A better understanding of the features that define the interaction between cancer cells and immune cells is important for the development of new cancer therapies1. However, focus is often given to interactions that occur within the primary tumour and its microenvironment, whereas the role of immune cells during cancer dissemination in patients remains largely uncharacterized2,3. Circulating tumour cells (CTCs) are precursors of metastasis in several types of cancer4,5,6, and are occasionally found within the bloodstream in association with non-malignant cells such as white blood cells (WBCs)7,8. The identity and function of these CTC-associated WBCs, as well as the molecular features that define the interaction between WBCs and CTCs, are unknown. Here we isolate and characterize individual CTC-associated WBCs, as well as corresponding cancer cells within each CTC–WBC cluster, from patients with breast cancer and from mouse models. We use single-cell RNA sequencing to show that in the majority of these cases, CTCs were associated with neutrophils. When comparing the transcriptome profiles of CTCs associated with neutrophils against those of CTCs alone, we detect a number of differentially expressed genes that outline cell cycle progression, leading to more efficient metastasis formation. Further, we identify cell–cell junction and cytokine–receptor pairs that define CTC–neutrophil clusters, representing key vulnerabilities of the metastatic process. Thus, the association between neutrophils and CTCs drives cell cycle progression within the bloodstream and expands the metastatic potential of CTCs, providing a rationale for targeting this interaction in treatment of breast cancer.
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Data analysis, statistical testing and visualization were conducted in R (version 3.4.0; R Foundation for Statistical Computing). RNA and exome sequencing data have been deposited in the Gene Expression Omnibus (GEO, NCBI; accession number GSE109761) and the European Nucleotide Archive (ENA, EMBL-EBI; accession number PRJEB24623), respectively. Original R scripts to reproduce data analysis have been deposited to GitHub (accession URL, https://github.com/CMETlab/CTC-WBC). Source data for all mouse experiments are provided. All data are available from the corresponding author upon reasonable request.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank all patients that donated blood for our study, as well as all involved clinicians and study nurses; J. Massagué (Memorial Sloan Kettering Cancer Center), D. Haber and S. Maheswaran (Massachusetts General Hospital and Harvard Medical School) for donating cell lines; G. Christofori for MMTV-PyMT mice and comments on the manuscript, and all members of the Aceto laboratory for feedback and discussions; K. Eschbach and E. Burcklen from the Genomics Facility Basel (D-BSSE of the ETH Zürich) for generating sequencing libraries and performing next-generation sequencing; S. Arnold (D-BSSE of the ETH Zürich) and S. Münst Soysal (University Hospital Basel) for support with sample acquisition and processing; and T. Ryser (Aceto laboratory, University of Basel) for help with CRISPR–Cas9-related experiments. Calculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing center of the University of Basel. Research in the Aceto laboratory is supported by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, the Basel Cancer League, the two Cantons of Basel through the ETH Zürich and the University of Basel.
Nature thanks K. Pantel and the other anonymous reviewer(s) for their contribution to the peer review of this work.