary screening method for accurately judging the prognosis of BC and a new perspective for personalized treatment of breast cancer patients. Ivyspring International Publisher 2023-09-11 /pmc/articles/PMC10539557/ /pubmed/37781080 http://dx.doi.org/10.7150/jca.87079 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Han, Xinwei
Chen, Yu
Xie, Jiaogui
Wang, Yichao
Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title_full Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title_fullStr Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title_full_unstemmed Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title_short Characteristics of m(6)A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy
title_sort characteristics of m(6)a-related lncrnas in breast cancer as prognostic biomarkers and immunotherapy
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539557/
https://www.ncbi.nlm.nih.gov/pubmed/37781080
http://dx.doi.org/10.7150/jca.87079
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