Purpose: Recently, an objective response rate of 12% was reported in a phase II study of cetuximab in patients with epidermal growth factor receptor (EGFR)-expressing metastatic colorectal cancer (mCRC) refractory to fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy (IMC-0144). In this large molecular correlates study, we tested whether K-ras mutation status and polymorphisms in genes involved in the EGFR-signaling pathway were associated with clinical outcome in IMC-0144.

Experimental Design: We analyzed all available tissue samples from 130 of 346 mCRC patients enrolled in the IMC-0144 phase II clinical trial of cetuximab. Genomic DNA was extracted from formalin-fixed paraffin-embedded tumor tissues, and K-ras mutation status and the genotypes were analyzed using PCR-RFLP, direct DNA-sequencing, and 5′-end [γ-33P] ATP–labeled PCR-protocols.

Results: The PFS of patients with cyclooxygenase-2 (COX-2) −765 G>C [C/C; risk ratio (RR), 0.31; 95% confidence interval (95% CI), 0.12-0.84; P = 0.032], COX-2 +8473 T>C (C/C; RR, 0.67; 95% CI, 0.40-1.13; P = 0.003), EGF +61 A>G (G/G; RR, 0.57; 95% CI, 0.34-0.95; P = 0.042), and EGFR +497 G>A (A/G; RR, 0.82; 95% CI, 0.56-1.20; P = 0.017) genotypes was significantly longer compared with those with other genotypes. In addition, patients whose tumors did not have K-ras mutations showed better RR, PFS, and overall survival than patients with K-ras mutations. In multivariable analysis, COX-2 +8473 T>C (adjusted P = 0.013) and EGFR +497 G>A (adjusted P = 0.010) remained significantly associated with progression-free survival, independent of skin rash toxicity, K-ras mutation status, and Eastern Cooperative Group performance status.

Conclusions: Polymorphisms in COX-2 and EGFR may be useful independent molecular markers to predict clinical outcome in patients with mCRC treated with single-agent cetuximab, independent of skin rash toxicity, K-ras mutation, and Eastern Cooperative Oncology Group performance status.

Translational Relevance

Epidermal growth factor (EGF) receptor (EGFR) is overexpressed in up to 77% of colorectal cancer, and anti-EGFR therapy with cetuximab has shown promising results in multiple phase II clinical trials. There are several mechanisms that may lead to aberrant EGFR activation and resistance to anti-EGFR treatment; some of them include EGF overexpression and EGFR amplification, as well as activating K-ras mutations. Here, we show for the first time that germline polymorphisms of genes involved in the EGFR-signaling pathway (cyclooxygenase-2 and EGFR) predict progression-free survival in metastatic colorectal patients treated with single-agent cetuximab, independently of skin rash toxicity and K-ras mutation status. Accordingly, the development of independent molecular markers of prognosis may not only be helpful in identifying patients who are more likely to progress, but they will also be critical in selecting more efficient treatment strategies. Larger, prospective biomarker-embedded clinical trials are needed to confirm and validate our preliminary findings.

Colorectal cancer (CRC) is the second leading lethal malignancy in the United States. In 2008, an estimated 148,810 new cases will be diagnosed and 49,960 people will die from this disease (1). Despite recent additions to our chemotherapeutic armamentarium used to treat metastatic CRC (mCRC; ref. 2, 3), the 5-year overall survival (OS) is relatively poor, with a median survival of 18 to 21 months (4, 5). Targeted agents such as cetuximab, an IgG1 monoclonal antibody to the epidermal growth factor (EGF) receptor (EGFR), have shown relevant clinical activity as monotherapy and combined with chemotherapy in several types of human cancer (6, 7).

EGFR is overexpressed in a variety of malignancies, including up to 77% of CRC, and is associated with tumor progression and poor prognosis (8, 9). Conversely, inhibition of the EGFR pathways with anti-EGFR monoclonal antibodies blocks cell cycle progression and induces apoptosis in numerous in vitro and xenograft models (1012). EGFR-targeted therapy with cetuximab has shown promising results in multiple phase II clinical trials. Cunningham et al. (6), Saltz et al. (7), and Lenz et al. (13) reported response rates of 9.0%, 10.8%, and 11.6%, respectively, for patients with mCRC treated with single-agent cetuximab refractory to fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy. All trials have thus far failed to show a significant correlation between EGFR expression, determined by immunostaining intensity and clinical outcome. In fact, antitumor activity of cetuximab was also noted in patients, whose tumors were negative for EGFR immunostaining (13).

There are several mechanisms that may lead to aberrant EGFR activation and resistance to anti-EGFR treatment; some of them include EGF overexpression and EGFR amplification, as well as activating K-ras and phosphatidylinositol-3-OH kinase mutations. These mutations in turn dysregulate mechanisms modulating tumor-angiogenesis and apoptosis that are normally controlled by multiple homeostatic mechanisms, including signals from the EGFR. As such, downstream EGFR signaling includes molecular targets, such as vascular endothelial growth factor (VEGF), a key regulator of angiogenesis, cyclin D1 (CCND1), an important mitogenic target of EGFR signaling that controls G1-S cell cycle progression, and cyclooxygenase (COX)-2 (1416), the key inducible and rate-limiting enzyme required for prostaglandin biosynthesis. Recent studies have shown that apoptosis (CCND1; ref. 17), tumor-angiogenesis, (VEGF, interleukin-8; ref. 18), and tumor-microenvironment (COX-2; ref. 18), contribute to the development of resistance to anti-EGFR therapy. Furthermore, cetuximab may exert an indirect antitumor activity by recruiting cytotoxic host effector cells such as monocytes and natural-killer cells (19). As such, antibody-dependent cell-mediated cytotoxicity has been implicated as an alternative mechanism to contribute to the antitumor activity of cetuximab, in addition to ligand/receptor blockade.

Given the recent focus on how K-ras mutations affect clinical outcome in mCRC and anti-EGFR therapy with cetuximab (2022), it would be of upmost clinical relevance to identify novel molecular markers, which are independent of K-ras mutational status and skin rash toxicity. Based on this information, we designed a retrospective study within a cohort of a prospectively conducted phase II clinical trial (IMC-0144; ref. 13), to evaluate whether 11 functional significant polymorphisms within 8 genes involved in the EGFR pathway (Table 1), alone or in combination, were associated with clinical outcome in mCRC patients treated with single-agent cetuximab, independent of K-ras mutation status and skin rash toxicity.

Table 1.

Analyzed polymorphisms and their functional significance

PolymorphismLocationMinor allele frequency*FunctionClinical significanceReference
FCGR2A 131 H>R (rs1801274) Exon 4 45-55% (H) H-allele: ↑ binding affinity of FCGR2A to IgG2 and IgG1 Mediates ADCC via FC γ receptor bearing immune effector cells (43) 
    Associated with clinical outcome in CRC  
FCGR3A 158 V>F (rs396991) Exon 5 15-25% (V) V-allele: ↑ binding affinity of FCGR3A to IgG2 and IgG1 Mediates ADCC via FC γ receptor bearing immune effector cells (43) 
   Enhanced effector cell stimulation and ADCC Associated with clinical outcome in CRC  
EGFR +497 G>A (rs11543848) Codon 497 25-35% (A) A-allele: ↓ EGFR ligand binding, growth stimulation, tyrosine kinase activation Associated with rectal cancer tumor recurrence (44) 
EGFR (CA)14-23 (rs45608036) Intron 1 25-30% (≥20) Length of CA microsatellite repeat correlates inversely with EGFR gene transcription Associated with rectal cancer tumor recurrence (44) 
Cyclin D1 +870 A>G (rs17852153) Exon 4 30-50% (A) A-allele: modulates CCND-1 mRNA splicing Apoptosis regulatory protein (17) 
   A-allele: ↑ longer half-life of Cyclin D1 protein EGFR activates CCND1 promoter  
    CCDN1-deregulation modulates efficacy of tyrosine kinase inhibitors  
    Resistance to cetuximab in CRC  
IL-8 -251 T>A (rs4073) 3′-UTR 35-40% (A) A-allele: ↑ IL-8 plasma levels Mediator of VEGF independent angiogenesis (45) 
    Associated with colon cancer tumor recurrence  
VEGF +936 C>T (rs3025039) 3′-UTR 15-20% (T) T-allele: ↓ VEGF plasma levels Activator of angiogenesis (45) 
    Associated with colon cancer tumor recurrence  
COX-2 −765 G>C (rs20417) 3′UTR 15-35% (G) C-allele: ↓ COX-2 promoter activity Downstream effector of the EGFR pathway (18) 
    COX-2 overexpression is associated with poor outcome and resistance to cetuximab in CRC  
COX-2 +8473 T>C (rs5275) Exon 10 35-50% (G) C-allele: ↓ mRNA stability Downstream effector of the EGFR pathway (18) 
   C-allele: protective effect against lung cancer COX-2 overexpression is associated with poor outcome and resistance to cetuximab in CRC  
EGF +61 A>G (rs4444903) 5′-UTR 30-55% (A) A-allele: ↓ EGF serum levels EGFR ligand (46) 
    Associated with esophageal cancer tumor recurrence  
NRP-1 C/T (rs3750733) Exon 2 15-20% (T) Not known VEGFR coreceptor (47) 
    Associated with clinical outcome in ovarian cancer  
PolymorphismLocationMinor allele frequency*FunctionClinical significanceReference
FCGR2A 131 H>R (rs1801274) Exon 4 45-55% (H) H-allele: ↑ binding affinity of FCGR2A to IgG2 and IgG1 Mediates ADCC via FC γ receptor bearing immune effector cells (43) 
    Associated with clinical outcome in CRC  
FCGR3A 158 V>F (rs396991) Exon 5 15-25% (V) V-allele: ↑ binding affinity of FCGR3A to IgG2 and IgG1 Mediates ADCC via FC γ receptor bearing immune effector cells (43) 
   Enhanced effector cell stimulation and ADCC Associated with clinical outcome in CRC  
EGFR +497 G>A (rs11543848) Codon 497 25-35% (A) A-allele: ↓ EGFR ligand binding, growth stimulation, tyrosine kinase activation Associated with rectal cancer tumor recurrence (44) 
EGFR (CA)14-23 (rs45608036) Intron 1 25-30% (≥20) Length of CA microsatellite repeat correlates inversely with EGFR gene transcription Associated with rectal cancer tumor recurrence (44) 
Cyclin D1 +870 A>G (rs17852153) Exon 4 30-50% (A) A-allele: modulates CCND-1 mRNA splicing Apoptosis regulatory protein (17) 
   A-allele: ↑ longer half-life of Cyclin D1 protein EGFR activates CCND1 promoter  
    CCDN1-deregulation modulates efficacy of tyrosine kinase inhibitors  
    Resistance to cetuximab in CRC  
IL-8 -251 T>A (rs4073) 3′-UTR 35-40% (A) A-allele: ↑ IL-8 plasma levels Mediator of VEGF independent angiogenesis (45) 
    Associated with colon cancer tumor recurrence  
VEGF +936 C>T (rs3025039) 3′-UTR 15-20% (T) T-allele: ↓ VEGF plasma levels Activator of angiogenesis (45) 
    Associated with colon cancer tumor recurrence  
COX-2 −765 G>C (rs20417) 3′UTR 15-35% (G) C-allele: ↓ COX-2 promoter activity Downstream effector of the EGFR pathway (18) 
    COX-2 overexpression is associated with poor outcome and resistance to cetuximab in CRC  
COX-2 +8473 T>C (rs5275) Exon 10 35-50% (G) C-allele: ↓ mRNA stability Downstream effector of the EGFR pathway (18) 
   C-allele: protective effect against lung cancer COX-2 overexpression is associated with poor outcome and resistance to cetuximab in CRC  
EGF +61 A>G (rs4444903) 5′-UTR 30-55% (A) A-allele: ↓ EGF serum levels EGFR ligand (46) 
    Associated with esophageal cancer tumor recurrence  
NRP-1 C/T (rs3750733) Exon 2 15-20% (T) Not known VEGFR coreceptor (47) 
    Associated with clinical outcome in ovarian cancer  

Abbreviations: UTR, untranslated region; FCGR, fragment c γ receptor; IL-8, interleukin-8; NRP-1, neuropilin-1; CCDN1, cyclin D1; ADCC, antibody-dependent cell-mediated cytotoxicity.

*

Minor alleles are indicated in brackets.

Patients. One hundred thirty patients with histopathologically confirmed metastatic colorectal carcinoma, who either failed at least two prior chemotherapy regimens or failed adjuvant therapy plus one chemotherapy regimen for metastatic disease, were included in this study. These 130 patients were part of a phase II open-label multicenter study (IMC 0144) of cetuximab, which included a total of 346 patients (13). Due to limited tissue sampling, 130 of 346 (38%) patients were assessable to determine gene polymorphisms. All patients with available tumor tissue samples were included for correlative studies, irrespective of clinical outcome and K-ras mutation status. The present study was conducted retrospectively from prospectively obtained clinical data (IMC 0144) and was done at the University of Southern California/Norris Comprehensive Cancer Center, after approval by the Institutional Review Board of the University of Southern California for Medical Sciences. All patients provided their written informed consent for tissue and blood collection to allow study of molecular correlates.

Clinical evaluation of response criteria. For patients with measurable disease, response was assessed every 6 wk during the course of the study, and criteria were based on modified WHO guidelines (13). An independent response assessment committee that was blinded to the investigator-reported measurements evaluated response to cetuximab retrospectively and assessments were reported in the study. Patients underwent weekly blood counts, and physical examinations were done at every third week. All patients received 2 wk of initial treatment with cetuximab and underwent a formal skin rash evaluation (13). A partial response required at least a 50% reduction in the sum of the bidimensional products of all measurable lesions documented at least 4 wk apart. Treatment was continued in the absence of intolerable toxicity or progressive disease, defined as at least a 25% increase in measurable disease, unequivocal growth of existing nonmeasurable disease, the appearance of one or more new lesions, or reappearance of old lesions (13).

Candidate polymorphisms. The polymorphisms we tested were selected by an EGFR-pathway approach with the goal of selecting genes known to modulate EGF driven angiogenesis (Table 1). We used the following criteria to select genes for study: (a) that the gene be part of a pathway for which there is a credible scientific basis to support its involvement in the EGFR-signaling pathway; (b) that the gene has an established, well-documented genetic polymorphism; (c) that the frequency of the polymorphism is high enough that its effect on clinical outcome will be meaningful; and/or (4) that the polymorphism has some degree of likelihood to alter the function of the gene in a biologically relevant manner.

Genotyping. Formalin-fixed and paraffin-embedded tumor samples were collected and genomic DNA was extracted using the QIAamp kit (Qiagen). The majority of the samples were tested using PCR RFLP technique. Briefly, forward and reverse primers were used for PCR amplification, PCR products were digested by restriction enzymes (New England Biolab), and alleles were separated on 4% NuSieve ethidium bromide stained agarose gel. Forward and reverse primer, restriction enzymes, and annealing temperatures are listed in Table 2. If no matching restriction enzyme could be found, samples were analyzed by direct sequencing. For quality assurance purposes, a total of 20% positive and negative duplicate-controls were matched for each polymorphism and were analyzed by direct DNA-sequencing where applicable. Genotype concordance was ≥99%.

Table 2.

Primer sequences, annealing temperatures, and restriction enzyme

GeneForward-primer (5′-3′)Reverse-primer (5′-3′)EnzymeAnnealing
FCGR2A GGAAAATCCCAGA CAACAGCCTGACTACCTA BstUI 55° 
131 H>R AATTCTCGC TTACGCGGG   
FCGR3A CTGAAGACACATTT TCCAAAAGCCACACTC n.a. 64° 
158 V>F TTACTCCCAAA/C AAAGAC   
EGFR TGCTGTGACCCACT CCAGAAGGTTGCACT Bst-NI 59° 
+497 G>A CTGTCT TGTCC   
EGFR ACCCCAGGGCTC TGAGGGCACAAGAAG n.a. 55° 
(CA)14-23 repeat TATGGGAA CCCCT   
Cyclin D1 GTGAAGTTCATTTCC GGGACATCACCCT ScrFI 61° 
+870 A>G AATCCGC CACTTAC   
IL-8 TTGTTCTAACACCTG GGCAAACCTGAGTC Mfe I 60° 
-251 T>A CCACTCT TCACA   
VEGF AAGGAAGAGGAGACT TAAATGTATGTATGTGGG Nla III 60° 
+936 C>T CTGCGCAGAGC TGGGTGTGTCTACAGG   
COX-2 ATTCTGGCCATCGC CTCCTTGTTTCTTGGAAA Aci I 55° 
−765 G>C CGCTTC GAGACG   
COX-2 GTTTGAAATTTTAA TTTCAAATTATTGTT BclI 53° 
+8473 T>C AGTACTTTTGAT TCATTGC   
EGF CATTTGCAAACAG TGTGACAGAGCAA Alu I 60° 
+61 A>G AGGCTCA GGCAAAG   
Cyclin D1 GTGAAGTTCATTTCC GGGACATCACCCT ScrFI 61° 
+870 A>G AATCCGC CACTTAC   
GeneForward-primer (5′-3′)Reverse-primer (5′-3′)EnzymeAnnealing
FCGR2A GGAAAATCCCAGA CAACAGCCTGACTACCTA BstUI 55° 
131 H>R AATTCTCGC TTACGCGGG   
FCGR3A CTGAAGACACATTT TCCAAAAGCCACACTC n.a. 64° 
158 V>F TTACTCCCAAA/C AAAGAC   
EGFR TGCTGTGACCCACT CCAGAAGGTTGCACT Bst-NI 59° 
+497 G>A CTGTCT TGTCC   
EGFR ACCCCAGGGCTC TGAGGGCACAAGAAG n.a. 55° 
(CA)14-23 repeat TATGGGAA CCCCT   
Cyclin D1 GTGAAGTTCATTTCC GGGACATCACCCT ScrFI 61° 
+870 A>G AATCCGC CACTTAC   
IL-8 TTGTTCTAACACCTG GGCAAACCTGAGTC Mfe I 60° 
-251 T>A CCACTCT TCACA   
VEGF AAGGAAGAGGAGACT TAAATGTATGTATGTGGG Nla III 60° 
+936 C>T CTGCGCAGAGC TGGGTGTGTCTACAGG   
COX-2 ATTCTGGCCATCGC CTCCTTGTTTCTTGGAAA Aci I 55° 
−765 G>C CGCTTC GAGACG   
COX-2 GTTTGAAATTTTAA TTTCAAATTATTGTT BclI 53° 
+8473 T>C AGTACTTTTGAT TCATTGC   
EGF CATTTGCAAACAG TGTGACAGAGCAA Alu I 60° 
+61 A>G AGGCTCA GGCAAAG   
Cyclin D1 GTGAAGTTCATTTCC GGGACATCACCCT ScrFI 61° 
+870 A>G AATCCGC CACTTAC   

The EGFR (CA)n repeat polymorphism was determined by a 5′-end 33p γATP–labeled PCR protocol with a few modifications. In summary, DNA template, deoxynucleotide triphosphates, 5′-end 33p γATP-labeled primer, unlabeled complementary primer, Taq Polymerase (Perkin-Elmer, Inc.), and PCR Buffer were used together in a final PCR. The reaction was carried out and the reaction products were separated on a 6% denaturing polyacrylamid DNA sequencing gel, which then was vacuum blotted for 1 h at 80°C and exposed to an XAR film (Eastman-Kodak Co.) overnight. In addition, the exact number of repeats was confirmed by direct sequencing.

K-ras mutation analysis. Mutational analyses of K-ras were done using available genomic DNAs isolated from tumor specimens. Primers used for K-ras exons 12 to 13, coding for the tyrosine kinase domain, were published previously. The primers used to evaluate exon 12 of K-ras and exon 13 of K-ras were as follows: K-ras forward, 5′-TGA CTG AAT ATA AAC TTG TGG TAG TTG-3′, and K-ras reverse, 5′-TCG TCC ACA AAA TGA TTC TGA A-3′. PCR was done using conditions as previously described (23). PCR fragments were sequenced on an ABI 3100A Capillary Genetic Analyzer (Applied Biosystems) and analyzed in both sense and antisense directions for the presence of heterozygous mutations. DNA sequence analyzes were done by two independent investigators (G.L and W.Z.) using the ABI Sequencing Scanner v1.0 (Applied Biosystems). Appropriate positive and negative controls were included for each of the exons evaluated. Mutational analyses were done without knowledge of clinical outcome, including tumor response.

Statistical analysis. The primary end points of this pharmacogenetic substudy were progression-free survival (PFS), OS, tumor response to cetuximab, and skin rash toxicity. The PFS was calculated from the time of the first date of cetuximab treatment until the first observation of disease progression or death from any cause. If a patient had not progressed or died, PFS was censored at the time of the last follow-up. The OS time was calculated as the period from the first day of cetuximab infusion or until death from any cause, at which the point data were censored.

The association between each polymorphism with OS and PFS was analyzed using Kaplan-Meier plots and the log-rank test. The distributions of polymorphisms across demographic characteristics were examined using Fisher's exact test. The associations of each polymorphism with tumor response and toxicity were summarized using contingency tables and the exact conditional test. Tumor response rate was defined as the total number of partial responses divided by the number of patients whose tumor response was evaluable.

The Benjamini and Hochberg method was used to control the false discovery rate (FDR) of multiple testing (24). In the univariate analysis, an FDR-adjusted P value of <0.15 was used to select polymorphisms as candidates for inclusion in the multivariable model.

With 130 patients, we would have 80% power to detect a minimum hazard ratio around 1.7 across a range of common allele frequencies (0.2-0.5) for both PFS and OS in a dominant model. For a recessive model, a minimum hazard ratio is below 3.6 when the allele frequency is 0.2 and approaches 1.8 when the allele frequency is 0.5. At the time of analysis, 23 patients (17%) were alive. Allelic distribution of all polymorphisms was tested for deviation from Hardy-Weinberg equilibrium. Multivariable analysis was conducted using Cox proportional hazards regression model. The level of significance was set to a P value of <0.05, and P values are given for 2-sided testing. All statistical test were done using the SAS statistical package version 9.1 (SAS Institute, Inc.), and Epilog Plus Version 1.0 (Epicentre Software).

Patients whose tissues samples were available for analysis of molecular correlates (n = 130) had a similar median PFS [1.3 months; 95% confidence interval (CI), 1.3-1.5], OS (6.3 months; 95% CI, 4.3-7.7), and response rate (9.2%; 95% CI, 4.9%-15.6%) compared with the clinical outcome of the patients without tissue samples available from the entire study population of IMC 0144 [n = 216; median PFS, 1.5 mo (95% CI, 1.4-2.6); OS, 6.8 months (95% CI, 5.8-8.1), and response rate of 13.0% (95% CI, 8.8%-18.2%); ref. 13]. There were 121 Caucasian (93%), 1 Hispanic (1%), 3 Asian (2%), 3 African-American (2%), and 2 other (2%) study participants. At the time of analysis, 23 (17%) patients were still alive: the follow-up for those patients ranged from 2.2 to 17.3 months (median follow-up, 12.3 months). Skin rash was observed in 87% (113 of 130) of patients. Forty-four percent (n = 57) had a grade 1, and 43% (n = 56) showed a grade 2 or 3 skin-reaction. Skin rash severity was significantly associated with PFS (P < 0.001, log-rank) and OS (P < 0.001, log-rank). The allelic frequencies observed for all polymorphisms analyzed were within the probability limits of Hardy-Weinberg equilibrium (P > 0.05, exact test for Hardy-Weinberg equilibrium). Detailed clinicopathologic and demographic characteristics are shown in Table 3.

Table 3.

Baseline patient characteristics, skin rash severity, K-ras mutation status, and clinical outcome (n = 130)

nResponse*
Skin-rash severity
PFS
OS
PRSDPDGrade 0Grade 1Grade 2-3Median, (95% CI)Relative risk, mo (95% CI)Median, mo (95% CI)Relative risk (95% CI)
Age, y            
    ≤54 36 2 (6%) 11 (33%) 20 (61%) 4 (11%) 16 (44%) 16 (44%) 1.2 (1.2, 1.5) 1 (Reference) 5.3 (3.6, 7.5) 1 (Reference) 
    54-64 45 6 (16%) 12 (32%) 19 (51%) 8 (18%) 21 (47%) 16 (36%) 1.4 (1.2, 2.5) 0.74 (0.48, 1.16) 7.0 (3.0, 11.5) 0.69 (0.42, 1.13) 
    ≥65 49 4 (9%) 14 (32%) 26 (59%) 5 (10%) 20 (41%) 24 (49%) 1.4 (1.3, 2.4) 0.77 (0.50, 1.19) 6.6 (3.8, 8.8) 0.86 (0.54, 1.38) 
    P  0.87   0.64   0.34  0.31  
Gender            
    Female 66 7 (12%) 23 (38%) 30 (50%) 8 (12%) 34 (52%) 24 (36%) 1.5 (1.3, 2.4) 1 (Reference) 7.9 (5.0, 8.9) 1 (Reference) 
    Male 64 5 (9%) 14 (26%) 35 (65%) 9 (14%) 23 (36%) 32 (50%) 1.3 (1.2, 1.4) 1.24 (0.88, 1.75) 4.8 (3.4, 7.0) 1.34 (0.91, 1.96) 
    P  0.22   0.37   0.21  0.13  
ECOG performance status score            
    0 52 6 (12%) 19 (39%) 24 (49%) 2 (4%) 19 (37%) 31 (60%) 1.4 (1.2, 2.4) 1 (Reference) 8.0 (5.3, 12.1) 1 (Reference) 
    1 76 6 (9%) 18 (28%) 40 (63%) 14 (18%) 37 (49%) 25 (33%) 1.3 (1.2, 1.8) 1.14 (0.80, 1.63) 4.9 (3.0, 7.0) 1.79 (1.19, 2.68) 
    P  0.21   <0.001   0.44  0.003  
Tumor site            
    Colon 99 10 (11%) 26 (30%) 51 (59%) 11 (11%) 45 (45%) 43 (43%) 1.3 (1.2, 1.5) 1 (Reference) 6.3 (3.8, 8.2) 1 (Reference) 
    Rectum 31 2 (7%) 11 (41%) 14 (52%) 6 (19%) 12 (39%) 13 (42%) 1.4 (1.2, 2.5) 1.14 (0.76, 1.72) 5.5 (3.4, 8.7) 0.96 (0.61, 1.52) 
    P  0.87   0.55   0.51  0.86  
No. of prior chemotherapy regimens            
    2-3 58 4 (8%) 16 (30%) 33 (62%) 4 (7%) 31 (53%) 23 (40%) 1.3 (1.2, 1.3) 1 (Reference) 5.5 (3.6, 7.7) 1 (Reference) 
    4-5 60 6 (12%) 18 (36%) 26 (52%) 11 (18%) 24 (40%) 25 (42%) 1.5 (1.3, 2.6) 0.79 (0.54, 1.13) 5.9 (3.7, 8.2) 1.06 (0.71, 1.58) 
    6-8 12 2 (18%) 3 (27%) 6 (55%) 2 (17%) 2 (17%) 8 (67%) 1.4 (1.1, 6.6) 0.62 (0.33, 1.16) 12.5 (6.4, 17.7) 0.60 (0.29, 1.22) 
    P  0.29   0.92   0.18  0.26  
EGFR tumor immunostaining intensity            
    1+ 79 8 (12%) 19 (28%) 41 (60%) 12 (15%) 36 (46%) 31 (39%) 1.3 (1.2, 1.5) 1 (Reference) 5.5 (3.8, 7.7) 1 (Reference) 
    2-3+ 50 4 (9%) 18 (40%) 23 (51%) 5 (10%) 20 (40%) 25 (50%) 1.4 (1.3, 2.5) 0.89 (0.62, 1.27) 7.3 (3.6, 8.7) 0.97 (0.65, 1.43) 
    P  0.67   0.24   0.51  0.86  
Skin-rash severity            
    Grade 0 17 0 (0%) 0 (0%) 7 (100%)    1.1 (0.9, 1.3) 1 (Reference) 2.0 (1.0, 3.4) 1 (Reference) 
    Grade 1 57 6 (11%) 16 (30%) 31 (58%)    1.3 (1.3, 1.5) 0.37 (0.21, 0.66) 6.5 (3.6, 8.7) 0.27 (0.15, 0.48) 
    Grade 2-3 56 6 (11%) 21 (39%) 27 (50%)    1.5 (1.2, 2.6) 0.35 (0.19, 0.61) 7.6 (5.4, 10.0) 0.21 (0.12, 0.39) 
    P  0.087      <0.0001  <0.0001  
K-ras mutation status            
    Wild-type 88 12 (16%) 26 (34%) 39 (51%) 12 (14%) 38 (43%) 38 (43%) 1.4 (1.3, 2.4) 1 (Reference) 6.6 (4.3, 8.9) 1 (Reference) 
    Mutant 42 0 (0%) 11 (30%) 26 (70%) 5 (12%) 19 (45%) 18 (43%) 1.3 (1.2, 1.6) 1.49 (1.01, 2.20) 4.9 (2.8, 6.6) 1.59 (1.05, 2.40) 
    P  0.012   1.00   0.023  0.020  
nResponse*
Skin-rash severity
PFS
OS
PRSDPDGrade 0Grade 1Grade 2-3Median, (95% CI)Relative risk, mo (95% CI)Median, mo (95% CI)Relative risk (95% CI)
Age, y            
    ≤54 36 2 (6%) 11 (33%) 20 (61%) 4 (11%) 16 (44%) 16 (44%) 1.2 (1.2, 1.5) 1 (Reference) 5.3 (3.6, 7.5) 1 (Reference) 
    54-64 45 6 (16%) 12 (32%) 19 (51%) 8 (18%) 21 (47%) 16 (36%) 1.4 (1.2, 2.5) 0.74 (0.48, 1.16) 7.0 (3.0, 11.5) 0.69 (0.42, 1.13) 
    ≥65 49 4 (9%) 14 (32%) 26 (59%) 5 (10%) 20 (41%) 24 (49%) 1.4 (1.3, 2.4) 0.77 (0.50, 1.19) 6.6 (3.8, 8.8) 0.86 (0.54, 1.38) 
    P  0.87   0.64   0.34  0.31  
Gender            
    Female 66 7 (12%) 23 (38%) 30 (50%) 8 (12%) 34 (52%) 24 (36%) 1.5 (1.3, 2.4) 1 (Reference) 7.9 (5.0, 8.9) 1 (Reference) 
    Male 64 5 (9%) 14 (26%) 35 (65%) 9 (14%) 23 (36%) 32 (50%) 1.3 (1.2, 1.4) 1.24 (0.88, 1.75) 4.8 (3.4, 7.0) 1.34 (0.91, 1.96) 
    P  0.22   0.37   0.21  0.13  
ECOG performance status score            
    0 52 6 (12%) 19 (39%) 24 (49%) 2 (4%) 19 (37%) 31 (60%) 1.4 (1.2, 2.4) 1 (Reference) 8.0 (5.3, 12.1) 1 (Reference) 
    1 76 6 (9%) 18 (28%) 40 (63%) 14 (18%) 37 (49%) 25 (33%) 1.3 (1.2, 1.8) 1.14 (0.80, 1.63) 4.9 (3.0, 7.0) 1.79 (1.19, 2.68) 
    P  0.21   <0.001   0.44  0.003  
Tumor site            
    Colon 99 10 (11%) 26 (30%) 51 (59%) 11 (11%) 45 (45%) 43 (43%) 1.3 (1.2, 1.5) 1 (Reference) 6.3 (3.8, 8.2) 1 (Reference) 
    Rectum 31 2 (7%) 11 (41%) 14 (52%) 6 (19%) 12 (39%) 13 (42%) 1.4 (1.2, 2.5) 1.14 (0.76, 1.72) 5.5 (3.4, 8.7) 0.96 (0.61, 1.52) 
    P  0.87   0.55   0.51  0.86  
No. of prior chemotherapy regimens            
    2-3 58 4 (8%) 16 (30%) 33 (62%) 4 (7%) 31 (53%) 23 (40%) 1.3 (1.2, 1.3) 1 (Reference) 5.5 (3.6, 7.7) 1 (Reference) 
    4-5 60 6 (12%) 18 (36%) 26 (52%) 11 (18%) 24 (40%) 25 (42%) 1.5 (1.3, 2.6) 0.79 (0.54, 1.13) 5.9 (3.7, 8.2) 1.06 (0.71, 1.58) 
    6-8 12 2 (18%) 3 (27%) 6 (55%) 2 (17%) 2 (17%) 8 (67%) 1.4 (1.1, 6.6) 0.62 (0.33, 1.16) 12.5 (6.4, 17.7) 0.60 (0.29, 1.22) 
    P  0.29   0.92   0.18  0.26  
EGFR tumor immunostaining intensity            
    1+ 79 8 (12%) 19 (28%) 41 (60%) 12 (15%) 36 (46%) 31 (39%) 1.3 (1.2, 1.5) 1 (Reference) 5.5 (3.8, 7.7) 1 (Reference) 
    2-3+ 50 4 (9%) 18 (40%) 23 (51%) 5 (10%) 20 (40%) 25 (50%) 1.4 (1.3, 2.5) 0.89 (0.62, 1.27) 7.3 (3.6, 8.7) 0.97 (0.65, 1.43) 
    P  0.67   0.24   0.51  0.86  
Skin-rash severity            
    Grade 0 17 0 (0%) 0 (0%) 7 (100%)    1.1 (0.9, 1.3) 1 (Reference) 2.0 (1.0, 3.4) 1 (Reference) 
    Grade 1 57 6 (11%) 16 (30%) 31 (58%)    1.3 (1.3, 1.5) 0.37 (0.21, 0.66) 6.5 (3.6, 8.7) 0.27 (0.15, 0.48) 
    Grade 2-3 56 6 (11%) 21 (39%) 27 (50%)    1.5 (1.2, 2.6) 0.35 (0.19, 0.61) 7.6 (5.4, 10.0) 0.21 (0.12, 0.39) 
    P  0.087      <0.0001  <0.0001  
K-ras mutation status            
    Wild-type 88 12 (16%) 26 (34%) 39 (51%) 12 (14%) 38 (43%) 38 (43%) 1.4 (1.3, 2.4) 1 (Reference) 6.6 (4.3, 8.9) 1 (Reference) 
    Mutant 42 0 (0%) 11 (30%) 26 (70%) 5 (12%) 19 (45%) 18 (43%) 1.3 (1.2, 1.6) 1.49 (1.01, 2.20) 4.9 (2.8, 6.6) 1.59 (1.05, 2.40) 
    P  0.012   1.00   0.023  0.020  

Abbreviations: PR, partial response; SD, stable disease; PD, progressive disease; ECOG, Eastern Cooperative Oncology Group.

*

Sixteen of 130 patients (12%) were not evaluable for tumor response.

P values were based on the exact conditional test for response and for skin rash severity, and the log-rank test for PFS and OS.

K-ras mutation status and clinical outcome.K-ras mutation was significantly associated with lack of response to cetuximab (Table 3). None of the 37 patients with a K-ras mutation whose tumor response was evaluable had a response to cetuximab, whereas 12 of the 77 wild-type K-ras patients were responders (0% versus 16%, respectively; P = 0.012). In the 130 patients assessable for survival, PFS and OS times of patients without K-ras mutation were significantly longer compared with the PFS and OS times of mutated patients [median PFS, 1.4 month (95% CI, 1.3-2.4 month) versus 1.3 month (95% CI, 1.2-1.6 month), respectively; P = 0.023; median OS, 6.6 months (95% CI, 4.3-8.9 months) versus 4.9 months (95% CI, 2.8-6.6 months), respectively; Table 3].

EGF +61 A>G polymorphism (rs4444903) and progression-free survival. Genotyping for EGF +61 A>G was successful in 116 (89%) of 130 cases. In the other 14 (11%) patients, genotyping was not successful because of limited quantity and quality of extracted genomic DNA. EGF +61 A>G polymorphism showed a significant association with PFS. Patients with the EGF +61 G/G homozygous genotype had a median PFS of 1.4 months (95% CI, 1.3-3.9 months), compared with 1.2 months (95% CI, 1.2-1.5 months) and 1.3 months (95% CI, 1.2-2.6 months), in patients homozygous and heterozygous for the A-allele, respectively (P = 0.042, log-rank test). For EGF +61 A>G, the FDR-adjusted P value did meet the criteria for variable selection as a candidate predictor in the multivariable model (FDR-adjusted P = 0.11; Table 4; Fig. 1A).

Table 4.

Genomic polymorphisms and clinical outcome in mCRC patients treated with single-agent cetuximab

nResponse*
Skin-rash severity
PFS
OS
PRSDPDPFDR-adjusted PGrade 0Grade 1Grade 2-3PFDR-adjusted PMedian, mo (95% CI)Relative risk (95% CI)PFDR-adjusted PMedian, mo (95% CI)Relative risk (95% CI)PFDR-adjusted P
FCGR2A 131 H>R (rs1801274)     0.93 0.92    0.72 0.93   0.50 0.85   0.49 0.87 
    H/H 35 2 (6%) 11 (34%) 19 (59%)   5 (14%) 14 (40%) 16 (46%)   1.3 (1.2, 1.6) 1 (Reference)   7.5 (3.6, 8.7) 1 (Reference)   
    H/R 29 4 (15%) 8 (31%) 14 (54%)   3 (10%) 11 (38%) 15 (52%)   1.2 (1.1, 3.9) 0.76 (0.46, 1.27)   5.3 (2.8, 8.7) 0.73 (0.41, 1.30)   
    R/R 36 4 (12%) 9 (26%) 21 (62%)   3 (8%) 21 (58%) 12 (33%)   1.3 (1.2, 2.5) 0.91 (0.57, 1.44)   5.9 (3.7, 8.6) 0.92 (0.55, 1.53)   
FCGR3A 158 V>F (rs396991)     0.85 0.92    0.13 0.78   0.42 0.85   0.34 0.87 
    F/F 32 3 (11%) 6 (21%) 19 (68%)   4 (13%) 10 (31%) 18 (56%)   1.3 (1.2, 1.6) 1 (Reference)   6.4 (3.4, 7.9) 1 (Reference)   
    F/V 58 6 (11%) 21 (38%) 28 (51%)   5 (9%) 29 (50%) 24 (41%)   1.3 (1.2, 2.5) 0.84 (0.55, 1.29)   6.3 (4.4, 8.7) 0.71 (0.45, 1.14)   
    V/V 37 3 (10%) 9 (29%) 19 (61%)   6 (16%) 18 (49%) 13 (35%)   1.3 (1.2, 1.5) 1.08 (0.68, 1.73)   4.1 (3.0, 9.3) 0.87 (0.53, 1.44)   
EGFR +497 G>A (rs11543848)     0.50 0.86    0.30 0.82   0.017 0.094   0.65 0.87 
    G/G 66 5 (9%) 20 (36%) 31 (55%)   10 (15%) 28 (42%) 28 (42%)   1.3 (1.2, 1.5) 1 (Reference)   5.5 (3.6, 7.6) 1 (Reference)   
    A/G 47 6 (14%) 15 (34%) 23 (52%)   4 (9%) 23 (49%) 20 (43%)   1.8 (1.3, 2.6) 0.82 (0.56, 1.20)   7.3 (4.8, 8.7) 0.90 (0.59, 1.37)   
    A/A 0 (0%) 1 (13%) 7 (88%)   1 (11%) 2 (22%) 6 (67%)   1.2 (1.1, 1.2) 2.16 (1.06, 4.43)   2.7 (1.8, 12.1) 1.30 (0.59, 2.88)   
EGFR (CA)14-23(rs45608036)     0.77 0.92    0.41 0.82   0.73 0.89   0.52 0.87 
Both repeats <20 54 6 (13%) 12 (26%) 29 (62%)   7 (13%) 20 (37%) 27 (50%)   1.3 (1.2, 1.5) 1 (Reference)   7.0 (4.1, 8.7) 1 (Reference)   
Any repeats ≥20 63 5 (9%) 22 (39%) 30 (53%)   7 (11%) 33 (52%) 23 (37%)   1.3 (1.3, 2.5) 1.06 (0.73, 1.54)   5.5 (3.7, 8.0) 1.14 (0.76, 1.71)   
CCDN1 +870 A>G (rs17852153)     0.60 0.86    0.36 0.82   0.62 0.85   0.87 0.87 
    G/G 44 2 (5%) 13 (34%) 23 (61%)   4 (9%) 19 (43%) 21 (48%)   1.3 (1.2, 1.6) 1 (Reference)   6.5 (3.6, 8.2) 1 (Reference)   
    G/A 48 7 (17%) 10 (24%) 24 (59%)   8 (17%) 18 (38%) 22 (46%)   1.3 (1.2, 2.3) 0.85 (0.56, 1.30)   5.4 (3.6, 8.7) 0.92 (0.59, 1.45)   
    A/A 34 2 (6%) 13 (41%) 17 (53%)   4 (12%) 18 (53%) 12 (35%)   1.4 (1.3, 2.8) 0.82 (0.52, 1.29)   5.5 (2.8, 8.6) 1.05 (0.64, 1.74)   
IL-8 -251 T>A (rs4073)     0.32 0.86    0.01 0.054   0.14 0.32   0.30 0.87 
    A/A 35 3 (12%) 5 (19%) 18 (69%)   7 (20%) 19 (54%) 9 (26%)   1.3 (1.2, 1.8) 1 (Reference)   3.4 (2.5, 6.1) 1 (Reference)   
    A/T 63 6 (10%) 19 (33%) 33 (57%)   8 (13%) 26 (41%) 29 (46%)   1.3 (1.2, 1.5) 0.81 (0.54, 1.24)   6.6 (4.8, 8.2) 0.85 (0.53, 1.35)   
    T/T 30 3 (10%) 12 (41%) 14 (48%)   1 (3%) 12 (40%) 17 (57%)   1.4 (1.2, 3.9) 0.63 (0.38, 1.05)   8.7 (5.3, 12.0) 0.66 (0.38, 1.14)   
VEGF C+936T (rs3025039)     0.45 0.86    0.81 0.93   0.87 0.93   0.19 0.87 
    C/C 89 7 (9%) 25 (32%) 45 (58%)   12 (13%) 36 (40%) 41 (46%)   1.3 (1.2, 1.6) 1 (Reference)   6.5 (4.9, 8.0) 1 (Reference)   
    C/T 26 4 (17%) 5 (21%) 15 (63%)   3 (12%) 14 (54%) 9 (35%)   1.3 (1.2, 2.8) 0.89 (0.58, 1.39)   3.4 (2.7, 8.6) 1.25 (0.77, 2.02)   
    T/T 0 (0%) 4 (80%) 1 (20%)   0 (0%) 3 (60%) 2 (40%)   1.3 (1.2, 5.4) 0.99 (0.40, 2.44)   14.5 (1.5, 15.0) 0.36 (0.09, 1.48)   
COX-2 −765 G>C (rs20417)     0.02 0.22    0.72 0.92   0.032 0.11   0.48 0.87 
    G/G 85 7 (9%) 22 (29%) 46 (61%)   9 (11%) 38 (45%) 38 (45%)   1.3 (1.2, 1.5) 1 (Reference)   5.3 (3.7, 7.9) 1 (Reference)   
    G/C 34 2 (7%) 11 (39%) 15 (54%)   7 (21%) 15 (44%) 12 (35%)   1.3 (1.2, 2.4) 1.03 (0.69, 1.54)   5.5 (3.4, 10.0) 0.92 (0.59, 1.43)   
    C/C 3 (75%) 1 (25%) 0 (0%)   0 (0%) 1 (25%) 3 (75%)   5.8 (3.8, 9.6) 0.31 (0.12, 0.84)   10.5 (10.1, 13.3) 0.51 (0.16, 1.61)   
COX-2 +8473 T>C (rs5275)     0.62 0.86    0.86 0.93   0.003 0.037   0.47 0.87 
    T/T 58 6 (11%) 18 (34%) 29 (55%)   5 (9%) 26 (45%) 27 (47%)   1.4 (1.3, 2.6) 1 (Reference)   7.6 (5.0, 8.8) 1 (Reference)   
    T/C 48 2 (5%) 12 (29%) 28 (67%)   9 (19%) 24 (50%) 15 (31%)   1.3 (1.2, 1.4) 1.49 (1.01, 2.22)   3.8 (2.6, 6.4) 1.27 (0.83, 1.96)   
    C/C 19 3 (19%) 7 (44%) 6 (38%)   2 (11%) 4 (21%) 13 (68%)   3.8 (1.2, 5.8) 0.67 (0.40, 1.13)   8.7 (3.3, 12.1) 0.98 (0.55, 1.74)   
EGF +61 A>G (rs4444903)     0.17 0.86    0.93 0.93   0.042 0.11   0.84 0.87 
    A/A 42 2 (6%) 12 (33%) 22 (61%)   6 (14%) 18 (43%) 18 (43%)   1.2 (1.2, 1.5) 1 (Reference)   6.4 (3.6, 8.4) 1 (Reference)   
    A/G 48 4 (9%) 14 (32%) 26 (59%)   4 (8%) 24 (50%) 20 (42%)   1.3 (1.2, 2.6) 0.72 (0.47, 1.10)   5.0 (3.6, 8.7) 1.13 (0.71, 1.79)   
    G/G 26 5 (23%) 6 (27%) 11 (50%)   4 (15%) 10 (38%) 12 (46%)   1.4 (1.3, 3.9) 0.57 (0.34, 0.95)   5.9 (3.0, 10.5) 0.99 (0.57, 1.73)   
NRP-1 C/T (rs3750733)     0.48 0.86    0.21 0.82   0.93 0.93   0.87 0.87 
    C/C 44 4 (10%) 15 (38%) 20 (51%)   6 (14%) 21 (48%) 17 (39%)   1.3 (1.2, 2.4) 1 (Reference)   7.3 (5.5, 8.7) 1 (Reference)   
    C/T 51 5 (12%) 13 (30%) 25 (58%)   6 (12%) 26 (51%) 19 (37%)   1.4 (1.2, 2.4) 0.98 (0.65, 1.47)   4.4 (3.6, 8.6) 0.91 (0.58, 1.42)   
    T/T 32 3 (10%) 8 (27%) 19 (63%)   4 (13%) 9 (28%) 19 (59%)   1.3 (1.2, 2.4) 0.92 (0.58, 1.47)   5.3 (3.4, 7.5) 1.02 (0.62, 1.68)   
nResponse*
Skin-rash severity
PFS
OS
PRSDPDPFDR-adjusted PGrade 0Grade 1Grade 2-3PFDR-adjusted PMedian, mo (95% CI)Relative risk (95% CI)PFDR-adjusted PMedian, mo (95% CI)Relative risk (95% CI)PFDR-adjusted P
FCGR2A 131 H>R (rs1801274)     0.93 0.92    0.72 0.93   0.50 0.85   0.49 0.87 
    H/H 35 2 (6%) 11 (34%) 19 (59%)   5 (14%) 14 (40%) 16 (46%)   1.3 (1.2, 1.6) 1 (Reference)   7.5 (3.6, 8.7) 1 (Reference)   
    H/R 29 4 (15%) 8 (31%) 14 (54%)   3 (10%) 11 (38%) 15 (52%)   1.2 (1.1, 3.9) 0.76 (0.46, 1.27)   5.3 (2.8, 8.7) 0.73 (0.41, 1.30)   
    R/R 36 4 (12%) 9 (26%) 21 (62%)   3 (8%) 21 (58%) 12 (33%)   1.3 (1.2, 2.5) 0.91 (0.57, 1.44)   5.9 (3.7, 8.6) 0.92 (0.55, 1.53)   
FCGR3A 158 V>F (rs396991)     0.85 0.92    0.13 0.78   0.42 0.85   0.34 0.87 
    F/F 32 3 (11%) 6 (21%) 19 (68%)   4 (13%) 10 (31%) 18 (56%)   1.3 (1.2, 1.6) 1 (Reference)   6.4 (3.4, 7.9) 1 (Reference)   
    F/V 58 6 (11%) 21 (38%) 28 (51%)   5 (9%) 29 (50%) 24 (41%)   1.3 (1.2, 2.5) 0.84 (0.55, 1.29)   6.3 (4.4, 8.7) 0.71 (0.45, 1.14)   
    V/V 37 3 (10%) 9 (29%) 19 (61%)   6 (16%) 18 (49%) 13 (35%)   1.3 (1.2, 1.5) 1.08 (0.68, 1.73)   4.1 (3.0, 9.3) 0.87 (0.53, 1.44)   
EGFR +497 G>A (rs11543848)     0.50 0.86    0.30 0.82   0.017 0.094   0.65 0.87 
    G/G 66 5 (9%) 20 (36%) 31 (55%)   10 (15%) 28 (42%) 28 (42%)   1.3 (1.2, 1.5) 1 (Reference)   5.5 (3.6, 7.6) 1 (Reference)   
    A/G 47 6 (14%) 15 (34%) 23 (52%)   4 (9%) 23 (49%) 20 (43%)   1.8 (1.3, 2.6) 0.82 (0.56, 1.20)   7.3 (4.8, 8.7) 0.90 (0.59, 1.37)   
    A/A 0 (0%) 1 (13%) 7 (88%)   1 (11%) 2 (22%) 6 (67%)   1.2 (1.1, 1.2) 2.16 (1.06, 4.43)   2.7 (1.8, 12.1) 1.30 (0.59, 2.88)   
EGFR (CA)14-23(rs45608036)     0.77 0.92    0.41 0.82   0.73 0.89   0.52 0.87 
Both repeats <20 54 6 (13%) 12 (26%) 29 (62%)   7 (13%) 20 (37%) 27 (50%)   1.3 (1.2, 1.5) 1 (Reference)   7.0 (4.1, 8.7) 1 (Reference)   
Any repeats ≥20 63 5 (9%) 22 (39%) 30 (53%)   7 (11%) 33 (52%) 23 (37%)   1.3 (1.3, 2.5) 1.06 (0.73, 1.54)   5.5 (3.7, 8.0) 1.14 (0.76, 1.71)   
CCDN1 +870 A>G (rs17852153)     0.60 0.86    0.36 0.82   0.62 0.85   0.87 0.87 
    G/G 44 2 (5%) 13 (34%) 23 (61%)   4 (9%) 19 (43%) 21 (48%)   1.3 (1.2, 1.6) 1 (Reference)   6.5 (3.6, 8.2) 1 (Reference)   
    G/A 48 7 (17%) 10 (24%) 24 (59%)   8 (17%) 18 (38%) 22 (46%)   1.3 (1.2, 2.3) 0.85 (0.56, 1.30)   5.4 (3.6, 8.7) 0.92 (0.59, 1.45)   
    A/A 34 2 (6%) 13 (41%) 17 (53%)   4 (12%) 18 (53%) 12 (35%)   1.4 (1.3, 2.8) 0.82 (0.52, 1.29)   5.5 (2.8, 8.6) 1.05 (0.64, 1.74)   
IL-8 -251 T>A (rs4073)     0.32 0.86    0.01 0.054   0.14 0.32   0.30 0.87 
    A/A 35 3 (12%) 5 (19%) 18 (69%)   7 (20%) 19 (54%) 9 (26%)   1.3 (1.2, 1.8) 1 (Reference)   3.4 (2.5, 6.1) 1 (Reference)   
    A/T 63 6 (10%) 19 (33%) 33 (57%)   8 (13%) 26 (41%) 29 (46%)   1.3 (1.2, 1.5) 0.81 (0.54, 1.24)   6.6 (4.8, 8.2) 0.85 (0.53, 1.35)   
    T/T 30 3 (10%) 12 (41%) 14 (48%)   1 (3%) 12 (40%) 17 (57%)   1.4 (1.2, 3.9) 0.63 (0.38, 1.05)   8.7 (5.3, 12.0) 0.66 (0.38, 1.14)   
VEGF C+936T (rs3025039)     0.45 0.86    0.81 0.93   0.87 0.93   0.19 0.87 
    C/C 89 7 (9%) 25 (32%) 45 (58%)   12 (13%) 36 (40%) 41 (46%)   1.3 (1.2, 1.6) 1 (Reference)   6.5 (4.9, 8.0) 1 (Reference)   
    C/T 26 4 (17%) 5 (21%) 15 (63%)   3 (12%) 14 (54%) 9 (35%)   1.3 (1.2, 2.8) 0.89 (0.58, 1.39)   3.4 (2.7, 8.6) 1.25 (0.77, 2.02)   
    T/T 0 (0%) 4 (80%) 1 (20%)   0 (0%) 3 (60%) 2 (40%)   1.3 (1.2, 5.4) 0.99 (0.40, 2.44)   14.5 (1.5, 15.0) 0.36 (0.09, 1.48)   
COX-2 −765 G>C (rs20417)     0.02 0.22    0.72 0.92   0.032 0.11   0.48 0.87 
    G/G 85 7 (9%) 22 (29%) 46 (61%)   9 (11%) 38 (45%) 38 (45%)   1.3 (1.2, 1.5) 1 (Reference)   5.3 (3.7, 7.9) 1 (Reference)   
    G/C 34 2 (7%) 11 (39%) 15 (54%)   7 (21%) 15 (44%) 12 (35%)   1.3 (1.2, 2.4) 1.03 (0.69, 1.54)   5.5 (3.4, 10.0) 0.92 (0.59, 1.43)   
    C/C 3 (75%) 1 (25%) 0 (0%)   0 (0%) 1 (25%) 3 (75%)   5.8 (3.8, 9.6) 0.31 (0.12, 0.84)   10.5 (10.1, 13.3) 0.51 (0.16, 1.61)   
COX-2 +8473 T>C (rs5275)     0.62 0.86    0.86 0.93   0.003 0.037   0.47 0.87 
    T/T 58 6 (11%) 18 (34%) 29 (55%)   5 (9%) 26 (45%) 27 (47%)   1.4 (1.3, 2.6) 1 (Reference)   7.6 (5.0, 8.8) 1 (Reference)   
    T/C 48 2 (5%) 12 (29%) 28 (67%)   9 (19%) 24 (50%) 15 (31%)   1.3 (1.2, 1.4) 1.49 (1.01, 2.22)   3.8 (2.6, 6.4) 1.27 (0.83, 1.96)   
    C/C 19 3 (19%) 7 (44%) 6 (38%)   2 (11%) 4 (21%) 13 (68%)   3.8 (1.2, 5.8) 0.67 (0.40, 1.13)   8.7 (3.3, 12.1) 0.98 (0.55, 1.74)   
EGF +61 A>G (rs4444903)     0.17 0.86    0.93 0.93   0.042 0.11   0.84 0.87 
    A/A 42 2 (6%) 12 (33%) 22 (61%)   6 (14%) 18 (43%) 18 (43%)   1.2 (1.2, 1.5) 1 (Reference)   6.4 (3.6, 8.4) 1 (Reference)   
    A/G 48 4 (9%) 14 (32%) 26 (59%)   4 (8%) 24 (50%) 20 (42%)   1.3 (1.2, 2.6) 0.72 (0.47, 1.10)   5.0 (3.6, 8.7) 1.13 (0.71, 1.79)   
    G/G 26 5 (23%) 6 (27%) 11 (50%)   4 (15%) 10 (38%) 12 (46%)   1.4 (1.3, 3.9) 0.57 (0.34, 0.95)   5.9 (3.0, 10.5) 0.99 (0.57, 1.73)   
NRP-1 C/T (rs3750733)     0.48 0.86    0.21 0.82   0.93 0.93   0.87 0.87 
    C/C 44 4 (10%) 15 (38%) 20 (51%)   6 (14%) 21 (48%) 17 (39%)   1.3 (1.2, 2.4) 1 (Reference)   7.3 (5.5, 8.7) 1 (Reference)   
    C/T 51 5 (12%) 13 (30%) 25 (58%)   6 (12%) 26 (51%) 19 (37%)   1.4 (1.2, 2.4) 0.98 (0.65, 1.47)   4.4 (3.6, 8.6) 0.91 (0.58, 1.42)   
    T/T 32 3 (10%) 8 (27%) 19 (63%)   4 (13%) 9 (28%) 19 (59%)   1.3 (1.2, 2.4) 0.92 (0.58, 1.47)   5.3 (3.4, 7.5) 1.02 (0.62, 1.68)   
*

Sixteen of 130 patients (12%) were not evaluable for tumor response.

P values were based on the exact conditional test for response and for skin rash severity and the log-rank test for PFS and OS.

The Benjamini-Hochberg method was used to control the FDR of multiple testing. The FDR adjusted p values were set at <15%.

Fig. 1.

A, PFS of patients with mCRC (IMC-0144) by EGF +61A>G. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. B, PFS of patients with mCRC (IMC-0144) by EGFR +497 G>A. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. C, PFS of patients with mCRC (IMC-0144) by COX-2 −765 G>C. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. D, PFS of patients with mCRC (IMC-0144) by COX-2 +8473 T>C. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data.

Fig. 1.

A, PFS of patients with mCRC (IMC-0144) by EGF +61A>G. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. B, PFS of patients with mCRC (IMC-0144) by EGFR +497 G>A. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. C, PFS of patients with mCRC (IMC-0144) by COX-2 −765 G>C. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data. D, PFS of patients with mCRC (IMC-0144) by COX-2 +8473 T>C. Because all patients showed progressive disease, there were no censored observations. Therefore, no vertical hash marks were added to indicate the time of last follow-up for those patients who have not progressed or died at the time of the analysis of data.

Close modal

EGFR +497 G>A polymorphism (rs11543848) and progression-free survival. Genotyping for EGFR +497 G>A was successful in 122 (94%) of 130 cases. In the other 8 (6%) patients, genotyping was not successful because of limited quantity and quality of extracted genomic DNA. EGFR +497 G>A polymorphism showed a significant association with PFS. Patients with the EGFR +497 A/A homozygous genotype had a median PFS of 1.2 months (95% CI, 1.1-1.2 months), compared with 1.3 months (95% CI, 1.2-1.5 months), and 1.8 months (95% CI, 1.3-2.6 months), in patients homozygous and heterozygous for the G-allele, respectively (P = 0.017, log-rank test). For EGFR +497 G>A, the FDR-adjusted P value did meet the criteria for variable selection as a candidate predictor in the multivariable model (FDR-adjusted P = 0.094; Table 4; Fig. 1B).

COX-2 −765 G>C polymorphism (rs20417) and progression-free survival. Genotyping for COX-2 −765 G>C was successful in 123 (95%) of 130 cases. In the other 7 (5%) patients, genotyping was not successful because of limited quantity and quality of extracted genomic DNA. COX-2 −765 G>C polymorphism showed a significant association with PFS. Patients with the COX-2 −765 G/G homozygous genotype had a median PFS of 1.3 months (95% CI, 1.2-1.5 months), compared with 1.3 month (95% CI, 1.2-2.4 months) and 5.8 month (95% CI, 3.8-9.6 months), in patients heterozygous and homozygous for the C-allele, respectively (P = 0.032, log-rank test). For COX-2 −765 G>C, the FDR-adjusted P value did meet the criteria for variable selection as a candidate predictor in the multivariable model (FDR-adjusted P = 0.11; Table 4; Fig. 1C).

COX-2 +8473 T>C polymorphism (rs5275) and progression-free survival. Genotyping for COX-2 +8473 T>C was successful in 125 (96%) of 130 cases. In the other 5 (4%) patients, genotyping was not successful because of limited quantity and quality of extracted genomic DNA. COX-2 +8473 T>C polymorphism showed a significant association with PFS. Patients with the COX-2 +8473 T/T homozygous genotype had a median PFS of 1.4 months (95% CI, 1.3-2.6 months), compared with 1.3 months (95% CI, 1.2 to 1.4 months) and 3.8 months (95% CI, 1.2-5.8 months), in patients heterozygous and homozygous for the C-allele, respectively (P = 0.003, log-rank test). For COX-2 +8473 T>C, the FDR-adjusted P value did meet the criteria for variable selection as a candidate predictor in the multivariable model (FDR-adjusted P = 0.037; Table 4; Fig. 1D).

COX-2 −765 G>C polymorphism (rs20417) and response to Cetuximab.COX-2 −765 G>C polymorphism showed a significant association with response to cetuximab. Patients homozygous for the COX-2 −765 G-allele (n = 85) were more likely to experience progressive disease (61%), compared with patients carrying the G/C (progressive disease, 54%) or C/C (progressive disease, 0%) genotype (P = 0.02, exact-conditional test). COX-2 −765 G>C was not significantly associated with response, after an FDR-adjusted P value of <0.15 was used (FDR-adjusted P = 0.22; Table 4).

Other tested gene polymorphisms and clinical outcome to Cetuximab. Other tested gene polymorphisms did not show statistically significant associations with OS, response to cetuximab, toxicity, and PFS (Table 4).

Multiple testing using Benjamini-Hochberg method. After adjusting for the FDR at <15% (P < 0.15), EGF +61 A>G (FDR-adjusted P = 0.11), EGFR +497 G>A (FDR-adjusted P = 0.094), COX-2 −765 G>C (FDR-adjusted P = 0.11), and COX-2 T+8473 (FDR-adjusted P = 0.037) were used as candidates for inclusion in the multivariable model (Table 4).

Multivariable analysis of COX-2 +8473 T>C (rs5275), EGF +61 A>G (rs4444903), and EGFR +497 G>A (rs11543848). When we analyzed COX-2 +8473 T>C (adjusted P = 0.013), EGF +61 A>G (adjusted P = 0.088), and EGFR +497 G>A (adjusted P = 0.010) jointly, adjusted by skin rash severity, K-ras mutation, and ECOG performance status, stratified by race, EGFR +497 G>A (rs11543848), and COX-2 +8473 T>C (rs5275) remained significantly associated with PFS (Table 5). Because both COX-2 single nucleotide polymorphisms are in strong linkage disequilibrium (data not shown), COX-2 −765 G>C was not included into the multivariable model due to multicolinearity issues. Multivariable analysis was not conducted for OS because no polymorphism was found to be significant for OS.

Table 5.

Multivariable analysis of COX-2, EGF and EGFR polymorphisms, and PFS

n*Adjusted RR (95%CI)Adjusted P
EGFR +497 G>A (rs11543848)   0.010 
    G/G 60 1 (Reference)  
    A/G 43 0.71 (0.46, 1.08)  
    A/A 2.82 (1.24, 6.38)  
    G/G + A/G vs A/A  3.04 (1.38-6.72)  
COX-2 +8473 T>C (rs5275)   0.013 
    T/T 50 1 (Reference)  
    T/C 43 1.59 (0.98, 2.58)  
    C/C 18 0.63 (0.34, 1.14)  
    T/T + T/C vs C/C  0.53 (0.30-0.93)  
EGF +61 A>G (rs4444903)   0.088 
    A/A 39 1 (Reference)  
    A/G 48 0.70 (0.43, 1.12)  
    G/G 24 0.51 (0.28, 0.95)  
    A/A vs A/G+G/G  0.64 (0.41, 1.00)  
Skin-rash severity    
    Grade 0 13 1 (Reference) 0.006 
    Grade 1 49 0.27 (0.13, 0.56)  
    Grade 2-3 49 0.28 (0.12, 0.61)  
K-ras mutation status   0.45 
    Wild-type 72 1 (Reference)  
    Mutant 39 1.20 (0.75, 1.92)  
ECOG performance status score   0.69 
    0 46 1 (Reference)  
    1 63 0.91 (0.59, 1.42)  
n*Adjusted RR (95%CI)Adjusted P
EGFR +497 G>A (rs11543848)   0.010 
    G/G 60 1 (Reference)  
    A/G 43 0.71 (0.46, 1.08)  
    A/A 2.82 (1.24, 6.38)  
    G/G + A/G vs A/A  3.04 (1.38-6.72)  
COX-2 +8473 T>C (rs5275)   0.013 
    T/T 50 1 (Reference)  
    T/C 43 1.59 (0.98, 2.58)  
    C/C 18 0.63 (0.34, 1.14)  
    T/T + T/C vs C/C  0.53 (0.30-0.93)  
EGF +61 A>G (rs4444903)   0.088 
    A/A 39 1 (Reference)  
    A/G 48 0.70 (0.43, 1.12)  
    G/G 24 0.51 (0.28, 0.95)  
    A/A vs A/G+G/G  0.64 (0.41, 1.00)  
Skin-rash severity    
    Grade 0 13 1 (Reference) 0.006 
    Grade 1 49 0.27 (0.13, 0.56)  
    Grade 2-3 49 0.28 (0.12, 0.61)  
K-ras mutation status   0.45 
    Wild-type 72 1 (Reference)  
    Mutant 39 1.20 (0.75, 1.92)  
ECOG performance status score   0.69 
    0 46 1 (Reference)  
    1 63 0.91 (0.59, 1.42)  
*

Patients with missing EGFR +497 G>A, COX-2 +8473 T>C, or EGF +61 A>G were excluded.

Likelihood ratio test based on Cox proportional hazards model, adjusted by skin rash severity, K-ras mutation, and ECOG performance status, stratified by race, with all three polymorphisms included.

Adjusted P values, reflect unpooled three-group genotype comparisons.

We were able to show that germline polymorphisms of genes involved in the EGFR pathway independently predict clinical outcome in mCRC patients treated with single-agent cetuximab. To the best of our knowledge, this is the first study to show that EGFR pathway–related germline polymorphisms might be important prognostic markers in mCRC patients treated with single-agent cetuximab, independent of skin rash toxicity, and K-ras mutation status.

COX is the rate-limiting enzyme in the conversion of arachidonic acid to prostaglandins. The isoform COX-1 is thought to be constitutively expressed in a variety of tissues, whereas COX-2 is induced by cytokines, growth factors, mitogens, and oncoproteins (25). COX-2 is involved in the regulation of a broad range of cellular processes including tumor onset and progression, metastases, angiogenesis, and resistance to chemotherapy (2630). The relationship between COX-2 and the EGF/EGFR signaling pathway is still controversial (31). COX-2 is thought to be a downstream effector of EGFR and was found to be induced by EGF-mediated stimulation of EGFR tyrosine kinase in human glioma cell lines (32). In vivo models by Xu et al. (32) showed that COX-2 expression is strongly induced by p38 mitogen–activated protein kinase–mediated EGF stimulation. Other studies showed that COX-2 may be an upstream effector of EGFR in human colon cancer cells lines, suggesting that COX-2 induces colon cancer carcinogenesis by the activation of EGFR (33, 34). Furthermore, COX-2 has been reported to be a predictive and prognostic factor in a variety of malignancies (18, 26, 27). In fact, high expression levels of COX-2 are associated with shorter OS in ovarian, head and neck, esophageal, and CRC (18, 3537). COX-2 −765 G>C is a frequent single nucleotide polymorphism and is located 765 bp upstream of the COX-2 transcription start site. The -765 C-allele was shown to be associated with significantly lower COX-2 promoter activity and associate lower C-reactive protein plasma levels compared with the −765 G-variant (38). Other common variants within the COX-2 gene include the COX-2 +8473 T>C single nucleotide polymorphism. The COX-2 +8473 T>C polymorphism locates within the functional region of 3-untranslated region of the gene and, therefore, may have a potential functional relevance in carcinogenesis, perhaps through control of mRNA-stability and degradation (39, 40). The +8473 C-allele was significantly less common in patients with lung cancer compared with healthy control patients, suggesting a protective effect against lung cancer (40). The present study found “low-expression” variants of COX-2 (COX-2 −765C and COX-2 +8473C) to be significantly associated with higher PFS in both univariate and multivariable analysis (Tables 4 and 5). These findings are therefore consistent with previous reports by our group, demonstrating that COX-2 mRNA overexpression is an adverse prognostic marker in mCRC (18). In addition, patients displaying the COX-2 −765 C/C genotype were more likely to experience partial response to cetuximab, compared with patients harboring the −765 G-allele (log-rank test; P = 0.02; Table 4). Interestingly, all three patients with the COX-2 −765 C/C genotype and with partial response to cetuximab also showed grade 2 to 3 skin toxicity and superior PFS (median PFS, 8 months; 5.8-9.6) compared with other genotype combinations. It should be noted, however, that our study population consisted of only four patients carrying the COX-2 −765 C-allele, and after adjustment for FDR, COX-2 −765 G>C did not remain significantly associated with response at the FDR of <15% level. Therefore, our data for COX-2 −765 G>C is tenuous and needs to be validated. Although not conclusive, our data indicate that genetic variants of COX-2 may be prognostic and/or predictive markers for mCRC patients treated with single-agent cetuximab.

A recent study by Lu and coworkers (41) showed novel mechanisms of acquired resistance escaping treatment by cetuximab. In vitro, cetuximab-resistant DiFi5 CRC cells were shown to have an enhanced ubiquitination and functional degradation of EGFR (41). The authors report that CRC cells may develop acquired resistance to cetuximab via altering EGFR levels through promotion of EGFR degradation and using Src kinase–mediated cell signaling to bypass their dependency on EGFR for tumor growth and survival (41). EGFR +497 G>A is a single nucleotide polymorphism in codon 497, which has been associated with an arginine → lysine substitution in the extracellular domain within subdomain IV. Moriai et al. (42) were able to show that the lysine/lysine (A/A) genotype confers an attenuated function in EGFR ligand binding, growth stimulation, tyrosine kinase activation, and induction of proto-oncogenes. In the present study, EGFR +497 A/A genotype was associated with poor clinical outcome and shorter PFS, compared with other genotypes. Our findings are therefore consistent with Lu et al.'s (41) observations, as cetuximab resistance may be associated, at least in part, with intratumoral EGFR degradation. To date, EGFR polymorphisms have not been reported to be independently associated with PFS in mCRC patients treated with single-agent cetuximab. In our study, EGFR +497 G>A was found to be significantly associated with PFS in both FDR-adjusted univariate and multivariable analysis (Tables 4 and 5).

As with all clinical outcome studies, this analysis has potential limitations; First, all patients included in this study were treated with single-agent cetuximab. Therefore, it was not possible to assess genotype combinations associated with clinical outcome in an untreated control group. Second, our findings are based on a relatively small number of patients; and third, we examined eight genes within the EGFR pathway. Although it is recognized that the observed associations and patterns require confirmation with an independent data set, and no amount of reanalysis with the current data set will eliminate that need, we have taken care to (a) select the candidate genes with a documented role in the EGFR-signaling pathway, which have been found to be associated with prognosis in previous studies at our institution and/or in published articles (Table 1); (b) perform an internal validation analysis to reduce the likelihood of overanalyzing this data set; and (c) adjust the FDR for multiple comparisons. Nevertheless, the results of this molecular correlates study should be interpreted carefully within the context of other publications and analyses.

Notwithstanding the aforementioned limitations, we have identified polymorphisms in COX-2, EGF, and EGFR as potential molecular markers for clinical outcome in mCRC patients treated with single-agent cetuximab. In addition, genetic variants of COX-2 and EGFR remained significantly associated with PFS in multivariable analysis, independent of skin rash toxicity and K-ras mutation status. Interestingly, genetic markers predicting clinical outcome seem to be different among patients with and without skin rash toxicity. In fact, only interleukin-8 T-251A was associated with skin rash toxicity, suggesting a specific and distinct genomic phenotype, which may be different in patients with high- and low-degree skin toxicity. In summary, this study supports the role of functional polymorphisms in COX-2, EGF, and EGFR in relation to PFS, which may be explained by both a predictive and/or a prognostic role of the aforementioned variants. Larger, prospective and biomarker-embedded clinical trials are needed to confirm and validate our findings.

H.-J. Lenz has received honoraria from Merck KG and Bristol-Myers Squibb. E.K. Rowinsky is employed by Imclone Systems, Inc. A. El-Khoueiry has received commercial research support from Bristol Myers Squibb. D.J. Mauro is employed by Bristol Myers Squibb. C. Langer is employed by and has an ownership interest in Bristol Myers Squibb.

Grant support: NIH grant 5 P30CA14089-27I and the Dhont Family Foundation and performed in the Sharon A. Carpenter Laboratory at University of Southern California.

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

Note: Presented in part at the Annual Meeting of the American Society of Clinical Oncology, Chicago, Illinois, June 1-5, 2007.

1
Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2008.
CA Cancer J Clin
2008
;
58
:
71
–96.
2
de Gramont A, Figer A, Seymour M, et al. Leucovorin and fluorouracil with or without oxaliplatin as first-line treatment in advanced colorectal cancer.
J Clin Oncol
2000
;
18
:
2938
–47.
3
Douillard JY, Cunningham D, Roth AD, et al. Irinotecan combined with fluorouracil compared with fluorouracil alone as first-line treatment for metastatic colorectal cancer: a multicentre randomised trial.
Lancet
2000
;
355
:
1041
–7.
4
Sargent DJ, Wieand HS, Haller DG, et al. Disease-free survival versus overall survival as a primary end point for adjuvant colon cancer studies: individual patient data from 20,898 patients on 18 randomized trials.
J Clin Oncol
2005
;
23
:
8664
–70.
5
Goldberg RM, Tabah-Fisch I, Bleiberg H, et al. Pooled analysis of safety and efficacy of oxaliplatin plus fluorouracil/leucovorin administered bimonthly in elderly patients with colorectal cancer.
J Clin Oncol
2006
;
24
:
4085
–91.
6
Cunningham D, Humblet Y, Siena S, et al. Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer.
N Engl J Med
2004
;
351
:
337
–45.
7
Saltz LB, Meropol NJ, Loehrer PJ, Sr., Needle MN, Kopit J, Mayer RJ. Phase II trial of cetuximab in patients with refractory colorectal cancer that expresses the epidermal growth factor receptor.
J Clin Oncol
2004
;
22
:
1201
–8.
8
Salomon DS, Brandt R, Ciardiello F, Normanno N. Epidermal growth factor-related peptides and their receptors in human malignancies.
Crit Rev Oncol Hematol
1995
;
19
:
183
–232.
9
Hemming AW, Davis NL, Kluftinger A, et al. Prognostic markers of colorectal cancer: an evaluation of DNA content, epidermal growth factor receptor, and Ki-67.
J Surg Oncol
1992
;
51
:
147
–52.
10
Fan Z, Baselga J, Masui H, Mendelsohn J. Antitumor effect of anti-epidermal growth factor receptor monoclonal antibodies plus cis-diamminedichloroplatinum on well established A431 cell xenografts.
Cancer Res
1993
;
53
:
4637
–42.
11
Karnes WE, Jr., Weller SG, Adjei PN, et al. Inhibition of epidermal growth factor receptor kinase induces protease-dependent apoptosis in human colon cancer cells.
Gastroenterology
1998
;
114
:
930
–9.
12
Wu X, Fan Z, Masui H, Rosen N, Mendelsohn J. Apoptosis induced by an anti-epidermal growth factor receptor monoclonal antibody in a human colorectal carcinoma cell line and its delay by insulin.
J Clin Invest
1995
;
95
:
1897
–905.
13
Lenz HJ, Van Cutsem E, Khambata-Ford S, et al. Multicenter phase II and translational study of cetuximab in metastatic colorectal carcinoma refractory to irinotecan, oxaliplatin, and fluoropyrimidines.
J Clin Oncol
2006
;
24
:
4914
–21.
14
Bissonnette M, Khare S, von Lintig FC, et al. Mutational and nonmutational activation of p21ras in rat colonic azoxymethane-induced tumors: effects on mitogen-activated protein kinase, cyclooxygenase-2, and cyclin D1.
Cancer Res
2000
;
60
:
4602
–9.
15
Fichera A, Little N, Jagadeeswaran S, et al. Epidermal growth factor receptor signaling is required for microadenoma formation in the mouse azoxymethane model of colonic carcinogenesis.
Cancer Res
2007
;
67
:
827
–35.
16
Muise-Helmericks RC, Grimes HL, Bellacosa A, Malstrom SE, Tsichlis PN, Rosen N. Cyclin D expression is controlled post-transcriptionally via a phosphatidylinositol 3-kinase/Akt-dependent pathway.
J Biol Chem
1998
;
273
:
29864
–72.
17
Zhang W, Gordon M, Press OA, et al. Cyclin D1 and epidermal growth factor polymorphisms associated with survival in patients with advanced colorectal cancer treated with Cetuximab.
Pharmacogenet Genomics
2006
;
16
:
475
–83.
18
Vallbohmer D, Zhang W, Gordon M, et al. Molecular determinants of cetuximab efficacy.
J Clin Oncol
2005
;
23
:
3536
–44.
19
Kurai J, Chikumi H, Hashimoto K, et al. Antibody-dependent cellular cytotoxicity mediated by cetuximab against lung cancer cell lines.
Clin Cancer Res
2007
;
13
:
1552
–61.
20
De Roock W, Piessevaux H, De Schutter J, et al. KRAS wild-type state predicts survival and is associated to early radiological response in metastatic colorectal cancer treated with cetuximab.
Ann Oncol
2008
;
19
:
508
–15.
21
Di Fiore F, Blanchard F, Charbonnier F, et al. Clinical relevance of KRAS mutation detection in metastatic colorectal cancer treated by Cetuximab plus chemotherapy.
Br J Cancer
2007
;
96
:
1166
–9.
22
Lievre A, Bachet JB, Boige V, et al. KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab.
J Clin Oncol
2008
;
26
:
374
–9.
23
Poehlmann A, Kuester D, Meyer F, Lippert H, Roessner A, Schneider-Stock R. K-ras mutation detection in colorectal cancer using the Pyrosequencing technique.
Pathol Res Pract
2007
;
203
:
489
–97.
24
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing.
J R Stat Soc
1995
;
57
:
289
–300.
25
Stoehlmacher J, Lenz HJ. Cyclooxygenase-2 inhibitors in colorectal cancer.
Semin Oncol
2003
;
30
:
10
–6.
26
Dandekar DS, Lokeshwar BL. Inhibition of cyclooxygenase (COX)-2 expression by Tet-inducible COX-2 antisense cDNA in hormone-refractory prostate cancer significantly slows tumor growth and improves efficacy of chemotherapeutic drugs.
Clin Cancer Res
2004
;
10
:
8037
–47.
27
Kishi K, Petersen S, Petersen C, et al. Preferential enhancement of tumor radioresponse by a cyclooxygenase-2 inhibitor.
Cancer Res
2000
;
60
:
1326
–31.
28
Oshima M, Dinchuk JE, Kargman SL, et al. Suppression of intestinal polyposis in Apc δ716 knockout mice by inhibition of cyclooxygenase 2 (COX-2).
Cell
1996
;
87
:
803
–9.
29
Tsujii M, Kawano S, DuBois RN. Cyclooxygenase-2 expression in human colon cancer cells increases metastatic potential.
Proc Natl Acad Sci U S A
1997
;
94
:
3336
–40.
30
Tsujii M, Kawano S, Tsuji S, Sawaoka H, Hori M, DuBois RN. Cyclooxygenase regulates angiogenesis induced by colon cancer cells.
Cell
1998
;
93
:
705
–16.
31
Dannenberg AJ, Lippman SM, Mann JR, Subbaramaiah K, DuBois RN. Cyclooxygenase-2 and epidermal growth factor receptor: pharmacologic targets for chemoprevention.
J Clin Oncol
2005
;
23
:
254
–66.
32
Xu K, Shu HK. EGFR activation results in enhanced cyclooxygenase-2 expression through p38 mitogen-activated protein kinase-dependent activation of the Sp1/Sp3 transcription factors in human gliomas.
Cancer Res
2007
;
67
:
6121
–9.
33
Kinoshita T, Takahashi Y, Sakashita T, Inoue H, Tanabe T, Yoshimoto T. Growth stimulation and induction of epidermal growth factor receptor by overexpression of cyclooxygenases 1 and 2 in human colon carcinoma cells.
Biochim Biophys Acta
1999
;
1438
:
120
–30.
34
Pai R, Soreghan B, Szabo IL, Pavelka M, Baatar D, Tarnawski AS. Prostaglandin E2 transactivates EGF receptor: a novel mechanism for promoting colon cancer growth and gastrointestinal hypertrophy.
Nat Med
2002
;
8
:
289
–93.
35
Denkert C, Kobel M, Pest S, et al. Expression of cyclooxygenase 2 is an independent prognostic factor in human ovarian carcinoma.
Am J Pathol
2002
;
160
:
893
–903.
36
Gallo O, Masini E, Bianchi B, Bruschini L, Paglierani M, Franchi A. Prognostic significance of cyclooxygenase-2 pathway and angiogenesis in head and neck squamous cell carcinoma.
Hum Pathol
2002
;
33
:
708
–14.
37
Lurje G, Vallbohmer D, Collet PH, et al. COX-2 mRNA Expression is significantly increased in acid-exposed compared to nonexposed squamous epithelium in gastroesophageal reflux disease.
J Gastrointest Surg
2007
;
11
:
1105
–11.
38
Papafili A, Hill MR, Brull DJ, et al. Common promoter variant in cyclooxygenase-2 represses gene expression: evidence of role in acute-phase inflammatory response.
Arterioscler Thromb Vasc Biol
2002
;
22
:
1631
–6.
39
Cok SJ, Morrison AR. The 3′-untranslated region of murine cyclooxygenase-2 contains multiple regulatory elements that alter message stability and translational efficiency.
J Biol Chem
2001
;
276
:
23179
–85.
40
Hu Z, Miao X, Ma H, et al. A common polymorphism in the 3′UTR of cyclooxygenase 2/prostaglandin synthase 2 gene and risk of lung cancer in a Chinese population.
Lung Cancer
2005
;
48
:
11
–7.
41
Lu Y, Li X, Liang K, et al. Epidermal growth factor receptor (EGFR) ubiquitination as a mechanism of acquired resistance escaping treatment by the anti-EGFR monoclonal antibody cetuximab.
Cancer Res
2007
;
67
:
8240
–7.
42
Moriai T, Kobrin MS, Hope C, Speck L, Korc M. A variant epidermal growth factor receptor exhibits altered type α transforming growth factor binding and transmembrane signaling.
Proc Natl Acad Sci U S A
1994
;
91
:
10217
–21.
43
Zhang W, Gordon M, Schultheis AM, et al. FCGR2A and FCGR3A polymorphisms associated with clinical outcome of epidermal growth factor receptor expressing metastatic colorectal cancer patients treated with single-agent cetuximab.
J Clin Oncol
2007
;
25
:
3712
–8.
44
Zhang W, Park DJ, Lu B, et al. Epidermal growth factor receptor gene polymorphisms predict pelvic recurrence in patients with rectal cancer treated with chemoradiation.
Clin Cancer Res
2005
;
11
:
600
–5.
45
Lurje G, Zhang W, Schultheis AM, et al. Polymorphisms in VEGF and IL-8 predict tumor recurrence in stage III colon cancer.
Ann Oncol
2008
;
19
:
1734
–41.
46
Lanuti M, Liu G, Goodwin JM, et al. A functional epidermal growth factor (EGF) polymorphism, EGF serum levels, and esophageal adenocarcinoma risk and outcome.
Clin Cancer Res
2008
;
14
:
3216
–22.
47
Schultheis AM, Lurje G, Rhodes K, et al. Polymorphisms and Clinical Outcome in Recurrent Ovarian Cancer Treated with Cyclophosphamide and Bevacizumab. Clin Cancer Res. In press 2008.