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Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer
BACKGROUND: Energy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients. METHODS:...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9590147/ https://www.ncbi.nlm.nih.gov/pubmed/36280825 http://dx.doi.org/10.1186/s12920-022-01369-8 |
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author | Lin, Yaobin Xiao, Yu Liu, Shan Hong, Liang Shao, Lingdong Wu, Junxin |
author_facet | Lin, Yaobin Xiao, Yu Liu, Shan Hong, Liang Shao, Lingdong Wu, Junxin |
author_sort | Lin, Yaobin |
collection | PubMed |
description | BACKGROUND: Energy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients. METHODS: The transcriptome profile and clinical data of patients with colon cancer were retrieved from The Cancer Genome Atlas database. Using consensus clustering, cases were divided into two clusters and Kaplan–Meier analysis was executed to analyze differences in their prognoses. The gene set enrichment analysis (GSEA) was used to discover biological processes and signaling pathways. A lipid metabolism-related lncRNA prognostic model (lipid metabolism-LncRM) was created utilizing the least absolute shrinkage and selection operator (LASSO) regression. The tumor microenvironment was evaluated on the basis of the composition of immune and stromal cells. RESULTS: The patients in Cluster 2 were found to have a better prognosis and higher expression of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) relative to Cluster 1. The results of GSEA showed the enrichment of energy metabolism pathways in Cluster 2. LASSO regression was used to identify the five LncRNAs that were shown to be most substantially linked to patient prognosis. These were NSMCE1-DT, LINC02084, MYOSLID, LINC02428, and MRPS9-AS1. Receiver operating characteristic (ROC) curves and survival analysis illustrated that the lipid metabolism-LncRM had a significant prognostic value. Further analysis showed that high- and low-risk groups were significantly different in terms of clinical characteristics and immune cells infiltration. CONCLUSIONS: Lipid metabolism-related lncRNAs could predict the prognoses and tumor microenvironment of colon cancer and might be important biomarkers relevant to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01369-8. |
format | Online Article Text |
id | pubmed-9590147 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95901472022-10-25 Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer Lin, Yaobin Xiao, Yu Liu, Shan Hong, Liang Shao, Lingdong Wu, Junxin BMC Med Genomics Research BACKGROUND: Energy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients. METHODS: The transcriptome profile and clinical data of patients with colon cancer were retrieved from The Cancer Genome Atlas database. Using consensus clustering, cases were divided into two clusters and Kaplan–Meier analysis was executed to analyze differences in their prognoses. The gene set enrichment analysis (GSEA) was used to discover biological processes and signaling pathways. A lipid metabolism-related lncRNA prognostic model (lipid metabolism-LncRM) was created utilizing the least absolute shrinkage and selection operator (LASSO) regression. The tumor microenvironment was evaluated on the basis of the composition of immune and stromal cells. RESULTS: The patients in Cluster 2 were found to have a better prognosis and higher expression of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) relative to Cluster 1. The results of GSEA showed the enrichment of energy metabolism pathways in Cluster 2. LASSO regression was used to identify the five LncRNAs that were shown to be most substantially linked to patient prognosis. These were NSMCE1-DT, LINC02084, MYOSLID, LINC02428, and MRPS9-AS1. Receiver operating characteristic (ROC) curves and survival analysis illustrated that the lipid metabolism-LncRM had a significant prognostic value. Further analysis showed that high- and low-risk groups were significantly different in terms of clinical characteristics and immune cells infiltration. CONCLUSIONS: Lipid metabolism-related lncRNAs could predict the prognoses and tumor microenvironment of colon cancer and might be important biomarkers relevant to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01369-8. BioMed Central 2022-10-21 /pmc/articles/PMC9590147/ /pubmed/36280825 http://dx.doi.org/10.1186/s12920-022-01369-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lin, Yaobin Xiao, Yu Liu, Shan Hong, Liang Shao, Lingdong Wu, Junxin Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title | Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title_full | Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title_fullStr | Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title_full_unstemmed | Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title_short | Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer |
title_sort | role of a lipid metabolism-related lncrna signature in risk stratification and immune microenvironment for colon cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9590147/ https://www.ncbi.nlm.nih.gov/pubmed/36280825 http://dx.doi.org/10.1186/s12920-022-01369-8 |
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