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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.

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/4ab5/10052244/7eb57120221d/nihpp-2023.03.09.532000v1-f0001.jpg

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