The emergence of single-cell analysis technologies provides researchers tools to investigate tumor heterogeneity on a cell-by-cell basis, enabling identification and characterization of clinically relevant cellular subpopulations that would have been masked by traditional bulk RNA-seq analysis. In a new Cell Reports article, Savage et al., utilized single-cell RNA-seq, in addition to other functional assays, to discover a stem-like tumorigenic population with EGFR-dependent tumor-initiating activity and sensitivity to EGFR-inhibition in triple-negative breast cancer (TNBC).
Therapies targeting epidermal growth factor receptor (EGFR) have variable and unpredictable responses in breast cancer. Screening triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), we identify a subset responsive to EGFR inhibition by gefitinib, which displays heterogeneous expression of wild-type EGFR. Deep single-cell RNA sequencing of 3,500 cells from an exceptional responder identified subpopulations displaying distinct biological features, where elevated EGFR expression was significantly enriched in a mesenchymal/stem-like cellular cluster. Sorted EGFRhi subpopulations exhibited enhanced stem-like features, including ALDH activity, sphere-forming efficiency, and tumorigenic and metastatic potential. EGFRhi cells gave rise to EGFRhi and EGFRlo cells in primary and metastatic tumors, demonstrating an EGFR-dependent expansion and hierarchical state transition. Similar tumorigenic EGFRhi subpopulations were identified in independent PDXs, where heterogeneous EGFR expression correlated with gefitinib sensitivity. This provides new understanding for an EGFR-dependent hierarchy in TNBC and for patient stratification for therapeutic intervention.
Read the full article in Cell Reports.
This study used the Chromium™ Single Cell 3’ Solution for gene expression analysis. Learn more about our single-cell analysis solutions:
- See how researchers are using single-cell RNA-seq for: T cell immunotherapy research, biological pathway dissection using Pertub-seq and studying intestinal stem cell self-renewal mechanisms
- Read single cell application notes
- Check out our data analysis and visualization tools - Cell Ranger and Loupe Cell Browser
- Download single cell datasets