Single-cell analysis of breast cancer metastasis reveals epithelial-mesenchymal plasticity signatures associated with poor outcomes
Juliane Winkler, … , Spyros Darmanis, Zena Werb
Juliane Winkler, … , Spyros Darmanis, Zena Werb
Published September 3, 2024
Citation Information: J Clin Invest. 2024;134(17):e164227. https://doi.org/10.1172/JCI164227.
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Research Article Oncology

Single-cell analysis of breast cancer metastasis reveals epithelial-mesenchymal plasticity signatures associated with poor outcomes

Abstract

Metastasis is the leading cause of cancer-related deaths. It is unclear how intratumor heterogeneity (ITH) contributes to metastasis and how metastatic cells adapt to distant tissue environments. The study of these adaptations is challenged by the limited access to patient material and a lack of experimental models that appropriately recapitulate ITH. To investigate metastatic cell adaptations and the contribution of ITH to metastasis, we analyzed single-cell transcriptomes of matched primary tumors and metastases from patient-derived xenograft models of breast cancer. We found profound transcriptional differences between the primary tumor and metastatic cells. Primary tumors upregulated several metabolic genes, whereas motility pathway genes were upregulated in micrometastases, and stress response signaling was upregulated during progression. Additionally, we identified primary tumor gene signatures that were associated with increased metastatic potential and correlated with patient outcomes. Immune-regulatory control pathways were enriched in poorly metastatic primary tumors, whereas genes involved in epithelial-mesenchymal transition were upregulated in highly metastatic tumors. We found that ITH was dominated by epithelial-mesenchymal plasticity (EMP), which presented as a dynamic continuum with intermediate EMP cell states characterized by specific genes such as CRYAB and S100A2. Elevated expression of an intermediate EMP signature correlated with worse patient outcomes. Our findings identified inhibition of the intermediate EMP cell state as a potential therapeutic target to block metastasis.

Authors

Juliane Winkler, Weilun Tan, Catherine M.M. Diadhiou, Christopher S. McGinnis, Aamna Abbasi, Saad Hasnain, Sophia Durney, Elena Atamaniuc, Daphne Superville, Leena Awni, Joyce V. Lee, Johanna H. Hinrichs, Patrick S. Wagner, Namrata Singh, Marco Y. Hein, Michael Borja, Angela M. Detweiler, Su-Yang Liu, Ankitha Nanjaraj, Vaishnavi Sitarama, Hope S. Rugo, Norma Neff, Zev J. Gartner, Angela Oliveira Pisco, Andrei Goga, Spyros Darmanis, Zena Werb

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Figure 5

Intermediate EMP cells are characterized by specific markers.

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Intermediate EMP cells are characterized by specific markers. (A) Heatma...
(A) Heatmap showing expression of DEGs for epithelial-like, mesenchymal-like, and intermediate EMP cells from the MULTI-Seq data. Cells are ordered by increasing EMP signature. Annotations indicate the EMP cell state, EMP signature expression, tumor model, and metastatic potential. The arrow highlights intermediate EMP cell marker genes. (B) Venn diagrams showing overlapping DEGs of epithelial-like, mesenchymal-like, and intermediate EMP cells between the Smart-Seq2 and MULTI-Seq data sets. The overlapping markers for intermediate EMP cells are highlighted. (C) Scatter plots show expression of the indicated genes in individual cells ordered by increasing EMP signature expression. The dots show expression levels in individual cells, and lines show smoothed expression of expressing cells. The bar charts on top shows the proportion of positively expressing cells for the EMP cell states. The MULTI-Seq data set is shown. (D) Kaplan-Meier plots show the RFS of patients with BC (METABRIC) stratified by PAM50 BC subtype using the mean expression of the epithelial-like, intermediate EMP, and mesenchymal-like signatures. The number of patients and P value are shown. The purple box indicates data with a significant P value calculated by log-rank test.