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A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer
Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer G...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470855/ https://www.ncbi.nlm.nih.gov/pubmed/36118850 http://dx.doi.org/10.3389/fgene.2022.934196 |
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author | Lu, Jianzhong Tan, Jinhua Yu, Xiaoqing |
author_facet | Lu, Jianzhong Tan, Jinhua Yu, Xiaoqing |
author_sort | Lu, Jianzhong |
collection | PubMed |
description | Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed ferroptosis-related lncRNAs using the differential expression and gene co-expression analysis. Then, univariate and multivariate Cox regression analyses were used to identify the effective ferroptosis-related lncRNAs for constructing the prognostic model for CC. Gene set enrichment analysis (GSEA) was conducted to explore the functional enrichment analysis. CIBERSORT and single-sample GSEA were performed to investigate the association between our model and the immune microenvironment. Finally, three ferroptosis-related lncRNAs (XXbac-B476C20.9, TP73-AS1, and SNHG15) were identified to construct the prognostic model. The results of the validation showed that our model was effective in predicting the prognosis of CC patients, which also was an independent prognostic factor for CC. The GSEA analysis showed that several ferroptosis-related pathways were significantly enriched in the low-risk group. Immune infiltration analysis suggested that the level of immune cell infiltration was significantly higher in the high-risk group than that in the low-risk group. In summary, we established a prognostic model based on the ferroptosis-related lncRNAs, which could provide clinical guidance for future laboratory and clinical research on CC. |
format | Online Article Text |
id | pubmed-9470855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94708552022-09-15 A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer Lu, Jianzhong Tan, Jinhua Yu, Xiaoqing Front Genet Genetics Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed ferroptosis-related lncRNAs using the differential expression and gene co-expression analysis. Then, univariate and multivariate Cox regression analyses were used to identify the effective ferroptosis-related lncRNAs for constructing the prognostic model for CC. Gene set enrichment analysis (GSEA) was conducted to explore the functional enrichment analysis. CIBERSORT and single-sample GSEA were performed to investigate the association between our model and the immune microenvironment. Finally, three ferroptosis-related lncRNAs (XXbac-B476C20.9, TP73-AS1, and SNHG15) were identified to construct the prognostic model. The results of the validation showed that our model was effective in predicting the prognosis of CC patients, which also was an independent prognostic factor for CC. The GSEA analysis showed that several ferroptosis-related pathways were significantly enriched in the low-risk group. Immune infiltration analysis suggested that the level of immune cell infiltration was significantly higher in the high-risk group than that in the low-risk group. In summary, we established a prognostic model based on the ferroptosis-related lncRNAs, which could provide clinical guidance for future laboratory and clinical research on CC. Frontiers Media S.A. 2022-08-31 /pmc/articles/PMC9470855/ /pubmed/36118850 http://dx.doi.org/10.3389/fgene.2022.934196 Text en Copyright © 2022 Lu, Tan and Yu. 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 Lu, Jianzhong Tan, Jinhua Yu, Xiaoqing A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title | A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title_full | A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title_fullStr | A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title_full_unstemmed | A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title_short | A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer |
title_sort | prognostic ferroptosis-related lncrna model associated with immune infiltration in colon cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470855/ https://www.ncbi.nlm.nih.gov/pubmed/36118850 http://dx.doi.org/10.3389/fgene.2022.934196 |
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