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Keywords:

  • drug resistance gene;
  • single nucleotide polymorphism;
  • gemcitabine;
  • pancreatic cancer;
  • survival

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

BACKGROUND:

The purpose of this study was to identify single nucleotide polymorphisms (SNPs) of multidrug resistance genes that are associated with clinical outcome in patients with potentially resectable pancreatic adenocarcinoma who were treated with preoperative gemcitabine-based chemoradiotherapy at M. D. Anderson Cancer Center.

METHODS:

We selected 8 SNPs of 7 drug resistance genes, including MDR1 (ABCB1), MRP1-5 (ABCC1-5), and BCRP (ABCG2), reported to be important in mediating drug resistance. Genotype was determined by the Taqman method. The associations of genotype with tumor response to therapy and overall survival (OS) were evaluated using log-rank test, Cox regression, and logistic regression models.

RESULTS:

MRP5 A-2G AA genotype showed significant association with OS (log-rank P = .010). The hazard ratio (95% confidence interval) was 1.65 (1.11-2.45) after adjusting for clinical predictors. The MRP2 G40A GG genotype had a weak association with reduced OS (log-rank P = .097). A combined effect of the two genotypes on OS was observed. Patients with none of the adverse genotypes had a median survival time (MST) of 34.0 months, and those with 1-2 deleterious alleles had a significantly lower MST of 20.7 months (log-rank P = .006). MRP2 G40A GG genotype was also significantly associated with poor histological response to chemoradiotherapy (P = .028).

CONCLUSIONS:

These observations suggest a potential role of polymorphic variants of drug resistance genes in predicting therapeutic efficacy and survival of patients with potentially resectable pancreatic cancer. Cancer 2011. © 2010 American Cancer Society.

Pancreatic cancer is one of the most aggressive human cancers with a 5-year survival rate of less than 5%,1 and highly resistant to most therapies. Gemcitabine is the current standard of care for chemotherapy of pancreatic cancer, but its efficacy is limited. Demonstrating the determinant of gemcitabine resistance in pancreatic cancer has great clinical implications.

Drug resistance, a major cause of treatment failure in oncology,2 consists of several processes (eg, increased drug efflux and decreased accumulation of drugs in the cell).3 Efflux transporters of the ATP-binding cassette (ABC) family—such as ABCB1 (multidrug resistance 1, MDR1), the ABCC (multidrug resistance-associated protein, MRP) family, and ABCG2 (breast cancer resistance protein, BCRP)—have been identified as major determinants of chemoresistance in tumor cells.4 Because of their ability to regulate the intracellular concentration and tissue distribution of xenobiotics and their metabolites, ABC transporters are potentially important players in drug response.5

The MDR, MRP, and BCRP family has 11, 13, and 5 (or 6) members, respectively.5 The MDR1 gene product P-glycoprotein is a membrane protein that functions as an ATP-dependent exporter of drugs from cells. Some studies demonstrated a high rate of MDR1 expression in pancreatic cancer tissue and cell lines,6, 7 and other studies reported that MDR1 overexpression is associated with sensitivity to gemcitabine.8, 9 MRP (ABCC) subfamily members differ in substrate specificity, tissue distribution, and cellular localization.10 MRP1, MRP2, and MRP3 transport lipophilic compounds conjugated with glutathione, glucuronate, or sulfate. MRP4 and MRP5 transport nucleotide analogs and cyclic nucleotides. In addition to endogenous compounds, MRPs are involved in exporting a variety of organic anions of xenobiotics and are important in conferring resistance to cytotoxic and antiviral drugs.10 It has been shown that MRP1-MRP5 mRNAs were overexpressed in several pancreatic cancer cell lines.3

Despite many reports of SNPs in the ABC transporter family,10-15 the impact of polymorphisms on pharmacokinetics and pharmacodynamics for gemcitabine remains to be defined. We hypothesized that genetic variation in drug resistance genes is associated with the clinical response and overall prognosis of pancreatic cancer patients treated with gemcitabine. We tested this hypothesis in a relatively homogeneous population of 154 patients with potentially resectable pancreatic cancer who had undergone neoadjuvant gemcitabine-based chemoradiation, with or without cisplatin induction therapy. For this study, we evaluated 8 coding region SNPs with minor allele frequencies >0.10 of the MDR1, MRP1-5, and BCRP genes.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Patient Recruitment and Data Collection

The study involved 154 patients who, at the time of diagnosis, had potentially resectable adenocarcinoma of the pancreas head and had not received any treatment for pancreatic cancer. All patients were enrolled in 1 of 2 phase II clinical trials (ID98-020 or ID01-341) of preoperative, combined, chemoradiation therapy for pancreatic cancer at The University of Texas M. D. Anderson Cancer Center (Houston, TX), conducted sequentially from February 1999 to 2006.16, 17 These 154 patients represented the subset of 176 patients enrolled in these clinical trials who had DNA samples for genotyping. The study was approved by the institutional review board of M. D. Anderson Cancer Center. Patients in the ID98-020 trial (n = 70) had received gemcitabine-based chemoradiotherapy consisting of weekly gemcitabine (400 mg/m2) for 4 weeks and radiation (30 Gy in 10 fractions) for 2 weeks. Patients in the ID01-341 trial (n = 84) had received induction therapy of gemcitabine (750 mg/m2/d) and cisplatin (30 mg/m2/d) every 2 weeks for 4 weeks, followed by weekly gemcitabine (400 mg/m2) for 4 weeks and radiation (30 Gy in 10 fractions) for 2 weeks. After chemoradiation, patients underwent pancreaticoduodenectomy using Whipple procedure.

Clinical information was collected retrospectively from the patients' medical records. Dates of death were obtained and cross-checked using at least one of the following sources: inpatient medical records, the M. D. Anderson tumor registry, and/or the Social Security Death Index (www.deathindexes.com/ssdi.html). OS times were calculated from the date of pathologic diagnosis to the date of death or last follow-up. Data for patients who were alive at the last follow-up evaluation were censored at that time. Serum CA19-9 levels were measured at the time of cancer diagnosis. Tumor size was estimated from measurements made by endoscopic ultrasonography (EUS) or computed tomography (CT) at the time of cancer diagnosis. Tumor differentiation was evaluated in most surgically resected tumors and a few biopsy samples. Tumor response to preoperative chemoradiotherapy was evaluated by CT before and after treatment, and defined according to the Response Evaluation Criteria in Solid Tumors as partial response, stable disease, or progressive disease. The histological effect of preoperative chemoradiotherapy was evaluated in resected tumors according to previously published criteria18; ie, tumors with >90% viable cancer cells were defined as treatment effect grade I, 51%-90% viable cells as grade IIA, 10%-50% viable cells as grade IIB, and <10% viable cells as grade III. Neither postsurgical treatment nor treatment received after tumor recurrence was considered in this study because of their minimal effect on overall survival.

DNA Extraction and Genotyping

We selected 8 SNPs of the MDR1, MRP1-5, and BCRP genes according to the following criteria: 1) minor allele frequency of the SNP was greater than 10% among Caucasians, 2) coding SNPs including nonsynonymous or synonymous SNPs, and 3) SNPs that have been associated with cancer risk or clinical outcome in prior studies. Table 1 summarizes the genes, chromosome locations, nucleotide substitutions, amino acid changes, reference SNP identification numbers, and minor allele frequencies of the 8 SNPs evaluated in this study.

Table 1. SNPs Evaluated
GeneChromosomeSNPFunctionRS No.Minor Allele Frequency
     Observeda/Reportedb
  • SNP indicates single-nucleotide polymorphism; RS No., reference SNP identification number.

  • a

    The data observed in current study.

  • b

    The reported minor allele frequency (Caucasian) was from SNP500 cancer database.

MDR17q21.12aEx27 -55T>CI1145I10456420.49/0.47
MRP116p13.11aEx28 36G>AS1219S22393300.28/0.24
MRP210q24.2cEx10 40G>AV417I22736970.25/0.23
  Ex28 -16C>TI1324I37400660.35/0.35
MRP317q21.33bEx26 -13C>TH1314H22776240.24/0.17
MRP413q32.1aEx8 40A>GR317R22744060.39/0.37
MRP53q27.1bEx10 -2A>GQ382Q76369100.35/0.39
BCRP4q22.1bEx5 43C>AQ141K22311420.12/0.10

Whole blood was collected from patients at the time of clinical trial enrollment, and DNA was extracted from peripheral-blood lymphocytes of 127 patients and from paraffin sections of normal adjacent tissues of 27 patients with resected tumors (20 from the ID98-020 trial), using a DNA isolation kit from Qiagen Inc., (Valencia, CA). Polymorphisms were detected using the TaqMan genotyping assays provided by Applied Biosystems (Foster City, CA). In duplicate analysis, discrepancies were seen in less than 1% of total samples. Discordant results were resolved by further genotyping analysis.

Statistical Methods

The distribution of genotypes was tested for Hardy-Weinberg equilibrium using the goodness-of-fit chi-square test. The association of clinical factors and genotypes with OS was evaluated using Kaplan-Meier method and the log-rank test. The median follow-up time was computed with censored observations only. Median survival time (MST) was calculated using data from all patients. The heterozygous and homozygous genotypes were combined in these analyses if the frequency of the homozygous mutant was low or if the homozygous and heterozygous genotypes had the same effect on survival or tumor response. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression models. Significant clinicopathologic factors on OS by log-rank test were included in the multivariate model when appropriate. Chi-square test and logistic regression were used to evaluate the association of genotypes with tumor response. All statistical testing was conducted with SPSS software, version 17.0 (SPSS, Chicago, IL). Statistical significance was defined as P <.05 and borderline significance as P <.10.

We estimated the false-positive report probability (FPRP) for the observed, statistically significant associations using the methods described by Wacholder et al.19 The prior probability employed was .25 and the FPRP value for noteworthiness was set at .2.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Patients' Characteristics and Survival Analysis

The patients' characteristics and clinical features of their tumors are summarized in Table 2. The median age of the 154 patients in this study was 62.8 years (range, 38-80 years). There were 111 deaths (72%) among 154 cases, and the MST was 21.7 months (95% CI, 17.5 to 25.9). The median follow-up time was 63.1 months for the living patients at the end of July 2008. After preoperative chemoradiotherapy, 116 patients underwent grossly completed surgical resection of the primary tumor. However, 7 resections among them turned out to be microscopically margin positive (R1 resection). The remaining 38 patients could not undergo resection because of disease progression. Diabetes, tumor size larger than 2.0 cm, a higher serum level of CA19-9 at diagnosis, progressive disease on tumor response, no resection, poor differentiation, lymph node metastasis, and ID01-341 trial were factors significantly associated with reduced OS (Table 2).

Table 2. Patient Characteristics and Overall Survival (n=154)
VariableNo. of PatientsNo. of DeathsMST (Months)Log- Rank PHRa (95% CI)P
  • MST, median survival time; PR, partial response; SD, stable disease; PD, progressive disease; GEM, gemcitabine; RT, radiation therapy.

  • a

    Crude hazard ratio.

  • b

    Percentage of viable cells by histological evaluation of resected tumor.

Age, y   .098  
 ≤50171618.5 reference 
 51-60442736.0 0.52 (0.28-0.97).039
 61-70604121.5 0.64 (0.36-1.15).134
 >70332721.2 0.89 (0.48-1.65).701
Sex   .369  
 Male967020.9 reference 
 Female584124.5 0.84 (0.57-1.23).370
Race   .704  
 White1339723.9 reference 
 Hispanic10718.2 0.95 (0.44-2.06).902
 African American7433.6 0.75 (0.27-2.03).565
 Other4310.7 1.79 (0.56-5.70).322
Diabetes status   .017  
 Negative1097427.6 reference 
 Positive453718.2 1.61 (1.08-2.40).019
Tumor size (cm)    .010 
 ≤2654034.0 reference 
 >2897120.7 1.66 (1.13-2.45).011
CA19-9 (units/mL)   .001  
 ≤47402152.8 reference 
 48-500785822.5 1.83 (1.11-3.01).018
 501-1,000141218.4 3.03 (1.48-6.22).002
 >1,000222015.3 2.90 (1.57-5.36).001
Tumor response   <.001  
 PR/SD1268527.8 reference 
 PD272510.3 4.35 (2.74-6.91)<.001
Tumor resection   <.001  
 Yes1167334.0 reference 
 No383810.5 9.28 (5.78-14.9)<.001
Tumor grade   .017  
 Well-to-moderate885733.6 reference 
 Poor322519.8 1.76 (1.10-2.82).019
Lymph node metastasis   .009  
 Negative613351.3 reference 
 Positive554026.4 1.85 (1.16-2.94).010
Histological effectb   .259  
 Grade I/IIA (>50%)704327.9 reference 
 Grade IIB/III (≤50%)433037.1 1.31 (0.82-2.09).261
Clinical Protocol   .026  
 ID98-020 (GEM/RT)704928.1 reference 
 ID01-341 (GEM/Cisplatin/RT)846218.4 1.54 (1.05-2.26).028

Genotype Frequency and Association With OS

Eight SNPs of interest were successfully amplified in 95.5%-100% of the samples. Genotype frequencies of all 8 SNPs were found to be in Hardy-Weinberg equilibrium (chi-square = 0.0003-3.78; P >.05). No significant racial difference in genotype frequency was observed (data not shown).

The genotype frequencies, MSTs, and hazard ratios (95% CI) are shown in Table 3. Two SNPs, MRP5 A-2G and MRP2 G40A, showed a significant or borderline significant association with OS in log-rank test (P = .010 and.097, respectively). The HRs (95% CI) of MRP5 A-2G and MRP2 G40A were 1.65 (1.11-2.45) and 1.55 (1.02-2.36). The MSTs of MRP5 A-2G AG/GG and AA genotype were 28.1 and 18.4 months, respectively. In addition, a combined genotype effect of MRP5 A-2G and MRP2 G40A was observed. As the number of at-risk alleles increased, the OS decreased: patients carrying 0 (n = 39) or 1-2 (n = 7112) at-risk alleles had median OS times of 34.0 and 20.7 months (P = .006, Table 3), as well as 5-year survival rates of 41.3% and 20.0% in the Kaplan-Meier plot (Fig. 1).

thumbnail image

Figure 1. Kaplan-Meier plot of overall survival by combined genotype effect of MRP2 40GG and MRP5 -2AA. The numbers of 0-2 indicate the number of deleterious alleles associated with reduced survival. P value was from log-rank test.

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Table 3. Overall Survival by Genotype
GenotypeNo. of PatientsNo. of DeathsMST±SE (Months)Log- Rank PHRa (95% CI)P
  • MST, median survival time; SE, standard error; HR, Hazard ratio

  • a

    HR was adjusted for history of diabetes, tumor size, serum level of CA19-9, tumor response, and tumor resection.

  • b

    MRP2 40GG and MRP5 -2AA.

MDR1 T-55C
 CC453223.8±5.3   
 CT644621.5±3.3   
 TT433121.7±3.4.982  
 CC vs TT/CT   .8691.24 (0.81-1.90).317
MRP1 G36A
 GG816421.5±2.4   
 AG603823.9±9.3   
 AA13921.4±6.1.247  
 AA/AG vs GG   .1361.03 (0.69-1.53).890
MRP2 G40A
 GG866721.2±2.6   
 AG553431.0±7.1   
 AA10717.5±4.8.172  
 AG/AA vs GG   .0971.55 (1.02-2.36).040
MRP2 C-16T
 CC634423.9±4.2   
 CT694920.7±4.0   
 TT191522.5±2.2.962  
 CC vs TT/CT   .7851.13 (0.75-1.69).557
MRP3 C-13T
 CC896721.4±2.3   
 CT473228.7±7.0   
 TT13823.9±10.9.307  
 CT/TT vs CC   .1291.10 (0.72-1.67).664
MRP4 A40G
 GG543426.4±8.1   
 AG765821.7±2.4   
 AA221714.6±2.6.172  
 GG/AG vs AA   .1581.29 (0.75-2.23).357
MRP5 A-2G
 AA685418.4±3.0   
 AG623831.0±4.2   
 GG221720.7±7.0.017  
 AG/GG vs AA   .0101.65 (1.11-2.45).013
BCRP C43A
 CC1168323.9±3.3   
 AC271921.2±0.8   
 AA4320.4±10.0.960  
 AA/AC vs CC   .9601.05 (0.65-1.72).834
No. of deleterious allelesb   .006  
 0392134.0±12.0   
 1-21128720.7±1.5 2.18 (1.32-3.60).002

Multivariate Analysis on OS

We performed multivariate analysis including both genotypes of MRP2 G40A and MRP5 A-2G by adjusting for significant clinical predictors for OS. In this analysis, MRP5 -2AA genotype remained as an independent predictor for reduced OS (HR = 1.56, 95% CI, 1.05-2.34, P = .029, Table 4). Because tumor resection was the strongest predictor for OS (HR = 7.56, 95% CI, 4.19-13.6, P = <.001), and 75% of the patients had tumor resection in this study, we further analyzed the genotype effect on survival among 116 patients with resected tumor only (Table 4). Both genotypes of MRP2 G40A and MRP5 A-2G were significant independent predictors for OS, with HRs (95% CI) of 1.99 (1.15-3.45, P = .015) and 1.88 (1.16-3.06, P = .011), respectively. The FPRP for these findings was .078 and .053, respectively, indicating noteworthiness.

Table 4. Multivariate Cox Regression Analysis of Genotypes on OS
CovariatePatients
All (n=154)Resected (n=116)
HRa (95% CI)PHRb (95% CI)P
  • a

    HR was adjusted for history of diabetes, tumor size, serum level of CA19-9, tumor response, tumor resection, and genotype.

  • b

    HR was adjusted for history of diabetes, tumor size, serum level of CA19-9, tumor response, and genotype.

MRP2 G40A
 AG/AAreference reference 
 GG1.48 (0.97-2.27).0681.99 (1.15-3.45).015
MRP5 A-2G
 AG/GGreference reference 
 AA1.56 (1.05-2.34).0291.88 (1.16-3.06).011

Genotype Effects on Response to Therapy

None of the genotypes was associated with tumor response in radiological evaluation (data not shown). However, the MRP2 G40A GG genotype, which was associated with a reduced survival, had a significant association with poor response to therapy in histological evaluation of the resected tumor (P = .028, Table 5). Thirty (47.6%) of the MRP2 40 GG carriers, compared with 13 (27.1%) of the AG/AA carriers, had a grade I or IIA response; ie, >50% of tumor cells were viable in the resected tumor. The odds ratio (95% CI) was 2.45 (1.09-5.48).

Table 5. Association Between Genotypes and Histological Effect of Chemoradiotherapy
VariableHistological EffectP (X2)ORa (95% CI)P
Grade IIB/IIIGrade I/IIA
No.(%)No.(%)
  • a

    Crude odds ratio.

MRP2 G40A    .028  
 AG/AA35(72.9)13(27.1) reference 
 GG33(52.4)30(47.6) 2.45 (1.09-5.48).030

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

In this study, we evaluated the association between 8 SNPs of drug resistance genes and clinical outcomes of patients with potentially resectable pancreatic adenocarcinoma. We demonstrated that the genotypes of MRP5 A-2G and MRP2 G40A had a significant association with OS. The MRP2 G40A GG genotype carriers also had a poorer histological response to preoperative gemcitabine-based chemoradiotherapy. These observations support a role of drug resistance-associated genes in cellular sensitivity to gemcitabine-based therapy and, as the result, survival of pancreatic cancer patients.

It has been shown that nucleotide analogs and cyclic nucleotides are substrates for MRP5 and MRP4,20 and, particularly, gemcitabine was reported to be a typical substrate for the MRP5 efflux pump.21 One study showed a significant association between expression level of MRP5 and gemcitabine sensitivity in a non-small cell lung cancer cell line.22 Another study demonstrated that HEK293 cells overexpressing the human MRP5 protein are twice as resistant to gemcitabine, compared with vector control cells.21 Because this study population received preoperative chemoradiotherapy, we did not think it appropriate to examine the gene expression profiles in resected tumors. However, a previous study has shown that MRP5 mRNA level was significantly higher in pancreatic carcinoma tissue versus normal pancreatic tissue,3 suggesting that overexpression of MRP5 could contribute to drug resistance in pancreatic cancer. Although many SNPs of the MRP5 gene have been reported,23 the functional significance of the vast majority of these SNPs is still unclear.24MRP5 A-2G (Q382Q) is a synonymous SNP that does not produce altered coding sequences or amino acid substitution. However, a previous study has demonstrated that a synonymous SNP in the MDR1 gene results in a protein product with altered drug and inhibitor interactions.25 Thus, the functional consequence of this SNP warrants investigation. It is also possible that this SNP is in linkage disequilibrium with other functional SNPs of either the MDR1gene or other important genes in this chromosome location. Further investigations, including haplotype analysis, will help to determine how this SNP is functionally associated with gemcitabine sensitivity and survival in pancreatic cancer patients.

MRP2 is reported to be involved in exporting not only bilirubin and certain drug glucuronides, but also anticancer drugs.4 This includes cisplatin, doxorubicin, etoposide, and methotrexate.26, 27 We observed that MRP2 G40A genotype has a relatively weak association with survival and tumor response to gemcitabine therapy in the entire study population. However, this association diminished when the 84 patients receiving cisplatin induction therapy were analyzed separately (data not shown). Gemcitabine is not thought to be a typical substrate of MRP2.28 Therefore, MRP2 might play an indirect role in sensitivity to gemcitabine and cisplatin combination therapy.

Although MDR1 T-55C and BCRP C43A were reported to be functional SNPs that change their protein functions,25, 29 none of these SNPs—nor the MRP1, MRP3, or MRP4 gene SNPs examined in this study—had any association with overall survival or tumor response to therapy. This suggests that these genes are probably not the most important determinants in cellular response to gemcitabine-based chemoradiotherapy. However, it is also possible that the limited number of SNPs selected for this study missed the most important functional variants of these genes. Further investigation is required to illustrate how these genes may affect the clinical outcome of pancreatic cancer.

In the same study population, we have previously shown significant associations of SNPs of DNA homolog recombination repair genes,30 DNA damage response genes,31 DNA mismatch repair genes,32 and gemcitabine metabolic genes33 with clinical outcome of pancreatic cancer. The current study has identified another important genetic factor, one that is associated with drug sensitivity and patient survival. Our results need to be confirmed in other study populations. The ultimate goal of this research is to generate a genetic profile that can be used to predict response to preoperative gemcitabine-based therapy as well as predict prognosis in patients with potentially resectable pancreatic cancer. If the genetic markers are established and validated, they may help with choice of therapy and patient stratification in future individualized cancer treatment.

CONFLICT OF INTEREST DISCLOSURES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Supported by National Institutes of Health (NIH) RO1 grant CA098380 (to D.L.), SPORE P20 grant CA101936 (to J.L.A.), NIH Cancer Center Core grant CA16672, and a research grant from the Lockton Research Funds (to D.L.).

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES
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