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Clinical Cancer Research Vol. 11, 1319-1326, February 2005
© 2005 American Association for Cancer Research

Cancer Therapy: Preclinical

Transcriptional Profiling Identifies Gene Expression Changes Associated with IFN-{alpha} Tolerance in Hepatitis C–Related Hepatocellular Carcinoma Cells

Nathalie Wong1, Kathy Y-Y. Chan1, Pascale F. Macgregor4, Paul B-S. Lai2, Jeremy A. Squire5, Ben Beheshti2, Monique Albert5 and Thomas W-T. Leung3

Departments of 1 Anatomical and Cellular Pathology and 2 Surgery, Chinese University of Hong Kong; 3 Oncology Centre, Hong Kong Sanatorium & Hospital, Hong Kong, China; 4 Microarray Centre, Clinical Genomics Centre, University Health Network; and 5 Departments of Medical Biophysics and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada

Requests for reprints: Nathalie Wong, Department of Anatomical and Cellular Pathology, Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, N.T., Hong Kong, China. Phone: 852-2632-1128; Fax: 852-2648-8842; E-mail: natwong{at}cuhk.edu.hk.


   ABSTRACT
Top
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Purpose: Treatment with IFN-{alpha} therapy has been shown to exhibit antitumor effects on patients with hepatocellular carcinoma (HCC). However, individual responses remained unpredictable because of the frequent presence of intrinsic or acquired IFN-{alpha} resistance. Hence, delineation of molecular targets implicated in the resistant pathway holds value in refining the therapeutic benefits of IFN-{alpha}.

Experimental Design: The current study analyzed the effect of IFN-{alpha} in human HCC cells. Three hepatitis C virus (HCV)–related, five hepatitis B virus (HBV)–related and two non-B non-C–related cell lines were subjected to IFN-{alpha} treatment and the cytotoxic effect on cell viability was measured. Further analysis by cDNA microarray and quantitative reverse transcription-PCR were conducted to examine the gene expression changes that mediated the IFN-{alpha} resistance observed.

Results: According to the IC50 values determined, HCV-related cell lines indicated distinct resistance (IC50, 389-1468 units/mL) compared with the HBV-related (IC50, 11-77 units/mL) and non-B non-C–related cell lines (IC50, 24-108 units/mL). Unsupervised hierarchical clustering on array data indicated three HCV-related cell lines to cluster independently from the sensitive cell lines, suggesting discrete features in association with IFN-{alpha} tolerance. Moreover, Significance Analysis of Microarrays analysis indicated the differential expression of 149 expressed sequence tags that represented 51 up-regulated and 98 down-regulated genes in the resistant cell lines. Comparing the temporal pattern of gene expression between 6- and 24-hour treatments, candidate genes that were considerably induced with time were further highlighted in the tolerant HCV-related cell lines. These candidates were verified by quantitative reverse transcription-PCR, which confirmed the down-regulation of UBA2, ZNF185, and FOXF1 and up-regulation of UBE4B in the drug-tolerant cells.

Conclusions: Our present study showed that the insensitivity to IFN-{alpha} therapy in HCC cells is associated with drug-inducible transcriptional alterations. Furthermore, our investigation highlighted potential candidate genes in conferring an anti-apoptotic effect toward IFN-{alpha} treatment.

Key Words: HCV-related hepatocellular carcinoma cells • IFN-{alpha} • cDNA microarray • UBA2 • ZNF185 • FOXF1 • UBE4B


   INTRODUCTION
Top
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide (1) and is a malignant disease that is commonly fatal. Approximately 315,000 cases of HCC are diagnosed each year, accounting for 4.1% of all new human cancer cases (2). The highest incidence rates of HCC occur in Asia and sub-Saharan Africa, where there is also a marked increase in younger-aged groups (3). Nevertheless, both incidence and mortality rates are found increasing in some countries in North America and Europe (4, 5) . Etiologic factors associated include chronic viral hepatitis B (HBV) or C (HCV) infection, exposure to aflatoxin, male gender, and chronic liver disease of any type (6). Surgical resection represents the only hope of long-term survival for patient with HCC. However, by the time of clinical presentation, >80% of the patients are at a late inoperable stage. This, in turn, has rendered systemic chemotherapy as a major treatment option for the overall survival improvements.

IFN-{alpha} is a pleiotropic cytokine that has a prominent role on the control of cellular proliferative and survival. Administration of IFN-{alpha} is currently one of the first-line therapies for the treatment of patients with HCC. As a single agent, a modest effect of IFN-{alpha} activity has been shown in advanced-stage HCC patients and was reported to be superior to doxorubicin in terms of survival, tumor regression rates, and toxicity in one randomized study (7). The antiproliferative and immunomodulatory activity has also led to its indications in some hematologic malignant diseases, including chronic myeloid leukemia, hairy cell leukemia, and low-grade lymphoma. Due to its antiangiogenesis effects, IFN-{alpha} is also used in the treatment of pulmonary angiomatosis. Nevertheless, whereas IFN-{alpha} therapy is widely accepted in selected human malignant diseases, the treatment regime is often complicated by the emergence of IFN-{alpha} resistance. Tumor resistance to IFN-{alpha}, either at the onset or during the course of treatment, is hence a major hurdle in the management of HCC.

Our present study aimed at investigating the genetic changes that conferred cellular resistance to IFN-{alpha}? To model this toxicity response, we employed in vitro models of HCC cell lines. Cell lines represent an ideal resource for our study because it would have been difficult to secure enough quality RNA from biopsies and there are limitations utilizing surgical tissues. In responding patients, the effect of IFN-{alpha} will not have provided viable cells for expression analysis; on the other hand, in nonresponding patients, curative surgery will unlikely be offered. Studies on drug insensitivity in HCV-related tumors have long been hampered by the lack of an experimental cell culture system. Here, we described the establishment of three cell lines from the tumorous liver tissues of HCC patients who were chronic HCV carriers. These cell lines, together with four cell lines previously developed from our group (HKCI-1, HKCI-2, HKCI-3, and HKCI-4; ref. 8) and three well-characterized cell lines (Hep3B, PLC/PRF/5, and HepG2), correspond to a panel of in vitro models that has enabled our assessment of IFN-{alpha} efficacy on human HCC cells. The IFN-{alpha} cytotoxicity tested against 10 cell lines indicated a remarkably consistent IFN-{alpha} tolerance in HCV-related cell lines. The IFN-{alpha}-induced gene expression profile was further examined directly by cDNA microarray. Differentially expressed genes identified belonged to a broad range of functional pathways that included ion transport, intracellular trafficking, cell-cycle control, and apoptosis.


   MATERIALS AND METHODS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Cell Lines. Seven HKCI series of human HCC cell lines (HKCI-1, HKCI-2, HKCI-3, HKCI-4, HKCI-C1, HKCI-C2, and HKCI-C3) were established and maintained in RPMI 1640 glutamax medium supplemented with 10% fetal bovine serum, 100 IU/mL streptomycin, 10 ng/mL selenium, 10 µg/mL transferrin, and 10 µg/mL insulin (8–10). These cell lines were derived from patients who underwent curative surgery for HCC at Prince of Wales Hospital, Hong Kong. Serologic analysis indicated three patients (HKCI-C1, HKCI-C2, and HKCI-C3) to be seropositive for the antibody to HCV (anti-HCV), three patients (HKCI-1, HKCI-3, and HKCI-4) seropositive for the HBV surface antigen (HbsAg), and one patient (HKCI-2) seronegative for both anti-HCV and HBsAg. Other cell lines, HepG2, Hep3B, and PLC/PRF/5, were obtained from the American Type Culture Collection (Rockville, MD) and grown in DMEM medium containing 10% fetal bovine serum and 100 units/mL penicillin and 100 mg/mL streptomycin. All cultures were maintained in a humidified chamber in a 5% CO2 atmosphere at 37°C. Cells in exponential phase of growth were used for the IFN-{alpha} treatment study.

The viral status in the established cell lines was examined by the nested PCR and nested reverse transcription-PCR (RT-PCR) for the presence of HBV core/precore region and the HCV 5' nontranslated conserved region, respectively. Whereas HKCI-C1, HKCI-C2, and HKCI-C3 cell lines were derived from HCV-infected patients, the maintenance of viral carriage during prolonged in vitro culture was not suggested. On the other hand, three cell lines, Hep3B, PLC/PRF/5, and HKCI-4, showed the presence of HBV core/precore region. In brief, our panel of 10 cell lines examined may be classified into three groups: three HCV related (HKCI-C1, HKCI-C2, and HKCI-C3), five HBV related (HKCI-1, HKCI-3, HKCI-4, Hep3B, and PLC/PRF/5) and two non-B non-C related (HKCI-2 and HepG2).

Cell Line Sensitivity to IFN-{alpha}. The effect of IFN-{alpha} was studied by incubating the drug at varying concentrations with HCC cell lines. Cells were seeded in 24-well plates at a density of 2,000 to 4,000 cells/well. After 24-hour incubation, freshly prepared IFN-{alpha} (Schering-Plough Company, Country Cork, Ireland) was delivered at sequential dilutions of concentrations that ranged from 10–1 to 105 units/mL. Incubation continued for an additional 4 days at 37°C in 5% CO2, after which Trypan Blue exclusion was used to assess the cell viability in triplicate assays for each concentration. The survival factor, determined as IC50, was defined as the concentration of IFN-{alpha} causing 50% inhibition of cell growth compared with untreated control. The cells without IFN-{alpha} treatment were used as the control. The percentage of maximum cell viability was plotted versus the log of IFN-{alpha} concentrations, and the IC50 values were generated using the GraphPad Prism software (GraphPad Software, San Diego, CA). The final IC50 value of each cell line was assigned from the average of triplicate assays derived from three independent experiments.

Microarray Analysis. Cells were treated for 24 hours at IFN-{alpha} dose corresponding to individual IC50 concentration determined; an additional time point at 6 hours was done on the three HCV-related cell lines. Total RNA was extracted from each treated and untreated cell line using TRIzol reagent (Invitrogen, Carlsbad, CA). The expression array experiments were carried out according to the method of University Health Network Microarray Center, Toronto, Canada (http://www.uhnres.utoronto.ca/services/microarray/protocols/). Briefly, 10 µg of total cellular RNA were reverse-transcribed by AncT mRNA primer using Superscript II reverse transcriptase (Invitrogen). Following fluorescence labeling of the transcribed cDNAs with Cy5-dCTP or Cy3-dCTP, the cDNAs were combined with calf thymus DNA, poly(dA), and yeast tRNA in Dighyb buffer (Roche Diagnostics, Mannheim, Germany) before hybridization onto cDNA microarray slides (Ontario Cancer Institute, Toronto, Canada). The 19K cDNA microarray employed contains sequence-verified human genes and expressed sequence tag sequences mapped to National Center for Biotechnology Information's UniGene database. Hybridization took place in a dark chamber at 37°C for 16 hours. Posthybridization washes were carried out in 1x SCC/0.1% SDS at 50°C, thrice at 10 minutes each, and gentle rinsing in 1x SSC twice for 1 to 2 minutes each. The slides were then scanned with ScanArray 5000 analysis system (GSI Lumonics, Packard BioScience, Pangbourne, United Kingdom) using emission and absorption wavelength for Cy5 and Cy3. Raw images acquired were analyzed and quantified by the GenePix Pro 4.0 (Axon, Union City, CA). The raw data obtained from GenePix was normalized by custom software Normalise Suite version 1.56 (11). Array experiment was carried out twice for each treated cell line. The Cy5:Cy3 normalized intensity ratio for each expressed sequence tag was hence averaged from duplicate spots between replicate experiments. The complete data set was finally subjected to hierarchical clustering by the Cluster software package (12). After 80% filtering and log transformation, average linkage hierarchical clustering was done. The Treeview software was used for generating the graphical visualization of the clustering. The significant genes between drug-resistant and drug-sensitive subgroups were selected by a permutation t test using the Significance Analysis of Microarrays software (SAM; ref. 13).

Quantitative Reverse Transcription-PCR. Total RNA extracted from HCC cell lines was subjected to DNase treatment to eliminate possible carryover of genomic DNA. Control experiments by minus-RT-PCR were also done to ensure RNA quality. First-strand cDNA was prepared from 2 µg total cellular RNA using random hexanucleotide primer and MultiScribe reverse transcriptase (Applied Biosystems, Foster City, CA). Quantitative PCR was done in triplicate assays using the SYBR Green PCR Core Reagents kit (Applied Biosystems) for each target genes. The sequences of primers used were listed as follows: UBA2 (sense: 5'-GATAACAGAGCTGCCCGAAAC-3'; antisense: 5'-ATAACACTCGGTCACACCCTTT-3'), ZNF185 (sense: 5'-CGCTATAGCAACGTCAGCAGCA-3'; antisense: 5'-GGGTAATCTTTGGACAGTCTCG-3'), FOXF1 (sense: 5'-AGCCGAGCTGCAAGGCATC-3'; antisense: 5'-CAGCCTCACATCACGCAAGG-3'), UBE4B (sense: 5'-TCGCCCTCTAATAGCCTTGA-3'; antisense: 5'-TATCACTGAGGCTCCGCTTT-3'), and STAT1 (sense: 5'-AACGGAGGCGAACCTGACTTCCA-3'; antisense: 5'-GGCCTGGAGTAATACTTTCCAA-3'). All primers were designed using the Primer3 software (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi/) with forward and reverse primers designed intron spanning. The reactions were done in 25 µL final mixture containing 4 µL cDNA preparation, 1x SYBR Green buffer, 4 mmol/L MgCl2, 0.2 µmol/L of each primers, 0.25 mmol/L deoxynucleotide triphosphates mix and 0.025 units of AmpliTaq Gold DNA polymerase (Applied Biosystems). The amplification was done for 40 cycles with denaturation at 94°C for 30 seconds, annealing at 60°C for 10 seconds, and elongation at 72°C for 10 seconds. The emission intensity from SYBR Green binding to double-stranded DNA was detected by the iCycler detection system (Bio-Rad Laboratories, Hercules, CA). Relative quantification values expressed as threshold cycle (Ct) were averaged and subsequently used to determine the relative expression ratios between cell lines with and without IFN-{alpha} treatment. To adjust for variations in the starting template, the expression levels of target genes in all samples were normalized by an internal reference gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH). A no-template negative control was also included in each experiment.


   RESULTS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Sensitivity to IFN-{alpha}. The growth inhibitory effect on HCC cells that were exposed to a range of IFN-{alpha} concentrations suggested varying degrees of tolerance and sensitivity (Fig. 1). The IFN-{alpha} potency had the highest antiproliferative effect on the HBV-related and non-B non-C cell lines. The IC50 values determined on five HBV-related cell lines ranged from 11 to 77 units/mL (median IC50, 67 units/mL); on the two non-B non-C cell lines, the values ranged from 24 to 108 units/mL (median IC50, 66 units/mL). Three HCV-related cell lines displayed distinct tolerance to IFN-{alpha} treatment with IC50 values determined to range from 389 to 1,468 units/mL (median IC50, 499 units/mL). Based on the cytotoxic study done, a similar sensitivity was suggested between the HBV-related and non-B non-C cell lines, although the HCV-related series seemed most tolerant to IFN-{alpha} treatment? The IC50 determined for the HCV, HBV, and non-B non-C–related cell lines is shown in Fig. 2.



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  		Fig. 1 Dose-response curve for growth inhibition by IFN-{alpha}. Dose-dependent growth inhibition of IFN-{alpha} was determined in a panel of 10 HCC cell lines, which consisted of (A) HBV-related and non-B non-C–related cell lines and (B) HCV-related cell lines. Percentage of growth inhibition at different concentrations of IFN-{alpha} relative to the corresponding untreated control: points, mean; bars, SD.

 


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  		Fig. 2 Survival factor IC50 of IFN-{alpha}-treated HCC cell lines. Each IC50 value represents an average of triplicate assays derived from three independent experiments: columns, mean; bars, SD.

 
Gene Expression Profiling. The expression profiles on IFN-{alpha}-treated cell lines were determined and the analysis of array results was done using web-available software (Cluster and TreeView). Before the clustering algorithm was applied, the fluorescence ratio for each spot was first log-transformed (log2); thereafter, the data for each sample were median-centered to remove experimental biases. By hierarchical clustering in an unsupervised manner, 10 HCC cell lines were classified into two distinct dendrograms that coincided with the IFN-{alpha} tolerance and sensitivity determined from the cytotoxic assay (Fig. 3). The microarray data sets were further analyzed by SAM to determine the inducible candidate genes associated with the anti-apoptotic effect in response to IFN-{alpha} treatment. Differential expression of 149 expressed sequence tags that represented 51 up-regulated and 98 down-regulated targets were highlighted from SAM at a false discovery rate of <0.5% (Table 1).



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  		Fig. 3 Clustering analysis on gene expression profiles of IFN-{alpha}-treated HCC cells. cDNA microarray analysis was done to evaluate gene expression changes in response to IFN-{alpha} treatment. Following 24-hour treatment, induced expression profiles in 10 HCC cell lines of differing viral etiologies were found to classify into two distinct dendrograms. From unsupervised hierarchical clustering, three HCV-related HCC cell lines (HKCI-C1, HKCI-C2, and HKCI-C3) clustered independently from five HBV-related cell lines (HKCI-1, HKCI-3, HKCI-4, Hep3B, and PLC/PRF/5) and two non-B non-C–related cell lines (HKCI-2 and HepG2). SAM analysis further highlighted differentially expressed up-regulated and down-regulated gene in conferring an anti-apoptotic effect toward IFN-{alpha} treatment.

 

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  		Table 1 Differentially expressed genes involved in IFN-{alpha} tolerance phenotype

 
Differentially Expressed Genes Associated with IFN-{alpha} Tolerance. Because three HCV-related cell lines clustered independently from the remaining sensitive cell lines, it suggested distinct features underlying the IFN-{alpha} tolerance. To further prioritize the 149 resistant targets identified in promoting the anti-apoptotic effect, an intermediate 6-hour treatment on the three HCV-related cell lines was done. The temporal pattern of gene expressions between the 24- and 6-hour experimental conditions is expected to highlight those genes that were most prominently induced in response to IFN-{alpha} treatment. Unsupervised clustering of 6- and 24-hour array data sets revealed two distinct cluster dendrograms that coincided with the two experimental time points. Multiple genes were further identified as being regulated differently between the two experimental conditions from SAM, which suggested predominantly down-regulated targets. Matching the 145 targets (142 down-regulated and 3 up-regulated genes at an estimated false discovery rate of <3.0%) derived from the temporal study against the 149 resistant targets obtained from the IFN-{alpha} cytotoxic study, few candidate genes were suggested. The deregulations of these IFN-{alpha}-inducible genes included UBA2, ZNF185, FOXF1, and UBE4B. Further verification of differentially expressed genes identified was done by quantitative RT-PCR. A good agreement with array findings was suggested. A down-regulation of UBA2, ZNF185, and FOXF1 and up-regulation of UBE4B was confirmed in the HCV-related cell lines compared with the HBV-related and non-B non-C cell lines (Fig. 4A). The STAT1 gene is thought to be involved in the direct antitumor effect of IFN-{alpha}. As a control, we have hence also examined the mRNA expression levels of STAT1. The induction of STAT1 up-regulation was found to be preserved in both series of sensitive and resistant HCC cell lines (Fig. 4B).



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  		Fig. 4 Quantitative levels of differentially expressed genes. The IFN-{alpha}-induced candidate gene expressions were determined by quantitative RT-PCR. Expression fold change of each gene in HCV-related cell lines (dark columns) and in HBV-related and non-B non-C cell lines (white columns). Columns, mean; bars, SE. A, down-regulated UBA2, ZNF185, and FOXF1 and up-regulated UBE4B were found in the HCV-related cell lines compared with the HBV-related and non-B non-C cell lines. B, fold induction of STAT1 gene in both series of sensitive and resistant HCC cell lines was found to be similar. Average Ct values were first normalized against the housekeeping gene GAPDH and converted to the induced fold change relative to the corresponding untreated control.

 

   DISCUSSION
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Despite the benefits of IFN-{alpha} therapy in resolving chronic inflammation from HBV and HCV infections, its antiproliferative and antitumor effects on HCC cells remained modest. This is largely because of the frequent emergence of drug resistance in tumor cells. The present study aimed at investigating the HCC genome for IFN-{alpha}-inducible genes that conferred resistance to the cytotoxic effect of IFN-{alpha}. To better understand the cellular response, global gene expression profiling on sensitive and resistant HCC cells were conducted. In unsupervised hierarchical clustering of array data, we observed an independent cluster of IFN-{alpha}-tolerant, HCV-related cell lines, suggesting distinct transcriptional features that underlined the phenomenon (Fig. 3). Further permutation t test analysis by SAM indicated 51 up-regulated and 98 down-regulated genes in the mediation of drug tolerance. The identified genes have been implied in a variety of functions including ion transport (GRIN2A, SKD3, and SLC5A2), intracellular trafficking (UBA2, ATP6V0B, and SNX1), signaling pathways (CDC42, NOG, and PLAUR), transcriptional regulation (PWP1, LZTR1, and FOXF1), drug metabolism (POR), DNA mismatch repair (MSH2 and MGMT), apoptosis (BIRC3 and REQ), and the control of cell cycle (PAK7, ZNF185, and DUSP3; Table 1). Cell cycle deregulations represent an important event in the acquisition of drug resistance. Notably, most genes that were being deregulated in the tolerant cells were found to encode for proteins described in the signal transduction and cell growth.

Chronic HCV is a common cause of liver disease, the complications of which include liver cirrhosis and HCC. In this study, the consistent observation of an increased IFN-{alpha} tolerance in HCV-related HCC cells strongly suggested a role for the viral infection and intrinsic drug resistance behavior. It has been reported that the expression of IFN-{alpha} receptor various among HCC cell lines and in patients with differing viral etiology. In fact, in the only other known HCV-related HCC cell line, Huh7, and in patients with HCV-associated chronic liver disease, resistance to IFN-{alpha} and combination therapy has also been reported (14, 15) . Whereas the presence of HCV has been implicated in multidrug resistance, the maintenance of viral carriage in vitro in Huh7 has not been suggested. Instead, the intrinsic drug resistance in Huh7 is associated with a lower IFN receptor expression compared with other HBV-related cell lines (e.g., PLC/PRF/5; ref. 14). A similar finding has also been reported in the liver tissues of patients with HCV-associated chronic liver disease, where a lower IFN receptor expressed has been suggested in close association with the reduced effectiveness of IFN-{alpha} therapy (15). Nevertheless, the nonstructural 5A protein of HCV has been reported to partially block the IFN-mediated induction via the repression of IFN-stimulated response elements (16). The downstream effect of IFN-stimulated response element repression may have bestowed cytotoxic tolerance in HCC cells in response to IFN-{alpha} therapy. In the present study, although the viral replicon in the HCV-derived HKCI-C1, HKCI-C2, and HKCI-C3 cell lines could not be shown from nested RT-PCR analysis, it is possible that a repressed IFN-stimulated response element–mediated transcription has arisen at the early onset of primary tumor development and the maintenance of such transcriptional alterations in vitro may well have conferred an intrinsic IFN-{alpha} tolerance phenotype.

Time course experiments can reveal temporal changes in gene expression profile as a function of drug response. The utility of time course analysis on microarray study has been described in the identification of genes involved directly rather than passively in the development of cisplatin-resistant lung cancer cells (17). In this study, temporal gene expression changes highlighted in three HCV-related cell lines from two experimental time points (6 and 24 hours) has led to the define of four candidate genes associated with IFN-{alpha} tolerance. Quantitative RT-PCR further confirmed a reduced expression of small ubiquitin-like modifier 1 (SUMO-1) activating enzyme subunit 2 (UBA2), zinc finger protein 185 (ZNF185), and forkhead box F1 (FOXF1) and an increased expression of ubiquitination factor E4B (UBE4B) in the tolerant HCC cells compared with the sensitive cells.

The SUMO-1 activating enzyme (UBA2) plays a role in the reaction of sumoylate conjugation of SUMO to a variety of target proteins. Among the substrates for SUMO modification, many have recently been implicated in various cellular processes, particularly the nucleocytoplasmic trafficking (18, 19). It is well recognized that IFN-{alpha} treatment induces the activation of signal transducer and activator of transcription 1 (STAT1), which upon nuclear translocation initiates specific transcription changes that lead to cellular apoptosis. Thus, STAT1 activation is essential for the antitumor activities of IFN stimulation. A lack of STAT1 induction has been described in the IFN-{alpha} resistance of renal cell carcinoma cells (20). Here, although we found both tolerant and sensitive HCC cells to share similar levels of STAT1 activation upon IFN-{alpha} induction, it is possible that a decreased UBA2 expression observed in the tolerant HCC cells has led to a reduced SUMO modification of proteins required for STAT1 nuclear transport (Fig. 4). Consequently, the STAT-mediated gene activation in response to IFN stimulus may have been hindered, resulting in an increased drug tolerance observed in the HCV-related HCC cells.

The ZNF185 gene encodes a LIM-domain zinc finger protein, which is thought to be involved in protein-protein interactions and in the regulation of cellular proliferation and/or differentiation. Our present observation of a relationship between a reduced ZNF185 expression and drug tolerance represents the first of such finding. Nevertheless, distinct down-regulations of ZNF185 have been described in the head and neck squamous cell carcinoma and prostate cancers (21, 22). Frequent transcriptional inactivation of ZNF185 by CpG dinucleotide methylation has been further suggested in high association with prostate cancer progression and the potential use of ZNF185 as a biomarker for predicting progression of cancer implicated (21). The FOXF1 gene, on the other hand, belongs to the forkhead family of transcription factors, which is characterized by a distinct forkhead domain. The FOXF1 transcriptional factor has been shown to play an important role in the hedgehog-signaling pathway during the embryonic development (23). Although its specific function in cancer drug resistance remained to be determined, recent mapping analysis has indicated FOXF1 as a candidate tumor suppressor gene in prostate cancer, where the FOXF1 expression is consistently and significantly reduced in prostate cancer tissues (24).

Selective protein degradation through the ubiquitin/proteasome system represents an important cellular mechanism in protecting eukaryotic cells against environmental stress. The modification of proteins with ubiquitin can target degradation of abnormal or short-lived proteins generated under normal but, more so, from stress conditions (25). The UBE4B gene encodes a conjugation factor, which is involved in multi-ubiquitin chain assembly on proteins required for efficient proteasomal targeting (26). In yeast, the UBE4B homologue has been linked to cell survival under stress circumstances. In this study, we have identified an up-regulation of UBE4B in IFN-{alpha}-tolerant HCC cells. It is possible that an increased expression of UBE4B can mediate a more effective degradation of stress-induced aberrant proteins aggravated from IFN-{alpha} stimulation. Based on its functional characteristics, UBE4B could represent a candidate drug-resistant gene.

Our study highlights the value of in vitro analysis as a primary step in the understanding of regulatory networks that affect drug insensitivity. Of particular interest was the finding of distinct IFN-{alpha} tolerance in the HCV-related cell lines. Differential expression patterns identified from cDNA microarray analysis has enabled the identification of a collection of genes in relation to drug tolerance and temporal analysis has highlighted biologically relevant targets that may hold value in the further refinement on the therapeutic benefits of IFN-{alpha} in HCC.


   FOOTNOTES
 
Grant support: Research Grants Council of Hong Kong Special Administrative Region (CUHK 4097/02M), Strategic Research Grant from the Chinese University of Hong Kong, and Kadoorie Charitable Foundations (under the auspices of the Hong Kong Cancer Genetics Research Group).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 9/ 1/04; revised 10/28/04; accepted 11/ 9/04.


   REFERENCES
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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