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一种整合系统生物学与实验的方法确定上皮可塑性、代谢和自噬的趋同以促进化疗耐药性。

An Integrative Systems Biology and Experimental Approach Identifies Convergence of Epithelial Plasticity, Metabolism, and Autophagy to Promote Chemoresistance.

作者信息

Xu Shengnan, Ware Kathryn E, Ding Yuantong, Kim So Young, Sheth Maya U, Rao Sneha, Chan Wesley, Armstrong Andrew J, Eward William C, Jolly Mohit Kumar, Somarelli Jason A

机构信息

Duke Cancer Institute and the Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA.

Department of Biology, Duke University Medical Center, Durham, NC 27710, USA.

出版信息

J Clin Med. 2019 Feb 7;8(2):205. doi: 10.3390/jcm8020205.

Abstract

The evolution of therapeutic resistance is a major cause of death for cancer patients. The development of therapy resistance is shaped by the ecological dynamics within the tumor microenvironment and the selective pressure of the host immune system. These selective forces often lead to evolutionary convergence on pathways or hallmarks that drive progression. Thus, a deeper understanding of the evolutionary convergences that occur could reveal vulnerabilities to treat therapy-resistant cancer. To this end, we combined phylogenetic clustering, systems biology analyses, and molecular experimentation to identify convergences in gene expression data onto common signaling pathways. We applied these methods to derive new insights about the networks at play during transforming growth factor-β (TGF-β)-mediated epithelial⁻mesenchymal transition in lung cancer. Phylogenetic analyses of gene expression data from TGF-β-treated cells revealed convergence of cells toward amine metabolic pathways and autophagy during TGF-β treatment. Knockdown of the autophagy regulatory, ATG16L1, re-sensitized lung cancer cells to cancer therapies following TGF-β-induced resistance, implicating autophagy as a TGF-β-mediated chemoresistance mechanism. In addition, high ATG16L expression was found to be a poor prognostic marker in multiple cancer types. These analyses reveal the usefulness of combining evolutionary and systems biology methods with experimental validation to illuminate new therapeutic vulnerabilities for cancer.

摘要

治疗耐药性的演变是癌症患者死亡的主要原因。治疗耐药性的发展受到肿瘤微环境内的生态动力学和宿主免疫系统的选择压力的影响。这些选择力常常导致在驱动疾病进展的途径或特征上出现进化趋同。因此,深入了解所发生的进化趋同可能会揭示治疗耐药性癌症的脆弱性。为此,我们结合了系统发育聚类、系统生物学分析和分子实验,以确定基因表达数据在常见信号通路中的趋同情况。我们应用这些方法来获得关于肺癌中转化生长因子-β(TGF-β)介导的上皮-间质转化过程中发挥作用的网络的新见解。对TGF-β处理细胞的基因表达数据进行系统发育分析发现,在TGF-β处理期间,细胞向胺代谢途径和自噬趋同。在TGF-β诱导耐药后,敲低自噬调节因子ATG16L1可使肺癌细胞对癌症治疗重新敏感,这表明自噬是一种TGF-β介导的化疗耐药机制。此外,发现高ATG16L表达是多种癌症类型中预后不良的标志物。这些分析揭示了将进化生物学和系统生物学方法与实验验证相结合以阐明癌症新治疗脆弱性的有用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2382/6406733/ebf7aaf10446/jcm-08-00205-g001.jpg

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