Translational microarray systems for outcome prediction of hepatocellular carcinoma

Abstract

DNA microarray technology has revolutionized our understanding of the molecular basis of hepatocellular carcinoma (HCC), one of the most fatal human cancers with a high recurrence rate. Many researchers have used DNA microarray technology to reclassify HCC with respect to metastatic potential and to develop predictors for the outcome of HCC. However, developed predictors have reached the level only of small retrospective studies, and their current status is far from that required for clinical use. This is due to the lack of transparent data, the high cost and data instability associated with the high dimensionality of the technique, the infancy of bioinformatics, and the complicated nature of recurrent HCC. This comprehensive review summarizes: (i) class comparison studies to identify genes or pathways involved in HCC metastasis (ii) class discovery studies that have resulted in the identification of a new molecular subclass of HCC with respect to metastasis, and (iii) class prediction studies to develop multidimensional predictors for HCC outcome. We also discuss issues that need to be addressed so that the power of array-based predictors can be estimated prospectively in large independent cohorts of HCC patients. (Cancer Sci 2008; 99: 659-665) H epatocellular carcinoma (HCC) is one of the most fatal cancers in humans, with an estimated 564 000 new cases worldwide in 2000. HCC represents a major international health problem because its incidence is exponentially increasing in many countries.(1) Despite many advances in the treatment of HCC, the recurrence rate at 3 and 5 years after curative treatment exceeds 50% and 70%, respectively.(2,3) Therefore, it is crucial to better understand the mechanisms involved in HCC recurrence and to provide effective therapies based on accurate outcome prediction. Many clinical staging systems have been applied to HCC patients (4,5) ; however, there are limitations of these systems in the accurate prediction in individual patients. This problem has long frustrated hepatologists and pathologists. A robust predictive system for use in HCC patients is therefore necessary.High-dimensional array technology started a revolution in medical science upon the first publication of this technology in 1995.(6) This high-tech technology provides great promise with respect to genome-wide searches for predictive molecular markers and has resulted in enhanced characterization of individual tumors with regard to metastatic potential compared to that provided by traditional clinicopathologic methods and singlemolecule systems. (7)(8)(9)(10) In the field of HCC research, Lau et al.used this technology to compare gene expression profiles of HCC and non-HCC liver tissues. Since then, more than 300 HCC studies with use of DNA microarray technology, including many elegant works from Japan, (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23) have been published. Many researchers, (24)(25)(26)(27)(28)(29)(30)(31) have also developed array-based predictors for metastasis, recurrence, and outcome of HCC; ho...

Molecular signatures of noncancerous liver tissue can predict the risk for late recurrence of hepatocellular carcinoma

“…The predictive accuracy of predictors ranges from 73 to 97%. No association was observed between the predictive accuracy and background factors, such as the number of genes used in predictors or test samples, publication year, and the array type [22]. Budhu et al [21] used the noncancerous liver tissue specimens to predict the early recurrence of HCC.…”

“…In another study [23], late recurrence was simply defined as tumor recurrence occurring more than 2 years after surgery. However, HCC recurrence due to intrahepatic metastasis can appear even 3 years after surgery, and intrahepatic recurrence due to de novo HCC can appear within 1 year after surgery [22,32]. A follow-up period after surgery is very important to determine whether patients have the late recurrence of HCC.…”

“…The sample must be precisely labeled to obtain accurate predictors [22,29]. However, it has limitations from the standpoint of diagnostic accuracy; the definition of late recurrence is mostly based on clinicopathologic findings rather than on molecular or genetic findings.…”

Detection of metallothionein 1G as a methylated tumor suppressor gene in human hepatocellular carcinoma using a novel method of double combination array analysis

“…Lau et al reported on the first study of an expression array for HCC in 2000 (37). Subsequently, many studies were performed to discover novel candidates of tumor suppressor genes in HCC using expression array technology (38)(39)(40). Moreover, SNP chip array analysis, which now enables us to simultaneously detect a large number of DNA polymorphic loci in a simple way, was further developed for genotyping.…”

Integrative and Functional Genomics of HCC

“…Such prediction models for HCC metastasis are expected to impact clinical practice since an appropriate therapeutic regime can be applied to patients with high-risk of recurrence (Budhu et al 2005b). Accordingly, specific gene expression signatures in tumor and surrounding nontumor tissues have been identified, and prediction models have been developed to predict vascular invasion, early intrahepatic recurrence, and metastasis (Iizuka et al 2008;Budhu et al 2005a;Iizuka et al 2008).…”