• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于集成的基因组规模建模预测结直肠癌中巨噬细胞亚型之间的代谢差异。

Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer.

作者信息

Gelbach Patrick E, Finley Stacey D

机构信息

Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.

Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.

出版信息

bioRxiv. 2023 Mar 11:2023.03.09.532000. doi: 10.1101/2023.03.09.532000.

DOI:10.1101/2023.03.09.532000
PMID:36993493
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10052244/
Abstract

1Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment, which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the tumor microenvironment. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

摘要
  1. 结直肠癌(CRC)的发病率和死亡率都很高,部分原因在于肿瘤微环境,它被视为疾病进展的积极推动者。巨噬细胞是肿瘤微环境中数量最多的细胞之一。这些免疫细胞通常分为具有炎症和抗癌特性的M1型,以及促进肿瘤增殖和存活的M2型。尽管M1/M2亚分类方案受代谢的影响很大,但各亚型之间的代谢差异仍知之甚少。因此,我们生成了一套计算模型来表征M1和M2特异性代谢状态。我们的模型显示了M1和M2代谢网络及能力之间的关键差异。我们利用这些模型来识别能使M2巨噬细胞的代谢状态更接近M1细胞的代谢扰动。总体而言,这项工作增进了对结直肠癌中巨噬细胞代谢的理解,并阐明了促进抗肿瘤巨噬细胞代谢状态的策略。
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/a0b1a4f6ddda/nihpp-2023.03.09.532000v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/7eb57120221d/nihpp-2023.03.09.532000v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/b309d7cabb3d/nihpp-2023.03.09.532000v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/780396db3102/nihpp-2023.03.09.532000v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/81ffda4ffca3/nihpp-2023.03.09.532000v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/a0b1a4f6ddda/nihpp-2023.03.09.532000v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/7eb57120221d/nihpp-2023.03.09.532000v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/b309d7cabb3d/nihpp-2023.03.09.532000v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/780396db3102/nihpp-2023.03.09.532000v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/81ffda4ffca3/nihpp-2023.03.09.532000v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ab5/10052244/a0b1a4f6ddda/nihpp-2023.03.09.532000v1-f0005.jpg

相似文献

1
Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer.基于集成的基因组规模建模预测结直肠癌中巨噬细胞亚型之间的代谢差异。
bioRxiv. 2023 Mar 11:2023.03.09.532000. doi: 10.1101/2023.03.09.532000.
2
Genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer.全基因组规模建模预测结直肠癌中巨噬细胞亚型之间的代谢差异。
iScience. 2023 Aug 9;26(9):107569. doi: 10.1016/j.isci.2023.107569. eCollection 2023 Sep 15.
3
Tumor cells-derived exosomal circVCP promoted the progression of colorectal cancer by regulating macrophage M1/M2 polarization.肿瘤细胞来源的外泌体 circVCP 通过调节巨噬细胞 M1/M2 极化促进结直肠癌的进展。
Gene. 2023 Jun 20;870:147413. doi: 10.1016/j.gene.2023.147413. Epub 2023 Apr 5.
4
Effect of colorectal cancer-derived extracellular vesicles on the immunophenotype and cytokine secretion profile of monocytes and macrophages.结直肠癌来源的细胞外囊泡对单核细胞和巨噬细胞免疫表型和细胞因子分泌谱的影响。
Cell Commun Signal. 2018 Apr 24;16(1):17. doi: 10.1186/s12964-018-0229-y.
5
EZH2 Inhibitors Suppress Colorectal Cancer by Regulating Macrophage Polarization in the Tumor Microenvironment.EZH2 抑制剂通过调节肿瘤微环境中的巨噬细胞极化抑制结直肠癌。
Front Immunol. 2022 Apr 1;13:857808. doi: 10.3389/fimmu.2022.857808. eCollection 2022.
6
Dysregulated metabolism: A friend-to-foe skewer of macrophages.代谢失调:巨噬细胞从朋友到敌人的转变。
Int Rev Immunol. 2023;42(4):287-303. doi: 10.1080/08830185.2022.2095374. Epub 2022 Jul 6.
7
TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content.肿瘤坏死因子相关凋亡诱导配体(TRAIL)可促进人类巨噬细胞向促炎性M1表型极化,并且与肿瘤巨噬细胞含量高的癌症患者生存率提高相关。
Front Immunol. 2023 Sep 21;14:1209249. doi: 10.3389/fimmu.2023.1209249. eCollection 2023.
8
The distribution of macrophages with a M1 or M2 phenotype in relation to prognosis and the molecular characteristics of colorectal cancer.M1 型和 M2 型巨噬细胞在结直肠癌中的分布与预后及分子特征的关系。
PLoS One. 2012;7(10):e47045. doi: 10.1371/journal.pone.0047045. Epub 2012 Oct 15.
9
Risk stratification of patients with right-sided colorectal cancer based on the tumor-infiltrating M1 macrophage.基于肿瘤浸润性M1巨噬细胞的右半结肠癌患者风险分层
Am J Cancer Res. 2022 Dec 15;12(12):5532-5551. eCollection 2022.
10
2-methylpyridine-1-ium-1-sulfonate modifies tumor-derived exosome mediated macrophage polarization: Relevance to the tumor microenvironment.2-甲基吡啶-1-磺酸根修饰肿瘤来源的外泌体介导的巨噬细胞极化:与肿瘤微环境的相关性。
Int Immunopharmacol. 2022 May;106:108581. doi: 10.1016/j.intimp.2022.108581. Epub 2022 Feb 8.

本文引用的文献

1
An integrated toolbox to profile macrophage immunometabolism.一种用于描绘巨噬细胞免疫代谢特征的综合工具包。
Cell Rep Methods. 2022 Mar 28;2(4):100192. doi: 10.1016/j.crmeth.2022.100192. eCollection 2022 Apr 25.
2
Intercellular communications and metabolic reprogramming as new predictive markers for immunotherapy responses in gastric cancer.细胞间通讯和代谢重编程作为胃癌免疫治疗反应的新预测标志物。
Cancer Commun (Lond). 2022 Jun;42(6):572-575. doi: 10.1002/cac2.12285. Epub 2022 Apr 9.
3
Eicosanoid production by macrophages during inflammation depends on the M1/M2 phenotype.
炎症期间巨噬细胞产生类花生酸取决于M1/M2表型。
Prostaglandins Other Lipid Mediat. 2022 Jun;160:106635. doi: 10.1016/j.prostaglandins.2022.106635. Epub 2022 Mar 18.
4
Systems-based approaches to study immunometabolism.基于系统的方法研究免疫代谢。
Cell Mol Immunol. 2022 Mar;19(3):409-420. doi: 10.1038/s41423-021-00783-9. Epub 2022 Feb 4.
5
Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics.通过整合基于约束的模型和 LC-MS 代谢组学阐明结直肠癌中的肿瘤-基质代谢串扰。
Metab Eng. 2022 Jan;69:175-187. doi: 10.1016/j.ymben.2021.11.006. Epub 2021 Nov 25.
6
Macrophage Reprogramming and Cancer Therapeutics: Role of iNOS-Derived NO.巨噬细胞重编程与癌症治疗学:iNOS 衍生的 NO 的作用。
Cells. 2021 Nov 16;10(11):3194. doi: 10.3390/cells10113194.
7
Macrophage polarization state affects lipid composition and the channeling of exogenous fatty acids into endogenous lipid pools.巨噬细胞极化状态影响脂质组成和外源性脂肪酸进入内源性脂质池的途径。
J Biol Chem. 2021 Dec;297(6):101341. doi: 10.1016/j.jbc.2021.101341. Epub 2021 Oct 23.
8
Reactive Oxygen Species in Macrophages: Sources and Targets.巨噬细胞中的活性氧物种:来源和靶点。
Front Immunol. 2021 Sep 30;12:734229. doi: 10.3389/fimmu.2021.734229. eCollection 2021.
9
Confronting false discoveries in single-cell differential expression.单细胞差异表达中虚假发现的应对策略。
Nat Commun. 2021 Sep 28;12(1):5692. doi: 10.1038/s41467-021-25960-2.
10
Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.用于研究肿瘤微环境中细胞间代谢竞争的基因组规模建模
Cancers (Basel). 2021 Sep 14;13(18):4609. doi: 10.3390/cancers13184609.