Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma
Abstract
1. Introduction
2. Biology of Circulating Tumor Cells
CTC Entry into the Circulation and Metastasis
3. Novel Strategies for CTCs’ Isolation in HCC
3.1. Label-Dependent Strategies
3.2. Label-Independent Methods
3.2.1. Size and Deformability
3.2.2. Density
4. Molecular Analysis of CTCs
4.1. Genomic Level
4.2. Transcriptomic Level
4.3. Proteomic Level
4.4. Epigenomic Level
Platform | Analyses | Marker(s)/Parameter | References |
---|---|---|---|
CellSearch® | Anti-EpCAM antibody Immunohistochemistry (IHC)-based approach | EpCAM | [44,98] |
NanoVelcro | Microfluidic chip coated with a cocktail of antibodies | Surface markers including ASGPR, glypican-3, and EpCAM | [99] |
CTC−BioTChip | Hydroxyapatite/chitosan nanofilm | EpCAM | [53] |
Refined CTC−BioTChip | Anti-EpCAM antibody and galactose-rhodamine-polyacrylamide nanoparticles were endocytosed into the CTCs through ASGPRs present on the surface of the CTCs. | EpCAM and ASGPR | [53] |
ISET® | Filtration-based technology | Cytokeratin (CK) | [100] |
Parsortix | Microfluidic-based system | Size and deformability | [69] |
RosetteSep | Density gradient centrifugation-based platform | Cocktail antibody | [101] |
OncoQuick | Density gradient centrifugation-based technologies | Buoyant density | [73] |
CanPatrolTM | Microfiltration and various EMT markers | EpCAM, CK8/9/19, vimentin, and TWIST | [78] |
EP@MNPs | Novel peptide-based magnetic nanoparticle | EpCAM recognition peptide followed by CD profiling to distinguish epithelial and mesenchymal subgroups | [102] |
NP@MNPs | Novel peptide-based magnetic nanoparticle | N-cadherin recognition peptide followed CDRNA profiling to distinguish epithelial and mesenchymal subgroups | [103] |
CytoSorter® and CytoSorter™ | CTC PD-L1 Kit | PD-L1 antibody | [104] |
Optimized CanPatrol CTC-enrichment | Combining nanotechnology filters and mRNA ISH array | EpCAM, CK8, CD18, CD45, Vimentin, TWIST, CK19, and NANOG | [105] |
EPIDROP | Single-cell proteomic and secretomic analyses of viable CTCs | EpCAM and other IHC markers | [85] |
RT-LAMP | Reverse transcription loop-mediated isothermal amplification | EpCAM, CK19, CD133, and CD90 | [106] |
RareCyte | High-definition single-cell analysis (HD-SCA) | EpCAM, CK, and other IHC markers | [107] |
DEPArray™ | Sub-sequential high-quality genomic profiling | A combination of dielectrophoresis (DEP) and image-based selection methods and some IHC markers | [108] |
NanoVelcro | Triple-immunofluorescence staining method | ASGPR, glypican-3, and epithelial cell adhesion molecule | [57] |
5. Clinical Value of CTC Detection in HCC
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Method | Application | Advantages | Disadvantages | |
---|---|---|---|---|
Genomic | Pure PCR-based amplification | Amplifying specific sites in the genome | Better uniformity of amplification | Uneven amplification, low coverage, amplification errors, allele dropout |
MDA-based methods in HCC | Point mutations amplifying to analyze the genome of patient-derived CTCs | Higher fidelity than PCR-based methods | Amplification bias, allele dropout | |
MALBAC combines MDA and PCR-based methods | Analysis of single-nucleotide variants (SNVs) | Intermediate coverage and uniformity | Allele dropout | |
LIANTI | Amplifies T7 promoter-tagged DNA fragments into thousands of RNA copies. | Covers 97% of the genome with a reduced false-negative rate. | ||
GenomPlex and Ampli1 | Copy-number variation (CNV) profiling | Maintains representation of the entire genome through subsequent reamplifications. Preserves precious source material by amplifying nanogram amounts of starting genomic DNA. | Significantly higher genomic coverage | |
Transcriptomic | STRT-seq | An established approach to profile entire transcriptomes of individual cells from different cell types | High specificity | 5′-only end base |
Smart-seq and Smart-seq2 | Single-cell gene expression analyses hold promise for characterizing cellular heterogeneity. | Good coverage of the transcriptome with rarer transcripts being detectable Independent of cell size | High cost, low specificity, low number of cells | |
CEL-seq | Single-cell RNA-Seq using multiplexed linear amplification | Sensitive, accurate, and reproducible | 3′-only end base, low number of cells | |
InDrop and Drop-seq | Sequence thousands of single cells in parallel | Cost benefit, high specificity | 3′-only end base | |
Mars-seq | Analysis to explore cellular heterogeneity by assembling an automated experimental platform that enables RNA profiling of cells | Long-term storage, cost benefit, high specificity | 3′-only end base | |
10x Genomics Chromium | A droplet-based scRNA-seq technology allowing genome-wide expression profiling for thousands of cells at once | Cost benefit, high sensitivity and precision | Must process immediately | |
Epigenomic | sci-ATAC-seq | Generation of sequencing library molecules is selective toward regions of open chromatin on the hyperactive derivative of the cut-and-paste Tn5 transposase | High throughput, independent of antibody | Low coverage per cell |
scChIP-seq | Enabled in-depth characterization of protein-DNA interactions of histone marks at single-cell resolution | High throughput | Low coverage per cell, dependence on antibody |
Method | Application | Advantage (s) |
---|---|---|
Pure PCR-based amplification | Amplifying specific sites in the genome | Better uniformity of amplification |
MDA-based methods | Point mutations amplification to analyze the genome of patient-derived CTCs | Higher fidelity than PCR-based methods |
MALBAC combining MDA and PCR-based methods | Analysis of single-nucleotide variants (SNVs) | Intermediate coverage and uniformity |
LIANTI | Amplifies T7-promoter-tagged DNA fragments into thousands of RNA copies | Covers 97% of the genome with a reduced false-negative rate |
GenomPlex and Ampli1 | Copy-number variation (CNV) profiling | Significantly higher genomic coverage |
Platform | Study Group | CTC Positive Detection Rate | Ref. |
---|---|---|---|
Cell Search | 123 HCC patients; 5 control patients; 10 healthy volunteers | 66.67% in patients prior to resection, 28.15% 1 month after resection | [47] |
59 HCC patients; 19 control patients | 30.5% in HCC patients | [109] | |
20 HCC; 10 control patients | 35% in HCC patients | [46] | |
21 HCC patients | 4.7% in HCC patients | [111] | |
57 HCC patients undergoing resection | 15% in HCC patients | [112] | |
89 HCC patients treated with chemoembolization | 56% in HCC patients | [113] | |
144 HCC patients | 56.9% in patients prior to resection, 30.6% 1 month after resection | [114] | |
26 HCC patients | 27% in HCC patients | [115] | |
CanPatrolTM | 195 HCC patients | 95% in HCC patients | [38] |
112 HCC patients; 12 HBV patients; 20 healthy volunteers | 90.18% in HCC patients, 16.67% in HBV patients | [93] | |
165 HCC patients | 70.9% High CTC count was correlated with BCLC stages, multiple tumors, and high levels of alpha-fetoprotein | [116] | |
113 HCC patients | 78.8% | [117] | |
99 HCC patients | 89.9% | [118] | |
160 HCC patients undergoing resection | 90% | [119] | |
56 HCC patients | 92.86% before liver transplantation surgery | [120] | |
ISET | 7 HCC patients undergoing tumor resection; 8 chronic cirrhosis patients; 8 healthy volunteers | 52% in HCC patients | [63] |
44 HCC patients; 30 chronic hepatitis patients; 39 liver cirrhosis patients; 38 healthy volunteers | 52% in HCC patients | [64] | |
RosetteSep | 109 HCC patients | 92.7% in patients with advanced HCC and candidates for sorafenib treatment | [121] |
32 HCC patients; 17 other types of cancer; 3 acute hepatitis A patients; 6 chronic hepatitis B patients; 4 chronic hepatitis C patients; 15 cirrhosis patients; 12 patients with benign intrahepatic space-occupying lesions | 91% | [61] | |
NanoVelcro | 61 HCC patients; 8 healthy control patients | 96.7% in HCC patients and 25% in healthy control patients | [57] |
CTC−BioTChip | 42 HCC patients | 59.5% | [53] |
OncoQuick | 17 HCC patients; 13 healthy volunteers | 76.5% in HCC patients | [122] |
CytoSorter™ | 47 HCC patients received PD-1 inhibitor combined with intensity-modulated radiotherapy and anti-angiogenic therapy | 95.7% | [123] |
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Salehi, M.; Lavasani, Z.M.; Keshavarz Alikhani, H.; Shokouhian, B.; Hassan, M.; Najimi, M.; Vosough, M. Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma. Cells 2023, 12, 2260. https://doi.org/10.3390/cells12182260
Salehi M, Lavasani ZM, Keshavarz Alikhani H, Shokouhian B, Hassan M, Najimi M, Vosough M. Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma. Cells. 2023; 12(18):2260. https://doi.org/10.3390/cells12182260
Chicago/Turabian StyleSalehi, Mahsa, Zohre Miri Lavasani, Hani Keshavarz Alikhani, Bahare Shokouhian, Moustapha Hassan, Mustapha Najimi, and Massoud Vosough. 2023. "Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma" Cells 12, no. 18: 2260. https://doi.org/10.3390/cells12182260
APA StyleSalehi, M., Lavasani, Z. M., Keshavarz Alikhani, H., Shokouhian, B., Hassan, M., Najimi, M., & Vosough, M. (2023). Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma. Cells, 12(18), 2260. https://doi.org/10.3390/cells12182260