Optimization of liver biopsy RNA sampling and use of reference RNA for cDNA microarray analysis

ANALYTICAL BIOCHEMISTRY Analytical Biochemistry 337 (2005) 224–234 www.elsevier.com/locate/yabio

Optimization of liver biopsy RNA sampling and use of reference RNA for cDNA microarray analysis Fumiyo Takemuraa, Niro Inabaa, Eiji Miyoshib, Takako Furuyaa, Hiroshi Terasakia, Satoshi Andoa, Noriaki Kinoshitac, Yoshiyasu Ogawad, Naoyuki Taniguchib, Satoru Itoa,¤,¤¤ b

a JGS Japan Genome Solutions, Inc., 51 Komiya-Cho, Hachioji, Tokyo 192-0031, Japan Department of Biochemistry, Osaka University Medical School, Graduate School of Medicine, B1, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan c IBL. Co. Ltd., 1091-1 Naka, Fujioka-Shi, Gunma 375-0005, Japan d Mitsubishi Kagaku Bio-Clinical Laboratories, Inc., 3-30-1 Shimura, Itabashi-ku, Tokyo 174-8555, Japan

Received 2 August 2004 Available online 8 December 2004

Abstract In this study, we used the rat liver as a model system to optimize the conditions for extracting RNA from liver biopsies for use in cDNA microarrays. We found that a 5-mm biopsy with a 16-gauge needle and storage in RNAlater at 4 °C were optimal conditions for RNA extraction. The most important factor for the quantity and quality of RNA extraction was the sample diameter. Using the optimized sampling conditions and a cDNA microarray, we compared the expression of genes in the normal and the Wbrotic tissues of the LEC rat liver, a model of liver tumorigenesis, with SD rat liver RNA as a reference. We found 29 genes that were up-regulated and 33 genes that were down-regulated in the Wbrotic part of the liver. Furthermore, with the help of the reference RNA, we were able to classify the expression proWles into Wve groups without complex mathematical analyses; without the reference RNA, the genes could be classiWed into only two groups. Finally, we found that osteopontin was expressed at a very high level in the Wbrotic portion of the LEC rat liver. This cDNA microarray result was validated by immunohistochemistry, which showed an elevated expression of osteopontin in the region of cholangiocarcinoma and a lack of expression in normal tissues. With optimized conditions, we should be able to apply the microarray system for routine practice.  2004 Elsevier Inc. All rights reserved. Keywords: RNA handling conditions; cDNA microarray; Reference RNA; LEC rat model; Tumorigenesis; Osteopontin

Although DNA microarrays have been mostly used for disease classiWcation, they are now employed for discovering clinically relevant genes and for investigating pathogenesis processes [1–3]. However, the microarray data can be aVected by a considerable numbers of variables, such as the RNA preparation and Cy-dye labeling steps. In our laboratory, we have been developing a cDNA microarray for predicting the eYcacy of inter*

Corresponding author. Fax: +81 426 45 0461. Visiting position: Medical Research Instiute, Tokyo Medical and Dental University. E-mail address: [email protected] (S. Ito).

feron treatment for chronic hepatitis C virus (HCV)1 using liver biopsy samples [4]. One problem that we faced was variability in the yield and quality of RNA extracted from the biopsy samples due to diVerences in the hospitals’ protocols. Part of the reason for this diYculty is that the volume of clinical samples is very limited. In fact, biopsy samples are often obtained only for pathological analysis and determination of the disease stage and activity grade. Some approaches have tried to overcome these diYculties by using a very

**

0003-2697/$ - see front matter  2004 Elsevier Inc. All rights reserved. doi:10.1016/j.ab.2004.10.041

1

Abbreviation used: HCV, hepatitis C virus.

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

small biopsy sample, for example, one obtained with an aspiratory needle [5–8]. However, the RNA quantity and quality from such samples does not appear to be suitable for microarray analysis. Furthermore, during our survey for the HCV interferon treatment eYcacy prediction project, we have noticed that even the same size and volume biopsy sample can give varying RNA yields, suggesting the inXuence of unknown factors [4]. Thus, clinical application of microarrays awaits the establishment of optimal biopsy sampling conditions. In the current experiments, we sought to identify conditions for the collection of reproducible microarray data. Therefore, we developed optimal conditions for the preparation of RNA from liver biopsy samples, which can contain inXamed, Wbrotic, or mixed tissues. We used rat models for these studies because we could not use human biopsy samples for routine analyses and development of biopsy sampling and RNA preparation methods. Because it is important to study both normal and Wbrotic liver tissues, we used biopsy samples from the Long–Evans cinnamon-like colored (LEC) rat, a model of cholangioWbrosis and tumor development in the liver [9–12] that has been used to investigate the genes responsible for tumor development [12–14]. In addition to optimizing biopsy sampling and RNA preparation conditions, we evaluated the quality of the RNA used for microarray analysis. Thus, we examined the expression of a subset of genes using a cDNA microarray. This requires a control or normal tissue RNA as a reference. Although the control RNA is usually obtained from normal tissues surrounding the tumor, which can be separated by laser-captured microdissection [15] or from an established cell line [16,17], in the current studies we used RNA from the liver of Sprague–Dawley (SD) rats as a control. With optimized conditions, we should be able to apply the microarray system for routine clinical practice.

Materials and methods Animals Animal care was carried out in accordance with each institution’s guidelines. Female SD rats (6 weeks old) were purchased from Charles River Japan (Yokohama, Japan). The animals were housed in an air-conditioned room at 23 § 2 °C with 55 § 5% humidity under a daily cycle of alternating 12 h periods of light and darkness and were fed a basal diet and water ad libitum. Female LEC rats were maintained for 2 years under the same conditions described above in the Animal Facility of Osaka University Medical School and sacriWced by asphyxiation in ether. Age-matched female SD rats were used for comparison with the LEC rats.

225

Preparation of liver biopsy samples Liver needle biopsy sampling of SD rats was carried out using needles with diVerent gauge sizes (16 and 18 gauge; Hakko, Tokyo, Japan). For the biopsy (16 gauge needle) of the LEC rat, we separated the healthy tissue and the white Wbrotic carcinoma parts of the liver by abdominal operation and then performed a single needle biopsy with a visual check to distinguish Wbrotic (white materials) from normal tissue. Liver biopsy samples for microarray analysis were dipped into RNAlater (Qiagen, Hilden, Germany) and stored overnight at 4 °C. Thereafter, the samples were kept at 4 °C or stored at ¡20 °C. Total RNA extraction Total RNA extraction and puriWcation of RNAlatertreated liver biopsy samples was carried out using an RNeasy kit (Qiagen) essentially according to the manufacturer’s instructions with some modiWcations. BrieXy, liver biopsy samples were removed from RNAlater and homogenized by RLT solution in the RNAeasy kit containing 2-mercaptoethanol using a Mixer Mill MM300 (Qiagen). The resulting homogenate was centrifuged for 3 min at 20,000g, and the supernatant containing the total RNA fraction was transferred into a new tube. An equal volume of 50–70% ethanol was added to the supernatant and mixed immediately by repeated pipetting. This RNA was puriWed using an RNeasy column according to the manufacturer’s instructions. The quantity and quality of extracted total RNA were determined using an UltraSpect4000 spectrophotometer (AmershamPharmacia Japan, Tokyo, Japan) and microcapillary electrophoresis on a Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). Microarray analysis of extracted RNA Total RNA (2
g) was ampliWed to produce ampliWed RNA (aRNA) for microarray analysis using the MessageAmp aRNA kit (Ambion, Austin, TX) according to the manufacturer’s instructions. Next, an external control RNA derived from  phage DNA was added to both the sample and the reference aRNA. A labeling reaction using 6
g aRNA was performed as described by Khodursky et al. [18] using Cy3- and Cy5-dUTP dyes (Perkin–Elmer, Boston, MA). The unreacted Cy3- and Cy5-dUTPs were eliminated using a QIAquick PCR puriWcation kit (Qiagen). The cDNA microarrays for rat (Functional DNA chip Rat toxicology, version 1.0) were purchased from TaKaRa Bio (Kyoto, Japan). Hybridized microarrays were scanned for both Cy3 and Cy5 Xuorescence using a ScanArray 5000 (Perkin–Elmer). Two scans of each dye were carried out using external spike control RNA signal levels of approximately 5000 and 30,000. Thus, data were collected from a total of

226

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four scans using an external control RNA to guide the scanning method. The resulting image data were converted into Xuorescence intensity signals using ImaGene software (BioDiscovery, El Segundo, CA). The two sets of data (two scanning powers for each dye) were merged to establish a single set of representative data for each gene expression proWle (Patent pending: PCT/JP03/ 06677). Immunohistochemistry Pathological analysis was performed using serial sections of the LEC rat liver biopsy samples. BrieXy, biopsy samples were Wxed overnight at room temperature in 10% formalin in 0.1 M phosphate buVer, pH 7.4. Next, the sections were treated with 0.3% H2O2 in methanol for 30 min to eliminate endogenous peroxidase and then treated for 10 min in a microwave (600 W; Tiger, Osaka, Japan) in the presence of 10 mM citrate buVer, pH 6.0. After washing, the sections (3
m) were blocked for 30 min at room temperature with 5% goat serum, followed by overnight incubation at 4 °C with 5
g/ml antirat osteopontin (O-17) rabbit IgG aYnity-puriWed antibodies (IBL, Fujioka, Japan). Immunoreactive signals were visualized using the Vectastain ABC kit (Vector Laboratories, Burlingame, CA). The speciWc immune complex was detected with a solution containing 0.02% 3,3⬘-diaminobenzidine, 50 mM Tris–HCl (pH 7.6), and 0.0005% H2O2. Sections were mounted on glass slides, dehydrated, and cover-slipped. Hematoxylin–eosin staining was also carried out on serial sections. Statistical analyses Dunnett’s test for over-three-group comparisons with control and Student’s t test for two-group comparisons were used for the analysis of RNA extraction and puriWcation. A paired t test was applied for our microarray analysis.

Results Optimization of sample handling conditions for RNA extraction In the current studies, we examined the eVects of various conditions on the isolation of nucleic acids from biopsy tissues. We Wrst compared the use of diVerent needle gauges, liver biopsy sample lengths, and storage conditions on the total yield and purity of RNA. Biopsy liver samples were placed in RNAlater immediately after isolation and then stored at 4 °C. The relationship between the sample length for cutting and the needle gauge size and the yield and purity of the extracted total RNA is shown in Fig. 1. We found that when the needle diameter was kept constant (16 gauge), the amount of total RNA extracted per biopsy tissue rose as the length of the biopsy sample increased (Fig. 1A). Likewise, increasing the needle diameter or biopsy length enhanced the quality of the RNA extracted as revealed by the 28S/18S ratio of ribosomal RNA (Fig. 1B). We chose the 16-gauge needle and a 5mm biopsy length for further studies because they gave a higher quality and quantity of RNA than the 18gauge £ 10-mm sample. We next examined the eVect of diVerent storage conditions in RNAlater on RNA yield and purity. Liver biopsy samples were stored in RNAlater at 4 or ¡20 °C. As shown in Fig. 2, the yield of RNA extracted was approximately fourfold higher when the biopsy samples were stored at 4 °C than at ¡20 °C. We used the RNeasy kit for RNA puriWcation, which employs adsorption of RNA to a spin column. During the course of our study, we observed that the RNA yield varied due to diVerences in the ability of RNA to bind to the column (data not shown). To identify the factors in the ethanol–homogenate mixture causing variability in the RNA yield, we tested the eVect of three concentrations of ethanol (50, 60, and 70%) on the binding of RNA to the spin column.

Fig. 1. InXuence of biopsy sampling conditions on extraction of total RNA. The horizontal axis represents the biopsy needle gauge size and tissue length in mm. (A) EVect of diVerent tissue lengths and needle sizes on the amount of total RNA extracted/biopsy tissue total mass. (B) EVect of diVerent tissue lengths and needle sizes on the RNA quality, expressed as the 28S/18S ratio of ribosomal RNA. The data represent the mean § SE from three liver tissues. Asterisks indicate signiWcant diVerence (p < 0.05) with control (18-gauge £ 10-mm) according to Dunnett’s test.

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

227

RNA yield from normal and Wbrotic tissues. For this study, we examined RNA extracted from biopsy samples from SD rat liver. We also studied the normal and Wbrotic portions of the LEC rat liver, which is a model of cholangioWbrosis and tumor development in the liver [9– 12] and has been used to investigate the genes responsible for tumor development [12]. To obtain a matched set of normal and Wbrotic samples from the LEC rat livers, we autopsied the LEC rat and used a visual check of the target portions during the sampling procedure to verify selection of the appropriate tissues. The RNA yield in the various tissues is shown in Fig. 4. The results show that the Wbrotic part provides less RNA than the normal part of the LEC liver. Fig. 2. EVect of storage conditions on RNA yield from liver biopsy samples. Liver biopsies were extracted using a 16-gauge needle to a 5mm length and stored in RNAlater at 4 or ¡20 °C. The graph shows the eVect of the storage temperature on the amount of total RNA extracted (
g/biopsy tissue). The data represent the mean § SE from three liver tissues. Double asterisk indicates a signiWcant diVerence (p < 0.01) according to Student’s t test.

Although the manufacturer’s protocol for the RNeasy kit uses 70% ethanol, based on the total yield of RNA in our experiments, 60% ethanol was the most eVective condition for binding RNA from RNAlater-treated liver biopsy samples (Fig. 3). We have previously noticed that liver biopsy sampling from hepatitis C patients leads to variable RNA yields even using the same biopsy size, suggesting that contamination of inXammatory tissue with Wbrotic tissue is a problem. Such contamination may lead to a reduction in RNA yield. To study the eVect of tissue histological stage on the RNA yield, we compared the

Optimization of Cy-labeled DNA puriWcation During the optimization of the Cy-labeled DNA puriWcation conditions, we noticed that the nucleic acid binding capacity of the spin column, which is used to eliminate excess Cy3- and Cy5-dUTP, varied from lot to lot; in fact, some lots had almost no binding capacity (data not shown) and there was even Xuctuation within the same lot (Fig. 5). This variability would be a signiWcant problem for quantitative assay, for example in clinical applications. We therefore investigated whether we could overcome this problem by reapplying the Xowthrough fraction from the Wrst column to a second column. We found that this double spin column arrangement alleviates the problem of variability in DNA binding (Fig. 5). Microarray analysis of liver RNA We next examined whether the quality of the RNA extracted by our procedures was suitable for use with a commercially available cDNA microarray. As suggested

Fig. 3. EVect of ethanol concentration on RNA binding capacity in the RNeasy spin column. Liver biopsies were extracted using 16-gauge needle to a 5-mm length. Various concentrations of ethanol (EtOH; 50, 60, or 70%) were used during the binding of RNA to the RNeasy spin column. The graph shows the eVect of the ethanol concentration of the amount of total RNA extracted (
g/biopsy tissue). The data represent the mean § SE from three liver tissues. Asterisks indicate a signiWcant diVerence (p < 0.05) compared to the control (70% ethanol) according to Dunnett’s test.

Fig. 4. Amount of total RNA extracted from liver biopsy tissues of SD and LEC rats. RNA was extracted from animals using a 16-gauge needle to a 5-mm biopsy length. For the LEC rats, the Wbrotic and normal parts of the liver were discriminated by visual observation. The graph shows the amount of total RNA extracted (
g/biopsy tissue) from each biopsy. The data represent the mean § SE from three liver tissues. Asterisk indicates a signiWcant diVerence (p < 0.05) between the results for the normal and the Wbrotic parts of the LEC liver according to Student’s t test.

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Fig. 5. Within-lot variation of QIAquick spin columns used for the separation of labeled Cy-labeled DNA and unreacted Cy-dye. The recovery of puriWed Cy-labeled DNA from equal starting amounts using diVerent QIAquick columns was assessed. The circles (I) show the results after a single elution. QIAquick columns 1, 2, 14, 21, 24, 25, 29, and 35 showed low recovery eYciency even though they were from the same lot. The triangles (䉱) show the results after reapplication of the Xow-through and a second elution. A second elution clearly raised the eYciency of recovery. The squares (䊏) show the combined recovery from the two elutions.

by the manufacturer, data from the array were normalized according to the data from housekeeping genes, including (GenBank Accession numbers in parentheses) brain hexokinase (J04526), RT1.Au (X82669), glucose-6phosphate dehydrogenase (X07467), alpha-tubulin (V01227), ribosomal protein S5 (XM_341788), H2A and H2B histones (X59961), polyubiquitin (D16554), F0ATPase subunit b (M35052), alpha initiation factor (X65948), ornithine decarboxylase (M16982), hypoxanthine-guanine phosphoribosyltransferase (X62085), pancreatic phospholipase A2 (D00036), and MHC class I (L23128). We also spiked RNA derived from the  phage A gene as an external control to adjust the scanning range and to help normalize the data. In the Wrst experiment, total RNA from the normal and Wbrotic parts of LEC rat liver was labeled with Cy5 and Cy3, respectively, and compared by competitive hybridization on the microarray. In a second experiment, RNA from the SD rat liver was labeled with Cy5, and RNA from the Wbrotic and normal parts of the LEC rat liver were labeled with Cy3. The expression proWles from each tissue are compared on scatter plots in Figs. 6A–C. The results show that expression proWles from the SD liver and the normal part of the LEC liver are closely related (Fig. 6C). Furthermore, there was a marked variation in the expression proWles in the normal and Wbrotic parts of the LEC liver (Fig. 6A), but a much greater diVerence was observed between the SD liver and the Wbrotic part of the LEC liver (Fig. 6B). We next examined the normalization procedure and the variability of the direct (Wbrotic vs. normal RNA) and indirect (Wbrotic vs. SD rat RNA) comparison meth-

ods using the respective data sets. Fig. 6D shows the average ratios of the Wbrotic LEC/normal LEC tissues plotted as a function of the Wbrotic LEC/SD signal ratio (Cy3 signal/Cy5 signal) divided by the normal LEC/SD signal ratio (Cy3 signal/Cy5 signal). The graph shows a close correlation (r D 0.990 and p D 0.0001) as determined by simple linear regression analysis. Genes that were more than 2-fold up- or down-regulated in the Wbrotic vs. the normal parts of the LEC rat liver are summarized in Tables 1 and 2, respectively; see also Fig. 7 . As shown in Table 1, many of these genes are oxidoreductases or are associated with tumor progression, calcium regulation, cell cycle regulation, or Wbrosis. Among these genes, sialoprotein, also known as osteopontin (Accession No. M14656) was elevated more than 20-fold in the Wbrotic part compared to the normal part of the LEC rat liver. In contrast, osteopontin was expressed at the same level in the normal part of the LEC rat liver as in the SD rat liver. This type of expression was deWned as group A, and it includes seven genes. Group B, which includes 22 genes, was made up of genes that are expressed at the highest level in the Wbrotic part of the LEC rat liver, and these genes were also expressed at a higher level in the normal part of the LEC rat liver than in the SD rat liver. In group B, the expressions of lipoprotein lipase (L03294) and macrophage metalloelastase (X98517) were more than 10-fold higher in the normal part of the LEC rat liver than in the SD rat liver. Genes expressed at a lower level in the Wbrotic part than the normal part of the LEC rat liver are listed in Table 2. Group C, which includes 23 genes, is made up of genes that were expressed at equal levels in the SD rat liver and in the normal part of the LEC rat liver. Group D, which includes 5 genes, includes genes expressed at a lower level in the normal part of the LEC rat liver than in the SD rat liver, while group E, which also includes 5 genes, consists of genes expressed at a higher level in the normal part of the LEC rat liver than in the SD rat liver. Groups C and D showed a very low level of expression in the Wbrotic part of the LEC rat liver compared to the SD rat liver. Pathological analysis of rat liver tissues by immunohistochemistry Because our results indicated that the expression of the mRNA for osteopontin was elevated in the Wbrotic part of the LEC rat liver, we examined the expression of the osteopontin protein in the LEC rat liver. Hematoxylin– eosin staining showed that there was a proliferation of bile ducts in the surrounding normal tissues of hepatic tumors (Fig. 8). In contrast, a cholangiocarcinoma lesion in severe cholangioWbrosis was observed in the Wbrotic part of the hepatic tissue (Fig. 7C). Immunohistochemistry of osteopontin showed positive staining for osteopontin in the region of the cholangiocarcinoma (Fig. 7D)

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

229

Fig. 6. Scatter plots comparing microarray data for various rat liver tissues. (A) Comparison of the Xuorescence signals for the Wbrotic part (Cy3) and from the normal part (Cy5) of the LEC rat liver. (B) Comparison of the Xuorescence signals from the Wbrotic part of the LEC rat liver (Cy3) and from the SD rat liver (Cy5). (C) Comparison of the Xuorescence signals from the normal part of the LEC rat liver (Cy3) and from the SD rat liver (Cy5). (D) Comparison of the ratio from indirect comparison between the Wbrotic part of the LEC rat liver and the artiWcial reference control (SD rat liver) and from a direct comparison between the Wbrotic and the normal parts of the LEC rat liver.

despite the negative staining in normal bile ducts of LEC rat liver (Fig. 7B).

Discussion In these studies, we optimized liver biopsy sampling for RNA extraction using the SD rat liver as a model. Although the volume from 18-gauge £ 10-mm and 16gauge £ 5-mm biopsy samples would be the same, the quantity and quality of RNA was higher in the former. Thus, the optimal liver biopsy needle size and sample length were 16 gauge and 5 mm, respectively. Longer and Wner biopsy samples resulted in a lower RNA yield and quality, possibly because of increased RNA degradation prior to extraction. We therefore recommend a 16-gauge needle for isolation of hepatitis patient liver biopsy samples when they are to be used for cDNA microarray analysis. Biopsy of tumors may be diVerent because they could require the use of a small needle to avoid spreading the tumor [5–7,19].

RNAlater is well documented as a preservative agent for tissue samples [20,21]. Although the manufacturer recommends storage at either ¡20 or 4 °C, we noticed that the RNA yield decreased when the biopsy small samples were stored at ¡20 °C. This was associated with crystallization of some reagent components, which could damage the RNA, despite the fact that the manufacturer’s protocol indicates that the biopsy small sample should not freeze in RNAlater. Therefore, we recommend shipping and archiving biopsy samples at 4 °C. In these studies, we also found that the ethanol concentration was critical for the puriWcation of the RNA with the minispin column from the RNeasy kit. The manufacturer’s protocol suggests the use of 70% ethanol, but we found that 60% gave a higher yield of total RNA from the liver biopsy samples. In contrast, 70% ethanol gave the best recovery of RNA from most other tissues and cells (data not shown). The reasons for this are not clear, although it could be due to high levels of lipid- and glycogen-associated materials in liver.

230

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Table 1 Genes expressed at a higher level in the Wbrotic than in the normal part of the LEC rat liver

Group A

Group B

GenBank Accession

Description

M14858 X73911 J05495 D50093 M86564 U07201 AF223677

Sialoprotein (osteopontin) amiloride binding protein (long form) Gal/GalNAc-speciWc lectin Prion protein, structural alpha-prothymosin Asparagine synthetase steroid sensitive gene-1- protein in (SSG-1)

J03026 Y13275 U11038 AF120275 X62952 D00680 U65656 M23697 AJ224880 M84488 L03294 X98517 U14526 M63837 X96394 Y00090 M21730 L33869 X67788 X63434 M65149 J03627

Matrix Gla protein D6.1A protein Lysyl oxidase connective tissue growth factor vimentin plasma glutathione peroxidase precursor gelatinase A Plasminogen activator, tissue collagen alpha 2 type V Vascular cell adhesion molecule 1 Lipoprotein lipase macrophage metalloelastase (MME) tissue inhibitor of metalloproteinases- 2 (TIMP-2) Platelet-derived growth factor receptor alpha multidrug resistance protein Sialophorin (gpL115, leukosianin, CD43) Annexin V Ceruloplasmin (ferroxidase) ezrin Urinary plasminogen activator, urokinase CCAAT/enhancer binding, protein (C/EBP) delta S-100 related protein

N/SD (mean § SD)

F/SD (mean § SD)

1.43 § 0.52 1.79 § 0.39 1.22 § 0.21 1.37 § 0.23 1.06 § 0.29 0.80 § 0.21 1.59 § 0.04

24.91 § 3.32 14.52 § 4.73 5.17 § 1.92 5.12 § 1.65 3.16 § 0.85 2.06 § 0.20 3.70 § 0.21

**

3.54 § 1.10 6.74 § 3.26 2.07 § 0.44 4.75 § 3.08 3.57 § 0.87 4.93 § 1.61 3.30 § 0.57 3.27 § 2.35 2.77 § 0.74 3.57 § 1.70 10.81 § 2.13 10.54 § 5.38 3.78 § 1.15 2.74 § 0.52 2.39 § 0.57 2.29 § 0.50 5.12 § 2.27 2.64 § 0.44 5.20 § 1.16 2.78 § 0.88 3.72 § 2.58 4.77 § 0.75

48.72 § 13.44 54.55 § 18.13 12.61 § 4.95 22.71 § 4.37 18.13 § 6.89 21.95 § 2.83 16.13 § 5.11 11.86 § 3.49 11.22 § 1.92 10.66 § 2.51 28.69 § 6.99 26.48 § 7.88 10.19 § 2.02 6.58 § 1.09 6.38 § 1.36 6.09 § 1.36 14.12 § 5.71 7.13 § 1.55 11.02 § 3.61 6.26 § 1.16 6.76 § 2.59 10.52 § 2.52

*

* * * * ** **

* * * * ** * ** * * * * * * ** * * * * ** * *

F/SD/N/SD (mean § SD)

F/N (mean § SD)

18.65 § 8.92 8.03 § 4.59 4.39 § 0.89 3.65 § 0.36 3.03 § 0.19 2.67 § 0.48 2.32 § 0.21

22.68 § 3.32 11.53 § 4.73 4.09 § 1.92 3.57 § 1.65 3.35 § 0.85 2.85 § 0.20 2.37 § 0.21

15.19 § 4.18 8.70 § 2.35 6.02 § 2.70 5.93 § 1.41 4.95 § 0.99 4.80 § 0.34 5.07 § 2.12 4.39 § 2.17 4.27 § 0.97 3.41 § 0.28 2.83 § 1.51 2.99 § 1.94 2.87 § 0.86 2.46 § 0.65 2.69 § 0.41 2.78 § 0.61 2.81 § 0.07 2.82 § 0.77 2.08 § 0.72 2.33 § 0.23 2.08 § 0.18 2.24 § 0.20

17.02 § 13.44 8.89 § 18.13 6.98 § 4.95 6.13 § 4.37 5.89 § 6.89 5.42 § 2.83 4.99 § 5.11 4.92 § 3.49 4.56 § 1.92 3.94 § 2.51 3.64 § 6.99 3.07 § 7.88 2.81 § 2.02 2.81 § 1.09 2.78 § 1.36 2.78 § 1.36 2.77 § 5.71 2.74 § 1.55 2.66 § 3.61 2.46 § 1.16 2.36 § 2.59 2.23 § 2.52

N/SD, comparison between the normal part of the LEC rat liver and the SD rat liver, F/SD, comparison between the Wbrotic part of the LEC rat liver and the SD rat liver; F/SD/N/SD, ratio of the two comparisons (indirect comparison); F/N, comparison between the Wbrotic and the normal parts of the LEC rat liver (direct comparison). The data represent the mean § SE from three rat livers. **p < 0.01; and *p < 0.05, signiWcant diVerences between N/SD and F/SD.

In addition to these modiWcations to the Cy-labeled DNA puriWcation protocol, we noticed that there was a signiWcant column-to-column variability in the nucleotide binding capacity of the QIAquick minispin columns even within a single lot (see Fig. 5). This is a problem for routine clinical applications because it interferes with precise quantiWcation. Therefore, we recommend using a double column for the puriWcation of the DNA after labeling. We reapplied the Xowthrough fraction from the Wrst column to a second column to ensure recovery of the Cy-labeled DNA. This should provide stable signals in the microarray analysis because it allows for reproducible recovery of the Cylabeled DNA. We have noticed some variability in the RNA yield and biopsy sample size during our studies [4]. We suspected that this may be due to local Wbrotic tissue contamination in the biopsy sample causing a reduction in RNA yield. Therefore, we investigated the relationship between the RNA yield from the normal and the Wbrotic parts of the LEC rat liver. We found that the Wbrotic part of liver gave a much lower RNA yield than the

normal part. Thus, extra care must be taken when obtaining clinical samples from later-stage hepatitis C patients. With the optimized conditions, we examined the RNA grade applicability to a cDNA microarray containing approximately 400 genes. This low-density microarray employs two Xuorescent dyes, Cy3 and Cy5, so that sample RNA can be compared to a normal reference RNA at the same time. Although a universal RNA reference containing a mixture of RNAs from diVerent tissues is commercially available (Control RNA for Microarray Experiments (April 2002) Clontechniques XVII (2): 6 www.bd.biosciences.com/), we tried to use a reference RNA derived speciWcally from the liver. Thus, for these experiments, we studied whether RNA from a SD rat liver biopsy sample could be used as a reference for Wbrotic biopsy samples from the LEC rat liver. Several studies have used microarrays to examine gene expression in clinical samples or in animal models of liver cirrhosis [22–25]. In this study, we used the LEC rat to study the gene expression proWle in a liver tumor because it is reported to be a good disease model of

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

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Table 2 Genes expressed at lower level in the tumor than in the normal part of the LEC rat liver

Group C

GenBank Accession

Description

N/SD (mean § SD)

F/SD (mean § SD)

X78847 X51974 D00675 M23601 NM_012564

Glutathione S-transferase, alpha type (Yc?) pI 6.1 esterase (ES-10) alpha-1-protease inhibitor Monoamine oxidase B Group-speciWc_component_ (vitamin_D-binding_protein) uricase contrapsin-like_protease_inhibitor_ related_protein_(CPi-26) Insulin-like growth factor I (IGF-I) Flavin-containing monooxygenase 1 GTP cyclohydrolase I feedback regulatory protein Serine protease inhibitor pre-alpha-inhibitor, heavy chain 3 acyl-coA oxidase macrophage stimulating protein vitronectin microsomal aldehyde dehydrogenase DCoH gene Superoxide dismutase 1, soluble S-transferase mitochondrial enoyl-CoA hydratase (EC 4.2.1.17) Transferrin Complement component 3 Guanidinoacetate methyltransferasease

0.62 § 0.23 1.70 § 0.78 0.66 § 0.06 1.38 § 0.32 0.87 § 0.11

0.16 § 0.10 0.56 § 0.47 0.23 § 0.11 0.52 § 0.31 0.33 § 0.18

*

0.67 § 0.09 0.87 § 0.17

0.27 § 0.14 0.38 § 0.19

**

1.16 § 0.14 1.69 § 0.68 0.53 § 0.08

0.45 § 0.22 0.66 § 0.30 0.24 § 0.13

**

0.90 § 0.47 0.64 § 0.07 0.86 § 0.04 0.73 § 0.03 0.79 § 0.15 0.70 § 0.14 0.78 § 0.10 0.51 § 0.07 0.62 § 0.11 0.74 § 0.04

0.37 § 0.18 0.28 § 0.15 0.42 § 0.28 0.31 § 0.09 0.34 § 0.19 0.34 § 0.11 0.35 § 0.15 0.25 § 0.08 0.28 § 0.18 0.34 § 0.13

*

0.62 § 0.12 0.93 § 0.35 51.0 § 0.05

0.29 § 0.16 0.43 § 0.21 0.24 § 0.12

**

cytochrome P450 2D18 Zn-alpha2-glycoprotein Acyl CoA synthetase, long chain Solute_carrier_family_10_(sodium/ bile_ acid_cotransporter family), member 1 Diaphorase (NADH/ NADPH)

0.28 § 0.04 0.46 § 0.24 0.38 § 0.15 0.50 § 0.20

0.11 § 0.05 0.18 § 0.10 0.19 § 0.10 0.22 § 0.12

**

0.30 § 0.11

0.14 § 0.44 0.91 § 0.79 1.71 § 1.10 1.23 § 0.72 1.21 § 0.56 1.56 § 0.88

J03959 X16359 M15651 M84719 U85512 M73231 X83231 J02752 X95096 U44845 M73714 AJ005542 Y00404 J03752 X15958 D38380 X52477 J03588 Group D

U48220 X75309 D90109 M77479 J02679

Group E

M28241 J00750 AB016800 M37394 AJ238392

Glutathione-S-transferase, mu type 2 (Yb2) Metallothionein 7-Sehydrocholesterol reductase epidermal growth factor receptor (Egfr) Sulfotransferase K2

3.17 § 1.18 5.05 § 0.71 3.64 § 0.07 2.60 § 0.66 3.89 § 1.35

Abbreviations are as described in Table 1. The data represent the mean § SE from three rat livers. between N/SD and F/SD.

Wilson’s disease and progression to hepatocellular carcinoma [26,27]. Development of liver tumors in these rats is reported to be due to metal oxidation reactions producing reactive oxygen species. Interestingly, consistent with a role of reactive oxygen species, we observed that the expression of glutathione peroxidase 4 (U37427) was reduced in the Wbrotic part of the LEC rat liver and lower than in the SD rat liver (n D 3; 0.56). Consistent with this Wnding, down-regulation of glutathione peroxidase has been reported during tumor progression in the LEC rat [28–30]. However, we found that it was another type of plasma glutathione peroxidase that was up-regulated in the tumor part of the LEC rat liver. Thus, the role of glutathione peroxidases in liver tumor progression remains to be more clearly deWned. A recent report describing the expression patterns in the LEC rat liver

**

F/SD/N/SD (mean § SD)

F/N (mean § SD)

0.25 § 0.09 0.30 § 0.13 0.34 § 0.13 0.38 § 0.19 0.36 § 0.13

0.24 § 0.10 0.32 § 0.47 0.33 § 0.11 0.36 § 0.31 0.37 § 0.18

0.39 § 0.13 0.43 § 0.16

0.38 § 0.14 0.38 § 0.19

0.37 § 0.12 0.39 § 0.09 0.44 § 0.17

0.40 § 0.22 0.40 § 0.30 0.41 § 0.13

0.43 § 0.06 0.43 § 0.17 0.48 § 0.21 0.43 § 0.12 0.41 § 0.17 0.48 § 0.09 0.43 § 0.11 0.48 § 0.13 0.43 § 0.19 0.46 § 0.12

0.41 § 0.18 0.42 § 0.15 0.42 § 0.28 0.43 § 0.09 0.43 § 0.19 0.44 § 0.11 0.45 § 0.15 0.45 § 0.08 0.45 § 0.18 0.46 § 0.13

0.44 § 0.15 0.44 § 0.16 0.47 § 0.19

0.48 § 0.16 0.50 § 0.21 0.50 § 0.12

0.39 § 0.15 0.39 § 0.07 0.49 § 0.11 0.43 § 0.09

0.36 § 0.05 0.41 § 0.10 0.42 § 0.10 0.43 § 0.12

*

4.70 § 0.08

0.50 § 0.04

*

0.28 § 0.14 0.32 § 0.16 0.34 § 0.20 0.45 § 0.08 0.38 § 0.11

0.28 § 0.79 0.32 § 1.10 0.39 § 0.72 0.47 § 0.56 0.48 § 0.88

* ** * **

**

* **

* * ** ** ** ** * ** *

* **

* * **

** * ** **

p < 0.01 and *p < 0.0 signiWcant diVerences

by oligo-based GeneChip analysis gave results similar to those of our microarray analysis [31]. For example, for LEC vs. LEA rat liver, they found an 18.4-fold up-regulation of RNA for plasma glutathione peroxidase precursor (Accession No. D00680), a 10.2-fold increase in the RNA for multidrug resistance protein (Accession No. X96394) in the Group B, and a 4.9-fold increase in the RNA for sulfotransferase K2 (Accession No. AJ238392). Similarly, in our analysis, we found 21.95- (in the Group B), 6.38- (in the Group B), and 3.89- (in the Group E) fold increases, respectively, of these mRNAs in cancerous liver vs. normal/SD rat liver. Among the genes that were examined in our microarray, the osteopontin gene was expressed at a much higher level in the Wbrotic part than in the normal part of the LEC rat liver, although it was expressed at the same

232

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

Fig. 7. Categories in Tables 1 and 2. N/SD, normal LEC liver/SD liver, F/SD; Wbrotic LEC liver/SD liver, F/N; Wbrotic LEC liver/normal LEC liver; !, within twofold changes between comparison tissues; ", >twofold expression diVerence between comparison tissues; #, >twofold expression diVerence between comparison tissues; "", >fourfold expression diVerence between comparison tissues; ##, >fourfold expression diVerence between comparison tissues.

levels in the normal part of the LEC rat liver and the SD rat liver. Due to technical aspects of the real-time PCR method, it is possible that the diVerence in expression at the protein level may actually be even larger than that

observed in the microarray analysis [32]. Therefore, we also examined the expression of osteopontin protein in the Wbrotic part of the LEC rat liver by immunohistochemistry. Interestingly, we found that osteopontin was highly expressed in transformed bile ducts/cholangiocarcinoma lesions but not in proliferating normal bile ducts. In agreement with this, in human hepatoma, overexpression of osteopontin correlates closely with indicators of a poor prognosis, including a high tumor grade, a late tumor stage, and an early recurrence [33]. Furthermore, other reports have shown that osteopontin acts as an autocrine mediator of hepatocyte growth and metastatic hepatocellular carcinoma [34–37] and that breast cancer metastases in the bone have a high expression of osteopontin [38]. High expression of osteopontin in transformed bile ducts/cholangiocarcinoma lesions might therefore be associated with the development of hepatic tumors in LEC rats. During the course of applying the optimized sample handling conditions to human biopsy samples, we have observed an improvement in the quantity and quality of RNA obtained from hepatitis C patients at various hospitals (data not shown). Thus, it appears that the opti-

Fig. 8. Immunohistochemical analysis of osteopontin expression in serial sections from the LEC rat liver. (A and B) Normal and (C and D) Wbrotic parts of the LEC liver. Serial sections were subjected to hematoxylin–eosin staining (A and C) and immunohistochemical staining with the anti-rat osteopontin antibodies (B and D).

Optimization of liver biopsy RNA sampling / F. Takemura et al. / Anal. Biochem. 337 (2005) 224–234

mized conditions are useful even for human clinical trials. These Wndings showed that we were able to develop and establish an optimized biopsy sampling system, including transportation and RNA extraction conditions, for clinical application of expression proWling and, in particular, for microarray analysis. A direct comparison of the gene expression patterns from the Wbrotic and normal parts of the LEC rat liver would result in only two categories of disease-associated genes: up- and down-regulated genes. However, by also comparing the gene expression proWles from the SD rat liver indirectly, we were able to separate the disease-associated genes into Wve categories. Groups A and C had equivalent expression in the SD rat liver and the normal part of the LEC rat liver, but genes in group A were expressed at a higher level in the Wbrotic part than in the normal part of the LEC rat liver, while genes in group C were expressed at a lower level in the Wbrotic part. This suggests that these genes may participate in tumorigenesis. The genes in groups B, D, and E had altered levels in the normal part of the LEC rat liver compared to the SD liver. These genes may represent diVerences between the SD rat and the LEC rat, but they could also be associated with the precancerous stage in the LEC rat. Genes in group B were already expressed at a higher level in the normal part of the LEC rat liver compared to the SD rat liver. Genes that were expressed at a much higher level in the tumor part compared to the normal part of the LEC rat liver included the following (Accession numbers in parentheses): gelatinase A (U65656), macrophage metalloelastase (X98517), TIMP-2 (U14526), connective tissue growth factor (AF120275), and collagen alpha 2 type V (AJ224880). Based on a direct comparison between the normal and the tumor parts of the LEC liver, groups A and B would be assumed to be up-regulated genes, whereas groups C, D, and E would be down-regulated genes. However, based on comparison with the SD rat liver data, the Wve groups are distinct. Whereas genes of groups A and C were considered to be tumor-speciWc genes, genes of groups B and D were categorized as representing the late stage of tumorigenesis, which may represent a metastatic event. Furthermore, genes in group E were up-regulated in the normal part of the LEC rat liver compared to the SD rat liver, which suggests that genes in this group may play a role in homeostasis against oxidative stress. Finally, in these studies, we observed the up-regulation of calcium metabolism-, angiogenesis-, and extracellular-matrix-related genes in the Wbrotic part of the LEC rat liver. Most of the genes that were altered in the Wbrotic tissue were not identiWed in the previous study of the early phase of liver disease [31]. This suggests that the late stage of tumorigenic progression in the LEC rat might represent the far end stage rather than the active process of tumor formation. In conclusion, in these studies, we optimized the conditions for liver biopsy sample handling for cDNA

233

microarray analysis. The results of the cDNA microarray were validated by our immunohistochemical studies, indicating that our microarray method is accurate. The results of this study suggest that liver function could be assessed throughout the progression of the disease by cDNA microarray with optimized RNA handling conditions. In addition, these studies show that the LEC rat is a useful model for investigating the development of liver disease. Using this model system together with a reference control from the SD rat, we were able to classify gene expression proWles into Wve groups. Further studies should focus on identifying the function of these genes and their interaction in tumor development.

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