Modelling the role of dual specificity phosphatases in herceptin resistant breast cancer cell lines

被引:3
作者
Buiga, Petronela [1 ,2 ]
Elson, Ari [1 ]
Tabernero, Lydia [2 ]
Schwartz, Jean-Marc [2 ]
机构
[1] Weizmann Inst Sci, Dept Mol Genet, Rehovot, Israel
[2] Univ Manchester, Fac Biol Med & Hlth, Sch Biol Sci, Manchester, Lancs, England
基金
奥地利科学基金会;
关键词
Boolean model; Herceptin; Breast cancer; Drug resistance; Dual-specificity phosphatase; PROTEIN-KINASE PHOSPHATASE-1; TRASTUZUMAB RESISTANCE; SIGNALING NETWORK; INHIBITOR; BIOLOGY;
D O I
10.1016/j.compbiolchem.2019.03.018
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Breast cancer remains the most lethal type of cancer for women. A significant proportion of breast cancer cases are characterised by overexpression of the human epidermal growth factor receptor 2 protein (HER2). These cancers are commonly treated by Herceptin (Trastuzumab), but resistance to drug treatment frequently develops in tumour cells. Dual-specificity phosphatases (DUSPs) are thought to play a role in the mechanism of resistance, since some of them were reported to be overexpressed in tumours resistant to Herceptin. Results: We used a systems biology approach to investigate how DUSP overexpression could favour cell proliferation and to predict how this mechanism could be reversed by targeted inhibition of selected DUSPs. We measured the expression of 20 DUSP genes in two breast cancer cell lines following long-term (6 months) exposure to Herceptin, after confirming that these cells had become resistant to the drug. We constructed several Boolean models including specific substrates of each DUSP, and showed that our models correctly account for resistance when overexpressed DUSPs were kept activated. We then simulated inhibition of both individual and combinations of DUSPs, and determined conditions under which the resistance could be reversed. Conclusions: These results show how a combination of experimental analysis and modelling help to understand cell survival mechanisms in breast cancer tumours, and crucially enable us to generate testable predictions potentially leading to new treatments of resistant tumours.
引用
收藏
页码:138 / 146
页数:9
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