Abstract 1982: Transcriptomic subtype identification of circulating tumor cells by label-free capture and single-cell RNA sequencing
Authors: Yoon-Tae Kang, Patricia Schnepp, Rashika Shrestha, Rain Yu Hong, Errile Pusod, Will Chow, Floyd Watkins, Kyle Thurston, Dominique Winston, Marta Gonzalez-Plasky, Angelica Olcott, David Coe, Michelle Racey, Elizabeth Dreskin
Journal: Cancer Research (2025)

Abstract Introduction: Single-cell RNA sequencing (scRNA-Seq) of rare cells, such as circulating tumor cells (CTCs), is critical for identifying various cell subtypes and understanding intercellular heterogeneity at the genetic level. Despite recent advances in scRNA-Seq, transcriptomic profiling of single CTCs has been technically demanding due to its limited cell utilization and background noise from unwanted cells during sequencing. In addition, conventional CTC isolation methods often miss important rare cell subtypes due to their low abundance and reliance on specific surface markers for detection. This limitation hinders comprehensive transcriptomic analysis, especially for CTCs undergoing the critical epithelial-mesenchymal transition (EMT), which may not express typical epithelial markers. To address these challenges, we present an optimized workflow that integrates high-purity label-free CTC capture with in-droplet barcoding-based scRNA-seq to achieve higher cell utilization and lower background sequencing noise. Methods: To model heterogeneous CTC subpopulations at different EMT status, samples were prepared by spiking in two types of cancer cells, MCF7 (epithelial CTCs) and HeLa (mesenchymal CTCs), into a total of 7.5 ml of whole blood from a healthy donor at a concentration of 100 cells/ml. CTCs were captured using the Genesis Cell Isolation System and the enriched CTCs were further purified to reduce leukocyte contamination or red blood cell (RBC) contamination using CD45 pre-conjugated magnetic beads or RBC lysis reagent, respectively. The processed CTC sample was then used to create scRNA-Seq libraries following the Bio-Rad ddSEQ Single-Cell 3’ RNA-Seq Kit protocol, which includes single-cell in-droplet barcoding, reverse transcription, and cDNA synthesis. Results: This Genesis System allowed for capturing both epithelial and mesenchymal CTCs to be sequenced. After sequencing and Omnition Software Analysis, individual cells were visualized using a Uniform Manifold Approximation and Projection (UMAP) plot and clustering analysis showed a distinct separation between epithelial and mesenchymal CTCs while each different cell population revealed expression of representative genes for each cell type. Discussion and Conclusions: By combining rare single cell capture with scRNA-seq library prep and analysis, our workflow provides an easy, highly sensitive and cost-effective solution for CTC single-cell transcriptomic studies, compatible with commercially available instruments and kits. This scRNA-seq workflow can be integrated into a broad spectrum of applications in liquid biopsy across many different cancer types and empowering researchers to gain deeper insights into tumor heterogeneity and gene expression patterns with greater efficiency and within the same budget.​ Citation Format: Yoon-Tae Kang, Patricia Schnepp, Rashika Shrestha, Rain Yu Hong, Errile Pusod, Will Chow, Floyd Watkins, Kyle Thurston, Dominique Winston, Marta Gonzalez-Plasky, Angelica Olcott, David Coe, Michelle Racey, Elizabeth Dreskin. Transcriptomic subtype identification of circulating tumor cells by label-free capture and single-cell RNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1982.