Volume 73, Issue 1 pp. 422-436

Review

Free Access

Detection of Circulating Tumor Cells and Their Implications as a Biomarker for Diagnosis, Prognostication, and Therapeutic Monitoring in Hepatocellular Carcinoma

Joseph C. Ahn,

Joseph C. Ahn

Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN

Search for more papers by this author

Pai-Chi Teng,

Pai-Chi Teng

Urologic Oncology Program and Uro-Oncology Research Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Search for more papers by this author

Pin-Jung Chen,

Pin-Jung Chen

Department of Molecular and Medical Pharmacology, California NanoSystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles, Los Angeles, CA

Search for more papers by this author

Edwin Posadas,

Edwin Posadas

Urologic Oncology Program and Uro-Oncology Research Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Translational Oncology Program, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Division of Hematology/Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Search for more papers by this author

Hsian-Rong Tseng,

Hsian-Rong Tseng

Department of Molecular and Medical Pharmacology, California NanoSystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles, Los Angeles, CA

Search for more papers by this author

Shelly C. Lu,

Shelly C. Lu

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA

Search for more papers by this author

Ju Dong Yang,

Corresponding Author

Ju Dong Yang

[email protected]

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA

ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

Ju Dong Yang, M.D., M.S.

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center

8900 Beverly Blvd.

Los Angeles, CA 90048

E-mail: [email protected]

Tel.: +1-310-423-1971

Search for more papers by this author

Joseph C. Ahn,

Joseph C. Ahn

Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN

Search for more papers by this author

Pai-Chi Teng,

Pai-Chi Teng

Urologic Oncology Program and Uro-Oncology Research Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Search for more papers by this author

Pin-Jung Chen,

Pin-Jung Chen

Department of Molecular and Medical Pharmacology, California NanoSystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles, Los Angeles, CA

Search for more papers by this author

Edwin Posadas,

Edwin Posadas

Urologic Oncology Program and Uro-Oncology Research Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Translational Oncology Program, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Division of Hematology/Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Search for more papers by this author

Hsian-Rong Tseng,

Hsian-Rong Tseng

Department of Molecular and Medical Pharmacology, California NanoSystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles, Los Angeles, CA

Search for more papers by this author

Shelly C. Lu,

Shelly C. Lu

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA

Search for more papers by this author

Ju Dong Yang,

Corresponding Author

Ju Dong Yang

[email protected]

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA

ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

Ju Dong Yang, M.D., M.S.

Division of Digestive and Liver Diseases, Department of Medicine, Cedars-Sinai Medical Center

8900 Beverly Blvd.

Los Angeles, CA 90048

E-mail: [email protected]

Tel.: +1-310-423-1971

Search for more papers by this author

First published: 04 February 2020

https://doi.org/10.1002/hep.31165

Citations: 263

Financial Support: National Institutes of Health (Grant/Award No. R01CA172086 to S.C.L.).

Potential conflict of interest: Dr. Posadas advises CytoLumina Technologies. Dr. Tseng owns stock in CytoLumina Technologies. Dr. Yang serves as a consultant for Exact Sciences.

Share a link

Email
Wechat
Bluesky

Abstract

Hepatocellular carcinoma (HCC) is among the leading causes of worldwide cancer-related morbidity and mortality. Poor prognosis of HCC is attributed primarily to tumor presentation at an advanced stage when there is no effective treatment to achieve the long term survival of patients. Currently available tests such as alpha-fetoprotein have limited accuracy as a diagnostic or prognostic biomarker for HCC. Liver biopsy provides tissue that can reveal tumor biology but it is not used routinely due to its invasiveness and risk of tumor seeding, especially in early-stage patients. Liver biopsy is also limited in revealing comprehensive tumor biology due to intratumoral heterogeneity. There is a clear need for new biomarkers to improve HCC detection, prognostication, prediction of treatment response, and disease monitoring with treatment. Liquid biopsy could be an effective method of early detection and management of HCC. Circulating tumor cells (CTCs) are cancer cells in circulation derived from the original tumor or metastatic foci, and their measurement by liquid biopsy represents a great potential in facilitating the implementation of precision medicine in patients with HCC. CTCs can be detected by a simple peripheral blood draw and potentially show global features of tumor characteristics. Various CTC detection platforms using immunoaffinity and biophysical properties have been developed to identify and capture CTCs with high efficiency. Quantitative abundance of CTCs, as well as biological characteristics and genomic heterogeneity among the CTCs, can predict disease prognosis and response to therapy in patients with HCC. This review article will discuss the currently available technologies for CTC detection and isolation, their utility in the clinical management of HCC patients, their limitations, and future directions of research.

Abbreviations

AFP: alpha-fetoprotein
ASGPR: asialoglycoprotein receptor
BCLC: Barcelona Clinic Liver Cancer
CK: cytokeratin
CTC: circulating tumor cell
ctDNA: circulating tumor DNA
DEP: dielectrophoresis
EMT: epithelial to mesenchymal transition
EpCAM: epithelial cell adhesion molecule
FDA: Food and Drug Administration
GPC3: glypican 3
HCC: hepatocellular carcinoma
HKR: higher karyoplasmic ratio
IFC: imaging flow cytometry
ISET: isolation by size of epithelial tumor cells
MACS: magnetic activated cell sorting
PD-L1: programmed death ligand 1
RT-PCR: reverse-transcription PCR
SE-iFISH: subtraction enrichment and immunostaining fluorescence in situ hybridization
Treg: regulatory T cells

Hepatocellular carcinoma (HCC) is an aggressive primary liver cancer that typically occurs in the setting of chronic liver disease and cirrhosis, and it is the sixth leading cause of cancer incidence and the fourth cause of cancer death globally.⁽¹⁾ Although a select group of patients with small, localized HCC may undergo curative therapies, those with large tumor burden, vascular invasion, or metastasis have a poor prognosis and are managed with systemic treatment and supportive care. There exists an unmet need for HCC biomarkers for early detection and prognostication, as well as prediction and monitoring for treatment response.

Currently, alpha-fetoprotein (AFP) is the most widely used biomarker for HCC. Biannual liver ultrasound with or without serum AFP is the main HCC screening strategy recommended by major societies.⁽^2-4⁾ AFP is used as a prognostic and predictive biomarker in patients with HCC. Elevated levels of AFP have been associated with increased tumor size and portal vein thrombosis, as well as increased risks of liver transplant wait-list dropout and posttransplant recurrence.⁽^{5, 6}⁾ Serum AFP is also a predictor of treatment response in patients with HCC after liver transplant and ramucirumab treatment.⁽^{7, 8}⁾ However, AFP’s role as a biomarker for early detection of HCC is limited by its poor sensitivity. Alternative protein-based serum tumor markers such as AFP lectin fraction (AFP-L3) and des-y-carboxy prothrombin (DCP) have been shown to improve the diagnostic performances when used in combination with AFP.⁽⁹⁾ Glypican 3 (GPC3),⁽¹⁰⁾ cytokeratin 19 (CK19),⁽¹¹⁾ golgi protein 73 (GP73),⁽¹²⁾ midkine,⁽¹³⁾ osteopontin,⁽¹⁴⁾ squamous cell carcinoma antigen (SCCA),⁽¹⁵⁾ and annexin A2⁽¹⁶⁾ have all been shown to have diagnostic and prognostic roles in HCC as well, but they have not been adopted for widespread clinical practice.

Liver biopsy allows direct sampling of the tumor tissue and molecular characterization of the tumor. However, it is an invasive test with a risk of bleeding and concern for possible tumor seeding. Moreover, as HCCs exhibit significant intertumoral or intratumoral heterogeneity from genetic aberrations, transcriptional and epigenetic dysregulation, a single biopsy specimen containing a small amount of tumor tissue may not be representative of the whole HCC tumor.⁽¹⁷⁾

Over recent years, a variety of “liquid biopsy” techniques have shown significant promise as biomarkers for HCC. In liquid biopsy, samples of body fluids are collected to obtain vital pieces of phenotypic, genetic, and transcriptomic information about the primary tumor.⁽¹⁸⁾ The primary forms of liquid biopsy include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), microRNA, and extracellular vesicles. First described in 1869, CTCs are malignant cells derived from either the primary tumor or metastases that migrate into the systemic circulation.⁽¹⁹⁾ CTCs represent a unique biomarker different from any of the existing cancer biomarkers, as they represent a sampling of the patient’s live tumor cells.⁽²⁰⁾ Analysis of CTCs can help guide treatment plans by identifying specific mutations in target genes and predicting response or resistance to specific treatments. This review article will discuss the CTCs and provide an overview of their biology, current and emerging techniques, and various studies investigating their roles as potential diagnostic and prognostic biomarkers for HCC.

Overview of CTC Biology and Clinical Implications

As a malignant tumor proliferates and invades into the adjacent tissue, the tumor cells secrete matrix metalloproteinase, which breaks the basement membrane, enabling the tumor cells to gain direct access to the nearby blood and lymphatic vessels⁽²¹⁾ (Fig. 1). Once in the bloodstream, the tumor cells become CTCs and can remain in circulation until they reach different tissues of the body and invade them. Most of the CTCs introduced into circulation get rapidly killed by processes such as anoikis, immune attacks, or shear stress.⁽²²⁾ Thus, the CTCs undergo a number of adaptations to survive in their hostile new environment. A key process is epithelial to mesenchymal transition (EMT), in which CTCs lose epithelial-type surface markers and gain mesenchymal markers, allowing them to behave like mesenchymal cells. CTCs that have undergone EMT can easily detach themselves from the primary tumor tissue and invade the capillaries and possess significantly improved ability to survive and metastasize. In addition, CTCs may form aggregates with fibroblasts, leukocytes, endothelial cells, or platelets to form CTC clusters, which possess a significantly higher metastatic potential and increased ability to survive, compared with individual CTCs.⁽²³⁾ It should be noted that CTCs are not identical clones of each other, but represent a heterogeneous population of cells from different tumor foci, with abilities to change their phenotypic and molecular characteristics under selective microenvironmental and therapeutic pressures.⁽²⁴⁾ Studies have shown that profound heterogeneities exist between tumor cells within the primary tumors and those within sites of metastasis. Therefore, liquid biopsy using CTCs should not be regarded merely as a less invasive alternative to an actual biopsy, but a way to obtain a comprehensive understanding of the heterogeneous tumor cells throughout the body. Detection and isolation of CTCs can enable the implementation of precision medicine by revealing the molecular characteristics of the tumor and identify markers for targeted therapy.

Details are in the caption following the image — **Fig. 1**
Open in figure viewer PowerPoint

Circulating tumor cells in HCC. HCC exhibits epithelial characteristics with surface expression of epithelial markers such as EpCAM and CK, as well as hepatocyte-specific markers such as ASGPR and GPC3. HCC cells enter the bloodstream to become CTCs in different ways: (1) maintaining the epithelial characteristic, (2) undergoing EMT with the expression of mesenchymal markers such as vimentin and twist, and (3) as CTC clusters consisting of multiple tumor cells as well as RBCs, platelets, stromal cells, and fibroblasts. After entering the circulation, most CTCs get destroyed by anoikis, shear stress, or immune attack. Some epithelial CTCs undergo EMT in transit. Eventually, CTCs that survive have acquired a more metastatic molecular profile with increased survival and decreased apoptosis. CTC clusters are protected from the processes that would kill isolated CTCs. Both the individual CTCs and CTC clusters that survive go on to metastasize and develop genetic, epigenetic, and transcriptomic heterogeneity as well as polyploidy. The CTCs and CTC clusters can be collected and isolated from the peripheral blood through a variety of different enrichment techniques and can help with early detection, prognostication, and molecular characterization of HCC.

CTCs are being extensively studied in a variety of solid organ malignancies. In patients with metastatic prostate cancer, CTC enumeration has been shown to be a reliable predictor of prognosis and treatment response.⁽²⁵⁾ Detection of HER2+ CTCs in patients with breast cancer can identify candidates for targeted therapy.⁽²⁶⁾ Although CTCs are highly promising as a form of liquid biopsy, there are technical challenges to be overcome before there can be widespread use of CTCs. Most importantly, CTCs have an extremely rare frequency in the circulation, and the number of CTCs tends to be proportional to tumor volume, which makes their detection in early-stage disease challenging.⁽²⁷⁾ Therefore, the challenge of CTC research lies in improving the sensitivity and specificity of CTC detection to the levels necessary for accurate and comprehensive molecular characterization.

Another cornerstone of liquid biopsy, ctDNA is the fraction of cell-free DNA (cfDNA), which originates from dying tumor cells or macrophages that have phagocytized tumor cells.⁽²⁸⁾ As ctDNA contains genetic mutations identical to those of their originating tumor cells, ctDNA can be used to identify heterogeneous tumor-specific mutations and epigenetic changes, and to monitor tumor dynamics in patients who are undergoing therapy. ctDNA is already used for treatment-response monitoring or early detection of relapse, and to identify specific mutations to make therapy decisions.⁽^29-31⁾ Similar to CTCs, the clinical application of ctDNA is challenged by the technical difficulty of identifying ctDNA in the background of a significantly larger amount of cfDNA from other tissues. Moreover, it is unclear whether ctDNA accurately represents the genetic make-up of actively proliferating and metastasizing tumor cells, as ctDNA may disproportionately represent DNA from “weaker” tumor cells that are more prone to dying and releasing their contents into circulation.⁽³²⁾ Compared with ctDNA, the main advantage of CTCs is that intact, viable tumor cells are being captured. As long as their cellular integrity is preserved, the captured CTCs can be used for functional assays and be cultured to evaluate drug resistance.⁽³³⁾

CTC Detection and Isolation

Several systems have been developed to improve the detection and isolation of CTCs, using their distinct physical and molecular characteristics. The platforms can largely be broken down into three categories of immunoaffinity-based enrichment, biophysical property-based enrichment, and enrichment-free methods (Table 1).

Table 1. CTC Detection Technologies

	Subcategory	Key Features	Capture Yield*	Refs.
Immunoaffinity
CellSearch	Immunomagnetic	Ferrofluid beads functionalized with anti-EpCAM. The only FDA-approved platform for CTC enumeration in metastatic prostate, breast, and colorectal cancer	≥85%	35
MACS	Immunomagnetic	MNPs conjugated to various antibodies. Large surface area to volume ratio. Can be used for both positive/negative enrichment	40%-90%	34
SERS	Immunomagnetic	MNPs used as the CTC enrichment platform and SERS signal amplification substrate. Dual-selectivity using anti-ASGPR nanoparticles and anti-GPC3 nanorods for HCC CTC isolation	>90%	77
SE-iFISH	Immunomagnetic, in situ karyotyping	Combines subtraction enrichment followed by in situ phenotypic and karyotypic characterization; especially useful for identifying chromosome aneuploidy	70%-87%	94
CTC-chip	Microfluidic	Microposts (^µpCTC-Chip) with geometric arrangement generate laminar flow, optimizing cell attachment. Herringbone-shaped grooves (^HBCTC-chip) and microvortices increase cell contact toward antibody-coated surfaces. High-purity processing of whole blood	>60%	36
CTC-iChip^†	Microfluidic, immunomagnetic, inertial focusing	Sequential steps of micropillar array, inertial focusing, and magnetophoresis (isolation of nucleated cells including CTCs and WBCs using deterministic lateral displacement, alignment of nucleated cells in a microfluific channel, and collection of magnetically tagged cells). Combining strengths of microfluidics and magnetic-based cell sorting	97%	37
NanoVelcro^†	Microfluidic	Anti-EpCAM/anti-ASGPR/anti-GPC-3 coated nanosubstrates, with integrated microfluidic chaotic mixers to facilitate CTC-substrate contact to achieve enhanced HCC-CTC capture. Vimentin(+) CTCs identified as a poor prognostic subset in HCC	80%-94%	38
Biophysical Property
ISET	Microfiltration	Size-based isolation of CTCs that are usually larger than hematologic cells. Track-etched membranes with nano-sized to micron-sized pores in thin polycarbonate films	N/A	42
ScreenCell	Microfiltration	Size-based isolation of CTCs that are usually larger than hematologic cells. Track-etched membranes with nano-sized to micron-sized pores in thin polycarbonate films	74%-91%	43
CellSieve	Microfiltration	Precision pores arranged in arrayed patterns to enable CTC capture under low-pressure state and preserve intracellular architecture	83%-91%	44
FMSA	Microfiltration	Flexible polymer micro springs minimize cell damage. Allows rapid enrichment directly from whole blood	90%	45
CanPatrol	Microfiltration, immunomagnetic	Microfiltration followed by detection of EMT markers using RNA in situ hybridization	80%-89%	85
Ficoll-Paque	DGC	Inexpensive, easy-to-use in combination with other techniques. The ratio of CTCs to PBMCs remains unchanged	84%	48
OncoQuick	DGC	Porous membrane above separation media for additional separation by filtration. Superior CTC capture ratio compared with Ficoll-Paque	87%	49
OncoQuick	Microfiltration		87%	49
RosetteSep CTC Enrichment Cocktail	DGC immunomagnetic	Antibody complexes targeting an extensive mixture of CTC antigens. Can be used with centrifugation platforms such as Ficoll-Paque to enhance capture efficiency	36%-60%	50
DEPArray	DEP	Traps single cells in DEP cages generated through an array of electrodes. Can recover single CTCs	N/A	55
Enrichment-Free
ImageStream	IFC	Uses size and karyoplasmic ratios to detect CTCs, without requiring antibodies or complex handling of blood samples	N/A	57
PAFC	In vivo direct imaging	Absorption of laser by nanoparticles, which are tagged on targeted cells through antibodies. Enables real-time detection of CTCs in veins using a laser-based technology	N/A	59
EPISPOT	Functional assay	Detects viable CTCs at the single-cell level by identifying proteins that are secreted/released/shed (antibody-based) from single epithelial cancer cells. Theoretically can be combined with any CTC enrichment step with live tumor cells	N/A	60

* From cell line spiking study (the capture yield may vary in different cancer types and different generations of the technology).
^† In each processed patient sample, background 500 and 200-1,000 white blood cells were nonspecifically captured in the CTC-iChip and NanoVelcro platform, respectively. Other platforms did not report a reliable purity.
Abbreviations: DGC, density gradient centrifugation; FMSA, flexible micro spring array; MNP, magnetic nanoparticle; N/A, not available; PAFC, photoacoustic flow cytometry; PBMC, peripheral blood mononuclear cell; SERS, surface-enhanced Raman scattering; WBC, white blood cells.

Immunoaffinity

Immunoaffinity-based CTC enrichment techniques use antibodies against cell surface markers tethered to the device surface or a magnetic substance. Positive enrichment refers to capturing CTCs by using antibodies against specific tumor-associated antigens expressed on CTC surfaces, whereas negative enrichment refers to depleting the hematopoietic cells in the background by using antibodies against CD45.⁽³⁴⁾ Until recent years, CTCs were defined as nucleated epithelial cell adhesion molecule (EpCAM+)/CK+/CD45- cells. The only Food and Drug Administration (FDA)–approved CTC diagnostic technology, the CellSearch system (Menarini Silicon Biosystems Inc., Bologna, Italy) uses an immunomagnetic separation system of ferrofluid beads coated with antibody to EpCAM (anti-EpCAM).⁽³⁵⁾ Microfluidic devices such as the CTC-chip (developed at the Massachusetts General Hospital, Boston, MA) are composed of antibody-coated microposts with a geometric arrangement to optimize cell attachment.⁽³⁶⁾ The CTC-iChip combines microfluidic and immunomagnetic technology and has demonstrated a greater sensitivity of CTC detection compared with CellSearch.⁽³⁷⁾ In parallel, Wang et al. pioneered a unique concept of “NanoVelcro,” which uses antibody-coated nanostructured substrates with integrated microfluidic chaotic mixers to facilitate CTC-substrate contact to enhance CTC capture.⁽³⁸⁾

Epithelial markers such as EpCAM are often down-regulated or lost during the EMT.⁽³⁹⁾ These CTCs with EMT phenotype have highly metastatic properties and can escape positive enrichment systems that target the epithelial markers such as EpCAM and CK. Given such limitations of relying on epithelial markers, positive enrichment strategies targeting stem cell markers (e.g., CD133), mesenchymal markers (e.g., vimentin), and cancer-specific antigens (e.g., HER2, PSMA) have also been developed.⁽⁴⁰⁾

However, even antibody cocktails targeting a wide variety of antigens may not account for the heterogeneity of CTC antigens. Negative enrichment strategies address this by targeting and removing background hematopoietic cells. There are commercialized platforms dedicated to negative enrichment, and some of the positive-enrichment technologies such as magnetic activated cell sorting (MACS) and CTC-iChip can be used for negative enrichment by replacing anti-EpCAM with anti-CD45.⁽³⁴⁾ Although they allow for higher sensitivity compared with positive-enrichment technologies, negative-enrichment technologies alone typically have a much lower purity.⁽⁴¹⁾

Biophysical Properties

Compared with blood cells, CTCs are distinguished by their large size, mechanical plasticity, and dielectric mobility properties. This enables them to be isolated using techniques such as membrane filtration, density gradient stratification, inertial focusing, and dielectric mobility. These so-called “label-free” methods are increasingly popular, as they avoid the challenges of targeting numerous specific antigens. They also make downstream processing easier, as the isolated CTCs are not tagged with antibodies.⁽³⁴⁾

Microfiltration uses the larger, more rigid phenotype observed by the CTCs. Isolation by ISET (size of epithelial tumor cells; Berlex Laboratories, Inc., Montville, NJ)⁽⁴²⁾ and ScreenCell (Sarcelles, France)⁽⁴³⁾ use track-etched membranes, whereas CellSieve (Creatv MicroTech, Inc., Rockville, MD)⁽⁴⁴⁾ and flexible micro spring array⁽⁴⁵⁾ use photolithography to construct membranes that minimize captured cell damage. The Cluster-Chip (Massachusetts General Hospital) is a unique 3D microfiltration system that is designed specifically to capture CTC clusters.⁽⁴⁶⁾ The main advantage of microfiltration is its ability to rapidly process blood for CTC enrichment. However, microfiltration systems are subject to clogging, and size overlap between leukocytes and CTCs makes it challenging to achieve high purity.⁽³⁴⁾

Density-based gradient centrifugation uses the differences in specific gravities of leukocytes and CTCs.⁽⁴⁷⁾ Although not initially developed for CTC isolation, Ficoll-Paque (GE Healthcare Life Sciences) has been able to detect CTCs in patients with various cancers.⁽⁴⁸⁾ OncoQuick (Greiner Bio-One) combines centrifugation and filtration and has superior CTC capture ratio compared with Ficoll-Paque.⁽⁴⁹⁾ Finally, the RosetteSep CTC Enrichment Cocktail (STEMCELL Technologies, Inc.) integrates immunoaffinity with density centrifugation, using antibody complexes targeting an extensive mixture of antigens.⁽⁵⁰⁾ Centrifugation is used widely used for CTC isolation due to its reliability and inexpensiveness, but it is best used as an initial step before additional enrichment using other strategies.⁽³⁴⁾

Inertial focusing uses the differential inertial effect on different sizes of cells to help with the isolation of CTCs. It is applicable to CTCs larger than background hematologic cells. This method has been combined into many microfluidic devices.⁽⁵¹⁾ By establishing a model accounting for wall interaction force, shear gradient lift force, and secondary-flow drag force, as well as other effects including particle properties (i.e., cells in CTC isolation devices), rotation, interparticle spacing, and fluid properties, researchers have recently made significant improvements in predicting the motion of cells according to inertial focusing in microfluidic devices.⁽⁵²⁾ These devices have shown promising results with a high sensitivity of CTC detection and viability of retrieved CTCs.⁽⁵³⁾

Another technology, dielectrophoresis (DEP), separates cells using distinct electrical fingerprints among different cell types.⁽⁵⁴⁾ The dielectric characteristics of cancer cells are significantly different from blood cells. By applying an alternating electrical field, cells are electrically polarized, and CTCs can be isolated through differential electric forces. Becker et al. demonstrated differential dielectric parameters in breast cancer cell lines, lymphocytes, and erythrocytes. The dielectric differences between cancer and blood cells may result from the different morphologic features of the cell membrane, including microvilli, membrane folds, and blebbing.⁽⁵⁴⁾ DEPArray (Menarini Silicon Biosystems, Inc.) can trap single cells in DEP cages and has been used to recover single CTCs for highly specific genetic analyses.⁽⁵⁵⁾

Enrichment-Free Methods

All enrichment technologies require verification of the captured cells, which can be significantly time-consuming. Advancements in the field of high-speed, fluorescence imaging have led to the development of imaging platforms that enable a direct identification of CTCs from blood samples without the enrichment step.⁽⁵⁶⁾ Imaging flow cytometry distinguishes CTCs from leukocytes using parameters such as higher karyoplasmic ratio and size.⁽^{57, 58}⁾ Another unique, in vivo direct imaging method to detect CTCs is photoacoustic flow cytometry, which enables real-time detection of CTCs in veins using a laser-based technology.⁽⁵⁹⁾ Finally, there are functional assays to detect CTC, which exploit aspects of liver cellular activity such as secretion of tumor-associated proteins and preferential adhesion of CTCs to a specialized matrix.⁽⁶⁰⁾

CTCs as a Biomarker in HCC

EpCAM-Based CTC Detection in HCC

The commonly used, immunoaffinity-based CTC enrichment techniques such as CellSearch have been used to detect and capture EpCAM+ CTCs in patients with HCC (Table 2). In 2013, Sun et al. used CellSearch to detect EpCAM+ CTCs in patients with HCC undergoing tumor resection. The authors preoperatively detected EpCAM+ CTCs in 67% of patients with HCC. A preoperative CTC count of two or greater was shown to be a predictor of tumor recurrence after surgery.⁽⁶¹⁾ Additional studies using CellSearch demonstrated that the presence of EpCAM+ CTCs in patients with HCC was associated with vascular invasion,⁽^{62, 63}⁾ significantly elevated AFP,⁽⁶³⁾ more advanced Barcelona Clinic Liver Cancer (BCLC) stage,⁽⁶²⁾ disease progression,⁽⁶⁴⁾ higher recurrence rate,⁽⁶⁵⁾ and shorter overall survival.⁽^62-66⁾ In 2014, Guo et al. established an optimized platform based on negative enrichment and quantitative reverse-transcription PCR (RT-PCR) for the detection of EpCAM+ CTCs and exhibited 76.7% consistency with the CellSearch system.⁽⁶⁷⁾ In 2016, Wang et al. used the CTC-^BioTChip to detect EpCAM+ CTCs in 60% of patients with HCC (n = 42) and found significant correlations between both the positive rate and number of CTCs with tumor, node, and metastases staging.⁽⁶⁸⁾ In 2016, Zhou et al. studied the prognostic value of EpCAM+ CTCs and regulatory T cells (Treg) in patients with HCC and found that elevated EpCAM+ CTC and Treg levels were associated with early recurrence and poor clinical outcome.⁽⁶⁹⁾ Unfortunately, EpCAM-based CTC enrichment platforms are limited by the loss of epithelial markers in CTCs undergoing EMT. Furthermore, a study showed that only a small proportion (30%-40%) of HCC cells express EpCAM.⁽⁷⁰⁾

Table 2. CTC Studies in HCC

Study	Patients	Method	CTC Marker	Main Findings
EpCAM-Based CTC Detection in HCC
Sun et al.,⁽⁶¹⁾ 2013	123 HCC; 5 BLD; 10 HV	CellSearch	EpCAM	CTCs identified in 67% of pre-op patients, and 28% 1 month after resection; ≥2 CTCs/7.5 mL predicted recurrence
Schulze et al.,⁽⁶²⁾ 2013	59 HCC; 19 BLD	CellSearch	EpCAM	CTCs identified in 31% of patients with HCC. Associated with advanced stage, vascular invasion, and shorter OS
Guo et al.,⁽⁶⁷⁾ 2014	299 HCC; 24 BHT; 25 CLD; 71 HV	RosetteSep, MACS, quantitative RT-PCR	EpCAM	Negative enrichment and quantitative RT-PCR-based platform had AUROC = 0.70, sensitivity = 42.6%, and specificity = 96.7%. Combined with AFP level, AUROC improved to 0.86 with sensitivity = 73.0% and specificity = 93.4%
Kelley et al.,⁽⁶³⁾ 2015	20 HCC; 10 BLD	CellSearch	EpCAM	CTCs detected in 40% of patients with metastatic HCC; ≥1/7.5 mL associated with vascular invasion and decreased OS
Wang et al.,⁽⁶⁸⁾ 2016	42 HCC	CTC-^BioTChip	EpCAM	CTCs detected in 60% of patients with HCC. Positive rate and number of CTCs highly correlated with TNM staging
Zhou et al.,⁽⁶⁹⁾ 2016	49 HCC undergoing curative resection; 50 HV	RosetteSep	EpCAM	Patients with high EpCAM mRNA⁺ CTCs and CD4⁺CD25⁺Foxp3⁺ Treg cells had higher risk of postoperative recurrence (67% vs. 10%) and 1-year recurrence (50% vs. 10%)
Zhou et al.,⁽⁶⁹⁾ 2016	49 HCC undergoing curative resection; 50 HV	Quantitative RT-PCR	CD4⁺CD25⁺Foxp3⁺
von Felden et al.,⁽⁶⁵⁾ 2017	57 HCC undergoing resection	CellSearch	EpCAM	CTCs detected in 15% of patients with HCC. CTC positivity associated with higher recurrence and shorter median RFS
Shen et al.,⁽⁶⁴⁾ 2018	89 HCC undergoing TACE	CellSearch	EpCAM	CTCs detected in 56% of patients with HCC. Higher number of CTCs associated with mortality and progression
Yu et al.,⁽⁶⁶⁾ 2018	139 HCC; 23 BHT	CellSearch	EpCAM	Patients with CTC ≥ 2 had shorter DFS and OS compared to patients with CTC < 2
Combined Markers-Based CTC Detection in HCC
Xu et al.,⁽⁷¹⁾ 2011	85 HCC; 37 BLD; 14 OT; 20 HV	AutoMACS	ASGPR, HER2, TP53	CTCs identified in 81% of patients with HCC. Positivity and number of CTCs correlated with tumor size, portal vein tumor thrombus, differentiation status, and disease extent
Li et al.,⁽⁷³⁾ 2014	27 HCC; 12 OT; 13 LC; 11 BLT; 7 CH; 15 HV	AutoMACS	ASGPR; CPS1	CTCs detected in 89% of patients with HCC. Anti-ASGPR-specific and efficient for HCC-CTC enrichment. Combining anti-P-CK and anti-CPS1 was superior (96.7%) to using one antibody alone (CPS1: 62.1%, P-CK: 85.2%)
Li et al.,⁽⁷³⁾ 2014	27 HCC; 12 OT; 13 LC; 11 BLT; 7 CH; 15 HV	AutoMACS	P-CK
Mu et al.,⁽⁷⁴⁾ 2014	62 HCC; 7 CH; 15 HV	MidiMACS	ASGPR, GPC3, CK	GPC3, ASGPR, and CK expression increased in patients with HCC. PPV and NPV: 90% and 71% for GPC3; 93% and 75% for ASGPR; 83% and 29% for CK. GPC3 and ASGPR expression associated with decreased OS
Liu et al.,⁽⁷⁵⁾ 2015	32 HCC; 17 OT; 12 BLT; 15 LC; 10 CH; 3 AH; 20 HV	Ficoll-Paque, RosetteSep	ASGPR	CD45 depletion of leukocytes recovered more CTCs compared with ASGPR⁺ selection. Combining anti-ASGPR and anti-CPS1 improved CTC detection vs. either antibody alone, and detected CTCs in 91% of patients with HCC
Liu et al.,⁽⁷⁵⁾ 2015	32 HCC; 17 OT; 12 BLT; 15 LC; 10 CH; 3 AH; 20 HV	Ficoll-Paque, RosetteSep	CPS1
Zhang et al.,⁽⁷⁶⁾ 2016	36 HCC; 14 BLD	CTC-chip	ASGPR, P-CK, CPS1	CTCs detected in 100% of patients with HCC. Captured CTCs readily released from CTC-chip and could subsequently be expanded to form a spheroid-like structure in a 3-dimensional cell culture assay
Pang et al.,⁽⁷⁷⁾ 2018	8 HCC; 5 OT; 5 HV	SERS	ASGPR, GPC3	SERS nanoplatform detected CTCs in 100% of patients with HCC, and enabled detection with small volume of blood
Label-Free (Biophysical and Enrichment-Free) Methods to Detect CTCs in HCC
Vona et al.,⁽⁴²⁾ 2000	7 HCC undergoing hepatectomy; 8 CH; 8 HV	ISET	AFP	CTCs detected in 43% and 86% of patients with HCC before and after surgery. ISET allowed subsequent analysis of cell morphology, enumeration of CTCs, and demonstration of tumor microemboli during surgery
Vona et al.,⁽⁴²⁾ 2000	7 HCC undergoing hepatectomy; 8 CH; 8 HV	RT-PCR	PSA
Vona et al.,⁽⁷⁹⁾ 2004	44 HCC; 30 CH; 39 LC; 38 HV	ISET	N/A	CTCs found in 52% of patients with HCC. Associated with portal tumor thrombosis and shorter survival
Morris et al.,⁽⁸⁰⁾ 2014	52 HCC	ISET	EpCAM	CellSearch detected CTCs in 28%, whereas ISET detected CTCs in 100% of patients with HCC. Presence of GPC3-positive CTCs by ISET was 100% concordant with GPC3-positive cells in the original tumor
Morris et al.,⁽⁸⁰⁾ 2014	52 HCC	CellSearch	GPC3
Liu et al.,⁽⁵⁷⁾ 2016	52 HCC; 12 HV	IFC	HKR	Using HKR, IFC had an AUROC of 0.82. Patients with HCC had significantly higher presence of microvascular thrombosis, as well as higher risk of recurrence and mortality
Ogle et al.,⁽⁵⁸⁾ 2016	69 HCC; 16 LC; 15 HV	IFC	Cell size	Size criteria + absence of CD45 led to capture of all positive biomarker CTCs, and 28% of biomarker negative CTCs. Increased CTCs associated with advanced tumor stage, portal vein thrombosis, and poorer survival
Ogle et al.,⁽⁵⁸⁾ 2016	69 HCC; 16 LC; 15 HV	IFC	CK, EpCAM, AFP, GPC-3, DNA-K
Biologic Characterization and Heterogeneity of CTCs in HCC
Li et al.,⁽⁷²⁾ 2013	60 HCC; 10 BLD; 10 OT; 10 HV	MiniMACS	ASGPR, vimentin, twist, ZEB1/2, snail, slug, cadherin	CTCs detected in 77% of patients with HCC. CTC positivity higher in patients with portal vein thrombus and advanced stages. EMT markers highly correlated with portal vein thrombus, TNM classification, and tumor size
Li et al.,⁽⁷²⁾ 2013	60 HCC; 10 BLD; 10 OT; 10 HV	Flow cytometry	ASGPR, vimentin, twist, ZEB1/2, snail, slug, cadherin
Li et al.,⁽⁸²⁾ 2016	109 HCC on sorafenib treatment	Ficoll-Paque	pERK	pERK/pAkt expression in CTC and tissue concordant in 90%. pERK+/pAkt- CTCs associated with PFS and predicted good prognosis. In vitro, pERK+/pAkt- HCC cells showed the greatest response to sorafenib
Li et al.,⁽⁸²⁾ 2016	109 HCC on sorafenib treatment	RosetteSep	pAkt
Shi et al⁽⁸¹⁾ 2016	47 HCC undergoing cryoablation	MACS	MAGE-3, survivin	Average CTCs decreased significantly following cryosurgery. Gene expression for tumor markers MAGE-3, surviving, and CEA all significantly decreased following cryosurgery as well
Shi et al⁽⁸¹⁾ 2016	47 HCC undergoing cryoablation	Quantitative RT-PCR	CEA
Kalinich et al.,⁽⁸⁴⁾ 2017	63 HCC; 31 CLD; 6 LM; 38 OT; 26 HV	CTC-iChip	AFP, AHSG, ALB, APOH, FABP1, FGB, FGG, GPC3, RBP4, TF	10 liver-specific transcripts identified CTCs in 56% of untreated patients with HCC vs. 3% of patients with nonmalignant liver disease at risk of developing HCC. CTC positivity declined in patients with HCC receiving therapy
Kalinich et al.,⁽⁸⁴⁾ 2017	63 HCC; 31 CLD; 6 LM; 38 OT; 26 HV	Digital PCR	AFP, AHSG, ALB, APOH, FABP1, FGB, FGG, GPC3, RBP4, TF
Chen et al.,⁽⁸⁶⁾ 2017	195 HCC	CanPatrol	CK, EpCAM, twist, cadherin, snail, vimentin, AKT2	CTCs detected in 95% of patients with HCC. Able to discriminate metastatic HCC with AUROC = 0.86, sensitivity = 86%, specificity = 81%. Mesenchymal CTCs associated with age, BCLC stages, metastasis, AFP levels, recurrence
Court et al.,⁽⁷⁸⁾ 2018	61 HCC; 11 BLD; 8 HV	NanoVelcro CTC Assay	EpCAM, ASGPR	CTCs detected in 97% of patients with HCC. Panel identified HCC with sensitivity = 84.2%, specificity = 88.5%, PPV = 69.6%, NPV = 94.7%, and AUROC = 0.92. Vimentin-positive CTCs associated with aggressive disease and metastasis
Court et al.,⁽⁷⁸⁾ 2018	61 HCC; 11 BLD; 8 HV	NanoVelcro CTC Assay	GPC3, vimentin
Qi et al.,⁽⁸⁷⁾ 2018	112 HCC treated with R0 resection; 12 HBV; 20 HV	CanPatrol	EpCAM, CK, vimentin, twist	CTCs detected in 90% of patients with HCC. CTC count ≥16 and mesenchymal-CTC percentage ≥2% associated with recurrence and metastasis. BCAT1 gene identified as a potential trigger of EMT
Ou et al.,⁽⁸⁸⁾ 2018	165 HCC undergoing radical resection	CanPatrol	EpCAM, CK, vimentin, twist	CTCs detected in 71% of patients with HCC. Increased CTCs associated with higher AFP, multiple tumors, advanced staging, and tumor embolus. Mesenchymal CTCs predicted earlier recurrence and shortest RFS
Yin et al.,⁽⁸⁹⁾ 2018	80 HCC; 10 HV	CanPatrol	Twist	Twist+ correlated with tumor burden/aggressiveness, staging, as well as post-op recurrence and mortality
Ye et al.,⁽⁹⁰⁾ 2018	42 HCC	CanPatrol	TP53	Post-op CTC counts and changes in CTC counts were independent prognostic indicators for PFS
Cheng et al.,⁽⁹¹⁾ 2018	113 HCC; 57 BLD; 6 LM	CanPatrol	CK, EpCAM	Total number of CTCs had AUROC = 0.774, which improved to 0.821 when combined with serum AFP. Mesenchymal CTCs were increased in late-stage patients with HCC
Cheng et al.,⁽⁹¹⁾ 2018	113 HCC; 57 BLD; 6 LM	CanPatrol	Vimentin, twist
Wang et al.,⁽⁸⁵⁾ 2018	62 HCC undergoing radical resection	CanPatrol	CK, EpCAM, vimentin, twist	CTCs detected in 84% of patients with HCC. Patients with post-op recurrence had significantly higher number of CTCs, mesenchymal CTCs, and mixed CTCs. Mesenchymal CTCs associated with shortened postoperative DFS
D’Avola et al.,⁽⁹²⁾ 2018	6 HCC; 1 HV	Single-cell RNA sequencing	CK, EpCAM	Single-cell RNA sequencing of CTCs showed significant transcriptome heterogeneity. Nonhepatic expression of ASGPR1 was detected in a significant proportion of non-CTCs, primarily monocytes
D’Avola et al.,⁽⁹²⁾ 2018	6 HCC; 1 HV	Single-cell RNA sequencing	GPC3, ASGPR1
Sun et al.,⁽⁹³⁾ 2018	73 HCC undergoing curative resection	CellSearch	EpCAM, CK, cadherin, slug, vimentin, snail	EMT status of CTCs was heterogeneous across different vascular compartments (peripheral vein, peripheral artery, hepatic vein, portal vein, IVC)
Sun et al.,⁽⁹³⁾ 2018	73 HCC undergoing curative resection	Quantitative RT-PCR	EpCAM, CK, cadherin, slug, vimentin, snail
Wang et al.,⁽⁹⁴⁾ 2018	14 HCC; 16 CCA; 4 GBC undergoing resection	SE-iFISH	C8 aneuploidy	Among CTCs detected, 8% were EpCAM+, and 86% were EpCAM−. Small aneuploid HCC CTCs were discovered. Post-op quantity of triploid CTCs, multiploid CTCs, or CTMs were correlated with poor prognosis
Winograd et al.,⁽⁸³⁾ 2018	73 HCC; 11 BLD; 8 HV	CTC-iChip	PD-L1	Presence of PD-L1+ CTCs predicted response to anti-PD1 therapy

Abbreviations: AH, acute hepatitis; AUROC, area under the receiver operating characteristic curve; BHT, benign hepatic tumor; BLD, benign liver disease; CCA, cholangiocarcinoma; CH, chronic hepatitis; CLD, chronic liver disease; CTM, circulating tumor microemboli; DFS, disease-free survival; GBC, gallbladder cancer; HBV, hepatitis B virus; HD, hepatic disease without HCC; HV, healthy volunteers; IVC, inferior vena cava; LC, liver cirrhosis; LM, liver metastasis; NPV, negative predictive value; OS, overall survival; OT, other malignant tumors; PD1, programmed death receptor 1; PFS, progress-free survival; PPV, positive predictive value; RFS, recurrence-free survival; SERS, surface-enhanced Raman scattering; TNM, tumor, node, and metastases.

Combined Markers-Based CTC Detection in HCC

To overcome the low sensitivity of EpCAM-based CTC detection platforms in HCC, alternative markers have been investigated (Table 2). For example, asialoglycoprotein receptor (ASGPR), a transmembrane protein exclusively expressed on hepatocyte surfaces, has been used in a variety of enrichment methods for CTC detection in patients with HCC.⁽^71-78⁾ In 2011, Xu et al. performed immunomagnetic separation using HCC cells bound by biotinylated asialofetuin, a ligand of ASGPR, and was able to detect CTCs in 81% of patients with HCC.⁽⁷¹⁾ Both the presence of CTCs and the quantity of CTCs significantly correlated with tumor extent, portal vein tumor thrombus, and differentiation status.⁽⁷¹⁾ In 2014, the same group used a synthetic anti-ASGPR antibody instead of ASGPR ligand with successful CTC detection in 89% of patients with HCC.⁽⁷³⁾ Another study achieved an even higher CTC detection rate of 91% in patients with HCC by using a mixture of antibodies against ASGPR and CPS1, combined with negative enrichment.⁽⁷⁵⁾ In 2016, Zhang et al. used a CTC-chip with antibodies to ASGPR, P-CK, and CPS1 and isolated CTCs from 100% of patients with HCC (n = 36).⁽⁷⁶⁾ Recently, Court et al. used the NanoVelcro CTC Assay with a multimarker panel of EpCAM, ASGPR, and GPC3, and captured CTCs in 97% of patients with HCC.⁽⁷⁸⁾

Label-Free (Biophysical and Enrichment-Free) Methods of CTC Detection in HCC

“Label-free” methods have also been investigated for CTC detection in HCC patients (Table 2). In 2000, Vona et al. used the ISET, a 2-dimensional microfiltration system, to detect CTCs in patients with HCC undergoing liver resection, and was able to capture tumor microemboli during surgery.⁽⁴²⁾ Vona et al. also found that the number of CTCs detected by ISET correlated with the presence of a diffuse tumor, portal tumor thrombosis, more advanced liver disease, as well as shorter survival.⁽⁷⁹⁾ A direct comparison of CellSearch and ISET in their ability to detect CTCs in patients with HCC revealed a significantly superior performance by ISET (ISET: 100%, CellSearch: 28%).⁽⁸⁰⁾ However, one disadvantage of the ISET is the difficulty of releasing CTCs for downstream genetic analysis.⁽²⁷⁾

In 2016, Liu et al. used imaging flow cytometry (IFC) to detect CTCs from blood samples of patients with HCC, using a higher karyoplasmic ratio (HKR) seen with CTCs. When compared with the traditional CTC detection method based on CD45- EpCAM+ cells, IFC using HKR cells showed significantly greater area under the receiver operating characteristic curve of 0.82 versus 0.73.⁽⁵⁷⁾ Ogle et al. studied IFC focusing on cell size and compared its effectiveness to a multimarker panel consisting of CK, EpCAM, AFP, GPC-3, and DNA-K. IFC with the inclusion of size criteria, combined with the depletion of CD45 cells, led to the capture of all positive biomarker CTCs, as well as an additional 28% of CTCs that did not express any of the biomarkers tested.⁽⁵⁸⁾ The advantages of IFC are its ease and cost-effectiveness without requiring antibodies or complex handling of blood samples. However, its specificity could be limited by the presence of immune cells, which also have large size and HKRs.⁽⁵⁷⁾

Biological Characterization and Heterogeneity of CTCs

Multimarker combination panels and downstream molecular analysis can reveal biological characteristics and heterogeneities of HCC CTCs (Table 2). Identification of CTCs expressing specific tumor markers and drug targets allows providers to predict response to therapy. Shi et al. used three CTC markers (MAGE3, survivin, and CEA) to evaluate the efficacy of cryosurgery on unresectable HCC, and found that they were reliable in predicting treatment response.⁽⁸¹⁾ In 2016, Li et al. used the expression status of pERK and pAkt to detect CTCs in 93% of patients with advanced HCC undergoing sorafenib treatment.⁽⁸²⁾ Among different patterns of pERK/pAkt expression, the presence of pERK+/pAkt- CTCs was significantly associated with longer progression-free survival and higher rate of response to sorafenib.⁽⁸²⁾ Winograd et al. evaluated for CTCs expressing programmed death ligand 1 (PD-L1) in patients with HCC, and found that the presence of PD-L1+ CTCs discriminated patients with HCC with early-stage and advanced/metastatic disease. Of the 6 patients receiving anti–programmed death protein 1 therapy, all 3 patients demonstrating response had PD-L1+ CTCs, compared with only 1 of 3 nonresponders, suggesting the possibility that PD-L1+ CTCs might be predictive of treatment response to immunotherapy.⁽⁸³⁾ In 2017, Kalinich et al. also devised a unique strategy of using the CTC-iChip to isolate CTCs, then applying RNA-based digital PCR to detect a panel of liver-specific transcripts, which were combined into a single metric CTC score. The CTC score was highly correlated with BCLC staging and declined in patients receiving therapy.⁽⁸⁴⁾

Expression of EMT markers such as vimentin and twist in CTCs of patients with HCC has been studied as markers for predicting recurrence and prognosis. Most of these studies used the CanPatrol CTC analysis platform (SurExam, Guangzhou, China), a two-step technique including microfiltration and subsequent characterization of CTCs using a variety of epithelial (EpCAM, CK8/9/19) and mesenchymal markers (vimentin and twist).⁽⁸⁵⁾ Using this method, Chen et al. detected CTCs in 95% of 195 patients with HCC.⁽⁸⁶⁾ The proportion of hybrid and mesenchymal CTCs was associated with increased age, BCLC stages, metastasis, and AFP levels.⁽⁸⁶⁾ Wang et al. studied 62 patients with HCC undergoing surgical resection and found that patients with a higher number of mesenchymal CTCs had increased risk of recurrence and shortened disease-free survival.⁽⁸⁵⁾ Other studies using CanPatrol showed a consistent association between mesenchymal CTCs and poor clinical outcomes.⁽^87-91⁾

An emerging body of literature suggests profound heterogeneity among the HCC CTCs. D’Avola et al. developed an analytical technique that combines IFC and single-cell mRNA sequencing.⁽⁹²⁾ Genome-wide expression profiling of CTCs using this approach demonstrated significant transcriptome heterogeneity, even among CTCs from the same patient with HCC.⁽⁹²⁾ Such marked heterogeneity among CTCs was also reported by Sun et al., who found significant heterogeneity in the EMT status of CTCs across different vascular compartments, with predominantly epithelial phenotype at release but switching to EMT phenotype during transit.⁽⁹³⁾ A recent study demonstrated even more heterogeneity among CTCs, both in size and karyotype. Wang et al. used subtraction enrichment and immunostaining fluorescence in situ hybridization (SE-iFISH), which uses in situ characterization of phenotypes and karyotypes to examine both chromosomal aneuploidy and tumor marker expressions. Using this strategy, the authors discovered the existence of small HCC CTCs smaller than white blood cells, with a very high prevalence of chromosome 8 aneuploidy. The postsurgical quantity of triploid or multiploid CTCs significantly correlated with poor prognosis.⁽⁹⁴⁾

Conclusion and Future Directions

Decades of research have led to significant advancements in the clinical utility of CTCs in patients with HCC (Fig. 1). As a form of liquid biopsy, CTCs hold great potential to facilitate the implementation of precision medicine in patients with HCC. CTCs are already FDA-approved for disease monitoring and prognostication in patients with metastatic breast and colorectal cancer, and there is an ongoing National Institutes of Health–sponsored clinical trial (NCT02973204) to investigate CTCs and ctDNA as clinical support tools in HCC. However, significant challenges remain before CTCs can be adopted for widespread clinical use in HCC. In addition to the technical challenges with CTC detection and isolation, there are numerous CTC detection methods, each with its own protocols for sample preparation, enrichment, and analysis. Most studies are small, single-center, case-control studies with widely varying patient demographics such as ethnicity, etiology of liver disease, and stage of HCC, which makes validation studies very difficult. Therefore, there needs to be a standardized assay protocol with high sensitivity and specificity that can capture the full spectrum of CTCs. This can potentially be achieved by multicenter, prospective studies with a larger sample size using a uniform CTC detection platform, which can provide effective validation of the findings.⁽⁹⁵⁾

Author Contributions

J.C.A.: Review of the literature, drafting of the manuscript, and approval of the final version. P.-C.T., P.-J.C.: Review of the literature, critical revision of the manuscript, and approval of the final version. E.P., H.-R.T., S.C.L.: Conceptualization, critical revision of the manuscript, and approval of the final version. J.D.Y.: Conceptualization, supervision, critical revision of the manuscript, and approval of the final version.

References

1Akinyemiju T, Abera S, Ahmed M, Alam N, Alemayohu MA, Allen C, et al. The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: results from the global burden of disease study 2015. JAMA Oncol 2017; 3: 1683-1661.
10.1001/jamaoncol.2017.3055
PubMed Web of Science® Google Scholar
2Marrero JA, Kulik LM, Sirlin CB, Zhu AX, Finn RS, Abecassis MM, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the american association for the study of liver diseases. Hepatology 2018; 68: 723-750.
10.1002/hep.29913
PubMed Web of Science® Google Scholar
3Omata M, Cheng AL, Kokudo N, Kudo M, Lee JM, Jia J, et al. Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update. Hepatol Int 2017; 11: 317-370.
10.1007/s12072-017-9799-9
PubMed Web of Science® Google Scholar
4Galle PR, Forner A, Llovet JM, Mazzaferro V, Piscaglia F, Raoul JL, et al. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2018; 69: 182-236.
10.1016/j.jhep.2018.03.019
PubMed Web of Science® Google Scholar
5Lou J, Zhang L, Lv S, Zhang C, Jiang S. Biomarkers for hepatocellular carcinoma. Biomarkers Cancer 2017; 9: 1-9.
10.1177/1179299X16684640
CAS PubMed Google Scholar
6Agopian VG, Harlander-Locke MP, Markovic D, Zarrinpar A, Kaldas FM, Cheng EY, et al. Evaluation of patients with hepatocellular carcinomas that do not produce α-fetoprotein. JAMA Surg 2017; 152: 55-64.
10.1001/jamasurg.2016.3310
PubMed Web of Science® Google Scholar
7Zhu AX, Kang YK, Yen CJ, Finn RS, Galle PR, Llovet JM, et al. Ramucirumab after sorafenib in patients with advanced hepatocellular carcinoma and increased α-fetoprotein concentrations (REACH-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol 2019; 20: 282-296.
10.1016/S1470-2045(18)30937-9
CAS PubMed Web of Science® Google Scholar
8Mehta N, Heimbach J, Harnois DM, Sapisochin G, Dodge JL, Lee D, et al. Validation of a risk estimation of tumor recurrence after transplant (RETREAT) score for hepatocellular carcinoma recurrence after liver transplant. JAMA Oncol 2017; 3: 493-500.
10.1001/jamaoncol.2016.5116
PubMed Web of Science® Google Scholar
9Johnson PJ, Pirrie SJ, Cox TF, Berhane S, Teng M, Palmer D, et al. The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers. Cancer Epidemiol Biomarkers Prev 2014; 23: 144-153.
10.1158/1055-9965.EPI-13-0870
CAS PubMed Web of Science® Google Scholar
10Hippo Y, Watanabe K, Watanabe A, Midorikawa Y, Yamamoto S, Ihara S, et al. Identification of soluble NH2-terminal fragment of glypican-3 as a serological marker for early-stage hepatocellular carcinoma. Cancer Res 2004; 64: 2418-2423.
10.1158/0008-5472.CAN-03-2191
CAS PubMed Web of Science® Google Scholar
11Feng J, Zhu R, Chang C, Yu L, Cao F, Zhu G, et al. CK19 and glypican 3 expression profiling in the prognostic indication for patients with HCC after surgical resection. PLoS One 2016; 11:e0151501.
10.1371/journal.pone.0151501
PubMed Web of Science® Google Scholar
12Marrero JA, Romano PR, Nikolaeva O, Steel L, Mehta A, Fimmel CJ, et al. GP73, a resident Golgi glycoprotein, is a novel serum marker for hepatocellular carcinoma. J Hepatol 2005; 43: 1007-1012.
10.1016/j.jhep.2005.05.028
CAS PubMed Web of Science® Google Scholar
13Zhu WW, Guo JJ, Guo L, Jia HL, Zhu M, Zhang JB, et al. Evaluation of midkine as a diagnostic serum biomarker in hepatocellular carcinoma. Clin Cancer Res 2013; 19: 3944-3954.
10.1158/1078-0432.CCR-12-3363
CAS PubMed Web of Science® Google Scholar
14Wan HG, Xu H, Gu YM, Wang H, Xu W, Zu MH. Comparison osteopontin vs AFP for the diagnosis of HCC: a meta-analysis. Clin Res Hepatol Gastroenterol 2014; 38: 706-714.
10.1016/j.clinre.2014.06.008
CAS PubMed Web of Science® Google Scholar
15Pozzan C, Cardin R, Piciocchi M, Cazzagon N, Maddalo G, Vanin V, et al. Diagnostic and prognostic role of SCCA-IgM serum levels in hepatocellular carcinoma (HCC). J Gastroenterol Hepatol 2014; 29: 1637-1644.
10.1111/jgh.12576
CAS PubMed Web of Science® Google Scholar
16Zhang H, Yao M, Wu W, Qiu L, Sai W, Yang J, et al. Up-regulation of annexin A2 expression predicates advanced clinicopathological features and poor prognosis in hepatocellular carcinoma. Tumour Biol 2015; 36: 9373-9383.
10.1007/s13277-015-3678-6
CAS PubMed Web of Science® Google Scholar
17Zhu S, Hoshida Y. Molecular heterogeneity in hepatocellular carcinoma. Hepatic Oncol 2018; 5:HEP10.
10.2217/hep-2018-0005
PubMed Web of Science® Google Scholar
18Ye Q, Ling S, Zheng S, Xu X. Liquid biopsy in hepatocellular carcinoma: circulating tumor cells and circulating tumor DNA. Mol Cancer 2019; 18: 114.
10.1186/s12943-019-1043-x
PubMed Web of Science® Google Scholar
19Parkinson DR, Dracopoli N, Petty BG, Compton C, Cristofanilli M, Deisseroth A, et al. Considerations in the development of circulating tumor cell technology for clinical use. J Transl Med 2012; 10: 138.
10.1186/1479-5876-10-138
PubMed Web of Science® Google Scholar
20Mego M. Emerging role of circulating tumor cells in cancer management. Indian J Med Paediatric Oncol 2014; 35: 237-238.
10.4103/0971-5851.144962
PubMed Google Scholar
21Kleiner DE, Stetler-Stevenson WG. Matrix metalloproteinases and metastasis. Cancer Chemother Pharmacol 1999; 43(Suppl): S42-S51.
10.1007/s002800051097
CAS PubMed Web of Science® Google Scholar
22Miller MC, Doyle GV, Terstappen LW. Significance of circulating tumor cells detected by the cell search system in patients with metastatic breast colorectal and prostate cancer. J Oncol 2010; 2010: 617421.
10.1155/2010/617421
PubMed Google Scholar
23Aceto N, Bardia A, Miyamoto DT, Donaldson MC, Wittner BS, Spencer JA, et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 2014; 158: 1110-1122.
10.1016/j.cell.2014.07.013
CAS PubMed Web of Science® Google Scholar
24Micalizzi DS, Maheswaran S, Haber DA. A conduit to metastasis: circulating tumor cell biology. Genes Dev 2017; 31: 1827-1840.
10.1101/gad.305805.117
CAS PubMed Web of Science® Google Scholar
25Pantel K, Hille C, Scher HI. Circulating tumor cells in prostate cancer: from discovery to clinical utility. Clin Chem 2019; 65: 87-99.
10.1373/clinchem.2018.287102
CAS PubMed Web of Science® Google Scholar
26Chen W, Zhang J, Huang L, Chen L, Zhou Y, Tang D, et al. Detection of HER2-positive circulating tumor cells using the liquidbiopsy system in breast cancer. Clin Breast Cancer 2019; 19: e239-e246.
10.1016/j.clbc.2018.10.009
CAS PubMed Web of Science® Google Scholar
27Okajima W, Komatsu S, Ichikawa D, Miyamae M, Ohashi T, Imamura T, et al. Liquid biopsy in patients with hepatocellular carcinoma: circulating tumor cells and cell-free nucleic acids. World J Gastroenterol 2017; 23: 5650-5668.
10.3748/wjg.v23.i31.5650
PubMed Web of Science® Google Scholar
28Alix-Panabieres C, Schwarzenbach H, Pantel K. Circulating tumor cells and circulating tumor DNA. Annu Rev Med 2012; 63: 199-215.
10.1146/annurev-med-062310-094219
CAS PubMed Web of Science® Google Scholar
29Schmiegel W, Scott RJ, Dooley S, Lewis W, Meldrum CJ, Pockney P, et al. Blood-based detection of RAS mutations to guide anti-EGFR therapy in colorectal cancer patients: concordance of results from circulating tumor DNA and tissue-based RAS testing. Mol Oncol 2017; 11: 208-219.
10.1002/1878-0261.12023
CAS PubMed Web of Science® Google Scholar
30Siravegna G, Bardelli A. Genotyping cell-free tumor DNA in the blood to detect residual disease and drug resistance. Genome Biol 2014; 15: 449.
10.1186/s13059-014-0449-4
PubMed Web of Science® Google Scholar
31Ulz P, Heitzer E, Geigl JB, Speicher MR. Patient monitoring through liquid biopsies using circulating tumor DNA. Int J Cancer 2017; 141: 887-896.
10.1002/ijc.30759
CAS PubMed Web of Science® Google Scholar
32Fiala C, Diamandis EP. Utility of circulating tumor DNA in cancer diagnostics with emphasis on early detection. BMC Med 2018; 16: 166.
10.1186/s12916-018-1157-9
CAS PubMed Web of Science® Google Scholar
33Maheswaran S, Haber DA. Ex vivo culture of CTCs: an emerging resource to guide cancer therapy. Can Res 2015; 75: 2411-2415.
10.1158/0008-5472.CAN-15-0145
CAS PubMed Web of Science® Google Scholar
34Ferreira MM, Ramani VC, Jeffrey SS. Circulating tumor cell technologies. Mol Oncol 2016; 10: 374-394.
10.1016/j.molonc.2016.01.007
CAS PubMed Web of Science® Google Scholar
35Allard WJ, Matera J, Miller MC, Repollet M, Connelly MC, Rao C, et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin Cancer Res 2004; 10: 6897-6904.
10.1158/1078-0432.CCR-04-0378
PubMed Web of Science® Google Scholar
36Talasaz AH, Powell AA, Huber DE, Berbee JG, Roh KH, Yu W, et al. Isolating highly enriched populations of circulating epithelial cells and other rare cells from blood using a magnetic sweeper device. Proc Natl Acad Sci U S A 2009; 106: 3970-3975.
10.1073/pnas.0813188106
CAS PubMed Web of Science® Google Scholar
37Karabacak NM, Spuhler PS, Fachin F, Lim EJ, Pai V, Ozkumur E, et al. Microfluidic, marker-free isolation of circulating tumor cells from blood samples. Nat Protoc 2014; 9: 694-710.
10.1038/nprot.2014.044
CAS PubMed Web of Science® Google Scholar
38Wang S, Liu K, Liu J, Yu ZT, Xu X, Zhao L, et al. Highly efficient capture of circulating tumor cells by using nanostructured silicon substrates with integrated chaotic micromixers. Angew Chem Int Ed Engl 2011; 50: 3084–3088.
10.1002/anie.201005853
CAS PubMed Web of Science® Google Scholar
39Polyak K, Weinberg RA. Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer 2009; 9: 265-273.
10.1038/nrc2620
CAS PubMed Web of Science® Google Scholar
40Satelli A, Brownlee Z, Mitra A, Meng QH, Li S. Circulating tumor cell enumeration with a combination of epithelial cell adhesion molecule- and cell-surface vimentin-based methods for monitoring breast cancer therapeutic response. Clin Chem 2015; 61: 259-266.
10.1373/clinchem.2014.228122
CAS PubMed Web of Science® Google Scholar
41Lara O, Tong X, Zborowski M, Farag SS, Chalmers JJ. Comparison of two immunomagnetic separation technologies to deplete T cells from human blood samples. Biotechnol Bioeng 2006; 94: 66-80.
10.1002/bit.20807
CAS PubMed Web of Science® Google Scholar
42Vona G, Sabile A, Louha M, Sitruk V, Romana S, Schutze K, et al. Isolation by size of epithelial tumor cells: a new method for the immunomorphological and molecular characterization of circulatingtumor cells. Am J Pathol 2000; 156: 57-63.
10.1016/S0002-9440(10)64706-2
CAS PubMed Web of Science® Google Scholar
43Desitter I, Guerrouahen BS, Benali-Furet N, Wechsler J, Janne PA, Kuang Y, et al. A new device for rapid isolation by size and characterization of rare circulating tumor cells. Anticancer Res 2011; 31: 427-441.
PubMed Web of Science® Google Scholar
44Adams DL, Stefansson S, Haudenschild C, Martin SS, Charpentier M, Chumsri S, et al. Cytometric characterization of circulating tumor cells captured by microfiltration and their correlation to the Cell Search((R)) CTC test. Cytometry A 2015; 87: 137-144.
10.1002/cyto.a.22613
CAS PubMed Web of Science® Google Scholar
45Harouaka RA, Zhou MD, Yeh YT, Khan WJ, Das A, Liu X, et al. Flexible micro spring array device for high-throughput enrichment of viable circulating tumor cells. Clin Chem 2014; 60: 323-333.
10.1373/clinchem.2013.206805
CAS PubMed Web of Science® Google Scholar
46Sarioglu AF, Aceto N, Kojic N, Donaldson MC, Zeinali M, Hamza B, et al. A microfluidic device for label-free, physical capture of circulating tumor cell clusters. Nat Methods 2015; 12: 685-691.
10.1038/nmeth.3404
CAS PubMed Web of Science® Google Scholar
47Seal SH. Silicone flotation: a simple quantitative method for the isolation of free-floating cancer cells from the blood. Cancer 1959; 12: 590-595.
10.1002/1097-0142(195905/06)12:3<590::AID-CNCR2820120318>3.0.CO;2-N
CAS PubMed Web of Science® Google Scholar
48Weitz J, Kienle P, Lacroix J, Willeke F, Benner A, Lehnert T, et al. Dissemination of tumor cells in patients undergoing surgery for colorectal cancer. Clin Cancer Res 1998; 4: 343-348.
CAS PubMed Web of Science® Google Scholar
49Rosenberg R, Gertler R, Friederichs J, Fuehrer K, Dahm M, Phelps R, et al. Comparison of two density gradient centrifugation systems for the enrichment of disseminated tumor cells in blood. Cytometry 2002; 49: 150-158.
10.1002/cyto.10161
CAS PubMed Web of Science® Google Scholar
50Naume B, Borgen E, Tossvik S, Pavlak N, Oates D, Nesland JM. Detection of isolated tumor cells in peripheral blood and in BM: evaluation of a new enrichment method. Cytotherapy 2004; 6: 244-252.
10.1080/14653240410006086
CAS PubMed Web of Science® Google Scholar
51Di Carlo D. Inertial microfluidics. Lab Chip 2009; 9: 3038-3046.
10.1039/b912547g
CAS PubMed Web of Science® Google Scholar
52Martel JM, Toner M. Inertial focusing in microfluidics. Annu Rev Biomed Eng 2014; 16: 371-396.
10.1146/annurev-bioeng-121813-120704
CAS PubMed Web of Science® Google Scholar
53Warkiani ME, Guan G, Luan KB, Lee WC, Bhagat AA, Chaudhuri PK, et al. Slanted spiral microfluidics for the ultra-fast, label-free isolation of circulating tumor cells. Lab Chip 2014; 14: 128-137.
10.1039/C3LC50617G
CAS PubMed Web of Science® Google Scholar
54Becker FF, Wang XB, Huang Y, Pethig R, Vykoukal J, Gascoyne PR. Separation of human breast cancer cells from blood by differential dielectric affinity. Proc Natl Acad Sci U S A 1995; 92: 860-864.
10.1073/pnas.92.3.860
CAS PubMed Web of Science® Google Scholar
55Abonnenc M, Manaresi N, Borgatti M, Medoro G, Fabbri E, Romani A, et al. Programmable interactions of functionalized single bioparticles in a dielectrophoresis-based microarray chip. Anal Chem 2013; 85: 8219-8224.
10.1021/ac401296m
CAS PubMed Web of Science® Google Scholar
56Han Y, Gu Y, Zhang AC, Lo YH. Review: imaging technologies for flow cytometry. Lab Chip 2016; 16: 4639-4647.
10.1039/C6LC01063F
CAS PubMed Web of Science® Google Scholar
57Liu Z, Guo W, Zhang D, Pang Y, Shi J, Wan S, et al. Circulating tumor cell detection in hepatocellular carcinoma based on karyoplasmic ratios using imaging flow cytometry. Sci Rep 2016; 6: 39808.
10.1038/srep39808
CAS PubMed Web of Science® Google Scholar
58Ogle LF, Orr JG, Willoughby CE, Hutton C, McPherson S, Plummer R, et al. Imagestream detection and characterisation of circulating tumour cells—a liquid biopsy for hepatocellular carcinoma? J Hepatol 2016; 65: 305-313.
10.1016/j.jhep.2016.04.014
CAS PubMed Web of Science® Google Scholar
59Galanzha EI, Zharov VP. Circulating tumor cell detection and capture by photoacoustic flow cytometry in vivo and ex vivo. Cancers (Basel) 2013; 5: 1691-1738.
10.3390/cancers5041691
PubMed Google Scholar
60Alix-Panabieres C, Pantel K. Liquid biopsy in cancer patients: advances in capturing viable CTCs for functional studies using the EPISPOT assay. Expert Rev Mol Diagn 2015; 15: 1411-1417.
10.1586/14737159.2015.1091729
CAS PubMed Web of Science® Google Scholar
61Sun YF, Xu Y, Yang XR, Guo W, Zhang X, Qiu SJ, et al. Circulating stem cell-like epithelial cell adhesion molecule-positive tumor cells indicate poor prognosis of hepatocellular carcinoma after curative resection. Hepatology 2013; 57: 1458-1468.
10.1002/hep.26151
CAS PubMed Web of Science® Google Scholar
62Schulze K, Gasch C, Staufer K, Nashan B, Lohse AW, Pantel K, et al. Presence of EpCAM-positive circulating tumor cells as biomarker for systemic disease strongly correlates to survival in patients with hepatocellular carcinoma. Int J Cancer 2013; 133: 2165-2171.
10.1002/ijc.28230
CAS PubMed Web of Science® Google Scholar
63Kelley RK, Magbanua MJ, Butler TM, Collisson EA, Hwang J, Sidiropoulos N, et al. Circulating tumor cells in hepatocellular carcinoma: a pilot study of detection, enumeration, and next-generation sequencing in cases and controls. BMC Cancer 2015; 15: 206.
10.1186/s12885-015-1195-z
PubMed Web of Science® Google Scholar
64Shen J, Wang WS, Zhu XL, Ni CF. High epithelial cell adhesion molecule-positive circulating tumor cell count predicts poor survival of patients with unresectable hepatocellular carcinoma treated with transcatheter arterial chemoembolization. J Vasc Interv Radiol 2018; 29: 1678-1684.
10.1016/j.jvir.2018.07.030
PubMed Web of Science® Google Scholar
65von Felden J, Schulze K, Krech T, Ewald F, Nashan B, Pantel K, et al. Circulating tumor cells as liquid biomarker for high HCC recurrence risk after curative liver resection. Oncotarget 2017; 8: 89978-89987.
10.18632/oncotarget.21208
PubMed Google Scholar
66Yu JJ, Xiao W, Dong SL, Liang HF, Zhang ZW, Zhang BX, et al. Effect of surgical liver resection on circulating tumor cells in patients with hepatocellular carcinoma. BMC Cancer 2018; 18: 835.
10.1186/s12885-018-4744-4
PubMed Web of Science® Google Scholar
67Guo W, Yang XR, Sun YF, Shen MN, Ma XL, Wu J, et al. Clinical significance of EpCAM mRNA-positive circulating tumor cells in hepatocellular carcinoma by an optimized negative enrichment and qRT-PCR-based platform. Clin Cancer Res 2014; 20: 4794-4805.
10.1158/1078-0432.CCR-14-0251
CAS PubMed Web of Science® Google Scholar
68Wang S, Zhang C, Wang G, Cheng B, Wang Y, Chen F, et al. Aptamer-mediated transparent-biocompatible nanostructured surfaces for hepotocellular circulating tumor cells enrichment. Theranostics 2016; 6: 1877-1886.
10.7150/thno.15284
CAS PubMed Web of Science® Google Scholar
69Zhou Y, Wang B, Wu J, Zhang C, Zhou Y, Yang X, et al. Association of preoperative EpCAM circulating tumor cells and peripheral Treg cell levels with early recurrence of hepatocellular carcinoma following radical hepatic resection. BMC Cancer 2016; 16: 506.
10.1186/s12885-016-2526-4
PubMed Web of Science® Google Scholar
70Went PT, Lugli A, Meier S, Bundi M, Mirlacher M, Sauter G, et al. Frequent EpCam protein expression in human carcinomas. Hum Pathol 2004; 35: 122-128.
10.1016/j.humpath.2003.08.026
CAS PubMed Web of Science® Google Scholar
71Xu W, Cao L, Chen L, Li J, Zhang XF, Qian HH, et al. Isolation of circulating tumor cells in patients with hepatocellular carcinoma using a novel cell separation strategy. Clin Cancer Res 2011; 17: 3783-3793.
10.1158/1078-0432.CCR-10-0498
PubMed Web of Science® Google Scholar
72Li YM, Xu SC, Li J, Han KQ, Pi HF, Zheng L, et al. Epithelial-mesenchymal transition markers expressed in circulating tumor cells in hepatocellular carcinoma patients with different stages of disease. Cell Death Dis 2013; 4:e831.
10.1038/cddis.2013.347
CAS PubMed Web of Science® Google Scholar
73Li J, Chen L, Zhang X, Zhang Y, Liu H, Sun B, et al. Detection of circulating tumor cells in hepatocellular carcinoma using antibodies against asialoglycoprotein receptor, carbamoyl phosphate synthetase 1 and pan-cytokeratin. PLoS One 2014; 9:e96185.
10.1371/journal.pone.0096185
PubMed Web of Science® Google Scholar
74Mu H, Lin KX, Zhao H, Xing S, Li C, Liu F, et al. Identification of biomarkers for hepatocellular carcinoma by semiquantitative immunocytochemistry. World J Gastroenterol 2014; 20: 5826-5838.
10.3748/wjg.v20.i19.5826
CAS PubMed Web of Science® Google Scholar
75Liu HY, Qian HH, Zhang XF, Li J, Yang X, Sun B, et al. Improved method increases sensitivity for circulating hepatocellular carcinoma cells. World J Gastroenterol 2015; 21: 2918-2925.
10.3748/wjg.v21.i10.2918
PubMed Web of Science® Google Scholar
76Zhang Y, Zhang X, Zhang J, Sun B, Zheng L, Li J, et al. Microfluidic chip for isolation of viable circulating tumor cells of hepatocellular carcinoma for their culture and drug sensitivity assay. Cancer Biol Ther 2016; 17: 1177-1187.
10.1080/15384047.2016.1235665
CAS PubMed Web of Science® Google Scholar
77Pang Y, Wang C, Xiao R, Sun Z. Dual-selective and dual-enhanced SERS nanoprobes strategy for circulating hepatocellular carcinoma cells detection. Chemistry 2018; 24: 7060-7067.
10.1002/chem.201801133
CAS PubMed Web of Science® Google Scholar
78Court CM, Hou S, Winograd P, Segel NH, Li QW, Zhu Y, et al. A novel multimarker assay for the phenotypic profiling of circulating tumor cells in hepatocellular carcinoma. Liver Transpl 2018; 24: 946-960.
10.1002/lt.25062
PubMed Web of Science® Google Scholar
79Vona G, Estepa L, Beroud C, Damotte D, Capron F, Nalpas B, et al. Impact of cytomorphological detection of circulating tumor cells in patients with liver cancer. Hepatology 2004; 39: 792-797.
10.1002/hep.20091
CAS PubMed Web of Science® Google Scholar
80Morris KL, Tugwood JD, Khoja L, Lancashire M, Sloane R, Burt D, et al. Circulating biomarkers in hepatocellular carcinoma. Cancer Chemother Pharmacol 2014; 74: 323-332.
10.1007/s00280-014-2508-7
CAS PubMed Web of Science® Google Scholar
81Shi J, Li Y, Liang S, Zeng J, Liu G, Mu F, et al. Circulating tumour cells as biomarkers for evaluating cryosurgery on unresectable hepatocellular carcinoma. Oncol Rep 2016; 36: 1845-1851.
10.3892/or.2016.5050
CAS PubMed Web of Science® Google Scholar
82Li J, Shi L, Zhang X, Sun B, Yang Y, Ge N, et al. pERK/pAkt phenotyping in circulating tumor cells as a biomarker for sorafenib efficacy in patients with advanced hepatocellular carcinoma. Oncotarget 2016; 7: 2646-2659.
10.18632/oncotarget.6104
PubMed Google Scholar
83Winograd P, Hou S, Court CM, Sadeghi S, Finn RS, DiPardo B, et al. Evaluation of hepatocellular carcinoma circulating tumor cells expressing programmed death-ligand 1. HPB 2018; 20: S2-S3.
10.1016/j.hpb.2018.02.004
Google Scholar
84Kalinich M, Bhan I, Kwan TT, Miyamoto DT, Javaid S, LiCausi JA, et al. An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma. Proc Natl Acad Sci U S A 2017; 114: 1123-1128.
10.1073/pnas.1617032114
CAS PubMed Web of Science® Google Scholar
85Wang Z, Luo L, Cheng Y, He G, Peng B, Gao Y, et al. Correlation between postoperative early recurrence of hepatocellular carcinoma and mesenchymal circulating tumor cells in peripheral blood. J Gastrointest Surg 2018; 22: 633-639.
10.1007/s11605-017-3619-3
PubMed Web of Science® Google Scholar
86Chen J, Cao SW, Cai Z, Zheng L, Wang Q. Epithelial-mesenchymal transition phenotypes of circulating tumor cells correlate with the clinical stages and cancer metastasis in hepatocellular carcinoma patients. Cancer Biomark 2017; 20: 487-498.
10.3233/CBM-170315
CAS PubMed Web of Science® Google Scholar
87Qi LN, Xiang BD, Wu FX, Ye JZ, Zhong JH, Wang YY, et al. Circulating tumor cells undergoing EMT provide a metric for diagnosis and prognosis of patients with hepatocellular carcinoma. Cancer Res 2018; 78: 4731-4744.
10.1158/0008-5472.CAN-17-2459
CAS PubMed Web of Science® Google Scholar
88Ou H, Huang Y, Xiang L, Chen Z, Fang Y, Lin Y, et al. Circulating tumor cell phenotype indicates poor survival and recurrence after surgery for hepatocellular carcinoma. Dig Dis Sci 2018; 63: 2373-2380.
10.1007/s10620-018-5124-2
CAS PubMed Web of Science® Google Scholar
89Yin LC, Luo ZC, Gao YX, Li Y, Peng Q, Gao Y. Twist expression in circulating hepatocellular carcinoma cells predicts metastasis and prognoses. Biomed Res Int 2018; 2018: 3789613.
10.1155/2018/3789613
PubMed Web of Science® Google Scholar
90Ye X, Li G, Han C, Han Q, Shang L, Su H, et al. Circulating tumor cells as a potential biomarker for postoperative clinical outcome in HBV-related hepatocellular carcinoma. Cancer Manag Res 2018; 10: 5639-5647.
10.2147/CMAR.S175489
CAS PubMed Web of Science® Google Scholar
91Cheng Y, Luo L, Zhang J, Zhou M, Tang Y, He G, et al. Diagnostic value of different phenotype circulating tumor cells in hepatocellular carcinoma. J Gastrointest Surg 2019; 23: 2354-2361.
10.1007/s11605-018-04067-y
PubMed Web of Science® Google Scholar
92D'Avola D, Villacorta-Martin C, Martins-Filho SN, Craig A, Labgaa I, von Felden J, et al. High-density single cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma. Sci Rep 2018; 8: 11570.
10.1038/s41598-018-30047-y
PubMed Web of Science® Google Scholar
93Sun YF, Guo W, Xu Y, Shi YH, Gong ZJ, Ji Y, et al. Circulating tumor cells from different vascular sites exhibit spatial heterogeneity in epithelial and mesenchymal composition and distinct clinical significance in hepatocellular carcinoma. Clin Cancer Res 2018; 24: 547-559.
10.1158/1078-0432.CCR-17-1063
CAS PubMed Web of Science® Google Scholar
94Wang L, Li Y, Xu J, Zhang A, Wang X, Tang R, et al. Quantified postsurgical small cell size CTCs and EpCAM(+) circulating tumor stem cells with cytogenetic abnormalities in hepatocellular carcinoma patients determine cancer relapse. Cancer Lett 2018; 412: 99-107.
10.1016/j.canlet.2017.10.004
CAS PubMed Web of Science® Google Scholar
95Li J, Han X, Yu X, Xu Z, Yang G, Liu B, et al. Clinical applications of liquid biopsy as prognostic and predictive biomarkers in hepatocellular carcinoma: circulating tumor cells and circulating tumor DNA. J Exp Clin Cancer Res 2018; 37: 213.
10.1186/s13046-018-0893-1
PubMed Web of Science® Google Scholar

Author names in bold designate shared co-first authorship.

Citing Literature

Volume73, Issue1

January 2021

Pages 422-436

This article also appears in:

Hepatology Reviews

Detection of Circulating Tumor Cells and Their Implications as a Biomarker for Diagnosis, Prognostication, and Therapeutic Monitoring in Hepatocellular Carcinoma