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Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer

BACKGROUND: Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. METHODS: Clinical i...

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Autores principales: Wang, Zhiyu, Zhang, Zhuoqi, Zhang, Ke, Zhou, Qiaoxia, Chen, Sidong, Zheng, Hao, Wang, Guoqiang, Cai, Shangli, Wang, Fujing, Li, Shenglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117699/
https://www.ncbi.nlm.nih.gov/pubmed/35600382
http://dx.doi.org/10.3389/fonc.2022.881953
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author Wang, Zhiyu
Zhang, Zhuoqi
Zhang, Ke
Zhou, Qiaoxia
Chen, Sidong
Zheng, Hao
Wang, Guoqiang
Cai, Shangli
Wang, Fujing
Li, Shenglong
author_facet Wang, Zhiyu
Zhang, Zhuoqi
Zhang, Ke
Zhou, Qiaoxia
Chen, Sidong
Zheng, Hao
Wang, Guoqiang
Cai, Shangli
Wang, Fujing
Li, Shenglong
author_sort Wang, Zhiyu
collection PubMed
description BACKGROUND: Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. METHODS: Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on. RESULTS: The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42–0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43–0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42–0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45–0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells. CONCLUSION: We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment.
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spelling pubmed-91176992022-05-20 Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer Wang, Zhiyu Zhang, Zhuoqi Zhang, Ke Zhou, Qiaoxia Chen, Sidong Zheng, Hao Wang, Guoqiang Cai, Shangli Wang, Fujing Li, Shenglong Front Oncol Oncology BACKGROUND: Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. METHODS: Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on. RESULTS: The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42–0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43–0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42–0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45–0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells. CONCLUSION: We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment. Frontiers Media S.A. 2022-05-05 /pmc/articles/PMC9117699/ /pubmed/35600382 http://dx.doi.org/10.3389/fonc.2022.881953 Text en Copyright © 2022 Wang, Zhang, Zhang, Zhou, Chen, Zheng, Wang, Cai, Wang and Li 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 Oncology
Wang, Zhiyu
Zhang, Zhuoqi
Zhang, Ke
Zhou, Qiaoxia
Chen, Sidong
Zheng, Hao
Wang, Guoqiang
Cai, Shangli
Wang, Fujing
Li, Shenglong
Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title_full Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title_fullStr Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title_full_unstemmed Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title_short Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer
title_sort multi-omics characterization of a glycerolipid metabolism-related gene enrichment score in colon cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117699/
https://www.ncbi.nlm.nih.gov/pubmed/35600382
http://dx.doi.org/10.3389/fonc.2022.881953
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