PT  - JOURNAL ARTICLE
AU  - Arvind Iyer
AU  - Krishan Gupta
AU  - Shreya Sharma
AU  - Kishore Hari
AU  - Yi Fang Lee
AU  - Neevan Ramalingam
AU  - Yoon Sim Yap
AU  - Jay West
AU  - Ali Asgar Bhagat
AU  - Balaram Vishnu Subramani
AU  - Burhanuddin Sabuwala
AU  - Tuan Zea Tan
AU  - Jean Paul Thiery
AU  - Mohit Kumar Jolly
AU  - Naveen Ramalingam
AU  - Debarka Sengupta
TI  - Integrative analysis and machine learning based characterization of single circulating tumor cells
AID  - 10.1101/867200
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 867200
4099  - http://biorxiv.org/content/early/2019/12/06/867200.short
4100  - http://biorxiv.org/content/early/2019/12/06/867200.full
AB  - 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 systems for label-free enrichment of CTCs.