Literature DB >> 18231104

Impacts of excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase, and epidermal growth factor receptor on the outcomes of patients with advanced gastric cancer.

J Matsubara1, T Nishina, Y Yamada, T Moriwaki, T Shimoda, T Kajiwara, T E Nakajima, K Kato, T Hamaguchi, Y Shimada, Y Okayama, T Oka, K Shirao.   

Abstract

Using laser-captured microdissection and a real-time RT-PCR assay, we quantitatively evaluated mRNA levels of the following biomarkers in paraffin-embedded gastric cancer (GC) specimens obtained by surgical resection or biopsy: excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase (DPD), methylenetetrahydrofolate reductase (MTHFR), epidermal growth factor receptor (EGFR), and five other biomarkers related to anticancer drug sensitivity. The study group comprised 140 patients who received first-line chemotherapy for advanced GC. All cancer specimens were obtained before chemotherapy. In patients who received first-line S-1 monotherapy (69 patients), low MTHFR expression correlated with a higher response rate (low: 44.9% vs high: 6.3%; P=0.006). In patients given first-line cisplatin-based regimens (combined with S-1 or irinotecan) (43 patients), low ERCC1 correlated with a higher response rate (low: 55.6% vs high: 18.8%; P=0.008). Multivariate survival analysis of all patients demonstrated that high ERCC1 (hazard ratio (HR): 2.38 (95% CI: 1.55-3.67)), high DPD (HR: 2.04 (1.37-3.02)), low EGFR (HR: 0.34 (0.20-0.56)), and an elevated serum alkaline phosphatase level (HR: 1.00 (1.001-1.002)) were significant predictors of poor survival. Our results suggest that these biomarkers are useful predictors of clinical outcomes in patients with advanced GC.

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Year:  2008        PMID: 18231104      PMCID: PMC2259181          DOI: 10.1038/sj.bjc.6604211

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Gastric cancer (GC) is the second leading cause of cancer-related deaths worldwide, annually accounting for 40–50 deaths per 100 000 population in Japan and 5–15 deaths per 100 000 population in Europe (Parkin, 2001). During the past decade, newly developed cytotoxic drugs have been included in treatment regimens for GC. These new regimens have better response rates, often at the cost of higher incidences of severe adverse events (Ajani, 2005). This situation has created a greater need for diagnostic techniques that can predict clinical outcomes such as tumour response and survival in GC (Ichikawa, 2006). Considerable evidence suggests that the intratumour gene expressions of drug-metabolising enzymes, DNA repair enzymes, or angiogenic enzymes are useful predictors of treatment outcomes such as survival and the response to anticancer drugs (Backus ; Ulrich ; Marsh and McLeod, 2004). However, the clinical significance of these biomarkers remains unclear, especially in GC. 5-Fluorouracil (5-FU) and cisplatin are key drugs for the management of GC. Pharmacogenetic variability in metabolising enzymes of 5-FU and folate is a major determinant of the sensitivity to 5-FU and survival in GC (Lenz ; Banerjee ; Ichikawa ; Napieralski ). Several enzymes have key roles in the metabolic pathway of 5-FU and folate (Figure 1): thymidylate synthase (TS) is a target enzyme of 5-FU; dihydropyrimidine dehydrogenase (DPD) is a degrading enzyme of 5-FU; thymidine phosphorylase (TP) and orotate phosphoribosyl transferase (OPRT) are important metabolic enzymes; and dihydrofolate reductase (DHFR) and methylenetetrahydrofolate reductase (MTHFR) participate in folate metabolism. Lenz and Ichikawa have found that high TS mRNA expression in GC could predict poor clinical outcomes of treatment with 5-FU. Napieralski reported that high DPD expression in GC may correlate with poor survival and no response to 5-FU.
Figure 1

5-Fluorouracil and folate metabolic pathways. Genes examined in our study are shown in bold. DPD, dihydropyrimidine dehydrogenase; DHFR, dihydrofolate reductase; MTHFR, methylenetetrahydrofolate reductase; OPRT, orotate phosphoribosyl transferase; TS, thymidylate synthase; TP, thymidine phosphorylase; . The official Human Genome Organization gene nomenclature is used. Common or alternative names for each gene can be found at http://pharmacogenetics.wustl. edu.

The cytotoxicity of cisplatin is attributed mainly to the induction of DNA intrastrand, interstrand, and DNA–protein crosslinks (Roberts and Thomson, 1979). Such DNA damage is thought to be repaired by the nucleotide excision pathway. Excision repair cross-complementing gene 1 (ERCC1) has a pivotal role in nucleotide excision repair and may promote the development of resistance to cisplatin (Dabholkar ; Bramson and Panasci, 1993). Excision repair cross-complementing gene 1 is also associated with responses to cisplatin- and 5-FU-based chemotherapy in GC. Metzger reported that high ERCC1 expression in GC may be associated with poor survival and no response to cisplatin. Other studies, however, have failed to confirm such correlations of the gene expressions of TS (Choi ; Kwon ), DPD (Ishikawa ; Miyamoto ), and ERCC1 (Napieralski ) with the outcomes of chemotherapy. Further larger studies are thus required to confirm or refute previous claims. This study was designed to further delineate the clinical implications of biomarkers and to identify potential predictors of the response to chemotherapy and survival in patients with GC. The epidermal growth factor receptor (EGFR) tyrosine kinase family and the vascular endothelial growth factor (VEGF) superfamily are also well-known mediators of tumour cell proliferation and tumour-related angiogenesis, which can influence tumour biology and survival (Carmeliet and Jain, 2000; Gamboa-Dominguez ; Juttner ). We tested the hypothesis that the clinical outcomes of chemotherapy (response rate, time to progression, and overall survival) in patients with advanced GC are related to the pretreatment intratumour mRNA levels of enzymes participating in critical pathways of drug resistance, such as 5-FU and folate metabolism (TS, DPD, TP, OPRT, DHFR, MTHFR), DNA repair (ERCC1), the EGFR signalling pathway (EGFR), and tumour-related angiogenesis (VEGF-A). We also compared the prognostic implications of these biomarkers with those of well-recognised prognostic factors (Chau ; Lee ).

PATIENTS AND METHODS

Patient eligibility

Patients with a diagnosis of histologically proven advanced GC were eligible for the study. Inclusion criteria were as follows: unresectable, locally-advanced, or metastatic disease; no prior chemotherapy and no prior adjuvant/neoadjuvant chemotherapy; specimens of primary gastric adenocarcinomas were obtained before the start of chemotherapy by surgical resection or biopsy at the National Cancer Center Hospital (Tokyo, Japan) or National Hospital Organization Shikoku Cancer Center (Matsuyama, Japan); first-line chemotherapy was received at either of the hospitals; radiographically measurable disease; and written informed consent. The tissue samples were collected retrospectively from patients who met these criteria. Measurable disease was assessed by computed tomography. Response was evaluated according to the standard UICC guidelines as complete response (CR), partial response (PR), no change (NC), or progressive disease (PD) (Hayward ). Tumour response and survival times as of December 2006 were confirmed in all patients. The response rate was calculated as the ratio of (CR+PR)/(CR+PR+NC+PD). Written informed consent was obtained before treatment and evaluation of tumour samples. This study was approved by the institutional review boards of both hospitals.

Clinical data

The following clinical data were included in analyses: performance status, liver and peritoneal metastases, and laboratory data at the start of chemotherapy, including leukocyte and lymphocyte counts and the serum levels of alkaline phosphatase (ALP), lactate dehydrogenase (LDH), albumin, C-reactive protein, and tumour markers (CEA, CA19-9).

Chemotherapy

The following first-line chemotherapy regimens were administered to the patients in our study: S-1 monotherapy (N=69), cisplatin plus S-1 (N=14), cisplatin plus irinotecan (N=29), 5-FU monotherapy (N=23), and other regimens (5-FU plus methotrexate, N=2; paclitaxel, N=2; uracil/ftorafur, N=1). For S-1 monotherapy, patients received S-1 (40 mg m−2 twice daily) on days 1–28 of a 42-day cycle. Treatment with cisplatin plus S-1 consisted of cisplatin (60 mg m−2) on day 8 and S-1 (40 mg m−2 twice daily) on days 1–21 of a 35-day cycle. Treatment with cisplatin plus irinotecan consisted of cisplatin (80 mg m−2) on day 1 and irinotecan (70 mg m−2) on days 1 and 15 of a 28-day cycle. For 5-FU monotherapy, patients received 5-FU (800 mg m−2 day−1) as a continuous infusion on days 1–5 of a 28-day cycle.

Laboratory methods

Ten-micrometre-thick sections obtained from identified areas with the highest tumour-cell concentration were mounted on uncoated glass slides. For histologic diagnosis, representative sections were stained with haematoxylin and eosin by standard methods. Before microdissection, sections were stained with nuclear fast red (American MasterTech Scientific, Lodi, CA, USA). The sections of interest were selectively isolated by laser-captured microdissection (PALM Microsystem, Leica, Wetzlar, Germany), according to standard procedures (Bonner ). The dissected particles of tissue were transferred to a reaction tube containing 400 μl of RNA lysis buffer. The samples were homogenised and heated at 92°C for 30 min. Fifty microlitres of 2 M sodium acetate was added at pH 4.0, followed by 600 μl of freshly prepared phenol/chloroform/isoamyl alcohol (250 : 50 : 1). The tubes were placed on ice for 15 min and then centrifuged at 13 000 r.p.m. for 8 min in a chilled (8°C) centrifuge. The upper aqueous phase was carefully removed. Glycogen (10 μl) and 300–400 μl of isopropanol were added. The tubes were chilled at −20°C for 30–45 min to precipitate the RNA. The samples were washed in 500 μl of 75% ethanol and air-dried for 15 min. The pellet was resuspended in 50 μl of 5 mM Tris. Finally, cDNA was prepared as described by Lord and colleagues (Lord ). Quantification of nine genes of interest and an internal reference gene (β-actin) was performed with a fluorescence-based real-time detection method (ABI PRISM 7900 Sequence Detection System, TaqMan®, Perkin-Elmer (PE) Applied Biosystem, Foster City, CA, USA) using the standard curve method. The PCR reaction mixture consisted of 1200 nM of each primer, 200 nM of probe, 0.4 U of AmpliTaq gold polymerase, 200 nM each of dATP, dCTP, dGTP, and dTTP, 3.5 mM of MgCl2, and 1 × Taqman buffer A containing a reference dye. The final volume of the reaction mixture was 20 μl (all reagents from PE Applied Biosystems, Foster City, CA, USA). Cycling conditions were 50°C for 2 min and 95°C for 10 min, followed by 46 cycles of 95°C for 15 s and 60°C for 1 min. The primers and probes used are listed in Table 1. Gene expression values (relative mRNA levels) are expressed as ratios (differences between Ct values) between the gene of interest and an internal reference gene (β-actin).
Table 1

Primer and probe sequences for quantitative RT–PCR

Gene Forward primer (5′-3′) Reverse primer (5′-3′) Taqman® probe (5′-3′)
TS GCCTCGGTGTGCCTTTCA CCCGTGATGTGCGCAAT TCGCCAGCTACGCCCTGCTCA
DPD AGGACGCAAGGAGGGTTTG GTCCGCCGAGTCCTTACTGA CAGTGCCTACAGTCTCGAGTCTGCCAGTG
TP CCTGCGGACGGAATCCT GCTGTGATGAGTGGCAGGCT CAGCCAGAGATGTGACAGCCACCGT
OPRT TAGTGTTTTGGAAACTGTTGAGGTT CTTGCCTCCCTGCTCTCTGT TGGCATCAGTGACCTTCAAGCCCTCCT
DHFR GTCCTCCCGCTGCTGTCA GCCGATGCCCATGTTCTG TTCGCTAAACTGCATCGTCGCTGTGTC
MTHFR CGGGTTAATTACCACCTTGTCAA GCATTCGGCTGCAGTTCA TGAAGGGTGAAAACATCACCAATGCCC
ERCC1 GGGAATTTGGCGACGTAATTC GCGGAGGCTGAGGAACAG CACAGGTGCTCTGGCCCAGCACATA
EGFR TGCGTCTCTTGCCGGAAT GGCTCACCCTCCAGAAGGTT ACGCATTCCCTGCCTCGGCTG
VEGF-A AGTGGTCCCAGGCTGCAC TCCATGAACTTCACCACTTCGT TGATTCTGCCCTCCTCCTTCTGCCAT
β-Actin GAGCGCGGCTACAGCTT TCCTTAATGTCACGCACGATTT ACCACCACGGCCGAGCGG

Abbreviations: DHFR=dihydrofolate reductase; DPD=dihydropyrimidine dehydrogenase; EGFR=epidermal growth factor receptor; ERCC1=excision repair cross-complementing gene 1; MTHFR=methylenetetrahydrofolate reductase; OPRT=orotate phosphoribosyl transferase; TP=thymidine phosphorylase; TS=thymidylate synthase; VEGF-A=vascular endothelial growth factor-A.

For each gene, we establish a usable Ct range for the data and document the precision of the measurements within the usable range. For maximum accuracy, we demonstrate that the slopes of the plots of ΔCt vs Log pg. RNA for target genes and the housekeeping gene (actin) demonstrate parallelism. Each replicate Ct data point is the average of Ct values obtained in three PCR reactions. To compare the results of two different TaqMan plates with each other, the same standardised samples are analysed on every plate.

Statistical analysis

We examined the objective tumour response to chemotherapy, time to progression, and overall survival. Time to progression and overall survival were calculated as the period from the start of first-line chemotherapy until disease progression or death from any cause, respectively. If patients were lost to follow-up, data were censored at the date of the last evaluation. To assess associations of gene expression levels with tumour response, time to progression, and overall survival, the expression levels of each gene were categorised into low and high values at optimal cutoff points. The maximal χ2 method (Halpern, 1982; Miller and Siegmund, 1982; Lausen and Schumacher, 1992) was used to determine which gene expression (optimal cutoff point) best segregated patients into poor- and good-outcome subgroups (in terms of likelihood of response and survival). To determine the corrected P-values on the basis of the maximal χ2 analysis, 2000 bootstrap-like simulations were used in univariate analyses to estimate the distribution of the maximal χ2 statistics under the null hypothesis of no association. The clinical laboratory data were treated as continuous variables. The estimates of hazard ratios (HRs) with 95% CIs, on the basis of a Cox proportional hazards model, were used to provide quantitative summaries of the gene expression data. All reported P-values are two-sided, and the level of statistical significance was set at P<0.010. Variables for multivariate analysis were selected by the Stepwise Method, using a significance level of <0.010 for entering into or remaining in the model. All analyses were performed using the statistical software package R, version 2.4.1, and the SAS statistical package, version 9.1.3 (SAS Institute Inc., Cary, NC, USA).

RESULTS

A total of 140 patients were eligible for the study. Eighty-six patients (61%) were recruited at the National Cancer Center Hospital and 54 patients (39%) at the National Hospital Organization Shikoku Cancer Center. Chemotherapy began in July 1997 in the first patient and in June 2004 in the last patient. The demographic characteristics of the patients are shown in Table 2. There were 108 (77%) men and 32 (23%) women with a median age of 65 years. At the time of analysis, 131 (94%) patients had died and nine (6%) patients were alive.
Table 2

Patient characteristics

  Patients
Characteristic No. %
All patients140 
Sex   
 Male10877
 Female3223
   
Age (years)   
 Median65 
 Range18–87 
   
ECOG performance status   
 07050
 16244
 286
   
Metastatic site   
 Lymph nodes8762
 Peritoneum4331
 Liver4331
 Lung86
 Other96
   
Histological type   
 Intestinal6043
 Diffuse8057
   
First-line chemotherapy regimen  (Response ratea (95% CI))
 S-16934.8 (23.7–47.2)
 Cisplatin+S-11435.7 (12.8–64.9)
 Cisplatin+irinotecan2944.8 (26.5–64.3)
 5-FU234.3 (0.1–22.0)
 5-FU+methotrexate20
 Paclitaxel250.0 (1.3–98.7)
 Uracil/ftorafur (UFT®)10

Abbreviation: ECOG=Eastern Cooperative Oncology Group.

Response rate was calculated as the ratio of (CR+PR)/(CR+PR+NC+PD).

The chemotherapy regimens received by the patients and the response rates are also listed in Table 2. Many patients received S-1 monotherapy or cisplatin-based regimens as first-line treatment. The response rates with first-line chemotherapies in our study were comparable to those reported previously (Sakata ; Boku ; Ohtsu ; Ajani ).

Gene expression levels of selected biomarkers, clinical data, and overall survival in all patients

Gene expression levels of selected biomarkers were quantifiable in 88.6–99.3% of the 140 tumours (Table 3). Gene expression cutoff values in terms of overall survival were defined by using the maximal χ2 method, and corrected P-values were calculated for each single gene. On univariate analyses, overall survival in the study group as a whole correlated with the expression levels of ERCC1, DPD, EGFR, and TS, the serum levels of LDH and ALP, and performance status (Table 4). Using these significant mRNA factors on univariate analyses, we performed combined analysis. Patients with low mRNA expressions of ERCC1, DPD, TS, and high expression of EGFR (N=30) had significantly longer overall survival than did the other patients (N=106) (median overall survival, 22.0 vs 11.2 months; P<0.001, log-rank test; Figure 2). Multivariate analysis with a Cox proportional hazards model demonstrated that high ERCC1 expression (HR: 2.38 (1.55–3.67)), high DPD expression (HR: 2.04 (1.37–3.02)), low EGFR expression (HR: 0.34 (0.20–0.56)), and an elevated serum ALP level (HR: 1.00 (1.001–1.002)) were significant predictors of poor survival (Table 4).
Table 3

Gene expression levels of analysed biomarkers in all 140 patients

   mRNA expression levels relative to β-actin ( × 10−3)
Gene No. of patients (%) Median Range
TS139 (99.3)2.810.84–16.05
DPD134 (95.7)0.850.07–13.54
TP139 (99.3)5.960.82–32.01
OPRT138 (98.6)0.990.28–4.55
DHFR124 (88.6)2.940.42–8.69
MTHFR136 (97.1)1.240.25–8.20
ERCC1139 (99.3)1.030.22–6.22
EGFR126 (90.0)1.240.12–57.78
VEGF-A137 (97.9)4.891.07–30.23

Abbreviations: DHFR=dihydrofolate reductase; DPD=dihydropyrimidine dehydrogenase; EGFR=epidermal growth factor receptor; ERCC1=excision repair cross-complementing gene 1; MTHFR=methylenetetrahydrofolate reductase; OPRT=orotate phosphoribosyl transferase; TP=thymidine phosphorylase; TS=thymidylate synthase; VEGF-A=vascular endothelial growth factor-A.

Table 4

Univariate analysis and Cox regression multivariate analysis of overall survival in all patients included in this study: correlation with mRNA expression levels and clinical data

     Univariate analysis
Multivariate analysis
Factora Cut point No. of patients Median (months) Hazard ratio (95% CI) P Hazard ratio (95% CI) P
LDHContinuous<0.001  
 Variable  1.00 (1.000–1.001)   
ALPContinuous<0.001< 0.001
 Variable  1.00 (1.001–1.002) 1.00 (1.001–1.002) 
ERCC1⩽1.42 × 10−310314.310.0021< 0.001
 >1.42 × 10−3369.82.12 (1.41–3.18) 2.38 (1.55–3.67) 
DPD⩽1.18 × 10−39314.510.0031< 0.001
 >1.18 × 10−34410.21.95 (1.34–2.83) 2.04 (1.37–3.02) 
PSContinuous0.004  
 Variable  1.55 (1.15–2.08)   
EGFR⩽0.33 × 10−3218.210.0051< 0.001
 >0.33 × 10−311813.60.42 (0.26–0.69) 0.34 (0.20–0.56) 
TS⩽2.61 × 10−36216.010.010  
 >2.61 × 10−37711.21.64 (1.15–2.34)   

Abbreviations: ALP=alkaline phosphatase; DPD=dihydropyrimidine dehydrogenase; EGFR=epidermal growth factor receptor; ERCC1=excision repair cross-complementing gene 1; LDH=lactate dehydrogenase; PS=performance status; TS=thymidylate synthase.

Note: ‘Cutoff point’ for mRNA expression level was determined by the maximal χ2 method.

Factors with P-values of <0.010 in univariate analyses are listed in ascending order of P-values. The stepwise method was used to select factors for multivariate analysis.

Figure 2

Kaplan–Meier plot of overall survival for all patients according to ERCC1, DPD, TS, and EGFR mRNA expression levels.

Gene expression levels of selected biomarkers, tumour response, and time to progression in patients treated with S-1 monotherapy or cisplatin-based regimens as first-line chemotherapy

To better understand the relation between mRNA levels of selected biomarkers and treatment outcomes with each chemotherapy regimen, we performed subgroup analyses. Gene expression cutoff values that best segregated patients into poor- and good-response subgroups were defined by using the maximal χ2 method. In patients given first-line S-1 monotherapy, low MTHFR (low: 44.9% vs high: 6.3%, P=0.006) gene expression alone correlated with a better response (Table 5). Expressions of the other eight genes did not correlate with response. In patients treated with first-line cisplatin-based regimens (combined with S-1 or irinotecan), low ERCC1 (low: 55.6% vs high: 18.8%, P=0.008) gene expression alone correlated with a better response (Table 5). Expressions of the other eight genes did not show any correlation with response.
Table 5

Gene expression levels and tumour response in patients with advanced gastric cancer according to first-line chemotherapy

  S-1 monotherapy (N=69)
Cisplatin-based regimensa (N=43)
Factor Total no. of patients Cut point ( × 10−3) RR (%) in low group RR (%) in high group P Total no. of patients Cut point ( × 10−3) RR (%) in low group RR (%) in high group P
TS663.6745.2 (19/42)20.8 (5/24)0.044433.4350.0 (15/30)23.1 (3/13)0.103
DPD650.8325.9 (7/27)44.7 (17/38)0.119420.8428.0 (7/25)58.8 (10/17)0.041
TP665.3725.9 (7/27)43.6 (17/39)0.121437.8132.1 (9/28)60.0 (9/15)0.049
OPRT650.610 (0/6)39.0 (23/59)0.059430.9457.1 (12/21)27.3 (6/22)0.029
DHFR591.6457.1 (4/7)28.8 (15/52)0.105392.3231.6 (6/19)45.0 (9/20)0.323
MTHFR651.8244.9 (22/49)6.3 (1/16) 0.006 431.1552.2 (12/23)30.0 (6/20)0.152
ERCC1650.9250.0 (14/28)24.3 (9/37)0.033431.1855.6 (15/27)18.8 (3/16) 0.008
EGFR661.2045.7 (16/35)25.8 (8/31)0.094431.3951.7 (15/29)21.4 (3/14)0.049
VEGF-A652.7054.5 (6/11)31.5 (17/54)0.104436.5253.8 (14/26)23.5 (4/17)0.022

Abbreviations: DHFR=dihydrofolate reductase; DPD=dihydropyrimidine dehydrogenase; EGFR=epidermal growth factor receptor; ERCC1=excision repair cross-complementing gene 1; MTHFR=methylenetetrahydrofolate reductase; OPRT=orotate phosphoribosyl transferase; RR=response rate; TP=thymidine phosphorylase; TS=thymidylate synthase; VEGF-A=vascular endothelial growth factor-A.

Note: ‘Cutoff point’ was determined by the maximal χ2 method. The level of significance was set at P<0.010. Significant values are shown in bold.

Cisplatin-based regimens: cisplatin+S-1 and cisplatin+irinotecan.

Gene expression cutoff values and the corrected P-values for time to progression analyses were determined by the same methods as those used in the analyses of overall survival. In patients given first-line S-1 monotherapy, expression levels of DHFR and EGFR were significantly associated with the time to progression (Table 6). When 2.89 × 10−3 was used as the cutoff value for DHFR, the median time to progression was 6.1 months in the low-expression group and 4.0 months in the high-expression group (corrected log-rank P=0.003, HR: 2.43 (95% CI: 1.37–4.29)). DHFR gene expression correlated with TS expression, with a Spearman's rank correlation coefficient of 0.456 (P<0.001). When a cutoff value of 0.33 × 10−3 was used for EGFR, the median time to progression was significantly longer in the high EGFR expression group (low: 2.8 months vs high: 5.3 months, P=0.007, HR: 0.31 (0.16–0.62)). The association between expression levels of TS, DPD, TP, OPRT, MTHFR, ERCC1, and VEGF-A and the time to progression did not show significant results (Table 6).
Table 6

Univariate analyses of time to progression in patients with advanced gastric cancer treated with S-1 monotherapy or cisplatin-based regimens as first-line chemotherapy: correlation with mRNA expression levels

  S-1 monotherapy (N=69)
Cisplatin-based regimensa (N=43)
Factor Cut point ( × 10−3) No. of patients Median (months) Hazard ratio (95% CI) P Cut point ( × 10−3) No. of patients Median (months) Hazard ratio (95% CI) P
TS⩽5.27604.510.131⩽3.36295.410.140
 >5.2794.22.11 (0.97–4.55) >3.36143.91.68 (0.87–3.24) 
DPD⩽1.57514.910.080⩽1.55374.61 0.008
 >1.57174.01.90 (1.06–3.43) >1.5551.24.87 (1.75–13.53) 
TP⩽5.58314.010.207⩽8.31304.210.222
 >5.58385.10.72 (0.44–1.18) >8.31136.20.62 (0.32–1.22) 
OPRT⩽1.44484.210.223⩽0.92206.210.036
 >1.44204.21.37 (0.79–2.36) >0.92233.91.93 (1.02–3.66) 
DHFR⩽2.89296.110.003⩽5.82354.510.215
 >2.89334.02.43 (1.37–4.29) >5.82414.60.41 (0.12–1.39) 
MTHFR⩽1.04202.910.158⩽0.94102.91 0.001
 >1.04485.10.59 (0.34–1.01) >0.94335.90.17 (0.07–0.42) 
ERCC1⩽1.30494.210.370⩽1.12244.210.318
 >1.30194.40.72 (0.41–1.27) >1.12195.90.75 (0.41–1.39) 
EGFR⩽0.33122.81 0.007 ⩽0.81163.910.158
 >0.33575.30.31 (0.16–0.62) >0.81275.20.53 (0.28–1.03) 
VEGF-A⩽2.4571.910.193⩽7.86343.810.130
 >2.45614.40.46 (0.21–1.02) >7.8697.20.43 (0.20–0.93) 

Abbreviations: DHFR=dihydrofolate reductase; DPD=dihydropyrimidine dehydrogenase; EGFR=epidermal growth factor receptor; ERCC1=excision repair cross-complementing gene 1; MTHFR=methylenetetrahydrofolate reductase; OPRT=orotate phosphoribosyl transferase; TP=thymidine phosphorylase; TS=thymidylate synthase; VEGF-A=vascular endothelial growth factor-A.

Note: ‘Cutoff point’ was determined by the maximal χ2 method. The level of significance was set at P<0.010. Significant values are shown in bold.

Cisplatin-based regimens: cisplatin+S-1 and cisplatin+irinotecan.

In patients who received cisplatin-based regimens as first-line chemotherapy, expression levels of DPD and MTHFR correlated with the time to progression (Table 6). At a DPD cutoff value of 1.55 × 10−3, the median time to progression was 4.6 months in the low DPD expression group as compared with only 1.2 months in the high DPD expression group (P=0.008, HR: 4.87 (1.75–13.53)). At a MTHFR cutoff value of 0.94 × 10−3, the median time to progression was significantly longer in the high-expression group (low: 2.9 months vs high: 5.9 months, P=0.007, HR: 0.17 (0.07–0.42)). The association between expression levels of the other seven genes and time to progression did not show significant results (Table 6).

DISCUSSION

In this study, we analysed mRNA expression levels of nine genes involved in 5-FU and folate metabolism, DNA repair, and angiogenesis in primary tumours from 140 patients with advanced GC. Our goal was to determine whether such expression levels are related to treatment outcomes such as survival and response. We found that high DPD expression, high ERCC1 expression, and low EGFR expression in GC specimens were significant predictors of poor survival in advanced GC. Recently, several studies have reported that patients’ genetic profiles are related to the outcomes of cancer therapy (van ‘t Veer ; Ruzzo ). In colorectal cancer, since many studies have examined molecular predictors of outcomes during the past decade, TS, DPD, and TP were newly included in ‘ASCO 2006 tumour marker guidelines in gastrointestinal cancer’ (Locker ). Because sufficient supporting evidence is lacking, however, the guidelines recommend that these biomarkers should not yet be used clinically to predict prognosis or treatment response. Further studies are therefore needed to more clearly define the relation between mRNA expression levels and clinical outcomes. Our study showed that gene expression levels of DPD (related to the pharmacokinetics of fluoropyrimidines) and ERCC1 (related to the pharmacodynamics of cisplatin) had significant impacts on the overall survival of patients with advanced GC. This finding is consistent with the results of previous investigations (Metzger ; Terashima ; Napieralski ). S-1, an oral DPD inhibitory fluoropyrimidine, is a novel antitumour drug combining tegafur (FT: a prodrug of 5-FU), gimeracil (CDHP: 5-chloro-2,4 dihydropyridine), and oteracil (Oxo: potassium oxonate) (Shirasaka , 1996). CDHP inhibits DPD activity and therefore prevents fluoropyrimidine degradation (Shirasaka ). Oxo is a gastrointestinal tract adverse effect modulator (Shirasaka ). In Japan, S-1 as monotherapy or combined with cisplatin is a standard regimen for advanced GC (Sakata ; Ajani ). Boku reported the result of a randomised controlled trial showing that S-1 is a promising standard regimen as compared with 5-FU, and Narahara showed that S-1 plus cisplatin is superior to S-1 alone. A multinational phase III study comparing S-1 plus cisplatin with 5-FU plus cisplatin (control regimen) is now underway. In the future, S-1 combined with cisplatin may become a standard regimen not only in Japan but also worldwide. In our study, 129 patients (92%) received S-1- or 5-FU-based regimens, and 73 patients (52%) received cisplatin-based regimens as first-line or subsequent chemotherapy. Our results strongly suggest that tumours with high DPD and ERCC1 gene expression are unlikely to respond to current standard therapy, resulting in inadequate tumour control and poor outcomes. Patients with such tumours would require newly developed drugs and combined treatment modalities tailored to their specific needs. Patients with low DHFR expression had a higher response rate and a longer time to progression while receiving S-1 monotherapy (Tables 5 and 6). DHFR is a key enzyme of folate metabolism. DHFR converts intracellular inactive dihydrofolate back to active tetrahydrofolate, which is reused in deoxythymidine-5′-monophosphate synthesis (Figure 1) and is crucial for 5-FU antitumour activity. Sowers reported that E2F transcription factors may participate in the regulation of both TS and DHFR expression. We showed that a Spearman's correlation coefficient for TS/DHFR was 0.456 (P<0.001). Backus reported that low TS expression in vitro correlated with increased sensitivity to 5-FU. Several clinical studies have found that patients with low TS gene expression in primary GC correlate with a better tumour response and longer survival after 5-FU or S-1 treatment (Lenz ; Ichikawa ). The results of these studies suggest that low DHFR expression is associated with better clinical outcomes in patients given S-1 monotherapy, consistent with the results of our study. DHFR might thus be a candidate predictive biomarker of the response to S-1 treatment. Our data suggested that low DHFR expression may be an important determinant of tumour-cell sensitivity to S-1. In patients who received S-1 monotherapy, low MTHFR gene expression also correlated with a better tumour response (Table 5). Some studies have reported that the MTHFR 677T mutation, linked to the reduced activity of MTHFR, increases chemosensitivity to 5-FU (Cohen ; Sohn ), whereas others have had inconsistent results (Etienne ; Ruzzo ). Although MTHFR and DHFR are key enzymes in folate metabolism, the role of MTHFR gene expression in the antitumour activity of 5-FU remains controversial. In patients given cisplatin-based regimens as first-line chemotherapy, low ERCC1 mRNA expression alone correlated with a better tumour response, confirming a previously reported association (Metzger ). With respect to EGFR gene expression, evidence supporting a correlation between mRNA expression levels and survival or time to progression in GC is scant. Vallbohmer reported that high mRNA expression of EGFR was associated with a better response as well as longer progression-free and overall survival in patients with colorectal cancer who received irinotecan therapy, which is partially in accord with our findings. In contrast, Gamboa-Dominguez found that strong membranous staining of EGFR on immunohistochemical analysis correlated with poor survival. The clinical implications of EGFR gene expression thus remain controversial. In conclusion, our study provides evidence that high DPD, high ERCC1, and low EGFR gene expression levels in GC specimens and an elevated serum ALP level are risk factors for poor survival in patients with advanced GC. To the best of our knowledge, this is the first study showing that mRNA expression levels of molecular markers in primary GC had as much impact on survival outcomes as did well-recognised prognostic factors. The results of our analysis will hopefully provide a more rational basis for clinical decision-making, risk stratification of patients, and selection of management strategies as well as suggest benchmarks for future randomised controlled trials. Our relatively small sample size precludes drawing any firm conclusions, and candidate biomarkers must be validated in prospective studies. To confirm and extend the results of this exploratory study, larger studies are being planned in Japan.
  41 in total

1.  Antitumor activity of 1 M tegafur-0.4 M 5-chloro-2,4-dihydroxypyridine-1 M potassium oxonate (S-1) against human colon carcinoma orthotopically implanted into nude rats.

Authors:  T Shirasaka; K Nakano; T Takechi; H Satake; J Uchida; A Fujioka; H Saito; H Okabe; K Oyama; S Takeda; N Unemi; M Fukushima
Journal:  Cancer Res       Date:  1996-06-01       Impact factor: 12.701

2.  Late phase II study of novel oral fluoropyrimidine anticancer drug S-1 (1 M tegafur-0.4 M gimestat-1 M otastat potassium) in advanced gastric cancer patients.

Authors:  Y Sakata; A Ohtsu; N Horikoshi; K Sugimachi; Y Mitachi; T Taguchi
Journal:  Eur J Cancer       Date:  1998-10       Impact factor: 9.162

3.  Laser capture microdissection: molecular analysis of tissue.

Authors:  R F Bonner; M Emmert-Buck; K Cole; T Pohida; R Chuaqui; S Goldstein; L A Liotta
Journal:  Science       Date:  1997-11-21       Impact factor: 47.728

4.  ERCC1 mRNA levels complement thymidylate synthase mRNA levels in predicting response and survival for gastric cancer patients receiving combination cisplatin and fluorouracil chemotherapy.

Authors:  R Metzger; C G Leichman; K D Danenberg; P V Danenberg; H J Lenz; K Hayashi; S Groshen; D Salonga; H Cohen; L Laine; P Crookes; H Silberman; J Baranda; B Konda; L Leichman
Journal:  J Clin Oncol       Date:  1998-01       Impact factor: 44.544

5.  Methylenetetrahydrofolate reductase polymorphism in advanced colorectal cancer: a novel genomic predictor of clinical response to fluoropyrimidine-based chemotherapy.

Authors:  Victor Cohen; Valerie Panet-Raymond; Nelly Sabbaghian; Isabelle Morin; Gerald Batist; Rima Rozen
Journal:  Clin Cancer Res       Date:  2003-05       Impact factor: 12.531

6.  Inhibition by oxonic acid of gastrointestinal toxicity of 5-fluorouracil without loss of its antitumor activity in rats.

Authors:  T Shirasaka; Y Shimamoto; M Fukushima
Journal:  Cancer Res       Date:  1993-09-01       Impact factor: 12.701

7.  Thymidylate synthase mRNA level in adenocarcinoma of the stomach: a predictor for primary tumor response and overall survival.

Authors:  H J Lenz; C G Leichman; K D Danenberg; P V Danenberg; S Groshen; H Cohen; L Laine; P Crookes; H Silberman; J Baranda; Y Garcia; J Li; L Leichman
Journal:  J Clin Oncol       Date:  1996-01       Impact factor: 44.544

8.  mRNA expression levels of E2F transcription factors correlate with dihydrofolate reductase, reduced folate carrier, and thymidylate synthase mRNA expression in osteosarcoma.

Authors:  Rebecca Sowers; Junya Toguchida; Jing Qin; Paul A Meyers; John H Healey; Andrew Huvos; Debabrata Banerjee; Joseph R Bertino; Richard Gorlick
Journal:  Mol Cancer Ther       Date:  2003-06       Impact factor: 6.261

Review 9.  Novel aspects of resistance to drugs targeted to dihydrofolate reductase and thymidylate synthase.

Authors:  Debabrata Banerjee; Philipp Mayer-Kuckuk; Gina Capiaux; Tulin Budak-Alpdogan; Richard Gorlick; Joseph R Bertino
Journal:  Biochim Biophys Acta       Date:  2002-07-18

Review 10.  Cancer pharmacogenetics.

Authors:  S Marsh; H L McLeod
Journal:  Br J Cancer       Date:  2004-01-12       Impact factor: 7.640

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  44 in total

1.  Bax predicts outcome in gastric cancer patients treated with 5-fluorouracil, leucovorin, and oxaliplatin palliative chemotherapy.

Authors:  Seong Hyun Jeong; Jae Ho Han; Jang Hee Kim; Mi Sun Ahn; Yoon Ho Hwang; Hyun Woo Lee; Seok Yun Kang; Joon Seong Park; Jin-Hyuk Choi; Kwang Jae Lee; Seung Soo Sheen; Ho-Yeong Lim
Journal:  Dig Dis Sci       Date:  2010-05-26       Impact factor: 3.199

2.  Molecular targeted therapies in advanced gastric cancer: does tumor histology matter?

Authors:  Hilda Wong; Thomas Yau
Journal:  Therap Adv Gastroenterol       Date:  2013-01       Impact factor: 4.409

Review 3.  How prognostic and predictive biomarkers are transforming our understanding and management of advanced gastric cancer.

Authors:  Christina Kim; Karen Mulder; Jennifer Spratlin
Journal:  Oncologist       Date:  2014-08-20

Review 4.  Anti-HER agents in gastric cancer: from bench to bedside.

Authors:  Lorenzo Fornaro; Maurizio Lucchesi; Chiara Caparello; Enrico Vasile; Sara Caponi; Laura Ginocchi; Gianluca Masi; Alfredo Falcone
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2011-06-07       Impact factor: 46.802

Review 5.  Role of the tumor microenvironment in the pathogenesis of gastric carcinoma.

Authors:  Hye Won Chung; Jong-Baeck Lim
Journal:  World J Gastroenterol       Date:  2014-02-21       Impact factor: 5.742

6.  Proteomics identifies multipotent and low oncogenic risk stem cells of the spleen.

Authors:  Francisco Dieguez-Acuña; Shohta Kodama; Yoshiaki Okubo; Ana Cristina Paz; Steven P Gygi; Denise L Faustman
Journal:  Int J Biochem Cell Biol       Date:  2009-12-18       Impact factor: 5.085

7.  Differential expression and prognostic value of ERCC1 and thymidylate synthase in resected gastric adenocarcinoma.

Authors:  Malcolm H Squires; Sarah B Fisher; Kevin E Fisher; Sameer H Patel; David A Kooby; Bassel F El-Rayes; Charles A Staley; Alton B Farris; Shishir K Maithel
Journal:  Cancer       Date:  2013-05-29       Impact factor: 6.860

8.  Predictive value of excision repair cross-complementation group 1 expression for platinum-based chemotherapy and survival in gastric cancer: a meta-analysis.

Authors:  Anqi Yao; You Wang; Xiaohong Peng; Rong Ye; Qiaoli Wang; Yuexiao Qi; Fuxiang Zhou
Journal:  J Cancer Res Clin Oncol       Date:  2014-07-04       Impact factor: 4.553

9.  Breast cancer resistance protein (BCRP) and excision repair cross complement-1 (ERCC1) expression in esophageal cancers and response to cisplatin and irinotecan based chemotherapy.

Authors:  Anubha Bharthuar; Sana Saif Ur Rehman; Jennifer D Black; Charles Levea; Usha Malhotra; Terry L Mashtare; Renuka Iyer
Journal:  J Gastrointest Oncol       Date:  2014-08

10.  Biomarker analysis in stage III-IV (M0) gastric cancer patients who received curative surgery followed by adjuvant 5-fluorouracil and cisplatin chemotherapy: epidermal growth factor receptor (EGFR) associated with favourable survival.

Authors:  J-S Kim; M-A Kim; T M Kim; S-H Lee; D-W Kim; S-A Im; T-Y Kim; W H Kim; H-K Yang; D S Heo; Y-J Bang; K-U Lee; K-J Choe; N K Kim
Journal:  Br J Cancer       Date:  2009-03-10       Impact factor: 7.640

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