Laser Capture Microdissection in Comparative Proteomic Analysis of Hepatocellular Carcinoma

Laser Capture Microdissection in Comparative Proteomic Analysis of Hepatocellular Carcinoma

CHAPTER 25 Laser Capture Microdissection in Comparative Proteomic Analysis of Hepatocellular Carcinoma Hong-Yang Wang International Cooperation Labor...

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Laser Capture Microdissection in Comparative Proteomic Analysis of Hepatocellular Carcinoma Hong-Yang Wang International Cooperation Laboratory on Signal Transduction Eastern Hepatobiliary Surgery Institute The Second Military Medical University Shanghai 200438, People’s Republic of China

I. Introduction II. Rationale III. Methods A. Preparation of Liver Tissue Sample B. Laser Capture Microdissection C. 2D PAGE D. Silver Staining and Image Analysis E. Nano-Flow ESI-MS/MS Identification of DiVerentially Expressed Proteins F. Immunohistochemical and Western Blot Analyses IV. Materials V. HCC Samples VI. Discussion A. LCM in Sample Preparation for Comparative Proteomics of HCC B. DiVerences in Protein Expression Between Surrounding Nontumorous Tissues and HCC Tissues C. DiVerential Proteomic Analysis of Liver Tissues of HCC Patients D. Immunohistochemical and Western Blot Analyses for Prx II in HCC VII. Summary References

METHODS IN CELL BIOLOGY, VOL. 82 Copyright 2007, Elsevier Inc. All rights reserved.


0091-679X/07 $35.00 DOI: 10.1016/S0091-679X(06)82025-X


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Hepatocellular carcinoma (HCC) is one of the most frequent visceral neoplasia worldwide and is a multifactorial and multistage pathogenesis that finally leads to the deregulation of cell homeostasis. A main problem with the analysis of HCC tissue samples, either at the level of proteins or genes, is the heterogeneous nature of the sample. Laser capture microdissection (LCM) may allow the more ready identification of diVerences in protein expression of selected cell types or areas of tissue and allows procuring a microscopic region as small as 3–5 mm in diameter. Here we applied the LCM to the isolation of hepatocyte for comparative proteomic analysis of hepatitis B-related HCC and surrounding nontumorous tissues. Proteome alterations were observed using two-dimensional polyacrylamide gel electrophoresis and electrospray ionization tandem mass spectrometry, and alterations in the proteome were examined. LCM was found to eliminate hemoglobin from homogenization of the HCC tissue, demonstrating its capacity of resolving the problem of heterogeneity and contamination in tissue samples. Twenty protein spots were selected and eleven proteins significantly altered in the surrounding nontumorous tissues and HCC tissues. Of the proteins that were selected, peroxiredoxin 2, apolipoprotein A-I precursor, 3-hydroxyacyl-CoA dehydrogenase type II, and 14.5-kDa translational inhibitor protein appear to be novel candidates for useful hepatitis B-related HCC markers. This study indicated LCM is a useful technological method in proteomic study of cancer tissue. The proteins revealed in this experiment can be used in the future for studies pertaining to hepatocarcinogenesis, or as diagnostic markers and therapeutic targets for HCC associated with Hepatitis B virus infection.

I. Introduction Hepatocellular carcinoma (HCC) is one of the most frequent visceral neoplasia worldwide, with an estimated 564,000 new cases in 2000 (Parkin et al., 2001). It is known that most HCCs develop from chronic inflammatory liver disease due to the Hepatitis B virus (HBV) infection, Hepatitis C virus (HCV) infection, and exposure to carcinogens such as aflatoxin (Stuver, 1998). Like other cancers, the development of HCC is a multifactorial and multistage pathogenesis that finally leads to the deregulation of cell homeostasis (Harris, 1994, 1996). Although the molecular interactions between hepatocytes and the specific etiologic agents of HCC are being elucidated in the past decade (Brechot, 1998; Diao et al., 2001; Smela et al., 2001), the mechanism of hepatocarcinogenesis is unclear. The term proteome was first stated to describe the set of proteins encoded by the genome (Wilkins et al., 1996). With the completion of the draft sequence of the human genome (Lander et al., 2001; Venter et al., 2001), there is a great deal of interest in the use of functional genomics, especially gene expression-profiling techniques such as DNA microarrays and proteomics, to identify cancer-associated genes and their protein products. In contrast to the genome, the proteome is dynamic and is in constant flux because of a combination of factors. Proteomic technologies allow for identification of the protein changes caused by the disease process in a relatively

25. Laser Capture Microdissection in Comparative Proteomic Analysis


accurate manner. At the protein level, distinct changes occur during the transformation of a healthy cell into a neoplastic cell, including altered expression, diVerential protein modification, changes in specific activity, and aberrant localization, all of which may aVect cellular function. Identifying and understanding these changes are the underlying theme in cancer proteomics (Srinivas et al., 2001). Two-dimensional polyacrylamide gel electrophoresis (2D PAGE) has been the mainstay of electrophoresis technology for a decade and is the most widely used tool for separating proteins. The use of narrow immobilized pH gradients (IPG) for the first dimension increases resolving power and can help to detect low-abundance proteins. Electrospray ionization tandem mass spectrometry (ESI-MS/MS) allows the analysis and identification of very small amounts of protein isolated from the gel (Kovarova et al., 2000; Neubauer et al., 1998). These advances have been combined to make 2D PAGE a more attractive option for the analysis of complex protein mixtures. However, a main problem with the analysis of tissue samples, either at the level of proteins or genes, is the heterogeneous nature of the sample. Laser capture microdissection (LCM) was used as a promising new approach to collect specific cell types from a tissue sample (Bonner et al., 1997; Craven et al., 2002; Zhou et al., 2002). This allows the selective, relatively rapid microdissection of specific areas of tissue using a low-maintenance system that is easy to operate (Emmert-Buck et al., 1996). Such an approach may allow the more ready identification of diVerences in protein expression of selected cell types or areas of tissue and allows procuring a microscopic region as small as 3–5 mm in diameter. LCM is rarely applied to the analysis of HCC, even proteomic characterization is recently being applied to a few studies on human HCC cell lines (Yu et al., 2000) and HCC tissues (Lim et al., 2002). It is possible to use LCM to capture cancer structures with high purity, but the amount of samples collected by LCM is often limited, complicating proteomic analysis by 2D gel-based methods. These limitations can be alleviated by the integration of LCM with the highly sensitive ESI-MS/MS technology. We formerly combined the LCM with isotope-coded aYnity tag (ICAT) technology and 2D liquid chromatography to investigate the proteomes of HCC (Li et al., 2004). In this chapter, we present the isolation of cancerous tissues using LCM approach, and the systemic identification of extracted proteins by 2D PAGE and ESI-MS/MS. The presence of peroxiredoxin 2 (Prx II) in the plaques was confirmed by immunohistochemistry and Western blot, Prx II was found to be a novel component of HCC in human specimen. These studies demonstrate a powerful new approach for achieving comprehensive analysis of the proteome of HCC.

II. Rationale LCM techniques have dramatically increased the ease of isolating specific cells from complex tissues for subsequent molecular analyses. Tissue preparation and microextraction protocols allow LCM microsamples to undergo quantitative proteomic analyses.


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III. Methods A. Preparation of Liver Tissue Sample All the HCC samples were rinsed in sterile phosphate-buVered saline (PBS) and snap frozen in liquid nitrogen within 30 min. Sections (10 mm) were subsequently cut using a Leica CM 1900 microtome. Each slide was stained by hematoxylin and eosin. Both the hematoxylin and eosin solutions contained complete protease inhibitor cocktail.

B. Laser Capture Microdissection Sections (10 mm) of frozen liver tissue from each sample above were cut and divided into two groups: one was placed directly in lysis buVer (described below) as the control; the other was placed on the slides for being applied with LCM. The slides were stained as described above. Then the sections were alternatively subjected to laser capture. The sections were captured using a 60-mm diameter laser beam at 30- to 80-mW power with pulse duration of 50 msec and machine gun mode with a laser-firing frequency of 1 shot per 500 msec. Typically, 500 shots were taken per cap. Each shot contained 20 cells and 10,000 cells were obtained per cap. The obtained samples were placed in lysis buVer immediately.

C. 2D PAGE Sample lysis buVer was based on the urea/thiourea mix previously described by Rabilloud et al. (1997). Samples were centrifuged at 40,000  g for 40 min at 4  C, the supernatant aliquoted and stored at 80  C until analysis. Protein concentration was determined with a Bio-Rad protein assay kit. First-dimensional electrophoresis IEF was carried out by IPGphor (Amersham Pharmacia Biotech, Uppsala, Sweden). The 18-cm IPG strips (pH 3–10 nonlinear) and samples were applied overnight using the in-gel rehydration method as previously described (Gorg et al., 2000). Samples containing 100- to 200-mg protein for analytical gels were diluted to 350 ml with rehydration solution, which contained 8-M urea; 2% CHAPS; 100-mM DTT; 0.5% (v/v) pH 3–10 IPG buVer. Proteins were focused initially at 400 V for 20 min, and then the voltage was increased to 8000 V within 3 h, and maintained at 8000 V for 7 h for a total of 60 kVh. After the firstdimensional IEF, IPG gel strips were placed in an equilibration solution (6-M urea, 2% SDS, 30% glycerol, 50-mM Tris–HCl, pH 8.8) containing 1% DTT for 15 min with shaking at 50 rpm on an orbital shaker. The gels were then transferred to the equilibration solution containing 2.5% iodoacetamide (IAA) and shaken for another 15 min. Then they were placed on a 30% gradient polyacrylamide gel slab (185  200  1.0 mm3), and the strips were overlayed with 1% agarose. Separation in the second dimension was carried out using Protean II xi electrophoresis equipment and Tris–glycine buVer (25-mM Tris, 192-mM glycine)

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containing 0.1% SDS. The 2D SDS-PAGE was developed until the bromophenol blue dye marker had reached the bottom of the gel. D. Silver Staining and Image Analysis Silver staining was performed similarly to the method described by Shevchenko et al. (1996). Briefly, after electrophoresis, the gel slab was fixed in 50% methanol, 5% acetic acid in water for 30 min. It was then washed for 10 min with 50% methanol in water and additionally for 3 10 min with water. The gel was sensitized by a 1-min incubation in 0.02% sodium thiosulfate, and it was then rinsed with two changes of distilled water for 3 min each. After rinsing, the gel was submerged in chilled 0.01% silver nitrate solution and incubated for 20 min at 4  C. Then the silver nitrate was discarded, and the gel slab was rinsed twice with distilled water for 2 min and then developed in 0.04% formalin (35% formaldehyde in water) in 2% sodium carbonate with intensive shaking. After the desired intensity of staining was achieved, the development was terminated by discarding the reagent, followed by washing of the gel slab with 5% acetic acid. Protein patterns in the gels were recorded as digitalized images using a high-resolution scanner. Gel image matching was done with the ImageMaster 2D Elite software 4.01 (Amersham Pharmacia Biotechnology). E. Nano-Flow ESI-MS/MS Identification of DiVerentially Expressed Proteins Gel spots of interest were excised to 1- to 2-mm2 plugs and rinsed with 25-mM ammonium bicarbonate/50% acetonitrile. In-gel trypsin digestion and peptide extraction were performed as described (Ying et al., 2003). For analysis of peptide mixture by LC-ESI-MS/MS, lyophilized peptide mixtures were dissolved with 5.5 ml of 0.1% formic acid (FA) in 2% ACN and injected by autosampler onto a 0.3  1 mm2 trapping column (PepMap C18, LC Packings) using a CapLC system. Peptides were directly eluted into a quadrupole time-of-flight mass spectrometer (Q-TOF Micro, Micromass) at 200 nl/min on a C18 column (75 mm  15 cm, LC Packings) using a 1-h gradient. Fragmentation mass lists were generated by the processing of MS/MS raw data with MassLynx3.5 (Micromass) and used to search against SWISS-PROT protein database via Internet available program Mascot ( F. Immunohistochemical and Western Blot Analyses Formalin-fixed and paraYn-embedded tissues were sectioned in 5-mm thickness. DeparaYnization and rehydration were performed using xylene and alcohol. The sections were treated with 0.3% hydrogen peroxidase for 3 min and blocking antibody for 30 min. The primary antibody used was human Prx II (rabbit polyclonal). Avidin–biotin complex methodology was used. The chromogen was diaminobenzidine, and counterstaining was performed with hematoxylin. For Western


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blot analysis, tissues were suspended in lysis buVer containing 20 mmol/liter Tris (pH 7.6), 150-mmol/liter NaCl, 5-mmol/liter ethylenediaminetetraacetic acid, 0.5% NP40, and 1-mmol/liter dithiothreitol. Suspensions were sonicated for 30 sec and centrifuged at 20,000  g for 15 min. Proteins (20 mg) were loaded onto each lane, size fractionated by sodium dodecyl sulfate/polyacrylamide gel electrophoresis, and transferred to nitrocellulose membrane blocked with PBS/5% skim milk/0.01% Tween 20 for 30 min at room temperature. Primary antibody, Prx II polyAb (1:2000), was diluted in blocking buVer, incubated for 1 h with goatradish peroxidase-conjugated secondary antibody, washed, and developed with ECL-Plus (Amersham Pharmacia Biotech).

IV. Materials IPG strips of pH 3–10 were purchased from Amersham Pharmacia Biotech (Immobiline DryStrip, 0.5  3  180 mm3). BioLyte (pH 3–10) was from BioRad, Hercules, CA. SDS, acrylamide, methylenebisacrylamide, TEMED, ammonium persulfate, DTT, urea, Tris, glycine, glycerol, and CHAPS were purchased from Bio-Rad. Silver nitrate and a-cyno-4-hydroxycinnamic acid were from Sigma (St. Louis, MO). Methanol, ethanol, phosphoric acid, acetic acid, and formaldehyde were purchased from Merck Schuchardt, Hohenbrunn, Germany. Trypsin (sequence grade) was obtained from Promega (Madison, WI). Trifluoroacetic acid (TFA) was from Acros (New Jersey). Ammonium bicarbonate was purchased from Sigma (St. Louis, MO). Acetonitrile (HPLC grade) was purchased from J.T. Baker Co. (Phillipsburg, NJ). FA was obtained from Beijing Chemical Co., Ltd. (Beijing, China). Other reagents were purchased from Sigma or Merck.

V. HCC Samples Human liver tissue samples were obtained from specimens routinely resected from the 10 HCC patients in the Eastern Hepatobiliary Hospital in 2003. Informed consent was obtained from all patients. The stage of the HCC used in the study was Edmondson’s grade III according to the pathological data.

VI. Discussion A. LCM in Sample Preparation for Comparative Proteomics of HCC The 2D PAGE technique has been used for over 20 years for protein separation. Even in light of most recent developments in the oV-gel approaches, 2D PAGE remains extremely powerful for highlighting such posttranslational modifications. For protein identification/characterization, ESI-MS/MS or MALDI-MS is always

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followed after 2D PAGE, which has been the primary technique for biomarker discovery in conventional proteomic analysis. This technique is uniquely suited for direct comparison of protein expression and has been used to identify protein that is diVerently expressed between normal and tumor tissues in various cancers. Proteomic characterization is also being applied to human HCC cell lines (Yu et al., 2000) and HCC tissues (Lim et al., 2002). Even with all the improvements that could be introduced, 2D gels will probably remain a rather low-throughput approach that requires a relatively large amount of samples. The latter is particularly problematic for clinical samples, as such samples are generally procured in limited amounts. Furthermore, tissue heterogeneity complicates the analysis of clinical samples. So far there are several studies of the proteomics of HCC (Lim et al., 2002; Yu et al., 2000); however the results are rather diVerent. Two possibilities can be proposed to explain these results. First, the causes of HCC are diVerent all over the world, for example HBV infection is the main factor in East Asia but HCV infection and alcohol are the prime factors in western countries. The second possible reason should be the heterogeneity of the samples, which might result in diVerent expression patterns of protein profiles. Various tissue microdissection approaches are beneficial to reduce heterogeneity, but they further reduce the amount of sample available. In particular, the use of LCM, which allows defined cell types to be isolated from tissues, yields amounts of proteins that are diYcult to reconcile with the need for greater amounts for 2D gels. Such an approach may allow the more ready identification of diVerences in protein expression of selected cell types or areas of tissue (Petricoin et al., 2002). Here, we applied the LCM to the proteomic study of HCC tissues. The map for the LCM samples was shown in Fig. 1A and the map for the homogenized control was shown in Fig. 1B. They represented a comprehensive view of the major proteins expressed in human HCC tissue. It showed obviously that there were more spots in the homogenized control (949 spots) sample than in the LCM sample (868 spots). However, some spots in homogenization of the HCC tissue could not be detected in the LCM samples, for example, the hemoglobin, which was shown in Fig. 1C and D. LCM technology has been proposed capable of resolving the problem of heterogeneity and contamination in tissue samples. Our results also confirmed this predominance of LCM technology. Although H&E staining was applied to the LCM samples, there was little eVect on the resulting protein profile of the two maps, indicating that the preservation of protein profiles after H&E staining was encouraging and LCM could be a useful method in the HCC tissue proteomic study. B. DiVerences in Protein Expression Between Surrounding Nontumorous Tissues and HCC Tissues By employing 2D PAGE technique, we analyzed the proteome of matched pairs of tumor tissue and surrounding nontumorous tissue from HCC patients, which was shown in Fig. 2. The enlarged area of some diVerential expression proteins






Fig. 1 2-DE map of human liver proteins obtained from liver tissue. 2-DE was performed on an immobilized pH 3–10 strip, followed by the 2D separation on 30% polyacrylamide gels. (A) 2-DE map of HCC tissue after LCM. (B) 2-DE map of homogenized control tissue. It showed that the hemoglobin was removed by LCM from the enlarged maps. (C) Enlarged area of hemoglobin, we could not see the protein from the LCM samples. (D) Enlarged area of hemoglobin, the arrow showed that the protein was in the homogenized control tissue. (E) Nano-flow ESI-MS/MS identification of hemoglobin.

Fig. 2 2-DE maps for (A) HCC tissues after LCM and (B) surrounding nontumorous tissues after LCM. Protein samples were prepared as described in Section II.C , and 100-mg proteins were separated on pH 3–10 nonlinear strips and then on 30% gradient SDS-PAGE. Staining was by silver nitrate.

25. Laser Capture Microdissection in Comparative Proteomic Analysis


Fig. 3 The types of protein expression patterns obtained from comparisons made between surrounding nontumorous tissue and HCC tissue. Each pattern is visualized by examples of protein spots in 2D gel. (A) The arrow showed that HAD have been upregulated in surrounding nontumorous tissues. (B) The arrow showed Prx II was upregulated in surrounding nontumorous tissues. (C) The arrow showed that PEBP was upregulated in HCC tissues.

was shown in Fig. 3. The analysis was carried out on soluble-fraction proteins with the pH range of 3–10. An image pair consisting of analytical gel images of surrounding nontumorous and cancer tissues of the same patient was comparatively analyzed for each patient. Each sample was examined at least five times. Approximately 100 2D gel images were analyzed. Ratios of normalized spot intensities of cancer to paraneoplastic tissue were calculated, and spots showing threefold diVerence were selected for each patient. Then, the frequencies of common alteration of the spots were calculated across the patients, and spots showing


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80% frequency were submitted to protein identification. One of the 2-DE results was confirmed by Western blot analysis. C. DiVerential Proteomic Analysis of Liver Tissues of HCC Patients The protein spots that altered prominently between surrounding nontumorous tissue and HCC tissue were excised from the gel, subjected to in-gel trypsin digestion, and identified by Nano-flow ESI-MS/MS as described above. From the analysis of the data for gel images, we could select 20 spots. Figure 4A showed the total ion chromatography (TIC) of the Nano-flow ESI-MS/MS analysis of the peptides derived from gel spot 11. Six peptides were matched to the phosphatidylethanolamine-binding protein (PEBP). The MS/MS spectrum of peptide corresponding to 32.36 in TIC was shown in Fig. 4B. The spectrum gave an unambiguous internal peptide sequence of PEBP. Summary of 11 interesting proteins that identified with tandem mass spectrometry was listed in Table I. Of the proteins selected, Prx II, apolipoprotein A-I precursor (Apo-AI), 3-hydroxyacyl-CoA dehydrogenase type II (HAD), and 14.5-kDa translational inhibitor protein (p14.5) (UK114 antigen homologue) appear to be novel candidates for useful HBV-related HCC markers. D. Immunohistochemical and Western Blot Analyses for Prx II in HCC To examine whether suppression of Prx II could also be seen in the tissues, immunohistochemical analyses were performed using sections from paraYnembedded normal liver tissues and HCC tumors using the antibody specific for Prx II. As shown in Fig. 5A, Prx II was not expressed in HCC tissues (left corner) as compared with adjacent nontumorous liver tissues (right corner), when tissue sections containing both normal and HCC lesions were used. This was clearer when each tissue was stained separately, that is, compared with normal tissue (Fig. 5B), Prx II is clearly undetectable (Fig. 5C). To determine the protein expression levels of Prx II, Western blot analysis was also performed using polyclonal antibodies against Prx II (Fig. 6). As expected, Prx II was found to be consistently suppressed in HCC whereas it was shown to be highly expressed in nontumorous tissues. Prx II is an antioxidant enzyme that reduces H2O2 and other reactive oxygen species using thioredoxin as the immediate electron donor (Chae et al., 1994), and its peroxidase activity prevents cells from reactive oxygen species insult (Chae et al., 1999). Prx II is also involved in the cellular-signaling pathways of growth factors and tumor necrosis factor-a, by virtue of its regulation of intracellular H2O2 (Kang et al., 1998; Sen, 1998). Prx expression is controversial in certain types of cancer tissues and there is no any other report of the relationship between Prx II and HCC so far. Three types of Prx (I, II, and III) have been shown to be overexpressed in the case of human breast cancer, and it has been suggested that their overexpressions are related to cancer development or/and progression


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1: TOF MS ES+ TIC 2.40e4

A 100 32.36


33.30 29.13




35.80 0

`Time 26.00






P P O 207.11 341.24 Y2 Y3



398.00 Y4

244.17 Y2










38.00 V




941.77 Y6

495.01 Y5 641.40 Y7

804.40 Y8 918.48 Y9

1006.60 1119.62 Y11 Y10

1376.69 Y14 1484.68


0 0










1000 1100 1200 1300 1400 1500

Fig. 4 Nano-flow ESI-MS/MS identification of spot 11. (A) TIC of the Nano-flow ESI-MS/MS analysis of the peptides derived from gel spot 11. (B) MS/MS spectrum of peptide from peak 32.36 in TIC, which corresponds to sequence of GNDISSGTVLSDYVGSGPPK.

Table I Summary of Proteins Identified with Nano-Flow ESI-MS/MS Index


01 02 03

P00441 P02766 P52758




Matched peptide


15795/5.7 15877/5.52 14485/8.74


30 68 83


Superoxide dismutase [Cu-Zn] (EC Transthyretin precursor (prealbumin) (TBPA) (TTR) 14.5-kDa translational inhibitor protein (p14.5) (UK114 antigen homologue) Apolipoprotein A-I precursor (Apo-AI)





Apolipoprotein A-I precursor (Apo-AI)




Peroxiredoxin 2 (EC 1.11.1.-) (thioredoxin peroxidase 1)




Superoxide dismutase [Cu-Zn] (EC




Uroporphyrinogen decarboxylase (EC (URO-D)




Glutathione transferase omega 1 (EC (GSTO 1-1)







3-Hydroxyacyl-CoA dehydrogenase type II (EC (Type II HADH) (endoplasmic reticulum-associated amyloid b-peptide-binding protein) Phosphatidylethanolamine-binding protein (PEBP) (prostatic-binding protein) (HCNPpp)










Proteins that diVerentially expressed were identified with Q-TOF Micro and the fragmented ion lists were searched with Mascot in SWISS-PROT database. The identified results were further verified by comparing the theoretical MW/pI of the proteins with the experimental ones. C*,These cysteines were modified by iodoacetamide during the equilibrium step of 2-DE.

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Fig. 5 Immunohistochemical detection of Prx II expression in human normal liver and HCC. (A) Right, normal liver showed strong staining by polyclonal antibodies to Prx II; left, HCC with reduced Prx II expression. (B) Expression of Prx II in normal liver. (C) HCC showed no immunoreactivity for Prx II.


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Fig. 6 Protein expression of Prx II in four HCC tissues and the normal tissues by Western blot analysis. Shown here were the 7 representative samples of 17 samples because the remaining samples showed similar or identical patterns of expression. Immunoblotting with a Prx II polyclonal antibody following SDS-PAGE was performed as described in Sections III and IV. We used b-actin as a reference value for comparison between surrounding noncancerous tissue and HCC. N, surrounding noncancerous tissue; C, cancerous tissue; M, marker.

(Noh et al., 2001). The increased expression of Prx I was also detected in lung cancer, thyroid tumors, and oral cancer, and is suggested to constitute a potential tumor marker (Chang et al., 2001; Yanagawa et al., 1999, 2000). However, Neumann et al. (2003) found that Prx I functions as a tumor suppressor. Reactive oxygen species are involved in many cellular metabolic and signaling processes and are thought to have a role in disease, particularly in carcinogenesis. Here we showed that Prx II was downregulated in HCC tissues, which suggested that Prx II may function as a tumor suppressor of HCC. Further study is needed to discover the molecular mechanism of Prx II in the hepatocarcinogenesis of HBV infection. Another interesting finding of the present study was that two enzymes of lipid catabolism were downregulated in cancer tissues: HAD and Apo-AI of which HAD has also been reported by Kim et al. (Li et al., 2004). Cancer cells require more cholesterol than normal cells. This requirement may be satisfied by higher hydroxymethylglutaryl-CoA reductase activity. Suto et al. (1999) have found that HAD was downregulated in HCC tissues by immunohistochemical analysis. Previous study suggested that fatty acid metabolism might contribute significantly to the HCC (Ockner et al., 1993). HAD catalyzes the third reaction of the fatty acid b-oxidation spiral in eukaryote as a critical housekeeping enzyme (He and Yang, 1996), which indicates a relationship between HAD and HCC. Apo-AI plays an important structural and functional role in lipid transport and metabolism, it serves as an antioxidant enzyme in lipid metabolism. Norton et al. (2003) observed that HBV decreased Apo-AI mRNA expression in hepG2 cells, which indicated the association between Apo-AI and HCC. In fact, it has long been recognized that HCC frequently exhibits an accumulation of fatty acids and other lipids in cells (Gibson and Sobin, 1978), which suggests that degradation of fatty acids may be repressed or their synthesis may be enhanced in the lesions. Our result seems to favor the first possibility. Further systematic surveys on lipid metabolism in tumor tissues are required to elucidate the phenotype.

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VII. Summary The proteome diVerences between HCC and surrounding nontumorous tissue still remain to be elucidated. Therefore, detection and identification of proteins related to HCC, especially those proteins whose expression is diVerent between surrounding nontumorous tissue and liver tumor, might shed light on the molecular mechanism of the carcinogenesis of HCC. In this study, we applied the LCM to the proteomic study of HBV-related HCC and compared the diVerential expression of proteins in the HCC tissue and the surrounding nontumorous tissue. Twenty protein spots were selected and 11 proteins significantly altered in the surrounding nontumorous tissues and HCC tissues. These proteins may play important roles in tumorigenesis and progression of human HCC, and thus could potentially make useful markers for diagnosis or targets for therapeutic intervention. Further functional analysis is needed for each of these cancer-associated protein candidates. Acknowledgments This work was supported by grants of National Development Program for Key Basic Research of China (No. 2001CB510205 and 2001CB510201), National Key Technologies R&D Program of China (No. 2002BA711A02–3 and 2001AA233031), and Key Basic Science Foundation of Shanghai (No. 03DJ14007 and 03dz14024).

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