cDNA microarray profiling of rat cholangiocarcinoma induced by thioacetamide
- Authors:
- Published online on: June 10, 2013 https://doi.org/10.3892/mmr.2013.1516
- Pages: 350-360
Abstract
Introduction
Cholangiocarcinoma (CCA) is a lethal malignancy derived from the epithelial cells (i.e. cholangiocytes) of the bile duct. CCA exhibits a considerable variety of symptoms commonly at the later stages of disease and therefore treatment for CCA is extremely difficult. CCA is grossly divided into mass forming (MF), periductal infiltrating and intraductal papillary subtypes (1). Gross pathological classifications of CCA are important in clinical practice and further translational investigations due to the distinct characteristics and outcomes following hepatectomy (2). The incidence of CCA exhibits considerable geographical variation but generally accounts for 5–30% of primary liver cancer (3). Previous studies have reported that the incidence and mortality rates of CCA have been increasing worldwide, particularly intrahepatic CCA (4–6). CCA is caused by a number of risk factors, including parasitic infections, primary sclerosing cholangitis, choledochal cysts, hepatolithiasis and carcinogen exposure, which leads to the significant variance in incidence rates of CCA worldwide (7–9).
Clinically, CCA remains extremely challenging as patients do not typically exhibit clear symptoms until the disease is quite advanced and therefore it is difficult to diagnose in its early stages. In addition to surgical treatments (2,10–14), radiation therapy and current chemotherapeutic protocols have not been found to significantly improve the long-term survival rates of CCA patients (8,15). In our previous study, a thioacetamide (TAA)-induced CCA rat model was established to analyze the molecular and morphological behavior of CCA, aiming to generate a powerful preclinical platform to provide insights into therapeutic and chemopreventative strategies for human CCA (16). Since the model recapitulates the dysplasia-carcinoma sequence of human CCA, it is likely to be crucial for the identification of the genetic basis of cholangiocellular neoplasia.
A number of previous studies have aimed to determine the molecular alterations involved in cholangiocarcinogenesis; however, these processes remain largely unknown (17–19). At present, gene expression profiling by DNA microarray represents a promising technique for understanding the molecular abnormalities involved in cancer development. In our previous study, MUC4 overexpression was identified in rat CCA (carcinogenesis caused by TAA) compared with non-tumor liver tissue (20). In the present study, a whole genome rat cDNA microarray was used to determine whether the gene expression profile for CCA reflects a specific etiological agent, with the aim to improve the understanding of the molecular events associated with CCA. In addition, this study compared the molecular profiles in non-cancerous liver to TAA-induced CCA to gain insight into changes in gene expression associated with cholangiocellular carcinogenesis and to identify potential diagnostic biomarkers. The investigation of the molecular pathophysiology associated with CCA is becoming increasingly important and necessary.
Materials and methods
Animals, treatment and CCA samples
The experimental animal ethics committee of Chang Gung Memorial Hospital (Linkou, Taiwan, R.O.C.) approved all animal protocols in this study. This study conformed to the US National Institute of Health guidelines for the care and use of laboratory animals (21). Seven adult male Sprague-Dawley (SD) rats (330–370 g) were used in these experiments. Rats were housed in an animal room under a 12:12-hour light-dark cycle (light between 08:00 a.m. and 08:00 p.m.) at an ambient temperature of 22±1°C, with food and water available ad libitum. Seven experimental rats were administered 300 mg/l TAA in their drinking water daily until week 24. CCA was collected over the 24-week TAA treatment. Only CCA was used for array analysis to avoid variations in expression arising from histologically different tumor progression. Each carcinoma used in this study was obtained from a separate rat.
RNA isolation
Total RNA was isolated using TRIzol (Invitrogen Life Technologies, Carlsbad, CA, USA) according to the manufacturer’s instructions. The integrity of RNA was checked using an agarose gel.
Expression array
The Whole Rat Genome oligo-microarray (P/N G4131A; Agilent Technologies, Santa Clara, CA, USA) was used for microarray experiments. RNA sample preparation for microarray analysis was performed according to the manufacturer’s instructions. In brief, 20 μg total RNA was used for cyanine 3-dUTP (Cy3; test) and Cy5-dUTP (reference) labeling. Labeling was performed by oligo(dT)-primed polymerization using SuperScript II reverse transcriptase (Life Technologies, Grand Island, NY, USA) and the labeled Cy3 and Cy5 cDNA probes were purified using a Qiagen PCR QIAquick PCR Purification kit (#28104; Qiagen, Hilden, Germany). Array hybridization was performed at 60°C for 14–16 h. Following hybridization, the array was washed and dried using the Agilent washing kit. The array image was captured using the Axon GenePix 4000 laser scanner and probe intensity was calculated with GenePix Pro 6.0 software (Molecular Devices, Sunnyvale, CA, USA). The raw data was further examined using Nexus Expression Software (BioDiscovery, Hawthorne, CA, USA).
Data processing and analysis
Microarray data analysis was performed as described previously with specific modifications (22). Image analysis was performed with GenePix Pro software. Automatic and manual flagging were used to localise absent or extremely weak spots (<2-fold higher than background), which were excluded from the analysis. The signal from each spot was calculated as the average intensity minus the average local background. Expression ratios of Cy5/Cy3 (or Cy3/Cy5 in case of dye-swap) were normalized using a method that accounts and corrects for intensity-dependent artefacts in the measurements; the LOWESS method in the SMA package. SMA is an add-on library written in the public domain statistical language, R. Three independent microarray experiments were performed. Following data normalization, genes with a 2-fold change in expression compared with the control sample were considered as differentially expressed genes between samples. All genes with a log2 ratio ≥1 or ≤-1 were considered to be statistically significant. Specific differentially expressed genes were grouped based on information from the KEGG database (23,24), NCBI, Gene Ontology and DAVID (25,26) (Tables I and II). Specific genes were annotated for several functions; however, genes were assigned to one group only (Tables I and II).
Quantitative real-time PCR (qPCR)
qPCR was performed using SYBR Green Super mix (Bio-Rad, Hercules, CA, USA) in a 20 μl total volume and a Bio-Rad iCycler iQ Real-Time Detection System according to the manufacturer’s instructions. Primers were designed using Beacon Designer software (Premier Biosoft International, Palo Alto, CA, USA) and are presented in Table III. PCR was performed in triplicate and relative gene expression levels in normal and tumor tissue were calculated by normalizing against β-actin expression levels using the comparative CT method. CT represents the cycle numbers at which the amplification reaches a threshold level selected in the exponential phase of all PCR. Data were analyzed using the iCycle iQ system software. Significance of expression difference was identified by the t-test calculator in Graph pad software (GraphPad Software, Inc., La Jolla, CA, USA).
Immunohistochemical analysis
Rat CCA tissues embedded in paraffin were cut into 5-mm sections. The sections were dewaxed in Bioclear (Bio-Optica, Milan, Italy) and rehydrated in decreasing concentrations of ethanol. Paraffin sections were pre-treated in 0.01 M citrate buffer in a microwave oven. Normal horse serum was used as a blocking agent. The sections were then incubated with antibodies against GLIpr2 (Santa Cruz Biotechnology, Inc., Santa Cruz, CA, US) and SLC10A1 (Abnova, Walnut, CA, USA). Following washing in TBS containing 0.1% Tween-20, the sections were exposed to a secondary antibody. Next, the slides were incubated with horseradish peroxidase-avidin-biotin complex (Vectastain ABC Elite; Vector Laboratories, Burlingame, CA, USA). The complex-binding site was visualized by 3,3′-diaminobenzidine (Vector Laboratories). Sections were counterstained with hematoxylin and dehydrated prior to mounting with Pertex (Histolab Products AB, Gothenburg, Sweden) and observed under a microscrope (Olympus, Yuan Li Instrument, Taipei, Taiwan).
Results
Systemic effects of TAA administration and tumor detection rate
No instances of TAA-induced mortality were observed during the 20-week study period. TAA-fed rats were observed to exhibit significantly lower levels of body weight gain compared with the control rats beginning at 8 weeks post-treatment. Our previous biochemical analysis revealed that levels of total protein, albumin, aspartate aminotransferase, alkaline phosphatase (ALK), bilirubin and prothrombin time (PT) were similar in both groups. According to necropsy and histological results, the incidence of TAA-induced CCA was 100% (16).
Comparative expression profiling of TAA-induced CCA and non-cancerous liver tissue
Microarray gene expression profiling identified 10,427 differentially expressed genes (8,318 for ≥2-fold upregulation, 3,489 for ≤0.5-fold downregulation) in CCA compared with the non-cancerous liver tissue. Fisher 344 pre-sialomucin complex, LOC366769 (similar to Ig heavy chain precursor V region), Serta domain-containing 1, LOC362509 (GliPR 2), Bcl2-like 11 (apoptosis facilitator), pyruvate kinase muscle isozyme (similar to pyruvate kinase, M1 isozyme) and LOC306628 were predominantly overexpressed at high levels in CCA tissues; however, usher syndrome 2A [similar to usherin (LOC289369)], TC500715, hydroxysteroid preferring 2 (sult2a1), LOC291810, olfactory receptor gene (Olr1692), LOC290148 (similar to T-cell receptor α chain precursor V and C regions (TRA29)-rat (fragment) and spinal cord expression protein 4 (RSEP4) were markedly downregulated (Tables I and II). The top 50 upregulated and downregulated genes were selected and classified based on their functional involvement as demonstrated in Tables I and II.
Association of differentially expressed genes with significant molecular processes
The top 50 genes were selected to determine their functional involvement. Molecular databases, including KEGG and NCBI, were used to identify the role of each gene with different pathways. The top most differentially expressed genes in CCA were found to play a significant role in controlling cellular metabolism (Tables I and II). Upregulated genes were largely classified in groups associated with cellular metabolism, extracellular regions and ECM organization/biosynthesis, tumorigenic cascades and other important pathways associated with liver disorders, including fibrosis. Similarly, pathway analysis was performed for downregulated genes. The majority of the downregulated genes were grouped under different pathways of various processes involved in metabolism. Specifically, Sult2a1 and Slc10a1 were classified under roles in bile secretion.
Gene expression validation by qPCR
A number of genes, including Clca3, Col1a2, Dcn, Glipr2 and Nid1 were selected from the microarray expression profile based on roles associated with liver disorders and the observed increased expression was validated. In addition, Cyp2c7 and Slc10a1 were selected to confirm significant alteration of the expression of these genes in the tumor when compared with the non-tumor liver samples. qPCR was performed using total RNA extracted from CCA tissues and normal tissue samples. β-actin was used as an internal control.
Consistent with microarray expression profiling data, Clca3, Col1a2, Dcn, Glipr2 and Nid1 were found to be upregulated in all rat tumor tissues compared with normal rat tissues (Fig. 1). However, expression of Slc10a1 and Cyp2c7 was lower in rat CCA tissues compared with normal rat tissues (Fig. 1). These expression patterns were found to be statistically significant (P<0.05).
Validation of GLIpr2 and SLC10A1 expression by immunohistochemical analysis
The mRNA expression levels of GLIpr2 and SLC10A1 were identified by microarray and qPCR analysis. To determine their protein expression in CCA tissues, immunohistochemical analysis was performed. GLIpr2 was observed as diffusely expressed in the cytoplasm and at the membrane in rat CCA samples; however, expression was absent in normal liver tissue (Fig. 2A). This observation was consistent with mRNA expression levels obtained by microarray where GLIpr2 expression was upregulated in rat CCA compared with normal liver tissue. Immunohistochemical validation was also performed for SLC10A1. However, protein expression levels were observed to be inconsistent with results obtained in the microarray; immunohistochemical analysis revealed upregulation of SLC10A1 protein levels in rat CCA compared with normal liver tissue (Fig. 2B), whereas, SLC10A1 mRNA levels were identified to be downregulated.
Discussion
CCA is a malignant neoplasm which develops through a multistep process, affecting thousands of individuals worldwide. TAA is used as a preservative for oranges; however, it is also considered to be a hepatotoxin and carcinogen, and requires metabolic activation by mixed-function oxidases (27–30). Cytochrome (CY) P450 2B, 2E1 and flavin monooxygenase metabolize TAA into its toxic metabolites (30). Previous studies have identified a number of TAA-induced liver diseases, including hyperplastic liver nodules, liver cell adenomas, hepatocarcinomas, liver cirrhosis and tumors (31–35). In our previous study, male SD rats were administered with 300 mg/l TAA in drinking water to construct an easy and reproducible animal model recapitulating the multi-stage progression of human CCA. The TAA rat model may serve as an important preclinical platform for the development of therapeutic strategies in invasive CCA and the evaluation of rational chemoprevention strategies in the dysplastic biliary epithelium. Yield of invasive CCA in the model rats was 100% at week 22 and at week 25, the yield of CCA and cirrhosis was 100% (16).
Although TAA-induced hepatic pathology is well characterized, a limited number of studies have analyzed the molecular alterations in the development of CCA. For example, alterations in the kinases, c-erb-B2 and c-met, together with possible aberrant autocrine expression of hepatocyte growth factor/scatter factor (HGF/SF), may play a significant role in the development and/or progression of human CCA (17,19,36). In addition, in our previous study the role of MUC4 as a marker of poor prognosis in mass-forming cholangiocarcinoma (MF-CCA) patients undergoing hepatectomy was investigated (20). The aim of the present study was to characterize the molecular alterations associated with TAA-induced rat CCA through cDNA microarray analysis and to identify significantly expressed genes as distinct diagnostic biomarkers for CCA. cDNA microarray analysis was used to identify the most common upregulated and downregulated genes of TAA-induced CCA. The majority of the genes were identified to play important roles in the control of various metabolic pathways.
The liver is the major drug metabolizing organ where several drug-metabolizing enzymes are present, including CYP450. CYP450 is a multi-gene family of important drug-metabolizing enzyme-encoding genes. P450 plays a key role in the metabolism of drugs, steroids, fatty acids and environmental pollutants (37). In the present microarray analysis, altered expression of members of the CYP450 family, including CYP2C7, CYP1A1, CYP4A3 and CYP1A2 (Tables I and II) was identified, consistent with the hypothesis that CYP450 family members are important for the metabolism of carcinogens. Similar to other hepatotoxins (e.g., diethylnitrosamine and carbon tetrachloride), TAA resulted in a significant reduction in the expression of CYP2C7. In agreement with previous studies (38,39), downregulation of CYP2C7 was found in male rats in the current analysis. In addition, increased expression of a number of other genes was identified, including glutathione peroxidase 3, solute carrier family 2, aldehyde dehydrogenase family 1, procollagen lysine and 2-oxoglutarate 5-dioxygenase 2, which are associated with various metabolic processes. These observations indicated that, to support the active function of cells in the CCA environment, genes involved in the metabolism of cells must be upregulated.
In addition, decreased expression of the Na+-dependent taurocholate co-transporting protein (SLC10A1; Fig. 1) was observed, a protein responsible for the majority of hepatocellular uptake of bile salt-coupled chemotherapeutics (40). Previously, downregulation of Ntcp1 (Slc10a1) protein levels has been implicated in cholestasis (41). Reduced expression of Sult2a1 and Slc10a1, genes important for bile secretion (Table III), may play an important role in CCA aetiopathogenesis and those specific proteins may represent future biomarkers.
Increased expression of CLCA3, COL1A2, DCN, GLIpr2 and NID1 was further validated by qPCR (Fig. 1). DCN is a member of the small leucine-rich repeat proteoglycan family and is a major component of the extracellular matrix (42). DCN has been reported to mediate a number of functions, including proliferation, migration and differentiation of human keratinocytes by interacting with the epidermal growth factor receptor, ErbB2 (43), TGFβ (44) and cytokines. In addition to its well-known role in extracellular matrix organization, previous studies have also reported abnormal expression in a number of types of cancer, including oral cancer (45). In the present study, DCN was found to be differentially expressed in CCA, indicating its appearance and overexpression as a possible biological marker of CCA progression.
Nid is an important constituent of basement membranes, which forms a defined supramolecular complex between the extracellular matrix molecules, laminin-1 and type IV collagen (46). Previously, Nid and specific laminin chains were revealed to play a crucial role in determining the outcome of hepatic injury, in a study involving partial hepatectomy. Increased expression of Nid1 may be involved in the concomitant correlation between TAA-induced rat CCA and liver cirrhosis.
In a previous study, increased GLIpr-2 expression in the kidney was hypothesized to contribute to the development of fibrosis by increasing the pool of activated fibroblasts, possibly through the induction of epithelial-mesenchymal transition (47). The biological function of GLIpr-2 remains poorly understood. The enhanced expression of GLIpr-2 in TAA-induced CCA may play a pivotal role in liver fibrosis and represent an additional molecular target which must be analyzed further.
In conclusion, the extensive information gained from the gene expression profiling of TAA-induced CCA performed in the present study is likely to provide important insights into the genes involved in the development of CCA. Further studies must be performed to develop a further understanding of the cellular activities of differentially expressed genes during CCA progression.
Acknowledgements
The present study was supported by grants from the Chang Gung Medical Research Program (no. CMRPG3B0531, CMRPG3B0532, CMRPG3B0361 and CMRPG3B0362).
References
|
Liver Cancer Study Group of Japan. Classification of Primary Liver Cancer. 1st English edition. Kanehara Press Co; Tokyo: 1997 | |
|
Yeh CN, Yeh TS, Chen TC, Jan YY and Chen MF: Gross pathological classification of peripheral cholangiocarcinoma determines the efficacy of hepatectomy. J Gastroenterol. Sep 25–2012.(Epub ahead of print). | |
|
Chen MF: Peripheral cholangiocarcinoma (cholangiocellular carcinoma): clinical features, diagnosis and treatment. J Gastroenterol Hepatol. 14:1144–1149. 1999. View Article : Google Scholar : PubMed/NCBI | |
|
Shaib YH, Davila JA, McGlynn K and El-Serag HB: Rising incidence of intrahepatic cholangiocarcinoma in the United States: a true increase? J Hepatol. 40:472–477. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Patel T: Worldwide trends in mortality from biliary tract malignancies. BMC Cancer. 2:102002. View Article : Google Scholar : PubMed/NCBI | |
|
Chang KY, Chang JY and Yen Y: Increasing incidence of intrahepatic cholangiocarcinoma and its relationship to chronic viral hepatitis. J Natl Compr Canc Netw. 7:423–427. 2009.PubMed/NCBI | |
|
Shaib Y and El-Serag HB: The epidemiology of cholangiocarcinoma. Semin Liver Dis. 24:115–125. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
DeGroen PC, Gores GJ, LaRusso NF, Gunderson LL and Nagorney DM: Biliary tract cancers. N Engl J Med. 341:1368–1378. 1999. View Article : Google Scholar : PubMed/NCBI | |
|
Albores-Saavedra J, Henson DE and Sobin LH: The WHO histological classification of tumors of the gallbladder and extrahepatic bile ducts. A commentary on the second edition. Cancer. 70:410–414. 1992. View Article : Google Scholar : PubMed/NCBI | |
|
Weber SM, Jarnagin WR, Klimstra D, DeMatteo RP, Fong Y and Blumgart LH: Intrahepatic cholangiocarcinoma: resectability, recurrence pattern and outcomes. J Am Coll Surg. 193:384–391. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Uenishi T, Hirohashi K, Kubo S, et al: Histologic factors affecting prognosis following hepatectomy for intrahepatic cholangiocarcinoma. World J Surg. 25:865–869. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Jarnagin WR, Fong Y and DeMatteo RP: Staging, resectability and outcome in 225 patients with hilar cholangiocarcinoma. Ann Surg. 234:507–519. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Patel T: Increasing incidence and mortality of primary intrahepatic cholangiocarcinoma in the United States. Hepatology. 33:1353–1357. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Shirabe K, Shimada M and Harimoto N: Intrahepatic cholangiocarcinoma: Its mode of spreading and therapeutic modalities. Surgery. 131:S159–S164. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Bathe OF, Pacheco JT and Ossi PB: Management of hilar bile duct carcinoma. Hepatogastroenterology. 48:1289–1294. 2001.PubMed/NCBI | |
|
Yeh CN, Maitra A, Lee KF, Jan YY and Chen MF: Thioacetamide-induced intestinal-type cholangiocarcinoma in rat: an animal model recapitulating the multi-stage progression of human cholangiocarcinoma. Carcinogenesis. 25:631–636. 2004.PubMed/NCBI | |
|
Terada T, Nakanuma Y and Sirica AE: Immunohistochemical demostration of MET overexpression in human intrahepatic cholangiocarcinoma and in hepatolithiasis. Hum Pathol. 29:175–180. 1998. View Article : Google Scholar : PubMed/NCBI | |
|
Endo K, Yoon BI, Pairojkul C, Demetris AJ and Sirica AE: ERBB-2 overexpression and cyclooxygenase-2 up-regulation in human cholangiocarcinoma and risk conditions. Hepatology. 36:439–450. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Hansel DE, Rahman A, Hidalgo M, et al: Identification of novel cellular targets in biliary tract cancers using global gene expression technology. Am J Pathol. 163:217–229. 2003. View Article : Google Scholar : PubMed/NCBI | |
|
Yeh CN, Pang ST, Wu RC, Chen TW, Jan YY and Chen MF: Prognostic value of MUC4 for mass-forming intrahepatic cholangiocarcinoma after hepatectomy. Oncol Rep. 21:49–56. 2009.PubMed/NCBI | |
|
National Institutes of Health. Guide for the Care and Use of Laboratory Animals. NIH publication no. 85–23, revised 1996. | |
|
Pang ST, Dillner K, Wu X, Pousette A, Norstedt G and Flores-Morales A: Gene expression profiling of androgen deficiency predicts a pathway of prostate apoptosis that involves genes related to oxidative stress. Endocrinology. 143:4897–906. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Kanehisa M, Goto S, Sato Y, Furumichi M and Tanabe M: KEGG for integration and interpretation of large-scale molecular datasets. Nucleic Acids Res. 40:D109–D114. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Kanehisa M and Goto S: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28:27–30. 2000. View Article : Google Scholar : PubMed/NCBI | |
|
Huang DW, Sherman BT and Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protoc. 4:44–57. 2009.PubMed/NCBI | |
|
Huang DW, Sherman BT and Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37:1–13. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Dasgupta A, Chatterjee R and Chowdhury JR: Thioacetamide-induced hepatocarcinoma in rat. Oncology. 38:249–253. 1981. View Article : Google Scholar : PubMed/NCBI | |
|
Fitzhugh OG and Nielson AA: Liver tumors in rats fed thiourea or thioacetamide. Science. 108:626–628. 1948. View Article : Google Scholar : PubMed/NCBI | |
|
Al-Bader AA, Mathew TC, Abul H, Al-Mosawi M, Panigrahi D and Dashti HM: Bacterial translocation in thioacetamide induced liver cirrhosis. J R Coll Surg Edinb. 43:278–82. 1998.PubMed/NCBI | |
|
Lee JW, Shin KD, Lee M, et al: Role of metabolism by flavin-containing monooxygenase in thioacetamide-induced immunosuppression. Toxicol Lett. 136:163–172. 2003. View Article : Google Scholar : PubMed/NCBI | |
|
Dashti H, Jeppsson B, Hagerstrand I, et al: Early biochemical and histological changes in rats exposed to a single injection of thioacetamide. Pharmacol Toxicol. 60:171–174. 1987. View Article : Google Scholar : PubMed/NCBI | |
|
Gallagher CH, Gupta DN, Judah JD and Rees KK: Biochemical changes in acute thioacetamide intoxication. J Path Bact. 72:193–201. 1956. View Article : Google Scholar : PubMed/NCBI | |
|
Gupta DN: Acute changes in the liver after administration of thioacetamide. J Pathol Bacteriol. 72:183–192. 1956. View Article : Google Scholar : PubMed/NCBI | |
|
Muller D, Zimmerman SI and Schiller F: Drug metabolism in rat liver injured by thioacetamide. Arch Toxicol. 5:368–371. 1982. View Article : Google Scholar | |
|
Dashti HM, Mathew TC, Jadaon MM and Ashkanani E: Zinc and liver cirrhosis: biochemical and histopathologic assessment. Nutrition. 13:206–212. 1997. View Article : Google Scholar : PubMed/NCBI | |
|
Sirica AE, Lai GH and Zhang Z: Biliary cancer growth factor pathways, cyclo-oxygenase-2 and potential therapeutic strategies. J Gastroenterol Hepatol. 16:363–372. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Nelson DR, Zeldin DC, Hoffman SM, Maltais LJ, Wain HM and Nebert DW: Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics. 14:1–18. 2004. View Article : Google Scholar | |
|
Henderson CJ, Russell AL, Allan JA and Wolf CR: Sexual differentiation and regulation of cytochrome P-450 CYP2C7. Biochim Biophys Acta. 1118:99–106. 1992. View Article : Google Scholar : PubMed/NCBI | |
|
Arun KA and Bernard HS: Latent overexpression of hepatic CYP2C7 in adult male and female rats neonatally exposed to phenobarbital: a developmental profile of gender-dependent P450s. J Pharmacol Exp Ther. 293:1027–1033. 2000.PubMed/NCBI | |
|
Hagenbuch B, Stieger B, Foguet M, Lübbert H and Meier PJ: Functional expression, cloning and characterization of the hepatocyte Na+/bile acid cotransport system. Proc Natl Acad Sci USA. 88:10629–10633. 1991. View Article : Google Scholar : PubMed/NCBI | |
|
Trauner M, Meier PJ and Boyer JL: Molecular regulation of hepatocellular transport systems in cholestasis. J Hepatol. 31:165–178. 1999. View Article : Google Scholar : PubMed/NCBI | |
|
Kjellén L and Lindahl U: Proteoglycans: structures and interactions. Annu Rev Biochem. 60:443–475. 1991. | |
|
Santra M, Eichstetter I and Iozzo RV: An anti-oncogenic role for decorin. Downregulation of ErbB2 leads to growth suppression and cytodifferentiation of mammary carcinoma cells. J Biol Chem. 275:35153–35161. 2000. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang Z, Li XJ, Liu Y, Zhang X, Li YY and Xu WS: Recombinant human decorin inhibits cell proliferation and downregulates TGF-beta1 production in hypertrophic scar fibroblasts. Burns. 33:634–641. 2007. View Article : Google Scholar : PubMed/NCBI | |
|
Abhijit GB, Indraneel B, William ML and Jamboor KV: Aberrant expression and localization of decorin in human oral dysplasia and squamous cell carcinoma. Cancer Res. 63:7769–7776. 2003.PubMed/NCBI | |
|
Pujuguet P, Simian M, Liaw J, Timpl R, Werb Z and Bissell MJ: Nidogen-1 regulates laminin-1-dependent mammary-specific gene expression. J Cell Sci. 113:849–858. 2000.PubMed/NCBI | |
|
Baxter RM, Crowell TP, George JA, Getman ME and Gardner H: The plant pathogenesis related protein GLIPR-2 is highly expressed in fibrotic kidney and promotes epithelial to mesenchymal transition in vitro. Matrix Biol. 1:20–29. 2007. View Article : Google Scholar |
