Identification of Genes with Differential Expression in Acquired Drug-Resistant Gastric Cancer Cells Using High-Density Oligonucleotide Microarrays

Gastric cancer is one of the most common cancers worldwide. Although the occurrence rate of gastric cancer has decreased, Asian countries such as Korea, China, and Japan, and some European and South American countries still have a high incidence of the disease (1, 2). Many chemotherapeutic agents have been used to treat gastric cancer patients, but the emergence of drug resistance has prevented successful treatment in many cases. The two major forms of drug resistance are intrinsic resistance, in which previously untreated tumor cells are inherently insensitive to the chemotherapeutic agent, and acquired resistance, in which treated tumor cells become insensitive after drug exposure (3). To date, many research groups have studied the various mechanisms of drug resistance, hoping to overcome this major obstacle in chemotherapy. Researchers have determined that acquired drug resistance is multifactorial, in that it involves host factors and genetic and epigenetic changes, as well as numerous molecular events (4). The resistance itself may be due to decreased drug accumulation, alteration of intracellular drug distribution, reduced drug-target interaction, increased detoxification response, cell-cycle deregulation, increased damaged-DNA repair, and reduced apoptotic response (5). However, although researchers believe that multiple factors participate in chemoresistance, most studies have focused on a limited number of candidate genes. For example, it has been well known that overexpression of the multidrug resistance gene (MDR1) is associated with cancer cells that have drug resistance. However, little is known about the genes differentially expressed in a variety of drug-resistant cancer cells, especially in gastric cancer (6). It is hoped that the recently developed techniques for genome-wide expression analysis will provide additional information, novel candidate genes associated with cancer drug resistance, and perhaps new therapeutic targets.

Microarray technologies have been widely used for comprehensive gene expression analysis as well as mutation and single nucleotide polymorphism detection (7, 8, 9, 10, 11, 12, 13, 14). In particular, large-scale microarray analysis of gene expression enables researchers to analyze simultaneous changes in thousands of genes and identify significant patterns. Because the genome-wide expression analysis in a variety of drug-resistant gastric cancer cells has not yet been performed, we have used the recently developed Affymetrix HG-U133A high-density oligonucleotide microarray for analysis of the global gene expression.

The drugs 5-fluorouracil (5-FU), doxorubicin, and cisplatin are widely used in the treatment of various malignancies: 5-FU is a well-known antimetabolite that acts as a thymidylate synthase inhibitor (3); doxorubicin targets topoisomerase II by interfering with the catalytic cycle (15); and cisplatin intercalates into DNA, leading to DNA damage in the cancer cells (16). In this study, we have examined genes that are differentially expressed in 5-FU-, doxorubicin-, or cisplatin-induced chemoresistant gastric cancer cell lines, as compared with their drug-sensitive parent cell lines. We identified genes showing altered expression in resistant cell lines, as well as several potential multidrug resistance candidate genes that were associated with resistance to two or more of the chemotherapeutic agents.

Four 5-FU-resistant gastric cancer cell lines (SNU-620R-5-FU/1000; SNU-638R-5-FU/50000; SNU-668R-5-FU/4000; SNU-719R-5-FU/600), 3 doxorubicin-resistant cell lines (SNU-620R-DOX/300; SNU-668R-DOX/50; SNU-719R-DOX/100), and 3 cisplatin-resistant cell lines (SNU-620R-CIS/2000; SNU-638R-CIS/400; SNU-668R-CIS/400) were created from four different gastric carcinoma cell lines (SNU-620; SNU-638; SNU-668; SNU-719) established by Park et al. (17). All 14 cell lines were cultured in RPMI 1640 supplemented with 10% fetal bovine serum (HyClone, Logan, UT), 20 mm HEPES, and 100 units/ml penicillin-streptomycin (Invitrogen, Carlsbad, CA) and the indicated concentrations of drugs in Table 1 (5-FU; doxorubicin; cisplatin) in a humidified incubator at 37°C in an atmosphere of 5% CO₂ until 80–90% confluence was achieved.

5-FU was purchased from Choongwae Pharma Corp. (Gyeonggi, Korea), doxorubicin from Dong-A Pharmaceutical Co. Ltd. (Seoul, Korea), and cisplatin from Ildong Pharmaceutical Co. Ltd. (Seoul, Korea). For production of the resistant cell lines, the four parent gastric cancer cells were initially exposed to the various drugs at concentrations indicated by the respective IC₅₀ values determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay (described below). The drug concentration was increased 2–4-fold after at least 8 weeks of continuous drug exposure. Fresh drugs were added by gradually increasing to the final concentrations shown in Table 1. Stable, drug-resistant cell lines were selected and cultured in the presence of the final drug concentrations. The establishment period of the drug-resistant cell lines varied from 11 months to 2 years. Before microarray experiments, cells were maintained for 1 week without drugs to eliminate acute effects.

Sensitivities of the drug-resistant and parent cell lines to 5-FU, doxorubicin, and cisplatin were determined by MTT assay as described previously (18). Briefly, single-cell suspensions were obtained by pipette disaggregation of the floating cells or by trypsinization of monolayer cultures. The number of cells plated into 96 wells was determined after preliminary cell growth studies so that untreated cells were in exponential growth phase at the time of initial harvest and at the end of the 4-day incubation. Equal number of cells was inoculated into each well in RPMI 1640 supplemented with 10% fetal bovine serum. For each drug, 5–10 concentrations were used, covering a 3–5-log concentration range that was chosen to span the 50% inhibitory concentration determined by preliminary assays. After 4 days of culture, MTT (Sigma Chemical Co., St. Louis, MO) was added to each well and was incubated at 37°C for an additional 4 h. The medium was aspirated from plates leaving about 30 μl of medium in each well. Care was taken not to disturb the formazan crystals at the bottom of the wells. One hundred fifty μl of DMSO was added to each well, and the plates were placed on a shaker for 15 min to solubilize the formazan crystals. The plates were then read immediately at 540 nm on a scanning multiwell spectrophotometer (ELISA reader; Biotek Instruments Inc., Burlington, VT). All of the data points represent the mean value of a minimum of six wells. Table 1 shows the IC₅₀ representing the drug concentration resulting in 50% growth inhibition and the relative resistance calculated from the ratio of the IC₅₀ of the drug-resistant cell lines versus that of the parent cell lines.

Total RNA was extracted using the Trizol reagent (Life Technologies, Inc. Carlsbad, CA) according to the manufacturer’s instructions. Genes expressed in 10 drug-resistant cell lines and their parent cell lines were analyzed on a high-density oligonucleotide microarray (HG-U133A; Affymetrix, Santa Clara, CA) containing 22,282 transcripts. Target preparation and microarray processing procedures were performed as described in the Affymetrix GeneChip Expression Analysis Manual (Affymetrix, Santa Clara, CA). Briefly, the extracted total RNA was purified with an RNeasy kit (Qiagen, Valencia, CA). Twenty μg of total RNA was used to synthesize double-strand cDNA with SuperScript II reverse transcriptase (Life Technologies, Inc. Rockville, MD) and a T7-(dT)₂₄ primer (Metabion, Germany). Then, biotinylated cRNA was synthesized from the double-stranded cDNA using the RNA Transcript Labeling kit (Enzo Life Sciences, Farmingdale, NY) and was purified and fragmented. The fragmented cRNA was hybridized to the oligonucleotide microarray, which was washed and stained with streptavidin-phycoerythrin. Scanning was performed with an Agilent Microarray Scanner (Agilent Technologies, Palo Alto, CA).

GeneChip analysis was performed based on the Affymetrix GeneChip Manual (Affymetrix Inc., Santa Clara, CA) with Microarray Analysis Suite (MAS) 5.0, Data Mining Tool (DMT) 2.0, and Microarray Database software. All of the genes represented on the GeneChip were globally normalized and scaled to a signal intensity of 500. Fold changes were calculated by comparing transcripts between parent and acquired drug-resistant cell lines. The Microarray Analysis Suite software used the Wilcoxon’s test to generate detected (present or absent) and changed (increased or decreased) calls, and used the calls to statistically determine whether a transcript was expressed or not, and whether it was relatively increased, decreased, or unchanged. After being filtered through a “present” call (p < 0.05), a transcript was considered differentially expressed when it satisfied one of the following two conditions: 1) by fold change, transcripts increased or decreased >1.5-fold; 2) by one-sided Wilcoxon’s rank test, transcripts’ average fold change exceeded 1.5, with an “increased” (p < 0.003) or “decreased” (p > 0.997) call. In the case of 5-FU, all transcripts meeting the above conditions in at least three of four cell lines were considered differentially expressed. Hierarchical clustering and dendrogram figures were generated using Cluster and TreeView software (http://rana.stanford.edu). A three-dimensional graph of the multidimensional scaling was created using SPSS (SPSS Inc., Chicago, IL) and SigmaPlot (SPSS Inc.). To evaluate the statistical significance of eight genes differentially expressed in two or three of the drug subsets, paired t test was performed using SPSS (SPSS Inc.).

We selected two genes for real-time quantitative reverse transcription (RT)-PCR and seven genes for semiquantitiative RT-PCR for validation of the microarray data. Five μg of total RNA was used for creation of single-stranded cDNA using the SuperScript Preamplification System for First Strand cDNA Synthesis (Life Technologies, Inc., Rockville, MD). The cDNA was diluted and quantitatively equalized for PCR amplification. For real-time quantitative RT-PCR of MDK (midkine) and BIRC5, TaqMan PCR method using a 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA) was performed according to the manufacturer’s instructions. We used the primers and probes provided as Assays-on-Demand Gene Expression Products (Applied Biosystems). The expression of seven genes (MDK, FOSB, NQO1, DDB2, ITGB4, ABCC1, and IGFBP2) was verified by semiquantitative RT-PCR. The primer sets for PCR amplification were as follows: MDK forward 5′-ATGCAGCACCGAGGCTTCCT-3′, reverse 5′-ATCCAGGCTTGGCGTCTAGT-3′; FOSB forward 5′-GAGAGGGGAAGAGACAAAGT-3′, reverse 5′-CTTCATCCTCACACAGGACT-3′; NQO1 forward 5′-TGGAGAATATTTGGGATGAG-3′, reverse 5′-AATCCAGGCTAAGGAATCTC-3′; DDB2 forward 5′-GGAGATATCATGCTCTGGAA-3′, reverse 5′-GGCTACTAGCAGACACATCC-3′; ITGB4 forward 5′-TTCCAAATCACAGAGGAGAC-3′, reverse 5′-CTTGAGGTTGTCCAGATCAT-3′; ABCC1 forward 5′-CTGACAAGCTAGACCATGAATGT-3′, reverse 5′-TCACACCAAGCCGGCGTCTTT-3′; and IGFBP2 forward 5′- TTCCAGTTCTGACACACGTA-3′, reverse 5′-GACACAGGGGTTCAAAAATA -3′.

PCR was carried out with 1 μl of cDNA as follows: initial denaturation at 94°C for 5 min followed by 25–30 cycles of 94°C for 30 s, 55°C for 30 s, 72°C for 1 min, followed by a final elongation at 72°C for 7 min.

To investigate the correspondence between mRNA and protein of MDK, we performed Western blot analysis in SNU-620, SNU-620R-5-FU/1000, SNU-620R-CIS/2000, SNU-638, and SNU-638R-CIS/400. MDK protein was detected with an MK antibody (Santa Cruz Biotechnology, Inc., Santa Cruz, CA). Western blot analysis was performed as described previously (19).

Because the high-density oligonucleotide microarray contains a large number of probes, two different statistical analysis methods were used in parallel to select genes that were differentially expressed in drug-resistant gastric cancer cells. First, we investigated genes that showed altered expression patterns in drug-specific cell line subsets composed of the four 5-FU-, three doxorubicin-, and three cisplatin-resistant cell lines. In the 5-FU-resistant gastric cancer cell lines, a total of 38 genes were selected as having significant fold-change and Wilcoxon’s test results. Twenty-two genes were up-regulated and 16 were down-regulated in at least three of the four 5-FU-resistant cell lines. In the doxorubicin-resistant cell lines, we found over 200 differentially expressed genes, many of which were overexpressed. In the cisplatin-resistant cell lines, we identified 27 differentially expressed genes, 19 of which were up-regulated and 8 of which were down-regulated. After the individual gene selection in each drug subset, we next screened for genes that were differentially expressed in more than one of the drug subsets, i.e. multidrug resistance genes. We identified eight genes that were differentially expressed in more than one drug subset; only one of the eight was differentially expressed in all three subsets.

To verify the expression of the genes identified in microarray experiments, either real-time quantitative RT-PCR or semiquantitative RT-PCR was performed using the same RNA as that used in the microarray analysis. We tested two genes (MDK and BIRC5) for real-time quantitative RT-PCR and seven genes (MDK, FOSB, NQO1, DDB2, ITGB4, ABCC1, and IGFBP2) for semiquantitative RT-PCR, and found that the results were in good agreement with those from the microarray data, in that the observed differences were not significant.

In 5-FU-resistant gastric cancer cell lines, we identified 38 differentially expressed genes (Table 2), most of which are involved in cell proliferation, metabolic pathways, cell growth, and cell organization. In addition, a subset of differentially expressed genes was associated with signaling, responses to external stimuli, and cell adhesion. In particular, we observed up-regulation of cell growth regulators (NOV and IGFBP2) and genes involved in nucleobase, nucleotide, and nucleic acid metabolism (HOXB6, SF3B3, TYMS, DGUOK, and DDB2). Also, the overexpression of TYMS (thymidylate synthetase) was consistent with the action of 5-FU as a TYMS inhibitor. The signal transducers sorcin (SRI), MDK, and NQO1 were up-regulated, and the calcium-binding protein SRI was up-regulated in all of the 5-FU-resistant cell lines. A novel hypoxia-inducible factor 1 (HIF-1)-responsive gene, RTP801, recently identified as involved in both pro- and antiapoptotic activities (20), was down-regulated, as were several calcium ion-binding molecules (S100P, CALB2, and LDLR).

Table 3 shows the top 54 up-regulated genes among >200 genes and 20 down-regulated in doxorubicin-resistant gastric cancer cells. Many of the up-regulated genes are associated with the cell cycle, including genes involved with regulation of the cell cycle (FOSB, CDC2, CDC20, CDKN3, and MKI67), control of the mitotic cell cycle (BUB1, BUB1B, RRM1, and RRM2), DNA replication (TOP2A and MCM4), and antiapoptosis (BIRC5-survivin). Among the ATP-binding cassette (ABC) transporters, ABCC1 was up-regulated and ATP2B1 was down-regulated. In our microarray data, the expression of the MDR1 gene, which encodes a P-glycoprotein, was not detected. The chloride transporter CLIC4, responders to external stimulus (TBL1X and MBP), and transcription factor NFAT5 were all down-regulated in doxorubicin-resistant gastric cancer cells.

We identified 27 genes that were differentially expressed in cisplatin-resistant gastric cancer cells, 19 of which were up-regulated and 8 of which were down-regulated (Table 4). The differentially expressed genes in cisplatin-resistant cells showed the lowest fold change levels among three different drug subsets. The up-regulated genes included cell proliferation regulators (IGFBP6, FTH1, and GRN), genes associated with cell cycle (CDKN1A), stress responders (HSPA1B), transporters (ATP7A), cell adhesion molecules (PCDHGB7 and JUP), and metabolic factor (SF3B3). In contrast, the DNA repair and cell cycle checkpoint gene NBS1, and the ubiquitin-conjugate enzyme and apoptosis suppressor HIP2 were down-regulated.

We identified eight genes that were differentially expressed in more than one of the three drug subsets. For example, MDK (p = 0.0007) was overexpressed by >1.5-fold in 9 of 10 drug-resistant gastric cancer cell lines. The remaining cell line (SNU-719R-DOX/100) showed a 1.4-fold MDK overexpression, which was slightly below the 1.5-fold cutoff value used to determine significance. CDKN1A (p = 0.088), SF3B3 (p = 0.029), and LZTFL1 (p = 0.00074) were overexpressed in both 5-FU- and cisplatin-resistant gastric cancer cells. NQO1 (p = 0.044), TYMS (p = 0.079), and IGFBP2 (p = 0.012) were overexpressed in both 5-FU-resistant and doxorubicin-resistant cell lines, whereas CALB2 (p = 0.051) was down-regulated in these cells.

Recently, several studies on the drug-sensitivity and drug-resistance in either untreated human cancer cell lines or drug-exposed cells have been performed using microarray technologies (7, 9, 11, 21, 22). They have revealed the correlations between gene expression and drug activity, as well as identification of genes differentially expressed in drug-sensitive and drug-resistant cancer cells. Also, several microarray studies on the identification of genes with altered expression in human gastric cancers have been performed (8, 10, 12). From these studies, numerous genes have been identified as being associated with gastric cancer development and progression, some of which will be used as novel chemotherapeutic targets for the treatment or prevention of gastric cancer. However, although the emergence of drug resistance is recognized as a major burden in all cancer treatment, few microarray studies have sought to identify candidate genes associated with drug resistance in gastric cancer. Here, we established 12 drug-resistant gastric cancer cell lines from 4 different gastric cancer cell lines (SNU-620, SNU-638, SNU-668, and SNU-719) by repeated exposure to the chemotherapeutic drugs 5-FU, doxorubicin, and cisplatin. The resistant cell lines have acquired drug-resistance over the long-term period from 11 months to 2 years, by increasing drug dosage, and confirmed their stable resistance by repeated drug sensitivity assays (MTT assay). It has previously been shown that gastric cancer cells are more sensitive to doxorubicin and cisplatin than to 5-FU (23). In support of this, we found that the relative resistances of 5-FU-resistant cell lines measured by MTT assay were higher than those of doxorubicin- and cisplatin-resistant cell lines. Of the 12 drug-resistant cell lines, two (the doxorubicin-resistant cell line from SNU-638 and the cisplatin-resistant cell line from SNU-719) were excluded from our microarray analysis because MTT assay determined that their relative resistances were <2-fold, which was regarded as a low degree of resistance. Thus, we used a total of 14 cell lines (10 drug-resistant and 4 parent cell lines) for genome-wide expression analysis to identify drug resistance candidate genes in drug-resistant gastric cancer cell lines.

It was suggested that each cancer cell represents a different pattern of drug-resistance gene expression even within cells clonally derived from the same cancer, and may be expected to exhibit a considerable amount of heterogeneity with respect to drug resistance (4). Because our four gastric cancer parent cell lines were genetically different (17), the overall gene expression pattern of each resistant cell line tended to be more similar to the same-parent-originated resistant cell lines than to the same-drug-treated resistant cell lines, as shown in multidimensional scaling (Fig. 1 A).

Our microarray data provided information on genes that were differentially associated with resistance to specific chemotherapeutic drugs, as well as those differentially associated with two or more of the drugs. In this study, cells were maintained without drugs before microarray experiments to avoid making note of transcriptional changes caused by the insult of drugs themselves. Thus, this precaution may not be compatible to detect dynamic changes in response to the drugs themselves, like acquired transcriptional activation. Although 5-FU, doxorubicin, and cisplatin exert their chemotherapeutic effects in different ways, we found eight genes that were differentially expressed in association with resistance to more than one of the tested drugs, and one that was overexpressed in association with resistance to all three tested drugs.

The doxorubicin-resistant cell lines provided the most differentially expressed genes. This suggests that the doxorubicin-resistant cells, although derived from different gastric cancer patients, contain more consistent molecular changes than the other drug-resistant cells. When we performed clustering analysis between all drug-resistant cell lines and the differentially expressed genes, we observed that the doxorubicin-resistant cell lines were clustered together (Fig. 1 B). A previous study demonstrated that at different time points, etoposide-resistant melanoma cells showed stable gene deregulation, whereas cisplatin- and fotemustine-resistant cells showed substantial variation (11). Together with our results, this suggests that anticancer drugs targeting topoisomerase II, such as doxorubicin and etoposide, exhibit coherent resistance in different cell types and during different periods.

Cell cycle deregulation is an important molecular event in the acquisition of drug resistance (5). Most of the genes we identified as overexpressed in doxorubicin-resistant gastric cancer cells were involved in the cell cycle, including the mitotic cell cycle-associated genes BUB1, BUB1B, CDKN3, RRM1, and RRM2. It was previously shown that cell cycle genes had an interesting expression pattern in microarray experiment after exposure to doxorubicin in MCF-7 cells and a subset of these genes was also constitutively overexpressed in MCF-7 doxorubicin-resistant cells (7). Thus, these results suggest that cell cycle genes might significantly contribute to the doxorubicin resistance. In our microarray result, the up-regulations of BIRC5 were observed in doxorubicin-resistant cells. BIRC5, also termed survivin, is a protein responsible for inhibiting apoptosis and preventing cell death (24). Negative correlation between BIRC5 (survivin) and 5-FU derivatives in untreated human cancer cell lines was suggested (9), implying that the overexpression of BIRC5 might be associated with drug-resistance. RRM2, one of two ribonucleotide reductase subunits, is a rate-limiting enzyme in DNA synthesis and repair (25). Previously, it was reported that the overexpression of RRM2 mRNA and protein was found in gemcitabine-resistant cells, implicating the gene in drug resistance (25). Finally, the ATP-binding cassette (ABC) transporter ABCC1 (MRP1) was up-regulated in all doxorubicin-resistant gastric cancer cells, as compared with ABCC1 expressions in the parent cells. Drug resistance through drug efflux pumps has been well described, and the ABC transporters are also known as energy-dependent drug efflux pumps (4). In both our doxorubicin-resistant cells and their parent gastric cancer cells, ABCB1 (MDR1) expressions were not detectable. It was previously demonstrated that the levels of MDR1 RNA was relatively low in gastric cancer cell lines, whereas intermediate or high levels were present in colorectal carcinoma cell lines (6, 18).

A total of 38 genes were differentially expressed in 5-FU-resistant gastric cancer cell lines. The relationship between the overexpression of TYMS and 5-FU resistance is well-characterized (3), and was noted in this investigation except in one case (SNU-638R–5-FU/50000). Although SNU-638R–5-FU/50000 represented the highest degree of resistance to 5-FU (>12,500-fold), TYMS expression was slightly decreased in these cells per our microarray data. This may be explained by the proposition that high doses of 5-FU reduce the activity of TYMS (26). Because the SNU-638R–5-FU/50000 cells were cultured at high 5-FU concentrations (380 μm) over almost 2 years, it is possible that TYMS transcription levels had been down-regulated, and that the acquired 5-FU resistance was not dependent on the TYMS mechanism. A more possible explanation for the TYMS down-regulation in SNU-638R-5-FU/50000 cells is that TYMS may be mutated and has a decreased affinity for 5-fluoro-dUMP. In our microarray data, DYPD expression was not significant in 5-FU resistant cells, although a previous report suggested that DYPD expression was negatively correlated with 5-FU sensitivity in cancer cells (21). Another up-regulated gene is that for SRI, a soluble resistance-related calcium-binding protein known to be overexpressed in various drug-resistant cancer cells (27, 28), although this is the first identification of its association with 5-FU resistance. All four of the 5-FU-resistant cell lines showed up-regulated SRI expression, and, although increased expression of SRI is believed to result from gene amplification (28), it is not yet known how SRI confers multidrug resistance. CLU (clusterin), also overexpressed in all of the 5-FU-resistant cell lines, is a ubiquitous glycoprotein that is highly overexpressed in some normal and malignant tissues undergoing apoptosis (29). The overexpression of CLU has been shown to inhibit apoptotic cell death in cisplatin-treated renal cell carcinoma, suggesting that CLU confers a chemoresistance phenotype through its antiapoptotic activity (29, 30). Moreover, it has been demonstrated that suppression of CLU expression by an antisense oligonucleotide had a chemosensitizing effect (29, 30). From these results, it can be suggested that CLU is a potent candidate gene for gastric cancer cell drug resistance.

In cisplatin-resistant gastric cancer cells, the differentially expressed genes were mainly associated with stress response, transport, cell cycle, and metabolism. ATP7A, a copper-transporting P-type adenosine triphosphatase, was overexpressed in cisplatin-resistant gastric cancer cells. The closely related ATP7B is well known for conferring resistance to cisplatin (31), but little is known about the association of ATP7A with cisplatin resistance. ATP7A is highly homologous with ATP7B and has a similar export function for copper. A recent report (32) showed ATP7A overexpression in a cisplatin-resistant ovarian cancer cell line. These results suggest a potential role for ATP7A in cisplatin resistance, as well as ATP7B, although the mechanism has not yet been elucidated (32). The Fos gene family members, FOS and FOSB, showed up-regulation in two of three cisplatin-resistant cells (not listed in Table 4), consistent with previous reports suggesting a relationship between Fos gene expression and drug resistance (33).

In this study, we have identified eight genes whose differential expression was associated with resistance to more than one of the three chemotherapeutic drugs tested. Of these, the MDK gene was consistently overexpressed in all 5-FU-, doxorubicin-, and cisplatin-resistant gastric cancer cells compared with the expressions in their parent cells, strongly suggesting that it may contribute to multidrug resistance. The correspondence between mRNA and protein of MDK was observed in SNU-620R-5-FU/1000 and SNU-638R-CIS/400 by Western blot analysis. MDK, a heparin-binding growth factor, is associated with promoting neuronal survival, inducing neurite outgrowth (34, 35, 36), and has been implicated in carcinogenesis and angiogenesis. Found at low levels in normal adult tissue, MDK is frequently overexpressed in esophageal, gastric, colon, pancreatic, hepatocellular, lung, breast, urinary bladder carcinoma, neuroblastoma and Wilms’ tumors (35, 36). Transfection of an MDK antisense oligodeoxynucleotide into CMT-93 mouse rectal carcinoma cells markedly suppressed tumor growth, suggesting that MDK could be a potent target for cancer therapy (36, 37). MDK has cytoprotective activity and has rescued cisplatin-induced apoptotic cell death in both murine kidney and cultured G401 cells, implying that MDK confers a cellular growth advantage by functioning as an antiapoptotic factor (34). Recently, the overexpression of HB-EGFGF (heparin-binding epidermal growth factor-like growth factor) was observed in the cisplatin-resistant and 5-FU-resistant gastric tumors by microarray analysis, suggesting that HB-EGFGF is a candidate chemoresistant-related gene of gastric cancer (38). Interestingly, these results support that heparin-binding growth factors such as MDK or HB-EGFGF might be one of the important genes contributing to chemoresistance in gastric cancers. Accordingly, we hypothesize that the overexpressed MDK can contribute to the growth progression of gastric cancer cells with an acquired multidrug resistance and may be a potent target to restore chemosensitivity. To clarify the relationship between MDK overexpression and multidrug resistance, it will be necessary to further investigate whether the inhibition of MDK overexpression in drug-resistant cancer cells leads to recovered sensitivity.

In summary, we have identified genes that are differentially expressed in 5-FU-, doxorubicin-, and cisplatin-resistant gastric cancer cells. Some of the identified genes were previously known to be associated with drug-resistance. To date, most studies on drug resistance in gastric cancer have focused on candidate gene work targeting a limited number of drug resistance genes identified in other cancers. In contrast, our use of microarray technology for a genome-wide screen of 10 drug-resistant gastric cancer cell lines has provided useful information on differentially expressed genes and possible new candidate multidrug resistance genes in gastric cancer cells. Although further in vivo validations for the identified genes are required because the materials used in the study were induced drug-resistant cells in vitro, this important information may lead to the discovery of new drug resistance targets, and perhaps to the development of better cancer chemotherapy strategies.