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CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis
BACKGROUND: Increasing evidence suggests that the metabolism of lipids plays a crucial role in the progression of gastric cancer. However, the expression of lipid metabolism-related genes (LMGs) still does not serve as a prognostic biomarker in gastric cancer. METHODS: We obtained transcriptome data...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10544546/ https://www.ncbi.nlm.nih.gov/pubmed/37784135 http://dx.doi.org/10.1186/s12920-023-01664-y |
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author | Zhou, Xinyi Meng, Fanyu Xiao, Linmei Shen, Hua |
author_facet | Zhou, Xinyi Meng, Fanyu Xiao, Linmei Shen, Hua |
author_sort | Zhou, Xinyi |
collection | PubMed |
description | BACKGROUND: Increasing evidence suggests that the metabolism of lipids plays a crucial role in the progression of gastric cancer. However, the expression of lipid metabolism-related genes (LMGs) still does not serve as a prognostic biomarker in gastric cancer. METHODS: We obtained transcriptome data for 751 LMGs and divided STAD patients into two subtypes based on differences in LMGs expression. Then, we analyzed genetic changes in two subtypes as well as immune features to determine their differences. We also constructed a prognostic risk model related to LMGs for individualized comprehensive evaluations. RESULTS: In this study, two lipid metabolic (LM) subtypes were identified anchored in the expression profiles of LMGs. Clinical information, genomic alterations, immune features, and immunotherapy response varied significantly between the two LM subtypes. A risk model based on LMGs was also developed to assess prognosis and distinguish patients with high risk from those at low risk. The prognosis differed significantly between the two risk groups of patients. In STAD patients, the risk score was strongly correlated with genomic alterations and immune profile scores. Also, the risk score was an excellent predictor of immune checkpoint inhibitors (ICIs) response. Anchored in preliminary results derived from the aforementioned bioinformatic analysis, we chose CYP19A1 as our target gene and the expression of CYP19A1 was verified in several common gastric cancer cell lines. Then, we carried out the Western blotting, CCK-8 assay, colony formation assay, wound healing assay, and transwell assay to explore the effects of CYP19A1 on malignant biological behavior, and positive consequences were obtained. CONCLUSIONS: In this study, STAD patients were divided into two subtypes based on LMGs expression. It is possible to assess the prognosis of a patient and the response to immunotherapy using the established prognostic risk model. A series of basic laboratory experiments also verified the functional role of CYP19A1 in gastric cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01664-y. |
format | Online Article Text |
id | pubmed-10544546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105445462023-10-03 CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis Zhou, Xinyi Meng, Fanyu Xiao, Linmei Shen, Hua BMC Med Genomics Research BACKGROUND: Increasing evidence suggests that the metabolism of lipids plays a crucial role in the progression of gastric cancer. However, the expression of lipid metabolism-related genes (LMGs) still does not serve as a prognostic biomarker in gastric cancer. METHODS: We obtained transcriptome data for 751 LMGs and divided STAD patients into two subtypes based on differences in LMGs expression. Then, we analyzed genetic changes in two subtypes as well as immune features to determine their differences. We also constructed a prognostic risk model related to LMGs for individualized comprehensive evaluations. RESULTS: In this study, two lipid metabolic (LM) subtypes were identified anchored in the expression profiles of LMGs. Clinical information, genomic alterations, immune features, and immunotherapy response varied significantly between the two LM subtypes. A risk model based on LMGs was also developed to assess prognosis and distinguish patients with high risk from those at low risk. The prognosis differed significantly between the two risk groups of patients. In STAD patients, the risk score was strongly correlated with genomic alterations and immune profile scores. Also, the risk score was an excellent predictor of immune checkpoint inhibitors (ICIs) response. Anchored in preliminary results derived from the aforementioned bioinformatic analysis, we chose CYP19A1 as our target gene and the expression of CYP19A1 was verified in several common gastric cancer cell lines. Then, we carried out the Western blotting, CCK-8 assay, colony formation assay, wound healing assay, and transwell assay to explore the effects of CYP19A1 on malignant biological behavior, and positive consequences were obtained. CONCLUSIONS: In this study, STAD patients were divided into two subtypes based on LMGs expression. It is possible to assess the prognosis of a patient and the response to immunotherapy using the established prognostic risk model. A series of basic laboratory experiments also verified the functional role of CYP19A1 in gastric cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01664-y. BioMed Central 2023-10-02 /pmc/articles/PMC10544546/ /pubmed/37784135 http://dx.doi.org/10.1186/s12920-023-01664-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Zhou, Xinyi Meng, Fanyu Xiao, Linmei Shen, Hua CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title | CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title_full | CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title_fullStr | CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title_full_unstemmed | CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title_short | CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
title_sort | cyp19a1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10544546/ https://www.ncbi.nlm.nih.gov/pubmed/37784135 http://dx.doi.org/10.1186/s12920-023-01664-y |
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