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Molecular diagnosis and therapy of hepatocellular carcinoma (HCC): An emerging field for advanced technologies

Open AccessPublished:July 21, 2011DOI:https://doi.org/10.1016/j.jhep.2011.07.007
      Despite great progress in diagnosis and management of hepatocellular carcinoma (HCC), the exact biology of the tumor remains poorly understood overall limiting the patients’ outcome. Detailed analysis and characterization of the molecular mechanisms and subsequently individual prediction of corresponding prognostic traits would revolutionize both diagnosis and treatment of HCC and is the key goal of modern personalized medicine. Over the recent years systematic approaches for the analysis of whole tumor genomes and transcriptomes as well as epigenomes became affordable tools in translational research. This includes simultaneous analyses of thousands of molecular targets using microarray-based technologies as well as next-generation sequencing. Although currently diagnosis and classification of hepatocellular cancers still rely on histological examination of tumor sections, these technologies show great promise to advance the current knowledge of hepatocarcinogenesis, complement diagnostic classification in a setting of microarray-aided pathology, and rationalize the individual drug selection. This review aims to summarize recent progress of system biological approaches in hepatocarcinogenesis and outline potential areas for translational application in a clinical setting. Further, we give an update about known signaling pathways active in HCC, summarize the historical application of whole genomic approaches in liver cancer and indicate ongoing experimental research utilizing novel technologies in diagnosis and treatment of this deadly disease. This will also include the discussion and characterization of new molecular and cellular targets such as Cancer Stem Cells (CSCs).

      Keywords

      Introduction

      Hepatocellular carcinoma (HCC) ranks among the most common cancers worldwide and is the third leading cause of cancer death overall accounting for more than half a million yearly deaths [
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      ]. Although prevalence remains highest in Eastern Asia and Africa, liver cancer incidence steadily increased in the Western world as well as Japan over the last 30–50 years [
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      Hepatocellular carcinoma: epidemiology, surveillance, and diagnosis.
      ]. Notably, confounding factors, such as up-streaming immigration rates, have considerable influence on these numbers and presumably the incidences in USA and Europe already peaked and stabilized in the last years, reflecting the drop in hepatitis B infections and improved treatment modalities against in chronic hepatitis C, which constitutes the predominant risk factor in Western countries. Besides viral hepatitis, other chronic liver diseases due to alcohol, nonalcoholic fatty liver disease (NAFLD), and other metabolic disorders are the main risk factors for the development of HCC. Among these, metabolic syndrome and NAFLD is of particular interest in Western countries due to an alarming increase in prevalence and high numbers of HCCs without underlying cirrhosis [
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      Currently, accurate diagnosis of frank HCC is achieved by radiologic imaging techniques such as computer tomography and magnetic resonance imaging. In inconclusive cases, the gold standard still remains histology [
      • Bruix J.
      • Sherman M.
      Management of hepatocellular carcinoma: an update.
      ]. More difficult is the proper diagnosis of small HCC which frequently does not present with typical vascular patterns in imaging tests and acquisition of reliable histological specimens often requires repetitive biopsies and pathological interpretation is demanding. Therefore, one of the most challenging aspects in hepatology is the detection of premalignant lesions [
      • Park Y.N.
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      ].
      Curative therapeutic strategies for HCC involve surgical resection, radio-frequency ablation and liver transplantation [
      • Bruix J.
      • Sherman M.
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      ]. Due to late detection and advanced underlying liver diseases, these treatments are unavailable to the majority of the patients [
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      • Galle P.R.
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      ].
      HCC are highly resistant to conventional systemic therapies. Although promising novel therapies and targets are currently under evaluation (www.clinicaltrials.gov) the only systemic standard of care for patients with advanced HCC is sorafenib with a mean survival benefit of only 3 months [
      • Llovet J.M.
      • Ricci S.
      • Mazzaferro V.
      • Hilgard P.
      • Gane E.
      • Blanc J.F.
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      Therefore, rationalizing and combining targeted therapies according to genomic and epigenomic signatures of the corresponding tumors will be a key goal in translational oncology and might significantly improve the treatment of liver cancer.
      Over the last decade, a plethora of novel cutting edge technologies became available for cancer research. Microarray based-approaches enabled the affordable and systematic analysis of the whole cancer (epi-) genomes and transcriptomes. During the last 10 years, detailed catalogs of somatic mutations in different cancers were generated and accelerated the understanding of carcinogenesis [
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      Although the translation of systembiology into the actually clinical routine is still in its infancy and currently pathological examination of stained tissue sections or cytology remains the main approach for diagnosis and classification of tumors, the molecular analysis of tumors and, in case of the liver, the disrupted hepatic microenvironment [
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      Signaling pathways and key oncogenic molecules

      Despite the progress in surveillance and management of HCC, the detailed molecular pathophysiology remains poorly understood [
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      ]. Hepatocarcinogenesis is believed to be a complex and multi-step process involving the accumulation of both epigenetic and genetic events. In particular, understanding of the sequence of molecular events leading to progression from the chronically diseased liver microenvironment to the occurrence of hyperplastic and dysplastic nodules and ultimately to initiation and promotion of cancer is still poorly understood [
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      ]. Over the recent years, extensive research focused on the identification of key oncogenes and tumor suppressors regulating cell cycle and apoptosis associated with the development of liver cancer. Additionally, different signaling pathways known to be involved in hepatocarcinogenesis have been studied intensively and are subject of many excellent reviews [
      • Aravalli R.N.
      • Steer C.J.
      • Cressman E.N.
      Molecular mechanisms of hepatocellular carcinoma.
      ,
      • Farazi P.A.
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      Hepatocellular carcinoma pathogenesis: from genes to environment.
      ,
      • Villanueva A.
      • Newell P.
      • Chiang D.Y.
      • Friedman S.L.
      • Llovet J.M.
      Genomics and signaling pathways in hepatocellular carcinoma.
      ]. Among these, old dogs such as p53, b-Catenin, ErbB family as well as new players like Igf signaling and the Hippo pathway have been implicated in this process. Widely accepted major pathways and molecules are shown in Table 1.
      Table 1Signaling in
      • Farazi P.A.
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      Hepatocellular carcinoma pathogenesis: from genes to environment.
      ,

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      Mutation of p53 gene in regenerative nodules in cirrhotic liver.
      ,
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      Association of TP53 mutations with stem cell-like gene expression and survival of patients with hepatocellular carcinoma.
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      Tumor heterogeneity in small hepatocellular carcinoma: analysis of tumor cell proliferation, expression and mutation of p53 and [beta]-catenin.
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      • Calvisi D.F.
      • Factor V.M.
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      • Thorgeirsson S.S.
      Disruption of beta-catenin pathway or genomic instability define two distinct categories of liver cancer in transgenic mice.
      ,
      • Ishizaki Y.
      Immunohistochemical analysis and mutational analyses of [beta]-catenin, Axin family and APC genes in hepatocellular carcinomas.
      ,
      • Hopfner M.
      Targeting the epidermal growth factor receptor by gefitinib for treatment of hepatocellular carcinoma.
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      Increased expression of the insulin-like growth factor I (IGF-I) receptor gene in hepatocellular carcinoma cell lines: implications of IGF-I receptor gene activation by hepatitis B virus X gene product.
      ,
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      Insulin and insulin-like growth factor signalling in neoplasia.
      ,
      • Tang S.H.
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      Hypomethylated P4 promoter induces expression of the insulin-like growth factor-II gene in hepatocellular carcinoma in a Chinese population.
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      IGF activation in a molecular subclass of hepatocellular carcinoma and pre-clinical efficacy of IGF-1R blockage.
      ,
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      • Coulouarn C.
      • Factor V.M.
      • Thorgeirsson S.S.
      Met-regulated expression signature defines a subset of human hepatocellular carcinomas with poor prognosis and aggressive phenotype.
      ,
      • Stella G.M.
      • Benvenuti S.
      • Comoglio P.M.
      Targeting the MET oncogene in cancer and metastases.
      ,
      • Coulouarn C.
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      Transforming growth factor-beta gene expression signature in mouse hepatocytes predicts clinical outcome in human cancer.
      ,
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      Sorafenib in advanced hepatocellular carcinoma.
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      The Hippo-Salvador pathway restrains hepatic oval cell proliferation, liver size, and liver tumorigenesis.
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      Mst1 and Mst2 maintain hepatocyte quiescence and suppress hepatocellular carcinoma development through inactivation of the Yap1 oncogene.
      .

      Next generation approaches in liver cancer diagnosis and therapeutic translation

      Genomics

      The advances in affordable, high-throughput technologies made a major contribution to the understanding of structural variation in the human genome. Recent genome wide association studies (GWAS) enrolling several thousand individuals led to the identification of liver disease specific susceptibility loci, including for HCC [
      • Kumar V.
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      Genome-wide association study identifies a susceptibility locus for HCV-induced hepatocellular carcinoma.
      ,
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      Genome-wide association analysis in primary sclerosing cholangitis identifies two non-HLA susceptibility loci.
      ,
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      • Berg T.
      • Weltman M.
      • Abate M.L.
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      IL28B is associated with response to chronic hepatitis C interferon-alpha and ribavirin therapy.
      ,
      • Tanaka Y.
      • Nishida N.
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      • Kurosaki M.
      • Matsuura K.
      • Sakamoto N.
      • et al.
      Genome-wide association of IL28B with response to pegylated interferon-alpha and ribavirin therapy for chronic hepatitis C.
      ,
      • Krawczyk M.
      • Mullenbach R.
      • Weber S.N.
      • Zimmer V.
      • Lammert F.
      Genome-wide association studies and genetic risk assessment of liver diseases.
      ]. Most of these studies employed high-throughput microarray technology for SNP genotyping and array-based comparative genomic hybridization (aCGH). In contrast to disease specific loci in well defined patient collectives, the application of whole genomic approaches for the analyses of the cancer genome yielded in enormous diversity and complexity underappreciated by the traditional hypothesis-driven approaches mainly focusing on few genes and/or pathways [
      • Beroukhim R.
      • Mermel C.H.
      • Porter D.
      • Wei G.
      • Raychaudhuri S.
      • Donovan J.
      • et al.
      The landscape of somatic copy-number alteration across human cancers.
      ,
      • Kan Z.
      • Jaiswal B.S.
      • Stinson J.
      • Janakiraman V.
      • Bhatt D.
      • Stern H.M.
      • et al.
      Diverse somatic mutation patterns and pathway alterations in human cancers.
      ]. Cancer cell genomes vary substantially from each other and even more dramatically from those of normal and non-cancerous tissues [
      • Meyerson M.
      • Gabriel S.
      • Getz G.
      Advances in understanding cancer genomes through second-generation sequencing.
      ]. In contrast to tightly controlled genomes of normal tissue, the mutational turn-over of cancer cells is rapid leading to dynamic structural variations (CNV, LOH, aneuploidity) which needs to be considered in translational cancer research.
      Due to this complexity, the application of these approaches in clinical routine currently remains limited. However, genomic profiling has a great potential as diagnostic and prognostic tool in personalized medicine.
      Phenotypic and molecular heterogeneity is a hallmark of hepatocellular cancers [
      • Lee J.S.
      • Thorgeirsson S.S.
      Genetic profiling of human hepatocellular carcinoma.
      ]. In particular, somatic alterations and structural variation of genes important for cell cycle and apoptosis are commonly associated with hepatocarcinogenesis [
      • Farazi P.A.
      • DePinho R.A.
      Hepatocellular carcinoma pathogenesis: from genes to environment.
      ]. Other key molecular features frequently altered in liver cancer involve the molecules and pathways listed in Table 1. Array-based SNP genotyping and CGH approaches have been extensively utilized to study structural abnormalities in both liver cancer cell lines and primary tumors [
      • Farazi P.A.
      • DePinho R.A.
      Hepatocellular carcinoma pathogenesis: from genes to environment.
      ,
      • Villanueva A.
      • Newell P.
      • Chiang D.Y.
      • Friedman S.L.
      • Llovet J.M.
      Genomics and signaling pathways in hepatocellular carcinoma.
      ,
      • Hoshida Y.
      • Toffanin S.
      • Lachenmayer A.
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      • Minguez B.
      • Llovet J.M.
      Molecular classification and novel targets in hepatocellular carcinoma: recent advancements.
      ,
      • Poon T.C.
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      • Lai P.B.
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      • Johnson P.J.
      • Sung J.J.
      A tumor progression model for hepatocellular carcinoma: bioinformatic analysis of genomic data.
      ].
      Recurrent copy number variations in various HCC cell lines have already been demonstrated more than one decade ago [
      • Keck C.L.
      • Zimonjic D.B.
      • Yuan B.Z.
      • Thorgeirsson S.S.
      • Popescu N.C.
      Nonrandom breakpoints of unbalanced chromosome translocations in human hepatocellular carcinoma cell lines.
      ,
      • Zimonjic D.B.
      • Keck C.L.
      • Thorgeirsson S.S.
      • Popescu N.C.
      Novel recurrent genetic imbalances in human hepatocellular carcinoma cell lines identified by comparative genomic hybridization.
      ]. Here, several genomic imbalances in HCC cell lines could be associated with the pathogenesis of liver cancer thereby providing a basis for array-based molecular diagnosis and monitoring of liver cancer. Recently, a similar approach was employed using high-density single nucleotide polymorphism arrays and uncovered 6 deletions and 126 amplifications shared by several cell lines [
      • Chen C.F.
      • Hsu E.C.
      • Lin K.T.
      • Tu P.H.
      • Chang H.W.
      • Lin C.H.
      • et al.
      Overlapping high-resolution copy number alterations in cancer genomes identified putative cancer genes in hepatocellular carcinoma.
      ]. More detailed analyses of identified genes (FNDC3B (3q26.3) and SLC29A2 (11q13.2)), previously not recognized in the context of liver cancer, confirmed consistent activation and clinical correlation of these genes in several HCC datasets. Moreover, further evaluation demonstrated a functional role for cancer cell proliferation and tumorigenicity, supporting the use of cell lines for discovery of diagnostic and therapeutic biomarkers and highlighting the power of whole genomic approaches. Since the majority of HCCs develop over many years on the basis of chronic inflammation, several redundant structural abnormalities are associated with primary liver cancer involving chromosomal regions with known driver genes in HCC such as c-MYC, RAS, and p53 [
      • Villanueva A.
      • Newell P.
      • Chiang D.Y.
      • Friedman S.L.
      • Llovet J.M.
      Genomics and signaling pathways in hepatocellular carcinoma.
      ]. A comprehensive catalog of common aberrations from both human and rodents is provided in the OncoDB.HCC (http://oncodb.hcc.ibms.sinica.edu.tw) database [
      • Su W.H.
      • Chao C.C.
      • Yeh S.H.
      • Chen D.S.
      • Chen P.J.
      • Jou Y.S.
      Onco DB. HCC: an integrated oncogenomic database of hepatocellular carcinoma revealed aberrant cancer target genes and loci.
      ]. This database provides a useful, validated, and graphical integration of published data derived from LOH analyses, aCGH, gene expression microarrays as well as proteomics which is publically assessable for validation of molecular targets. However, due to molecular diversity of the alterations behind these loci, a major obstacle remains the functional evaluation of individual genes and identification of driver genes.
      Traditionally, the functional role of identified genes has been studied using genetically modified mouse models [
      • Lee J.S.
      • Chu I.S.
      • Mikaelyan A.
      • Calvisi D.F.
      • Heo J.
      • Reddy J.K.
      • et al.
      Application of comparative functional genomics to identify best-fit mouse models to study human cancer.
      ,
      • Zender L.
      Identification and validation of oncogenes in liver cancer using an integrative oncogenomic approach.
      ]. Although these mouse models revealed important insights into the molecular pathogenesis of liver cancer, they have several shortcomings that limit their use for translational medicine [
      • Zimonjic D.B.
      • Ullmannova-Benson V.
      • Factor V.M.
      • Thorgeirsson S.S.
      • Popescu N.C.
      Recurrent and nonrandom DNA copy number and chromosome alterations in Myc transgenic mouse model for hepatocellular carcinogenesis: implications for human disease.
      ].
      Recently, a systematic strategy to identify potential driver genes by integrating whole genome copy number data with gene expression profiles of HCC patients was introduced [
      • Woo H.G.
      • Park E.S.
      • Lee J.S.
      • Lee Y.H.
      • Ishikawa T.
      • Kim Y.J.
      • et al.
      Identification of potential driver genes in human liver carcinoma by genomewide screening.
      ]. By selecting only genes with prognostic significance in HCC patients, a total of 50 putative driver genes were identified and functionally evaluated by RNAi. Further, by using the connectivity map an association of the 50 genes with specific signaling molecules in HCC could be established (mTOR, AMPK, and EGFR). The Connectivity map is a publically available and powerful tool that enables discovery of functional connections between drugs and genes using a collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules [
      • Lamb J.
      The connectivity map: a new tool for biomedical research.
      ,
      • Lamb J.
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      • Peck D.
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      • Blat I.C.
      • Wrobel M.J.
      • et al.
      The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease.
      ].
      In summary, over the recent decades extensive studies on genomic changes revealed recurrent molecular changes associated with liver cancer. Availability of systematic and multidimensional approaches for integrative genomic analyses of whole genomes from both rodent and human tumors will further provide novel insights into molecular mechanisms in liver cancer, that are likely to change the clinical management of this disease.

      Transcriptomics

      The use of gene-expression signatures is a powerful aid in the development of novel diagnostic tools and for accurate and unbiased identification of prognostic subclasses and new cellular targets in liver cancer [
      • Lee J.S.
      • Chu I.S.
      • Heo J.
      • Calvisi D.F.
      • Sun Z.
      • Roskams T.
      • et al.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Lee J.S.
      • Heo J.
      • Libbrecht L.
      • Chu I.S.
      • Kaposi-Novak P.
      • Calvisi D.F.
      • et al.
      A novel prognostic subtype of human hepatocellular carcinoma derived from hepatic progenitor cells.
      ,
      • Yamashita T.
      • Forgues M.
      • Wang W.
      • Kim J.W.
      • Ye Q.
      • Jia H.
      • et al.
      EpCAM and alpha-fetoprotein expression defines novel prognostic subtypes of hepatocellular carcinoma.
      ]. Moreover, the use of whole transcriptome data from patients before and after drug treatment to conduct pharmacogenomic analysis is a promising approach to predict drug sensitivity and rationalize the use of drugs that already has successfully been applied in several studies [
      • Ayers M.
      • Symmans W.F.
      • Stec J.
      • Damokosh A.I.
      • Clark E.
      • Hess K.
      • et al.
      Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer.
      ]. The era of whole transcriptomic analyses for HCC started almost 10 years ago [
      • Iizuka N.
      Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection.
      ,
      • Lee J.S.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Ye Q.H.
      • Qin L.X.
      • Forgues M.
      • He P.
      • Kim J.W.
      • Peng A.C.
      • et al.
      Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning.
      ]. Since then, more than 20 clinically relevant gene expression signatures have been generated in HCC (Table 2). The clinical utility of these studies is ranging from diagnosis over prediction of survival and metastatic spread to prediction of recurrent diseases.
      Table 2Prognostic signatures in
      • Iizuka N.
      Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection.
      ,
      • Ye Q.H.
      • Qin L.X.
      • Forgues M.
      • He P.
      • Kim J.W.
      • Peng A.C.
      • et al.
      Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning.
      ,
      • Lee J.S.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Budhu A.
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      • Ye Q.H.
      • Jia H.L.
      • He P.
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      Prediction of venous metastases, recurrence, and prognosis in hepatocellular carcinoma based on a unique immune response signature of the liver microenvironment.
      ,
      • Kaposi-Novak P.
      • Lee J.S.
      • Gomez-Quiroz L.
      • Coulouarn C.
      • Factor V.M.
      • Thorgeirsson S.S.
      Met-regulated expression signature defines a subset of human hepatocellular carcinomas with poor prognosis and aggressive phenotype.
      ,
      • Lee J.S.
      A novel prognostic subtype of human hepatocellular carcinoma derived from hepatic progenitor cells.
      ,
      • Wang S.M.
      • Ooi L.L.
      • Hui K.M.
      Identification and validation of a novel gene signature associated with the recurrence of human hepatocellular carcinoma.
      ,
      • Boyault S.
      • Rickman D.S.
      • De Reynies A.
      • Balabaud C.
      • Rebouissou S.
      • Jeannot E.
      • et al.
      Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets.
      ,
      • Woo H.G.
      • Park E.S.
      • Cheon J.H.
      • Kim J.H.
      • Lee J.S.
      • Park B.J.
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      Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma.
      ,
      • Hoshida Y.
      • Villanueva A.
      • Kobayashi M.
      • Peix J.
      • Chiang D.Y.
      • Camargo A.
      • et al.
      Gene expression in fixed tissues and outcome in hepatocellular carcinoma.
      ,
      • Coulouarn C.
      • Factor V.M.
      • Thorgeirsson S.S.
      Transforming growth factor-beta gene expression signature in mouse hepatocytes predicts clinical outcome in human cancer.
      ,
      • Yamashita T.
      • Forgues M.
      • Wang W.
      • Kim J.W.
      • Ye Q.
      • Jia H.
      • et al.
      EpCAM and alpha-fetoprotein expression defines novel prognostic subtypes of hepatocellular carcinoma.
      ,
      • Yoshioka S.
      • Takemasa I.
      • Nagano H.
      • Kittaka N.
      • Noda T.
      • Wada H.
      • et al.
      Molecular prediction of early recurrence after resection of hepatocellular carcinoma.
      ,
      • Hoshida Y.
      • Nijman S.M.
      • Kobayashi M.
      • Chan J.A.
      • Brunet J.P.
      • Chiang D.Y.
      • et al.
      Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma.
      ,
      • Kaposi-Novak P.
      • Libbrecht L.
      • Woo H.G.
      • Lee Y.H.
      • Sears N.C.
      • Conner E.A.
      • et al.
      Central role of c-Myc during malignant conversion in human hepatocarcinogenesis.
      ,
      • Andersen J.B.
      • Loi R.
      • Perra A.
      • Factor V.M.
      • Ledda-Columbano G.M.
      • Columbano A.
      • et al.
      Progenitor-derived hepatocellular carcinoma model in the rat.
      ,
      • Woo H.G.
      • Lee J.H.
      • Yoon J.H.
      • Kim C.Y.
      • Lee H.S.
      • Jang J.J.
      • et al.
      Identification of a cholangiocarcinoma-like gene expression trait in hepatocellular carcinoma.
      ,
      • Roessler S.
      • Jia H.L.
      • Budhu A.
      • Forgues M.
      • Ye Q.H.
      • Lee J.S.
      • et al.
      A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.
      .
      The power of gene expression signatures to complement diagnostic strategies could be demonstrated in several studies. By utilizing whole transcriptome analyses, a recent study tried to discriminate and identify key regulatory molecules between cirrhotic (regenerative) nodules, dysplastic nodules (DN), and early stage HCC [
      • Kaposi-Novak P.
      • Libbrecht L.
      • Woo H.G.
      • Lee Y.H.
      • Sears N.C.
      • Conner E.A.
      • et al.
      Central role of c-Myc during malignant conversion in human hepatocarcinogenesis.
      ]. As a result, the authors demonstrated that upregulation of MYC (8q) in dysplastic nodules could be used as a marker for malignant conversion. Notably, other markers commonly associated to hepatocarcinogenesis (GPC3) could also be detected.
      Several hallmark prognostic signatures have been generated for HCC by applying global gene expression analyses (Table 2).
      Considerable heterogeneity across these signatures results in different non-overlapping numbers of genes and differences in prognostic relevance. Nevertheless, hallmark signaling of tumors, well established for the majority of solid tumors, such as proliferative signaling, resistance against cell death, immortality, pro-angiogenic signaling, activation of invasive and metastatic programs as well as pro-inflammatory signaling could also be recapitulated for HCC [
      • Lee J.S.
      • Chu I.S.
      • Heo J.
      • Calvisi D.F.
      • Sun Z.
      • Roskams T.
      • et al.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Hanahan D.
      • Weinberg R.A.
      Hallmarks of cancer: the next generation.
      ,
      • Hoshida Y.
      • Nijman S.M.
      • Kobayashi M.
      • Chan J.A.
      • Brunet J.P.
      • Chiang D.Y.
      • et al.
      Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma.
      ]. Other pathways associated with bad survival involved less studied pathways such as ubiquitination, histone modifications as well as stemness traits [
      • Lee J.S.
      • Chu I.S.
      • Heo J.
      • Calvisi D.F.
      • Sun Z.
      • Roskams T.
      • et al.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Lee J.S.
      • Heo J.
      • Libbrecht L.
      • Chu I.S.
      • Kaposi-Novak P.
      • Calvisi D.F.
      • et al.
      A novel prognostic subtype of human hepatocellular carcinoma derived from hepatic progenitor cells.
      ,
      • Andersen J.B.
      • Factor V.M.
      • Marquardt J.U.
      • Raggi C.
      • Lee Y.H.
      • Seo D.
      • et al.
      An integrated genomic and epigenomic approach predicts therapeutic response to zebularine in human liver cancer.
      ,
      • Woo H.G.
      • Lee J.H.
      • Yoon J.H.
      • Kim C.Y.
      • Lee H.S.
      • Jang J.J.
      • et al.
      Identification of a cholangiocarcinoma-like gene expression trait in hepatocellular carcinoma.
      ]. Since then, several of the identified markers have been tested for their significance as therapeutic targets and will be discussed later in this review [
      • Lee Y.H.
      • Andersen J.B.
      • Song H.T.
      • Judge A.D.
      • Seo D.
      • Ishikawa T.
      • et al.
      Definition of ubiquitination modulator COP1 as a novel therapeutic target in human hepatocellular carcinoma.
      ,

      Lee YH, Judge AD, Seo D, Kitade M, Gomez-Quiroz LE, Ishikawa T, et al. Molecular targeting of CSN5 in human hepatocellular carcinoma: a mechanism of therapeutic response. Oncogene 2011.

      ,
      • Villanueva A.
      • Chiang D.Y.
      • Newell P.
      • Peix J.
      • Thung S.
      • Alsinet C.
      • et al.
      Pivotal role of mTOR signaling in hepatocellular carcinoma.
      ]. Interestingly, a recent study generated a prognostic signature from liver tissue adjacent to the tumor, underlining the role of the diseased microenvironment for the progression of liver cancer [
      • Hoshida Y.
      • Villanueva A.
      • Kobayashi M.
      • Peix J.
      • Chiang D.Y.
      • Camargo A.
      • et al.
      Gene expression in fixed tissues and outcome in hepatocellular carcinoma.
      ]. Villanueva et al. used an integrative approach combining different published prognostic gene expression profiling in HCC. As a result, they were able to composite a prognostic model for HCC recurrence, based on gene expression patterns in an independent set of tumor and adjacent liver tissues confirming the power of gene expression to complement findings from clinical and pathology analyses [
      • Villanueva A.
      • Hoshida Y.
      • Battiston C.
      • Tovar V.
      • Sia D.
      • Alsinet C.
      • et al.
      Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma.
      ].
      Several examples from different solid tumors exist on how gene-expression profiles may be used in clinical practice for risk prediction e.g. of recurrent disease (70-gene profile (MammaPrint) [
      • Glas A.M.
      • Floore A.
      • Delahaye L.J.
      • Witteveen A.T.
      • Pover R.C.
      • Bakx N.
      • et al.
      ], the 21-gene recurrence score (Oncotype DX) [
      • Cobleigh M.A.
      • Tabesh B.
      • Bitterman P.
      • Baker J.
      • Cronin M.
      • Liu M.L.
      • et al.
      Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes.
      ]; 76-gene outcome Rotterdam signature [
      • Foekens J.A.
      • Atkins D.
      • Zhang Y.
      • Sweep F.C.
      • Harbeck N.
      • Paradiso A.
      • et al.
      Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer.
      ]). In case of HCC, besides the mentioned prognostic signatures several signatures predictive for e.g. recurrence and metastasis have been generated (Table 2). Already in 2002, a 12-gene signature was generated that could predict early intrahepatic recurrence [
      • Iizuka N.
      Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection.
      ]. Later, a group from NCI was able to generate a 17-gene immune response-related signature from non-cancerous tissues in metastatic livers that accurately predicted venous metastases, recurrence, and prognosis of HCC patients [
      • Budhu A.
      • Forgues M.
      • Ye Q.H.
      • Jia H.L.
      • He P.
      • Zanetti K.A.
      • et al.
      Prediction of venous metastases, recurrence, and prognosis in hepatocellular carcinoma based on a unique immune response signature of the liver microenvironment.
      ]. Although all of these signatures had significant predictive ability, the successful translation and rigorous evaluation for a clinical application is yet to be generated.
      Another useful application of gene expression data is the generation of publically available databases [
      • Sherlock G.
      • Hernandez-Boussard T.
      • Kasarskis A.
      • Binkley G.
      • Matese J.C.
      • Dwight S.S.
      • et al.
      The Stanford microarray database.
      ,
      • Subramanian A.
      • Tamayo P.
      • Mootha V.K.
      • Mukherjee S.
      • Ebert B.L.
      • Gillette M.A.
      • et al.
      Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
      ]. Although highly useful, successful integration of the obtained data in a disease context, in particular for liver diseases, is usually missing.
      We have recently tried to address the interaction of molecular networks from gene expression data with their association to human liver diseases and generated the first comprehensive and valid database for published molecular associations to close the gap between genome wide microarray data and individual highly validated data from PubMed [
      • Buchkremer S.
      • Hendel J.
      • Krupp M.
      • Weinmann A.
      • Schlamp K.
      • Maass T.
      • et al.
      Library of molecular associations: curating the complex molecular basis of liver diseases.
      ]. Currently, Library of Molecular Associations (LOMA) holds approximately 1260 manually confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. All data is available in a publicly available database and can be accessed under: http://www.medicalgenomics.org/databases/loma/news. A more global tool for cancer gene expression and data-mining also including liver cancer data is the Oncomine cancer database (https://www.oncomine.org/). Selected genes across all analyses or for multiple genes in a selected analysis can be simultaneously investigated and evaluated for clinically important annotations [
      • Rhodes D.R.
      • Yu J.
      • Shanker K.
      • Deshpande N.
      • Varambally R.
      • Ghosh D.
      • et al.
      ONCOMINE: a cancer microarray database and integrated data-mining platform.
      ].
      Together, integration, systematic evaluation and data-mining of different gene expression signatures as well as efficient application in a clinical setting (e.g., in microarray-aided pathology) can be of indispensible value for modern personalized medicine.

      Epigenomics and micronomics

      Growing evidence suggests that abnormal epigenetic regulation is one of the fundamental mechanisms underlying many human diseases including cancer [
      • Feinberg A.P.
      Phenotypic plasticity and the epigenetics of human disease.
      ]. Epigenetic alterations add further complexity also to the pathogenesis of cancer. Changes in DNA methylation are believed to be the early events in carcinogenesis preceding allelic imbalances and lead to ultimately cancer progression [
      • Feinberg A.P.
      • Tycko B.
      The history of cancer epigenetics.
      ]. Not surprisingly, epigenetic dysregulation, in particular global hypomethylation and promoter hypermethylation with subsequent silencing of tumor suppressor genes has been increasingly recognized in the pathogenesis of liver cancer [
      • Kumar V.
      • Kato N.
      • Urabe Y.
      • Takahashi A.
      • Muroyama R.
      • Hosono N.
      • et al.
      Genome-wide association study identifies a susceptibility locus for HCV-induced hepatocellular carcinoma.
      ]. As reported in other cancers, epigenetic changes in the diseased liver microenvironment are supposed to be early events also predisposing for liver cancer [
      • Gao W.
      • Kondo Y.
      • Shen L.
      • Shimizu Y.
      • Sano T.
      • Yamao K.
      • et al.
      Variable DNA methylation patterns associated with progression of disease in hepatocellular carcinomas.
      ,
      • Lee S.
      Aberrant CpG island hypermethylation along multistep hepatocarcinogenesis.
      ]. The concept of a multistep, epigenetic driven hepatocarcinogenesis was recently confirmed in HBV-related liver cancers. A stepwise increase of methylation in CpG islands of nine well described genes was seen in a total of 133 samples (45 cirrhotic nodules, 29 LGDNs, 13 HGDNs, 14 eHCCs, and 32 progressed HCCs) [
      • Um T.H.
      • Kim H.
      • Oh B.K.
      • Kim M.S.
      • Kim K.S.
      • Jung G.
      • et al.
      Aberrant CpG island hypermethylation in dysplastic nodules and early HCC of hepatitis B virus-related human multistep hepatocarcinogenesis.
      ]. Other studies could successfully use methylation patterns to classify patients according to different etiological factors (e.g., HBV, HCV, alcohol) [
      • Hernandez-Vargas H.
      • Lambert M.P.
      • Le Calvez-Kelm F.
      • Gouysse G.
      • McKay-Chopin S.
      • Tavtigian S.V.
      • et al.
      Hepatocellular carcinoma displays distinct DNA methylation signatures with potential as clinical predictors.
      ,
      • Lambert M.P.
      • Paliwal A.
      • Vaissiere T.
      • Chemin I.
      • Zoulim F.
      • Tommasino M.
      • et al.
      Aberrant DNA methylation distinguishes hepatocellular carcinoma associated with HBV and HCV infection and alcohol intake.
      ]. Furthermore, Calvisi et al. recently revealed that changes in global and distinct methylation patterns strongly correlate with the biological behavior of the tumors and the clinical outcome of cancer patients [
      • Calvisi D.F.
      • Ladu S.
      • Gorden A.
      • Farina M.
      • Lee J.S.
      • Conner E.A.
      • et al.
      Mechanistic and prognostic significance of aberrant methylation in the molecular pathogenesis of human hepatocellular carcinoma.
      ]. Using a 807 cancer-related gene panel in a group of 23 primary HCCs, the same group could successfully separate primary HCC samples according to their subtype, again suggesting a correlation between clinical outcome and methylation [
      • Andersen J.B.
      • Factor V.M.
      • Marquardt J.U.
      • Raggi C.
      • Lee Y.H.
      • Seo D.
      • et al.
      An integrated genomic and epigenomic approach predicts therapeutic response to zebularine in human liver cancer.
      ]. Consistent with previous studies, patients with progenitor cell origin displayed the worse clinical outcome [
      • Lee J.S.
      A novel prognostic subtype of human hepatocellular carcinoma derived from hepatic progenitor cells.
      ].
      Besides DNA methylation, other important epigenetic mechanisms regulating gene expression are modification of histones (e.g., acetylation, methylation, phosphorylation, ubiquitylation, and sumoylation) [
      • Esteller M.
      Epigenetics in cancer.
      ].
      Although modifications of e.g. patterns of repressing histone marks such as histone H3 lysine 27 and histone H3 lysine 9 as well as activating histone H3 lysines 4 have significant impact on gene expression of critical genes associated with hepatocarcinogenesis, whole genomic approaches such as CHIP-CHIP and CHIP-seq. are needed to address the role of these changes from a more global perspective [
      • Hoshida Y.
      • Toffanin S.
      • Lachenmayer A.
      • Villanueva A.
      • Minguez B.
      • Llovet J.M.
      Molecular classification and novel targets in hepatocellular carcinoma: recent advancements.
      ].
      Furthermore, MicroRNAs are a class of epigenetically active small regulatory RNAs that function to modulate protein expression [
      • Ventura A.
      • Jacks T.
      MicroRNAs and cancer: short RNAs go a long way.
      ]. This control allows for fine-tuning of the cellular phenotype, including regulation of proliferation, cell signaling, and apoptosis.
      Aberrant expressions of MicroRNAs considerably contribute to cancer initiation, propagation, and progression. Emerging evidence indicates that certain MicroRNAs are frequently deregulated in HCC, and that some specific MicroRNAs are associated with the clinicopathological features of HCC [
      • Coulouarn C.
      • Factor V.M.
      • Andersen J.B.
      • Durkin M.E.
      • Thorgeirsson S.S.
      Loss of miR-122 expression in liver cancer correlates with suppression of the hepatic phenotype and gain of metastatic properties.
      ]. These studies demonstrated that MircoRNAs have essential roles in HCC progression by directly contributing to cell proliferation, apoptosis, and metastasis of HCC and by targeting a large number of critical protein-coding genes involved in hepatocarcinogenesis [
      • Mott J.L.
      MicroRNAs involved in tumor suppressor and oncogene pathways: implications for hepatobiliary neoplasia.
      ]. Not surprising, that MicroRNAs are also associated with the regulation of liver CSC [
      • Dirks P.B.
      MicroRNAs and parallel stem cell lives.
      ,
      • Ji J.
      • Yamashita T.
      • Budhu A.
      • Forgues M.
      • Jia H.L.
      • Li C.
      • et al.
      Identification of microRNA-181 by genome-wide screening as a critical player in EpCAM-positive hepatic cancer stem cells.
      ,
      • Ma S.
      • Tang K.H.
      • Chan Y.P.
      • Lee T.K.
      • Kwan P.S.
      • Castilho A.
      • et al.
      miR-130b Promotes CD133(+) liver tumor-initiating cell growth and self-renewal via tumor protein 53-induced nuclear protein 1.
      ].
      In liver carcinogenesis, MicroRNAs have been found to have both tumor suppressive (miR-122, miR-26, miR-223, Let-7 family) and oncogenic activity (miR-221, miR-222, Mir-224, Mir-9, and Mir-181). For some MicroRNAs (e.g., miR-221, miR-125B, miR-26, miR-122) a prognostic relevance and prediction of drug sensitivity (e.g., interferon) could be demonstrated [
      • Hoshida Y.
      • Toffanin S.
      • Lachenmayer A.
      • Villanueva A.
      • Minguez B.
      • Llovet J.M.
      Molecular classification and novel targets in hepatocellular carcinoma: recent advancements.
      ,
      • Marquardt J.U.
      • Factor V.M.
      • Thorgeirsson S.S.
      Epigenetic regulation of cancer stem cells in liver cancer: current concepts and clinical implications.
      ,
      • Budhu A.
      • Jia H.L.
      • Forgues M.
      • Liu C.G.
      • Goldstein D.
      • Lam A.
      • et al.
      Identification of metastasis-related microRNAs in hepatocellular carcinoma.
      ,
      • Ji J.
      • Shi J.
      • Budhu A.
      • Yu Z.
      • Forgues M.
      • Roessler S.
      • et al.
      MicroRNA expression, survival, and response to interferon in liver cancer.
      ].
      In the last years, the power of MicroRNA profiling for classification of liver cancers has been demonstrated. MicroRNA profiles revealed subclasses associated with histologic and etiologic factors, clinical phenotypes as well as mutations in several oncogenic pathways such as b-Catenin and HNF1A [
      • Ladeiro Y.
      • Couchy G.
      • Balabaud C.
      • Bioulac-Sage P.
      • Pelletier L.
      • Rebouissou S.
      • et al.
      MicroRNA profiling in hepatocellular tumors is associated with clinical features and oncogene/tumor suppressor gene mutations.
      ]. Recently, MicroRNA profiling of 89 HCC samples using a ligation-mediated amplification method revealed three distinct clusters of HCCs reflecting the clinical behavior of the tumors. The functional role of different identified MicroRNAs in particular of the miR-517 family was further investigated in cell lines and in an orthotopic mouse model of liver cancer. As a result, the authors could associate these MicroRNAs with increased proliferation, migration, and invasion of HCC cells in vitro and in vivo, indicating the therapeutic potential of MicroRNA based treatment modalities [
      • Toffanin S.
      • Hoshida Y.
      • Lachenmayer A.
      • Villanueva A.
      • Cabellos L.
      • Minguez B.
      • et al.
      MicroRNA-based classification of hepatocellular carcinoma and oncogenic role of miR-517a.
      ].
      Novel technologies such as next generation sequencing will likely contribute to a more detailed understanding of the role of this interesting class of molecules in hepatocarcinogenesis [
      • Ramsingh G.
      • Koboldt D.C.
      • Trissal M.
      • Chiappinelli K.B.
      • Wylie T.
      • Koul S.
      • et al.
      Complete characterization of the microRNAome in a patient with acute myeloid leukemia.
      ,
      • Schulte J.H.
      • Marschall T.
      • Martin M.
      • Rosenstiel P.
      • Mestdagh P.
      • Schlierf S.
      • et al.
      Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma.
      ].

      Therapeutic translation and target therapeutics in HCC

      Aberrant activation of different signaling pathways has been frequently demonstrated in several solid tumors and raised substantial interest for translational research also for liver cancer [
      • Eisenhauer E.A.
      From the molecule to the clinic – inhibiting HER2 to treat breast cancer.
      ,
      • Tsao M.S.
      • Sakurada A.
      • Cutz J.C.
      • Zhu C.Q.
      • Kamel-Reid S.
      • Squire J.
      • et al.
      Erlotinib in lung cancer – molecular and clinical predictors of outcome.
      ]. Highlighting the success of multi-tyrosinkinase inhibitor sorafenib the major affected signaling pathways dysregulated in liver cancer are involved in cellular functions, such as proliferation (e.g., EGF, IGF, HGF, RAS/mitogen-activated protein kinase), apoptosis and survival (e.g., Akt, Nf-Kb), angiogenesis, etc. (e.g., VEGF, PDGF) (Table 1) [
      • Llovet J.M.
      • Ricci S.
      • Mazzaferro V.
      • Hilgard P.
      • Gane E.
      • Blanc J.F.
      • et al.
      Sorafenib in advanced hepatocellular carcinoma.
      ,
      • Worns M.A.
      • Galle P.R.
      Novel inhibitors in development for hepatocellular carcinoma.
      ,
      • Farazi P.A.
      • DePinho R.A.
      Hepatocellular carcinoma pathogenesis: from genes to environment.
      ,
      • Hanahan D.
      • Weinberg R.A.
      Hallmarks of cancer: the next generation.
      ,
      • Llovet J.M.
      • Bruix J.
      Molecular targeted therapies in hepatocellular carcinoma.
      ]. Gene expression analyses could recapitulate most of these pathways and associate them with molecular and prognostic subclasses [
      • Thorgeirsson S.S.
      Genomic decoding of hepatocellular carcinoma.
      ,
      • Thorgeirsson S.S.
      • Grisham J.W.
      Molecular pathogenesis of human hepatocellular carcinoma.
      ].
      The efficiency of whole genomic approaches for the identification of new molecular targets and the development of pathway-orientated treatment strategies has been successfully applied in different studies. Using an integrational approach of genomic and transcriptomic as well as protein levels, Villaneuva et al. could demonstrate the importance of mTOR signaling in the pathogenesis of liver cancer. Deregulation of the signaling was frequently observed in primary human liver cancer specimens and associated with different other relevant pathways (e.g., IGF and EGF). Specific inhibitor and RNAi mediated blockade of the signaling reduced the proliferation of cancer cells in vitro and in vivo, indicating the potential for targeting the mTOR pathway in HCC [
      • Villanueva A.
      • Chiang D.Y.
      • Newell P.
      • Peix J.
      • Thung S.
      • Alsinet C.
      • et al.
      Pivotal role of mTOR signaling in hepatocellular carcinoma.
      ].
      Other examples stem from a group at the NCI. The authors made use of identified targets from prognostic gene expression signatures for the treatment of HCC. Using whole genomic analyses, the group previously identified COP1 and CSN5 as two critical regulators of p53 activity via proteasome-dependent degradation in a screen for survival genes in human HCC [
      • Lee J.S.
      • Chu I.S.
      • Heo J.
      • Calvisi D.F.
      • Sun Z.
      • Roskams T.
      • et al.
      Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.
      ,
      • Kaposi-Novak P.
      • Libbrecht L.
      • Woo H.G.
      • Lee Y.H.
      • Sears N.C.
      • Conner E.A.
      • et al.
      Central role of c-Myc during malignant conversion in human hepatocarcinogenesis.
      ]. Subsequently, Lee et al. successfully demonstrated that targeting of both genes can provide novel therapeutic modalities against liver cancer cells in vitro. RNAi mediated silencing of each gene, inhibited proliferation of HCC cells and increased apoptotic cell death through the restoration of p53 function. The authors further utilized a systemic delivery of the modified target siRNAs by stable-nucleic-acid-lipid-particles (SNALP) and confirmed remarkable suppression of malignant growth and increased survival in an orthotopic xenograft mouse model without eliciting overt immune response. Further, analysis of COP1 knockdown signature revealed that the anti-tumor effect in vivo was driven by p53-dependent apoptosis [
      • Lee Y.H.
      • Andersen J.B.
      • Song H.T.
      • Judge A.D.
      • Seo D.
      • Ishikawa T.
      • et al.
      Definition of ubiquitination modulator COP1 as a novel therapeutic target in human hepatocellular carcinoma.
      ,

      Lee YH, Judge AD, Seo D, Kitade M, Gomez-Quiroz LE, Ishikawa T, et al. Molecular targeting of CSN5 in human hepatocellular carcinoma: a mechanism of therapeutic response. Oncogene 2011.

      ]. Together, these studies suggest that systemic analyses of gene expression data can provide an important new step towards potential clinical application in personalized medicine.
      Targeting of epigenetic modifications provides an exciting new field for therapeutic strategies in HCC. Epigenetic changes are reversible by different therapeutic drugs leading to re-activation of silenced genes. Demethylating agents like 5-azacytidine as well as HDAC inhibitors such as virinostat and valproic acid are already approved for the treatment of hematologic cancers and focus of many clinical studies in solid cancers (www.clinicaltrials.gov) [
      • Hoshida Y.
      • Toffanin S.
      • Lachenmayer A.
      • Villanueva A.
      • Minguez B.
      • Llovet J.M.
      Molecular classification and novel targets in hepatocellular carcinoma: recent advancements.
      ].
      Recently, the individual drug-response of HCC cell lines to the DNA methylation inhibitor zebularine could be demonstrated [
      • Andersen J.B.
      • Factor V.M.
      • Marquardt J.U.
      • Raggi C.
      • Lee Y.H.
      • Seo D.
      • et al.
      An integrated genomic and epigenomic approach predicts therapeutic response to zebularine in human liver cancer.
      ]. Using transcriptomic and epigenomic profiling, a drug response signature could be generated that classified liver cancer cells according to their corresponding sensitivity. In drug-sensitive cell lines, epigenetic modulation caused cell cycle arrest and increased apoptosis, whereas drug-resistant cell lines showed up-regulation of dominant oncogenic networks (for example, E2F1, MYC, and TNF). Therapeutic efficiency against sensitive cancer cells was further revealed in vivo, leading to increased survival and decreased pulmonary metastasis. Subsequent integration of the generated gene expression and demethylation response signatures allowed differentiation of patients with HCC according to their clinical outcome. The study provided first insights into prediction of treatment success against epigenetic chemotherapy and demonstrates the power of the pharmaco-epigenomic approaches to identify cancer patients who likely benefit from targeting the cancer epigenome.

      Novel cellular targets in HCC: a role for hepatic Cancer Stem Cells

      The hierarchic model of cancer origin is based on the assumption that tumor heterogeneity originates from a small population of so called Cancer Stem Cell (CSC) that share multiple characteristics of tissue stem cells [
      • Marquardt J.U.
      • Thorgeirsson S.S.
      Stem cells in hepatocarcinogenesis: evidence from genomic data.
      ]. This model does not contradict the classical stochastic tumor model, it just redefines the importance of cells with aberrant differentiation capacity and is helpful to approach the above mentioned tumor heterogeneity. Moreover, while the cellular origin remains undefined in the term CSC, the existence of these cells is of fundamental importance for translational cancer research and harbors broad clinical implications, in particular from the therapeutic point of view [
      • Marquardt J.U.
      • Thorgeirsson S.S.
      Stem cells in hepatocarcinogenesis: evidence from genomic data.
      ,
      • Kakarala M.
      • Wicha M.S.
      Implications of the cancer stem-cell hypothesis for breast cancer prevention and therapy.
      ].
      Many studies tried to elucidate the presence of CSC in hepatocarcinogenesis and mainly employed immunogeneic as well as functional isolation methods for prospective isolation [
      • Marquardt J.U.
      • Factor V.M.
      • Thorgeirsson S.S.
      Epigenetic regulation of cancer stem cells in liver cancer: current concepts and clinical implications.
      ,
      • Marquardt J.U.
      • Thorgeirsson S.S.
      Cancer stem cells and liver cancer.
      ]. Few studies also addressed the clinical relevance of CSC for treatment and outcome of patients. Drug resistance with subsequent initiation of relapses and/or metastatic spread of tumor cells are supposed to be fundamental properties of CSCs, [
      • Jordan C.T.
      • Guzman M.L.
      • Noble M.
      Cancer stem cells.
      ] thereby making CSC a prime cellular target for diagnostic and therapeutic strategies in multi-resistant cancers such as HCC, which are characterized by poor therapeutic response and fatal outcome of the patients [
      • Llovet J.M.
      • Bruix J.
      Molecular targeted therapies in hepatocellular carcinoma.
      ,
      • Philip P.A.
      • Mooney M.
      • Jaffe D.
      • Eckhardt G.
      • Moore M.
      • Meropol N.
      • et al.
      Consensus report of the national cancer institute clinical trials planning meeting on pancreas cancer treatment.
      ]. Specific targeting liver CSCs in pre-clinical studies, e.g. by targeting EpCAM + cells by RNAi mediated inhibition or forced differentiation using oncostatin M in combination with conventional chemotherapy, showed increased apoptosis and decreased cell proliferation, indicating the potential of CSCs for therapeutic modalities in liver cancer [
      • Yamashita T.
      • Honda M.
      • Nio K.
      • Nakamoto Y.
      • Takamura H.
      • Tani T.
      • et al.
      Oncostatin m renders epithelial cell adhesion molecule-positive liver cancer stem cells sensitive to 5-fluorouracil by inducing hepatocytic differentiation.
      ,
      • Yamashita T.
      • Ji J.
      • Budhu A.
      • Forgues M.
      • Yang W.
      • Wang H.Y.
      • et al.
      EpCAM-positive hepatocellular carcinoma cells are tumor-initiating cells with stem/progenitor cell features.
      ]. Recently, CD13 was identified as a new marker of hepatic CSCs by using gene expression profiling of isolated Side-Population cells from liver cancer cell lines [
      • Christ B.
      • Stock P.
      • Dollinger M.M.
      CD13: waving the flag for a novel cancer stem cell target.
      ,
      • Haraguchi N.
      • Ishii H.
      • Mimori K.
      • Tanaka F.
      • Ohkuma M.
      • Kim H.M.
      • et al.
      CD13 is a therapeutic target in human liver cancer stem cells.
      ]. The authors found that CD13 enriches for semiquiescent CSCs and showed that targeting these cells might provide a way to treat HCC. Direct targeting of this molecule by a CD13 inhibitor in combination with fluorouracil (5-FU) drastically reduced tumorigenicity and self-renewing capacity of the cells.
      Although the existence of these CSC in liver cancer is still matter of controversies, several studies demonstrated the clinical significance of stem-like gene expression signatures for liver cancer patients. The notion that HCC patients who share gene features of progenitor cells have a worse clinical outcome has been repeatedly demonstrated.
      Andersen et al. recently established CK19 as a relevant marker of neoplastic transformation in a rat model of liver cancer. Likewise, a CK19 gene expression signature enriched for ‘stemness’, successfully classified HCC patients according to the clinical outcome [
      • Villanueva A.
      • Hoshida Y.
      • Battiston C.
      • Tovar V.
      • Sia D.
      • Alsinet C.
      • et al.
      Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma.
      ,
      • Andersen J.B.
      • Loi R.
      • Perra A.
      • Factor V.M.
      • Ledda-Columbano G.M.
      • Columbano A.
      • et al.
      Progenitor-derived hepatocellular carcinoma model in the rat.
      ].
      In human, the concept of CK19 as a clinical surrogate of a progenitor cell origin could further be confirmed. CK19 positive tumors highly overlapped with the proliferation subclass generated by earlier studies of the authors. A human-based CK19 gene expression signature was highly associated with the CK19 rat signature and other progenitor-derived signatures [
      • Villanueva A.
      • Hoshida Y.
      • Battiston C.
      • Tovar V.
      • Sia D.
      • Alsinet C.
      • et al.
      Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma.
      ].

      Future perspectives

      Over the last decades considerable advancements in the clinical management of liver cancer have been made. Due to efficient surveillance, improved diagnostic assessment, as well as increasing efforts in therapeutic strategies, liver cancer emerged from a universally deadly to a treatable disease [
      • Bruix J.
      • Sherman M.
      Management of hepatocellular carcinoma: an update.
      ]. Although whole genomic approaches evolved to affordable tools in cancer research with a dramatic impact on translational science, there remains a significant gap for the translational applications of these technologies in liver cancer.
      The exact molecular mechanisms of how currently used targeted therapies (e.g., sorafenib, erlotinib) contribute their efficacy in HCC are still unknown and molecular classification of HCC patients into relevant subclasses based on individual (epi-)genomic tumor signatures as well as individualized therapeutic approaches remain a futuristic vision. Successful translation into clinical practice will require prospective application of high-throughput whole genomic approaches and standardized validation in independent patient cohorts. Further, pharmaco-genomic analyses should accompany clinical trials to rationalize the combination of available targeted therapies and unravel the mechanisms of drug resistance.
      Next-generation technologies such as deep sequencing are promising tools to further increase our understanding of cancer biology and extensive application of these novel high-throughput technologies such as already performed in the International Cancer Genome Consortium (http://www.icgc.org) and the Cancer Genome Atlas (http://cancergenome.nih.gov) will undoubtfully contribute to the identification of new molecular targets. Several recent studies already successfully employed deep sequencing approaches and showed stepwise progression of genomic variations during cancer progression in different cancers, whereby concomitantly identifying novel mutations, e.g., during the acquisition of metastatic traits, that could be used for drug development [
      • Campbell P.J.
      • Yachida S.
      • Mudie L.J.
      • Stephens P.J.
      • Pleasance E.D.
      • Stebbings L.A.
      • et al.
      The patterns and dynamics of genomic instability in metastatic pancreatic cancer.
      ,
      • Yachida S.
      • Jones S.
      • Bozic I.
      • Antal T.
      • Leary R.
      • Fu B.
      • et al.
      Distant metastasis occurs late during the genetic evolution of pancreatic cancer.
      ]. Large-scale and systematic application of novel technologies on all molecular levels i.e. genome, transcriptome, proteome, and epigenome are urgently needed to decode the biology of hepatocellular cancers and improve the limited prognosis of our patients. One of the major challenges of this century will be the meaningful interpretation and application of the enormous flood of data in a meaningful clinical context. Further, integration of this vast amount of data and assembly of cumulative hypotheses will be extremely challenging in translational science. Another major obstacle is the integration of different biological layers (genome, transcriptome, proteome, epigenome), in particular due to a lack of sufficient bioinformatics strategies. Further increasing the biological complexity, biological/pathological changes observed in individual biological compartments do not necessarily have to be conforming to each other. It has been well established in model organisms that in normal liver tissue, approximately 25% of changes in gene expression are not accompanied by simultaneous changes in protein abundance. This is a particular problem for low expressed genes [
      • Gygi S.P.
      • Rochon Y.
      • Franza B.R.
      • Aebersold R.
      Correlation between protein and mRNA abundance in yeast.
      ]. However, it has also been established that findings of differential gene and protein expression may complement one another and thus lead to a more comprehensive view of biological changes. First, approaches to generate algorithms and platforms for integrating all these diverse biological information have been made, e.g., BiologicalNetworks2.0 [
      • Kozhenkov S.
      • Dubinina Y.
      • Sedova M.
      • Gupta A.
      • Ponomarenko J.
      • Baitaluk M.
      Biological networks 2.0 – an integrative view of genome biology data.
      ]. However, the currently available platforms artificially reduce the information to one biological level, i.e. integrating all data according to the transcriptome and changes in protein expression are treated as additional transcriptomic changes. Although those platforms are a promising step ahead, they are far from offering a comprehensive data integration.
      However, unraveling the tight and complex interactions between the diverse biological levels and dissecting the different signaling pathways activated during hepatocarcinogenesis will certainly lead to a whole new perception of HCC development and subsequently disclose novel strategies for the diagnosis and treatment of HCC. This also requires the consequent, systematic and standardized collection of tissue specimens from HCC patients (e.g., biopsies) for subsequent prospective molecular analyses, to condense the unprecedented new insights into tumor biology that originate from high-throughput technologies into clinically relevant information. Therefore, tight integration of expertise and knowledge from clinicians, biologists, and bio-informaticians will be essential to achieve this ambitious goal. The next years will demonstrate if hepatology can take the challenges of modern molecular medicine.

      Conflict of interest

      J.M. has nothing to disclose. A.T. is supported by a research grant from Roche.

      Acknowledgements

      Dr. Marquardt thanks Dr. Snorri S. Thorgeirsson and Valentina M. Factor for continuous support and helpful discussions. Dr. Andreas Teufel is currently supported by research grants from the Boehringer Ingelheim Foundation and Roche.

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