Editorial Open Access
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Aug 28, 2015; 7(18): 2133-2135
Published online Aug 28, 2015. doi: 10.4254/wjh.v7.i18.2133
Optimal surveillance program for hepatocellular carcinoma - getting ready, but not yet
Grace Lai-Hung Wong
Grace Lai-Hung Wong, Department of Medicine and Therapeutics, 9/F Prince of Wales Hospital, the Chinese University of Hong Kong, Hong Kong, China
Grace Lai-Hung Wong, Institute of Digestive Disease, the Chinese University of Hong Kong, Hong Kong, China
Grace Lai-Hung Wong, State Key Laboratory of Digestive Disease, the Chinese University of Hong Kong, Hong Kong, China
Author contributions: Wong GLH was responsible for the conception, writing, review and revision of the manuscript.
Conflict-of-interest statement: Grace Lai-Hung Wong has served as an advisory committee member for Otsuka and Gilead. She has also served as a speaker for Abbvie, Bristol-Myers Squibb, Echosens, Furui, Gilead and Otsuka.
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: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Grace Lai-Hung Wong, MD, Department of Medicine and Therapeutics, 9/F Prince of Wales Hospital, the Chinese University of Hong Kong, 30-32 Ngan Shing Street, Shatin, Hong Kong, China. wonglaihung@cuhk.edu.hk
Telephone: +852-26323538 Fax: +852-26373852
Received: December 29, 2014
Peer-review started: December 30, 2014
First decision: January 20, 2015
Revised: June 29, 2015
Accepted: August 10, 2015
Article in press: August 11, 2015
Published online: August 28, 2015

Abstract

Hepatocellular carcinoma (HCC) secondary to chronic viral hepatitis is a major health problem in Asian-Pacific regions due to the endemics of chronic hepatitis B and C virus infection. HCC surveillance has been recommended to patients who are at risk to develop HCC. Unfortunately, a significant proportion of patients still died in long run due to tumor recurrence. The key components of an optimal surveillance program include an accurate tumor biomarker and optimal surveillance interval. Serum alpha-fetoprotein (AFP), despite of being the most widely used biomarker for HCC surveillance, it was criticized as neither sensitive nor specific. Other HCC biomarkers, including lectin-reactive AFP (AFP-L3), des-gamma carboxyprothrombin, are still under investigations. Recent study showed cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing to be accurate with both sensitivity and specificity close to 90% in detecting HCC in a case-control study. Concerning the optimal surveillance interval, we believe one size does not fit all patients. Accurate risk prediction to assist prognostication with well-validated HCC risk scores would be useful to decide the need for HCC surveillance. These key components of an optimal HCC surveillance program should be further validated at a surveillance setting.

Key Words: Antiviral therapy, Biomarkers, Hepatocellular carcinoma, Hepatocellular carcinoma risk scores, Liver stiffness measure, Surveillance program

Core tip: The key components of an optimal surveillance program include an accurate tumor biomarker and optimal surveillance interval for hepatocellular carcinoma (HCC). Cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing are two promising genomic markers of HCC. Risk prediction by HCC risk scores may assist prognostication and to decide the optimal surveillance interval.



INTRODUCTION

Hepatocellular carcinoma (HCC) secondary to chronic viral hepatitis is a major health problem in Asian-Pacific regions due to the endemics of chronic hepatitis B and C virus infection[1]. Antiviral therapy reduces the risk but does not eliminate HCC[2]. Therefore cancer surveillance remains indispensable to patients who remain at high risk despite antiviral therapy, namely those with cirrhosis[3].

BENEFITS OF HCC SURVEILLANCE

It has been recommended to offer HCC surveillance to patients who are at risk to develop HCC for almost a decade[4]. The surveillance program recommended at that time was composed of the 6-mo trans-abdominal ultrasonography and serum alpha-fetoprotein (AFP) testing. HCC surveillance improves prognosis of patients by identifying tumors of smaller sizes, fewer numbers of tumors, and longer overall survival[5]. Unfortunately, nearly 40% of patients still died in 5 years even they had received regular HCC surveillance[5]. This implies the current HCC surveillance is still far from perfect.

THE PERFECT HCC BIOMARKER - DOES IT EXIST?

The key components of the perfect surveillance program include an accurate tumor biomarker and optimal surveillance interval. Serum AFP is the most extensively applied biomarker for HCC surveillance[3]. However, its low sensitivity (20% to 65%) and specificity (50% to 94%) in discovering early HCC has resulted in the latest American guidelines abandoning AFP but using ultrasonography alone as the single surveillance tool[6]. Despite it has been recently demonstrated the high specificity of AFP in patients receiving antiviral therapy[7], it is well known that this commonly adopted tumor marker remains suboptimal.

There have been a handful of HCC biomarkers, e.g., lectin-reactive AFP (AFP-L3), des-gamma carboxyprothrombin (DCP), under investigations[8]. Despite some of the biomarkers appeared promising initially, subsequent studies could not always reproduce the similar results[9]. Hence the latest European guidelines still commented that accurate tumor biomarkers for early detection of HCC needed to be developed. Such biomarkers (i.e., AFP, AFP-L3 and DCP) are indeed suboptimal for routine clinical practice[3].

The dysregulated signaling pathways in HCC have been under intensive study for both diagnostic and therapeutic targets[10]. Nonetheless, HCC often involves heterogeneous pathogenesis such that multiple genes are involved (Table 1). This made using a single or a few genomic markers as HCC biomarker infeasible. Recently, cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing has been found to be accurate with both sensitivity and specificity close to 90% in detecting HCC in a case-control study[11]. The remaining issue of such genomic sequencing is that it is rather costly (approximately United States $10000 per assay). Apart from further validation of these novel genomic biomarkers in a surveillance setting, further optimization of the assay to reduce the cost yet maintaining the accuracy would be essential to make it applicable and accessible to more patients.

Table 1 Major cancer genes involved in the pathogenesis of hepatocellular carcinoma.
GeneTypePathways
MYCOncogeneProliferation control
EGFOncogeneEGFR signaling (mitogenic signaling)
TGFAOncogeneEGFR signaling (mitogenic signaling)
APCTumor suppressor geneWnt-signaling
PTENTumor suppressor genePI3K/Akt/mTOR signaling
AKTOncogenePI3K/Akt/mTOR signaling
HGFOncogeneGrowth factor
METOncogeneGrowth factor receptor
PDGFROncogeneGrowth factor receptor
RASOncogeneRas/MAPK signaling
P53Tumor suppressor geneStress response, cell cycle inhibition
E2F1OncogeneCell cycle
CCND1OncogeneCell cycle
TelomeraseOncogeneCell senescence
OPTIMAL SURVEILLANCE INTERVAL - DOES ONE SIZE FITS ALL?

There would be much economic implication in many low-to-middle economic countries if all patients at risk of HCC received antiviral therapy together with HCC surveillance. Therefore an accurate risk prediction would be able to help prognostication, deciding on the need for antiviral therapy as well as HCC surveillance. Several well-established risk factors for HBV-related HCC include advanced age, male gender, high viral load, cirrhosis. These factors are the core components of three well-validated HCC risk scores: CU-HCC[12], GAG-HCC[13] and REACH-B scores[14]. These risk scores were confirmed to be accurate in forecasting HCC up to 10 years in patients with chronic hepatitis B (CHB) who were mostly treatment-naïve.

Their validity and applicability have been recently illustrated in a large cohort of patients receiving antiviral treatment entecavir[15]. A reducion in risk scores after antiviral therapy renders to a lower risk of HCC[15]. CU-HCC score was further optimized with liver stiffness measure (LSM) by transient elastography[16]. This new LSM-HCC score excludes future HCC with high negative predictive value (99.4%-100%) at 5 years[16]. All these observations support to apply these HCC risk scores in CHB patients. Levels of care and intensities of HCC surveillance accordingly to the risk profile of patients should be offered accordingly. Patients at intermediate or high risk of HCC should receive regular HCC surveillance, despite the use of antiviral treatment[5,17].

CONCLUSION

The key components of a perfect HCC surveillance program are getting ready. They should be further validated at a surveillance setting in order to understand how exactly they can benefit our patients. Data on the cost-effectiveness of such a perfect HCC surveillance program would be useful to our policy maker. The days of HCC becoming a mostly curable disease are getting closer and closer.

Footnotes

P- Reviewer: Doganay L, He ST S- Editor: Gong XM L- Editor: A E- Editor: Liu SQ

References
1.  Chan HL, Sung JJ. Hepatocellular carcinoma and hepatitis B virus. Semin Liver Dis. 2006;26:153-161.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 165]  [Cited by in F6Publishing: 165]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
2.  Wong GL, Chan HL, Mak CW, Lee SK, Ip ZM, Lam AT, Iu HW, Leung JM, Lai JW, Lo AO. Entecavir treatment reduces hepatic events and deaths in chronic hepatitis B patients with liver cirrhosis. Hepatology. 2013;58:1537-1547.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 295]  [Cited by in F6Publishing: 282]  [Article Influence: 36.9]  [Reference Citation Analysis (0)]
3.  European Association For The Study Of The Liver; European Organisation For Research And Treatment Of Cancer. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012;56:908-943.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3642]  [Cited by in F6Publishing: 3455]  [Article Influence: 404.7]  [Reference Citation Analysis (1)]
4.  Bruix J, Sherman M; Practice Guidelines Committee, American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma. Hepatology. 2005;42:1208-1236.  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Wong GL, Wong VW, Tan GM, Ip KI, Lai WK, Li YW, Mak MS, Lai PB, Sung JJ, Chan HL. Surveillance programme for hepatocellular carcinoma improves the survival of patients with chronic viral hepatitis. Liver Int. 2008;28:79-87.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 90]  [Cited by in F6Publishing: 83]  [Article Influence: 6.4]  [Reference Citation Analysis (0)]
6.  Bruix J, Sherman M; American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53:1020-1022.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5422]  [Cited by in F6Publishing: 5076]  [Article Influence: 542.2]  [Reference Citation Analysis (0)]
7.  Wong GL, Chan HL, Tse YK, Chan HY, Tse CH, Lo AO, Wong VW. On-treatment alpha-fetoprotein is a specific tumor marker for hepatocellular carcinoma in patients with chronic hepatitis B receiving entecavir. Hepatology. 2014;59:986-995.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 83]  [Cited by in F6Publishing: 82]  [Article Influence: 11.9]  [Reference Citation Analysis (0)]
8.  Lok AS, Sterling RK, Everhart JE, Wright EC, Hoefs JC, Di Bisceglie AM, Morgan TR, Kim HY, Lee WM, Bonkovsky HL. Des-gamma-carboxy prothrombin and alpha-fetoprotein as biomarkers for the early detection of hepatocellular carcinoma. Gastroenterology. 2010;138:493-502.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 338]  [Cited by in F6Publishing: 302]  [Article Influence: 28.2]  [Reference Citation Analysis (0)]
9.  Bertino G, Ardiri A, Malaguarnera M, Malaguarnera G, Bertino N, Calvagno GS. Hepatocellualar carcinoma serum markers. Semin Oncol. 2012;39:410-433.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 103]  [Cited by in F6Publishing: 101]  [Article Influence: 11.4]  [Reference Citation Analysis (0)]
10.  Zender L, Villanueva A, Tovar V, Sia D, Chiang DY, Llovet JM. Cancer gene discovery in hepatocellular carcinoma. J Hepatol. 2010;52:921-929.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 113]  [Article Influence: 10.9]  [Reference Citation Analysis (0)]
11.  Chan KC, Jiang P, Chan CW, Sun K, Wong J, Hui EP, Chan SL, Chan WC, Hui DS, Ng SS. Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing. Proc Natl Acad Sci USA. 2013;110:18761-18768.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 229]  [Cited by in F6Publishing: 203]  [Article Influence: 28.6]  [Reference Citation Analysis (0)]
12.  Wong VW, Chan SL, Mo F, Chan TC, Loong HH, Wong GL, Lui YY, Chan AT, Sung JJ, Yeo W. Clinical scoring system to predict hepatocellular carcinoma in chronic hepatitis B carriers. J Clin Oncol. 2010;28:1660-1665.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 290]  [Cited by in F6Publishing: 106]  [Article Influence: 26.4]  [Reference Citation Analysis (0)]
13.  Yuen MF, Tanaka Y, Fong DY, Fung J, Wong DK, Yuen JC, But DY, Chan AO, Wong BC, Mizokami M. Independent risk factors and predictive score for the development of hepatocellular carcinoma in chronic hepatitis B. J Hepatol. 2009;50:80-88.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 352]  [Cited by in F6Publishing: 351]  [Article Influence: 27.1]  [Reference Citation Analysis (0)]
14.  Yang HI, Yuen MF, Chan HL, Han KH, Chen PJ, Kim DY, Ahn SH, Chen CJ, Wong VW, Seto WK; REACH-B Working Group. Risk estimation for hepatocellular carcinoma in chronic hepatitis B (REACH-B): development and validation of a predictive score. Lancet Oncol. 2011;12:568-574.  [PubMed]  [DOI]  [Cited in This Article: ]
15.  Wong GL, Chan HL, Chan HY, Tse PC, Tse YK, Mak CW, Lee SK, Ip ZM, Lam AT, Iu HW. Accuracy of risk scores for patients with chronic hepatitis B receiving entecavir treatment. Gastroenterology. 2013;144:933-944.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 120]  [Article Influence: 15.0]  [Reference Citation Analysis (0)]
16.  Wong GL, Chan HL, Wong CK, Leung C, Chan CY, Ho PP, Chung VC, Chan ZC, Tse YK, Chim AM. Liver stiffness-based optimization of hepatocellular carcinoma risk score in patients with chronic hepatitis B. J Hepatol. 2014;60:339-345.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 155]  [Cited by in F6Publishing: 130]  [Article Influence: 19.4]  [Reference Citation Analysis (0)]
17.  Wong GL, Wong VW. Risk prediction of hepatitis B virus-related hepatocellular carcinoma in the era of antiviral therapy. World J Gastroenterol. 2013;19:6515-6522.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 30]  [Cited by in F6Publishing: 26]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]