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