Profiling of protein-protein interactions via single-molecule techniques predicts the dependence of cancers on growth-factor receptors
SCIE
SCOPUS
- Title
- Profiling of protein-protein interactions via single-molecule techniques predicts the dependence of cancers on growth-factor receptors
- Authors
- Lee, Hong-Won; Choi, Byoungsan; Kang, Han Na; Kim, Hyunwoo; Min, Ahrum; Cha, Minkwon; Ryu, Ji Young; Park, Sangwoo; Sohn, Jinyoung; Shin, Kihyuk; Yun, Mi Ran; Han, Joo Yeun; Shon, Min Ju; Jeong, Cherlhyun; Chung, Junho; Lee, Seung-Hyo; Im, Seock-Ah; Cho, Byoung Chul; Yoon, Tae-Young
- Date Issued
- 2018-04
- Publisher
- NATURE PUBLISHING GROUP
- Abstract
- The accumulation of genetic and epigenetic alterations in cancer cells rewires cellular signalling pathways through changes in the patterns of protein-protein interactions (PPIs). Understanding these patterns may facilitate the design of tailored cancer therapies. Here, we show that single-molecule pull-down and co-immunoprecipitation techniques can be used to characterize signalling complexes of the human epidermal growth-factor receptor (HER) family in specific cancers. By analysing cancer-specific signalling phenotypes, including post-translational modifications and PPIs with downstream interactions, we found that activating mutations of the epidermal growth-factor receptor (EGFR) gene led to the formation of large protein complexes surrounding mutant EGFR proteins and to a reduction in the dependency of mutant EGFR signalling on phosphotyrosine residues, and that the strength of HER-family PPIs is correlated with the strength of the dependence of breast and lung adenocarcinoma cells on HER-family signalling pathways. Furthermore, using co-immunoprecipitation profiling to screen for EGFR-dependent cancers, we identified non-small-cell lung cancers that respond to an EGFR-targeted inhibitor. Our approach might help predict responses to targeted cancer therapies, particularly for cancers that lack actionable genomic mutations.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/106618
- DOI
- 10.1038/s41551-018-0212-3
- ISSN
- 2157-846X
- Article Type
- Article
- Citation
- Nature Biomedical Engineering, vol. 2, no. 4, page. 239 - 253, 2018-04
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