Iyer, A and Gupta, K and Sharma, S and Hari, K and Lee, YF and Ramalingam, N and Yap, YS and West, J and Bhagat, AA and Subramani, BV and Sabuwala, B and Tan, TZ and Thiery, JP and Jolly, MK and Ramalingam, N and Sengupta, D (2021) Integrative analysis and machine learning based characterization of single circulating tumor cells. In: Journal of Clinical Medicine, 9 (4). pp. 1-2.
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Abstract
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.
| Item Type: | Journal Article |
|---|---|
| Publication: | Journal of Clinical Medicine |
| Publisher: | MDPI |
| Additional Information: | The copyright for this article belongs to the Authors. |
| Keywords: | Blood; CTC; High-throughput sequencing; Machine learning; Rare cell type; RNA-seq; Single-cell |
| Department/Centre: | Division of Interdisciplinary Sciences > Centre for Biosystems Science and Engineering |
| Date Deposited: | 22 May 2023 04:29 |
| Last Modified: | 22 May 2023 04:29 |
| URI: | https://eprints.iisc.ac.in/id/eprint/81711 |
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