The mechanism of drug resistance in ovarian cancer is multifactorial, and accumulation of multiple genetic changes may lead to the drug-resistant phenotype. In our attempt to find characteristic genetic changes in drug-resistant tumors, we screened the whole genome for gene aberrations in 28 primary ovarian cancers using the comparative genomic hybridization method. These cancers included 14 tumors from patients who did not respond to cisplatin-based combination chemotherapy and 14 tumors from patients who had complete response to the chemotherapy. We found gains in chromosomal regions 1q21–q22 and 13q12–q14 to be related to the drug-resistant phenotype in ovarian cancer patients. Several genes encoding transcription factors, oncogenes, cell cycle regulators, and regulators of the apoptotic pathway are located on these regions of the chromosomes, and these genes are potential modulators for toxic insults in cancer cells. This is the first report that shows the relationship between certain genomic aberrations and clinical resistance to cisplatin-based chemotherapy in ovarian cancer patients based on the comparative genomic hybridization analysis. Present findings suggest that these chromosomal gains may be potential indicators for prediction of resistance in ovarian cancer patients before cisplatin-based chemotherapy.

Ovarian cancer is the leading cause of death from gynecological cancer in the United States and Japan (1). Initially, cisplatin-based combination chemotherapy is associated with a 40–60% clinical response rate. However, the overall 5-year survival rate for advanced ovarian cancer patients is still around 20% (2). This low survival rate is due to the fact that some primary tumors and most recurrent tumors develop drug resistance that leads to treatment failure (3). Thus, overcoming drug resistance is the key to successful treatment of ovarian cancer.

Mechanisms of cisplatin resistance in human cancer cells have been examined extensively in vitro. Decreased drug accumulation and activated detoxification pathways, such as increased cellular levels of glutathiones, γ-glutamylcysteine synthetase (3), glutathione S-transferase π, or metallothioneins, may be associated with cisplatin resistance (4, 5). Recent studies on normal cell cycle and apoptotic regulatory pathways provided insights into the involvement of their regulators in the cellular response to DNA-damaging agents, showing a possible role for the cisplatin-resistant phenotype in human cancer (6, 7, 8, 9). Because DNA repair through transcriptional induction of GADD45 (10), ERCC1 and ERCC3(11), or transcription factor IIH-associated nucleotide excision repair (12) occurs after DNA damage, the role of these genes in the drug-resistant phenotype has been reported. Possible regulation of DNA repair by a mutated cAMP-dependent protein kinase regulatory subunit in cisplatin-resistant Chinese hamster ovary cells has also been observed (13). In addition, transcription factor nuclear factor κB (5, 14), metastasis suppressor gene nm-23(15), mismatch repair genes hMLH2 and hMSH1(16), cell matrix protease cathepsin D (17), the multidrug resistance P-glycoprotein and its relatives multidrug resistance-associated protein and lung resistance-associated protein (18), and growth factor receptors epidermal growth factor receptor or HER-2/neu (19) have been evaluated for their role in cisplatin resistance in various human cancer cells.

In clinical resistance to cisplatin-based chemotherapy, the status of these genes has been evaluated as a potential marker for the drug-resistant phenotype and prognosis (20, 21, 22). Nevertheless, the underlying mechanisms and pathways that lead to clinical drug resistance seem complex and are not well understood. In view of tumor heterogeneity and the large number of genetic changes accumulated through tumorigenesis (23), it is necessary to investigate all of the genetic changes that yield the drug-resistant phenotype by a whole-genome approach.

CGH,3 developed by Kallioniemi et al.(24, 25), is one of the most powerful cytogenetic tools for the analysis of structural genetic abnormalities in the entire genome in a single experiment. Several novel aberration sites in human cancers have been found by CGH studies (26), but to our knowledge, no attempt at showing a correlation between CGH profiles and drug-resistant phenotypes in ovarian cancer patients has been reported. Our purpose in this study is to identify patterns of genetic changes that would predict resistance to chemotherapy in patients with ovarian cancer.

Patients, Chemotherapy, and Response Evaluation.

Of 71 patients with primary epithelial ovarian cancer treated at the National Defense Medical College Hospital (Saitama, Japan) between 1993 and 1997, the following patients were selected: (a) patients who received no chemotherapy prior to any surgical therapy; (b) patients who harbored any residual tumors after initial debulking surgery; and (c) patients treated with six courses of cisplatin-based combination chemotherapy (described below) after the initial surgery. The subjects were then grouped into the following four categories according to their response to chemotherapy: (a) CR; (b) partial response; (c) no change; and (d) PD (3). Only patients in the CR (n = 14) and PD (n = 14) groups were included in this study. Our chemotherapy regimen for primary epithelial ovarian cancer was as follows: a drip infusion of 50 mg/m2 cisplatin for 3 h accompanied by an i.v. injection of 50 mg/m2 doxorubicin and 500 mg/m2 cyclophosphamide was given every 4 weeks for six courses (3). Histological diagnosis was confirmed by microscopic examination of H&E-stained sections according to the WHO criteria. Clinical stages were determined according to the International Federation of Gynecology and Obstetrics (FIGO) system.

DNA Extraction.

High molecular weight genomic DNAs from primary tumors were isolated by proteinase K digestion, phenol-chloroform extraction, and ethanol precipitation, as described previously (27). All samples were examined by 1% agarose gel electrophoresis for conservation of high molecular weight.

CGH.

CGH was performed by indirect labeling methods (24) with slight modifications. Briefly, tumor DNA and reference DNA were labeled by nick translation with biotin-16-dUTP (Boehringer Mannheim, Manheim, Germany) and digoxigenin-11-dUTP (Boehringer Mannheim), respectively. Before hybridization, the metaphase preparation from normal lymphocytes (Vysis, Downers Grove, IL; FML, Tokyo Japan) was denatured at 73°C for 5 min in 70% formamide and 2× SSC [1× SSC = 0.15 m NaCl-0.015 m sodium citrate (pH 7.0)] and dehydrated by sequential immersion in 70% ethanol at −20°C, 85% ethanol at RT, and 100% ethanol at RT. A total of 900 ng of labeled tumor and reference DNAs with 10 μg of human Cot-1 DNA (Life Technologies, Inc., Gaithersburg, MD) in 10 μl of hybridization buffer (50% formamide, 10% dextran sulfate, and 2× SSC) were denatured for 5 min at 73°C and applied onto metaphase cells on slides. Hybridization was performed at 37°C for about 60 h in a moisturized chamber. Posthybridization washes were performed as follows: (a) three times in 50% formamide/2× SSC; (b) twice in 2× SSC; and (c) once in 0.1× SSC at 45°C for 10 min each. Staining was performed as described below. After blocking in 1% BSA/4× SSC for 5 min, slides were incubated with 1% BSA/4× SSC containing 5 μg/ml FITC-conjugated avidin (Vector Laboratories) for 30 min at RT and washed sequentially with 4× SSC, 0.1% Triton X-100/4× SSC, and 4× SSC at RT for 10 min each. After blocking in PNM, slides were incubated with 2 μg/ml rhodamine-conjugated antidigoxgenin antibody (Boehringer Mannheim) and 5 μg/ml biotinylated antiavidin antibody (Vector Laboratories) in PNM for 45 min at RT. Slides were washed four times with 0.1 m Na2HPO4 and 0.1% NP40 for 5 min at RT and then immersed in PNM for 5 min, followed by incubation in PNM containing 5 μg/ml FITC-conjugated avidin for 30 min at RT. The slides were washed twice with 0.1 m Na2HPO4 and 0.1% NP40 for 5 min and washed twice with distilled water for 5 min. Chromosomes were counterstained with 4′,6-diamidino-2-phenylindole (Molecular Probes, Inc., Eugene, OR).

Digital Image Analysis.

Metaphase images were analyzed by a cooled charge-coupled device camera (Applied Imaging, Santa Clara, CA) attached to a fluorescence microscope (Leica, Wetzlar, Germany). Three-color images (green, labeled tumor DNA; red, labeled reference DNA; and blue, counterstaining) were captured. Digital images were processed for quantitation of fluorescence intensity with Cytovision software (Applied Imaging). The green:red fluorescence ratio along individual chromosomes was calculated. The green:red ratios from several metaphases were averaged and plotted along the chromosomes. Reliability was assessed with 95% confidence intervals. Ratios higher than 1.25 were defined as chromosomal gains, and ratios below 0.75 were defined as chromosomal losses, respectively (24). The telomeric and heterochromatic regions were excluded from CGH analysis (24).

Statistical Analysis.

Fisher’s exact test was used to evaluate the relationship between chromosomal status and clinical or biological features.

In this study, we analyzed the patterns of genetic aberration in 14 PD group tumors and 14 CR group tumors from patients with primary epithelial ovarian cancer (Table 1). CR group cases consist of six serous, two mucinous, four endometrioid, and two clear cell adenocarcinomas. Ten of the 14 CR cases were stage III–IV. PD group cases consist of five serous, two mucinous, one endometrioid, and six clear cell adenocarcinomas. Thirteen of the 14 PD cases were stage III–IV. Fig. 1 shows schematic representations of all chromosomal aberrations found in CR group patients (Fig. 1,A) and PD group patients (Fig. 1 B). Each tumor from CR and PD group patients harbored more than three regions of genetic aberration, and the average number of regions with genetic changes in CR and PD group tumors was 11.6 ± 9.2 and 15.9 ± 8.6, respectively. The number of chromosomes involved in genetic changes in CR and PD group tumors was 9.1 ± 6.0 and 11.9 ± 5.3, respectively.

As shown in Table 2, frequent alterations observed in primary ovarian cancer were gains at 1q21–q22 (11 of 28 patients, 39%), 3q13 (11 of 28 patients, 39%), 3q28 (13 of 28 patients, 46%), 8q24 (13 of 28 patients, 46%), 17q25 (11 of 28 patients, 39%), and 20q13.1 (13 of 28 patients, 46%). In comparison to the genetic changes in CR group tumors, more frequent gains at 1q21–q22 (9 of 14 patients, 64%), 9q34 (5 of 14 patients, 36%), 12p13 (4 of 14 patients, 29%), 13q12–q14 (5 of 14 patients, 36%), and 20q13.1 (9 of 14 patients, 64%) and loss at 13q31 (5 of 14 patients, 36%) were observed in PD group tumors. In the CR group tumors, gains at 12p13 or 13q12–q14 were not observed, and gains at 1q21–q22 (2 of 14 patients, 14%) and 9q34 (1 of 14 patients, 7%) and loss at 13q31 (1 of 14 patients, 7%) were observed in only a small number of cases (Table 2).

We performed a statistical analysis for the existence of a correlation between the abundance of certain gene aberrations and the clinical drug-resistant phenotype. As a consequence, only gains at 1q21–q22 (P = 0.0183) and 13q12–q14 (P = 0.0407) were observed in significantly high abundance in PD group tumors, compared to those of CR group tumors (Table 2). Other changes, including gains at 3q13, 3q28, 8q24, 9q34, 12p13, 17q25, and 20q13.1 and loss at 13q31, did not show any significant difference in abundance between the PD and CR group tumors. Frequent aberrations on chromosomes 1q and 13q in PD group tumors are shown schematically in Fig. 2, compared to those of CR group tumors.

In this study, we examined the associations between patterns of genetic alterations and response to chemotherapy, which is one of the most important factors for achieving remission in advanced or recurrent ovarian cancer (1, 2, 3). Our data show that drug-resistant tumors harbor a larger number of chromosomal regions with genetic abnormalities. This is because the majority of ovarian cancers appear to be sporadic and have complex accumulation of multiple genetic changes, which may contribute to the development and progression of cancer and, consequently, provoke the drug-resistant phenotype (23). In a previous study, Wasenius et al.(28) reported that gains in chromosomes 2q, 4, 6q and 8q or losses in chromosomes 2p, 7p, 11p, 13, and X were the genetic imbalances responsible for cisplatin resistance in ovarian cancer cell lines. However, no characteristic CGH patterns in clinically resistant tumors have been reported to date.

Our data show a significantly higher ratio of genetic changes characterized by 1q21–q22 and 13q12–q14 gains in cisplatin-resistant tumors than in cisplatin-sensitive tumors (Table 2). Abnormalities in 1q21, including amplifications, rearrangements, and translocations, have been reported in a number of human solid tumors and hematological malignancies (29, 30). Genetic abnormality is also associated with poor chemotherapeutic response in B-cell lymphoma (31). Many candidate genes contributing to the drug-resistant phenotype are located on 1q21–q22, including BCL-2-related myeloid leukemia sequence (MCL-1), cathepsins (CTSS and CTSK), the polymorphic mucinous tumor-associated gene (MUC-1), Src homology 2 domains containing transforming protein 1 (SHC-1), the transcription factor-like 1 (YL-1 or TCFL-1), and the papillary renal cell carcinoma gene (PRCC). Several reports showed that up-regulation of MCL-1 expression, along with GADD45 and BAX, was caused by DNA-damaging agents in cells sensitive to apoptosis, thus suggesting a possible role for these genes in drug resistance (29). The MUC-1 gene was reported to be frequently amplified and expressed in breast cancer, indicating a potential role in the carcinogenesis of breast tumors (30). The role of these genes and their abnormalities in the drug-resistant phenotype in ovarian cancer remain to be examined.

Gain in 13q12–q14 is also interesting because it is observed only in drug-resistant tumors (Table 2). This region contains the retinoblastoma 1 gene (RB1) and the breast cancer 2 gene (BRCA2), as well as several candidate genes, including thioredoxin-dependent peroxidase reductase (TDPX1) and forkhead 1 in rhabdomyosarcoma (FKHR). The thioredoxin-dependent peroxide reductase encoded by TDPX1 modulates the activity of the thioredoxin system, which plays a major role in removing reactive oxygen species and free radicals (32). This system is also involved in the acquisition of drug resistance in certain types of malignant tumors (32). The FKHR gene encodes a transcription factor that fuses with the transcription activator PAX3 and acts as an oncogene in rhabdomyosarcoma (33). Overexpression of wild-type p53 in cells containing the PAX-FKHR fusion protein shows sensitization to DNA-damaging agents, suggesting a possible role of these gene products in the drug-resistant phenotype (33).

Gains in 9q34, 12p13, and 20q13.1 and loss at 13q31 were also observed more frequently in drug-resistant tumors. However, none of these abnormalities was statistically significant, possibly due to the sample size.

Gains of chromosomal regions 3q and 8q are the most commonly observed changes in ovarian cancer, as well as in breast, prostate, and renal carcinomas (26, 34, 35). Iwabuchi et al.(34) showed a high frequency of 3q26 amplification in poorly differentiated ovarian cancer. A recent report shows a frequent copy number increase of the telomerase gene (hTR) located on chromosome 3q26 (36). A few reports show that telomerase activity can be modulated by chemotherapy in human cancer (37), but no relationship between drug resistance and telomerase activity has been shown. The commonly gained loci 8q24 is known to harbor the C-MYC oncogene, which is reported to be amplified in 30% of ovarian cancer (38). Amplification of 3q28 and 8q24 was present in 46% of the clinical specimens, regardless of their response, suggesting that these genetic imbalances are related to oncogenesis but not to the drug-resistant phenotype in ovarian cancer.

With regard to previous studies of functional analysis on drug-resistant tumors, the amplification of chromosomal regions for MDM-2 on 12q14.3–q15, MYCN on 2p24.1, EGFR on 7p12.1–p12.3, PGY1 encoding P-glycoprotein on 7q21.1, and GLCLC encoding γ-glutamylcysteine synthetase on 6p12 or loss of the regions for the TP53 gene on 17p13.1 and CDKN2A encoding p16 on 9p21 are possible genetic changes in drug-resistant ovarian tumors. In our study, however, these genetic changes are not observed in the drug-resistant tumors. It is possible that the expression of some of the genes is regulated at the transcriptional or posttranscriptional level, but not by gene amplification (5). Moreover, some of the changes may be too small in size to be detected by CGH analysis because the minimum detectable size is reported to be 5–10 Mb or more (24, 25).

Becuse CGH is a purely cytogenetic analytical method, the result does not lead directly to gene isolation. However, those regions that show frequent changes in drug-resistant tumors may be exploited as indicators for predicting the drug-resistant phenotype for cisplatin-based chemotherapy in ovarian cancer patients. Recent development of cDNA microarray technology may enable the analysis of whole expression of genes that may contribute to the drug-resistant phenotype in human cancer through its potential ability to approach functional genomics (39, 40). Together with the data from the CGH analysis of drug-resistant tumors in ovarian cancer patients, this information may offer significant insights into the dominant mechanisms that lead to the drug-resistant phenotype in these patients.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

        
1

Supported in part by Grants-in-Aid for Cancer Research from the Ministry of Education, Sciences, Sports and Culture of Japan and from the second-term Comprehensive 10-Year Strategy for Cancer Control and Cancer Research from the Ministry of Health and Welfare of Japan.

                
3

The abbreviations used are: CGH, comparative genomic hybridization; CR, complete response; PD, progressive disease; RT, room temperature; PNM, 0.1 m Na2HPO4, 0.1% NP40, and 1% skim milk.

Fig. 1.

Chromosomal aberrations of primary epithelial ovarian cancers. The aberrations in the CR group (A) and the PD group (B) are shown separately. Lines on the right and left sides, gains and losses of DNA copy number, respectively. Each line represents an alteration of one tumor.

Fig. 1.

Chromosomal aberrations of primary epithelial ovarian cancers. The aberrations in the CR group (A) and the PD group (B) are shown separately. Lines on the right and left sides, gains and losses of DNA copy number, respectively. Each line represents an alteration of one tumor.

Close modal
Fig. 2.

Frequent chromosomal aberrations on chromosomes 1q and 13q in PD group tumors (right) of primary epithelial ovarian cancers, as compared to the CR group tumors (left). The frequency of each aberration is designated in Table 2.

Fig. 2.

Frequent chromosomal aberrations on chromosomes 1q and 13q in PD group tumors (right) of primary epithelial ovarian cancers, as compared to the CR group tumors (left). The frequency of each aberration is designated in Table 2.

Close modal
Table 1

Clinical characteristics of 28 primary ovarian cancers

Case no.PathologyStageaResponseb
108 Serous IIIC CR 
133 Serous IIIC CR 
141 Serous IIIC CR 
159 Serous IIIC CR 
160 Serous IIIC CR 
111 Serous IV CR 
128 Mucinous IIC CR 
161 Mucinous IIIA CR 
163 Endometrioid IIC CR 
150 Endometrioid IIIB CR 
104 Endometrioid IIIC CR 
148 Endometrioid IIIC CR 
171 Clear cell IIC CR 
173 Clear cell IIC CR 
112 Serous IIIC PD 
164 Serous IIIC PD 
166 Serous IIIC PD 
172 Serous IIIC PD 
119 Serous IV PD 
158 Mucinous IIIC PD 
145 Mucinous IV PD 
134 Endometrioid IC PD 
101 Clear cell IV PD 
165 Clear cell IIIB PD 
109 Clear cell IIIC PD 
132 Clear cell IIIC PD 
152 Clear cell IIIC PD 
167 Clear cell IIIC PD 
Case no.PathologyStageaResponseb
108 Serous IIIC CR 
133 Serous IIIC CR 
141 Serous IIIC CR 
159 Serous IIIC CR 
160 Serous IIIC CR 
111 Serous IV CR 
128 Mucinous IIC CR 
161 Mucinous IIIA CR 
163 Endometrioid IIC CR 
150 Endometrioid IIIB CR 
104 Endometrioid IIIC CR 
148 Endometrioid IIIC CR 
171 Clear cell IIC CR 
173 Clear cell IIC CR 
112 Serous IIIC PD 
164 Serous IIIC PD 
166 Serous IIIC PD 
172 Serous IIIC PD 
119 Serous IV PD 
158 Mucinous IIIC PD 
145 Mucinous IV PD 
134 Endometrioid IC PD 
101 Clear cell IV PD 
165 Clear cell IIIB PD 
109 Clear cell IIIC PD 
132 Clear cell IIIC PD 
152 Clear cell IIIC PD 
167 Clear cell IIIC PD 
a

FIGO clinical stage.

b

Response to cisplatin-based chemotherapy, represented by either CR or PD, according to the criteria proposed by the Japanese Association for Cancer Treatment.

Table 2

Association of 1q21–q22 and 13q12–q14 gains with PD in primary ovarian cancers

Chromosome regionaCR (%)b (n = 14)PD (%)b (n = 14)Total (%) (n = 28)P                  c
+1q21–q22 2 (14) 9 (64) 11 (39) 0.0183 
+3q13 4 (29) 7 (50) 11 (39) NS 
+3q28 8 (57) 7(50) 13 (46) NS 
+8q24 6 (43) 7 (50) 13 (46) NS 
+9q34 1 (7) 5 (36) 6 (21) NS 
+12p13 0 (0) 4 (29) 4 (14) NS 
+13q12–q14 0 (0) 5 (36) 5 (18) 0.0407 
−13q31 1 (7) 5 (36) 6 (21) NS 
+17q25 5 (36) 6 (43) 11 (39) NS 
+20q13.1 4 (29) 9 (64) 13 (46) NS 
Chromosome regionaCR (%)b (n = 14)PD (%)b (n = 14)Total (%) (n = 28)P                  c
+1q21–q22 2 (14) 9 (64) 11 (39) 0.0183 
+3q13 4 (29) 7 (50) 11 (39) NS 
+3q28 8 (57) 7(50) 13 (46) NS 
+8q24 6 (43) 7 (50) 13 (46) NS 
+9q34 1 (7) 5 (36) 6 (21) NS 
+12p13 0 (0) 4 (29) 4 (14) NS 
+13q12–q14 0 (0) 5 (36) 5 (18) 0.0407 
−13q31 1 (7) 5 (36) 6 (21) NS 
+17q25 5 (36) 6 (43) 11 (39) NS 
+20q13.1 4 (29) 9 (64) 13 (46) NS 
a

Regions of chromosomal gains and losses observed in 28 primary ovarian cancers. In the first column, + and − represent gain and loss, respectively.

b

Response to cisplatin-based chemotherapy, represented by either CR or PD, according to the criteria proposed by the Japanese Association for Cancer Treatment. Values in parentheses are the percentage of the total number of CR or PD tumors.

c

The association of each gene aberration with PD in primary ovarian cancers was estimated by Fisher’s exact test and represented as P.

We thank Khew-Voon Chin and Mary Ellen Cvijic for helpful reading of and comments on the manuscript.

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