An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma

Abstract

Circulating tumor cells (CTCs) are shed into the bloodstream by invasive cancers, but the difficulty inherent in identifying these rare cells by microscopy has precluded their routine use in monitoring or screening for cancer. We recently described a high-throughput microfluidic CTC-iChip, which efficiently depletes hematopoietic cells from blood specimens and enriches for CTCs with well-preserved RNA. Application of RNA-based digital PCR to detect CTC-derived signatures may thus enable highly accurate tissue lineage-based cancer detection in blood specimens. As proof of principle, we examined hepatocellular carcinoma (HCC), a cancer that is derived from liver cells bearing a unique gene expression profile. After identifying a digital signature of 10 liver-specific transcripts, we used a cross-validated logistic regression model to identify the presence of HCC-derived CTCs in nine of 16 (56%) untreated patients with HCC versus one of 31 (3%) patients with nonmalignant liver disease at risk for developing HCC (P < 0.0001). Positive CTC scores declined in treated patients: Nine of 32 (28%) patients receiving therapy and only one of 15 (7%) patients who had undergone curative-intent ablation, surgery, or liver transplantation were positive. RNA-based digital CTC scoring was not correlated with the standard HCC serum protein marker alpha fetoprotein (P = 0.57). Modeling the sequential use of these two orthogonal markers for liver cancer screening in patients with high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively. Thus, digital RNA quantitation constitutes a sensitive and specific CTC readout, enabling high-throughput clinical applications, such as noninvasive screening for HCC in populations where viral hepatitis and cirrhosis are prevalent.circulating tumor cells | early cancer detection | hepatocellular carcinoma | blood biopsy | predictive modeling T he shedding by epithelial cancers of circulating tumor cells (CTCs) into the bloodstream underlies the blood-borne dissemination of cancer, although only a small fraction of CTCs gives rise to metastases (1). Enumeration and analysis of CTCs may thus enable noninvasive monitoring of advanced cancers, as well as early detection of invasive but localized tumors before they give rise to viable metastases. Recent advances in CTC isolation provide sensitive and high-throughput platforms to enrich for these rare tumor cells within blood specimens, but antibody staining and microscopic imaging of captured cancer cells remain a critical bottleneck limiting broad application of the technology (2). Classical CTC staining criteria include the presence of cell surface epithelial cell adhesion molecule (EpCAM) and cytoplasmic epithelial cytokeratins and the absence of the hematopoietic CD45 marker (3), but epithelial marker expression is highly variable and extensive imaging criteria must be applied to score immunofluorescent signals reliably from rare cancer cells surrounded by contaminating leukocytes (4). Emerging microfluidic C...

Liquid biopsy - emergence of a new era in personalized cancer care

“…The transcript expression pattern was able to correctly distinguish HCC with 88% specificity and 50% sensitivity from other malignancies. Positive CTC scores declined in treated patients receiving therapy [134].…”

Label-free ferrohydrodynamic cell separation of circulating tumor cells

“…Polystyrene microparticles (Polysciences, Inc., Warminster, PA) with diameters of 15.7 µm were mixed together with WBCs at the concentration of 1×10 4 particles mL −1 for model calibration. Microparticle and cell mixtures were injected into inlet A of a FCS device with a flow rate of 1.2–6 mL h −1 .…”

“…Probe solution was replaced with culture medium by centrifuging at 200× g for 5 minutes. Cells were counted with a hemocytometer (Hausser Scientific, Horsham, PA) and serially diluted in culture medium to achieve a solution with approximately 1×10 4 cells per mL. Cells were then counted with a Nageotte counting chamber (Hausser Scientific, Horsham, PA) to determine the exact number of cells per µL.…”

Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping

“…Most single-cell transcriptional analysis methods are based on RNA sequencing 3 , quantitative reverse transcription PCR (RT-qPCR) combined with microfluidics 4,5 , or techniques based on fluorescence hybridization 6,7 . Unfortunately, RNA sequencing requires mRNA isolation and pre-amplification using PCR, and this may result in amplification bias as well as a significant loss of transcripts 8 .…”