Profiling of protein–protein interactions via single-molecule techniques predicts the dependence of cancers on growth-factor receptors

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.

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Fig. 1: Single-molecule analysis of signalling complexes and PPIs.
Fig. 2: Biased interaction of oncogenic mutant EGFR towards Grb2.
Fig. 3: Interaction of Grb2 with the mutant EGFR signalling complex in a pTyr-independent manner.
Fig. 4: Predictive power of PPI count for the response of receptor-tyrosine-kinase-targeted cancer drugs.
Fig. 5: Predictive power of EGFR PPI count for EGFR-targeted inhibitor responses in lung cancer PDTX models.
Fig. 6: Application of single-molecule co-IP and immunolabelling to human tumour specimens.

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Acknowledgements

We thank S. H. Baek and H. Kim (Seoul National University) for technical assistance with the molecular work. This work was supported by the Samsung Science and Technology Foundation under project number SSTF-BA1301-10. Generation of the patient-derived cell lines and tumour xenograft models was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Science and ICT (to B.C.C.; project number 2016R1A2B3016282).

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H.-W.L., J.C., S.-H.L., S.-A.I., B.C.C. and T.-Y.Y. designed the experiments. H.-W.L., B.C., H.K., S.P., M.C., C.J. and T.-Y.Y. performed the single-molecule experiments. H.N.K., J.S., K.S., S.-H.L. and B.C.C. characterized the lung adenocarcinoma cells. A.M. and S.-A.I. characterized the breast cancer cells. H.N.K., M.R.Y., J.Y.H. and B.C.C. generated the PDTXs and measured their drug responses. H.-W.L., J.Y.R. and M.J.S. developed the single-molecule imaging and analysis programs. H.-W.L. and H.K. performed the PLA analysis. H.-W.L. and T.-Y.Y. wrote the paper with input from all authors.

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Correspondence to Seock-Ah Im or Byoung Chul Cho or Tae-Young Yoon.

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Competing interests

H.-W.L. and T.-Y.Y. hold a patent based on these findings (PCT/KR2014/010299). S.-A.I. received research funding from AstraZeneca and acts in an advisory role for Novartis and AstraZeneca. H.-W.L. and J.Y.R. are senior scientists at Proteina.

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Lee, H., Choi, B., Kang, H.N. et al. Profiling of protein–protein interactions via single-molecule techniques predicts the dependence of cancers on growth-factor receptors. Nat Biomed Eng 2, 239–253 (2018). https://doi.org/10.1038/s41551-018-0212-3

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