Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells

• DOI: 10.1002/advs.202410120
• Publication Date: 2024-11-18T19:15:32Z
• Authors: 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
• Keywords: Circulating tumor cell

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 biology dynamic changes. Here, CTC Digital Simultaneous Cross‐dimensional Output Unified Tracking (d‐SCOUT) technology is introduced, which enables detailed interpretation HCC transcriptional biomarkers. Based on self‐developed multi‐real‐time digital PCR (MRT‐dPCR) algorithms, d‐SCOUT allows unified Asialoglycoprotein Receptor (ASGPR), Glypican‐3 (GPC‐3), Epithelial Cell Adhesion Molecule (EpCAM) proteins, as well Programmed Death Ligand 1 (PD‐L1), GPC‐3, EpCAM mRNA in CTCs, with good sensitivity (LOD 3.2 CTCs per mL blood) reproducibility (mean %CV = 1.80–6.05%). In study 99 clinical samples, molecular signatures derived from demonstrated strong diagnostic potential (AUC 0.950, 90.6%, specificity 87.5%). Importantly, by integrating machine learning, clustering characteristics at protein levels, mapping normalized heterogeneous 2D assess metastatic risk. Dynamic tracking eight patients undergoing different treatments visually illustrated therapeutic effects, validating this technology's capability quantify treatment efficacy. enhances management.