Genome wide analysis and clinical correlation of chromosomal and transcriptional mutations in cancers of the biliary tract

  • George Miller1,

    Affiliated with

    • Nicholas D Socci2,

      Affiliated with

      • Deepti Dhall3,

        Affiliated with

        • Michael D'Angelica4,

          Affiliated with

          • Ronald P DeMatteo4,

            Affiliated with

            • Peter J Allen4,

              Affiliated with

              • Bhuvanesh Singh4,

                Affiliated with

                • Yuman Fong4,

                  Affiliated with

                  • Leslie H Blumgart4,

                    Affiliated with

                    • David S Klimstra3 and

                      Affiliated with

                      • William R Jarnagin4Email author

                        Affiliated with

                        Journal of Experimental & Clinical Cancer Research200928:62

                        DOI: 10.1186/1756-9966-28-62

                        Received: 01 February 2009

                        Accepted: 12 May 2009

                        Published: 12 May 2009

                        Abstract

                        Background

                        The pathogenesis of biliary cancers is ill-defined. This study investigates changes in gene expression and copy number in biliary cancers and correlates these changes with anatomical site of origin, histopathology and outcome.

                        Methods

                        We performed gene expression and CGH analysis on 34 biliary tract cancer specimens. Results were confirmed by RT-PCR. Clinical-pathologic correlation was made using functional over-representation analysis of the top 100 mutations associated with each variable.

                        Results

                        There were 545 genes with altered expression in extrahepatic cholangiocarcinoma, 2,354 in intrahepatic cholangiocarcinoma, and 1,281 in gallbladder cancer. Unsupervised hierarchical clustering analysis indicated there was no difference in the global gene expression patterns between each biliary cancer subgroup. CGH analysis revealed that short segments of chromosomes 1p, 3p, 6q, 8p, 9p, and 14q were commonly deleted across all cancer subtypes. Commonly amplified regions included segments of 1q, 3q, 5p, 7p, 7q, 8q, and 20q. Over-representation analysis revealed an association between altered expression of functional gene groupings and pathologic features.

                        Conclusion

                        This study defined regions of the genome associated with changes in DNA copy number and gene expression in specific subtypes of biliary cancers. The findings have implications for identification of therapeutic targets, screening, and prognostication.

                        Background

                        Biliary tract cancers account for approximately 10–20% of hepatobiliary neoplasms. Approximately 9,000 cases of biliary tumors are diagnosed in the USA each year. Gallbladder carcinoma (GBC) is the most common, accounting for 60% of cases [1]. The remaining 40% are cholangiocarcinomas and are further sub-classified as intrahepatic (IHC) when they arise from intrahepatic biliary radicles or extrahepatic (EHC) when they arise from the confluence of the main left and right hepatic ducts or distal in the bile ducts. The classification of biliary tract cancers into these anatomically-based subtypes has substantial clinical relevance, as risk factors, presentation, staging, and treatment varies for each [2, 3]. Regardless of subtype, most patients with carcinoma of the biliary tract present with advanced disease, with median survival of approximately one to two years from the time of diagnosis [46].

                        Little is known regarding the genetic alterations in the biliary epithelium that lead to cancer. Studies have shown that biliary carcinogenesis may be related in-part to loss of heterozygosity at the loci of chromosomes 1p, 6q, 9p, 16q, and 17p, and point mutations at the K-ras oncogene and the p-53 tumor suppressor gene [7, 8]. Enhanced expression of VEGF in cholangiocarcinoma cells and localization of VEGF receptor-1 and receptor-2 in endothelial cells is thought to play a crucial role in tumor progression [9]. Clyclooxygenase-2 and c-erbB-2 are also overexpressed in cholangiocarcinoma [10]. In addition, interleukin-6 is important in the proliferation of malignant biliary epithelial cells [11, 12]. Our recent work examining cell cycle-regulatory protein expression in biliary tract cancers revealed differentially expressed cell cycle-regulatory proteins based on tumor location and morphology, and an overlap in the pathogenesis of GBC and EHC was suggested [13].

                        The present study investigates alterations in gene expression and gene copy number in frozen tumor specimens from patients with GBC, IHC, and EHC. Gene expression results were correlated with comparative genomic hybridization (CGH) data by identifying transcriptional changes in the most highly unstable genomic regions. Additionally, the genetic findings were correlated with clinical disease characteristics and pathologic features.

                        Methods

                        Patients and specimens

                        Biliary tract cancers from 34 patients (13 IHC, 12 EHC, 9 GBC) were snap-frozen and stored at -80°C. In addition 9 non-cancerous gallbladders and 9 non-cancerous bile duct controls were obtained from patients who had resections for diseases not involving the gallbladder or bile duct (in these patients the gallbladder or bile duct was removed for surgical access to other hepatobiliary or pancreatic structures). Each sample was re-examined histologically using H&E-stained cryostat sections. Surrounding non-neoplastic tissue was dissected from the frozen block under 10× magnification and care was taken that at least 90% for remaining cells were cancerous. All studies were approved by the Memorial Sloan-Kettering IRB.

                        RNA isolation, probe preparation, and expression microarray hybridization

                        Total RNA was isolated from tissue using the DNA/RNA all prep kit (Qiagen, Germantown, Maryland, USA). Quality of RNA was ensured before labeling by analyzing 20–50 ng of each sample using the RNA 6000 NanoAssay and a Bioanalyzer 2100 (Agilent, Santa Clara, California, USA). Samples with a 28S/18S ribosomal peak ratio of 1.8–2.0 and a RIN number >7.0 were considered suitable for labeling. RNA from one IHC specimen, two EHC specimens, and three cases of GBC failed to meet this standard and were discarded from the gene expression analysis. For the remaining samples, 2 μg of total RNA was used for cDNA synthesis using an oligo-dT-T7 primer and the SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen, Carlsbad, California, USA). Synthesis, linear amplification, and labeling of cRNA were accomplished by in-vitro transcription using the MessageAmp aRNA Kit (Ambion, Austin, Texas, USA) and biotinylated nucleotides (Enzo Diagnostics, New York, USA). Ten micrograms of labeled and fragmented cRNA were then hybridized to the Human HG-U133A GeneChip (Affymetrix, Santa Clara, California, USA) at 45°C for 16 hours. Post hybridization staining, washing were processed according to manufacturer. Finally, chips were scanned with a high-numerical aperture and flying objective lens in the GS3000 scanner (Affymetrix). The image was quantified using GeneChip Operating Software (GCOS) 1.4 (Affymetrix).

                        Array CGH profiling

                        Genomic DNA was extracted using the DNA/RNA prep kit (Qiagen). DNA integrity was checked on a 1% agarose gel and was intact in all specimens except one case of EHC. 3 μg of DNA was then digested and labeled by random priming using RadPrime (Invitrogen) and Cy3 or Cy5-dUTP. Labeled DNA was hybridized to 244 K CGH arrays (Agilent) for 40 hours at 60°C. Slides were scanned and images quantified using Feature Extraction 9.1 (Agilent).

                        Real-Time PCR

                        1 ug of total RNA was reverse-transcribed using the Thermoscript RT-PCR system (Invitrogen) at 52°C for 1 h. 20 ng of resultant cDNA was used in a Q-PCR reaction using an iCycler (Biorad, Hercules, California, USA) and pre-designed TaqMan ABI Gene expression Assays (Hs00270424_m1 for CCNB2, Hs00938777_m1 for CDC2, Hs00175938_m1 for CDKN1C, Hs01665258_m1 for DLC1, Hs01547109_m1 for FOSB, Hs99999032_m1 for IL6, s01118813_m1 for NR4A2, Hs00971643_g1 for SRD5A1, Hs01014001_m1 for STAT1, Hs00426591_m1 for TYMS, Hs00197374_m1 for UBD). Primers were chosen based on their ability to span the most 3' exon-exon junction. Amplification was carried for 40 cycles (95C for 15 sec, 60C for 1 min). To calculate the efficiency of the PCR reaction, and to assess the sensitivity of each assay, we also performed a 7 point standard curve (5, 1.7,0.56,0.19,0.062,0.021, and 0.0069 ng). Amounts of target were interpolated from the standard curves and normalized to HPRT (Hs99999909_m1).

                        Data Analysis

                        Image files were quantified using GCOS 1.1 to generate the CEL files. These were normalized using the GC-RMA package from the Bioconductor toolkit (Bioconductor, Seattle, Washington State, USA). Expression values were log (base 2) transformed for all subsequent analysis. Unsupervised hierarchical clustering was done using a distance measure derived from the Pearson correlation (distance = (1-ρ)/2 were ρ is the correlation coefficient) and average linkage options. To determine differentially expressed genes a variant of the t- and F-tests were used as implemented in the LIMMA toolkit (Bioconductor). To account for multiple-testing the False Discovery Rate (FDR) method was used. An FDR < 0.01 was considered statistically significant. For clinicopathologic correlation, a functional over-representation analysis was done on the top 100 genes. p < 0.001 was considered significant.

                        For the array-CGH data, the raw images were quantified with the Agilent Feature Extraction program and normalized using a combination of intensity dependent and GC-content dependent non-linear normalization procedure. To determine significant changes in copy number, the Circular Binary Segmentation algorithm [14] was used with alpha set to 0.001. Segments that had a log 2 ratio of intensity greater than a sample dependent threshold and a signal-to-noise ratio greater than 0.5 were considered either amplified or deleted.

                        Results

                        Clinicopathologic Data

                        Frozen tissue was analyzed from 34 patients who underwent surgery for biliary tract cancers between August 1993 and December 2005. 13 patients had IHC, 12 had EHC, either at the bile duct bifurcation or in the mid or distal bile duct, and 9 patients had tumors originating within the gallbladder. Selected clinicopathologic features are shown in Table 1. The median age of patients was 64 (range 46–88) and 20 (59%) patients were female. 31 (91%) patients had margin-negative resections, two (6%) patients had margin-positive resections, and one (3%) patient underwent biopsy only.
                        Table 1

                        Clinicopathologic features of biliary tract cancer patients in this study

                        Biliary Cancer Subtype

                        Age

                        Sex

                        Lymph Node Invasion

                        Vascular Invasion

                        Perineural Invasion

                        Pathologic Differentiation

                        Size (cm)

                        Follow-up (months)

                        Disease Status a

                        Extrahepatic

                        77

                        F

                        Present

                        Absent

                        Present

                        Poor

                        2.0

                        42

                        DOD

                        Extrahepatic

                        57

                        F

                        Present

                        Present

                        Present

                        Moderate

                        1.5

                        61

                        DOD

                        Extrahepatic

                        60

                        M

                        Present

                        Present

                        Present

                        Poor

                        1.6

                        18

                        DOD

                        Extrahepatic

                        78

                        M

                        Absent

                        Present

                        Present

                        Poor

                        1.7

                        16

                        NED

                        Extrahepatic

                        81

                        F

                        Absent

                        Absent

                        Absent

                        Well

                        3.1

                        58

                        AWD

                        Extrahepatic

                        75

                        M

                        Absent

                        Present

                        Absent

                        Moderate

                        2.2

                        87

                        AWD

                        Extrahepatic

                        77

                        F

                        Absent

                        Absent

                        Present

                        Moderate

                        4.0

                        45

                        DOD

                        Extrahepatic

                        56

                        M

                        Absent

                        Absent

                        Present

                        Moderate

                        2.0

                        13

                        DOD

                        Extrahepatic

                        67

                        F

                        Absent

                        Absent

                        Present

                        Moderate

                        1.8

                        20

                        DOD

                        Extrahepatic

                        56

                        M

                        Absent

                        Present

                        Present

                        Moderate

                        4.8

                        40

                        DOD

                        Extrahepatic

                        62

                        M

                        Absent

                        Absent

                        Absent

                        Well

                        5.9

                        58

                        NED

                        Extrahepatic

                        47

                        M

                        Absent

                        Absent

                        Present

                        Moderate

                        2.3

                        6

                        DOD

                        Intrahepatic

                        64

                        M

                        Absent

                        Absent

                        Absent

                        Moderate

                        8.0

                        32

                        DOD

                        Intrahepatic

                        66

                        F

                        Absent

                        Present

                        Absent

                        Moderate

                        13.0

                        6

                        DOD

                        Intrahepatic

                        63

                        M

                        Absent

                        Present

                        n/a

                        Poor

                        9.9

                        14

                        DOD

                        Intrahepatic

                        56

                        M

                        Absent

                        Present

                        Absent

                        Moderate

                        11.0

                        18

                        DOD

                        Intrahepatic

                        70

                        M

                        Absent

                        Absent

                        n/a

                        Moderate

                        6.0

                        98

                        NED

                        Intrahepatic

                        53

                        F

                        Absent

                        Present

                        Present

                        Moderate

                        8.5

                        23

                        DOD

                        Intrahepatic

                        60

                        F

                        Absent

                        Absent

                        Absent

                        Poor

                        18.0

                        40

                        DOD

                        Intrahepatic

                        68

                        F

                        Absent

                        Absent

                        Absent

                        Moderate

                        12.0

                        33

                        DOD

                        Intrahepatic

                        50

                        M

                        Absent

                        Absent

                        Absent

                        Well

                        21.0

                        68

                        NED

                        Intrahepatic

                        60

                        F

                        Absent

                        Absent

                        Absent

                        Moderate

                        20.0

                        20

                        DOD

                        Intrahepatic

                        58

                        M

                        Present

                        Present

                        Absent

                        Moderate

                        9.0

                        38

                        DOD

                        Intrahepatic

                        46

                        F

                        Present

                        Present

                        Absent

                        Moderate

                        7.0

                        37

                        NED

                        Intrahepatic

                        87

                        F

                        Present

                        Absent

                        Absent

                        Moderate

                        14.0

                        11

                        NED

                        Gallbladder

                        58

                        F

                        Present

                        Absent

                        Present

                        Moderate

                        1.5

                        n/a

                        n/a

                        Gallbladder

                        78

                        F

                        Absent

                        Absent

                        Absent

                        Moderate

                        12.0

                        77

                        NED

                        Gallbladder

                        79

                        F

                        Absent

                        Absent

                        Absent

                        Moderate

                        9.0

                        62

                        NED

                        Gallbladder

                        51

                        F

                        Present

                        Present

                        Present

                        Poor

                        4.7

                        24

                        AWD

                        Gallbladder

                        61

                        F

                        Present

                        Present

                        Present

                        Moderate

                        2.0

                        1

                        DUC

                        Gallbladder

                        88

                        F

                        Absent

                        n/a b

                        n/a

                        Moderate

                        8.7

                        2

                        DOD

                        Gallbladder

                        68

                        F

                        Absent

                        n/a

                        n/a

                        Moderate

                        3.5

                        82

                        NED

                        Gallbladder

                        78

                        F

                        Present

                        Present

                        Present

                        Moderate

                        9.0

                        3

                        DOD

                        Gallbladder

                        78

                        M

                        Present

                        Present

                        Present

                        Moderate

                        4.7

                        13

                        NED

                        At last follow-up, 10 (29%) patients were alive without evidence of disease, 3 (9%) patients were alive with recurrent disease and 19 (56%) died as a result of their disease. One (3%) patient died of an unrelated cause and one (3%) patient was lost to follow-up. The median follow-up for surviving patients was 58 months (range 11–98). A review of pathologic features revealed that 6 (18%) patients had poorly differentiated tumors, 11 (32%) patients had evidence of lymph node invasion, 15 (44%) had vascular invasion, and 15 (44%) had perineural invasion. The median tumor size was 11.0 cm (range 6.0 – 21.0) for IHC, 2.1 cm (range 1.5 – 5.9) for EHC, and 4.7 cm (range 1.5 – 12.0) for GBC (Table 1).

                        Gene Transcriptional Alterations in Biliary Carcinomas

                        We analyzed alterations in gene expression in EHC, IHC, and GBC compared with non-cancerous bile duct or gallbladder controls using the Human Genome U133A GeneChip. Figure 1 depicts the 40 top ranking overexpressed and underexpressed genes for (a) extrahepatic cholangiocarcinoma, (b) IHC, and (c) GBC. Ranking was based on FDR values. Table 2 summarizes the extent of gene expression alterations for each type of biliary tract cancer. In the EHC specimens, differential expression was noted in 545 genes compared with 2,354 in IHC and 1,281 in GBC (See additional files 1, additional file 2, and additional file 3). There was a near equal distribution of overexpressed and underexpressed genes for each tumor type. However, higher fold changes in expression levels were seen more commonly with underexpressed genes. In particular, depending on cancer subtype, 16–22% of genes with decreased expression had greater than 10-fold changes expression levels compared with controls. Conversely, only 2–12% of genes with increased expression had alterations of 10-fold or greater (Table 2).
                        Table 2

                        Summary of transcription mutations in subtypes of biliary tract carcinoma

                         

                        Extrahepatic Cholangiocarcinoma

                        Intrahepatic Cholangiocarcinoma

                        Gallbladder Carcinoma

                        Number of transcriptional changes

                        545

                        2354

                        1281

                        Increased expression

                        200

                        1286

                        479

                        Decreased expression

                        345

                        1068

                        802

                        Increased > 20-fold

                        3

                        10

                        26

                        Increased > 10-fold

                        16

                        31

                        59

                        Decreased > 20-fold

                        22

                        88

                        72

                        Decreased > 10-fold

                        56

                        227

                        174

                        http://static-content.springer.com/image/art%3A10.1186%2F1756-9966-28-62/MediaObjects/13046_2009_Article_149_Fig1_HTML.jpg
                        Figure 1

                        Gene Expression Alterations in Biliary Tract Cancers. Heat maps showing the top 40 overexpressed (red) and top 40 underexpressed (green) genes for (a) EHC, (b) IHC, and (c) GBC. (d) All malignant subtypes were also combined for analysis and compared in terms of gene expression with benign bile duct and gallbladder controls. Genes were ranked based on FDR values. (e) A Venn diagram is used to depict the relationship of transcriptional changes among biliary cancer subtypes. There were 165 common genes with significantly altered expression in all three biliary tract cancer subtypes.

                        Comparative Analysis of Biliary Cancer Subtypes

                        Unsupervised hierarchical clustering analysis revealed that the three cancer subtypes did not cluster separately, implying that there was no difference in the global gene expression patterns between the biliary cancer subgroups. Figure 1d depicts the top 40 up-regulated and down-regulated genes for all cancers combined versus the 18 control specimens. However, while the individual cancer subtypes did not cluster separately, there was unique differential expression of many genes compared with normal biliary epithelium in each cancer subtypes. The relationship of gene transcriptional changes among the three biliary cancer subtypes is depicted in a Venn diagram (Figure 1e). There was unique altered expression of 1633, 80, and 790 genes in IHC, EHC, and GBC, respectively. Overall, 165 probe sets were commonly differentially expressed in all 3 cancer types (See additional file 4). Selected commonly differentially expressed genes are listed in Table 3.
                        Table 3

                        Selected genes with significantly altered expression in all three biliary cancer subtypes with the fold-change (Δ) in expression

                        Δ GB

                        Δ Intra

                        Δ Extra

                        Gene Symbol

                        Gene Title

                        Chromosomal Location

                        Functional Pathway

                        58

                        11

                        11

                        RRM2

                        ribonucleotide reductase M2 polypeptide

                        chr2p25-p24

                        Nucleotide metabolism

                        41

                        6

                        10

                        PTTG1

                        pituitary tumor-transforming 1

                        chr5q35.1

                        Cell cycle

                        26

                        9

                        7

                        TYMS

                        thymidylate synthetase

                        chr18p11.32

                        Nucleotide metabolism

                        19

                        4

                        5

                        CDC2

                        Cell division cycle 2, G1 to S and G2 to M

                        chr10q21.1

                        Cell cycle

                        18

                        4

                        7

                        CCNB2

                        cyclin B2

                        chr15q22.2

                        Cell cycle

                        12

                        3

                        4

                        RACGAP1

                        Rac GTPase activating protein 1

                        chr12q13.12

                        S1P Signaling

                        6

                        5

                        4

                        SHMT2

                        serine hydroxymethyltransferase 2 (mitochondrial)

                        chr12q12-q14

                        Amino acid metabolism

                        3

                        3

                        3

                        PPAT

                        phosphoribosyl pyrophosphate amidotransferase

                        chr4q12

                        Purine metabolism

                        3

                        3

                        5

                        MCM6

                        MCM6 minichromosome maintenance deficient 6

                        chr2q21

                        Cell cycle

                        3

                        3

                        3

                        GMPS

                        guanine monphosphate synthetase

                        chr3q24

                        Nucleotide metabolism

                        2

                        2

                        2

                        RPS19

                        ribosomal protein S19

                        chr19q13.2

                        Ribosomal protein

                        2

                        3

                        2

                        CBX3

                        chromobox homolog 3

                        chr7p15.2

                        Circadian exercise

                        2

                        3

                        2

                        EIF2AK1

                        eukaryotic translation initiation factor 2-alpha kinase 1

                        chr7p22

                        Translation factor

                        2

                        2

                        2

                        EPRS

                        glutamyl-prolyl-tRNA synthetase

                        chr1q41-q42

                        Glutamate metabolism

                        2

                        2

                        2

                        PARP1

                        poly (ADP-ribose) polymerase family, member 1

                        chr1q41-q42

                        Apoptosis

                        2

                        2

                        2

                        SNRPD2

                        small nuclear ribonucleoprotein D2 polypeptide 16.5 kDa

                        chr19q13.2

                        mRNA processing

                        -2

                        -2

                        -2

                        UBE2G2

                        ubiquitin-conjugating enzyme E2G 2 (UBC7 homolog)

                        chr21q22.3

                        Proteolysis

                        -2

                        -2

                        -2

                        HNRPH1

                        Heterogeneous nuclear ribonucleoprotein H1

                        chr5q35.3

                        mRNA processing

                        -2

                        -3

                        -3

                        SUI1

                        putative translation initiation factor

                        chr17q21.2

                        Translation factor

                        -3

                        -4

                        -3

                        RBM5

                        RNA binding motif protein 5

                        chr3p21.3

                        mRNA processing

                        -3

                        -2

                        -2

                        SFRS5

                        splicing factor, arginine/serine-rich 5

                        chr14q24

                        mRNA processing

                        -3

                        -3

                        -3

                        BCL2L2

                        BCL2-like 2

                        chr14q11.2-q12

                        Apoptosis

                        -4

                        -10

                        -7

                        CDKN1C

                        cyclin-dependent kinase inhibitor 1C (p57, Kip2)

                        chr11p15.5

                        G1 to S cell cycle

                        -4

                        -8

                        -5

                        ZNF423

                        zinc finger protein 423

                        chr16q12

                        TGF-β signaling

                        -4

                        -3

                        -3

                        ACACB

                        acetyl-Coenzyme A carboxylase beta

                        chr12q24.11

                        Fatty acid synthesis

                        -4

                        -4

                        -3

                        RBM5

                        RNA binding motif protein 5

                        chr3p21.3

                        mRNA processing

                        -5

                        -7

                        -5

                        PRKAR2B

                        protein kinase, cAMP-dependent, regulatory, type II, beta

                        chr7q22

                        G protein signaling

                        -5

                        -4

                        -4

                        ACACB

                        acetyl-Coenzyme A carboxylase beta

                        chr12q24.11

                        Fatty acid synthesis

                        -6

                        -4

                        -4

                        ITGA7

                        integrin, alpha 7

                        chr12q13

                        Cellular adhesion

                        -6

                        -7

                        -5

                        RGS2

                        regulator of G-protein signaling 2, 24 kDa

                        chr1q31

                        Calcium regulation

                        -6

                        -9

                        -5

                        KLF9

                        Kruppel-like factor 9

                        chr9q13

                        Circadian exercise

                        -7

                        -7

                        -7

                        RPS6KA2

                        ribosomal protein S6 kinase, 90 kDa, polypeptide 2

                        chr6q27

                        Ribosomal protein

                        -7

                        -15

                        -10

                        ANK2

                        ankyrin 2, neuronal

                        chr4q25-q27

                        Ribosomal protein

                        -8

                        -5

                        -6

                        ACACB

                        acetyl-Coenzyme A carboxylase beta

                        chr12q24.11

                        Fatty acid synthesis

                        -10

                        -4

                        -4

                        MYOM1

                        myomesin 1 (skelemin) 185 kDa

                        chr18p11.32-p11.31

                        Muscle contraction

                        -11

                        -13

                        -8

                        ITGA7

                        integrin, alpha 7

                        chr12q13

                        Cellular adhesion

                        -13

                        -27

                        -14

                        CDKN1C

                        Cyclin-dependent kinase inhibitor 1C (p57, Kip2)

                        chr11p15.5

                        G1 to S cell cycle

                        -61

                        -27

                        -26

                        ALDH1A2

                        aldehyde dehydrogenase 1 family, member A2

                        chr15q21.3

                        Metabolism/Biosynthesis

                        -67

                        -20

                        -7

                        CNN1

                        calponin 1, basic, smooth muscle

                        chr19p13.2-p13.1

                        Muscle contraction

                        -85

                        -51

                        -18

                        CES1

                        carboxylesterase 1

                        chr16q13-q22.1

                        Irinotecan pathway

                        -102

                        -30

                        -24

                        DES

                        desmin

                        chr2q35

                        Muscle contraction

                        Genomic Alterations in Biliary Carcinogenesis

                        To better understand the molecular pathogenesis of biliary tract cancers we used an array based CGH analysis to detect chromosomal areas of DNA copy number gain (DNA copy number of 3 or greater) and loss (DNA copy number of 0 or 1) in the GBC, IHC, and EHC specimens. Figure 2a depicts the chromosomal alterations for each individual cancer specimen while Figure 2b–d represents cumulative summaries of the chromosomal changes for each cancer subtype. Cumulative chromosomal changes for all biliary tract cancers combined are shown in Figure 2e.
                        http://static-content.springer.com/image/art%3A10.1186%2F1756-9966-28-62/MediaObjects/13046_2009_Article_149_Fig2_HTML.jpg
                        Figure 2

                        Chromosomal Structural Mutations in Biliary Tract Cancers. (a) A cumulative depiction of the copy number changes across the genome for all biliary cancer specimens is shown. Chromosomal number is listed on the left. Amplification is depicted in red and deletion in blue. White is unchanged from genomic DNA controls. Increased amplification or deletion within a cancer specimen is reflected in increased color intensity. The percentage of patient specimens that have either amplifications or deletions at each chromosomal loci is shown for (b) EHC, (c) IHC, (d) GBC, and (e) all biliary tract cancers combined.

                        Overall, patients with GBC exhibited the greatest genomic instability while patients with IHC had the fewest amplifications and deletions. In particular, the mean number of chromosomal alterations per patient with GBC was 60.6 (range 17–110) with deletions (mean 35.0, range 9–55) more frequent than amplifications (mean 25.6, range 8–55). Patients with IHC had an average of 49.2 alterations (range 11–101) in DNA copy number with slightly more deletions (mean 26.9, range 8–80) than amplifications (mean 22.2, range 2–47). EHC specimens had an average of 43.8 chromosomal alterations (range 3–110) with an average of 22.5 deletions (range 1–61) and 21.4 amplifications (range 1–62). Moreover, there was considerable heterogeneity in the extent of chromosomal instability between patients even within specific cancer subtypes. For example, a number of patients within each cancer subtype had mutations in nearly every chromosomal arm while other patients with the same tumor type had minimal structural changes in their entire genome (Figure 2a).

                        While the cumulative pattern of chromosomal alterations was highly variable, there appeared to be selected chromosomal regions that were commonly altered across all cancer subtypes. For example, a short segment of chromosome 1p was deleted in greater than 75% of patients with GBC and IHC and nearly 50% of patients with EHC. Similarly, segments of chromosomes 3p, 6q, 8p, 9p, and 14q were commonly deleted across subtypes of biliary cancers. Commonly amplified regions across cancer types include segments of 1q, 3q, 5p, 7p, 7q, 8q, and 20q (Figure 2a–e).

                        Analysis of Transcriptional Changes in Commonly Unstable Genomic Regions

                        To further elucidate the pathogenesis of biliary tract cancers, we integrated the array based CGH data with our gene expression profiling with by identifying gene expression alterations in regions of highest genomic instability. To this end, we investigated the gene expression changes in regions of the genome for which greater than 40% of patients had either chromosomal gains or losses in each cancer subtype (See additional files 5, additional file 6 and additional file 7). Selected alterations in gene expression within these unstable genomic regions are shown in Table 4. Analysis of this data reveals that, as expected, a positive correlation could be made between chromosomal deletion and the loss of gene expression. Conversely, there were no instances of increased gene transcription in regions of chromosomal deletion. However, in regions of chromosomal amplification, both increased and decreased gene transcription were seen with similar frequency.
                        Table 4

                        Selected changes in gene expression in commonly amplified or deleted regions of the genome for all biliary tract cancer specimens

                        Chromosomal Location

                        % Amplified (+) or Deleted (-)

                        Fold Change

                        Gene Title

                        Gene Symbol

                        Functional Properties

                        chr7p11

                        +42%

                        6.5

                        IGF-II mRNA-binding protein 3

                        IMP-3

                        RNA processing

                        chr7p13-p12

                        +45%

                        3.6

                        insulin-like growth factor binding protein 3

                        IGFBP3

                        Regulation of cell growth

                        chr5p15.33

                        +42%

                        3.5

                        thyroid hormone receptor interactor 13

                        TRIP13

                        Regulation of transcription

                        chr20q13.32

                        +45%

                        3.5

                        RAE1 RNA export 1 homolog

                        RAE1

                        mRNA-nucleus export

                        chr7p21.1

                        +48%

                        3.2

                        basic leucine zipper and W2 domains 2

                        BZW2

                        Translation initiation factor

                        chr7q22.1

                        +42%

                        3.0

                        origin recognition complex, subunit 5-like

                        ORC5L

                        DNA replication initiation

                        chr20q13.3

                        +42%

                        2.7

                        ribosomal protein S21

                        RPS21

                        Protien biosysthesis

                        chr7p15

                        +42%

                        2.6

                        oxysterol binding protein-like 3

                        OSBPL3

                        Steroid metabolism

                        chr7p15-p13

                        +42%

                        2.5

                        v-ral simian leukemia viral oncogene homolog A

                        RALA

                        GTPase mediated signal transduction

                        chr20q13.2

                        +48%

                        -6.9

                        docking protein 5

                        DOK5

                        Insulin receptor binding

                        chr7q11.2

                        +42%

                        -7.8

                        CD36 antigen

                        CD36

                        Lipid metabolism

                        chr7q21.1

                        +42%

                        -7.9

                        ATP-binding cassette, sub-family B, member 1

                        ABCB1

                        Cell surface transport

                        chr7p21

                        +45%

                        -9.1

                        interleukin 6

                        IL6

                        Acute phase response

                        chr20q11.23

                        +42%

                        -10.0

                        myosin, light polypeptide 9, regulatory

                        MYL9

                        Regulation of muscle contraction

                        chr7q31-q32

                        +42%

                        -10.9

                        solute carrier family 13, member 1

                        SLC13A1

                        Ion transport

                        chr20q13.13

                        +45%

                        -14.7

                        prostaglandin I2 synthase

                        PTGIS

                        Prostaglandin biosynthesis

                        chr7q31

                        +42%

                        -38.1

                        solute carrier family 26, member 3

                        SLC26A3

                        Transcription factor activity

                        chr6q22.1

                        -55%

                        -46.2

                        phospholamban

                        PLN

                        Calcium ion transport

                        chr9q22

                        -42%

                        -41.0

                        osteoglycin

                        OGN

                        Growth factor activity

                        chr6q24-q25

                        -58%

                        -19.2

                        A kinase anchor protein 12

                        AKAP12

                        Signal transduction

                        chr14q24.3

                        -42%

                        -17.1

                        v-fos FBJ murine osteosarcoma viral oncogene homolog

                        FOS

                        DNA methylation

                        chr14q32.1

                        -45%

                        -13.6

                        fibulin 5

                        FBLN5

                        Cell-matrix adhesion

                        chr3p26-p25

                        -45%

                        -10.0

                        inositol 1,4,5-triphosphate receptor, type 1

                        ITPR1

                        Cation transport

                        chr3p13

                        -52%

                        -9.2

                        PDZ domain containing RING finger 3

                        PDZRN3

                        Protein ubiquitination

                        chr3p21.1

                        -58%

                        -8.9

                        TU3A protein

                        TU3A

                        Regulation of cell growth

                        chr14q32.1

                        -48%

                        -8.5

                        serine proteinase inhibitor, clade A, member 5

                        SERPINA5

                        Endopeptidase inhibitor

                        chr3p22-p21.3

                        -58%

                        -8.5

                        C-type lectin domain family 3, member B

                        CLEC3B

                        Skeletal development

                        chr9p13.2-p13.1

                        -42%

                        -8.3

                        tropomyosin 2

                        TPM2

                        Muscle development

                        chr14q32

                        -48%

                        -8.1

                        delta-like 1 homolog

                        DLK1

                        Calcium ion binding

                        chr6q27

                        -58%

                        -6.5

                        ribosomal protein S6 kinase, 90 kDa, polypeptide 2

                        RPS6KA2

                        Amino acid phosphorylation

                        chr6q24-q25

                        -52%

                        -6.2

                        pleiomorphic adenoma gene-like 1

                        PLAGL1

                        Regulation of transcription

                        chr9p13-p12

                        -42%

                        -5.8

                        reversion-inducing-cysteine-rich protein with kazal motifs

                        RECK

                        Cell cycle regulation

                        chr3p21.2-p21.1

                        -61%

                        -5.4

                        aminomethyltransferase

                        AMT

                        Glycine catabolism

                        chr6pter-qter

                        -48%

                        -5.4

                        transcription factor 21

                        TCF21

                        Regulation of transcription

                        chr9q13

                        -42%

                        -5.1

                        Kruppel-like factor 9

                        KLF9

                        Regulation of transcription

                        chr6q23

                        -48%

                        -3.8

                        serum/glucocorticoid regulated kinase

                        SGK

                        Amino acid phosphorylation

                        chr3p26-p25

                        -45%

                        -3.6

                        inositol 1,4,5-triphosphate receptor, type 1

                        ITPR1

                        Cell cycle regulation

                        chr1p36.13-p36.11

                        -55%

                        -3.2

                        neuroblastoma, suppression of tumorigenicity 1

                        NBL1

                        calcium ion transport

                        chr6q22

                        -55%

                        -2.6

                        mannosidase, alpha, class 1A, member 1

                        MAN1A1

                        Carbohydrate metabolism

                        chr3p22

                        -48%

                        -2.5

                        transforming growth factor, beta receptor II

                        TGFBR2

                        Regulation of cell proliferation

                        Validation of Findings

                        The Affymetrix U133A gene expression array data were both internally and externally validated. First, a large number of gene transcripts were represented by more than one probe set in the array. In each case, the different probes for each detected similar expression levels of transcript (See additional files 1, additional file 2, and additional file 3). This includes genes with altered expression in EHC (i.e. CDKN1C, NR4A3, RBM5, SASH1), IHC (ADH1B, GREM1, MCM4, NR4A2), and GBC (HIST2H2AA, NUSAP1 RPS10, RPS19).

                        In addition, to externally validate our data, selected differentially expressed genes were measured for transcript levels in biliary carcinoma specimens and in normal biliary epithelial controls using quantitative reverse transcriptase PCR. We assayed 11 genes with differing biologic functions and involvement in diverse molecular pathways but with known importance in carcinogenesis. These included genes which were overexpressed in EHC (SRDA21, STAT1, UBD, TYMS), underexpressed in EHC (FOSB, CDKN1C, IL6), overexpressed in IHC (SRDA21, STAT1, UBD, TYMS), underexpressed in IHC (DLC1, NR4A2, IL6), and overexpressed in GBC (UBD, TYMS, CDC2, CCNB2). PCR data was normalized to HPRT which was expressed at similar levels in both the cancerous and the control biliary epithelium (not shown). Results are shown in Figures (3a–f, 4g–k) and, for each gene tested, confirm the Affymetrix U133A gene expression array data. The array-based CGH results were internally validated by correlation of the X chromosome copy number with patient gender.
                        http://static-content.springer.com/image/art%3A10.1186%2F1756-9966-28-62/MediaObjects/13046_2009_Article_149_Fig3_HTML.jpg
                        Figure 3

                        Real-Time PCR Based Validation of Gene Expression Findings. To confirm the gene expression changes in biliary tract cancers identified on microarray analysis, selected genes were tested in tumor and control specimens by RT PCR and normalized to HRPT which is similarly expressed in tumors and normal biliary epithelia. Results are shown for (a) TYMS, (b) UBD, (c) STAT1, (d) SRD5A1, (e) CCNB2, (f) CDC2.

                        http://static-content.springer.com/image/art%3A10.1186%2F1756-9966-28-62/MediaObjects/13046_2009_Article_149_Fig4_HTML.jpg
                        Figure 4

                        Real-Time PCR Based Validation of Gene Expression Findings. To confirm the gene expression changes in biliary tract cancers identified on microarray analysis, selected genes were tested in tumor and control specimens by RT PCR and normalized to HRPT which is similarly expressed in tumors and normal biliary epithelia. Results are shown for (g) IL6, (h) FOSB, (i) CDKN1C, (j) NR4A2, and (k) DLC.

                        Correlation of Gene Expression Profiles with Clinicopathologic Features

                        To determine whether certain clinicopathologic features are associated with specific gene expression changes in biliary carcinomas, we performed over-representation analyses by determining whether certain functional gene categories were over-represented among the top 100 ranking genes (by FDR) with altered expressing in patients with specific clinicopathologic features. Altered expression of genes associated with functional categories related to ribosomal structure, cellular and protein biosynthesis and cellular metabolism were significantly associated with high grade tumors (See additional file 8). Similarly, a strong correlation could be made between vascular invasion and mutated expression of genes involved with electron transport and metabolism (See additional file 9). Perineural invasion was correlated with altered expression of genes in the functional categories associated with mitochondrial structure and electron transport (See additional file 10). There was no significant association between gene expression patterns and lymph node invasion. Similarly, we did not find a significant correlation between functional gene category over-representation and survival.

                        Discussion

                        The molecular pathogenesis of biliary tract cancers is poorly understood. By performing immunohistochemical analysis of more than 125 surgically resected cases of biliary tract carcinoma, we have previously shown altered cell cycle regulatory protein expression in biliary tact cancers [13]. Our current findings also show mutated expression of a large number of cell cycle regulators including UBD, BCL2L2, CDC2, MCM2, and CDKN1C in all subtypes. Similarly, Kang et al. [15] found that expression of G1-S modulators were commonly mutated in 42 cases of IHC. Total loss of p16, p27, and Rb were detected at rates of in 36%, 31%, 12%, respectively, in cancer specimens. Furthermore, in the above study, even in 7 of 13 cases of biliary dysplasia, without frank carcinoma, abnormal expression of p53, cyclin D1 or p16 was detected. Kim et al. [16] reported that the mutation of the p53, p16, and K-ras genes occurred at rates of 36%, 31% and 20%, respectively, in GBC. A further finding of the above study was that 100% of GBCs and 80% of adenomas displayed loss of heterozygosity at a minimum of one locus which is consistent with our CGH results. Chang et al. [17] studied loss of heterozygosity in 32 cases of GBC and 11 cases of dysplasia. Loss of one allele was identified on chromosomes 5q (55%) and 17p (40%) in the dysplastic cases and on chromosomes 3p (52%), 5q (66%), 9p (52%), and 17p (58%) in the carcinomas. Loss of heterozygosity on multiple chromosomes was significantly more frequent in patients with metastatic disease than in cases without metastases. In the current report, we similarly found that segments of 3p and 9p were commonly deleted across all subtypes of biliary cancers. However, we additionally discovered that segments of 6q, 8p, and 14q were commonly deleted across subtypes of biliary cancers

                        There is increasing evidence that overexpression of tyrosine kinase growth factor receptors such as ErbB-2, epidermal growth factor receptor (EGFR), and Met play important roles in the development of biliary tract carcinomas. Nakasawa et al. [18] studied tyrosine kinase receptor proteins expression by in 221 biliary tract carcinomas and found that overexpression of ErbB-2 was found in 16% of carcinomas of the gallbladder and a slightly lower percentage of extrahepatic bile duct tumors. ErbB-2 gene amplification was present in 79% of cases. Overexpression of EGFR was found in 8% of tumors and was also associated with a high frequency of gene amplification (77%). Met overexpression was most frequent in IHC (21.4%) but was not associated with gene amplification. Microsatellite instability also appears to be a critical factor in selected cases of biliary carcinogenesis. Roa et al. [19] performed microsatellite analysis on 59 frozen GBC specimens using 13 different markers. They found evidence of microsatellite instability in equal proportions in early and late cancers, and it was also found in premalignant lesions, indicating that inactivation of mismatch repair genes occurs early in gallbladder carcinogenesis.

                        In addition to finding that a large proportion of differentially expressed genes in this study involved in cell cycle regulation and apoptosis, we also discovered a disproportionate number of mutated genes that control transcriptional regulation, RNA procession, cellular signaling, or are involved with cytoskeletal structure, extracellular matrix, and cellular adhesion. Differentially expressed genes involved with transcriptional regulation include STAT1, NARG1, HOXC6, and MMP11. Important genes involved with signal transduction with altered expression include CXCL5, ECT2, GPRC5A, MELK, and CKS2. Dysregulated genes involved with cytoskeleton, extracellular matrix and cellular adhesion include ITGA7, LAMB3, CECAM5, KRT6B, and CLDN18.

                        The findings of the present study will serve as a resource for other investigators in this area as we have indentified many potential targets for therapeutic intervention. As an example, we found that TYMS, which encodes an enzyme that catalyzes 5-fluorouracil, was overexpressed 7.2 – 26.0-fold depending on biliary cancer subtype. TYMS expression is correlated inversely with clinical response to 5-fluorouracil-based chemotherapy and the overexpression may explain the futility of 5-fluorouracil-based chemotherapy for biliary carcinomas [20].

                        We also found that a number of genes in the ubiquitin pathway had altered expression in each cancer subtypes. For example, more than 20 ubiquitin-related genes had significantly altered expression IHC. In GBC, UBD was overexpressed more than 200-fold and UBE2C was overexpressed nearly 15-fold. Ubiquitin and ubiquitin-like proteins are signaling messengers that regulate a variety of cellular processes including cell proliferation, cell cycle regulation, DNA repair, and apoptosis. There is accumulating evidence that deregulation of this pathway as a result of mutations or altered expression of ubiquitylating or de-ubiquitylating enzymes as well as of Ub-binding proteins affect crucial mediators of these functions and are underlie the pathogenesis of several human malignancies [21]. A variety of inhibitors of the ubiquitin system are currently being experimentally tested in clinical trials with promising early results [22]. These data suggests these inhibitors may have applicability as adjuvants in treating patients with biliary tract carcinomas.

                        Another promising target uncovered in this report is STAT-1 which was overexpressed nearly 9-fold in cases of cholangiocarcinoma. The Signal Transducers and Activator of Transcription (STAT) proteins regulate many aspects of cell growth, survival and differentiation. The transcription factors of this family are activated by the Janus Kinase JAK and dysregulation of this pathway has been observed in primary tumors and leads to increased angiogenesis, metastases, enhanced survival of tumors, and immunosuppression [23, 24]. A number of JAK/STAT pathway inhibitors are being tested in pre-clinical studies and their application to cancers of the biliary tract may prove promising [25].

                        Conclusion

                        Both gene expression and CGH data support an overlapping pathogenetic mechanism for all subsets of biliary tract cancers. However, exceptional diversity of mutational findings between individual patient specimens is also apparent. Functional over-representation analysis revealed a significant association between altered expression of genes involved with regulation of cellular metabolism and biosynthesis and high pathologic grade. Vascular invasion was associated with mutated expression of genes involved with electron transport and cellular metabolism. CGH analysis revealed that short segments of chromosomes 1p, 3p, 6q, 8p, 9p, and 14q were commonly deleted across all cancer subtypes while commonly amplified regions included segments of 1q, 3q, 5p, 7p, 7q, 8q, and 20q. The data also offer opportunities to uncover potential targets for experimental therapeutics.

                        Declarations

                        Acknowledgements

                        This work was supported in part by the Christina and Paul Martin Foundation. The authors thank Tina Thomas for her help in preparing this manuscript for publication.

                        Authors’ Affiliations

                        (1)
                        Department of Surgery and Cell Biology, New York University School of Medicine
                        (2)
                        Department of Biostatistics, Memorial Sloan-Kettering Cancer Center
                        (3)
                        Department of Pathology, Memorial Sloan-Kettering Cancer Center
                        (4)
                        Department of Surgery, Memorial Sloan-Kettering Cancer Center

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                        Copyright

                        © Miller et al; licensee BioMed Central Ltd. 2009

                        This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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