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.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$99.00 per year
only $8.25 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout






Similar content being viewed by others
References
Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).
Kandoth, C. et al. Mutational landscape and significance across 12 major cancer types. Nature 502, 333–339 (2013).
Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011).
McGranahan, N. & Swanton, C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 27, 15–26 (2015).
Citri, A. & Yarden, Y. EGF–ERBB signalling: towards the systems level. Nat. Rev. Mol. Cell Biol. 7, 505–516 (2006).
Pawson, T. & Nash, P. Protein–protein interactions define specificity in signal transduction. Genes Dev. 14, 1027–1047 (2000).
Rolland, T. et al. A proteome-scale map of the human interactome network. Cell 159, 1212–1226 (2014).
Huttlin, E. L. et al. Architecture of the human interactome defines protein communities and disease networks. Nature 545, 505–509 (2017).
Scholl, C. et al. Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell 137, 821–834 (2009).
Houle, D., Govindaraju, D. R. & Omholt, S. Phenomics: the next challenge. Nat. Rev. Genet. 11, 855–866 (2010).
Rual, J. F. et al. Towards a proteome-scale map of the human protein–protein interaction network. Nature 437, 1173–1178 (2005).
Jain, A. et al. Probing cellular protein complexes using single-molecule pull-down. Nature 473, 484–488 (2011).
Jain, A., Liu, R., Xiang, Y. K. & Ha, T. Single-molecule pull-down for studying protein interactions. Nat. Protoc. 7, 445–452 (2012).
Lee, H. W. et al. Real-time single-molecule co-immunoprecipitation analyses reveal cancer-specific Ras signalling dynamics. Nat. Commun. 4, 1505 (2013).
Lee, H. W. et al. Real-time single-molecule coimmunoprecipitation of weak protein–protein interactions. Nat. Protoc. 8, 2045–2060 (2013).
Eid, J. et al. Real-time DNA sequencing from single polymerase molecules. Science 323, 133–138 (2009).
Lemmon, M. A. & Schlessinger, J. Cell signaling by receptor tyrosine kinases. Cell 141, 1117–1134 (2010).
Zhang, X., Gureasko, J., Shen, K., Cole, P. A. & Kuriyan, J. An allosteric mechanism for activation of the kinase domain of epidermal growth factor receptor. Cell 125, 1137–1149 (2006).
Seet, B. T., Dikic, I., Zhou, M. M. & Pawson, T. Reading protein modifications with interaction domains. Nat. Rev. Mol. Cell Biol. 7, 473–483 (2006).
Rozakis-Adcock, M. et al. Association of the Shc and Grb2/Sem5 SH2-containing proteins is implicated in activation of the Ras pathway by tyrosine kinases. Nature 360, 689–692 (1992).
Jones, R. B., Gordus, A., Krall, J. A. & MacBeath, G. A quantitative protein interaction network for the ErbB receptors using protein microarrays. Nature 439, 168–174 (2006).
Chen, D. et al. Regulation of transcription by a protein methyltransferase. Science 284, 2174–2177 (1999).
Wan, P. T. et al. Mechanism of activation of the RAF–ERK signaling pathway by oncogenic mutations of B-RAF. Cell 116, 855–867 (2004).
Falchook, G. S. et al. Dabrafenib in patients with melanoma, untreated brain metastases, and other solid tumours: a phase 1 dose-escalation trial. Lancet 379, 1893–1901 (2012).
The Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).
Sharma, S. V., Bell, D. W., Settleman, J. & Haber, D. A. Epidermal growth factor receptor mutations in lung cancer. Nat. Rev. Cancer 7, 169–181 (2007).
Batzer, A. G., Rotin, D., Urena, J. M., Skolnik, E. Y. & Schlessinger, J. Hierarchy of binding sites for Grb2 and Shc on the epidermal growth factor receptor. Mol. Cell. Biol. 14, 5192–5201 (1994).
Tanaka, M., Gupta, R. & Mayer, B. J. Differential inhibition of signaling pathways by dominant-negative SH2/SH3 adapter proteins. Mol. Cell. Biol. 15, 6829–6837 (1995).
Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).
Lynch, T. J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).
Pao, W. et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med. 2, e73 (2005).
Cross, D. A. et al. AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov. 4, 1046–1061 (2014).
Yang, S. et al. Association with HSP90 inhibits Cbl-mediated down-regulation of mutant epidermal growth factor receptors. Cancer Res. 66, 6990–6997 (2006).
Zhang, X. et al. Inhibition of the EGF receptor by binding of MIG6 to an activating kinase domain interface. Nature 450, 741–744 (2007).
Petschnigg, J. et al. The mammalian-membrane two-hybrid assay (MaMTH) for probing membrane–protein interactions in human cells. Nat. Methods 11, 585–592 (2014).
The Cancer Genome Atlas Research Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).
Hudis, C. A. Trastuzumab—mechanism of action and use in clinical practice. N. Engl. J. Med. 357, 39–51 (2007).
Musolino, A. et al. Immunoglobulin G fragment C receptor polymorphisms and clinical efficacy of trastuzumab-based therapy in patients with HER-2/neu-positive metastatic breast cancer. J. Clin. Oncol. 26, 1789–1796 (2008).
Cho, H. S. et al. Structure of the extracellular region of HER2 alone and in complex with the Herceptin Fab. Nature 421, 756–760 (2003).
Junttila, T. T. et al. Ligand-independent HER2/HER3/PI3K complex is disrupted by trastuzumab and is effectively inhibited by the PI3K inhibitor GDC-0941. Cancer Cell 15, 429–440 (2009).
Fallahi-Sichani, M., Honarnejad, S., Heiser, L. M., Gray, J. W. & Sorger, P. K. Metrics other than potency reveal systematic variation in responses to cancer drugs. Nat. Chem. Biol. 9, 708–714 (2013).
Fredriksson, S. et al. Protein detection using proximity-dependent DNA ligation assays. Nat. Biotechnol. 20, 473–477 (2002).
Tentler, J. J. et al. Patient-derived tumour xenografts as models for oncology drug development. Nat. Rev. Clin. Oncol. 9, 338–350 (2012).
The Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519–525 (2012).
Rothenberg, S. M. et al. Modeling oncogene addiction using RNA interference. Proc. Natl Acad. Sci. USA 105, 12480–12484 (2008).
Li, J. et al. Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms. Mol. Syst. Biol. 9, 705 (2013).
Jadwin, J. A., Curran, T. G., Lafontaine, A. T., White, F. M. & Mayer, B. J. Src homology 2 domains enhance tyrosine phosphorylation in vivo by protecting binding sites in their target proteins from dephosphorylation. J. Biol. Chem. 293, 623–637 (2018).
Kaelin, W. G. Jr. The concept of synthetic lethality in the context of anticancer therapy. Nat. Rev. Cancer 5, 689–698 (2005).
Nero, T. L., Morton, C. J., Holien, J. K., Wielens, J. & Parker, M. W. Oncogenic protein interfaces: small molecules, big challenges. Nat. Rev. Cancer 14, 248–262 (2014).
Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012).
Smith, M. A. et al. Annotation of human cancers with EGFR signaling-associated protein complexes using proximity ligation assays. Sci. Signal. 8, ra4 (2015).
Yachida, S. et al. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 467, 1114–1117 (2010).
Collisson, E. A. et al. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat. Med. 17, 500–503 (2011).
International Cancer Genome Consortium. International network of cancer genome projects. Nature 464, 993–998 (2010).
The Cancer Genome Atlas Research Network et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat. Genet. 45, 1113–1120 (2013).
Carr, T. H. et al. Defining actionable mutations for oncology therapeutic development. Nat. Rev. Cancer 16, 319–329 (2016).
Leiserson, M. D. et al. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat. Genet. 47, 106–114 (2015).
Kris, M. G. et al. Efficacy of gefitinib, an inhibitor of the epidermal growth factor receptor tyrosine kinase, in symptomatic patients with non-small cell lung cancer: a randomized trial. JAMA 290, 2149–2158 (2003).
Thatcher, N. et al. Gefitinib plus best supportive care in previously treated patients with refractory advanced non-small-cell lung cancer: results from a randomised, placebo-controlled, multicentre study (Iressa Survival Evaluation in Lung Cancer). Lancet 366, 1527–1537 (2005).
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).
Author information
Authors and Affiliations
Contributions
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.
Corresponding authors
Ethics declarations
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.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary figures
Rights and permissions
About this article
Cite this article
Lee, HW., 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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41551-018-0212-3
This article is cited by
-
Testing cancer inhibitors at scale
Nature Biomedical Engineering (2018)