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Argininosuccinate lyase is a metabolic vulnerability in breast development and cancer

Argininosuccinate lyase is a metabolic vulnerability in breast development and cancer

Title: Argininosuccinate lyase is a metabolic vulnerability in breast development and cancer
Author: Karvelsson, Sigurður Trausti
Wang, Qiong
Hilmarsdóttir, Bylgja
Sigurðsson, Arnar
Moestue, Siver Andreas
Mælandsmo, Gunhild Mari
Halldórsson, Skarphédinn
Guðmundsson, Steinn   orcid.org/0000-0002-2758-2720
Rolfsson, Óttar   orcid.org/0000-0003-4258-6057
Date: 2021-09-17
Language: English
Scope: 36
Department: Faculty of Medicine
Clinical Laboratory Services, Diagnostics and Blood Bank
Series: npj Systems Biology and Applications; 7(1)
ISSN: 2056-7189
DOI: https://doi.org/10.1038/s41540-021-00195-5
Subject: Brjóstakrabbamein; Erfðafræði; Breast Neoplasms* / genetics; Proteomics; Genome; Argininosuccinate Lyase /genetics; Modeling and Simulation; Biochemistry, Genetics and Molecular Biology (all); Drug Discovery; Computer Science Applications; Applied Mathematics
URI: https://hdl.handle.net/20.500.11815/2959

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Karvelsson , S T , Wang , Q , Hilmarsdóttir , B , Sigurðsson , A , Moestue , S A , Mælandsmo , G M , Halldórsson , S , Guðmundsson , S & Rolfsson , Ó 2021 , ' Argininosuccinate lyase is a metabolic vulnerability in breast development and cancer ' , npj Systems Biology and Applications , vol. 7 , no. 1 , 36 , pp. 36 . https://doi.org/10.1038/s41540-021-00195-5


Epithelial-to-mesenchymal transition (EMT) is fundamental to both normal tissue development and cancer progression. We hypothesized that EMT plasticity defines a range of metabolic phenotypes and that individual breast epithelial metabolic phenotypes are likely to fall within this phenotypic landscape. To determine EMT metabolic phenotypes, the metabolism of EMT was described within genome-scale metabolic models (GSMMs) using either transcriptomic or proteomic data from the breast epithelial EMT cell culture model D492. The ability of the different data types to describe breast epithelial metabolism was assessed using constraint-based modeling which was subsequently verified using 13C isotope tracer analysis. The application of proteomic data to GSMMs provided relatively higher accuracy in flux predictions compared to the transcriptomic data. Furthermore, the proteomic GSMMs predicted altered cholesterol metabolism and increased dependency on argininosuccinate lyase (ASL) following EMT which were confirmed in vitro using drug assays and siRNA knockdown experiments. The successful verification of the proteomic GSMMs afforded iBreast2886, a breast GSMM that encompasses the metabolic plasticity of EMT as defined by the D492 EMT cell culture model. Analysis of breast tumor proteomic data using iBreast2886 identified vulnerabilities within arginine metabolism that allowed prognostic discrimination of breast cancer patients on a subtype-specific level. Taken together, we demonstrate that the metabolic reconstruction iBreast2886 formalizes the metabolism of breast epithelial cell development and can be utilized as a tool for the functional interpretation of high throughput clinical data.


Funding Information: This work was supported by the Icelandic Research Fund (#163254-051), Göngum Saman, and the Norwegian Research Council (#239940). The authors thank Freyr Johannsson and Sarah McGarrity for valuable input regarding constraint-based modeling methodology, 13C isotope tracer, and metabolomics analysis. Publisher Copyright: © 2021, The Author(s).

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