Cargando…
N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma
N1-methyladenosine methylation (m(1)A), as an important RNA methylation modification, regulates the development of many tumours. Metabolic reprogramming is one of the important features of tumour cells, and it plays a crucial role in tumour development and metastasis. The role of RNA methylation and...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485621/ https://www.ncbi.nlm.nih.gov/pubmed/36147503 http://dx.doi.org/10.3389/fgene.2022.993594 |
_version_ | 1784792112344072192 |
---|---|
author | Wang, Guowei Wang, Hongyi Cheng, Sha Zhang, Xiaobo Feng, Wanjiang Zhang, Pan Wang, Jianlong |
author_facet | Wang, Guowei Wang, Hongyi Cheng, Sha Zhang, Xiaobo Feng, Wanjiang Zhang, Pan Wang, Jianlong |
author_sort | Wang, Guowei |
collection | PubMed |
description | N1-methyladenosine methylation (m(1)A), as an important RNA methylation modification, regulates the development of many tumours. Metabolic reprogramming is one of the important features of tumour cells, and it plays a crucial role in tumour development and metastasis. The role of RNA methylation and metabolic reprogramming in osteosarcoma has been widely reported. However, the potential roles and mechanisms of m(1)A-related metabolic genes (MRmetabolism) in osteosarcoma have not been currently described. All of MRmetabolism were screened, then selected two MRmetabolism by least absolute shrinkage and selection operator and multifactorial regression analysis to construct a prognostic signature. Patients were divided into high-risk and low-risk groups based on the median riskscore of all patients. After randomizing patients into train and test cohorts, the reliability of the prognostic signature was validated in the whole, train and test cohort, respectively. Subsequently, based on the expression profiles of the two MRmetabolism, we performed consensus clustering to classify patients into two clusters. In addition, we explored the immune infiltration status of different risk groups and different clusters by CIBERSORT and single sample gene set enrichment analysis. Also, to better guide individualized treatment, we analyzed the immune checkpoint expression differences and drug sensitivity in the different risk groups and clusters. In conclusion, we constructed a MRmetabolism prognostic signature, which may help to assess patient prognosis, immunotherapy response. |
format | Online Article Text |
id | pubmed-9485621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94856212022-09-21 N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma Wang, Guowei Wang, Hongyi Cheng, Sha Zhang, Xiaobo Feng, Wanjiang Zhang, Pan Wang, Jianlong Front Genet Genetics N1-methyladenosine methylation (m(1)A), as an important RNA methylation modification, regulates the development of many tumours. Metabolic reprogramming is one of the important features of tumour cells, and it plays a crucial role in tumour development and metastasis. The role of RNA methylation and metabolic reprogramming in osteosarcoma has been widely reported. However, the potential roles and mechanisms of m(1)A-related metabolic genes (MRmetabolism) in osteosarcoma have not been currently described. All of MRmetabolism were screened, then selected two MRmetabolism by least absolute shrinkage and selection operator and multifactorial regression analysis to construct a prognostic signature. Patients were divided into high-risk and low-risk groups based on the median riskscore of all patients. After randomizing patients into train and test cohorts, the reliability of the prognostic signature was validated in the whole, train and test cohort, respectively. Subsequently, based on the expression profiles of the two MRmetabolism, we performed consensus clustering to classify patients into two clusters. In addition, we explored the immune infiltration status of different risk groups and different clusters by CIBERSORT and single sample gene set enrichment analysis. Also, to better guide individualized treatment, we analyzed the immune checkpoint expression differences and drug sensitivity in the different risk groups and clusters. In conclusion, we constructed a MRmetabolism prognostic signature, which may help to assess patient prognosis, immunotherapy response. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9485621/ /pubmed/36147503 http://dx.doi.org/10.3389/fgene.2022.993594 Text en Copyright © 2022 Wang, Wang, Cheng, Zhang, Feng, Zhang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Wang, Guowei Wang, Hongyi Cheng, Sha Zhang, Xiaobo Feng, Wanjiang Zhang, Pan Wang, Jianlong N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title | N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title_full | N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title_fullStr | N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title_full_unstemmed | N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title_short | N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
title_sort | n1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485621/ https://www.ncbi.nlm.nih.gov/pubmed/36147503 http://dx.doi.org/10.3389/fgene.2022.993594 |
work_keys_str_mv | AT wangguowei n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT wanghongyi n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT chengsha n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT zhangxiaobo n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT fengwanjiang n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT zhangpan n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma AT wangjianlong n1methyladenosinemethylationrelatedmetabolicgenessignatureandsubtypesforpredictingprognosisandimmunemicroenvironmentinosteosarcoma |