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A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation

BACKGROUND: Lipid metabolism is a key factor in tumorigenesis and drug resistance, and models related to lipid metabolism have shown potential to predict survival and curative effects of adjuvant therapy in various cancers. However, the relationship between lipid metabolism and prognosis and treatme...

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Autores principales: Lei, Yangyang, Zhou, Boxuan, Meng, Xiangzhi, Liang, Mei, Song, Weijian, Liang, Yicheng, Gao, Yushun, Wang, Minghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597940/
https://www.ncbi.nlm.nih.gov/pubmed/37874388
http://dx.doi.org/10.1007/s12672-023-00802-3
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author Lei, Yangyang
Zhou, Boxuan
Meng, Xiangzhi
Liang, Mei
Song, Weijian
Liang, Yicheng
Gao, Yushun
Wang, Minghui
author_facet Lei, Yangyang
Zhou, Boxuan
Meng, Xiangzhi
Liang, Mei
Song, Weijian
Liang, Yicheng
Gao, Yushun
Wang, Minghui
author_sort Lei, Yangyang
collection PubMed
description BACKGROUND: Lipid metabolism is a key factor in tumorigenesis and drug resistance, and models related to lipid metabolism have shown potential to predict survival and curative effects of adjuvant therapy in various cancers. However, the relationship between lipid metabolism and prognosis and treatment response of lung adenocarcinoma (LUAD) are still unclear. METHODS: We enrolled seven bulk RNA-sequence datasets (GSE37745, GSE19188, GSE30219, GSE31547, GSE41271, GSE42127, and GSE72094) from the GEO database and one single-cell RNA-sequencing dataset (GSE117570) from the TISCH2 database. Non-negative matrix factorization (NMF) was utilized to construct the risk score model based on lipid score calculated by GSVA algorithm. Phs000452.v3, PMID: 26359337, PMID: 32472114, PRJEB23709 datasets were used to test the response to immunotherapy. Drug sensitivity analysis was assessed according to the GDSC database, and immunotherapy response was evaluated using the Wilcoxon test. Cellular function assays including clone formation, EDU assays and flow cytometry were implemented to explore the phenotype alteration caused by the knockdown of PTDSS1, which is one of key gene in risk score model. RESULTS: We analyzed both bulk and single-cell RNA sequencing data to establish and validate a risk score model based on 18 lipid metabolism-related genes with significant impact on prognosis. After divided the patients into two groups according to risk score, we identified differences in lipid-related metabolic processes and a detailed portrait of the immune landscapes of high- and low-risk groups. Moreover, we investigated the potentials of our risk score in predicting response to immunotherapy and drug sensitivity. In addition, we silenced PTDSS1 in LUAD cell lines, and found that the proliferation of the cells was weakened, and the apoptosis of the cells was increased. CONCLUSION: Our study highlights the crucial roles of lipid metabolism in LUAD and provides a reliable risk score model, which can aid in predicting prognosis and response to immunotherapy. Furthermore, we investigated the roles of PTDSS1 in LUAD carcinogenesis, which showed that PTDSS1 regulated proliferation and apoptosis of LUAD cells. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-023-00802-3.
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spelling pubmed-105979402023-10-26 A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation Lei, Yangyang Zhou, Boxuan Meng, Xiangzhi Liang, Mei Song, Weijian Liang, Yicheng Gao, Yushun Wang, Minghui Discov Oncol Research BACKGROUND: Lipid metabolism is a key factor in tumorigenesis and drug resistance, and models related to lipid metabolism have shown potential to predict survival and curative effects of adjuvant therapy in various cancers. However, the relationship between lipid metabolism and prognosis and treatment response of lung adenocarcinoma (LUAD) are still unclear. METHODS: We enrolled seven bulk RNA-sequence datasets (GSE37745, GSE19188, GSE30219, GSE31547, GSE41271, GSE42127, and GSE72094) from the GEO database and one single-cell RNA-sequencing dataset (GSE117570) from the TISCH2 database. Non-negative matrix factorization (NMF) was utilized to construct the risk score model based on lipid score calculated by GSVA algorithm. Phs000452.v3, PMID: 26359337, PMID: 32472114, PRJEB23709 datasets were used to test the response to immunotherapy. Drug sensitivity analysis was assessed according to the GDSC database, and immunotherapy response was evaluated using the Wilcoxon test. Cellular function assays including clone formation, EDU assays and flow cytometry were implemented to explore the phenotype alteration caused by the knockdown of PTDSS1, which is one of key gene in risk score model. RESULTS: We analyzed both bulk and single-cell RNA sequencing data to establish and validate a risk score model based on 18 lipid metabolism-related genes with significant impact on prognosis. After divided the patients into two groups according to risk score, we identified differences in lipid-related metabolic processes and a detailed portrait of the immune landscapes of high- and low-risk groups. Moreover, we investigated the potentials of our risk score in predicting response to immunotherapy and drug sensitivity. In addition, we silenced PTDSS1 in LUAD cell lines, and found that the proliferation of the cells was weakened, and the apoptosis of the cells was increased. CONCLUSION: Our study highlights the crucial roles of lipid metabolism in LUAD and provides a reliable risk score model, which can aid in predicting prognosis and response to immunotherapy. Furthermore, we investigated the roles of PTDSS1 in LUAD carcinogenesis, which showed that PTDSS1 regulated proliferation and apoptosis of LUAD cells. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-023-00802-3. Springer US 2023-10-24 /pmc/articles/PMC10597940/ /pubmed/37874388 http://dx.doi.org/10.1007/s12672-023-00802-3 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/) .
spellingShingle Research
Lei, Yangyang
Zhou, Boxuan
Meng, Xiangzhi
Liang, Mei
Song, Weijian
Liang, Yicheng
Gao, Yushun
Wang, Minghui
A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title_full A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title_fullStr A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title_full_unstemmed A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title_short A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
title_sort risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597940/
https://www.ncbi.nlm.nih.gov/pubmed/37874388
http://dx.doi.org/10.1007/s12672-023-00802-3
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