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Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer
BACKGROUND: The interaction between tumor cells and immune or non-immune stromal cells creates a unique tumor microenvironment, which plays an important role in the growth, invasion and metastasis of gastric cancer (GC). METHODS: The candidate genes were selected to construct risk-score by univariat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158005/ https://www.ncbi.nlm.nih.gov/pubmed/37138287 http://dx.doi.org/10.1186/s12920-023-01515-w |
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author | Dai, Jing Li, Qiqing Quan, Jun Webb, Gunther Liu, Juan Gao, Kai |
author_facet | Dai, Jing Li, Qiqing Quan, Jun Webb, Gunther Liu, Juan Gao, Kai |
author_sort | Dai, Jing |
collection | PubMed |
description | BACKGROUND: The interaction between tumor cells and immune or non-immune stromal cells creates a unique tumor microenvironment, which plays an important role in the growth, invasion and metastasis of gastric cancer (GC). METHODS: The candidate genes were selected to construct risk-score by univariate and multivariate Cox regression analysis. Nomograms were constructed by combining clinical pathological factors, and the model performance was evaluated by receiver operating characteristic curve, decision curve analysis, net reclassification improvement and integrated discrimination improvement. The functional enrichment between high-risk group (HRisk) and low-risk group (LRisk) was explored through GO, KEGG, GSVA and ssGSEA. CIBERSORT, quanTIseq and xCell were used to explore the immune cell infiltration between HRisk and LRisk. The relevant EMT scores, macrophage infiltration scores and various metabolic scores were calculated through the “IOBR” package and analyzed visually. RESULTS: Through univariate and multivariate Cox regression analysis, we obtained the risk-score of fittings six lipid metabolism related genes (LMAGs). Through survival analysis, we found that risk-score has significant prognostic significance and can accurately reflect the metabolic level of patients. The AUCs of the nomogram model incorporating risk-score 1, 3 and 5 years were 0.725, 0.729 and 0.749 respectively. In addition, it was found that the inclusion of risk-score could significantly improve the prediction performance of the model. It was found that the arachidonic acid metabolism and prostaglandin synthesis were up-regulated in HRisk, and more tumor metastasis related markers and immune related pathways were also enriched. Further study found that HRisk had higher immune score and M2 macrophage infiltration. More importantly, the immune checkpoints of tumor associated macrophages involved in tumor antigen recognition disorders increased significantly. We also found that ST6GALNAC3 can promote arachidonic acid metabolism and up-regulate prostaglandin synthesis, increase M2 macrophage infiltration, induce epithelial mesenchymal transformation, and affect the prognosis of patients. CONCLUSIONS: Our research found a novel and powerful LMAGs signature. Six-LMAGs features can effectively evaluate the prognosis of GC patients and reflect the metabolic and immune status. ST6GALNAC3 may be a potential prognostic marker to improve the survival rate and prognostic accuracy of GC patients, and may even be a potential biomarker of GC patients, indicating the response to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01515-w. |
format | Online Article Text |
id | pubmed-10158005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101580052023-05-05 Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer Dai, Jing Li, Qiqing Quan, Jun Webb, Gunther Liu, Juan Gao, Kai BMC Med Genomics Research BACKGROUND: The interaction between tumor cells and immune or non-immune stromal cells creates a unique tumor microenvironment, which plays an important role in the growth, invasion and metastasis of gastric cancer (GC). METHODS: The candidate genes were selected to construct risk-score by univariate and multivariate Cox regression analysis. Nomograms were constructed by combining clinical pathological factors, and the model performance was evaluated by receiver operating characteristic curve, decision curve analysis, net reclassification improvement and integrated discrimination improvement. The functional enrichment between high-risk group (HRisk) and low-risk group (LRisk) was explored through GO, KEGG, GSVA and ssGSEA. CIBERSORT, quanTIseq and xCell were used to explore the immune cell infiltration between HRisk and LRisk. The relevant EMT scores, macrophage infiltration scores and various metabolic scores were calculated through the “IOBR” package and analyzed visually. RESULTS: Through univariate and multivariate Cox regression analysis, we obtained the risk-score of fittings six lipid metabolism related genes (LMAGs). Through survival analysis, we found that risk-score has significant prognostic significance and can accurately reflect the metabolic level of patients. The AUCs of the nomogram model incorporating risk-score 1, 3 and 5 years were 0.725, 0.729 and 0.749 respectively. In addition, it was found that the inclusion of risk-score could significantly improve the prediction performance of the model. It was found that the arachidonic acid metabolism and prostaglandin synthesis were up-regulated in HRisk, and more tumor metastasis related markers and immune related pathways were also enriched. Further study found that HRisk had higher immune score and M2 macrophage infiltration. More importantly, the immune checkpoints of tumor associated macrophages involved in tumor antigen recognition disorders increased significantly. We also found that ST6GALNAC3 can promote arachidonic acid metabolism and up-regulate prostaglandin synthesis, increase M2 macrophage infiltration, induce epithelial mesenchymal transformation, and affect the prognosis of patients. CONCLUSIONS: Our research found a novel and powerful LMAGs signature. Six-LMAGs features can effectively evaluate the prognosis of GC patients and reflect the metabolic and immune status. ST6GALNAC3 may be a potential prognostic marker to improve the survival rate and prognostic accuracy of GC patients, and may even be a potential biomarker of GC patients, indicating the response to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01515-w. BioMed Central 2023-05-03 /pmc/articles/PMC10158005/ /pubmed/37138287 http://dx.doi.org/10.1186/s12920-023-01515-w Text en © The Author(s) 2023 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 Dai, Jing Li, Qiqing Quan, Jun Webb, Gunther Liu, Juan Gao, Kai Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title | Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title_full | Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title_fullStr | Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title_full_unstemmed | Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title_short | Construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
title_sort | construction of a lipid metabolism-related and immune-associated prognostic score for gastric cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158005/ https://www.ncbi.nlm.nih.gov/pubmed/37138287 http://dx.doi.org/10.1186/s12920-023-01515-w |
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