SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Improved methods for predicting chemoresponsiveness involving the identification of polymorphic markers is highly desirable, considering narrow therapeutic index and frequent resistance to anti-cancer regimens. The genome-wide screening of chemosensitive single nucleotide polymorphisms (SNPs) was undertaken in association with in vitro chemosensitivity assays in 104 colorectal cancer patients for the initial screening step. Allele frequency, linkage disequilibrium, potential function, and Hardy–Weinberg equilibrium of the candidate SNPs were then determined for the identifying step. Finally, clinical association analysis in the other 260 evaluable patients or cell viability assays of transfected RKO cells was used to verify candidate SNPs for the validation step. In total, 12 SNPs to six regimens were initially chosen during the screening and identifying steps. In patients receiving fluoropyrimidine-based adjuvant chemotherapy, the substitution alleles of GPC5 rs553717 (AA) correlated significantly with tumor recurrence and shorter disease-free survival (P = 0.019 and 0.023, respectively). Interestingly, RKO cells expressing mutant GPC5 showed enhanced cell death in response to 5-FU in cytotoxicity assays. Patients that were homozygous for the reference alleles SSTR4 rs2567608 (AA) and EPHA7 rs2278107 (TT) showed lower disease control rates in response to irinotecan and oxaliplatin regimens, respectively, than those with substitution alleles (P = 0.022 and 0.014, respectively). Thus, we identified chemosensitive SNP markers using a novel three step process of genome-wide analysis consisting of in vitro screening, identification, and validation. The candidate chemosensitive SNP markers identified in our study, including those identified in vitro, can now be further verified in a large cohort study.

(Cancer Sci 2010; 101: 1007–1013)

Colorectal cancer is one of the four most commonly diagnosed cancers and is responsible for over 10% of cancer-related deaths in most developed countries.(1,2) Up to 50% of patients who receive curative operations experience recurrence and 20% of all patients present with metastatic disease at diagnosis.(3) Fluoropyrimidine-based chemotherapy has become an adjunct to surgery to reduce recurrence in patients with stage III and high-risk stage II colorectal cancer.(4) Systemic chemotherapy of metastatic colorectal cancers has been shown to prolong survival and improve quality of life. Several clinical trials have shown that both oxaliplatin and irinotecan can be successfully combined with 5-fluorouracil and leucovorin (FL) as a first-line treatment for patients with metastatic colorectal carcinoma, and that this regimen leads to high response rates and effectively improves overall survival.(4) Approximately 37 clinical trials are currently underway to evaluate the therapeutic efficacy of histone deacetylase inhibitors in hematological and solid malignancies with few end-point outcomes to date.(5)

Considering the narrow therapeutic index for many anti-cancer regimens, improving the ability to predict the response to a particular treatment is highly important to the clinician. Several commercial and preclinical in vitro drug sensitivity tests are available.(6) However, all of the in vitro assays have limitations, including reproducibility, tumor cell heterogeneity, and few clinical correlation outcomes, such that at present, none of the tests are broadly accepted. Thus, it is important to find molecular or genetic determinants of treatment outcomes, or predictive markers, to facilitate the identification of patients most likely to benefit from given treatments.(7,8) The identification of polymorphic markers that can predict responses to chemotherapy might enable physicians to efficiently select patients for various regimens.

The identification of surrogate single nucleotide polymorphism (SNP) markers that can predict responses to chemotherapy could enable the efficient selection of patients for various regimens. Genome-wide association studies in clinical populations are theoretically capable of identifying markers that are capable of influencing drug responses.(9) However, such studies are limited by sample size, the availability of relevant populations and the expense of genotyping.(10) One particular study used SNP chip assays of 176 HapMap cell lines to identify representative SNPs that contribute to cisplatin-induced cytotoxicity through the modulation of expression of specific genes, although these SNPs remain to be clinically validated.(11)

In the current study, we used a three-step process to select chemosensitive SNP markers for applicable regimens in colorectal cancer. Our primary aim was to discover surrogate SNP markers of chemotherapy response, thereby establishing a way to increase the likelihood that individual patients carrying specific markers would benefit from a given treatment.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Study design and patients.  We carried out a three-step process consisting of initial screening, identification, and validation of SNP markers using clinical association analyses or biological utility assessments (Fig. 1). For the initial screening, 104 patients with sporadic colorectal cancer were recruited in 2007 at the Asan Medical Center (Seoul, Korea) for genome-wide SNP screening according to drug response using in vitro chemosensitivity assay (Table 1). Initial screening was followed by an identification step according to the order in which SNPs were selected that were located in the linkage disequilibrium block of Japanese populations on the HapMap dataset (http://www.hapmap.org) and WGAViewer.(12) This step also identified SNPs that had minor allele frequencies of greater than 5% in Japanese and Han Chinese populations, and showed no departure from the Hardy–Weinberg equilibrium (DHW; > 0.01) (Fig. 2). In addition, non-synonymous and haplotype-tagged SNPs were preferentially selected. For DHW assessment and clinical association analysis, another cohort of 260 evaluable patients who had received chemotherapy, and 330 healthy controls, were also included for the genotyping of selected SNPs, using their genomic DNA. The healthy controls were recruited from our Health Evaluation Center, came from the general Korean population and confirmed that they had no family history of cancer by personal recall. All patients provided written informed consent, and the study protocol was approved by the Institutional Review Board for Human Genetic and Genomic Research (Seoul, Korea), in accordance with the Declaration of Helsinki.

image

Figure 1.  Schematic diagram of the three-step process of initial screening, identification, and validation of single nucleotide polymorphism (SNP) markers. Biological utility assessment by the cell viability assay using transfected RKO cells. CRC, colorectal cancer; DHW, departure from Hardy–Weinberg equilibrium; HDRA, histoculture drug response assay; LD, linkage disequilibrium; MAF, minor allele frequency.

Download figure to PowerPoint

Table 1.   Demographic and biological features of patients with colorectal cancer in the initial screening and clinical association analysis for chemosensitive single nucleotide polymorphism markers
Clinicopathological featuresNo. of patients (missing)P-value*
Initial screeningClinical association
  1. *Comparison of initial screening and clinical association by Pearson’s χ2-test or Student’s t-test. †Cancer staging according to: American Joint Committee on Cancer. AJCC Cancer Staging Manual, 6th edn. New York, NY, USA: Springer, 2001. ‡Lymphovascular invasion and p53 expression, showing significant difference between the two groups, were not associated with recurrence and survival in the adjuvant chemotherapy (P < 0.069–0.869), and response rate and time-to-progression in the metastatic chemotherapy (P < 0.099–0.926). §Microsatellite stability (MSS) and microsatellite instability at low frequency (MSI-L) indicates tumors with no or one unstable marker. Microsatellite instability at high frequency (MSI-H) indicates tumors with two or more unstable markers. ¶Stained cells divided into two grades: negative at ≤10% and positive at >10% cells with nuclear staining. NA, not assessed; MD, moderately differentiated; muc, mucinous; PD, poorly differentiated; WD, well differentiated.

Male/female59/45156/1040.519
Age, mean ± SD, years56 ± 1156 ± 100.674
Stage†, I/II/III/IV9/42/44/90/126/100/340.921
Tumor characteristics
 Location, right/left/rectum32/29/4378/80/1020.893
 Growth, expanding/infiltrative87/17229/310.26
 Differentiation, WD + MD/PD + muc92/12231/291
 Lymphovascular invasion, no/yes75/29155/1050.03‡
 MSS and MSI-L/MSI-H§89/15236/240.148
 KRAS codons 12 and 13 mutation, no/yesNA128/48(84)NA
 p53 expression, ≤10%/>10%¶51/5395/163 (2)0.05‡
image

Figure 2.  Linkage disequilibrium (LD) harboring 12 candidate chemosensitive single nucleotide polymorphisms (SNPs) to the six regimens (marked as horizontal red bars). The red square represents regions of the highest degree of LD (D′ = 1). The LD blocks in the Japanese populations were used from the HapMap dataset (http://www.hapmap.org) and WGAViewer.12 These SNPs were further selected with the following criteria, in order: minor allele frequencies of greater than 5%, no departure from Hardy–Weinberg equilibrium (> 0.01), and non-synonymous and haplotype-tagged SNPs.

Download figure to PowerPoint

In vitro chemosensitivity assay.  The chemosensitivity of tumor tissue from the initial cohort of 104 patients was assessed using the histoculture drug response assay (HDRA) and the following four established regimens and two histone deacetylase inhibitors: FL; capecitabine; FL and irinotecan (FOLFIRI); FL and oxaliplatin (FOLFOX); suberoylanilide hydroxamic acid (Merck Research Laboratories, Boston, MA, USA), and PXD101 (CuraGen, Branford, CT, USA).(13) HDRA uses MTT as a quantitative end-point to assess total tumor cell viability.(14) The inhibition rate (IR) cut-off value for a positive response was previously determined as ≥30%, similar to the RECIST criteria.(15)

Affymetrix genome-wide human SNP array.  SNP mapping for the initial screening was done using genomic DNA from subjects who had been assessed by HDRA, according to the manufacturer’s protocol (http://www.affymetrix.com/), using the Affymetrix Genome-Wide Human SNP Nsp/Sty Assay Kit and SNP Array 5.0 (Affymetrix, Santa Clara, CA, USA). The SNP Nsp/Sty Array 5.0 was scanned by Affymetrix GeneChip Operating Software (version 1.4) using an Affymetrix GeneChip Scanner 3000. Signal intensity data was initially analyzed by the dynamic model algorithm. Genotypes were then determined using the Affymetrix Genotyping Console software (version 2.1) based on the BRLMM-P algorithm. We used an ANOVA test to identify SNPs associated with quantitative HDRA drug sensitivity. We used a liberal P-value (<0.001) for the initial screening of candidate regions due to the relatively small sample size. The raw data have been deposited in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/projects/geo/) under the accession number GSE16718.

Genotyping assay.  The 12 chemosensitive SNPs were genotyped by pyrosequencing for 260 patients and 330 healthy controls. Briefly, DNA was extracted from white blood cells recovered from whole blood using the Wizard Purification Kit (Promega, Madison, WI, USA). The PCR protocol and sequencing primers were designed using Assay Design Software (version 1.0.6; Biotage, Uppsala, Sweden) (Table S1). PCR optimization was carried out using an ABI 2700 thermocycler (Applied Biosystems, Foster City, CA, USA), then the samples were prepared on a Vacuum Prep Workstation (Biotage) according to standard protocols. Amplified PCR products were purified using streptavidin–Sepharose HP beads (Amersham Biosciences, Uppsala, Sweden), denatured, then sequenced according to the manufacturer’s recommendations.

Chemotherapy and evaluation.  Eligibility criteria included histologically-verified colorectal adenocarcinoma, an Eastern Cooperative Oncology Group performance status of 0 or 1, and an age of 75 years or less. A total of 223 patients underwent a postoperative adjuvant fluoropyrimidine-based chemotherapy. Of the patients presenting with metastases, including 25 inoperable patients and 29 patients with systemic recurrence after curative operation, 43 and 36 patients (25 patients with crossover treatment) received either FL or capecitabine with irinotecan (FOLFIRI or XELIRI), and either FL or capecitabine with oxaliplatin (FOLFOX or XELOX), respectively. Patients who underwent curative operations or metastatic chemotherapy received follow-up care every 6 months or 6–8 weeks, respectively, for a mean follow-up time of 40 months (range, 4–108 months). Tumor response was assessed using RECIST criteria with response and disease control rates calculated according to intent-to-treat analysis.(15) Adverse events were evaluated based on National Cancer Institute (Bethesda, MD, USA) Common Toxicity Criteria (version 3.0).

Cell viability assay using transfected cells. GPC5 cDNA (KRIBB, Daejoen, Korea) was amplified by PCR then subcloned into the myc-tagged expression vector pcDNA3. A mutant form of GPC5 (GPC5 A155V) was generated by substitution of amino acid using a site-directed mutagenesis kit (Intron Biotechnology, Seongnam, Korea). Transient transfection was carried out using Lipofectamine 2000, according to the manufacturer’s protocol (Invitrogen, Carlsbad, CA, USA). Stable GPC5-expressing RKO cells were generated by G418 (Invitrogen) selection after transient transfection. The stable expression of GPC5 was confirmed by Western blot using an anti-myc antibody (Santa Cruz Biotechnology, Santa Cruz, CA, USA). Cell death was determined using an annexin V staining kit (BD Biosciences, San Diego, CA, USA) or a cell cytotoxicity assay kit (CCK-8; Dojindo Molecular Technologies, Rockville, MD, USA) to measure phosphatidylserine exposure on the cell membrane, according to the manufacturer’s instructions.

Detection of microsatellite instability, KRAS codon 12–13 mutations and p53 expression.  The microsatellite instability status of tumors was determined according to the Bethesda panel (BAT25, BAT26, D5S346, D2S123, and D17S250) using an ABI PRISM 310 DNA Sequencer and GeneScan 3.1 software (Applied Biosystems), according to the manufacturer’s instructions. KRAS codon 12 and 13 mutations were detected by PCR-RFLP analysis as previously described.(16) These assays included two rounds of PCR using different primers designed to introduce MvaI and BglI (Takara, Kyoto, Japan) restriction sites for KRAS codons 12 and 13, respectively, in the wild-type alleles at the end of each PCR. Immunohistochemical staining was carried out according to the labeled streptavidin–biotin method with a Dako LSAB kit (Dako, Carpinteria, CA, USA), using monoclonal antibodies against p53 (DO-7; Dako, Glostrup, Denmark).

Statistical analysis.  An Altman’s nomogram, assuming putative chemosensitivity ranges between 25% and 75%, was used to determine the sample size to obtain the 80% power to detect chemosensitive SNPs for the initial screening. Similarly, the patients’ number for the validation step was determined on the basis of reported chemosensitivity ranges between 13% and 87% for the metastatic chemotherapy.(4,17) Allele frequency and Hardy–Weinberg probability were determined using GENEPOP software (http://genepop.curtin.edu.au). Genotype and allele frequencies were compared in terms of recurrence, disease control response, biological features and case–control associations by cross-table analysis using Fisher’s exact test. Potential variables were verified by multivariate analysis using binary logistic regression. Survival rates were compared using the Kaplan–Meier method with a log–rank test, and survival factors were verified using Cox’s regression model. Statistical significance was defined as a P-value <0.05, and all calculations were done using SPSS software (version 14; SPSS, Chicago, IL, USA).

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Initial SNP screening according to in vitro chemosensitivity.  In tumor samples from 104 colorectal cancer patients, the IR in response to six different chemotherapy regimens were between 49% and 83.7% (Fig. 3). The IRs for the six regimens examined correlated significantly with the respective patients (≤ 0.038–0.0001). The average genotyping call rate among the individuals was 98.7% on a microarray. Of 443 913 SNPs, 12 974 (missing rate >0.1) and 86 891 (minor allele frequency <0.01) were filtered out, leaving 344 048 SNPs for subsequent statistical analysis. Initial screening identified 766 SNPs that were highly associated with in vitro chemosensitivity to the six regimens (P < 0.001). Then we chose 12 SNPs from the identification step, based on the criteria described in the study design section (Table 2). Of the 12 SNPs, one (EPHA7 rs2278106) showed a significant departure from the DHW in colorectal cancer patients (< 0.01), but not in controls (Table S2).

image

Figure 3.  Comparison of inhibition rates (IR) of colorectal tumor growth (left) and response rates at IR30 (chemosensitivity) (right) between five chemotherapy regimens. IRs of suberoylanilide hydroxamic acid (SAHA) and PXD101 were significantly greater than those of the other four regimens (≤ 0.001–0.0001), whereas significant differences were not found among 5-fluorouracil and leucovorin (FL), FL + irinotecan (FR) and capecitabine (Cape). FX, FL + oxaliplatin.

Download figure to PowerPoint

Table 2.   Twelve candidate single nucleotide polymorphisms (SNPs) related to chemosensitivity to six regimens drawn from the initial screening and identifying steps
RegimensGenesSNP IDAllelesConsequence
ReferenceSubstitution
  1. †Showing significant departure from Hardy–Weinberg equilibrium for the homozygous substitution alleles of colorectal cancer patients (< 0.01). FL, 5-FU/leucovorin; FOLFIRI, FL + irinotecan; FOLFOX, FL + oxaliplatin; SAHA, suberoylanilide hydroxamic acid.

FLGPC5rs553717GAA155V
CapecitabineAJAP1rs242056GAG263R
CapecitabineERCC4rs4309380CTUpstream
FOLFIRITNFRSF11Brs2073618CGN3K
FOLFOXSULT1C2rs17036104TGS255A
FOLFOXSULT1C4rs7580171CTUpstream
FOLFOXEPHA7rs2278106GAR278C
FOLFOXEPHA7rs2278107TCI138V
FL, FOLFIRI, FOLFOXSSTR4rs2567608AGF321S
SAHAOR5AC2rs4518168GAM200I
SAHAOR5H1rs6775533TCUpstream
PXD101DPYDrs1801265CTR29C

Identification of an SNP associated with recurrence in patients receiving adjuvant chemotherapy.  The mean number of adjuvant chemotherapy cycles was 6.7 (range, 2–12 cycles) in 223 patients with stage II and III colorectal cancers (Table 3). Tumor recurrence was more frequent in patients with advanced stage tumors (< 0.0001), infiltrating tumors (P = 0.002), and left colon and rectal cancers (P = 0.011). Among these recurrence-prone parameters, advanced stage tumors were closely correlated with the substitution allele of SSTR4 rs2567608 (= 0.014). In contrast, the substitution allele of TNFRSF11B rs2073618 was significantly associated with p53 expression in tumor (P = 0.027), whereas the substitution allele of EPHA7 rs2278106 was correlated with KRAS mutations in codons 12 and 13 (P = 0.043). For GPC5 rs553717, the recurrence rate was more than two times greater in patients with homozygous substitution alleles (AA; 20 patients) than in those with homozygous (GG; 102 patients) and heterozygous (GA; 101 patients) reference alleles (35%vs. 13.3%; P = 0.018). In a multivariate analysis, which included these recurrence-prone biological features, genotypes with homozygous substitution alleles of GPC5 rs553717 correlated significantly with tumor recurrence (P = 0.019). Similarly, disease-free survival periods (mean ± SEM) were significantly shorter in patients with this genotype than in those with homozygous and heterozygous reference alleles (52.8 ± 7.3 months vs. 87.9 ± 2.8 months; P = 0.023) (Fig. 4).

Table 3.   Demography, stage, and outcome of regimens in patients with colorectal cancer receiving adjuvant chemotherapy and metastatic chemotherapy
Regimens†Mean age (range), yearsSex M/FStage‡ II/III/IVResponse§ CR/PR/SD/PDDFS/PFS¶OS
No. of patientsMean ± SEM, months
  1. †Postoperative adjuvant fluoropyrimidine regimen in 223 patients and metastatic chemotherapy using irinotecan or oxaliplatin regimens in 54 patients. No significant difference between irinotecan and oxaliplatin regimens in terms of gender, age, stage, and outcome. ‡Cancer staging according to: American Joint Committee on Cancer. AJCC Cancer Staging Manual, 6th edn. New York, NY, USA: Springer, 2001. §Tumor response was assessed using RECIST criteria.(15)¶Disease-free survival (DFS) for the adjuvant chemotherapy using fluoropyrimidine regimen and progression-free survival (PFS) for the metastatic chemotherapy using irinotecan and oxaliplatin regimens. Objective responses (complete response [CR] + partial response [PR]) and disease control responses (CR + PR + stable disease [SD]): 35% and 63%, respectively, in patients with irinotecan regimen and 36% and 58%, respectively, in patients with oxaliplatin regimen. NA, not available; OS, overall survival; PD, progressive disease.

Fluoropyrimidine57 (28–75)134/89123/100/0NA86.1 ± 2.798.4 ± 2.1
Irinotecan54 (28–74)30/135/11/270/15/12/1612.6 ± 2.732.9 ± 2.8
Oxaliplatin57 (28–74)24/124/11/211/12/8/1510.1 ± 1.431.8 ± 3.1
image

Figure 4.  Overall survival and disease-free survival periods (mean ± SEM) relative to GPC5 rs553717 genotypes in stage II and III colorectal cancer patients treated with fluoropyrimidine-based regimens.

Download figure to PowerPoint

SNPs associated with chemotherapy response in metastatic colorectal cancers.  The mean number of chemotherapy cycles given to patients with metastatic colorectal cancer was 8.9 (range, 3–22 cycles) for 43 patients treated with irinotecan regimens and 7.3 (range, 2–12 cycles) for 36 patients treated with oxaliplatin regimens (Table 3). Among the chemosensitive SNPs to fluoropyrimidine or its combination regimens, specific genotypes of three SNPs (SSTR4 rs2567608, and EPHA7 rs2278107 and rs2278106) were associated concurrently with the disease control responses of patients receiving these regimens (Table 4). However, these genotypes did not differ with respect to adverse events. Similarly, the median progression-free survival (PFS) period was significantly longer in those carrying homozygous and heterozygous substitution alleles of SSTR4 rs2567608 than in those carrying homozygous reference alleles (9 ± 1.1 months vs. 3 ± 0.6 months) based on Cox regression analysis (relative risk, 10.97; 95% confidence interval, 2.926–41.13; < 0.0001). However, these genotypes did not differ with respect to adverse events.

Table 4.   Genotype frequencies of candidate single nucleotide polymorphisms (SNPs) associated with disease control response in patients with colorectal cancer treated with oxaliplatin and irinotecan regimens
GenesSNP IDGenotypesNo. with disease control response†/total patients (%)
Irinotecan‡P-value*Oxaliplatin‡P-value*
  1. *Compared between two different genotypes by Fisher’s exact test. †Including complete response, partial response, and stable disease. ‡Irinotecan regimens: irinotecan + 5-fluorouracil/leucovorin (FOLFIRI) or capecitabine (XELIRI). Oxaliplatin regimens: oxaliplatin + 5-flourouracil/leucovorin (FOLFOX) or capecitabine (XELOX).

EPHA7rs2278106GG21/33 (64)0.55814/28 (50)0.064
GA + AA6/10 (60)7/8 (88)
EPHA7rs2278107TT22/35 (63)0.64214/29 (48)0.014
TC + CC5/8 (63)7/7 (100)
SSTR4rs2567608AA2/8 (25)0.0224/7 (57)0.633
AG + GG25/35 (71)17/29 (59)
TNFRSF11Brs2073618CC14/20 (70)0.2779/14 (64)0.411
CG + GG13/23 (57)12/22 (55)
SULT1C2rs17036104TT24/37 (65)0.39418/31 (58)0.663
TG + GG3/6 (50)3/5 (60)
SULT1C4rs7580171CC24/40 (60)0.23720/34 (59)0.667
CT + TT3/3 (100)1/2 (50)

In vitro cytotoxicity in GPC5-expressing cells.  RKO cells were used to generate stable cell lines that expressed mutant or wild-type GPC5 (Fig. 5a). To determine the chemosensitivity of the SNP GPC5 rs553717, we examined FL-induced apoptosis in RKO colorectal cancer cells expressing wild-type or mutant GPC5 (A155V). FACS and CCK-8 cytotoxicity analysis revealed that RKO cells expressing mutant GPC5 (A155V) showed enhanced cell death in response to FL treatment as compared to wild-type GPC5-expressing cells (Fig. 5b,c). Caspase-3 was activated to a greater extent in cells expressing mutant GPC5, which indicated that mutant, but not wild-type, GPC5 sensitized cells to FL-induced cytotoxicity (Fig. 5d).

image

Figure 5.  GPC5 A155V mutants are more sensitive to 5-fluorouracil and leucovorin (FL)-induced cytotoxicity. (a) Stable expression of GPC5 was confirmed by Western blot using an anti-myc antibody. WT, wild type. (b) RKO cells stably expressing WT or mutant (A155V) GPC5 were incubated in the presence or absence of FL (50 μg/mL 5-FU and 10 μg/mL leucovorin) for 24 h. Apoptotic cell death was determined by flow cytometry after annexin V/propidium iodide (PI) staining. –, FL(−). (c) Cell viability of stable GPC5-expressing cells was determined using a cell cytotoxicity assay kit (CCK8) after FL treatment. –, FL(−). (d) Cell lysates from RKO, WT GPC5-expressing and mutant GPC5-expressing cells were prepared, and caspase-3 activation (active caspase-3) after FL treatment was analyzed by Western blot. Actin was analyzed as a loading control. Data represents the means ± SEM of quadruplicates. *< 0.05 compared to WT cells (Student’s t-test).

Download figure to PowerPoint

Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Our approach was based on a three-step process of screening, identification and validation of SNP markers using clinical association analysis or biological utility assessments. During the initial screening step, specific genotypes on an SNP array were filtered in association with quantitative drug sensitivity data from the HDRA, minimizing pharmacokinetic implications and thereby reducing the amount of genotyping required, without sacrificing power. The HDRA, an MTT-based tissue culture assay, is a valuable tool for assessing total tumor cell viability, and for facilitating the evaluation of chemosensitivity to clinical responses.(18,19) The inherent limitations of the in vitro assay used in the initial screening step can be reduced through clinical or biological validation of the tumor response. There is little guidance on how to distinguish between markers whose DHW is due to chance or to their proximity to an allele that affects a certain phenotype.(20) As a DHW of EPHA7 rs2278106 was exclusively identified in colorectal cancer patients without genotyping error, we cannot rule out natural selection or co-segregation for this allele.

In patients treated with fluoropyrimidine-based adjuvant chemotherapy, the homozygous substitution allele genotype (AA) of GPC5 rs553717 correlated significantly with tumor recurrence and poor disease-free survival. As the clinical response of tumors could not be measured directly in adjuvant settings after curative operation, we used biological validation. Interestingly, in cytotoxic assays of RKO cells, the expression of mutant GPC5 resulted in enhanced apoptosis in response to FL treatment. Previously, it was shown that GPC5 increases cellular proliferation by potentiating the actions of fibroblast growth factor 2, hepatocyte growth factor, and Wnt1A.(21) Colon carcinoma cells overexpress c-myc due to defective Wnt signaling, but only patients whose tumors have an amplified c-myc gene show improved survival in response to 5-FU.(22) In our study, recurrence was associated with advanced stage, infiltrative tumor, and left colon and rectal cancer in patients treated with adjuvant fluoropyrimidine chemotherapy. Our analysis of adjuvant chemotherapy suggests that the use of an additional drug together with fluoropyrimidine might reduce recurrence in a subset of patients with mutant GPC5 rs553717 and these biological risk factors.

In the current study, in vitro responses to the six regimens correlated significantly with each other, which might be related to the specific SNP genotype of SSTR4 rs2567608, associated with chemosensitivity to FL, FOLFIRI, and FOLFOX. Patients that were homozygous for the reference alleles (AA) of SSTR4 rs2567608 showed poor disease control and PFS rates to irinotecan regimens. Somatostatin receptor 4 (SSTR4), which belongs to the G-protein coupled receptor 1 family, is functionally coupled to the activation of both the arachidonate release and the MAPK cascade.(23) Previously, treatment of SW-620 tumors with tolerated doses of AZD6244, a potent ATP-non-competitive inhibitor of MAPK/ERK1/2, along with irinotecan or docetaxel resulted in significantly enhanced anti-tumor efficacy relative to that of either agent alone.(24) In rats, SSTR4 can be sensitized to agonist-induced internalization by mutation of threonine 331 (T331A), adjacent to codon F321S, possibly explaining a close correlation between SSTR4 rs2567608 substitution allele and advanced stages in our study.(25) Mutant alleles of SSTR4 rs2567608 might similarly enhance irinotecan chemosensitivity, leading to an increase in disease control and PFS rates.

In the current study, patients with homozygous reference alleles of EPHA7 rs2278107 (TT) and rs2278106 (GG) showed lower (rs2278107), or a tendency towards lower (rs2278106), disease control rates in response to oxaliplatin regimens as compared to those with substitution alleles. Human EphA7 (HEK11), originally isolated from a human fetal brain library, is widely distributed in human tissues and shows reduced expression in colorectal cancer.(26,27) EphA7 is an essential mediator of ERK1/2 phosphorylation in cells expressing ALL1 fusion proteins.(28) In the current study, the substitution allele of EPHA7 rs2278106 was correlated with KRAS mutation, the upstream regulator of the ERK pathway. Oxaliplatin inactivates ERK, and the suppression of ERK activity by the specific inhibitor PD98059 or expression of a dominant negative plasmid (DN-MEK1) enhances the oxaliplatin-induced expression of PUMA (p53 upregulated modulator of apoptosis) and apoptosis in a p53-independent manner.(29) Thus, oxaliplatin chemosensitivity appears to be decreased in tumors with wild-type EphA7, depending on the level of EphA7-mediated ERK activity. We identified the substitution allele of TNFRSF11B rs2073618 to be correlated with p53 expression in tumor. TNFRSF11B is a member of the tumor necrosis factor receptor superfamily, specifically binding to osteoprotegerin (OPG), and elevated level of serum OPG is detected in both solid and hematologic malignancies.(30) One study using p53 knock-out mice indicated that activation of the p53 pathway downregulates OPG expression released by vascular endothelial cells.(31)

Limited data have been available on the efficacy of histone deacetylase inhibitors as a single agent in metastatic or refractory colorectal cancer.(5) Supplementarily to the current study, we identified an inconsistent viability outcome to PXD101 depending on clonal differences of the RKO cell line, transfected with mutant DPYD rs1801265 (data not shown). As few chemosensitive genotypes carry an exclusive response to the specific regimen, negative findings cannot always indicate these genotypes to be unrelated to chemosensitivity. Additionally, several of the candidate SNPs identified in the current study did not show differential chemosensitivity in clinical association analyses. Although discrepancies can occur due to limited sample numbers in the metastatic setting, pharmacokinetic differences and tumor heterogeneity cannot be excluded as factors that affect in vivo responses.

To our knowledge, this is the first study to identify chemosensitive SNP markers in a three-step process of genome-wide analysis consisting of in vitro screening, identification, and validation of SNPs. Our chemosensitive SNPs, including those identified in vitro, can be used for further verification in large cohorts, and their use as chemosensitivity markers should increase our ability to predict the likelihood that individual patients will respond to specific chemotherapy regimens.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

This research was supported by funding from the Korea Health 21 R&D Project, Ministry of Health, Welfare, and Family Affairs, grant A062254.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References
  8. Supporting Information

Table S1. Sequencing and PCR primers with conditions for pyrosequencing in 12 selected single nucleotide polymorphisms (SNPs) of 11 genes.

Table S2. Allele frequencies and Hardy–Weinberg equilibrium (HWE) in colorectal cancer patients and normal controls.

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

FilenameFormatSizeDescription
CAS_1461_sm_supplementarytables.doc161KSupporting info item

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.