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Cancer Research 67, 4337, May 1, 2007. doi: 10.1158/0008-5472.CAN-06-3640
© 2007 American Association for Cancer Research
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Cell, Tumor, and Stem Cell Biology

Mammalian Target of Rapamycin Activation Impairs Hepatocytic Differentiation and Targets Genes Moderating Lipid Homeostasis and Hepatocellular Growth

Romain Parent, Deepak Kolippakkam, Garrett Booth and Laura Beretta

Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington

Requests for reprints: Laura Beretta, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109. Phone: 206-667-7080; Fax: 206-667-2537; E-mail: lberetta{at}fhcrc.org.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The mammalian target of rapamycin (mTOR) pathway, a major regulator of translation, is frequently activated in hepatocellular carcinomas. We investigated the effects of mTOR activation in the human HepaRG cells, which possess potent hepatocytic differentiation capability. Differentiation of HepaRG cells into functional and polarized hepatocyte-like cells correlated with a decrease in mTOR and Akt activities. Stable cell lines expressing an activated mutant of mTOR were generated. Sustained activation of mTOR impaired the hepatocytic differentiation capability of these cells as shown by impaired formation of bile canaliculi, absence of polarity, and reduced secretion of {alpha}1-antitrypsin. An inhibitor of mTOR, rapamycin, was able to revert this phenotype. Furthermore, increased mTOR activity in HepaRG cells resulted in their resistance to the antiproliferative effects of transforming growth factor-ß1. Profiling of polysome-bound transcripts indicated that activated mTOR specifically targeted genes posttranscriptionally regulated on hepatocytic differentiation. Three major biological networks targeted by activated mTOR were identified: (a) cell death associated with tumor necrosis factor superfamily members, IFNs and caspases; (b) lipid homeostasis associated with the transcription factors PPAR{alpha}, PPAR{delta}, and retinoid X receptor ß; and (c) liver development associated with CCAAT/enhancer binding protein {alpha} and hepatic mitogens. In conclusion, increased mTOR activity conferred a preneoplastic phenotype to the HepaRG cells by altering the translation of genes vital for establishing normal hepatic energy homeostasis and moderating hepatocellular growth. [Cancer Res 2007;67(9):4337–45]


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Hepatocellular carcinoma (HCC) is the fifth most common cause of cancer, and its incidence is increasing worldwide because of the dissemination of hepatitis B and C virus infections. The overall prognosis for patients with HCC is dismal with few effective treatment options (1). Understanding the pathways involved in hepatocarcinogenesis is of particular interest because these factors may represent novel therapeutic targets for the treatment of patients with chronic liver diseases that predispose them to development of HCC. Specific signaling pathways, such as p53, Wnt/ß-catenin, phosphatase and tensin homologue (PTEN)/phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), and the telomerase immortalization enzyme, are frequently dysregulated in HCC (2, 3). The pathway of relevance to this study is the PTEN/PI3K/Akt/mTOR pathway. In mice, hepatocyte-specific PTEN deficiency results in HCCs (4). In other organs, tumor formation resulting from PTEN ablation is suppressed by treatment of the mice with the rapamycin derivative CCI-779, a specific inhibitor of the mTOR kinase (5, 6). The ability of rapamycin to suppress tumor formation in PTEN-deficient mice has been attributed to the mTOR dependence of PI3K signaling. mTOR stimulates protein translation through phosphorylation of 4E-BP1 and p70 S6 kinase (7, 8). Overexpression of the activated phosphorylated form of mTOR was observed in 15% of human HCCs and increased expression of p70 S6 kinase was found in 45% of cases and positively correlated with tumor size (9). The aim of this study was to examine the role of activated mTOR in mediating the behavior of hepatocytic cells during neoplastic transformation.

The HepaRG cell line has been established from the nontumoral region of a resected HCV-associated HCC. These cells display bipotent differentiation-inducible properties and share some features with liver progenitor cells (10). Throughout differentiation, HepaRG cells evolve from a homogeneous, dedifferentiated, depolarized, epithelial phenotype showing no specific organization to a well structurally defined and polarized monolayer closely resembling those formed in primary human hepatocyte culture, with bright canaliculi-like structures (10). At the hepatocytic differentiated state, hepatocytic polarization markers such as ZO-1 and CD26 and liver-specific proteins such as albumin and transferrin, the glycolytic enzyme aldolase B, and enzymes involved in detoxification (CYP2E1, CYP3A4, and glutathione S-transferase {alpha}) are expressed at levels similar to those found in normal liver biopsies (10, 11). Finally, iron storage and metabolism, typical features of mature hepatocytes, never observed in HCC, remain intact in HepaRG cells (12). Although HepaRG cells do bear chromosomal aberrations (11) and cannot be considered normal liver parenchymal cells with differentiation-inducible properties, they constitute a powerful model for studying the role of specific pathways on hepatocytic differentiation and for evaluating the consequences of their dysregulation on hepatocarcinogenesis.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cell culture and generation of {Delta}TOR and control HepaRG clones. The HepaRG cell line was cultured in William's E medium (Invitrogen) supplemented with 10% FCS (Cellgro), 100 units/mL penicillin, 100 µg/mL streptomycin (Invitrogen), 5 µg/mL insulin (Sigma), and 5 x 10–5 mol/L hydrocortisone hemisuccinate (Sigma). To generate {Delta}TOR and control HepaRG clones, 2 x 106 cells were transfected with 2 µg of pCDNA3 plasmid (Invitrogen), bearing or not the {Delta}TOR insert (provided by Dr. Edinger), using Lipofectamine 2000 (Invitrogen). After 24 h, 600 µg/mL G418 (Invitrogen) was added to the culture medium, allowing selection of G418-resistant clones.

To induce differentiation, a two-step procedure was used as previously described (10). Cells were seeded at a density of 4 x 104/cm2 and maintained for 2 weeks in the growth medium. Then, the culture medium was supplemented with 1% DMSO (Sigma) and 20 ng/mL epidermal growth factor (Peprotech) for 2 additional weeks. For reversion experiments, rapamycin (2 ng/mL) was added from day 3 postseeding until the end of the differentiation process. For transforming growth factor-ß (TGF-ß) treatment, cells were seeded at a density of 104/cm2. After 24 h, TGF-ß (Peprotech) was added at a concentration of 2.5 ng/mL in medium supplemented with 0.5% FCS. After 72 h, cells were analyzed with a FACScan analyzer equipped with the Cell Quest software (Becton Dickinson). Cell culture pictures were taken using a phase-contrast microscope (Nikon) equipped with the Metamorph software. Differentiation was evaluated morphologically by counting bile canaliculi (refringent area) at the intersection of two or three hepatocyte-like cells (10).

Western blotting and ELISA. Cells were lysed in 50 mmol/L Tris-HCl (pH 8), 150 mmol/L NaCl, 0.1% SDS, 1% NP40, supplemented with protease inhibitors (Complete, Roche). Twenty micrograms of proteins were resolved on 5%, 10%, or 15% SDS-polyacrylamide gels and electrotransferred onto nitrocellulose membrane (Amersham Biosciences). Equal loadings and homogeneous blotting were confirmed by Ponceau red staining. Membranes were blocked with 5% nonfat milk in TBS and incubated with primary antibodies overnight. The following antibodies were used: anti–phospho-Akt, anti-Akt, anti–phospho-mTOR, anti-mTOR, anti–4E-BP1, anti–p70 S6 kinase (Cell Signaling Technologies; dilution, 1/2,000); anti-AU1 tag (Babco; dilution, 1/2,000); anti-p21(WAF1/CIP1) (PharMingen; dilution, 1/2,000). Horseradish peroxidase–conjugated immunoglobulins (Dako) were used as secondary antibodies and proteins were visualized with enhanced chemiluminescence reagent (Amersham Biosciences). {alpha}1-Antitrypsin quantitation in the supernatant was done using an ELISA with an {alpha}1-antitrypsin capture antibody (Antibody Shop), a rabbit anti–{alpha}1-antitrypsin detection antibody (Dako), and a donkey anti-rabbit immunoglobulin-horseradish peroxidase conjugate (Jackson ImmunoResearch).

Reverse transcription-PCR. One microgram of DNase I–treated (Promega) total RNA was reverse transcribed using Moloney murine leukemia virus reverse transcriptase and random hexamers (Invitrogen) for 50 min at 42°C. Primers for cyclin D1 and actin were 5'-GGATGCTGGAGGTCTGCGA-3' and 5'-AGAGGCCACGAACATGCAAG-3', 5'-TGGACTTCGAGCAAGAGATGG-3' and 5'-GGAAGGAAGGCTGGAAGAGTG-3', respectively. PCR cycle numbers for cyclin D1 and actin were 35 and 23 cycles, respectively.

Polysome-bound RNA preparation. Before harvest, cycloheximide (100 µg/mL) was added to the medium for 3 min. The medium was then removed and the cells were washed with ice-cold PBS containing 100 µg/mL cycloheximide. The cells were then scraped, centrifuged at 800 x g for 5 min at 4°C, and cytoplasmic RNA was obtained by lysing the cell pellet in 1 mL of polysome buffer containing 10 mmol/L Tris-HCl (pH 8.0), 140 mmol/L NaCl, 1.5 mmol/L MgCl2, 0.5% NP40, and a RNase inhibitor, RNasin (500 units/mL; Promega). After the removal of nuclei, the cytosolic supernatant was supplemented with 100 µg/mL cycloheximide, 665 µg/mL heparin, 20 mmol/L DTT, and 1 mmol/L phenylmethanesulfonyl fluoride. Mitochondria and membrane debris were removed by centrifugation, and postmitochondrial supernatant was overlaid onto a 15% to 40% sucrose gradient (13). Fractions (750 µL) were collected from the bottom of each gradient and deproteinated with 100 µg of proteinase K in the presence of 1% SDS and 10 mmol/L EDTA. After acid phenol extraction, RNA integrity was controlled by electrophoresis analysis on 1.2% agarose gel. Densitometry (GelDoc, Bio-Rad) was used to determine fractions in which the 28S/18S ratio equals 2 (i.e., fractions corresponding to polysome-bound RNA). The polysome-bound RNA–containing fractions were pooled from each sucrose gradient according to the distribution profile.

Double-stranded cDNA and cRNA synthesis and microarray hybridization. Total RNA and polysomal RNAs were purified using the RNeasy mini-kit clean-up protocol (Qiagen). First-strand cDNA, double-stranded cDNA, and cRNA were synthesized, and cRNA was fragmented using Affymetrix kits and guidelines.1 All cRNA final products were tested in terms of amount and integrity by Bioanalyzer (Agilent) before microarray hybridization. cRNA samples were processed on Affymetrix HGU133A arrays with strict adherence to the labeling, hybridization, and staining protocols provided by Affymetrix. GeneChip image analysis was done using GCOS v1.4 (Affymetrix). Probe-level analysis, preprocessing, and normalization steps were carried out using GeneTraffic 3.2.-11 (Iobion Stratagene Microarray Analysis Software).

Data mining. The Ingenuity Pathway Analysis2 was used to analyze selected probe sets obtained from the microarray data. Each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base. The application uses a right-sided Fisher's exact test to identify networks that had higher odds ratio of containing significant genes. These genes, called Focus Genes, were then overlaid onto a global molecular network. Networks of these Focus Genes were then algorithmically generated. For the selected probe sets listed in Supplementary Tables S1 and S2, the corresponding data from the Total RNA data sets were extracted. Scatter plots were then drawn and the corresponding correlation coefficients were calculated. Microarray data have been deposited into the Array Express repository3 under the accession no. E-MEXP-958.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Down-regulation of the Akt-mTOR pathway on hepatocytic differentiation. We investigated the Akt-mTOR pathway activity in the human HepaRG cells on their differentiation into hepatocyte-like cells. The amount of phosphorylated Akt (Ser473 residue) decreased on differentiation, whereas total Akt amounts remained unchanged, indicative of a reduction in Akt activity on differentiation. Amounts of total and Ser2448-phosphorylated mTOR also decreased throughout the differentiation process (Fig. 1A ). Reduced phosphorylation of the mTOR substrates, 4E-BP1 and p70 S6 kinase, was also observed on differentiation (Fig. 1B). In conclusion, the activity of the Akt-mTOR pathway decreases during differentiation of HepaRG cells into hepatocyte-like cells.


Figure 1
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  		Figure 1. Down-regulation of the Akt/mTOR pathway on hepatocytic differentiation. Differentiation of HepaRG cells was induced as described in Materials and Methods. Expression levels of phospho-Akt (P-Akt), Akt, phospho-mTOR (P-mTOR), and mTOR (A) and of phospho-4E-BP1 (P-4E-BP1), 4E-BP1, phospho-p70 S6 kinase (P-p70S6k), and p70 S6 kinase (B) were assessed by immunoblotting. P, proliferative stage; D, differentiated stage. Representative of three independent experiments.

 
Generation of HepaRG cells expressing a constitutively activated mTOR mutant and initial characterization. To determine the role of mTOR in hepatocytic differentiation and the consequence of its dysregulation, we generated HepaRG clones expressing a constitutively activated mTOR mutant ({Delta}TOR). mTOR contains a kinase domain and a repressor domain. The kinase activity of mTOR increases by 3.5- to 10-fold when the repressor domain is deleted (14). {Delta}TOR- and backbone vector–bearing cells were generated and screened for the expression of the {Delta}TOR-AU1 tag fusion protein and of total mTOR (Fig. 2A ). To confirm the functional activity of the transgene, 4E-BP1 phosphorylation was examined in proliferative and differentiated clones. Consistent with the induced enzymatic activity of {Delta}TOR, 4E-BP1 phosphorylation was higher in {Delta}TOR-bearing cells than in control cells at both the proliferative and differentiated states. In particular, 4E-BP1 remained in majority phosphorylated on differentiation in the {Delta}TOR-expressing cells (65 ± 3%) whereas 4E-BP1 was only partially phosphorylated at the differentiated stage in control cells (39 ± 2% for vector-bearing cells and 42 ± 1% for HepaRG cells; Fig. 2B).


Figure 2
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  		Figure 2. Generation of {Delta}TOR-expressing HepaRG cells and initial characterization. A, stable clones of HepaRG cells expressing the empty vector or {Delta}TOR were generated. The mTOR transgene expression was examined by Western blotting with antibodies against the AU1 tag or mTOR. B, phosphorylation status of 4E-BP1 in proliferative (P) and differentiated (D) {Delta}TOR, vector, and HepaRG cells by Western blot with an antibody against 4E-BP1. Representative of three independent experiments. C, cell sizes for {Delta}TOR, vector, and HepaRG cells were measured by flow cytometry. Columns, mean of three independent experiments; bars, SD. D, cyclin D1 and ß-actin transcripts at the differentiated state were amplified by PCR and the PCR products were resolved on a 2% agarose gel.

 
Increased cell size is associated with tumorigenesis. The size of {Delta}TOR-expressing cells was significantly higher at days 5 and 7 postseeding, compared with vector-containing cells (day 5, P = 0.017; day 7, P = 0.035) and parental HepaRG cells (day 5, P = 0.018; day 7, P = 0.029; Fig. 2C). At the seeding density used in this study, confluence is reached after 4 days. The cell size of {Delta}TOR-expressing cells was not significantly changed until day 7 and, therefore, {Delta}TOR cells, unlike control cells, did not seem to be sensitive to confluency. Cyclin D1 promotes mitogen-independent cell cycle progression in primary hepatocytes. To evaluate the capacity of {Delta}TOR-expressing cells to proliferate even at the end of the differentiation process, cyclin D1 mRNA expression levels were measured by semiquantitative reverse transcription-PCR (Fig. 2D). Cyclin D1 mRNA levels were significantly higher in {Delta}TOR-expressing cells compared with controls. Taken together, these data suggest that increased mTOR activity results in a proliferative advantage in HepaRG cells on differentiation.

Impaired hepatocytic differentiation in {Delta}TOR-expressing HepaRG cells and its reversion by rapamycin. The differentiation capability along the hepatocytic lineage was analyzed in {Delta}TOR-expressing cells. Whereas no morphologic differences were noticed between proliferative cell lines, striking differences were observed at the end of the differentiation process (Fig. 3A ). Differentiated hepatocytes display refractile cellular borders, dark cytosol, clearly delineated nuclei, and tridimensional polarization with the appearance of refringent circular canaliculi vertically. {Delta}TOR-expressing cells did not establish any structured monolayer in contrast to control cell lines, and none of the morphologic criteria described above was observed in {Delta}TOR cells in contrast to the two control cell lines. Bile canaliculi were counted in the three cell lines at the end of the differentiation process, indicating a quasi-absence of tridimensional polarization in {Delta}TOR-expressing cells [25 ± 25/cm2 in {Delta}TOR cells, 492 ± 124/cm2 in vector-containing cells (P = 0.021), and 342 ± 51/cm2 in HepaRG cells (P = 0.004); Fig. 3B]. The capacity of hepatocytes to secrete plasmatic proteins in appropriate amounts correlates with their differentiation status. Levels of secreted {alpha}1-antitrypsin were measured in the three cell lines at the end of the differentiation protocol. The amount of {alpha}1-antitrypsin released in the supernatant by {Delta}TOR-expressing cells was 40.75 ± 8% of the amount secreted by HepaRG cells, whereas the amount released by vector-bearing cells was 101 ± 3% of the amount secreted by HepaRG cells (P < 0.001; Fig. 3C).


Figure 3
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  		Figure 3. Impaired hepatocytic differentiation of HepaRG cells expressing an activated mutant of mTOR. A, {Delta}TOR, control vector, and HepaRG parental cells were induced to differentiate as described in Materials and Methods. Pictures (magnification, x40) were taken in three randomly selected fields at the proliferative (P) and differentiated (D) stages. Representative of three independent experiments. B, bile canaliculi were counted from three randomly selected fields in three independent experiments. C, {alpha}1-antitrypsin levels were quantified by ELISA in the supernatant of each cell line at the differentiated stage and normalized by cell count. Columns, mean of three independent experiments; bars, SD.

 
To further confirm that impaired differentiation of {Delta}TOR-bearing HepaRG cells was indeed due to increased mTOR kinase activity and to exclude any clonal effect, differentiation of {Delta}TOR-expressing HepaRG cells was carried out in the presence of an inhibitor of mTOR, rapamycin, in two independent experiments. Morphologic evaluation showed an organized and polarized phenotype in rapamycin-treated {Delta}TOR cells (Fig. 4A ), with a bile canaliculi density comparable to levels found in control cell lines [693 ± 233/cm2 in rapamycin-treated {Delta}TOR cells and 50 ± 10/cm2 in vehicle-treated {Delta}TOR cells (P = 0.05); Fig. 4B; see also Fig. 3B]. In conclusion, increased mTOR activity impairs the morphologic and biochemical hepatocytic differentiation of the HepaRG cells.


Figure 4
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  		Figure 4. Reversion by rapamycin of the altered phenotype. {Delta}TOR-bearing cells were treated throughout the differentiation protocol with rapamycin (2 ng/mL) or vehicle alone. A, morphology. B, columns, mean bile canaliculi densities from three randomly selected fields and from two independent experiments; bars, SE.

 
Loss of TGF-ß responsiveness in {Delta}TOR-expressing HepaRG cells. TGF-ß plays a critical role in the transition of stem cells or progenitor cells to a fully differentiated phenotype in the liver parenchyma and controls cell growth and apoptosis in the liver. Active TGF-ß1 secretion levels were assessed in the {Delta}TOR-containing HepaRG cells and in control cells. Similar amounts of this cytokine (<70 pg/mL/d) were detected in the supernatant of all cell lines, independently of {Delta}TOR expression (data not shown). In comparison, conventional doses of TGF-ß used in in vitro assays are between 2,000 and 5,000 pg/mL. Therefore, the capability of {Delta}TOR to modulate the antiproliferative effects of TGF-ß1 was tested. No apoptosis was observed in any cell line on TGF-ß1 treatment (data not shown). Phase-contrast microscopy analysis indicated that {Delta}TOR-expressing HepaRG cells were less susceptible to the acquisition of a spindle-shaped morphology, typical of TGF-ß1–induced response (Fig. 5A ). In addition, {Delta}TOR-expressing cells were resistant to the antiproliferative effect of TGF-ß1 compared with control cells with a proliferation inhibition rate of 9 ± 2% in {Delta}TOR-expressing cells, 51 ± 9% in vector-containing cells (P = 0.043), and 38 ± 15% in HepaRG cells (P = 0.003; Fig. 5B). Finally, expression of the cell cycle inhibitor p21(WAF1/CIP1) was induced on TGF-ß1 treatment in control cell lines but not in {Delta}TOR-expressing cells (Fig. 5C). Taken together, these results suggest that increased mTOR activity leads to loss of TGF-ß responsiveness in hepatocytes.


Figure 5
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  		Figure 5. Loss of TGF-ß responsiveness in {Delta}TOR-expressing HepaRG cells. Cells were incubated with TGF-ß1 for 3 d. A, pictures were taken from three randomly selected fields. B, cells were analyzed by fluorescence-activated cell sorting using the cell count function of the device. Columns, mean of three experiments; bars, SD. C, p21(WAF1/CIP1) expression levels were assessed by immunoblotting.

 
Comparative polysome-bound RNA profiling of {Delta}TOR-expressing HepaRG cells and control cell lines on hepatocytic differentiation and data mining. To identify the mechanisms by which activated mTOR impairs hepatocytic differentiation and generates a preneoplastic phenotype in the HepaRG cells, profiling of total RNAs and polysome-bound RNAs was done in {Delta}TOR-expressing cells and in control cells (vector-bearing and parental HepaRG) at the proliferative stage and at the end of the differentiation protocol using Affymetrix microarrays. mTOR is a regulator of translation and, therefore, we used polysome-bound RNA profiling for our analysis to detect changes occurring at both transcriptional and translational levels. We selected polysome-bound transcripts significantly modified in control cells by at least 2-fold on differentiation in three independent experiments but not in {Delta}TOR cells (P ≤ 0.05). These include 590 up-regulated (Supplementary Table S1) and 49 down-regulated (Supplementary Table S2) transcripts.

To investigate whether activation of mTOR was affecting transcripts regulated at the transcriptional level or at posttranscriptional levels on differentiation of control cells, total RNA fold changes in control cells were plotted against polysome-bound RNA fold changes in control cells for these selected transcripts. For the up-regulated transcripts, the slope of the regression curve calculated from all experimental values was 0.6222 (Fig. 6A ). The slope of this curve is greater than zero, indicative of a positive correlation between polysome-bound RNA and total RNA fold change values. However, the correlation coefficient for this regression curve was 0.3798, showing a poor correlation between changes in the polysome-bound fractions and changes in total RNA on differentiation of HepaRG cells. Similarly, a poor correlation between changes in the polysome-bound fractions and changes in total RNA on differentiation of HepaRG cells was observed for the down-regulated genes, with a correlation coefficient of 0.0791 (Fig. 6B). These results suggest that mTOR activity is specifically targeting transcripts modified at a posttranscriptional level on hepatocytic differentiation of HepaRG cells.


Figure 6
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  		Figure 6. Correlation between total RNA and polysomal RNA fold changes and Ingenuity pathway analysis. Scatter plots were drawn for the selected 615 up-regulated probe sets (A) and the selected 49 down-regulated probe sets (B) between the log-transformed polysome-bound RNA fold changes and the corresponding total RNA fold changes. Dotted line, total/polysome-bound RNA ratio of 1 (slope = 1). Solid line, regression curve calculated from all plots. C and D, the identified networks are represented as nodes displayed using various shapes that represent the functional class of the gene product and lines/arrows displayed with various labels that describe the specific relationship between the nodes. Gene abbreviation is located within the symbol. The significance of the shapes of the symbols, and the letters mentioned between nodes can be found in the Ingenuity website (http://www.ingenuity.com). Solid lines, direct interaction. Dotted lines, indirect interaction. An asterisk appears next to any gene for which the input file contained more than one identifier. C, a total of 35 differentially expressed genes were revealed in this network with a highly significant score of 50. Gene symbols found in this network: ADM, adrenomedullin; CASP8, caspase-8, apoptosis-related cysteine protease; CASP9, caspase-9, apoptosis-related cysteine protease; TNFRSF5, TNF receptor superfamily, member 5 or CD40; CRADD, CASP2 and RIPK1 domain containing adaptor with death domain; CTNND1, catenin (cadherin-associated protein), {delta}1; DHFR, dihydrofolate reductase; ENO1, enolase 1, ({alpha}); FADD, Fas (TNFRSF6)-associated via death domain; FAF1, Fas (TNFRSF6)-associated factor 1; IFI16, IFN, {gamma}-inducible protein 16; IHPK2, inositol hexaphosphate kinase 2; JAK2, Janus kinase 2; MADD, mitogen-activated protein kinase activating death domain; OAS1, 2',5'-oligoadenylate synthetase 1; PDCD8, programmed cell death 8; PDE4A, phosphodiesterase 4A, cyclic AMP-specific; PECAM1, platelet/endothelial cell adhesion molecule; PIAS1, protein inhibitor of activated STAT, 1; PIP5A1C, phosphatidylinositol-4-phosphate 5-kinase, type I, {gamma}; PTBP1, polypyrimidine tract-binding protein 1; PTPN6, protein tyrosine phosphatase, nonreceptor type 6; RBM5, RNA-binding motif protein 5; SMPD1, sphingomyelin phosphodiesterase 1, acid lysosomal; SRPX, sushi-repeat-containing protein, X-linked; STAT1, signal transducer and activator of transcription 1; TCEB2, transcription elongation factor B (SIII), polypeptide 2; TNFRSF25, TNF receptor superfamily, member 25; TNFRSF10C, TNF receptor superfamily, member 10c, decoy; TNFRSF11B, TNF receptor superfamily, member 11b; TNFRSF1A, TNF receptor superfamily, member 1A; TNFRSF6B, TNF receptor superfamily, member 6b, decoy; TNFSF10, TNF (ligand) superfamily, member 10 (TRAIL); TNFSF13, TNF (ligand) superfamily, member 13 (APRIL); TRADD, TNFRSF1A-associated via death domain. D, a total of 35 differentially expressed genes were revealed in this network with a highly significant score of 50. Gene symbols found in this network: ACOX1, acyl-CoA oxidase 1; AKAP13, a kinase (PRKA) anchor protein 13; ARNT, aryl hydrocarbon receptor nuclear translocator; C19ORF29, chromosome 19 open reading frame 29; CEBPD, CCAAT/enhancer binding protein, {delta}; CITED2, CREB binding protein/p300-interacting transactivator, 2; CPT2, carnitine palmitoyltransferase II; DDIT4, DNA-damage-inducible transcript 4; EFNA1, ephrin-A1; FABP4, fatty acid–binding protein 4; FGB, fibrinogen ß chain; FKBP1A, FK506 binding protein 1A; FN1, fibronectin 1; FRAP1, FK506 binding protein 12-rapamycin associated protein 1; GLUD1, glutamate dehydrogenase 1; GPHN, gephyrin; HADHA, hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, {alpha} subunit; HADHB, hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, ß subunit; IL1R1, interleukin-1 receptor, type I; MIA, melanoma inhibitory activity; MLYCD, malonyl-CoA decarboxylase; NAB2, nuclear polyadenylated RNA-binding protein; PDHA1, pyruvate dehydrogenase (lipoamide) {alpha}1; PDK2, pyruvate dehydrogenase kinase, isoenzyme 2; PDK3, pyruvate dehydrogenase kinase, isoenzyme 3; PDK4, pyruvate dehydrogenase kinase, isoenzyme 4; PPARA, peroxisome proliferator–activated receptor, {alpha}; PPARD, peroxisome proliferator–activated receptor, {delta}; PRKAR1A, protein kinase, cyclic AMP-dependent, regulatory, type I, {alpha}; PRKAR2A, protein kinase, cyclic AMP-dependent, regulatory, type II, {alpha}; RHEB, Ras homologue enriched in brain; RXRB, retinoid X receptor ß; ST6GAL1, ST6 ß-galactosamide {alpha}-2,6-sialyltranferase 1; TCF4, transcription factor 4; TSC2, tuberous sclerosis 2.

 
The contents of the Supplementary Tables S1 and S2 were analyzed using the Ingenuity Systems Pathways Knowledge Base4 (March 2006 release). This database enables search for gene product interactions and annotations coming from curated data from publications and peer-reviewed resources. The Ingenuity pathway analysis identified two molecular networks generated from the up-regulated transcripts displaying 100% overlay between the selected regulated genes found in our study and the software-preselected members. The first network includes 35 genes associated with the proapoptotic tumor necrosis factor (TNF) superfamily– and caspase-related pathways and with the IFN system (Fig. 6C). It includes two members of the TNF superfamily, TNFSF10 [TNF-related apoptosis-inducing ligand (TRAIL)] and TNFSF13 (APRIL), and six members of the TNF receptor superfamily, TNFRSF1A, TNFRSF10C (TRAILR3), TNFRSF25 (death receptor 3, Apo3), TNFRSF5 (CD40), TNFRSF6B (decoy receptor 3), and TNFRSF11B. The other main components of this network are caspase-8 (CASP8) and caspase-9 (CASP9), Janus kinase 2 (JAK2), and signal transducer and activator of transcription 1 (STAT1). Other proteins associated with increased susceptibility to apoptosis include CRADD, FADD, TRADD, MADD, IHPK2, sphingomyelin phosphodiesterase 1, and programmed cell death 8. Finally, two members of this network are IFN-inducible genes: 2',5'-oligoadenylate synthetase-1 (OAS1) and IFI16. IFI16 showed the largest fold change (54.1-fold) and is also associated with proapoptotic functions, in addition to negative regulator of cell growth. In addition to the transcripts depicted in this network, several transcripts also involved in susceptibility to apoptosis included cell death activator CIDE-3, insulin-like growth factor (IGF)–binding protein 1, tuberous sclerosis complex protein 2, growth arrest–specific 2, and programmed cell death 4 (Table S1).

The second network is associated with lipid and carbohydrate metabolisms and includes 35 genes (Fig. 6D). These include the peroxisome proliferator–activated receptors {alpha} and {delta} (PPAR{alpha} and PPAR{delta}) and the retinoid X receptor ß (RXRß), a modulator of PPAR{alpha} activity. PPARs and RXRs induce the expression of proteins and enzymes involved in pyruvate metabolism, such as PDK2, PDK3, PDK4, and PDHA1, and in lipid metabolism such as HADHA, HADHB, C/EBP{delta}, ACOX1, and FABP4. In addition to the transcripts depicted in this network, transcripts involved in lipid transport and/or metabolism included CCAAT/enhancer binding protein (C/EBP)-{alpha}, solute carrier family 27-member 3, sterol regulatory element–binding transcription factor 2, lipoic acid synthetase, low-density lipoprotein receptor–related protein 1, and apolipoprotein M (Table S1).

Remarkably, down-regulation of the growth factors vascular endothelial growth factor (VEGF), hepatocyte growth factor (HGF), fibroblast growth factors 2 and 5 (FGF2 and FGF5), and PDGFB upon differentiation of the HepaRG cells was inhibited by {Delta}TOR (Table S2).

Taken together, these results indicate that {Delta}TOR affects the posttranscriptional regulation of genes vital for modulating sensitivity to apoptosis, lipid homeostasis, and hepatocellular growth.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this study, we used the human HepaRG cell line to increase our knowledge about the possible involvement of mTOR activation in the development of HCC. HepaRG cells display potent hepatocytic differentiation–inducible properties and share some features with liver progenitor cells (10). The number of human liver progenitor cells correlates with the severity of liver diseases such as chronic viral hepatitis, alcoholic and nonalcoholic fatty liver diseases, which predispose patients to HCC. Activation of progenitor cells in these diseases suggests that they form a potential target cell population, precursors of HCC, and, indeed, a subtype of human HCCs express one or more markers of progenitor cells (15, 16).

We showed that the activity of mTOR decreases on hepatocytic differentiation of the HepaRG cells and that sustained mTOR activation impairs their differentiation and their polarization status. {Delta}TOR-expressing cells were unable to settle tridimensional organization and polarization, mandatory for normal endocrine and exocrine functionality of the hepatocyte. In agreement with our observation that control HepaRG cells but not {Delta}TOR-expressing cells reached a mature hepatocytic functional state, induction of radixin and catenin-{delta}1, genes involved in epithelium polarization and organization (17), was impaired by mTOR activation. Loss of hepatocytic and trabecular organization in the lobule is a hallmark of many HCCs and HCC grades have been defined according to these features (18). Another hallmark of many HCCs is their loss of responsiveness to TGF-ß1. TGF-ß1 has antiproliferative and proapoptotic properties in normal hepatocytes and in rat partial hepatectomy models. In our study, {Delta}TOR expression conferred resistance to TGF-ß1–induced inhibition of proliferation. Recent studies suggested that mTOR abolishes TGF-ß/ALK5–mediated Smad3 activation (19), in agreement with our observed antagonism between the Akt/mTOR pathway and TGF-ß1 antitumorigenic function.

mTOR is a critical component of translational control (7). To identify the altered events in {Delta}TOR-expressing HepaRG cells leading to their preneoplastic phenotype, we analyzed polysome-bound RNAs by microarray and selected changes occurring on differentiation in control cells but not in {Delta}TOR cells. Comparing changes of the selected transcripts at both the total RNA and polysome-bound RNA levels indicated that mTOR specifically targeted genes posttranscriptionally regulated on differentiation of HepaRG cells. mTOR impaired the up-regulation of a large number of members of the TNF/caspase transduction pathway. These include TNFSF10 (TRAIL) and caspase-8, known to play a crucial role in inducing apoptosis in human hepatocytes and HCCs (20). Caspase-8, a key mediator of death receptor–induced apoptosis, has previously been reported to be frequently inactivated by epigenetic silencing in many tumors. This network also shows that mTOR impaired the up-regulation of JAK2 and STAT1 and of IFN-induced proteins such as OAS1 or IFI16 (>50-fold). There is currently no information on IFI16 in the liver but IFI16 is an essential mediator of growth inhibition in medullary thyroid carcinoma cells (21) and of p53 and p21(WAF1/CIP1) functions (22). IFI16 expression is increased by TRAIL in breast carcinoma cells (23). Noteworthy, both up-regulated caspases identified (caspase-8 and caspase-9) belong to the initiator caspases family, whereas none of the members of the effector caspase family (caspase-3, caspase-6, and caspase-7; ref. 24) was affected, supporting the fact that control cells did not undergo apoptosis in culture. Numerous additional transcripts coding for antiproliferative, neoplastic transformation inhibitors and proapoptotic proteins were identified to be up-regulated in control cells on differentiation but not in {Delta}TOR-expressing cells. Normal hepatocytes are highly sensitive to cell death upon, for example, drug-induced liver toxicity, and three-dimensional polarization sensitizes hepatocytes to Fas apoptotic signaling (25). Therefore, sustained activation of mTOR may contribute to neoplastic cell expansion by altering receptor-induced apoptosis sensitivity. Our data also suggest an important molecular cross-talk between the TRAIL and IFN pathways in liver progenitor cells. mTOR may induce resistance to TRAIL- and/or IFN-induced apoptosis. Defects in IFN signaling that result in loss of expression of IFN-inducible proteins are associated with cellular immortalization, an important early event in the development of human cancer.

mTOR activation impaired the induction of the transcription factors PPAR{alpha}, PPAR{delta}, and RXRß and their target genes. The lipid-lowering function of PPAR{alpha} occurs across a number of mammalian species, thus showing the essential role of this nuclear receptor in lipid homeostasis and normal liver function. Mice deficient in PPAR{alpha} lack hepatic peroxisomal proliferation, have an impaired expression of several hepatic target genes, and show a massive accumulation of lipids in their livers (26). Ethanol impairs fatty acid catabolism in liver by blocking PPAR{alpha}-mediated responses contributing to the development of alcoholic fatty liver, which can be overcome by PPAR{alpha} agonists (27). HCV infection is also associated with altered expression and function of PPAR{alpha} (28). PPAR{delta} also plays a role in lipid metabolism including cholesterol efflux and fatty acid oxidation (29, 30); activates fat metabolism to prevent obesity (31); and regulates fatty acid synthesis, glucose metabolism, and insulin sensitivity (32). Interestingly, it has been reported that PPAR{delta} attenuates colon carcinogenesis (33). RXR heterodimers serve as key regulators in cholesterol homeostasis by governing reverse cholesterol transport from peripheral tissues, bile acid synthesis in liver, and cholesterol absorption in intestine (34). Liver-specific loss of function of retinoic acid leads to steatohepatitis and liver tumors in vivo (35). Therefore, sustained mTOR activity may contribute to the development of steatosis observed in most HCCs by impairing lipid homeostasis.

Another major target of {Delta}TOR is C/EBP{alpha}. This transcription factor regulates two aspects of hepatic terminal differentiation: induction of differentiation-specific genes and repression of mitogenesis (36–38). C/EBP{alpha} reduces HCC susceptibility in mice (39) and down-regulation of C/EBP{alpha} in HCC correlates with tumor size and progression (40). C/EBP{alpha}-deficient mice present with severely disturbed liver architecture with acinar formation in a pattern suggestive of either regenerating liver or HCC, abnormally active hepatocytic proliferation, impaired hepatic glycogen storage, and accumulation of lipids in the liver (41, 42). These mice also show lowered plasma levels of free fatty acid, triglyceride, and cholesterol as well as marked changes in PPAR{alpha} and apoliproteins (43). Therefore, by impairing induction of C/EBP{alpha} on hepatocytic differentiation, mTOR is affecting numerous vital liver-specific functions.

Dysregulation of pleiotropic growth factors and their receptors represent a central protumorigenic principle in human hepatocarcinogenesis. Especially the IGF, HGF, and TGF-ß pathways, all found affected by activated mTOR in the HepaRG cells, contribute to proliferation, antiapoptosis, and invasive behavior of tumor cells. HGF is the primary agent promoting the proliferation and apoptosis resistance of mature hepatocytes. Serum HGF levels are strongly associated with liver diseases including insulin resistance and nonalcoholic steatohepatitis. Blockage of HGF suppresses HCC in mice by inhibiting tumor cell motility and angiogenesis (44). FGF2, VEGF, and PDGFB are potent mitogenic and angiogenic factors and stimulate tumor growth (45). Expression of VEGF and FGF2 is altered in patients with HCC and, interestingly, VEGF and FGF2 concentrations are elevated before the emergence of HCC (46). By maintaining high levels of expression of these factors on hepatocytic differentiation, mTOR may accelerate abnormal proliferation and angiogenesis.

In conclusion, we have shown that an enhanced activity of mTOR, as found in clinical HCC samples, is capable of preventing hepatocytic differentiation not only through inhibition of induction of C/EBP{alpha} but also by preventing hepatocytic polarization. In addition, sustained mTOR activity may lead to reduced susceptibility to TGF-ß antiproliferative effects and to TRAIL/TNF– and IFN-induced apoptosis. Sustained mTOR activity may also lead to abnormal expression of genes modulating lipid homeostasis, hepatocellular growth, and angiogenesis. These effects, taken together, could contribute to the neoplastic transformation of these cells. Our study also suggests that combination therapy strategies aimed at overcoming TRAIL and IFN resistance and PPAR{alpha} and PPAR{delta} defects may be effective for treatment of HCC with activated mTOR or PTEN deletion.


   Acknowledgments
 
Grant support: NIH/National Institute of Diabetes and Digestive and Kidney Diseases grant DK066840 (Fred Hutchinson Cancer Research Center).

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.

We thank Dr. A. Edinger (University of California, Los Angeles, CA) for the gift of the {Delta}TOR constructs and Drs. C. Trépo and M-A. Petit (Institut National de la Santé et de la Recherche Médicale Unit 271, Lyon, France) for the gift of HepaRG cells.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

1 http://www.affymetrix.com/support/technical/technotesmain.affx Back

2 https://analysis.ingenuity.com Back

3 http://www.ebi.ac.uk/arrayexpress Back

4 http://www.ingenuity.com Back

Received 10/ 2/06. Revised 1/ 5/07. Accepted 2/ 9/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Sala M, Forner A, Varela M, Bruix J. Prognostic prediction in patients with hepatocellular carcinoma. Semin Liver Dis 2005;25:171–80.[CrossRef][Medline]
  2. Roberts LR, Gores GJ. Hepatocellular carcinoma: molecular pathways and new therapeutic targets. Semin Liver Dis 2005;25:212–25.[CrossRef][Medline]
  3. Lee JS, Thorgeirsson SS. Comparative and integrative functional genomics of HCC. Oncogene 2006;25:3801–9.[CrossRef][Medline]
  4. Horie Y, Suzuki A, Kataoka E, et al. Hepatocyte-specific Pten deficiency results in steatohepatitis and hepatocellular carcinomas. J Clin Invest 2004;113:1774–83.[CrossRef][Medline]
  5. Neshat MS, Mellinghoff IK, Tran C, et al. Enhanced sensitivity of PTEN-deficient tumors to inhibition of FRAP/mTOR. Proc Natl Acad Sci U S A 2001;98:10314–9.[Abstract/Free Full Text]
  6. Podsypanina K, Lee RT, Politis C, et al. An inhibitor of mTOR reduces neoplasia and normalizes p70/S6 kinase activity in Pten+/– mice. Proc Natl Acad Sci U S A 2001;98:10320–5.[Abstract/Free Full Text]
  7. Beretta L, Gingras AC, Svitkin YV, Hall MN, Sonenberg N. Rapamycin blocks the phosphorylation of 4E-BP1 and inhibits cap-dependent initiation of translation. EMBO J 1996;15:658–64.[Medline]
  8. Burnett PE, Barrow RK, Cohen NA, Snyder SH, Sabatini DM. RAFT1 phosphorylation of the translational regulators p70 S6 kinase and 4E-BP1. Proc Natl Acad Sci U S A 1998;95:1432–7.[Abstract/Free Full Text]
  9. Sahin F, Kannangai R, Adegbola O, Wang J, Su G, Torbenson M. mTOR and P70 S6 kinase expression in primary liver neoplasms. Clin Cancer Res 2004;10:8421–5.[Abstract/Free Full Text]
  10. Parent R, Marion MJ, Furio L, Trepo C, Petit MA. Origin and characterization of a human bipotent liver progenitor cell line. Gastroenterology 2004;126:1147–56.[CrossRef][Medline]
  11. Gripon P, Rumin S, Urban S, et al. Infection of a human hepatoma cell line by hepatitis B virus. Proc Natl Acad Sci U S A 2002;99:15655–60.[Abstract/Free Full Text]
  12. Troadec MB, Glaise D, Lamirault G, et al. Hepatocyte iron loading capacity is associated with differentiation and repression of motility in the HepaRG cell line. Genomics 2006;87:93–103.[CrossRef][Medline]
  13. Grolleau A, Bowman J, Pradet-Balade B, et al. Global and specific translational control by rapamycin in T cells uncovered by microarrays and proteomics. J Biol Chem 2002;277:22175–84.[Abstract/Free Full Text]
  14. Sekulic A, Hudson CC, Homme JL, et al. A direct linkage between the phosphoinositide 3-kinase-AKT signaling pathway and the mammalian target of rapamycin in mitogen-stimulated and transformed cells. Cancer Res 2000;60:3504–13.[Abstract/Free Full Text]
  15. Matthews VB, Yeoh GC. Liver stem cells. IUBMB Life 2005;57:549–53.[Medline]
  16. Roskams TA, Libbrecht L, Desmet VJ. Progenitor cells in diseased human liver. Semin Liver Dis 2003;23:385–96.[CrossRef][Medline]
  17. Fouassier L, Duan CY, Feranchak AP, et al. Ezrin-radixin-moesin-binding phosphoprotein 50 is expressed at the apical membrane of rat liver epithelia. Hepatology 2001;33:166–76.[CrossRef][Medline]
  18. Edmondson HA, Steiner PE. Primary carcinoma of the liver: a study of 100 cases among 48,900 necropsies. Cancer 1954;7:462–503.[CrossRef][Medline]
  19. Song K, Wang H, Krebs TL, Danielpour D. Novel roles of Akt and mTOR in suppressing TGF-ß/ALK5-mediated Smad3 activation. EMBO J 2006;25:58–69.[CrossRef][Medline]
  20. Rodrigues CM, Steer CJ. Fooling the Fas ligand in death. Hepatology 2006;44:314–7.[CrossRef][Medline]
  21. Kim EJ, Park JI, Nelkin BD. IFI16 is an essential mediator of growth inhibition, but not differentiation, induced by the leukemia inhibitory factor/JAK/STAT pathway in medullary thyroid carcinoma cells. J Biol Chem 2005;280:4913–20.[Abstract/Free Full Text]
  22. Fujiuchi N, Aglipay JA, Ohtsuka T, et al. Requirement of IFI16 for the maximal activation of p53 induced by ionizing radiation. J Biol Chem 2004;279:20339–44.[Abstract/Free Full Text]
  23. Kumar-Sinha C, Varambally S, Sreekumar A, Chinnaiyan AM. Molecular cross-talk between the TRAIL and interferon signaling pathways. J Biol Chem 2002;277:575–85.[Abstract/Free Full Text]
  24. Danial NN, Korsmeyer SJ. Cell death: critical control points. Cell 2004;116:205–19.[CrossRef][Medline]
  25. Haouzi D, Baghdiguian S, Granier G, Travo P, Mangeat P, Hibner U. Three-dimensional polarization sensitizes hepatocytes to Fas/CD95 apoptotic signalling. J Cell Sci 2005;118:2763–73.[Abstract/Free Full Text]
  26. Costet P, Legendre C, More J, Edgar A, Galtier P, Pineau T. Peroxisome proliferator-activated receptor {alpha}-isoform deficiency leads to progressive dyslipidemia with sexually dimorphic obesity and steatosis. J Biol Chem 1998;273:29577–85.[Abstract/Free Full Text]
  27. Crabb DW, Galli A, Fischer M, You M. Molecular mechanisms of alcoholic fatty liver: role of peroxisome proliferator-activated receptor {alpha}. Alcohol 2004;34:35–8.[CrossRef][Medline]
  28. Dharancy S, Malapel M, Perlemuter G, et al. Impaired expression of the peroxisome proliferator-activated receptor {alpha} during hepatitis C virus infection. Gastroenterology 2005;128:334–42.[CrossRef][Medline]
  29. Oliver WR, Jr., Shenk JL, Snaith MR, et al. A selective peroxisome proliferator-activated receptor {delta} agonist promotes reverse cholesterol transport. Proc Natl Acad Sci U S A 2001;98:5306–11.[Abstract/Free Full Text]
  30. Tanaka T, Yamamoto J, Iwasaki S, et al. Activation of peroxisome proliferator-activated receptor {delta} induces fatty acid ß-oxidation in skeletal muscle and attenuates metabolic syndrome. Proc Natl Acad Sci U S A 2003;100:15924–9.[Abstract/Free Full Text]
  31. Wang YX, Lee CH, Tiep S, et al. Peroxisome-proliferator-activated receptor {delta} activates fat metabolism to prevent obesity. Cell 2003;113:159–70.[CrossRef][Medline]
  32. Lee CH, Olson P, Hevener A, et al. PPAR{delta} regulates glucose metabolism and insulin sensitivity. Proc Natl Acad Sci U S A 2006;103:3444–9.[Abstract/Free Full Text]
  33. Harman FS, Nicol CJ, Marin HE, Ward JM, Gonzalez FJ, Peters JM. Peroxisome proliferator-activated receptor-{delta} attenuates colon carcinogenesis. Nat Med 2004;10:481–3.[CrossRef][Medline]
  34. Repa JJ, Turley SD, Lobaccaro JA, et al. Regulation of absorption and ABC1-mediated efflux of cholesterol by RXR heterodimers. Science 2000;289:1524–9.[Abstract/Free Full Text]
  35. Shiota G. Loss of function of retinoic acid in liver leads to steatohepatitis and liver tumor: a NASH animal model. Hepatol Res 2005;33:155–60.[CrossRef][Medline]
  36. Hayashi Y, Wang W, Ninomiya T, Nagano H, Ohta K, Itoh H. Liver enriched transcription factors and differentiation of hepatocellular carcinoma. Mol Pathol 1999;52:19–24.[Abstract]
  37. Birkenmeier EH, Gwynn B, Howard S, et al. Tissue-specific expression, developmental regulation, and genetic mapping of the gene encoding CCAAT/enhancer binding protein. Genes Dev 1989;3:1146–56.[Abstract/Free Full Text]
  38. Watkins PJ, Condreay JP, Huber BE, Jacobs SJ, Adams DJ. Impaired proliferation and tumorigenicity induced by CCAAT/enhancer-binding protein. Cancer Res 1996;56:1063–7.[Abstract/Free Full Text]
  39. Tan EH, Hooi SC, Laban M, et al. CCAAT/enhancer binding protein {alpha} knock-in mice exhibit early liver glycogen storage and reduced susceptibility to hepatocellular carcinoma. Cancer Res 2005;65:10330–7.[Abstract/Free Full Text]
  40. Tomizawa M, Watanabe K, Saisho H, Nakagawara A, Tagawa M. Down-regulated expression of the CCAAT/enhancer binding protein {alpha} and ß genes in human hepatocellular carcinoma: a possible prognostic marker. Anticancer Res 2003;23:351–4.[Medline]
  41. Flodby P, Barlow C, Kylefjord H, Ahrlund-Richter L, Xanthopoulos KG. Increased hepatic cell proliferation and lung abnormalities in mice deficient in CCAAT/enhancer binding protein {alpha}. J Biol Chem 1996;271:24753–60.[Abstract/Free Full Text]
  42. Wang ND, Finegold MJ, Bradley A, et al. Impaired energy homeostasis in C/EBP{alpha} knockout mice. Science 1995;269:1108–12.[Abstract/Free Full Text]
  43. Yang J, Croniger CM, Lekstrom-Himes J, et al. Metabolic response of mice to a postnatal ablation of CCAAT/enhancer-binding protein {alpha}. J Biol Chem 2005;280:38689–99.[Abstract/Free Full Text]
  44. Son G, Hirano T, Seki E, et al. Blockage of HGF/c-Met system by gene therapy (adenovirus-mediated NK4 gene) suppresses hepatocellular carcinoma in mice. J Hepatol 2006;45:688–95.[CrossRef][Medline]
  45. Cao R, Brakenhielm E, Pawliuk R, et al. Angiogenic synergism, vascular stability and improvement of hind-limb ischemia by a combination of PDGF-BB and FGF-2. Nat Med 2003;9:604–13.[CrossRef][Medline]
  46. Uematsu S, Higashi T, Nouso K, et al. Altered expression of vascular endothelial growth factor, fibroblast growth factor-2 and endostatin in patients with hepatocellular carcinoma. J Gastroenterol Hepatol 2005;20:583–8.[CrossRef][Medline]



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