Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells
Hao Li, Jinze Li, Zhiqi Zhang, Qi Yang, Hong Du, Qiongzhu Dong, Zhen Guo, Jia Yao, Shuli Li, Dongshu Li, Nannan Pang, Chuanyu Li, Wei Zhang, Lianqun Zhou
Abstract
Hepatocellular carcinoma (HCC) circulating tumor cells (CTCs) exhibit significant phenotypic heterogeneity and diverse gene expression profiles due to epithelial-mesenchymal transition (EMT). However, current detection methods lack the capacity for simultaneous quantification of multidimensional biomarkers, impeding a comprehensive understanding of tumor biology and dynamic changes. Here, the CTC Digital Simultaneous Cross-dimensional Output and Unified Tracking (d-SCOUT) technology is introduced, which enables simultaneous quantification and detailed interpretation of HCC transcriptional and phenotypic biomarkers. Based on self-developed multi-real-time digital PCR (MRT-dPCR) and algorithms, d-SCOUT allows for the unified quantification of Asialoglycoprotein Receptor (ASGPR), Glypican-3 (GPC-3), and Epithelial Cell Adhesion Molecule (EpCAM) proteins, as well as Programmed Death Ligand 1 (PD-L1), GPC-3, and EpCAM mRNA in HCC CTCs, with good sensitivity (LOD of 3.2 CTCs per mL of blood) and reproducibility (mean %CV = 1.80-6.05%). In a study of 99 clinical samples, molecular signatures derived from HCC CTCs demonstrated strong diagnostic potential (AUC = 0.950, sensitivity = 90.6%, specificity = 87.5%). Importantly, by integrating machine learning, d-SCOUT allows clustering of CTC characteristics at the mRNA and protein levels, mapping normalized heterogeneous 2D molecular profiles to assess HCC metastatic risk. Dynamic digital tracking of eight HCC patients undergoing different treatments visually illustrated the therapeutic effects, validating this technology's capability to quantify the treatment efficacy. CTC d-SCOUT enhances understanding of tumor biology and HCC management.