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 multidimens...
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| Format: | Article |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202410120 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Hao Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9231a719761a4dc59cee4b4408d046ed |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-9231a719761a4dc59cee4b4408d046ed2025-01-13T15:29:43ZengWileyAdvanced Science2198-38442025-01-01122n/an/a10.1002/advs.202410120Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor CellsHao Li0Jinze Li1Zhiqi Zhang2Qi Yang3Hong Du4Qiongzhu Dong5Zhen Guo6Jia Yao7Shuli Li8Dongshu Li9Nannan Pang10Chuanyu Li11Wei Zhang12Lianqun Zhou13Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaThe Second Affiliated Hospital of Soochow University Suzhou 215000 ChinaDepartment of General Surgery Huashan Hospital & Cancer Metastasis Institute Fudan University Shanghai 200040 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSchool of Biomedical Engineering (Suzhou) Division of Life Sciences and Medicine University of Science and Technology of China Hefei 230026 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaSuzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Suzhou 215163 ChinaAbstract 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.https://doi.org/10.1002/advs.202410120Circulating tumor cellsd‐SCOUTHCC managementmRNAsmulti‐real‐time digital PCRproteins |
| spellingShingle | 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 Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells Advanced Science Circulating tumor cells d‐SCOUT HCC management mRNAs multi‐real‐time digital PCR proteins |
| title | Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells |
| title_full | Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells |
| title_fullStr | Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells |
| title_full_unstemmed | Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells |
| title_short | Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells |
| title_sort | digital quantitative detection for heterogeneous protein and mrna expression patterns in circulating tumor cells |
| topic | Circulating tumor cells d‐SCOUT HCC management mRNAs multi‐real‐time digital PCR proteins |
| url | https://doi.org/10.1002/advs.202410120 |
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