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Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer
Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hyp...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9599075/ https://www.ncbi.nlm.nih.gov/pubmed/36291742 http://dx.doi.org/10.3390/biom12101533 |
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author | Li, Yaning Liang, Xinyue Che, Gang Chen, Yutong Luo, Lisi Liu, Kecheng Xie, Rongzhi Zeng, Linjuan |
author_facet | Li, Yaning Liang, Xinyue Che, Gang Chen, Yutong Luo, Lisi Liu, Kecheng Xie, Rongzhi Zeng, Linjuan |
author_sort | Li, Yaning |
collection | PubMed |
description | Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles. |
format | Online Article Text |
id | pubmed-9599075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95990752022-10-27 Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer Li, Yaning Liang, Xinyue Che, Gang Chen, Yutong Luo, Lisi Liu, Kecheng Xie, Rongzhi Zeng, Linjuan Biomolecules Article Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles. MDPI 2022-10-21 /pmc/articles/PMC9599075/ /pubmed/36291742 http://dx.doi.org/10.3390/biom12101533 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Yaning Liang, Xinyue Che, Gang Chen, Yutong Luo, Lisi Liu, Kecheng Xie, Rongzhi Zeng, Linjuan Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title | Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title_full | Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title_fullStr | Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title_full_unstemmed | Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title_short | Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer |
title_sort | molecular classification of genes associated with hypoxic lipid metabolism in pancreatic cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9599075/ https://www.ncbi.nlm.nih.gov/pubmed/36291742 http://dx.doi.org/10.3390/biom12101533 |
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