Integrative Analysis and Machine Learning based Characterization of Single Circulating Tumor Cells

J Clin Med. 2020 Apr 22;9(4):1206. doi: 10.3390/jcm9041206.


We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype. Further, we used this classifier to validate circulating breast tumor cells captured using a newly developed microfluidic system for label-free enrichment of CTCs.

Keywords: CTC; RNA-seq; blood; high-throughput sequencing; machine learning; rare cell type; single-cell.