Human plasma contains RNA transcripts released by multiple cell types within the body. Single-cell transcriptomic analysis allows the cellular origin of circulating RNA molecules to be elucidated at high resolution and has been successfully utilized in the pregnancy context. Researchers at the Chinese University of Hong Kong explored the application of a similar approach to develop plasma RNA markers for cancer detection.
Single-cell RNA sequencing was performed to decipher transcriptomic profiles of single cells from hepatocellular carcinoma (HCC) samples. Cell-type-specific transcripts were identified and used for deducing the cell-type-specific gene signature (CELSIG) scores of plasma RNA from patients with and without HCC.
Six major cell clusters were identified, including hepatocyte-like, cholangiocyte-like, myofibroblast, endothelial, lymphoid, and myeloid cell clusters based on 4 HCC tumor tissues as well as their paired adjacent nontumoral tissues. The CELSIG score of hepatocyte-like cells was significantly increased in preoperative plasma RNA samples of patients with HCC (n = 14) compared with non-HCC participants (n = 49). The CELSIG score of hepatocyte-like cells declined in plasma RNA samples of patients with HCC within 3 days after tumor resection. Compared with the discriminating power between patients with and without HCC using the abundance of ALB transcript in plasma [area under curve (AUC) 0.72)], an improved performance (AUC: 0.84) was observed using the CELSIG score. The hepatocyte-specific transcript markers in plasma RNA were further validated by ddPCR assays. The CELSIG scores of hepatocyte-like cell and cholangiocyte trended with patients’ survival.
Cell types and cell-type-specific gene signatures identified in the human hepatocellular cancer (HCC) tumors and paired normal tissues based on single-cell RNA sequencing
(A), Schematic diagram of workflow for single-cell RNA sequencing. (B), Visualization of cell types for 17 176 HCC and adjacent nontumor liver cells using t-distributed stochastic neighbor embedding (t-SNE). (C), Expression patterns of those representative cell-type-specific gene signatures. (D), Heatmap plot for the expression of the cell-type-specific gene signatures.
The combination of single-cell transcriptomic analysis and plasma RNA sequencing represents an approach for the development of new noninvasive cancer markers.