Biomarkers for virus-induced hepatocellular carcinoma (HCC).

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Contents lists available at ScienceDirect

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Review

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Biomarkers for virus-induced hepatocellular carcinoma (HCC)

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Shilu Mathew a,b,c, Ashraf Ali d, Hany Abdel-Hafiz e, Kaneez Fatima f, Mohd Suhail d, Govindaraju Archunan c, Nargis Begum a, Syed Jahangir a, Muhammad Ilyas g, Adeel G.A. Chaudhary d, Mohammad Al Qahtani b, Salem Mohamad Bazarah h, Ishtiaq Qadri d,⇑ a

Post Graduate Department of Biotechnology and Chemistry, Jamal Mohamed College, Tiruchirappalli 620 020, India Center of Excellence in Genomic Medicine Research, King AbdulAziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia Department of Animal Science, Bharathidasan University, Tiruchirappalli 620 024, India d King Fahd Medical Research Center, King AbdulAziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia e University of Colorado Denver AMC, Aurora, CO 80045, USA f IQ-Institute of Infection and Immunity, Lahore, Pakistan g Post Graduate Department of Botany, Jamal Mohamed College, Tiruchirappalli 620 020, Tamil Nadu, India h Department of Gastroenterology, School of Medicine, King AbdulAziz University Hospital, P.O. Box 80215, Jeddah 21589, Saudi Arabia b c

a r t i c l e

i n f o

Article history: Received 4 April 2014 Received in revised form 14 June 2014 Accepted 14 June 2014 Available online xxxx Keywords: Biomarkers Hepatocellular carcinoma Hepatitis viruses Prognosis

a b s t r a c t Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and is advanced by severe viral hepatitis B or C (HBV or HCV) as well as alcoholic liver disease. Many patients with early disease are asymptomatic therefore HCC is frequently diagnosed late requiring costly surgical resection or transplantation. The available non-invasive detections systems are based on the clinical utility of alpha fetoprotein (AFP) measurement, together with ultrasound and other more sensitive imaging techniques. The hallmark of liver disease and its propensity to develop into fully blown HCC is depended on several factors including the host genetic make-up and immune responses. While common symptoms involve diarrhea, bone pain, dyspnea, intraperitoneal bleeding, obstructive jaundice, and paraneoplastic syndrome, the evolution of cell and immune markers is important to understand viral induced liver cancers in humans. The circulating miRNA, cell and immune based HCC biomarkers are imperative candidates to successfully develop strategies to restrain liver injury. The current molecular genetics and proteomic analysis have lead to the identification of number of key biomarkers for HCC for earlier diagnosis and more effective treatment of HCC patients. In this review article, we provide latest updates on the biomarkers of HBV or HCV-associated HCC and their co-evolutionary relationship with liver cancer. Ó 2014 Elsevier B.V. All rights reserved.

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Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 HCC biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

Abbreviations: AFP, a-fetoprotein; HCC, hepatocellular carcinoma; HBV/HCV, Hepatitis B virus/C virus; DCP, des-gamma-carboxy prothrombin; GP73, Golgi protein; GPC3, Glypican-3; CD10, Cluster of differentiation 10; CD36, Cluster of differentiation 36; SAGE, serial analysis of gene expression; CALLA, common acute lymphatic leukemia antigen; LC–MS, liquid chromatography–mass spectrography; PIVKA-II, proteins induced by vitamin K absence; MMP, matrix metalloproteinase; 2D-PHAGE, 2-dimensional phage; MALDI-TOF, matrix-assisted laser desorption/ionization; SELDI-TOF, surface enhanced laser desorption/ionization time-of-flight; FNAB, fine needle aspiration biopsy; FNAC, fine needle aspiration cytology; FAT, fatty acid translocase; NAFLD, non-alcoholic fatty liver disease; CLD, chronic liver disease; CK7, Cytokeratin 7; CK19, Cytokeratin 19; NASH, nonalcoholic steatohepatitis; SFRP, secreted frizzled-related proteins; GRIPS, glypican-related integral membrane proteoglycans; ICC, intra hepatic cholangiocarcinoma; SCCA, squamous cell carcinoma antigen; FC-GP73, fucosylated GP73; GGT, c-glutamyl transferase; AFU, a-1-fucosidase; TGF-b1, transforming growth factor-b1; HCR2, human carbonyl reductase 2 enzyme; GOLPH2, Golgi phosphoprotein 2; TSGF, tumor-specific growth factor; EGFR, epidermal growth factor receptor; EGF, epidermal growth factor; HGF, hepatocyte growth factor; FGF, fibroblast growth factor; TNF, tumor necrosis factor; IL-6, interleukin 6; DEN, diethylnitrosamine; STAT, signal transducer and activator of transcription; CXCR, N-terminal cysteines of CXC chemokines receptor; TH2, T-helper 2; VEGF, vascular endothelial growth factor; miR, miRNA; SCARB1, scavenger receptor class B member 1; SCARB2, scavenger receptor class B member 2; PTEN, phosphatase and tensin homolog; PDC4, pyruvate decarboxylase regulator 4; RECKS, reversion-inducing cysteines-rich protein with Kazal motifs. ⇑ Corresponding author. Tel.: +966 535168434; fax: +966 26952076. E-mail addresses: [email protected], [email protected] (I. Qadri). http://dx.doi.org/10.1016/j.meegid.2014.06.014 1567-1348/Ó 2014 Elsevier B.V. All rights reserved.

Please cite this article in press as: Mathew, S., et al. Biomarkers for virus-induced hepatocellular carcinoma (HCC). Infect. Genet. Evol. (2014), http:// dx.doi.org/10.1016/j.meegid.2014.06.014

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2.1.

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3. 4.

Protein biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1. Alpha fetoprotein (AFP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2. Des-gamma-carboxy prothrombin (DCP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3. Golgi protein 73 (GP73) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.4. Neprilysin (CD10) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.5. CD36 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.6. Cytokeratin 7 (CK7) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.7. Cytokeratin 19 (CK19) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.8. Wnt pathway proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.9. Glypican-3 (GPC3) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Enzymes and isoenzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Growth factors and its receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1. Interleukin 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2. Interleukin 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3. Interleukin 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5. Nucleic acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.1. Circulating mRNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.2. Solid tumor mRNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.3. Micro RNA (miRNA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evolutionary relationship of proactive cytokines and inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction

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Each year more than 500,000 new patients are diagnosed with hepatocellular carcinoma (HCC) in the world El-Serag, 2011. HCC is one of the fastest rising cancers in the region of China, Southeast Asia as well as Africa (Parkin et al., 2005). An overview of the basic understanding of epidemiology, stages and its multidisciplinary character of the disease is necessary to conquer the challenges faced in clinical research (Zoulim and Locarnini, 2012). It is the third most deadliest and fifth most common cancer across the world. HCC is a multi-factor, multi-step and complex process which occurs due to persistent infection of hepatitis B virus (HBV) and hepatitis C virus (HCV) (Kumar et al., 2003). Besides, usage of alcohol, aflatoxin B1 consumption is another etiological agent in HCC. The fatality rate is quite higher due to rapid tumor progression. In countries where hepatitis is not endemic, most of the HCC are not primary but metastasis of cancer from other parts of the body. Hepatitis is the inflammation of the liver caused by hepatitis virus. It can also be caused by other infections, toxic substances and autoimmune diseases. There are 6 different types of hepatitis viruses including A, B, C, D, E, and G, from which type A, B, and C are the most common. Hepatitis B is transmitted through blood and infected body fluid while hepatitis C virus is spread only through exposure to an infected person’s blood (Mizejewski, 2001). Hepatic resection or transplantation is the only curative treatment available now for HCC patients (Mizejewski, 2001). Due to its asymptomatic nature, early detection of HCC is difficult and many patients present with advanced form of the disease at diagnosis and the prognosis for such patients remain poor. This review summarizes recent studies of potential biomarkers for diagnosis and to monitoring metastasis or recurrence of HCC.

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2. HCC biomarkers

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Biomarkers detectable in blood, urine, or tissue samples are used as molecular indicators for various types of diseases and their management. Their thresholds concentrations are used to detect the presence of various cofactors responsible for activating the diseases. Fluctuations in threshold concentrations have resulted in the prospective disease progression, diagnosis and guide therapy. Several biomarkers have been recognized for different diseases as well as

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research studies are still ongoing to fully understand and evaluate the clinical significance of utilizing such biomarkers. A lot of money and time can be saved as compared to empiric or other broad treatment approaches. Biomarkers could be more useful as a measurement tool to detect presence and progression of diseases, ultimately guiding them towards more targeted therapy. Understanding these markers is quite successful in detecting several type of cancer. They can also be used effectively in case of HCC. Molecular biomarkers were discovered using scientific platforms such as genomics along with proteomics. Fig. 1 depicts the various pathways activated when HCC is induced. Apart from genomics and proteomics platforms, biomarker assay techniques such as glycomics, metabolomics, secretomics and lipidomics are the most commonly used as techniques in identification of biomarkers. Northern blot, Gene expression, SAGE and DNA Microarray, Proteomic Approach involves 2D-PAGE, LC–MS, SELDI-TOF (or MALDI-TOF), Ab Microarray and Tissue Microarray are involved to develop the screening of biomarkers at various grades of the disease.

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2.1. Protein biomarkers

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2.1.1. Alpha fetoprotein (AFP) For decades, the most commonly used biochemical blood test to detect liver cancer is by screening for alpha fetoprotein (AFP). AFP is a glycoprotein with a molecular weight of 70 kDa, secreted by immature fetal liver cells and appears in cancer cells. AFP acts as a transporter molecule for several ligands, such as fatty acids, phytoestrogen, heavy metals, retinoid, steroids, flavonoids, dyes, bilirubin, dioxin and various drugs (Mizejewski, 2001). AFP is thought to exhibit immunosuppressive activity; as it plays a vital role in regulation of cell proliferation (O’Neill et al., 1982). This plasma protein is synthesized by yolk sac and by the liver. It is one of the chief proteins secreted during the fetus development and is present in very low levels in adults. Therefore AFP is one of the several tumor markers that are present at high level when a person is affected by cancer. It is mainly found in nonseminomatous germ cell tumor and in liver cancer. Patients with cirrhosis or chronic hepatitis also are reported with higher blood levels of alpha-feto protein (Fattovich et al., 2004). The level of AFP is higher in early stages of HCC, but it normalizes as disease progresses (Llovet et al., 2008). In general, it has been indicated serum AFP level more than 500 ng/mL, indicating the presence of HCC but

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Fig. 1. Schematic diagram depicting activation of various pathways activated and various signature molecules induced from HCC.

Fig. 2. Phylogenetic tree shows the evolutionary relationship of AFP among different species. Branch length is indicated in percentage (colored red). This tree was generated by using Multiple alignments: MUSCLE, alignment curation: Gblocks, construction of phylogenetic tree: PhyML and visualized by TreeDyn. Phylogram was generated by using approximate Likelihood-ration Test (aLRT): SH-like. The number below the Phylogram denotes the unit change in the amino acid sequence among the indicated species. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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lower AFP are also seen in benign hepatocellular carcinoma (Mizejewski, 2001). AFP is further subdivided into three different forms of glycoforms such as AFP-L1, AFP-L2 and AFP-L3, in which AFP-L3 is associated with large mass of cancer tissue, poor differentiation and malignant features (Lin et al., 2004). AFP-L3 is mostly useful in the differential diagnosis of individuals with total serum AFP 6 200 ng/mL, which may result from a variety of benign pathologies including chronic liver diseases (Zabora et al., 2001). A close evolutionary relationship was studied between some of the species synthesizing AFP. The FASTA sequence of AFP was retrieved from UniProtKB for different species and the phylogenetic analysis was done by using Phylogeny.fr (Anisimova and Gascuel, 2006; Dereeper et al., 2008, 2010; Guindon and Gascuel, 2003; Castresana, 2000). Fig. 2 shows an evolutionary relationship of AFP among different species with their Uniprot ID. Human, chimpanzee and gorilla are closely related as the branch lengths leads to the node. Rat and mouse protein sequence appears to be

a close relative of AFP, whereas the branch length for chick sequence is so long may be due to high amount of AFP sequence divergence.

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2.1.2. Des-gamma-carboxy prothrombin (DCP) DCP is an abnormal prothrombin protein induced by antagonist II (PIVKA-II), discovered in 1984 and its level increases in case of liver cancer (Liebman et al., 1984). DCP represents an abnormal product of liver carboxylation during the formation of thrombogen that acts as an autologous mitogen for HCC cell lines (Ikoma et al., 2002; Suzuki et al., 2005). Previous studies have shown that the combination of serum AFP and DCP was better for detecting HCC than using either AFP or DCP alone (Zhu et al., 2013).

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2.1.3. Golgi protein 73 (GP73) GP73 is a 73 kDa transmembrane glycoprotein that normally resides within the golgi complex. It is expressed in normal biliary

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epithelial cells whereas normal hepatocytes do not express this protein, and its expression is significantly increases in liver diseases including HCC (Kladney et al., 2002). Serum GP73 is a valuable biomarker for patients with HCC (Riener et al., 2009; Mao et al., 2010). 2.1.4. Neprilysin (CD10) Neprilysin (CD10) is metalloprotease enzyme present on cell surface, composed of 90–110 kDa and located at 3q21–27 of the human chromosome (McIntosh et al., 1999). It is enrolled in inactivating bioactive peptides. CD10 are also called as common acute lymphatic leukemia antigen (CALLA) plays a significant role in degrading the abnormal misfolding of amyloid beta sheets in nerve tissue (McIntosh et al., 1999). CD10 is considered in differentiating B cells, T cells as well as natural killer cells (Galy et al., 1995). CD10 antigen has been reported on the surface of normal early lymphoid progenitor cells, germinal center B cells within lymphoid tissue and in immature B cells (McIntosh et al., 1999). Abnormal methylation of CD10 results in expression of surface proteins in normal cells, precursor B cells and neoplastic B cells (McIntosh et al., 1999). Therefore loss in CD10 will increase the migration, growth and survival of cells contributing to neoplastic development and progression (Papandreou and Nanus, 2010). It is considered as an important marker for expression in B cell for hepatocellular and renal cell carcinoma. The expression of CD10 is more in metastatic melanomas rather than primary carcinoma (Bilalovic et al, 2004). The persistence of heavier inflammation in the liver is one of the common problems faced in HCC (Jia et al., 2007). Many genes encode for cytokines which are produced by immune cells to communicate either up or down regulation of the immune response (Jia et al., 2007). Normal liver tissue had a specific pattern in immune cell activities as they are involved in increasing the cytokines responsible for anti-inflammatory response and suppressing the immune action (Jia et al., 2007). Mainly the invasive role of cancer levels is necessary by stromal cells, which has both stimulatory and inhibitory factors that can associate functions like cellular adhesion, cell migration and expression of genes (Bemis and Schedin, 2000; Sternlicht et al., 1999; Tran et al., 1999), similarly the identical structure of CD10 with matrix metalloproteinase’s (MMPs) can facilitate a root for tumor cell growth as well as metastasis (Basset et al., 1994; Talvensaari-Mattila et al., 1998). Around 55 cases from United States were diagnosed with HCC and were studied further from formalin fixed sample; paraffin embedded blocks obtained by FNAB (fine needle aspiration biopsy) from the liver, and was immunostained using monoclonal antibody against CD10 antigen, out of which 86% (22 HCC patients) showed positive for canalicular staining pattern for CD10 whereas 13% (23 metastatic cancers) were positive for cytoplasmic and membranous staining pattern (Lin et al., 2004). Study comprising from liver biopsies of 164 UK patients, the CD10 stain canalicular pattern

was reported in liver tissues with mild fibrosis and inflammation, which becomes drastically down with increase in fibrosis or lobular inflammation (Shousha et al., 2004). Comparing samples extracted by FNAC (fine needle aspiration cytology) of 22 HCC cases (7 cases of HCC and 15 cases of metastatic) from India, also reported 68% positive for CD10 canalicular staining pattern (Ahuja et al., 2008). CD10 expressions is also clearly seen in differentiating HCC and non HCC cases by immunostaining antibodies against CD10 for 63 HCC cases and 25 non-HCC cases from Germany (Borscheri et al., 2001). Therefore CD10 is a useful biomarker stain for specifically determining HCC versus non HCC warrants further study (Chu and Arber, 2000).

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2.1.5. CD36 CD36 known as fatty acid translocase (FAT) is a membrane protein, present as fourth glycoprotein on the platelet surface as they are grouped under proteins that involve in lysosomal integral membrane protein II and SR-BI (type B scavenger receptors) (Abumrad et al., 1993; Janssen et al., 2001). Being a multifunctional complex, it takes part in lipid transport, removes apoptotic cells, cell adhesion, controls inflammation, atherosclerosis as well as diabetes (Silverstein and Febbraio, 2000). One of the major activities of CD36 is experimentally known for lipid homeostasis (Febbraio et al., 2002). Recent studies have noticed CD36 linked to synthesis of prostaglandin E2, calcium flux ion channels and phospholipase activation (Kuda et al., 2011). In tumor tissue, the expression of CD36 is poised peculiarly in distinguishing multiple cell type phenotypes such as promoting production of foam cells, activating cytokines, reactive oxygen species and blocks migration (Silverstein and Febbraio, 2009). This reduced expression of CD36 even in dendritic cells, also mediates extracting apoptotic cells thereby allowing tumor antigens into cytotoxic T cells, which results in attacking the immune system (McDonnell et al., 2010). Therefore any modulation in CD36 expression will actively spread carcinoma. CD36 is highly expressed in endothelial cells but spotting of this molecule was done using a novel antibody named MO30, which reacted with microvilli of cultured hepatoma and melanoma cells (Maeno et al., 1994). The expression of CD36 in 66 cases affected with HCV and 32 non diseased liver cases from Spain showed CD36 up regulated and linked with increase steatosis, hyperinsulineamia and insulin Q2 resistance (Pez et al., 2013). It has been found that translocation of CD36 fatty acid to the plasma membrane results in depositing liver fat in HCV and non-alcoholic fatty liver disease (NAFLD) affected patients (Miquilena-Colina et al., 2010). It has been recently suggested that the serum CD36 levels reflect the severity of CD36 expression on the Kupffer cells in patients with HCV-related chronic liver disease (CLD-C), and that the serum CD36 levels were associated with obesity (Himoto et al., 2013). Evolutionary study for different species synthesizing CD10 and CD36 is depicted in Fig. 3. The presence of overlapping species

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Fig. 3. Phylogram analysis for CD10 (colored purple) and CD36 (colored blue) species. The number below the Phylogram denotes the unit change in the amino acid sequence among the indicated species. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


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names for CD36 represents its sequence closely related branch lengths leading to nodes are very close to zero. Similar is noted for CD10, except for C-elegans that do not appear to be closest relative. 2.1.6. Cytokeratin 7 (CK7) Cytokeratin are proteins consisting of intermediate filament proteins, also known as keratins (Schweizer et al., 2006). They are expressed in both pairs of keratinized and non-keratinized epithelial cells, which constitute about 85% of mature keratinocytes. There active role is to take part in differentiation, tissue specialization and managing the structural function within the epithelial cells. Cytokeratin 7 (CK7) is also called as sacolectin, which is categorized under the subgroup of glandular epithelia and its tumors, similarly with transitional epithelium and transitional carcinoma (Monoclonal Antibodies to Cytokeratins). Cytokeratin also plays a key role by interfering production of interferon-dependent secondary proteins thereby reversing interferon induction and storing cells. It is present on the membrane surface of both normal and transformed cells (Cytokeratin 7 Antibody (LP1K)). The study of intermediate expression of filaments, for the cytokeratin in fibrolamellar carcinoma was done by using paraffin sections, reacted with monoclonal antibodies to provide signals, that can communicate with epitopes shared by cytokeratin polypeptides (Van Eyken et al., 1990). A case study was presented from Germany for two patients affected with HCC, were CK7 was strongly expressed in fibrolamellar carcinoma of the liver, where as in normal tissue it is present only in bile ducts (Van Eyken et al., 1990). Western blotting studies of the lymph node metastasis further confirmed the immunohistochemical data for CK7 (Van Eyken et al., 1990). An immunohistochemistry study done for 20 HCC cases from USA, in which epithelial cell adhesion cells showed positive expression for both the CK7 and CK9 for about 53% and 26% (Krings et al., 2013). Matsuura et al. have reported the higher level of immunohistochemical expression of CK7 in scirrhous HCC than in ordinary HCC (Matsuura et al., 2005). Similarly Fanni et al. have used CK7 to distinguish HCC from peripheral cholangiocarcinoma (CC) Fanni et al., 2009, suggesting that CK can be used as biomarkers for certain categories of epithelial differentiation of cells (Van Eyken et al., 1990). 2.1.7. Cytokeratin 19 (CK19) Cytokeratin 19 (CK19) is a 40kda protein and involved in structural integrity by maintaining the filament proteins. It is located specifically at the periderm, a layer that coats the epidermis. Keratin 19 is involved in signal transduction of B-lymphocyte activation, development and differentiation (Chu and Weiss, 2002). Therefore CK19 is a chronic keratins expressed in carcinoma, cleaved by caspase3 that releases the soluble fragments which are detected in cancer patients (Pujol et al., 1993). Antibodies to CK19 were diagnosed for 32 HCC cases from Hong Kong, were anti-CK19 produced distinctive staining of the bile ducts (Leong et al., 1998). CK19 was reported to be expressed in HCC and is correlated with HCC metastasis and recurrence. It has also been

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reported as a prognostic marker in HCC after operation (Yang et al., 2008). Evolutionary relationship between CK7 and CK19 secreting species is indicated in Fig. 4. There exist a close relation between mouse and rat with CK19, showing closeness towards human CK19 sequence, where as for CK7 represents strongly related sequence between rat and mouse protein sequence as well as among human and chimpanzee FASTA sequence as their branch length leading to these nodes are very close. The unit change in amino acid sequence among the species is 0.4%.

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2.1.8. Wnt pathway proteins Wnt signal transduction pathway is made up of proteins that pass signals from outside of a cell through cell surface receptors to inside of the cell (Cadigan and Nusse, 1997). These proteins are secreted by lipid-modified glycoproteins that are 350–400 amino acids in length. Wnt signaling was first recognized for its role in carcinogenesis, but has since been known for its function in embryonic development. Activation of this pathway results in two different cascades called non-canonical and canonical and thereby involving beta-catenin proteins (Pez et al., 2013). Deregulation is an earlier indication in HCC resulting in major aggressive phenotype. Transcriptomic and metabolomic datasets from human liver tissue representing nonalcoholic fatty liver disease (NAFLD) progression from normal, steatosis, nonalcoholic steatohepatitis (NASH) and compared to published data for HCC from USA. These data indicate an overlap in the pathogenesis of NAFLD and HCC where several classes of HCC related genes and metabolites are altered in NAFLD. Wnt signaling and several metabolites are different, thus implicating these genes and metabolites as mediators in the transition from NASH to HCC (Clarke et al., 2014). Another genotyping study from USA consisting of 425 chronically infected HCV veterans reported the activation of several genes from Wnt signaling pathway thereby resulting in hepatic fibrosis (Liu et al., 2013). An epigenetic study from China from secreted frizzledrelated proteins (SFRPs), one of the antagonists for Wnt signaling pathway, was found to be down regulated in hepatocarcinogenesis. Their study also suggests the silencing of SFRP1 constitutes activation of Wnt signaling pathway (Quan et al., 2013). Whole genome sequencing of 88 tumor/normal cases from USA has determined 62.5% of Wnt pathway altered resulting as one of the major oncogenic drivers for HCC (Kan et al., 2013). Therefore, the suppression of Wnt/beta-catenin signaling pathway exerts pressure on rapid proliferation and apoptosis of liver tissues.

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2.1.9. Glypican-3 (GPC3) Glypican 3 (GPC3) is member of protein family coded by GPC3 gene (Filmus and Capurro, 2013). These glypican-related integral membrane proteoglycans (GRIPS) are connected to the surface of cell through glycosyl-phosphatidylinositol linkage. They play a major role is to regulate several growth factors as well as it has the capacity to stimulate or inhibit its action through signaling

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Fig. 4. Phylogenetic tree depicting relationship between CK7 and CK19 (colored green and red box). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


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receptors (Glypican-3). GPC3 is expressed commonly in fetal liver cells and placenta but not expressed in adult liver tissue (Shafizadeh et al., 2008). Several studies have shown that the levels of GPC3 were higher in the serum of HCC patients in comparison with benign liver disease and healthy donors, suggesting GPC3 as a possible tumor marker for HCC (Febbraio et al., 2002; Anatelli et al., 2008). GPC3 is involved in stimulating tumor growth by activating the Wnt signaling pathway (Gao and Ho, 2011). Patients with hepatitis have higher percentage of GPC3 positive compared with GPC3 negative (Yu et al., 2013). Immunohistochemistry staining for 80 resection HCC cases from USA, also identified that the GPC3 was sensitive for diagnosing HCC but its poorly seen in highly well differentiated hepatocytes and fibrolamellar variant of HCC (Shafizadeh et al., 2008). In China, study was done by using 7D11 mAb for GPC3 in normal as well intra hepatic cholangiocarcinoma (ICC) samples, revealing 85% of expression of Glypican suggesting larger scale of clinical diagnosis can be done (Yu et al., 2013).

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2.2. Enzymes and isoenzymes

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Isoenzymes play an important role in tuning metabolism for developing tissue in the body. As we discussed earlier DCP level has better correlation with tumor resection and is known to be better marker for tumor (Weitz and Liebman, 1993). In the comparative study of various HCC markers, DCP is found as the most useful in predicting HCC with less sensitive to risk factors, like liver cirrhosis and thereby differentiates HCC from non-malignant carcinoma (Volk et al., 2007). Similarly, c-glutamyl transferase (GGT) in healthy cells are synthesized from bile duct, hepatic kupffer but it is more active in HCC tissue (Cui et al., 2003). They are concentrated in the liver to metabolize toxins and other drugs but are also present in gall bladder, kidney, spleen and pancreas. GGT tests mostly involve differentiating enzyme level in bile duct or liver disorder. A lysosomal enzyme called serum a-1-fucosidase (AFU) is involved in hydrolyzes fucose glycosidic linkage of glycol lipids and proteins in normal cells. It is reported to be elevated in serum of HCC patients. Measurement of AFU is beneficial in early diagnosis of HCC along with AFP (Tangkijvanich et al., 1999; Wei et al., 2000). Human carbonyl reductase 2 enzyme (HCR2) also called as DCXR is a detoxification enzyme against alpha-dicarbonyl and reactive oxidative stress in HCC and identified to be inversely correlated to different grades in HCC affected patients (Liu et al., 2006). It has been reported that disturbance in HCR-2 related detoxification is an important pathway towards progression of HCC in Chinese patients measured by immunohistochemistry and western blot techniques (Liu et al., 2006). Finally, Golgi phosphoprotein 2 (GOLPH2) is type II transmembrane protein present at cis and golgi cisternae, with its expression in human is witnessed in epithelial cells but in a poorly defined conditions, as it is cleaved and transported to extracellular spaces (Kim et al., 2012). This protein is detected with high sensitivity compared to AFP in the serum of HCC patients (Kim et al., 2012).

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2.3. Growth factors and its receptors

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Growth factors are naturally occurring substances that stimulates cellular growth, cellular differentiation and proliferation (Growth Factor). Different types of growth factors and their bioactive roles are discussed in this section. Transforming Growth Factor-Beta (TGF-b) is involved in polypeptide signaling molecule and are predominant form of growth factor present in humans. TGF-b plays an important role in the development of HCC. It is reported that TGF-b levels increased in cirrhotic livers of HCC patients (Okumoto et al., 2004). Tumor-specific growth factor (TSGF) is released by malignant tumor in the serum during the proliferation of the cells. Therefore, the serum levels of TSGF can be used

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as a marker for the presence of cancerous cell with high accuracy (Zhou et al., 2006). The epidermal growth factor receptor (EGFR) is transmembrane tyrosine kinase with its receptor family which includes erbB-1, c-erb-2, c-erb-3 and c-erb-4. These receptors bind to EGF, heparin-binding EGF and TGF-alpha family and associated with early recurrence in HCC (Ito et al., 2001). EGFR system acts as ‘signaling hub’ where diverse types of survival signals and epidermal growth signals converge (Berasain et al., 2011). Hepatocyte growth factor (HGF) is a cytokine that facilitates multiple from embryonic development till liver regeneration. It is produced by various tissues such as neoplasms and it provides stimulus for movement of malignant cells by autocrine and paracrine mechanism. The HGF receptor is identified as oncogene c-met key to facilitate cell invasion. It is recognized as imperative not only for liver tissue growth but includes metastasis also (Jiang et al., 1993). Therefore HGF involved in molecular activity in hepatic carcinoma and reduced overall survival rate (Osada et al., 2008). Fibroblast growth factor (FGF) is a soluble heparin-binding polypeptide, whose elevated levels are also known for decreased disease free-survival (Poon et al., 2001). FGF is reported to increase the synthesis of plasminogen activators and collagenases in cultured cells, which resembles tumor invasion (Montesano et al., 1986). Since these FGF have strong roles in cell migration and proliferation, its expression have vital character in the development of solid cancerous tumor, where a sustained vascular platform is essential (Chow et al., 1998). Targeted inhibition of fibroblast growth factor (FGF) with lenalidomide showed promising activity in HCC cases (Safran et al., 2013). Recent study has reported that FGF protein expression is an effective predictor of early recurrence and a marker for poor prognosis of HCC (Hyeon et al., 2013).

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2.4. Cytokines

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Cytokines are small, 5–20 kDa, proteins that has an important role in cell signaling. Cytokines involve as interferons, lymphokines, interleukins, tumor necrosis factor (TNF) and chemokines. They are synthesized by wide range of cells including mast cells, macrophages, endothelial cells, stromal cells, B lymphocytes and T lymphocytes as well as fibroblast cells (Lackie, 2010). These signaling molecules mediated by receptors that act as a pillar for immune system to spread responses to the infected part of cells. Liver is known as the central region of cytokine due to hepatocytes that are highly susceptible to cytokine activity in various pathophysiological and physiological processes. However, the nonparenchymal kupffer cells (KCs) are able to produce cytokines that can act on other parts of the body (Ramadori and Armbrust, 2001). There is high evidence that cytokines inflammate and causes apoptosis as well as necrosis of liver cells. On the other lane, they are as experts for liver tissue regeneration after injury (Ramadori and Armbrust, 2001). Therefore, inhibition of this mediator might impair hepatic recovery system.

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2.4.1. Interleukin 6 Interleukin (IL-6) is a multifunctional cytokine that plays a critical role in hematopoiesis, as well as in the differentiation and growth of different cell types such as endothelial cells, neuronal cells, keratinocytes, ostoclasts and ostoblasts. They are secreted by T cells, macrophages to stabilize immune response. Smooth muscle cells also produce cytokines for pro-inflammatory actions. IL-6 blood serum level has been reported elevated in patients with severe liver diseases such as alcoholic hepatitis, viral hepatitis (HCV and HBV) as well as steatohepatitis. Wong et al. has shown that patients who subsequently developed HCC had raised IL-6 levels 2–3 years before HCC development (Wong et al., 2009). Disruption of IL-6 gene in transgenic resulted in reduction DEN-induced hepatocarcinogenesis suggesting that IL-6 play an significant role in HCC (Naugler et al., 2007). A study done by Cressman et al.,

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Fig. 5. Evolutionary tree of interleukin family members. The unit change in the amino acid sequence among the IL species is 1%. Each group of IL8, IL6 and IL10 are colored blue, brown and green box. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) 514 515 516 517 518 519

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reports targeted disruption of IL-6 done for mice, that impaired liver regeneration, followed by liver necrosis and failure. IL-6 deficient mice returned with STAT3 binding, gene expression hepatocyte proliferation when treated again with IL-6 and thus prevented liver damage. As a result, ensuring IL-6 as a critical component for liver regeneration (Cressman et al., 1996). 2.4.2. Interleukin 8 Interleukin 8 is a pro-inflammatory cytokine involved in the cellular response to inflammation. IL-8 is produced by a wide variety of cells, including neutrophils, monocytes, fibroblasts, and endothelial cells (Wang et al., 2014; Yahya et al., 2013). IL-8 mediates its biological function by interacting with specific G-protein-coupled receptors such as CXCR1 and CXCR2. A study explored in Chinese population for IL8 polymorphism with HCC cases, resulted in high serum level compared to healthy controls (Welling et al., 2012). Recent Egyptian study on patients with chronic Hepatitis C virus (HCV) infection has shown that serum levels of IL-8 were higher in patients with HCV-associated HCC compared with control subjects (Elewa et al., 2010). Similarly, high levels of IL-8 have been found in study performed on 90 HCC cases and 180 cirrhotic controls from USA (Welling et al., 2012). Therefore, the ability to measure IL-8 level in serum could be a useful marker of HCC in patients. 2.4.3. Interleukin 10 Interleukin 10 (IL-10) is a pleiotropic cytokine produced by Thelper 2(TH2), macrophages and B-lymphocytes and can stimulate or inhibit the immune response (Yin et al., 2011). Recently, it has been reported that the serum levels of IL-10 is significantly elevated in patients with HCV-associated HCC and IL-10 take part in the development of HCC with suppression of immune response. These immune suppressive effects of IL-10 may play a critical role in the development of HCC by suppressing interferon production and enhancement of tumor cells metastatic potential. It has been shown that IL-10 values are correlated significantly with the tumor size suggesting that IL-10 levels can be used as tumor markers and contribute to the deferential diagnosis in HCC patients (Othman et al., 2013). Evolutionary relationship for IL-8, IL-6 and IL-10 was also analyzed by retrieving protein sequence from Uniprot (See Fig. 5). Clades of IL-10, IL-6 and IL-8 are nested within one another, forming

a nested IL hierarchy. The lengths of node represent the substitution rate defined in percentage of substitution for alignment length. Branch length is indicated in percentage (colored red). The branch length for human IL-8 sequence shows closer identity towards monkey, rhesus monkey and macaque monkey compared to other species which are diverged high. IL-6 also depicts closer variation with human IL6; whereas IL-10 has wide distribution of amino acid sequence between chick, human, mouse as well as rat sequence.

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2.5. Nucleic acids

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2.5.1. Circulating mRNA Circulating mRNAs provide a useful marker to investigate various pathological and physiological conditions of HCC patients and can be used for early diagnosis. Using reverse-transcription polymerase chain reaction (RT-PCR), AFP mRNA has been detected in blood circulation in HCC patients (Matsumura et al., 1994). Hepatitis B infected patients were strongly associated with AFP mRNA in blood (Montaser et al., 2007). Blood circulating Insulin-Like Growth Factors I and II (IGF-II) mRNA had diagnostic value for HCC, as they are necessary for development and liver regulation. Their expression level was studied in rats during hepatic development and carcinogen, with high levels of IGF-I mRNA detected compared to IGFII mRNA (Himoto et al., 2005). c-Glutamyl transferase (GGT) mRNA is present in liver tissues and serum of healthy humans as well as in patients with different grades of liver disease. They are further classified into type A and type B, in which type B GGT mRNA are spotted in cancerous and non cancerous tissue sample but with poor outcome (Behne and Copur, 2012). Albumin mRNA is another type synthesized by liver to detect in plasma and is known to be a sensitive diagnostic marker for HCC. It can be detected by using in-situ hybridization in paraffin embed tissue and shows positive for non-cirrhotic, focal nodular hyperplasia, hepatocellular carcinoma, hepatoblastoma and hepatocellular adenomas (Behne and Copur, 2012).

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2.5.2. Solid tumor mRNA It has been shown that RNA expression profiles are useful markers for classification of solid tumors including HCC. Several investigators have reported that livers from HCC patients have a different expression profiles in comparison with the livers from

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control subjects Kim et al. reported a molecular signature containing 273 significantly altered genes in HCC. Among them, 12 genes encoded secretory proteins detectable in sera, which may be used as markers for early diagnosis of HCC (Jia et al., 2007; Kim et al., 2004; Budhu et al., 2006). 2.5.3. Micro RNA (miRNA) MicroRNAs (miRNAs) are small noncoding RNAs involved in the regulation of gene expression (Gramantieri et al., 2008). They are synthesized from their respective genes or from introns. Their function is activated by base pairing with mRNA complementary sequence or mRNA degradation thereby resulting in gene silencing (Matsumura et al., 1994). About 1000 miRNAs are encoded in our human genome (Montaser et al., 2007). These molecules act as oncogenes or tumor suppressor genes by controlling the key proteins associated with cell signaling pathway in cancer metabolism (Himoto et al., 2005). Recently, it has been reported that miRNA might be very useful biomarkers, because they are very stable and are present in the blood (Giordano and Columbano, 2013). Preclinical and clinical studies demonstrated that cancer affects the levels of circulating miRNA and that specific miRNAs can be associated with specific tumors (Giordano and Columbano, 2013). In HCC, miRNAs have been shown to be involved in the deregulation of many signaling pathways including p53, P13K/AK/mTOR, WNT/ b-catenin, MET, MYC, RAS/MAPK and transforming growth factors (Bartel, 2009). Recent miRNA expression profiles have identified molecular signatures associated with progression, prognosis, and response to treatment. Recent study has found three up regulated miRNAs in HCC samples, whereas five were down regulated. In addition, the expression levels of miR-92, miR-20, and miR-18 were inversely correlated with the degree of HCC (Murakami et al., 2006). Several miRNAs have been reported to be involved in HCC including miR-142, miR-223, mi-122, miR-199, miR-221 and miR-21 (Chen and Rajewsky, 2007). The expression level of miR-21 is highly elevated in human cancers (Yu et al., 2013; Bartel, 2009) and thereby promoting carcinoma by targeting PTEN, PDCD4 and RECKS (miRBase, 1824). Similarly high level of expression is all viewed in culture supernatants of HCC cell lines with miR-15b, miR-21, miR-130b and miR-183 (Morozova et al., 2012). miRNA is not only found in serum and plasma but also they are found in the urine of HCC patients suggesting that more work has to be done to select the best type of samples to be used for diagnosis (Callegari et al., 2013). 3. Evolutionary relationship of proactive cytokines and inflammation Understanding the relationship between immunology, diagnosis and treatment for viral disease is a critical factor. Large animals are interesting group of studies, as they represent great diversity in the control of innate immunity and its dependence on adaptive immunity (Bubanovic and Najman, 2004). Cytokines are key molecules responsible for host response to various types of infections, immune response, inflammation as well as trauma (Dinarello, 2000). These molecules make disease worse (proinflammatory) as well as serve in rescuing inflammation and promote healing (anti-inflammatory) Dinarello, 2000. They have been identified and extensively studied in mammal, but a very few knowledge is known about their presence in vertebrate group (Bubanovic and Najman, 2004). Homolog’s of cytokine has also been found within jawless vertebrates (Bird et al., 2002). Cytokines such as IFN, IL and TGF-b is identified in reptiles, birds, amphibians as well as bone fish (Bubanovic and Najman, 2004). IL-10 related T cell-derived inducible factor (IL-TIF) was recognized to have 79% amino acid homology to humans by two groups and designated as IL-22

(Kumar et al., 2013). Wide evidence has suggested close functional relationship and a common evolutionary origin for alpha-feto protein and albumin as they have similar gene structure (Dugaiczyk and Harper, 1983). Baker et.al compared rat, mouse, bovine and human AFP domain with albumin domain, by computer program designed to quantify relationship origin of the protein, revealing that each domain is much conserved. This study suggested the change in amino acid substitution among the domains of albumin and AFP during the past 400 million years, since they diverged from common ancestors (Baker, 1988). A comparative study for CD36 protein structure and gene locations were determined by using data from various vertebrate genome projects, that shared about 53–100% uniqueness as compared to 32% identity with CD36 super family members like SCARB1 and SCARB2 (Holmes, 2012). A phylogenetic analyses was examined to study the potential relationship and origins of CD36 gene especially SCARB1 and SCARB2 in vertebrates, which propose that CD36 originated in ancestral genome and further duplicated subsequently resulting in three vertebrate CD36 gene family members such as CD36, SCARB1 and SCARB2 (Holmes, 2012). Qadri et al. have shown activated expression CD3 in HCV expressing cells and this protein may be exploited in future to explore as possible marker in HCV-induced liver disease (Qadri et al., 2012). With the evolution of vertebrates, there seems dramatically growth of regulatory cell with its multiple functions in controlling of immune response. It has been studied in lower vertebrates, cytokine network of immune response consist cytokines which are mainly present in mammal known to be pro-inflammatory cytokines (Dinarello, 2000). Evolution relationship of cytokines of immune system in birds is mostly similar to mammalian (Bubanovic and Najman, 2004). Diversification of cytokines with the evolution of suppressive cytokines, and their control mechanism can be defined as another output of adoptive immunity (Dinarello, 2000). There are important correlations between adoptive immunity as well as multiple cytokines in various classes of vertebrates, which associate anti-tumor immunity failure and foremost source for different incidence of neoplasm in vertebrates.

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4. Summary and conclusions

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Treatment and management of HCC continues to be a challenging task. There are many molecular abnormalities involved in the development and progression of HCC. Current molecular research confirmed that HCC tissue from different individuals have various phenotypic differences. However the features that unite HCC along with HBV and HCV infections may result in improved hepatocyte turnover that occurs to replace immunologically affected cells (Block et al., 2003). Primary hepatocellular carcinoma (PHCC) refers to HCC originally within the organ liver (Block et al., 2003). There occurs high mortality associated with HCC due to non-capsular region of liver is deficient from sensory fibers and therefore results in symptoms for HCC repeatedly occur late PHCC, resulting in 5-year survival rate of less than 5% (Mason and El-Serag, 1999). Individuals persistently infected with HBV have a risk of death to PHCC between 10% and 25% (Mason and El-Serag, 1999; Evans et al., 1998; Montalto et al., 2002). Lifetime risk patients chronically affected with HCV are between 2% and 7% (Bisceglie, 1997; Liang et al., 2000). To date, many studies have investigated the oncogenic pathway mechanism behind development of HCC thought to accelerate the chance has been identified are Wnt/beta catenin, c-met, phosphoinositol-3kinase, myc and cellular proliferation (El-Serag and Rudolph, 2007). Activation of AKT signaling promotes tumor formation by suppressing transforming growth factor induced apoptosis (El-Serag and Rudolph, 2007). The tissue level of some polypeptides including aldehyde-dehydrogenase (ADH), chymotrypsin antitryp-

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Table 1 Potential diagnostic and prognostic HCC biomarkers. Potential biomarker

Diagnostic application

Expression pattern in HCC patients

References

AFU AFU + AFP TGF-b1* VEGF AFP* AFP-L3* HSP70 SCCA GP73 GPC3* FC-GP73 GGT AFP-mRNA DCP HCBR2 GOLPH2 HGF TSGF

Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Upregulation Downregulation Upregulation NA NA

Tangkijvanich et al. (1999) Tangkijvanich et al. (1999) Okumoto et al. (2004) Poon et al. (2001) Chen et al. (1984) and Farinati et al. (2006) Khien et al. (2001) Decaens and Fartoux (2011) Bertino et al. (2011) Tangkijvanich et al. (1999) and Capurro et al. (2003) Capurro et al. (2003) Capurro et al. (2003) Cui et al. (2003) Matsumura et al. (1994) and Jeng et al. (2004) Weitz and Liebman (1993) and Marrero et al. (2003) Liu et al. (2006) Riener et al. (2009) and Marrero et al. (2003) Osada et al. (2008) and Korn (2001) Zhou et al. (2006)

EGFR family* miR-21

Diagnosis Diagnosis Prognosis Prognosis Diagnosis Diagnosis Prognosis Diagnosis Diagnosis Diagnosis Diagnosis Diagnosis Prognosis and Recurrence Early diagnosis and prognosis Prognosis Tumor aggressiveness Prognosis and disease recurrence Diagnosis complementary to other markers Early recurrence Diagnosis

Irregular Upregulation

miR-122* miR-29 miR-500

Prognosis Prognosis Prognosis

Downregulation Downregulation Downregulation

Ito et al. (2001) Rfam:miRNA, Ferracin et al. (2010), Ura et al. (2009), Ladeiro et al. (2008) and Chung et al. (2010) Ladeiro et al. (2008) and Wei et al. (2013) Ura et al. (2009) and Wei et al. (2013) Wei et al. (2013)

NA – Data not available: There is not clear evidence available which suggests that above biomarkers are induced by only virus. But mostly are involved in indirect way in inducing HCC. AFU, a-1-fucosidase; AFP, alpha-fetoprotein; HCC, hepatocellular carcinoma; HBV/HCV, hepatitis B virus/C virus; TGF-b1, transforming growth factor-b1; VEGF, vascular endothelial growth factor; HSP 70, heat shock protein 70; SCCA, squamous cell carcinoma antigen; GP73, golgi protein (Glypican) 73; GGT, c-glutamyl transferase; DCP, desgamma-carboxy prothrombin; GPC3, glypican-3; FC-GP73, fucosylated GP73; HCBR2, human carbonyl reductase 2; GOLPH2, Golgi phosphoprotein 2; HGF, hepatocyte growth factor; TSGF, tumor specific growth factor; EGFR, epidermal growth factor receptor; miR, miRNA. * Marker linked with virus.

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sin, c-reactive proteins have been reported by immunostaining HCC tissue (Hurlimann and Gardiol, 1991). Similarly p53 mutations is characteristic in HCC, present 10–20% of tumor characterized is associated with significant geographical and environmental factors (Hsu et al., 1993). Whereas virus induced HCC causes hepatocyte injury, chronic inflammation, and accumulation of mutations in the host genome resulting in chromosomal rearrangements, genetic alteration, activation of oncogenes and inactivation of tumor suppresser genes (But et al., 2008) and activation of proinflammatory cytokine, interleukins (Cua et al., 2007). Both HBV and HCV viral infection increase the likelihood of developing liver cancer. It is reported that about half of liver cancer cases are attributable to HBV, and one third of liver cancer cases are attributable to HCV (Sanyal et al., 2010). Though it is not easy to distinguish between clinical characters ensuing from hepatitis B and C as well as both as the cause for PHCC. Therefore better understanding of etiology of HCC may offer best chance of achievements earlier diagnosis and intervention, which ultimately improve the risk of developing HCC induced through viral infections. Therefore, it is important to identify actuate and useful biomarkers for early diagnosis of HCC and correct treatment decisions. As we reviewed in this article, several useful markers have been reported and are summarized in Table 1. It is difficult to find one marker that is both specific and sensitive. Thus a combination of at least two or three markers is highly recommended for more specific and sensitive diagnosis for HCC. HCC biomarkers AFP-L3 and DCP are intended to be used in in vitro diagnostic as they are shown to be specific to HCC and their combined use aids in early detection of chronic liver disease. Various studies have shown the clinical utility of the HCC biomarkers is improved with the combination of biomarkers (Arii et al., 2010; Choi et al., 2013; Ertle et al., 2013; Nomura et al., 1999; Shimauchi et al., 2000; http://www.wakodiagnostics.com/hccbio-

markers.html). The AFP-L3 and DCP biomarkers are both complementary and are effective in early detection of HCC. The combined use of these tests is currently available with a single test code as laboratories can measure levels of AFP-l3 and DCP with a single serum sample on a single analyzer (Choi et al., 2013; Kagebayashi et al., 2009). Increase in concentration of AFP-L3 isoform indicates PHCC and germ cell tumor. It is more specific than total AFP and other forms of AFP isoforms in HCC patients (Sato et al., 1993). The test represents the ratio of AFP-L3 to total AFP in percentage. Higher levels of AFP-L3 values (P10%) have indicated associated with 7-fold risk of HCC within next 21 months (Liebman et al., 1984). Similarly elevated DCP (P75 ng/ml) is associated with 5-fold of HCC risk (http://www.wakodiagnostics.com/pivka_dcptest.html). Similarly a meta-analysis was conducted by Hu B et al., by using area under curve (AUC) to evaluate the diagnostic accuracy of combination of biomarkers. Combination of AFP+GP73 is better to AFP in diagnosing HCC as well as differentiating HCC patients from nonHCC patients and can be considered as useful diagnosis biomarker (Hu et al., 2013). Squamous cell carcinoma antigen (SCCA) a family of serine proteases along with total AFP can be potential for combinational screening leading to an accuracy of 90% (Giannelli and Antonaci, 2006). Though many tumor markers have been reported in various studies, but none of them are completely optimal. Therefore combinations of two or three HCC biomarkers are recommended for highly specific and sensitive diagnosis of HCC. For decades the most widely used biochemical blood test used to detect liver cancer is detection of alpha fetoprotein (AFP) which is made by immature fetal liver cells and appears in cancer cells (Benowitz, 2007). Serum AFP levels of more than 400 ng/ml is considered diagnostic but this much value is observed only in very few cases (Behne and Copur, 2012). Also the false negative rate is quite high with early stage HCC. Even in chronic HCC the AFP level found


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to be normal in 15–30% of patients (Singhal et al., 2012). AFP is often found to be elevated for reason other than cancer including liver injury so it does not necessarily indicate the presence or absence of liver cancer (Benowitz, 2007). Several biomarkers are in clinical trials now but only AFP L3 or fucosylated is FDA approved. With the increase of AFP-L3 chance of liver cancer also increases. Currently, alpha-fetoprotein blood test is clinically offered and this test can also be used in patients already diagnosed with HCC that is available at less than 1 US $/test. The AFP level can help in determining if the treatment is effective as the AFP level should go down. Other blood tests such as liver function test, blood clotting tests, tests for viral hepatitis, kidney function test and complete blood count test are presently used as they measure levels of certain substances in the blood that determines the function of the liver. The other two promising biomarker candidates are DCP and GP73 (Benowitz, 2007). DCP which is a precursor of a liver protein that helps in blood clotting. Its level increases in case of liver cancer. DCP is found to be more accurate than AFP in diagnosis of liver cancer. Other promising candidate is GP73 an early detection biomarker for liver disease and one of several potential glycoprotein biomarker for liver disease. Poorly designed studies, lack of diverse population studies have hampered the progress of biomarker discovery. At present the testing for AFP + PIVKA-II in intervals of 3 months is more effective in diagnosing early stages of HCC than the 6 months interval of AFP which is normally used (http:// www.cancer.gov/clinicaltrials). At the present the screening for HCC in patients with liver cirrhosis is conducted by ultrasound and measurement of AFP. In this trial the biomarkers AFP- L3 and DCP are calculated in order to receive information about the course of these biomarkers before the detection of a HCC nodule. The futures of developing biomarkers for HCC must describe a consensual sorting of HCC with a common terminology based on genomic and well-established molecular information as well as to identify prognostic markers in HCC and predictors to treatment response and to develop a prospect plan to further integrate additional molecular and clinical information There has been marked advancement in the treatment of HCC. However, efficient treatments are limited to patients with less advanced HCC. The diagnosis of HCC at an early stage is still a must for enhanced prognosis. To address this trouble, a variety of screening modalities are used, including measurement of alpha-fetoprotein (AFP) and ultrasonography (US) at regular intervals in high-risk populations. Other markers have been used in some counties, but largely are not commercially available. MiRNA 122 can be good blood based marker to be developed in the future. Unfortunately, poor sensitivity and specificity of AFP and the operator-dependency of US limit the value of either test to diagnose early-stage lesions. Current developments in geneexpressing microarrays and proteomics assure even more potential diagnostic options to improve the prediction of HCC.

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