Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 21, 2017; 23(31): 5650-5668
Published online Aug 21, 2017. doi: 10.3748/wjg.v23.i31.5650
Liquid biopsy in patients with hepatocellular carcinoma: Circulating tumor cells and cell-free nucleic acids
Wataru Okajima, Shuhei Komatsu, Daisuke Ichikawa, Mahito Miyamae, Takuma Ohashi, Taisuke Imamura, Jun Kiuchi, Keiji Nishibeppu, Tomohiro Arita, Hirotaka Konishi, Atsushi Shiozaki, Ryo Morimura, Hisashi Ikoma, Kazuma Okamoto, Eigo Otsuji
Wataru Okajima, Shuhei Komatsu, Daisuke Ichikawa, Mahito Miyamae, Takuma Ohashi, Taisuke Imamura, Jun Kiuchi, Keiji Nishibeppu, Tomohiro Arita, Hirotaka Konishi, Atsushi Shiozaki, Ryo Morimura, Hisashi Ikoma, Kazuma Okamoto, Eigo Otsuji, Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan
Author contributions: Okajima W and Komatsu S contributed equally to this work; Okajima W and Komatsu S wrote the manuscript; Ichikawa D and Otsuji E helped to draft the manuscript; Miyamae M, Ohashi T, Imamura T, Kiuchi J, Nishibeppu K, Arita T, Konishi H, Morimura R, Shiozaki A, Ikoma H and Okamoto K collected the literature.
Conflict-of-interest statement: The authors have no conflicts of interest to report.
Data sharing statement: Technical appendix and study data are available from the corresponding author at (Shuhei Komatsu) under the permission of Shuhei Komatsu. Participants gave informed consent for data sharing. No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Correspondence to: Shuhei Komatsu, MD, PhD, Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachihirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan.
Telephone: +81-75-2515527 Fax: +81-75-2515522
Received: January 28, 2017
Peer-review started: February 8, 2017
First decision: March 3, 2017
Revised: April 14, 2017
Accepted: July 4, 2017
Article in press: July 4, 2017
Published online: August 21, 2017


Hepatocellular carcinoma (HCC), with its high incidence and mortality rate, is one of the most common malignant tumors. Despite recent development of a diagnostic and treatment method, the prognosis of HCC remains poor. Therefore, to provide optimal treatment for each patient with HCC, more precise and effective biomarkers are urgently needed which could facilitate a more detailed individualized decision-making during HCC treatment, including the following; risk assessment, early cancer detection, prediction of treatment or prognostic outcome. In the blood of cancer patients, accumulating evidence about circulating tumor cells and cell-free nucleic acids has suggested their potent clinical utilities as novel biomarker. This concept, so-called “liquid biopsy” is widely known as an alternative approach to cancer tissue biopsy. This method might facilitate a more sensitive diagnosis and better decision-making by obtaining genetic and epigenetic aberrations that are closely associated with cancer initiation and progression. In this article, we review recent developments based on the available literature on both circulating tumor cells and cell-free nucleic acids in cancer patients, especially focusing on Hepatocellular carcinoma.

Key Words: Hepatocellular carcinoma, Biomarker, Liquid biopsy, Circulating tumor cells, Cell-free nucleic acids

Core tip: Accumulating evidence about circulating tumor cells and cell-free nucleic acids in the blood of cancer patients has suggested their potent clinical utilities as novel biomarker. This concept, so-called “liquid biopsy” is widely known as an alternative approach to cancer tissue biopsy. This method might facilitate a more sensitive diagnosis and better decision-making by obtaining genetic and epigenetic aberrations that are closely associated with cancer initiation and progression. In this article, we review recent developments based on the available literature on both circulating tumor cells and cell-free nucleic acids in cancer patients, especially focusing on Hepatocellular carcinoma.

Citation: Okajima W, Komatsu S, Ichikawa D, Miyamae M, Ohashi T, Imamura T, Kiuchi J, Nishibeppu K, Arita T, Konishi H, Shiozaki A, Morimura R, Ikoma H, Okamoto K, Otsuji E. Liquid biopsy in patients with hepatocellular carcinoma: Circulating tumor cells and cell-free nucleic acids. World J Gastroenterol 2017; 23(31): 5650-5668

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide, but it ranks as the second most common cause of cancer-related death worldwide[1]. Despite recent development of a diagnostic and treatment method, the prognosis of HCC remains poor. Even in major advanced economies, the mortality rates have been increasing. Although HCC is a typical viral infection-related malignancy derived from chronic hepatitis B and C[2,3], HCC has also been strongly associated with lifestyle. Excessive alcohol consumption, obesity, and type 2 diabetes are strongly associated with the carcinogenesis and development of HCC[4-7]. Both the proportion and number of HCC patients with non-viral etiologies have been increasing on a global scale. Therefore, defining the target population should be added to screening as the most important clinical issues.

Early screening of patients for HCC has been reported to confer a survival benefit[8,9]. Patients who are identified early have multiple treatment options leading to improved outcomes. However, in clinical settings, only approximately 30% to 40% of patients with HCC can get effective treatment at the right time[10], and few molecules have been used as clinical biomarkers for HCC. Alpha-fetoprotein (AFP), AFP lectin fraction (AFP-L3), and des-γ-carboxy prothrombin (DCP, also known as proteins induced through vitamin K deficiency or antagonist-II, PIVKA-II) have been used as conventional serum tumor markers. However, these markers often show false-positive results, and lack sufficient sensitivity and specificity[11-13]. Therefore, to provide optimal treatment for each patient with HCC, more precise and effective biomarkers are urgently needed. Accumulating evidence of liquid biopsy might facilitate a more sensitive diagnosis and individualized decision-making in the duration of treatment of HCC.

In various cancers, many studies have demonstrated a large number of genetic and epigenetic aberrations contribute to carcinogenesis and their clinical utility[14-18]. Traditionally, these tumor-linked alterations has been provided from tissue samples of HCC patients. However, conventional procedures for tissue sampling from HCC patients is not always be conducted due to their clinical difficulties such as anatomical reasons, invasive nature, and/or the patient’s poor hepatic status[19,20]. Because of such backgrounds, conventional procedures have some problems: (1) Results from a single biopsy could provide considerably restricted information; and (2) they could not reflect current cancer status, such as treatment sensitivity and therapeutic efficiency. Detecting circulating tumor cells (CTCs) and/or circulating cell-free nucleic acids (cfNAs) in the blood of cancer patients could provide us a so-called “liquid biopsy”, which would realize repeated samplings and reflecting the characteristics and dynamics of tumor[21-24].

To date, many study groups have revealed the possibility of CTCs and cfNAs in the blood, as blood-based biomarkers, for several types of cancers[21-24]. These novel biomarkers are thought to have great potential and could provide more detailed individualized decision-making during HCC treatment, including the following; risk assessment, early cancer detection, prediction of treatment or prognostic outcome. In this article, based on the available literature, we review the histological backgrounds, recent developments and prospects for the future of liquid biopsy, particularly focusing on Hepatocellular carcinoma.


CTCs are generally recognized as the “seeds” of tumors, which are shed into peripheral blood from a tumor in situ and eventually establish metastatic tumors in other organs[20]. Therefore, theoretically, circulating tumor cells (CTCs) are useful markers for early diagnosis. In 1869, Ashworth initially demonstrated the presence of CTCs[25] in the blood of breast cancer patient. This patients has widespread breast cancer, and the cells similar to those in the primary breast cancer had been detected in her blood. Afterwards, to validate Ashworth’s remarks, many researches have challenged to investigate peripheral blood of various cancer patients to identify CTCs.

However, the effort has been hampered by some difficulties. The problem is that the earlier the stage is, the less the cells are. Namely, the cell tends to be proportional to tumor volume. Moreover, CTCs have estimated infrequencies of approximately 1-10 CTCs in a background of millions of blood cells in patients with metastatic diseases[26]. In addition, less than 0.01% of CTCs introduced into the circulation survive to produce metastases. Furthermore, in phenotype, as well as genotype, CTCs are considered to be quite heterogeneous[27-29]. As CTCs are thought to be derived from the primary cancer or metastases, they are rarely present in patients with non-neoplastic disorders healthy person[30]. Therefore, the performance such as sensitivity and specificity of detection technique should be achieved to a proper level, precise detection of CTCs has been a major problem in this field for researchers.


In recent years, various CTC isolation and enrichment technologies have emerged, their approaches are generally categorized into two methods.

Physical methods

Physical methods mainly depend on the physical properties of CTCs, such as density, size, migratory capacity, deformability and electric charge[31]. Most CTCs originate from epithelial tumors are thought to larger than other blood cells, several filtration-based techniques has been developed[32,33]. However, substantial difference has been demonstrated in cell size not only in an individual cancer patient but also in different cancer patients[34-36]. Thus, novel techniques adopting multiple filters have been studied to solve these issues and improve accuracy of enrichment of CTCs[37,38]. These micro device could isolate cancer cells using their physical properties such as size continuously and deformability. For example, Mohamed et al[37] designed a micro-machined device, which had arrays of four successively narrower channels, were able to fractionate cancer cells without interference from the blood cells. Those novel techniques could have substantial possibilities, their utility should be validated in the future.

Biological methods

Another approach is biological methods, which mainly rely on antigen-antibody binding and antibodies against tumor-specific biomarkers including epithelial cell adhesion molecule (EpCAM), human epidermal growth factor receptor2 (Her2), and prostate-specific antigen (PSA) that are typically used in CTCs purification[39]. Currently, Cell-SearchTM (Veridex LLC, NJ, United States) is the most commonly used CTC platform. In this platform, immunomagnetic beads coated with EpCAM antibodies capture CTCs, followed by immunostaining with two positive markers, which are cytokeratins 8/18/19 for cytoplasmic epithelium and 4′,6′-diamidino-2-phenylindole hydrochloride for nucleic acids, and a negative marker, leukocyte-specific CD45. Its utility as a clinical indicator has been shown in the patients with metastatic breast, prostate, and colon cancers[40-45]. Therefore, this system has been the only CTC platform to be approved by the United States Food and Drug Administration. However, it could not capture CTCs that have increased the malignant potential, caused by the acquisition of an epithelial-mesenchymal transition (EMT). Concerning the detection and isolation capability and the clinical utility of CTCs, many challenges remain. To overcome its insufficient capability and accuracy, advanced technologies have emerged. “CTC-chip” is the representative technology without being influenced by the heterogeneity of them. It is a unique microfluidic platform, capable of efficient and selective separation of viable CTCs from peripheral whole blood samples, mediated by the interaction of target CTCs with antibody (EpCAM)-coated microposts[46]. Most recently, CTC-Chip was reported to detect CTCs with high accuracy by using tumor-specific markers, such as human epidermal growth factor (HER2) in breast cancer or prostate-specific antigen (PSA) in prostate cancer, in addition to epithelial markers[46,47]. Another unique approach was reported by Saucedo-Zeni et al[48] They captured and enriched CTCs from medical Seldinger guidewire, which were inserted into cubital veins. Despite these advances, the methodology of isolation and enrichment of CTCs has been in the process of development.

The identification process is generally conducted after the isolation and enrichment process. To identify genetic aberrations and other biological characteristics of CTCs, several methodologies, such as immunocytochemistry and molecular techniques, have been used. Conventionally, immunostaining using 4′,6′-diamidino-2-phenylindole hydrochloride as a nuclear stain, CK as an epithelial marker, and CD45 as a hematopoietic marker has been commonly adopted[49]. In various molecular approaches, quantitative reverse transcription-polymerase chain reaction (RT-PCR) has been widely used to identify the molecular characteristics of CKs, CEA, and other markers[50].


In the past decades, CTCs in HCC patients have been intensively studied. Table 1 is the summary of previously demonstrated candidates. As described in the last paragraph, these approaches are generally categorized into two methods: physical and biological methods.

Table 1 Circulating tumor cells in hepatocellular carcinoma.
Ref.HCC patientsEthnicityBackground liver statusPatient backgroundControlsMethodologyPositive rate
Matsumura, et al[51], 199988JapanHCV: 85%, HBV: 6%Pre and post (TAE or PEI)NART-PCR (AFP)63.0%
Mou et al[56], 200230ChinaHBV: 100%Pre resection25 (HV: 25)RT-PCR (MAGE1/3)43.3%
LC: 100%
Witzigmann et al[55], 200285GermanyNAPre, during, post (Resection: 24, LT: 10, TACE: 13, No treatment: 38)116 ( OLT: 50, HD: 39, HV: 27)RT-PCR (AFP)28.0%
Vona et al[31], 200444FranceLC: 89%Pre/post resection: 22107 (HV: 38, HD: 69)ISET52.2%
Unresectable: 22
Jeng et al[53], 200481ChinaHBV: 77%, HCV: 38%Pre and post resection50 (HV: 30, HD: 20)RT-PCR (AFP)23.4%
LC: 69%
Cillo et al[52], 200450ItalyHCV: 50%,HBV: 12%Pre (Resection: 17, LT: 9, PT: 17)50 (HD: 6, OT: 44)RT-PCR (AFP)40.0%
HCV and HBV: 6%
Alcohol: 10%No treatment: 7
LC: 84%
Kong et al[59], 2009343South KoreaHBV: 78%, HCV: 10%Pre (Resection: 12, TACE: 224, RFA: 44, Chemotherapy: 12, Radiotherapy: 12, No treatment: 39)NART-PCR (AFP)
Alcohol: 6%(hTERT)59.5%
LC: 52%14.0%
Fan et al[69], 201182ChinaHBV: 80%Pre and post resectionNACellSearchTM68.3%
Xu et al[70], 201185ChinaHBV: 84%, HCV: 7%Pre Resection: 6371 (HD: 37, HV: 20, OT: 14)CellSearchTM81.0%
HBV and HCV: 5%Clinical Diagnosis: 22
nonB, nonC: 4%
Liu et al[67], 201360ChinaHBV: 93%Pre resectionNAFlow cytometry50.0%
LC: 93%
Yao et al[57], 2013123ChinaHBV: 72%NA276 (HV: 30, HD: 196, OT: 50)RT-PCR (GPC-3)70.77%
LC: 93%
Sun et al[73], 2013123ChinaHBV: 75%Pre/post resectionNACellSearchTM66.6%
LC: 76%
Schulze et al[72], 201359GermanyAlcohol: 38%Pre (resection or systemic therapy)19 (HD: 19)CellSearchTM30.5%
HBV: 17%, HCV: 13%
LC: 89%
Li et al[71], 201360ChinaHBV: 92%, HCV: 3%NA30 (HD: 10, HV: 10, OT: 10)CellSearchTM76.6%
nonB, nonC: 7%
LC: 88.7%
Bahnassy et al[68], 201470EgyptHCV: 100%NA63 (HD: 30, HV: 33)Flow cytometry (CK19, CD90, 133)73.0%, 49.8%, 69.5%
RT-PCR (Telomerase, MAGE1/3)55.7%, 60.0%, 62.9%
Li et al[76], 201427ChinaNANA61 (HD: 34, HV: 15, OT: 12)CellSearchTM88.9%
Mu et al[78], 201462ChinaHBV: 95.2%NA22 (HD: 7, HV: 15)CellSearchTM48.3%
Fang et al[74], 201442ChinaLC: 55%Pre and post TACE20 (HV: 10, HD: 10)CellSearchTM52.3%
Morris et al[77], 201452United KingdomAlcohol: 38%,No treatmentNACellSearchTM28%
HBV: 8%ISET100%
Diabetes: 12%
Guo et al[75], 2014299ChinaHBV: 90%Pre/post (Resection: 157, TACE: 76, RFA: 66)120 (HV: 71, HD: 25, BT: 24)CellSearchTM42.6%
LC: 90%
Choi et al[58], 201581South KoreaHBV: 80%, HCV: 11%Pre and post (Resection: 64, LT: 17)16 (LHD: 16)RT-PCR (K19, CD44)22.2%
Alcohol: 4%
LC: 59%
Kelley et al[19], 201520Caucasian: 55%,HBV: 25%, HCV: 45%NA10 (HD: 10)CellSearchTM40.0%
Asian: 35%,HBV and HCV: 10%
American: 10%Alcohol: 5%
(African-5%)NAFLD: 10%
Wang et al[79], 201642ChinaHBV: 81%, HCV: 2%NANACTC-Chip59.5%
nonB, nonC: 17%
Zhang et al[207], 201636ChinaNANANACTC-Chip100%
Physical methods

Vona et al[31] first reported the isolation by size of epithelial tumor cell (ISET) method to detect CTCs in HCC patients. By cytomorphologic analysis, they demonstrated that the spontaneous circulation of CTCs in peripheral blood reflects tumor progression and tumor spread in patients with HCC. Compared with expensive and cumbersome molecular techniques, ISET is a unique, inexpensive methodology. In this method, we can apply the cytopathological diagnosis of tumor cells, which were widely used in clinical oncology, as peripheral blood samples without any special equipment[32]. However, ISET device is still hard to release CTCs from the membrane. This may limit the application of downstream genetic analysis.

Biological methods

The presence and clinical utility of CTCs in HCC was first reported by Matsumura et al[51] using RT-PCR. They demonstrated the following. (1) the presence of alpha-fetoprotein (AFP) messenger RNA (mRNA) in peripheral blood could be a marker of circulating HCC cells; (2) the status of AFP mRNA in blood were investigated at entry, extrahepatic metastasis developed more frequently among the AFP mRNA-positive patients than among the AFP mRNA-negative patients; and (3) after treatment, AFP mRNA was investigated, and cumulative metastasis-free survival and overall survival were significantly better in patients whose AFP mRNA became negative after treatment than in patients with persistently positive AFP mRNA. In summary, they demonstrated that the presence or absence of AFP mRNA in blood (CTCs’ positivity) could be a predictor of outcome in patients with HCC.

Following this study, the clinical utility of peripheral AFP mRNA was validated by other groups[52,53]; however, the significance as prognostic marker has not been adequately confirmed[54,55]. Thus, other tumor-specific molecules in the bloodstream, such as MAGE-1, MAGE3[56], glypican-3 (GPC-3)[57], keratin 19 (K19), cluster of differentiation 44 (CD44)[58], and hTERT[59] mRNA, have been investigated for markers of circulating HCC cells. For example, MAGE gene transcripts have been considered as HCC-specific markers[60]. Mou et al[56] demonstrated that detection of MAGE transcripts in blood with a follow-up survey could predict the prognosis and monitor the response to therapy. GPC-3 is a membrane-anchored heparin sulfate proteoglycan, known to be a reliable biomarker for HCC[61]. Yao et al[57] demonstrated that GPC-3 mRNA abnormality is useful as clinical biomarkers from early cancer detection to evaluating metastasis. Furthermore, K19 and CD44 have been shown to be cancer stem cell markers in HCC[62-65], their significance of prognostic factor in peripheral blood were also demonstrated by Choi et al[58]. However, HCC associated genes were not always candidates for the markers of CTCs. Although serum human telomerase reverse transcriptase protein (hTERT) mRNA expression has been suggested as a potential candidate diagnostic marker for HCC[66], the significance as prognostic marker has not been adequately confirmed[59].

Liu et al[67] and Bahnassy et al[68] used flow cytometry to analyze intercellular adhesion molecule 1 (ICAM-1) expression, cytokeratin 19, CD133, and CD90 in HCC blood samples and demonstrated their prognostic value. Among various techniques, EpCAM-based Cell-SearchTM is currently the most widely used CTC platform[19,69-78]. Using this method, Sun et al[73] collected blood samples from 123 HCC patients who underwent curative resection and suggested that EpCAM+ CTCs could be useful for real-time parameter for monitoring treatment response and be also used for therapeutic target in HCC recurrence. Guo et al[75] collected blood samples from 299 HCC patients with various kinds of treatment and 120 control subjects, and demonstrated that this method could be useful in early decision-making to tailor the most effective antitumor strategies. Most recently, Wang et al[79] suggested that novel CTC-Chip platform might be a new method for a simple and efficient detection of CTCs in HCC patients. They created biocompatible and transparent Hydroxyapatite/chitosan nanofilm coated by aptamer for carbohydrate sialyl Lewis Xto and demonstrated that it could be useful as prognostic marker.

Overall, the usefulness of CTCs as biomarkers in HCC might be practically guaranteed. However, several challenges that must be overcome remain. Firstly, it is possible that etiological differences of patients and controls, such as background liver disease, haptic status, and race, could be responsible for the heterogeneity of the results. Secondly, a novel methodology for the detection should be provided for solving the problem of the rarity and heterogeneity of CTCs. Thirdly, the techniques and results of past research have greatly differed. Consequently, a large-scale validation using patients with homogeneous backgrounds and development of a unified methodology are required for future applications.


cfNAs in peripheral blood of cancer patients, comprised of DNA, mRNA, and miRNA, are known to come from apoptotic and necrotic cells or are released from living eukaryotic cells[21]. The first discovery of cfNAs in human peripheral blood was in 1948 by Mandel and Metais[80]. However, their work did not gain attention for a long time due to insufficient understanding of that new concept, completely different from conventional ones. Cell free DNAs were first discovered by Leon et al[81] in the serum of cancer patients in 1977. They also suggested it could be a clinical indicator of treatment outcome, showing decreased cfDNA levels in response to radiotherapy. Since then, numerous alterations in cfNAs have been demonstrated in various cancer patients. Cell free DNA with cancer characteristics was first discovered by Vasioukhin et al[82] in 1989. Tumours can shed DNA into the circulation. Their discovery indicated the possibility that cancers could release DNA into the blood of the cancer patients. This hypothesis was validated in the plasma of cancer patients: KRAS mutation in the pancreatic cancer patients[83] and NRAS mutation in the leukemia patients[84].

The state of RNA in the blood is easy-to degrade by the presence of endogenous ribonuclease, however, cell-free RNA has been demonstrated in blood. The presence of cfRNA was first discovered in 1999 from the serum of patients with nasopharyngeal carcinoma[85] and malignant melanoma[86]. Afterwards, many study group have demonstrated the presence and utility of mRNA in the blood of various cancer patients[87-89].

In 2008, Mitchell et al[90] first demonstrated that circulating microRNAs (miRNAs) in patients with solid cancers could be a promising biomarker. Since then, circulating noncoding RNAs have been intensively studied. Among them, miRNAs has especially gained attention. Other noncoding RNAs, such as small nucleolar RNA (snoRNA), small nuclear RNA (snRNA), piwi-interacting RNA (piRNA), and long noncoding RNA (lncRNA), have been also expected to be biomarkers, however, there are few studies of these. In the future, further research will probably be necessary.


Circulating cfDNA, a naturally occurring biological material, is generally considered to be a potential novel biomarker for a long time[91]. These abnormalities can be divided into two changes, such as quantitative changes and qualitative changes. Quantitative changes appear as higher concentrations of total circulating cfDNA, qualitative changes are gene mutations, DNA copy number variations, tumor-specific methylation, microsatellite instability (MSI) and loss of heterozygosity. Thus, analysis of circulating cell-free DNA in the plasma/serum can be mainly categorized into two strategies. One of these strategies is to measure the quantity of cell-free DNA in circulation. The other strategy is to detect tumor-specific genetic aberrations. Most researchers have adopted studies the later one as liquid biopsy[92-95].

Table 2 is the summary of previously demonstrated candidates. Some researchers have adopted a quantitative analysis[96-102]. Huang et al[100] and Chen et al[99] demonstrated that plasma DNA or serum DNA levels were significantly higher in HCC patients and they were associated with a poorer prognosis; however, it has not become a mainstream of cfDNA studies because the elevated levels of cfDNA were not specific for HCC. Although single nucleotide mutation[103] and copy number variation[95,104] were representative changes for the qualitative strategy, the “methylation pattern” has been the most intensively investigated. Initially, the presence and the clinical utility of circulating cell-free DNA in HCC was reported by Wong et al[105]. Using methylation-specific PCR, they analyzed p15 methylation patterns in three kinds of samples such as plasma, serum, and tissues surgically resected from HCC patients and showed the following: (1) in the blood samples, methylated p15 sequences were detected in 25% of patients with p15 methylation in the tissue; (2) nearly all patients showing p15 and p16 methylation in the tissue had detectable methylation abnormalities in their blood samples; and (3) clinical metastasis or recurrence were developed in the patients with p15/p16 methylation. In summary, these epigenetic markers could serve as diagnostic and prognostic markers. As previous studies revealed that changes of DNA methylation exited in various malignancies and played an important role in carcinogenesis[106,107], following this study, many researchers investigated the cfDNA methylation profile in HCC patients[108-124]. For example, Iyer et al[115] compared the tumor methylation profile for tumor suppressor genes, such as APC, FHIT, p15, p16, and E-cadherin, and in tumor tissues and plasma from the same HCC patients, and demonstrated that concordance between the two types of specimens was statistically significant for all five genes. It suggested that plasma DNA reliably predicts methylation events in tissue DNA; therefore, plasma DNA could be used for methylation studies. Huang et al[116] analyzed the plasma methylation status of four genes (APC, GSTP1, RASSF1A, and SFRP1) and showed the sufficient diagnostic value of cfDNAs. Although the area under the receiver-operation characteristic curve (AUC-ROC) for an individual gene was not adequate, the combination analysis of these four genes indicated higher AUC (0.933) in discriminating HCC from the normal control. Furthermore, they demonstrated methylated RASSF1A in plasma could be an independent prognostic factor for overall survival.

Table 2 Circulating cell-free DNA in hepatocellular carcinoma.
RefHCC patientsSampleEthnicityBackground liverControlscfDNA abnormalitiesTarget
Wong et al[105], 200025Plasma/serumHong-KongHBV: 88%55 (HD: 35, HV: 20)MethylationP16
15Buffy coatHCV: 2%35 (HD: 15, HV: 20)MS-PCR
Wong et al[108], 200329/22Plasma/serumHong KongNA50 (HD and HV)MethylationP16INK4A
29Buffy coat35 (HD: 15, HV: 20)MS-PCR
Chu et al[109], 200446SerumKoreaHBV: 65%23 (HD: 23)MethylationP16INK4A
Yeo et al[110], 200540PlasmaHong-KongHBV: 83%10 (HV: 10)MethylationRASSF1A
Iizuka et al[96], 200652SerumJapanHCV: 100%46 (HD: 30, HV: 16)Quantitative analysisGSTP1
Real-time PCR
Ren et al[97], 200679PlasmaChinaHBV: 85% LC: 86%40 (HD: 20, HV: 20)Quantitative analysisNA
Real-time PCR
Allelic imbalance analysisD8S258 and D8S264
Zhang et al[112], 200750SerumTaiwanHBV: 22%50MethylationP15, P16
HCV: 16%HV: 50MS-PCR
Tan et al[111], 20078SerumSingaporeNA72 (OT: 62, HV: 10)MethylationRUNX3
Chan et al[113], 200885SerumHong-KongHBV: 92%135 (HD: 63, HV: 72)MethylationRASSFIA
Chang et al[114], 200819PlasmaChinaHBV: 89%17 (LC: 17)MethylationAPC, GSTP1, RASSF1A, P16, E-cadherin
Iyer et al[115], 201028PlasmaEgyptHCV: 79%NAMethylationAPC, FHIT, P15, P16 and E-cadherin
Yang et al[98], 201160PlasmaChinaNA50 (HD: 21, HV: 29)Quantitative analysishTERT
Szymañska et al[103], 201114PlasmaChinaMostly HBVNASingle nucleotide mutationR249S (TP53 mutation)
Iizuka et al[117], 2011220SerumJapanHCV: 100%202 (HD: 202)MethylationSPINT2, SRD5A2
Huang et al[116], 201172PlasmaChinaHBV: 85%37 (HD: 37)MethylationAPC, GSTP1, RASSF1A, and SFRP1
Huang et al[100], 201272PlasmaChinaHBV: 85%115 (HD: 74, HV: 41)Quantitative analysisNA
Real-time PCR
Chen et al[99], 201280SerumChinaHBV: 100%130 (HD: 80, HV: 50)Quantitative analysisNA
Real-time PCR
Mohamed et al[118], 201240SerumEgyptHCV: 100%60 (HD: 40, HV: 20)MethylationRASSF1A
Real-time PCR
Chen et al[101], 201339SerumChinaHBV: 79%45 (HV: 45)Quantitative analysisNA
Real-time PCR
Piciocchi et al[102], 201366PlasmaItalyHCV: 51%76 (HD: 76)Quantitative analysishTERT
Alcohol: 27%Real-time PCR
Chan et al[95], 20134PlasmaChinaNA20 (HD: 4, HV: 16)Copy number variationNA
Sun et al[119], 201343SerumChinaHBV: 86%50 (HD: 24, HV: 26)MethylationTFPI2
Zhang et al[120], 201337SerumChinaHBV: 100%33 (HD: 33)MethylationDBX2, THY1
Bead Chip, Hot-start PCR, Pyrosequencing
Huang et al[122], 201466SerumUnited StatesHCV: 100%43 (HD: 43)MethylationINK4A
HCV and HBV: 6%Pyrosequencing, MS-PCR
Han et al[121], 2014160SerumChinaHBV: 22%133 (HD: 88, HV: 45)MethylationTRG5
Ji et al[123], 2014121SerumChinaHBV: 83%68 (HD: 37, HV: 31)MethylationMT1M
Kuo et al[124], 201440PlasmaTaiwanNA34MethylationHOXA9
Jiang et al[104], 201590PlasmaHong-KongNA135 (HD: 103, HV: 32)Copy number variationNA

MS-PCR has been widely used for methylation research, because it provides a rapid and simple method with high sensitivity and accuracy. More recently, droplet digital PCR[125-128] and genome-wide high-throughput sequencing[128,129] has been reported as a further accurately detection tools for rare and multiple types of mutations in circulating DNA. These novel approaches has revealed that genetic aberrations in cell-free DNA gained from the bloodstream of cancer patients and drug resistance were correlating[130-132]. It is required that the potent clinical utility of cell-free DNA, such as risk assessment, early cancer detection, prediction of drug resistance and prognostic outcome, could be demonstrated in the patients with HCC.


Although RNA is fragile, easily degraded by ribonuclease (RNase) and the concentration of RNase in plasma/serum is known to be elevated in cancer patients[133], many researchers have successfully demonstrated the stable presence of cell-free mRNAs in the bloodstream of cancer patients. Recently, novel mechanistic insights have been gained that these RNAs can be incorporated into other surrounding such as exosomes, microvesicles and multivesicles, which considered to be sufficiently protected from the degradation by RNases and released from the cellular surface to the blood[134]. There are many studies of cell-free mRNA in the blood of patients with various solid cancers, and most of them targeted the mRNAs in plasma/serum whose up-regulation were previously validated in cancer tissues[87-89,135-137]. Regarding HCC, several study groups investigate mRNA in peripheral blood mononuclear cells as a marker for the detection of CTCs[51-53,55-57,59]; however, the quantity of cell-free mRNAs in plasma/serum is exceedingly small. Further studies of cell-free mRNA in patients with HCC may provide new knowledge to the research field of liquid biopsy.


Although as much as 80% of genomic DNA had already demonstrated to be transcribed into RNAs[138], the Human Genome Project revealed that the open reading frames of protein genes is only 2% of the 3.2 billion bases[139,140]. It can be paraphrased as there are only a very few human genomic DNAs that actually code proteins. It is gradually reveled that various noncoding RNAs (ncRNAs) play crucial roles in several cellular processes in the transition from DNA to protein. Therefore, the expression patterns of ncRNAs could be promising molecular biomarkers in novel diagnostic techniques[141].

For circulating ncRNAs, particular attention has been paid to miRNAs. MiRNAs are small non-coding RNAs that play crucial roles in various cellular processes. A single miRNA could regulate the expression of genes as follows: A guide strand of mature miRNA is taken into the RNA-induced silencing complex and then hybridizes to the 3′-untranslated region of their target mRNAs to translate or degrade these mRNAs. Thus, miRNAs have occupied important place in all cellular processes, some alterations in miRNA expression has come to draw a lot of attention in the association with various disease. Particularly, some researchers have demonstrated that specific miRNAs could act like oncogenes or tumor suppressors. Several studies in recent years on this subject have also shown that some extracellular miRNAs were generated from both cell lysis and active secretion[21,142,143]. Furthermore, several researchers have detected miRNAs in the plasma/serum in a remarkably stable form. In this regard, Kosaka et al[143] proved that secretory mechanisms and intercellular transfer of microRNAs in living cells. A group of miRNAs is packaged into small membrane vesicles called exosomes and released through a ceramide-dependent secretory machinery. Furthermore, miRNAs are remarkably stable form in plasma as they bind to certain proteins, such as argonaute 2 and high-density lipoproteins[144]. Therefore, all circulating miRNAs, regardless of whether they are taken into certain protein complexes and/or cell-derived microvesicles, has been thought to be sufficiently protected against the degradation by RNases in the bloodstream. These findings of recent years have pioneered a novel research field in cancer science.

In 2008, Mitchell et al[90] first reported that circulating miRNAs could be useful for stable blood-based markers for cancer detection. Since then, circulating miRNAs in the blood of cancer patients have been intensively studied to validate their potential as biomarkers. Table 3 is the summary of previously demonstrated candidates. In 2010, Li et al[145] first demonstrated that serum miRNAs expression profile could be useful as novel noninvasive biomarkers for the distinction between HBV infection and HBV-positive HCC. Since then, several research groups have reported the potential utility of miRNAs circulating in plasma/serum in clinical applications. Concerning circulating miRNAs in HCC, more than 70 miRNAs have been thought to be useful for biomarkers[145-195]. Some miRNAs had been used in combination with AFP, conventional serum tumor marker, to improve diagnostic accuracy[158,171,177,188,191,195]. Moreover, one miRNA could influence various mRNAs, more and more miRNAs and related mRNAs continues to be reported by numerous research groups. However, they are not always superimposable due to the large variances in the results. Thus, to realize more accurate diagnosing, some researchers have tried to use miRNAs in combination. Zhou et al[150] using the unique panel consisting of 7 mRNAs (miR-122, -192, -21, -223, -26a, -27a, and -801), based on the expression in plasma, could differentiate HCC from healthy (AUC = 0.941), chronic hepatitis B (AUC = 0.842), and cirrhosis (AUC = 0.884). More recently, Tan et al[166] reported that a combination of eight miRNAs could provide high diagnostic accuracy for HCC.

Table 3 Circulating cell-free microRNA in hepatocellular carcinoma.
miRExpressionSampleHCC patientsEthnicityBackground liverControlsValueRef.
miR-1UpSerum195GermanyHCV: 45%, Alcohol: 33%, HBV: 17%54 (HD: 54)PKöberle et al[155] 2013
miR-10bUpBlood27ChinaAlcohol: 23%81 (HD: 81)DJiang et al[175] 2015
miR-15bUpSerum153ChinaHBV: 88%59 (HD: 29, HV: 39)DLiu et al[152] 2012
miR-15b-5pDownPlasma37ChinaNA60 (HD: 29, HV: 31)DChen et al[170] 2015
miR-16DownSerum105United StatesHCV: 64%, HBV: 20%178 (HD: 107, HV: 7)DQu et al[148] 2011
90ChinaNA60 (HV: 60)DGe et al[161] 2014
40EgyptHCV: 100%60 (HD: 40, HV: 20)DEl-Abd et al[174] 2015
miR-17-5pUpSerum136ChinaNANAPZheng et al[159] 2013
8TurkeyHCV: 100%84 (HD: 56, HV: 28)DOksuz et al[178] 2015
miR-18aUpSerum101ChinaHBV: 100%90 (HD: 30, HV: 60)DLi et al[151] 2012
UpSerum20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
miR-19aDownSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-21UpPlasma457ChinaHBV:100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
136JapanHCV:68%, HBV: 23%80 (HD: 30, HV: 50)D, PTomimaru et al[153] 2012
Serum101ChinaHBV: 75%137 (HD: 48, HV: 89)DXu et al[149] 2011
136ChinaHBV: 95%NAPLiu et al[164] 2014
97ChinaHBV: 62%30 (HV: 30)D, PWang et al[180] 2015
23EgyptHCV: 87%, HBV: 13%17 (HD: 17)DAmr et al[186] 2016
DownSerum70ChinaHBV: 100%72 (HD 48, HV: 24)DQi et al[147] 2011
90ChinaNA60 (HV: 60)D, PGe et al[161] 2014
52ChinaHBV: 63%, HCV: 4%85 (HD: 42, HV: 43)DZhuang et al[195] 2016
miR-22DownSerum192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
miR-24-3pUpSerum84ChinaHBV: 100%77 (HD: 31, HV: 46)D, PMeng et al[165] 2014
miR-26aDownPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
Serum52ChinaHBV: 63%, HCV: 4%85 (HD42, HV: 43)DZhuang et al[195] 2016
miR-26a-5pDownSerum261ChinaHBV: 100%406 (HD 233, HV: 173)DTan et al[166] 2014
miR-27aDownPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
miR-29bDownSerum192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
miR-30cDownSerum242ChinaHCV: 63%NAPLiu et al[176] 2015
miR-30c-5pDownSerum8TurkeyHCV: 100%84 (HD: 56, HV: 28)DOksuz et al[178] 2015
miR-34aUpSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-92a-3pUpPlasma20TurkeyHBV: 100%74 (HD: 46, HV: 28)DGiray et al[162] 2014
miR-96UpSerum104ChinaHBV: 100%400 (HD: 280, HV: 120)DChen et al[171] 2015
miR-101UpSerum25ChinaHBV: 100%20 (HV: 20)DFu et al[154] 2013
DownSerum67ChinaHBV: 100%170 (HD: 140, HV: 3,)DXie et al[167] 2014
20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
52ChinaHBV: 63%, HCV: 4%85 (HD: 42, HV: 43)DZhuang et al[195] 2016
miR-106bUpBlood27ChinaAlcohol: 23%81 (HD: 31, HV: 50,)DJiang et al[175] 2015
miR-122UpSerum70ChinaHBV: 100%72 (HD: 48, HV: 24,)DQi et al[147] 2011
101ChinaHBV: 75%137 (HD: 48, HV: 89,)DXu et al[149] 2011
195GermanyHCV: 45%, Alcohol: 33%, HBV: 17%54 (HD: 54)PKöberle et al[155] 2013
30EgyptHCV: 100%70 (HD: 60, HV: 10)DEl-Garem et al[160] 2014
136ChinaHBV: 95%NAPLiu et al[164] 2014
192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
DownPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
Serum20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
122ChinaNANAPXu et al[181] 2015
miR-122aDownSerum85ChinaHBV: 88%HV (HV: 85)DLuo et al[156] 2013
miR-122-5pUpPlasma20TurkeyHBV: 100%74 (HD: 46, HV: 28)DGiray et al[162] 2014
Plasma120South KoreaHBV: 100%NAPCho et al[172] 2015
Serum120ChinaHBV: 100%DN: 30DHung et al[189] 2016
DownSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-125bDownPlasma64ChinaHBV: 100%178 (HD: 122, HV: 56)DChen et al[187] 2016
miR-125b-5pUpPlasma20TurkeyHBV: 100%74 (HD: 46, HV: 28)DGiray et al[162] 2014
miR-126UpPlasma59IndiaHBV: 100%38 (HD: 20, HV: 18)DGhosh et al[188] 2016
DownSerum23EgyptHCV: 100%55 (HD: 55)DKhairy et al[190] 2016
miR-128-2UpSerum222ChinaHBV: 87%NAPZhuang et al[184] 2015
miR-129DownSerum23EgyptHCV: 100%55 (HD: 55)DKhairy et al[190] 2016
miR-130aUpSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-130bUpSerum153ChinaHBV: 88%59 (HD: 29, HV: 30)DLiu et al[152] 2012
miR-139DownPlasma31ChinaNA31 (HD: 31)D, PLi et al[163] 2014
miR-141-3pUpSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-143UpSerum95ChinaNA245 (HD: 118, HV: 127)DZhang et al[168] 2014
miR-143-3pUpPlasma59IndiaHBV: 100%38 (HD: 20, HV: 18)DGhosh et al[188] 2016
miR-146aUpSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-150DownSerum120ChinaHBV: 100%230 (HD: 110, HV: 120)D, PYu et al[183] 2015
miR-155DownSerum23EgyptHCV: 100%55 (HD: 55)DKhairy et al[190] 2016
miR-181aDownBlood27ChinaAlcohol: 23%81 (HD: 31, HV: 50)DJiang et al[75] 2015
miR-181bUpSerum192EgyptHCV: 100%192 (HD: 192)DZekr et al[194] 2016
miR-182UpSerum103ChinaNA135 (HD: 95, HV: 40)D, PChen et al[169] 2015
miR-192UpPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
Serum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-192-5pDownSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-195DownSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
miR-199aDownSerum105United StatesHCV: 64%, HBV: 20%178 (HD: 107, HV: 71)DQu et al[148] 2011
40EgyptHCV: 100%60 (HD: 40, HV: 20)D, PEl-Abd et al[174] 2015
78ChinaNA156 (HV: 156)DYin et al[182] 2015
23EgyptHCV: 87%, HBV: 13%17 (HD: 17)DAmr et al[186] 2016
miR-199a-3pDownSerum192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
miR-199a-5pDownSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-200aUpSerum136ChinaHBV: 95%NAPLiu et al[176] 2015
miR-203DownSerum23EgyptHCV: 100%55 (HD: 55)DKhairy et al[190] 2016
miR-203aDownSerum242ChinaHCV: 63%NAPLiu et al[176] 2015
miR-206UpSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-215UpSerum95ChinaNA245 (HD: 118, HV: 127)DZhang et al[168] 2014
miR-218DownSerum156ChinaHBV: 72%162 (HD: 98, HV: 64)D, PYang et al[193] 2016
miR-221UpSerum20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
DownSerum30EgyptHCV: 100%70 (HD: 60, HV: 10)DEl-Garem et al[174] 2014
miR-222UpSerum70ChinaHBV: 100%72 (HD: 48, HV: 24)DQi et al[147] 2011
20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
miR-223UpSerum70ChinaHBV: 100%72 (HD: 48, HV: 24)Qi et al[147] 2011
Serum101ChinaHBV: 75%137 (HD: 48, HV: 89)DXu et al[149] 2011
DownPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
Serum23EgyptHCV: 100%55 (HD: 55)DKhairy et al[190] 2016
miR-223-3pDownPlasma20TurkeyHBV: 100%74 (HD: 46, HV: 28)DGiray et al[162] 2014
Serum8TurkeyHCV: 100%84 (HD: 56, HV: 28)DOksuz et al[178] 2015
miR-224UpPlasma107JapanHCV: 41%, HBV: 18%, Alcohol: 15%102 (HD: 27, HV: 75)D, P, TOkajima et al[192] 2016
Serum20South KoreaHBV: 70%40 (HD: 40)DSohn et al[179] 2015
182ChinaHBV: 87%NAD, PZhuang et al[185] 2015
122ChinaHBV: 100%157 (HD: 135, HV: 22)DLin et al[191] 2016
miR-224-5pUpSerum136ChinaHBV: 95%NAPLiu et al[164] 2014
miR-296UpSerum112EgyptHCV: 100%167 (HD: 125, HV: 42)DMotawi et al[177] 2015
miR-302c-3pDownSerum8TurkeyHCV: 100%84 (HD: 56, HV: 28,)DOksuz et al[178] 2015
miR-331-3pUpSerum103ChinaNA135 (HD: 95, HV: 40)D, PChen et al[169] 2015
miR-335DownSerum125ChinaNA250 (HD: 125, HV: 125)D, PCui et al[173] 2015
miR-338-5pUpPlasma37ChinaNA60 (HD: 29, HV: 31)DChen et al[170] 2015
miR-375UpSerum120ChinaHBV: 100%393 (HD: 183, HV: 210)DLi et al[145] 2010,
Down78ChinaNA156 (HV: 156)DYin et al[182] 2015.
miR-433-3pUpSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
miR-483-5pUpSerum69United StatesHCV: 63%, HBV: 14%69 (HV: 69)DShen et al[157] 2013
112ChinaNA141 (HD: 56, HV: 85)DZhang et al[158] 2013
miR-500aUpSerum112ChinaNA141 (HD: 56, HV: 85)DZhang et al[158] 2013
miR-764UpPlasma37ChinaNA60 (HD: 29, HV: 31)DChen et al[170] 2015
miR-801UpPlasma457ChinaHBV: 100%477 (HD: 310, HV: 167)DZhou et al[150] 2011
miR-885-5pUpSerum46ChinaHBV: 72%105 (HD: 64, HV: 24, GC: 17)DGui et al[146] 2011
192EgyptHCV: 100%192 (HD: 192)DZekri et al[194] 2016
miR-1228-5pUpSerum261ChinaHBV: 100%406 (HD: 233, HV: 173)DTan et al[166] 2014
let-7bUpSerum120ChinaHBV: 100%30 (DN: 30)DHung et al[189] 2016
let-7fDownSerum90ChinaNA60 (HV: 60)D, PGe et al[161] 2014

In terms of diagnosis, it should fully consider that HCC is an extremely prominent cancer among high-risk group patients. Patients who are already infected with HBV and HCV, and/or liver cirrhosis are at risk of developing liver cancer; however, some candidate miRNAs could not discriminate HCC patients from patients with liver chronic hepatitis, or cirrhosis[146,147,149,160,162,179,187]. They were useful for detecting HCC from general population, but not suitable for further screening, narrowing down patients who already have some risks for HCC. Recently, Zhou et al[150], Okusuz et al[178], Lin et al[191], and Zekri et al[194] defined three subgroups of healthy volunteers, with patients with chronic hepatitis and cirrhosis as controls. Most recently, Motawi et al[177] and our group[192] set subgroups according to fibrosis stage. To demonstrate the clinical utility for diagnosis, it is necessary to select appropriate controls.

Accumulating evidence of circulating cell-free miRNAs made clear their clinical utility as prognostic biomarker as well as a marker for the detection of HCC[184,196-205]. In terms of the two types of curative treatment, Zheng et al[159] demonstrated that the level of serum miR-17-5p could serve as a novel prognostic marker for HCC patients who underwent surgical resection, and Cho et al[172] demonstrated that high plasma miR-122 expression was associated with poor overall survival in patients with HBV-related HCC who underwent radiofrequency ablation (RFA). In terms of the treatment for unresectable HCC, trans-arterial chemoembolization (TACE), Liu et al[164] demonstrated that miR-200a was the independent prognostic factor associated with survival.

Most recently, our group found that miR-224 may be an indicator of residual tumor in non-surgical treatment, such as percutaneous ablation therapy and/or TACE, although this was preliminary result because the number of cases was small[192]. Despite accumulating evidence, we should recognize that several challenges remain for clinical application. Regarding inter- and intra-individual variation, the kind of blood samples such as serum, plasma or all blood for better clinical application of miRNAs as a liquid-based biomarker, many issues should be addressed. Furthermore, it is necessary to build a consensus what molecule is suitable for clinical application.

Recent research has demonstrated that several noncoding RNAs regulate oncogenic and/or tumor-suppressive functions. PTEN[150,180], Stathmin1[150], RUNX3[152], Rho-kinase 2[164], Mcl-1[167], SOX9[167], p21/E2F5[175], FNDC3B[168], VEGF[177], TP53INP1[169], LIN28B[187], ADAM17[194], ISRE[194], CDKN1B/p27[194], CDKN1C/p57[194], TIMP3[194], HDAC4[194], and mTOR[194], have been demonstrated to have cancer-related functions, and validated as targets for specific miRNAs in the blood of patients with HCC[206]. The noncoding RNAs, such as lncRNA, snoRNA, snRNA, and piRNA, in the blood of patients with HCC remain unexplored. We hope further studies of circulating noncoding RNAs based on the knowledge of recent years in HCC will shed more light on this research field.


Blood-based molecular biomarkers, the most typical one of the so-called liquid biopsy, are promising as diagnostic, therapeutic and/or prognostic markers for HCC because researchers has got over their clinical difficulties such as anatomical reasons, invasive nature, and/or the patient’s poor hepatic status. Although the clinical utility of liquid biopsy in HCC has been practically guaranteed by many research groups, there remains large variance in the results. The lack of a standardized technical approach has contributed to the lack of consensus. The techniques adopted, patient’s hepatic status, sample type, storage conditions and target molecules have differed according to study groups. Thus, large-scale study, which is performed in a uniform methodology through all processes, is required. Another important reason is the etiological difference in each cohort. HCC is a marked regional clustering cancer, the background liver is different for each study group. For example, as indicated in each of the Tables, while all patients were infected with HBV in some reports from China and South Korea, all patients infected with HCV in other reports from Egypt. Their results were too biased by sample characteristics, it is desirable to be validated in another cohort before further clinical application.

The utility of the current serum biomarkers, such as AFP, AFP-L3, and proteins induced through vitamin K deficiency, and imaging modalities, such as ultrasonography, computed tomography, and gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced liver magnetic resonance imaging (GdEOB-DTPA-enhanced MRI) is far from satisfactory. What is now required is less invasive and repeatable methodology. Accumulating evidence of liquid biopsy might facilitate a more sensitive diagnosis and individualized decision-making in the duration of treatment of HCC. A challenge is how to achieve further development based on recent studies. Many issues should be addressed before these promising results can be translated into a real clinical settings.


Manuscript source: Invited manuscript

Specialty type: Gastroenterology and hepatology

Country of origin: Japan

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P- Reviewer: Lee HC, Yao DF, Lee HC S- Editor: Qi Y L- Editor: A E- Editor: Li D

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