Diversity within or between tumours and metastases (known as intra-patient tumour heterogeneity) that develops during disease progression is a serious hurdle for therapy1,2,3. Metastasis is the fatal hallmark of cancer and the mechanisms of colonization, the most complex step in the metastatic cascade4, remain poorly defined. A clearer understanding of the cellular and molecular processes that underlie both intra-patient tumour heterogeneity and metastasis is crucial for the success of personalized cancer therapy. Here, using transcriptional profiling of tumours and matched metastases in patient-derived xenograft models in mice, we show cancer-site-specific phenotypes and increased glucocorticoid receptor activity in distant metastases. The glucocorticoid receptor mediates the effects of stress hormones, and of synthetic derivatives of these hormones that are used widely in the clinic as anti-inflammatory and immunosuppressive agents. We show that the increase in stress hormones during breast cancer progression results in the activation of the glucocorticoid receptor at distant metastatic sites, increased colonization and reduced survival. Our transcriptomics, proteomics and phospho-proteomics studies implicate the glucocorticoid receptor in the activation of multiple processes in metastasis and in the increased expression of kinase ROR1, both of which correlate with reduced survival. The ablation of ROR1 reduced metastatic outgrowth and prolonged survival in preclinical models. Our results indicate that the activation of the glucocorticoid receptor increases heterogeneity and metastasis, which suggests that caution is needed when using glucocorticoids to treat patients with breast cancer who have developed cancer-related complications.
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All mass spectrometry raw data files have been deposited to the ProteomeXchange Consortium- accession code PXD009102, http://proteomecentral.proteomexchange.org. The mRNA sequencing data are deposited in the Gene Expression Omnibus (GEO) database under accession code GSE124817. Processed transcriptomic data that support the findings of this study are available on reasonable request from the corresponding author.
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We thank members of the Bentires-Alj laboratory for advice and discussion. Tissue samples that correspond to PDX1, PDX2 and PDX4–PDX11 were provided by the Cooperative Human Tissue Network, which is funded by the National Cancer Institute. Other investigators may have received specimens from the same subjects. We thank A. L. Welm (University of Utah) for the PDX3 and PDX12–PDX16 models; H.-R. Hotz for offering the QuasR and edgeR tools in the FMI Galaxy server; and S. Bichet and P. Hirschmann for help with immunohistochemistry. We are grateful for the support of the FMI, DBM and Biozentrum core facilities. Research in the Bentires-Alj laboratory is supported by the Swiss Initiative for Systems Biology- SystemsX, the European Research Council, the Swiss National Science Foundation, Novartis, the Krebsliga Beider Basel, the Swiss Cancer League, the Swiss Personalized Health Network (Swiss Personalized Oncology driver project) and the Department of Surgery of the University Hospital Basel.
Nature thanks Melanie Flint and the other anonymous reviewer(s) for their contribution to the peer review of this work.