cDNA microarray profiling of rat cholangiocarcinoma induced by thioacetamide

  • Authors:
    • Chun‑Nan Yeh
    • Wen‑Hui Weng
    • Govinda Lenka
    • Lee‑Cheng Tsao
    • Kun‑Chun Chiang
    • See‑Tong Pang
    • Tsung‑Wen Chen
    • Yi‑Yin Jan
    • Miin‑Fu Chen
  • View Affiliations

  • Published online on: June 10, 2013     https://doi.org/10.3892/mmr.2013.1516
  • Pages: 350-360
Metrics: HTML 0 views | PDF 0 views     Cited By (CrossRef): 0 citations

Abstract

Cholangiocarcinoma (CCA) is a malignant neoplasm affecting thousands of individuals worldwide. CCA develops through a multistep process. In the current study, an oral thioacetamide (TAA)‑induced model of rat CCA was established which generates the histological progression of human CCA, particularly the mass‑forming type. Seven male Sprague‑Dawley rats were treated with TAA for 24 weeks to induce CCA. Following the generation of the rat CCA model, whole rat genomic oligo microarray was performed to examine gene expression profiles in CCA and non‑cancerous liver samples. In brief, 10,427 genes were found to be differentially expressed (8,318 upregulated and 3,489 downregulated) in CCA compared with non‑tumor liver tissue. The top 50 genes (upregulated or downregulated) were selected and their functional involvement in various pathways associated with cancer progression was analyzed, including cell proliferation, apoptosis, metabolism and the cell cycle. In addition, increased expression of CLCA3, COL1A2, DCN, GLIPr2 and NID1, and decreased expression of CYP2C7 and SLC10A1 were validated by quantitative real‑time PCR. Immunohistochemical analysis was performed to determine the protein expression levels of GLIPr2 and SLC10A1. The gene expression profiling performed in this study provides a unique opportunity for understanding the carcinogenesis of TAA‑induced CAA. In addition, expression profiling of a number of specific genes is likely to provide important novel biomarkers for the diagnosis of CCA and the development of novel therapeutic strategies for CCA.

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 (46). 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 (79).

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 (2,1014), 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 (1719). 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).

Table I

Top 50 significantly upregulated genes with biological process ontologies.

Table I

Top 50 significantly upregulated genes with biological process ontologies.

OntologyGene IDGene symbolGene descriptionFold change
Cell adhesion moleculesNM_031521Ncam1Neural cell adhesion molecule 1 3.92235410303046
NM_012705Cd4CD4 antigen 3.85832760624149
NM_172067Spon1Spondin 1 3.83860585169924
NM_053909NfascNeurofascin 3.44243163237158
Cell deathNM_001007735Sertad1Serta domain-containing 1 4.75153117961431
NM_171988Bcl2l11Bcl2-like 11 (apoptosis facilitator; Bcl2l11), transcript variant 3 4.34809778573906
Cell growthAF454371AhnakAhnak-related protein 4.14343358370448
NM_057211Bteb1Basic transcription element binding protein 1 3.63347765601812
NM_199267v-relV-rel reticuloendotheliosis viral oncogene homolog A (avian; Rela) 3.53615002143989
NM_012817Igfbp5Insulin-like growth factor binding protein 5 3.38491249464085
Deoxyribonuclease I activityNM_013097Dnase1Deoxyribonuclease I 3.8275058577354
FibrosisXM_342827GliPR2Similar to chromosome 9 open reading frame 19; 17 kD fetal brain protein (LOC362509) 4.42322128503159
NM_031050LumLumican 3.45085666984717
Hematopoietic cell lineageNM_001008884RT1-Db1RT1 class II, locus Db1 3.36846228092561
Metabolic pathwaysNM_022525Gpx3Glutathione peroxidase 3 3.93130723332512
NM_012879Slc2a2Solute carrier family 2 (facilitated glucose transporter), member 2 3.8236468641884
NM_153300Aldh1a3Aldehyde dehydrogenase family 1, subfamily 3.74838767192997
NM_175869Plod2Procollagen lysine, 2-oxoglutarate 5-dioxygenase 2 3.42998378780718
Neuroendocrine secretory pathwayNM_019279Pcsk1nProprotein convertase subtilisin/kexin type 1 inhibitor 3.43934389253231
Neuronal differentiationNM_053369Tcf4Transcription factor 4 3.35972972064775
OsteoporosisXM_213440COLIA1Similar to collagen α1 (LOC287636)3.580131772724
Protein digestion and absorptionXM_216399LOC298069Collagen, type XV, α1 (Col15a1) 3.33229268844969
NM_031341Slc7a7Solute carrier family 7 (cationic amino acid transporter, y+ system), member 7 3.33134108780008
RNA transportNM_017063Kpnb1Karyopherin (importin) β1 3.51437343518773
Signal transduction pathwaysNM_001007005ArhgdiaRho gdp dissociation inhibitor (GDI) α 3.9113860940851
NM_013127Cd38Cd38 antigen 3.91115383379829
NM_057116Ppp2r2cProtein phosphatase 2 (formerly 2A), regulatory subunit B (PR 52), γ isoform 3.40886940369163
NM_024129DcnDecorin 3.36137935471163
Structural proteinsNM_181089Mast1Microtubule associated serine/threonine kinase 1 4.11144062655087
OthersU06751pSMCFisher 344 pre-sialomucin complex 6.57759198187846
XM_345756LOC366769Similar to Ig heavy chain precursor V region (IdB5.7) 4.80829731905218
XM_341923LOC361644Similar to pyruvate kinase, M1 isozyme (pyruvate kinase muscle isozyme) 4.24360287494609
XM_225043LOC306628Similar to collagen α 2(IV) chain precursor 4.20372195431914
XM_223569LOC305482Similar to myotubularin-related protein 3 4.15416630589892
XM_233686LOC313722Similar to SPRY domain-containing SOCS box protein SSB-1 4.08502203156001
XM_223781LOC305679Similar to vinculin (metavinculin) 3.90695618191964
NM_139041MUC-13Putative cell surface antigen (LOC207126) 3.89086963314564
XM_236535LOC300920Similar to claudin-2 3.84946284637836
XM_214861LOC292699Similar to casitas B-lineage lymphoma c 3.77729841356227
XM_223944LOC305824Similar to α enolase (2-phospho-D-glycerate hydro-lyase) (Non-neural enolase; NNE; Enolase 1) 3.69235152157205
XM_242992LOC313536Similar to β-1,4-galactosyltransferase II 3.67034914805361
XM_343901LOC363605Similar to RIKEN cDNA 2210407C18 3.66158192578579
XM_342245LOC361945Similar to osteoblast specific factor 2 precursor 3.66054009489806
XM_237497LOC316717Similar to protein phosphatase 1 3.60236548308193
XM_344268LOC364208Similar to DKFZP566K1924 protein 3.51188899584009
XM_214386LOC290856Similar to defensin 5 precursor (RD-5; Enteric defensin) 3.45619469144432
XM_227388LOC310614Similar to transcription repressor p66 3.42529996437158
XM_346200LOC367530Similar to RIKEN cDNA 4933431D05 3.41118393261051
XM_243652Plxnb2Similar to KIAA0315 (LOC315217) 3.40547098028761
XM_233386LOC313499Similar to hypothetical protein DKFZp566D1346 3.40381726129247

Table II

Top 50 significantly downregulated genes with biological process ontologies.

Table II

Top 50 significantly downregulated genes with biological process ontologies.

OntologyGene IDGene symbolGene descriptionFold change
Bile secretionNM_133616Sult2a1Hydroxysteroid preferring 2 (Sth2) −4.9054121581746
NM_017047Slc10a1Solute carrier family 10 (sodium/bile acid cotransporter family), member 1 −3.14433787788225
Cell differentiationXM_223053Usher syndrome 2ASimilar to usherin (LOC289369) −6.40569654980506
Complement and coagulation cascadesNM_022257Masp1Mannose-binding protein associated serine protease-1 −2.85305822741612
Lipid metabolic processNM_139192Scd1Stearoyl-coenzyme A desaturase 1 −3.31761447196781
XM_341791Sult2a2Similar to alcohol sulfotransferase (hydroxysteroid sulfotransferase; ST; ST-60; LOC361510) −3.18536619753157
NM_053923Pik3c2g Phosphatidylinositol 3-kinase, C2 domain containing, γ polypeptide (Pik3c2g)− 3.01034237267081
NM_144750LOC246266 Lysophospholipase −2.92586164948934
NM_012737Apoa4Apolipoprotein A-IV −2.84424543169138
Metabolic pathwaysNM_017158Cyp2c7Cytochrome P450, family 2, subfamily c, polypeptide 7 −3.66306395998859
NM_138904Gls2Glutaminase 2 (liver, mitochondrial) −3.34037650319876
NM_012540Cyp1a1Cytochrome P450, family 1, subfamily a, polypeptide 1 −3.32079040147379
NM_017193AadatAminoadipate aminotransferase −3.01966588124673
NM_175760Cyp4a3Cytochrome P450, family 4, subfamily a, polypeptide 3 −2.87595624954108
NM_017159HalHistidine ammonia lyase −2.84715718276888
NM_053902Kynukynureninase (L-kynurenine hydrolase) −2.71604891669278
NM_030850Bhmt Betaine-homocysteine methyltransferase −2.68923042042384
NM_031835Agxt2Alanine-glyoxylate aminotransferase 2 (Agxt2) −2.64435761342884
NM_012541Cyp1a2Cytochrome P450, family 1, subfamily a, polypeptide 2 (Cyp1a2) −2.64005746673363
NM_001013057LOC291283Aldo-keto reductase family 1, member C2 (Akr1c2) −2.62748122574613
NM_198784Mup4Major urinary protein 4 (Mup4) −2.57882737786856
Olfactory transductionNM_001000888Olr1692Olfactory receptor gene −4.83343644893506
NM_001000696Olr1845Olfactory receptor gene −3.1610886895668
NM_001000386Olr415Olfactory receptor gene −2.75631096513904
Peroxisome biogenesisNM_031587Pxmp2Peroxisomal membrane protein 2 (Pxmp2) −2.79776944314083
Signaling pathwaysNM_024352Mst1Macrophage stimulating 1 (hepatocyte growth factor-like) −3.01686336303489
NM_012630PrlrProlactin receptor (Prlr) −2.78270670754098
NM_012799NmbrNeuromedin B receptor (Nmbr) −2.72210897797388
Trypsin inhibitorNM_152936LOC266602Serine peptidase inhibitor, Kazal type 1 (Spink1) −2.72988934134003
OthersTC500715TC500715Unknown −4.99924740959998
XM_226197LOC291810Similar to cDNA sequence BC033409 −4.85708838735576
XM_224106LOC290148Similar to T-cell receptor α chain precursor V and C regions (TRA29)-rat (fragment) −4.47997612759399
NM_001001799RSEP4Spinal cord expression protein 4 −3.92583197177519
TC462695TC462695I52849 alcohol sulfotransferase −3.75483258125134
U33847Gucy2gksGC mRNA, complete cds −3.68824766043768
XM_228610LOC302446Similar to expressed sequence AW011752 −3.59095310312283
AY383691AY383691LRRGT00036 mRNA, complete cds −3.20650059581476
AF010442AF010442MARRLC7A mRNA −3.17415725515125
TC490222TC490222AB027125 aldo-keto reductase AKR1C13 −3.12591316822196
XM_224468LOC290458Similar to tripartite motif-containing 52 −3.12295823834706
XM_222983LOC289295Similar to putative pheromone receptor (Go-VN2) −3.0085660426128
XM_230584LOC311387Similar to CG1090-PB (Drosophila melanogaster) −2.85086212260344
XM_341007LOC360734Similar to dnaJ (Hsp40) homolog, subfamily B, member 11 −2.82980905422533
XM_233818LOC313840Similar to hypothetical protein −2.79863476103598
XM_344625LOC364771Similar to aldo-keto reductase family 1 member C3 (Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase) (Chlordecone reductase homolog HAKRb) (HA1753) (Dihydrodiol dehydrogenase, type I) (Dihydrodiol dehydrogenase 3; DD3) −2.795863390899
XM_342422LOC362120Similar to complement C5 precursor −2.70059226884497
NM_012674Spink3Serine peptidase inhibitor, Kazal type 3 (Spink3) −2.67592384788853
AY387049AY387049LRRGT00063 −2.65932082072998
NM_147215Obp3α-2u globulin PGCL4 (Obp3) −2.65115608927097
XM_235065LOC299735Similar to hypothetical protein MGC35366 (LOC299735) −2.64919760822929
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).

Table III

Primer sequences used for qPCR validation.

Table III

Primer sequences used for qPCR validation.

Accession no.GeneGene namePrimers (forward/reverse)Annealing temperature (°C)
XM_217689Clca3Chloride channel calcium activated 35′-AAG GTG GCC TAC CTC CAA GT-3′
5′-GAG AAT AGG CGA GGC TCC TT-3′
58
NM_053356Col1a2Procollagen, type I, α25′-TTG ACC CTA ACC AAG GAT GC-3′
5′-CAC CCC TTC TGC GTT GTA TT-3′
60
NM_024129DcnDecorin5′-CAA TAG CAT CAC CGT TGT GG-3′
5′-CCG GAC AGG GTT GCT ATA AA-3′
60
XM_342827Glipr2GLI pathogenesis-related 25′-GAA TGT CCC ACC TCC AAA GA-3′
5′-TCA CAG GAG ATG CTC ACA GG-3′
60
XM_213954Nid 1Nidogen 15′-CCA CCC ACA TAA GCA TAC CC-3′
5′-ACT CCC AAG GTG TTG TCA GG-3′
60
NM_017158Cyp2c7Cytochrome P450, family 2, subfamily c, polypeptide 75′-ACG GGG AGA AGT TTT CTG GT-3′
5′-TGT GCT TCC TCT TGA ACA CG-3′
60
NM_017047Slc10a1Solute carrier family (sodium/bile acid cotransporter family), member 110 5′-GGT GCC CTA CAA AGG CAT TA-3′
5′-TGA TGA CAG AGA GGG CTG TG-3′
60
Reference60
β-actin5′-GAC AGG ATG CAG AAG GAG AT-3′
5′-CTG CTT GCT GAT CCA CAT CT-3′
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 (2730). 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 (3135). 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).

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August 2013
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APA
Yeh, C., Weng, W., Lenka, G., Tsao, L., Chiang, K., Pang, S. ... Chen, M. (2013). cDNA microarray profiling of rat cholangiocarcinoma induced by thioacetamide. Molecular Medicine Reports, 8, 350-360. https://doi.org/10.3892/mmr.2013.1516
MLA
Yeh, C., Weng, W., Lenka, G., Tsao, L., Chiang, K., Pang, S., Chen, T., Jan, Y., Chen, M."cDNA microarray profiling of rat cholangiocarcinoma induced by thioacetamide". Molecular Medicine Reports 8.2 (2013): 350-360.
Chicago
Yeh, C., Weng, W., Lenka, G., Tsao, L., Chiang, K., Pang, S., Chen, T., Jan, Y., Chen, M."cDNA microarray profiling of rat cholangiocarcinoma induced by thioacetamide". Molecular Medicine Reports 8, no. 2 (2013): 350-360. https://doi.org/10.3892/mmr.2013.1516