Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics
Cancers. 2021;13(19):4885. DOI 10.3390/cancers13194885. PMID 34638368. PMCID PMC8508335.
How to cite
AMA
Pauken CM, Kenney SR, Brayer KJ, Guo Y, Brown-Glaberman UA, Marchetti D. Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics. Cancers (Basel). 2021;13(19):4885. doi:10.3390/cancers13194885APA
Pauken, C. M., Kenney, S. R., Brayer, K. J., Guo, Y., Brown-Glaberman, U. A., & Marchetti, D. (2021). Heterogeneity of circulating tumor cell neoplastic subpopulations outlined by single-cell transcriptomics. Cancers, 13(19), 4885. https://doi.org/10.3390/cancers13194885BibTeX
@article{pauken2021heterogeneity,
title = {Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics},
author = {Pauken, Christine M. and Kenney, Shelby Ray and Brayer, Kathryn J. and Guo, Yan and Brown-Glaberman, Ursa A. and Marchetti, Dario},
journal = {Cancers},
volume = {13},
number = {19},
pages = {4885},
year = {2021},
doi = {10.3390/cancers13194885}
}Circulating tumor cells break away from a breast tumor and travel in the blood, where they can seed new growths far from where they started. For years these cells have been defined narrowly, by a small set of surface markers, so any tumor cell that does not fit the definition is simply missed.
This study drew blood from 21 women with metastatic breast cancer and kept every nucleated cell instead of pre-selecting for the usual markers, then imaged the slides to count tumor cells over time. Blood from three of the patients was read one cell at a time by single-cell sequencing.
That single-cell view found a distinct group of circulating cells carrying the classic tumor markers alongside genes never before tied to these cells, evidence that a tumor cell in the blood is a spectrum of states rather than one fixed type.
Key findings
- Circulating tumor cells from 21 metastatic breast cancer patients were captured and enumerated on the RareCyte platform without antigen pre-enrichment. Each 7.5 mL blood draw was spread across 8 slides for whole-slide imaging, and serial draws tracked a CTC burden that varied widely between patients and exceeded 15,000 CTCs/mL in one sample.
- Single-cell RNA sequencing of lineage-negative and lineage-positive fractions from three of these patients resolved 16 distinct cell clusters. Every cluster drew cells from each patient, and sequencing captured 500 to 2115 cells per sample.
- One cluster (cluster 10) grouped circulating cells whose transcriptomes were not those of immune cells. These cells co-expressed classical markers such as EPCAM and TACSTD2 with genes not previously tied to circulating tumor cells, extending the definition beyond the EpCAM- and cytokeratin-positive “classic” phenotype.
CyteFinder II in the methods
“Slides were then fixed, permeabilized, and stained using the Breast Cancer identification kit (RareCyte, Seattle, WA, USA, 0700-MA) which contains DAPI, which contains antibodies to human CD45 for the visualization of normal immune cells, and antibodies to human EpCAM and Pan-Cytokeratin for the detection of classical CTCs (EpCAM+/CK+/DAPI+ but CD45- cells). Slides were then imaged and analyzed using Cytefinder II software (RareCyte, Seattle, WA, USA). CTCs were visualized and enumerated by CyteMapper TM software.”
— Pauken et al., Cancers (2021), Materials and Methods, section 2.3 “RareCyte Cytefinder II™ Analysis”
Disclosure: RareCyte is named in the competing-interests statement of the publication cited above.
Why it matters for CyteFinder II users
If you count circulating tumor cells, the hardest problem is the cell you never see. A method that enriches for an epithelial antigen before it images discards any cell carrying too little of that antigen, so the count reflects only the cells that already fit the definition you began with. This study took the opposite route on CyteFinder II: it retained every nucleated cell from each 7.5 mL blood draw, spread the cells across slides, and imaged the whole slide, so a tumor cell was scored after capture rather than selected before it. That is what let the authors hold on to the atypical, marker-low cells a pre-enrichment step removes, the same cells single-cell sequencing later showed to carry a distinct neoplastic signature. For your own work the point is practical: if you are asking whether circulating tumor cells are more varied than the classical definition allows, the detection step has to keep the cells that break that definition.
