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

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.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells ; day:18 ; month:11 ; year:2024 ; extent:20
Advanced science ; (18.11.2024) (gesamt 20)

Creator
Li, Hao
Li, Jinze
Zhang, Zhiqi
Yang, Qi
Du, Hong
Dong, Qiongzhu
Guo, Zhen
Yao, Jia
Li, Shuli
Li, Dongshu
Pang, Nannan
Li, Chuanyu
Zhang, Wei
Zhou, Lianqun

DOI
10.1002/advs.202410120
URN
urn:nbn:de:101:1-2411191321211.353491235453
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:22 AM CEST

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Associated

  • Li, Hao
  • Li, Jinze
  • Zhang, Zhiqi
  • Yang, Qi
  • Du, Hong
  • Dong, Qiongzhu
  • Guo, Zhen
  • Yao, Jia
  • Li, Shuli
  • Li, Dongshu
  • Pang, Nannan
  • Li, Chuanyu
  • Zhang, Wei
  • Zhou, Lianqun

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