Purpose:FcγR polymorphisms have been reported to enhance the immune-mediated effects of cetuximab in metastatic colorectal cancer. There are no data on the relationship between these polymorphisms and cetuximab in the early-stage setting. We performed a pharmacogenomic analysis of EXPERT-C, a randomized phase II trial of neoadjuvant CAPOX followed by chemoradiotherapy, surgery, and adjuvant CAPOX ± cetuximab in high-risk, locally advanced rectal cancer.

Experimental Design:FcγRIIa-H131R and FcγRIIIa-V158F polymorphisms were analyzed on DNA from peripheral blood samples. Kaplan–Meier method and Cox regression analysis were used to calculate survival estimates and compare treatment arms.

Results: Genotyping was successfully performed in 105 of 164 (64%) patients (CAPOX = 54, CAPOX-C = 51). No deviation from the Hardy–Weinberg equilibrium or association of these polymorphisms with tumor RAS status was observed. FcγRIIa-131R (HR, 0.38; P = 0.058) and FcγRIIIa-158F alleles (HR, 0.21; P = 0.007) predicted improved progression-free survival (PFS) in patients treated with cetuximab. In the CAPOX-C arm, carriers of both 131R and 158F alleles had a statistically significant improvement in PFS (5 years: 78.4%; HR, 0.22; P = 0.002) and overall survival (OS; 5 years: 86.4%; HR, 0.24; P = 0.018) when compared with patients homozygous for 131H and/or 158V (5-year PFS: 35.7%; 5-year OS: 57.1%). An interaction between cetuximab benefit and 131R and 158F alleles was found for PFS (P = 0.017) and remained significant after adjusting for prognostic variables (P = 0.003).

Conclusion: This is the first study investigating FcγRIIa and FcγRIIIa polymorphisms in patients with early-stage colorectal cancer treated with cetuximab. We showed an increased clinical benefit from cetuximab in the presence of 131R and 158F alleles. Clin Cancer Res; 20(17); 4511–9. ©2014 AACR.

Translational Relevance

The relationship between FcγRIIa and FcγRIIIa polymorphisms and cetuximab benefit in metastatic colorectal cancer has been investigated with controversial results. However, according to preclinical studies, the mechanism of antibody-dependent cell-mediated cytotoxicity (ADCC) may be more relevant in the presence of micrometastatic disease. We found that in a prospective series of patients with locally advanced rectal cancer, carriers of 131R and 158F alleles had an increased clinical benefit from cetuximab and this effect appeared to be independent of RAS. These results suggest the hypothesis of a dual mechanism of action of cetuximab (i.e., inhibition of EGFR downstream signaling pathways prevalent for macroscopic disease and ADCC prevalent for microscopic foci of disease) and may trigger further research into the role of the immune-mediated effects of cetuximab and other monoclonal antibodies in the adjuvant setting.

Cetuximab is a chimeric IgG1 monoclonal antibody which targets the extracellular domain of the EGF receptor (EGFR; ref. 1). Its antitumor activity is largely secondary to the competitive inhibition of EGFR–ligand interactions, prevention of receptor dimerization and autophosphorylation, and blockage of EGFR signaling through the MAPK and PI3K/AKT/mTOR pathways. Following binding to EGFR, cetuximab exerts an inhibitory effect on tumor proliferation, survival, motility, invasion, and angiogenesis (2). Studies showed that the activity of this agent is mainly limited to those patients whose tumors lack mutations of the RAS genes and cetuximab is currently used for the treatment of RAS wild-type metastatic colorectal cancer (3–5).

In contrast with the metastatic setting, cetuximab failed to improve the outcome of patients treated with standard adjuvant chemotherapy (6, 7) and screening for KRAS or RAS mutations did not appear to identify early-stage tumors with increased sensitivity to EGFR inhibition (6–8). In a recent update of the EXPERT-C trial, we showed a nonsignificant improvement in survival with cetuximab in both the KRAS/BRAF wild-type and molecularly unselected population. Moreover, in a retrospective biomarker analysis of this study, patients with TP53 wild-type tumors had significantly better survival outcomes when treated with cetuximab and the association between TP53 status and cetuximab benefit was independent of RAS (9). We hypothesized that antibody-dependent cell-mediated cytotoxicity (ADCC) may have accounted for most of the beneficial effects of cetuximab observed in this trial.

ADCC is an alternative mechanism whereby IgG1 monoclonal antibodies can exert their antitumoral properties (10). ADCC is initiated when the antigen-binding fragment (Fab) and the crystalline fragment (FC) of the monoclonal antibody engage the tumor cell antigen and an FC gamma receptor (FcγR) on an effector cell, respectively (11). As a result, antibody-coated tumor cells are attacked and eliminated by activated natural killer (NK) cells, monocytes, and macrophages.

Three distinct classes of FcγRs (FcγRI, FcγRII, and FcγRIII) have been identified and shown to modulate the antitumor activity of monoclonal antibodies by enhancing or inhibiting their immune-mediated, cytotoxic potential (12–14). Moreover, SNPs in the coding regions of the activating FcγRIIA (C>T substitution at position 131 which changes the amino acid from histidine to arginine) and FcγRIIIA genes (T>G substitution at position 158 which changes the amino acid from valine to phenylalanine) have been reported to correlate with the in vitro antitumor activity and in vivo clinical benefit from rituximab, trastuzumab, and cetuximab (11, 15–17). However, there are currently no available clinical data on the potential role of ADCC when these monoclonal antibodies are administered in the adjuvant setting.

In this study, we analyzed the association between FcγRIIa–FcγRIIIa polymorphisms and cetuximab benefit in a population of patients with high-risk, locally advanced rectal cancer treated within the EXPERT-C trial.

EXPERT-C was an international, multicenter, randomized phase II trial investigating the addition of cetuximab to a sequential treatment strategy with neoadjuvant capecitabine and oxaliplatin (CAPOX) chemotherapy followed by chemoradiotherapy (CRT), total mesorectal excision (TME), and adjuvant CAPOX (18). Patients were randomized in a 1:1 ratio to receive cetuximab throughout the study treatment or not. Eligibility criteria for EXPERT-C have been described in detail previously (18). Briefly, patients had to have a locally advanced rectal adenocarcinoma with high-risk features according to a baseline MRI. Baseline high-risk features included circumferential resection margin involved or at risk (tumor within 1 mm of mesorectal fascia), T3 distal tumor (tumor at/below levators), extramural extension ≥ 5 mm (T3c/T3d), T4 tumor, or presence of extramural vascular invasion. Study procedures, including treatment design, chemotherapy and radiotherapy regimens, timing of surgery, pathologic assessment of surgical specimens, and clinical follow-up, have been previously reported (18).

This study was approved by local ethics committees, and written informed consent was obtained from each patient before study entry.

FcγRIIa and FcγRIIIa polymorphisms analysis

DNA was extracted from peripheral blood mononuclear cells (PBMC) with QIAamp DNA Blood Mini Kit on QIAcube (Qiagen). Polymorphism analyses of FcγRIIa and FcγRIIIa were done as previously described by Bibeau and colleagues, (19), with modifications. Briefly, sequencing analysis of the FcγRIIa was done on Genetic Analyser 3730 (Life Technologies), and results were analyzed using Mutation Surveyor Software (Softgenetics). Multiplex reaction with specific FcγRIIIa-V and FcγRIIIa-F reverse primers were amplified in combination with FcγRIIIa-specific forward primer. Given the high degree of sequence homology between FcγRIIIa and FcγRIIIb, an FcγRIIIa-specific forward primer was used whose 3′ end of the primer is at a one of the regions where the 2 genes differ in exon 4 (i.e., forward primer for FcγRIIIa: TCCAAAAGCCACACTCAAAGAC; homologous sequence in FcγRIIIb: TCCAAAAGCCACACTCAAAGAT). Genetic Analyser 3500 (Life Technologies) was used for the fragment analysis of the FcγRIIIa amplification products in the presence of Hi-Di Formamide (Life Technologies) and GeneScan 500 LIZ Size Standard (Life Technologies). Results were analyzed using GeneMapper Software (Life Technologies).

Tumor molecular analyses

Mutational analyses of KRAS (exons 2–4), NRAS (exons 2–4), and TP53 (exons 4–9) were performed centrally on genomic DNA extracted from formalin-fixed, paraffin-embedded tissue from pretreatment biopsy and/or primary resection samples as previously described (8, 9, 18).

Statistical considerations

The primary endpoint of the EXPERT-C trial was complete response (CR) in patients with KRAS/BRAF wild-type tumors. Radiological response to treatment, pattern of failure, progression-free survival (PFS), and overall survival (OS) were secondary endpoints and calculated as previously reported (18). Distant PFS (DPFS) was measured from date of randomization to date of extrapelvic progression.

The χ2 test was used to assess whether the polymorphic variants of FcγRIIa and FcγRIIIa in the study population were in Hardy–Weinberg equilibrium. The Kaplan–Meier method was used to calculate survival estimates, and comparison of the treatment arms was carried out using a log-rank analysis. HRs and 95% confidence intervals (CI) were obtained from Cox regression.

An interaction term between treatment arm and polymorphism status was included in the Cox regression to test for a significant interaction. Multivariate Cox regression was used to assess whether a significant interaction remained significant after addition of known prognostic variables. Variables were included in the multivariate model using forward selection if P < 0.1.

Of 164 eligible patients enrolled into the EXPERT-C trial, 106 (64.6%) had a baseline blood sample available for genotyping. One patient was not assessable for both FcγRIIa and FcγRIIIa polymorphisms and was not included in this analysis. Of 105 assessable patients, 54 were treated in the CAPOX arm and 51 in the CAPOX-C arm. The study population was representative of the overall trial population (data not shown).

The FcγRIIa and FcγRIIIa genotype frequencies are reported in Table 1. Twenty-five patients (23.8%) were homozygous for FcγRIIa-131H allele, 52 (49.5%) were heterozygous (131H/R), and 28 (26.7%) were homozygous for 131R allele. Thirteen patients (12.4%) were homozygous for FcγRIIIa-158V allele, 48 (45.7%) were heterozygous (158V/F), and 44 (41.9%) were homozygous for 158F allele. The FcγRIIa and FcγRIIIa genotype frequencies were in line with those expected and no deviation from the Hardy–Weinberg equilibrium (FcγRIIa: χ2 = 0.928; FcγRIIIa: χ2 = 0.987) or association with tumor RAS or TP53 status was observed (data not shown). Baseline patient characteristics by FcγR allelic variants were overall balanced between the treatment arms (Supplementary Table S1).

Table 1.

FcγRIIa and FcγRIIIa polymorphisms in the study population by treatment arm

CAPOXCAPOX-C
FcγR polymorphismn (%)n (%)
FcγRIIa 
 HH 14 (25.9) 11 (21.6) 
 HR 27 (50.0) 25 (49.0) 
 RR 13 (24.1) 15 (29.4) 
FcγRIIIa 
 FF 22 (40.7) 22 (43.1) 
 VF 24 (44.4) 24 (47.1) 
 VV 8 (14.8) 5 (9.8) 
FcγRIIa/FcγRIIIa 
 HH and/or VV 17 (31.5) 14 (27.5) 
 R and F 37 (68.5) 37 (72.5) 
CAPOXCAPOX-C
FcγR polymorphismn (%)n (%)
FcγRIIa 
 HH 14 (25.9) 11 (21.6) 
 HR 27 (50.0) 25 (49.0) 
 RR 13 (24.1) 15 (29.4) 
FcγRIIIa 
 FF 22 (40.7) 22 (43.1) 
 VF 24 (44.4) 24 (47.1) 
 VV 8 (14.8) 5 (9.8) 
FcγRIIa/FcγRIIIa 
 HH and/or VV 17 (31.5) 14 (27.5) 
 R and F 37 (68.5) 37 (72.5) 

In the group of patients treated with cetuximab, no statistically significant differences in response to neoadjuvant chemotherapy, CRT, or CR based on the FcγRIIa-H131R or FcγRIII-V158F polymorphisms were observed (Table 2). However, after a median follow-up of 67.4 months, an increased benefit from cetuximab in terms of PFS was found in favor of FcγRIIa-131R carriers (5-year PFS: 72.5% vs. 45.5%; HR, 0.38; 95% CI, 0.14–1.03; P = 0.058) and FcγRIIIa-F carriers (5-year PFS: 71.7% vs. 20.0%; HR, 0.21; 95% CI, 0.07–0.66; P = 0.007) when compared with 131H/H and 158V/V patients, respectively. Patients with FcγRIIa-131R allele had also a significantly better 5-year DPFS (76.4%) than patients homozygous for FcγRIIa-131H (45.5%; HR, 0.30; 95% CI, 0.11–0.85; P = 0.023). A similar difference in OS between the above-mentioned groups was also found; however, this did not reach the statistical significance. In particular, 5-year OS was 82.4% in FcγRIIa-131R carriers versus 63.6% in patients homozygous for 131H allele (HR, 0.42; 95% CI, 0.12–1.45; P = 0.171) and 80.0% in FcγRIIIa-158F carriers versus 60.0% in patients homozygous for 158V allele (HR, 0.33; 95% CI, 0.07–1.55; P = 0.162; Table 3).

Table 2.

Response to neoadjuvant chemotherapy, CRT, and complete response rate by FcγRIIa and FcγRIIIa polymorphisms and treatment

Response rate after neoadjuvant chemotherapy (%)Treatment by FcγR SNP interactionResponse rate after CRT (%)Treatment by FcγR SNP interactionComplete response rate (%)Treatment by FcγR SNP interaction
FcγR polymorphismCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)P
HH 63.6 63.6 0.735 75.0 80.0 0.944 7.1 18.2 0.434 
HR 50.0 65.2  72.0 82.6  14.8 12.0  
RR 41.7 64.3  83.3 85.7  7.7 26.7  
HH 63.6 63.6 0.475 75.7 83.8 0.854 12.5 17.5 0.645 
HR/RR 47.4 64.9  75.0 80.0  7.1 18.2  
VV 33.3 100 0.546 50.0 100 0.976 20.0 0.808 
VF 59.1 56.5  72.7 78.3  8.3 16.7  
FF 47.6 68.2  85.7 86.4  18.2 18.2  
VV 33.3 100 0.999 50.0 100 0.999 20.0 0.999 
VF/FF 53.5 62.2  79.1 82.2  13.0 17.4  
HH and/or VV 57.1 66.7 0.815 73.3 81.8 0.957 5.9 14.3 0.686 
R and F 48.6 63.9  76.5 83.3  13.5 18.9  
Response rate after neoadjuvant chemotherapy (%)Treatment by FcγR SNP interactionResponse rate after CRT (%)Treatment by FcγR SNP interactionComplete response rate (%)Treatment by FcγR SNP interaction
FcγR polymorphismCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)P
HH 63.6 63.6 0.735 75.0 80.0 0.944 7.1 18.2 0.434 
HR 50.0 65.2  72.0 82.6  14.8 12.0  
RR 41.7 64.3  83.3 85.7  7.7 26.7  
HH 63.6 63.6 0.475 75.7 83.8 0.854 12.5 17.5 0.645 
HR/RR 47.4 64.9  75.0 80.0  7.1 18.2  
VV 33.3 100 0.546 50.0 100 0.976 20.0 0.808 
VF 59.1 56.5  72.7 78.3  8.3 16.7  
FF 47.6 68.2  85.7 86.4  18.2 18.2  
VV 33.3 100 0.999 50.0 100 0.999 20.0 0.999 
VF/FF 53.5 62.2  79.1 82.2  13.0 17.4  
HH and/or VV 57.1 66.7 0.815 73.3 81.8 0.957 5.9 14.3 0.686 
R and F 48.6 63.9  76.5 83.3  13.5 18.9  
Table 3.

Survival outcomes by FcγRIIa and FcγRIIIa polymorphisms in the group of patients treated with cetuximab (n = 51)

FcγR SNPs5-y PFS (95% CI)HR (95% CI)P5-y DPFS (95% CI)HR (95% CI)P5-y OS (95% CI)HR (95% CI)P
HH 45.5 (16.1–74.9) 1.0 [0.100] 45.5 (16.1–74.9) 1.0 [0.052] 63.6 (35.2–92.0) 1.0 [0.252] 
HR 80.0 (64.3–95.7) 0.27 (0.08–0.90) 0.032 83.5 (68.6–98.4) 0.21 (0.06–0.74) 0.016 88.0 (75.3–100) 0.28 (0.06–1.27) 0.100 
RR 60.0 (35.3–84.7) 0.57 (0.18–1.77) 0.331 64.3 (39.2–89.4) 0.46 (0.14–1.51) 0.198 72.7 (49.8–95.6) 0.66 (0.16–2.67) 0.567 
HH 45.5 (16.1–74.9) 1.0 0.058 45.5 (16.1–74.9) 1.0 0.023 63.6 (35.2–92.0) 1.0 0.171 
HR/RR 72.5 (58.6–86.4) 0.38 (0.14–1.03)  76.4 (62.9–89.9) 0.30 (0.11–0.85)  82.4 (70.6–94.2) 0.42 (0.12–1.45)  
VV 20.0 (0–55.1) 1.0 [0.017] 33.3 (0–86.7) 1.0 [0.250] 60.0 (17.1–100) 1.0 [0.271] 
VF 62.5 (43.1–81.9) 0.28 (0.09–0.94) 0.039 62.5 (43.1–81.9) 0.54 (0.12–2.53) 0.438 74.2 (59.9–88.5) 0.43 (0.09–2.16) 0.308 
FF 81.8 (65.7–97.9) 0.14 (0.03–0.55) 0.005 81.8 (65.7–97.9) 0.25 (0.05–1.41) 0.117 86.4 (72.1–100) 0.23 (0.04–1.37) 0.107 
VV 20.0 (0–55.1) 1.0 0.007 33.3 (0–86.7) 1.0 0.236 60.0 (17.1–100) 1.0 0.162 
VF/FF 71.7 (58.8–84.6) 0.21 (0.07–0.66)  71.7 (58.8–84.6) 0.41 (0.09–1.81)  80.0 (68.6–91.8) 0.33 (0.07–1.55)  
HH and/or VV 35.7 (10.6–60.8) 1.0 0.002 42.0 (13.9–70.0) 1.0 0.012 57.1 (31.2–83.0) 1.0 0.018 
R and F 78.4 (65.1–91.7) 0.22 (0.08–0.57)  78.4 (65.1–91.7) 0.27 (0.10–0.75)  86.4 (75.2–97.6) 0.24 (0.07–0.78)  
FcγR SNPs5-y PFS (95% CI)HR (95% CI)P5-y DPFS (95% CI)HR (95% CI)P5-y OS (95% CI)HR (95% CI)P
HH 45.5 (16.1–74.9) 1.0 [0.100] 45.5 (16.1–74.9) 1.0 [0.052] 63.6 (35.2–92.0) 1.0 [0.252] 
HR 80.0 (64.3–95.7) 0.27 (0.08–0.90) 0.032 83.5 (68.6–98.4) 0.21 (0.06–0.74) 0.016 88.0 (75.3–100) 0.28 (0.06–1.27) 0.100 
RR 60.0 (35.3–84.7) 0.57 (0.18–1.77) 0.331 64.3 (39.2–89.4) 0.46 (0.14–1.51) 0.198 72.7 (49.8–95.6) 0.66 (0.16–2.67) 0.567 
HH 45.5 (16.1–74.9) 1.0 0.058 45.5 (16.1–74.9) 1.0 0.023 63.6 (35.2–92.0) 1.0 0.171 
HR/RR 72.5 (58.6–86.4) 0.38 (0.14–1.03)  76.4 (62.9–89.9) 0.30 (0.11–0.85)  82.4 (70.6–94.2) 0.42 (0.12–1.45)  
VV 20.0 (0–55.1) 1.0 [0.017] 33.3 (0–86.7) 1.0 [0.250] 60.0 (17.1–100) 1.0 [0.271] 
VF 62.5 (43.1–81.9) 0.28 (0.09–0.94) 0.039 62.5 (43.1–81.9) 0.54 (0.12–2.53) 0.438 74.2 (59.9–88.5) 0.43 (0.09–2.16) 0.308 
FF 81.8 (65.7–97.9) 0.14 (0.03–0.55) 0.005 81.8 (65.7–97.9) 0.25 (0.05–1.41) 0.117 86.4 (72.1–100) 0.23 (0.04–1.37) 0.107 
VV 20.0 (0–55.1) 1.0 0.007 33.3 (0–86.7) 1.0 0.236 60.0 (17.1–100) 1.0 0.162 
VF/FF 71.7 (58.8–84.6) 0.21 (0.07–0.66)  71.7 (58.8–84.6) 0.41 (0.09–1.81)  80.0 (68.6–91.8) 0.33 (0.07–1.55)  
HH and/or VV 35.7 (10.6–60.8) 1.0 0.002 42.0 (13.9–70.0) 1.0 0.012 57.1 (31.2–83.0) 1.0 0.018 
R and F 78.4 (65.1–91.7) 0.22 (0.08–0.57)  78.4 (65.1–91.7) 0.27 (0.10–0.75)  86.4 (75.2–97.6) 0.24 (0.07–0.78)  

Fourteen patients (27.4%) in the CAPOX-C arm were homozygous for 131H and/or 158V allele, whereas 37 (72.6%) carried both 131R and 158F alleles. When these 2 groups were compared, a statistically significant improvement in PFS (HR, 0.22; 95% CI, 0.08–0.57; P = 0.002) and OS (HR, 0.24; 95% CI, 0.07–0.78; P = 0.018) was observed in favor of the 131R and 158F allele carriers (5-year PFS: 78.4%; 95% CI, 65.1–91.7 vs. 35.7%; 95% CI, 10.6–60.8; 5-year OS: 86.4%; 95% CI, 75.2–97.6 vs. 57.1%; 95% CI, 31.2–83.0; Fig. 1). Moreover, 131R and 158F allele carriers were also found to have a lower incidence of distant tumor recurrence at 5 years (21.6%; 95% CI, 8.3–34.9 vs. 58%; 95% CI, 30.0–86.1; HR 0.27; P = 0.012; Table 3).

Figure 1.

Kaplan–Meier curves for PFS and OS in patients homozygous for 131H and/or 158V (A and C) and in carriers of 131R and 158F alleles (B and D).

Figure 1.

Kaplan–Meier curves for PFS and OS in patients homozygous for 131H and/or 158V (A and C) and in carriers of 131R and 158F alleles (B and D).

Close modal

When we also analyzed the outcome of patients treated in the CAPOX control arm according to the FcγRIIa and FcγRIIIa polymorphims, an interaction between cetuximab benefit and presence of 131R and 158F alleles was found for PFS (P = 0.017) and DPFS (P = 0.032). After adjusting for prognostic variables, including World Health Organization (WHO) performance status, T4, RAS status, TP53 status, and skin rash, this interaction remained significant for both PFS (P = 0.003) and DPFS (P = 0.028). An interaction, although not statistically significant, was also observed for OS (P = 0.08, adjusted P value = 0.09; Table 4).

Table 4.

Survival outcomes by FcγRIIa and FcγRIIIa polymorphisms and treatment

5-y PFS (95% CI)Treatment by FcγR SNP interaction5-y DPFS (95% CI)Treatment by FcγR SNP interaction5-y OS (95% CI)Treatment by FcγR SNP interaction
FcγR polymorphismCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)P
HH 61.5 (35.0–88.0) 45.5 (16.1–74.9) 0.088 80.0 (55.3–100) 45.5 (16.1–74.9) 0.051 69.2 (44.1–94.3) 63.6 (35.2–92.0) 0.186 
HR 45.9 (26.5–65.3) 80.0 (64.3–95.7)  63.5 (44.3–82.7) 83.5 (68.6–98.4)  50.2 (30.9–69.4) 88.0 (75.3–100)  
RR 69.2 (44.1–94.3) 60.0 (35.3–84.7)  81.8 (59.1–100) 64.3 (39.2–89.4)  69.2 (44.1–94.3) 72.7 (49.8–95.6)  
HH 61.5 (35.0–88.0) 45.5 (16.1–74.9) 0.096 80.0 (55.3–100) 45.5 (16.1–74.9) 0.042 69.2 (44.1–94.3) 63.6 (35.2–92.0) 0.232 
HR/RR 53.9 (38.2–69.6) 72.5 (58.6–86.4)  69.2 (53.9–84.5) 76.4 (62.9–89.9)  56.6 (41.1–72.1) 82.4 (70.6–94.2)  
VV 42.9 (6.3–79.6) 20.0 (0–55.1) 0.356 80.0 (44.9–100) 33.3 (0–86.6) 0.416 42.9 (6.2–79.6) 60.0 (17.1–100) 0.880 
VF 50.0 (30.0–70.0) 62.5 (43.1–81.9)  70.7 (50.9–90.5) 62.5 (43.1–81.9)  58.3 (38.5–78.1) 74.2 (56.4–92.0)  
FF 67.3 (47.3–87.3) 81.8 (65.7–97.9)  70.8 (51.0–90.6) 81.8 (65.7–97.9)  67.0 (47.0–86.9) 86.4 (72.1–100)  
VV 42.9 (6.3–79.6) 20.0 (0–55.1) 0.157 80.0 (44.9–100) 33.3 (0–86.6) 0.278 42.9 (6.2–79.6) 60.0 (17.1–100) 0.666 
VF/FF 57.9 (43.4–72.4) 71.7 (58.8–84.6)  70.7 (56.8–84.6) 71.7 (58.8–84.6)  62.4 (48.3–76.5) 80.2 (68.6–91.8)  
HH and/or VV 56.3 (32.0–80.6) 35.7 (10.6–60.8) 0.017 75.5 (51.4–99.6) 42.0 (14.0–70.0) 0.032 62.5 (38.8–86.2) 57.1 (31.2–82.9) 0.080 
R and F 55.7 (38.8–72.6) 78.4 (65.1–91.7)  69.8 (54.1–85.5) 78.4 (65.1–91.7)  58.5 (42.4–74.6) 86.4 (75.2–97.6)  
5-y PFS (95% CI)Treatment by FcγR SNP interaction5-y DPFS (95% CI)Treatment by FcγR SNP interaction5-y OS (95% CI)Treatment by FcγR SNP interaction
FcγR polymorphismCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)PCAPOX (n = 54)CAPOX-C (n = 51)P
HH 61.5 (35.0–88.0) 45.5 (16.1–74.9) 0.088 80.0 (55.3–100) 45.5 (16.1–74.9) 0.051 69.2 (44.1–94.3) 63.6 (35.2–92.0) 0.186 
HR 45.9 (26.5–65.3) 80.0 (64.3–95.7)  63.5 (44.3–82.7) 83.5 (68.6–98.4)  50.2 (30.9–69.4) 88.0 (75.3–100)  
RR 69.2 (44.1–94.3) 60.0 (35.3–84.7)  81.8 (59.1–100) 64.3 (39.2–89.4)  69.2 (44.1–94.3) 72.7 (49.8–95.6)  
HH 61.5 (35.0–88.0) 45.5 (16.1–74.9) 0.096 80.0 (55.3–100) 45.5 (16.1–74.9) 0.042 69.2 (44.1–94.3) 63.6 (35.2–92.0) 0.232 
HR/RR 53.9 (38.2–69.6) 72.5 (58.6–86.4)  69.2 (53.9–84.5) 76.4 (62.9–89.9)  56.6 (41.1–72.1) 82.4 (70.6–94.2)  
VV 42.9 (6.3–79.6) 20.0 (0–55.1) 0.356 80.0 (44.9–100) 33.3 (0–86.6) 0.416 42.9 (6.2–79.6) 60.0 (17.1–100) 0.880 
VF 50.0 (30.0–70.0) 62.5 (43.1–81.9)  70.7 (50.9–90.5) 62.5 (43.1–81.9)  58.3 (38.5–78.1) 74.2 (56.4–92.0)  
FF 67.3 (47.3–87.3) 81.8 (65.7–97.9)  70.8 (51.0–90.6) 81.8 (65.7–97.9)  67.0 (47.0–86.9) 86.4 (72.1–100)  
VV 42.9 (6.3–79.6) 20.0 (0–55.1) 0.157 80.0 (44.9–100) 33.3 (0–86.6) 0.278 42.9 (6.2–79.6) 60.0 (17.1–100) 0.666 
VF/FF 57.9 (43.4–72.4) 71.7 (58.8–84.6)  70.7 (56.8–84.6) 71.7 (58.8–84.6)  62.4 (48.3–76.5) 80.2 (68.6–91.8)  
HH and/or VV 56.3 (32.0–80.6) 35.7 (10.6–60.8) 0.017 75.5 (51.4–99.6) 42.0 (14.0–70.0) 0.032 62.5 (38.8–86.2) 57.1 (31.2–82.9) 0.080 
R and F 55.7 (38.8–72.6) 78.4 (65.1–91.7)  69.8 (54.1–85.5) 78.4 (65.1–91.7)  58.5 (42.4–74.6) 86.4 (75.2–97.6)  

Tumor mutational status of RAS was available for 98 of 105 (93.3%) patients. Tumor mutational status of TP53 was available for 94 of 105 (89.5%) patients. Although further stratification by RAS and TP53 status reduced significantly the number of assessable patients in each group, the beneficial effect of cetuximab in the presence of 131R and 158F alleles did not appear to be significantly influenced by the either RAS or TP53 tumor status (Table 5).

Table 5.

Survival outcomes by FcγRIIa and FcγRIIIa polymorphisms and treatment in RAS-mutant versus RAS wild-type patients and TP53-mutant versus TP53 wild-type patients

FcγR polymorphismBiomarker status5-y PFS (95% CI)Treatment by FcγR SNP interaction5-y DPFS (95% CI)Treatment by FcγR SNP interaction5-y OS (95% CI)Treatment by FcγR SNP interaction
CAPOXCAPOX-CPCAPOXCAPOX-CPCAPOXCAPOX-CP
HH and/or VVR and F RAS mutant (n = 46) 44.4 (11.9–76.9) 0 (0–0) 0.071 66.7 (29.1–100) 0 (0–0) 0.108 55.6 (23.1–88.1) 50.0 (0–100) 0.349 
  58.2 (32.5–83.9) 70.6 (48.8–92.3)  74.3 (48.8–99.8) 70.8 (49.0–92.6)  57.8 (31.9–83.7) 81.9 (63.3–100)  
HH and/or VVR and F RAS wild-type (n = 52) 71.4 (37.9–100) 50.0 (10.0–89.9) 0.064 83.3 (53.5–100) 50.0 (10.0–89.9) 0.076 71.4 (37.9–100) 66.7 (29.1–100) 0.182 
  55.0 (32.9–77.1) 84.2 (67.7–100)  68.6 (47.8–89.4) 84.2 (67.7–100)  60.0 (38.4–81.6) 89.5 (75.8–100)  
HH and/or VVR and F TP53 mutant (n = 49) 50.0 (10.0–90.0) 14.3 (0–40.2) 0.070 80.0 (44.9–100) 17.1 (0–47.7) 0.059 50.0 (10.0–90.0) 42.9 (6.2–79.6) 0.281 
  47.6 (21.9–73.3) 63.2 (41.4–84.9)  54.7 (27.3–82.1) 63.2 (41.4–84.9)  54.2 (29.1–79.3) 78.9 (60.5–97.3)  
HH and/or VVR and F TP53 wild-type (n = 45) 60.0 (29.6–90.4) 66.7 (13.4–100) 0.322 75.0 (45.0–100) 66.7 (13.4–100) 0.382 70.0 (41.6–98.4) 100 (100–100) 0.987 
  53.5 (29.4–77.6) 92.9 (79.4–100)  81.6 (62.8–100) 92.9 (79.4–100)  61.1 (38.6–83.6) 93.3 (80.0–100)  
FcγR polymorphismBiomarker status5-y PFS (95% CI)Treatment by FcγR SNP interaction5-y DPFS (95% CI)Treatment by FcγR SNP interaction5-y OS (95% CI)Treatment by FcγR SNP interaction
CAPOXCAPOX-CPCAPOXCAPOX-CPCAPOXCAPOX-CP
HH and/or VVR and F RAS mutant (n = 46) 44.4 (11.9–76.9) 0 (0–0) 0.071 66.7 (29.1–100) 0 (0–0) 0.108 55.6 (23.1–88.1) 50.0 (0–100) 0.349 
  58.2 (32.5–83.9) 70.6 (48.8–92.3)  74.3 (48.8–99.8) 70.8 (49.0–92.6)  57.8 (31.9–83.7) 81.9 (63.3–100)  
HH and/or VVR and F RAS wild-type (n = 52) 71.4 (37.9–100) 50.0 (10.0–89.9) 0.064 83.3 (53.5–100) 50.0 (10.0–89.9) 0.076 71.4 (37.9–100) 66.7 (29.1–100) 0.182 
  55.0 (32.9–77.1) 84.2 (67.7–100)  68.6 (47.8–89.4) 84.2 (67.7–100)  60.0 (38.4–81.6) 89.5 (75.8–100)  
HH and/or VVR and F TP53 mutant (n = 49) 50.0 (10.0–90.0) 14.3 (0–40.2) 0.070 80.0 (44.9–100) 17.1 (0–47.7) 0.059 50.0 (10.0–90.0) 42.9 (6.2–79.6) 0.281 
  47.6 (21.9–73.3) 63.2 (41.4–84.9)  54.7 (27.3–82.1) 63.2 (41.4–84.9)  54.2 (29.1–79.3) 78.9 (60.5–97.3)  
HH and/or VVR and F TP53 wild-type (n = 45) 60.0 (29.6–90.4) 66.7 (13.4–100) 0.322 75.0 (45.0–100) 66.7 (13.4–100) 0.382 70.0 (41.6–98.4) 100 (100–100) 0.987 
  53.5 (29.4–77.6) 92.9 (79.4–100)  81.6 (62.8–100) 92.9 (79.4–100)  61.1 (38.6–83.6) 93.3 (80.0–100)  

To our knowledge, this is the first study that investigated the potential role of FcγRIIa and FcγRIIIa polymorphisms in predicting cetuximab benefit in the perioperative setting of colorectal cancer. We showed that in patients with locally advanced rectal cancer but without radiologic evidence of metastatic disease, polymorphic variants of FcγRIIa and FcγRIIIa were associated with increased clinical benefit from cetuximab. In particular, we found that patients carrying 131R and 158F alleles had better survival than patients homozygous for the 131H and/or 158V alleles when cetuximab was administered in association with systemic chemotherapy and CRT in the perioperative setting.

On the basis of the in vitro data suggesting an increased binding affinity of FcγRIIa and FcγRIIIa for IgG when amino acid changes occur at specific positions in the IgG binding domain, several studies have investigated the predictive role of genetic polymorphisms of these FcγRs in patients treated with cetuximab for metastatic colorectal cancer (19–31). Possibly due to the retrospective design, small numbers, variable endpoints, heterogeneity of patient populations and treatments received in association with cetuximab, and methodological issues, the findings of these studies have been inconsistent (11). As a result, although ADCC may account for some of the antitumor effects of cetuximab, inhibition of the EGFR signaling pathway is generally considered the main mechanism of action of this monoclonal antibody and mutations downstream of EGFR are the only validated markers used to predict treatment outcome and guide patient selection (32).

However, it is legitimate to hypothesize that the main reason for the failure to consistently replicate in vivo the association observed in vitro between genetic polymorphisms of FcγRs and increased activity of cetuximab may be the influence of tumor burden on ADCC against cancer cells. The ability of the immune effector cells to kill antibody-coated tumor cells is dependent on the tumor microenvironment and ADCC may be more effective against micrometastases than large tumor lesions, which are less accessible to immune effector cells and are more likely to have acquired resistance to the mechanisms of immune-mediated cytotoxicity. In support of this contention, a study conducted in intrinsically trastuzumab-resistant, HER-2–positive breast cancer xenografts, the ability of trastuzumab to inhibit tumor growth by ADCC was maintained only in the presence of microscopic disease which simulated the general conditions of adjuvant therapy (33). Moreover, the immune-mediated effects of IgG1 monoclonal antibodies are highly dependent on the functional activity of NK cells which is known to be significantly impaired in patients with advanced disease when compared with patients with early-stage disease or healthy individuals (34, 35).

Altogether, these data suggest the hypothesis of a dual mechanism of action for cetuximab (i.e., inhibition of EGFR downstream signaling pathways prevalent for macroscopic tumor lesions and ADCC prevalent for microscopic foci of disease). We acknowledge that our post hoc, retrospective analysis of a relatively small phase II trial cannot definitively confirm this hypothesis but provides further supportive evidence. Intriguingly, we observed a disconnect between radiologic response of the primary tumor and long-term outcome. Although FcγRIIa-131H and FcγRIIIa-158V polymorphisms predicted favorable survival outcomes with cetuximab, they did not identify patients with a higher rate of tumor response during preoperative treatment or pathologic complete response at the time of surgery. In contrast, we have previously shown that the mutational status of KRAS (or RAS) maintained its predictive value for response of the primary tumor to cetuximab but did not significantly correlate with the potential, long-term beneficial effect of this drug (8, 9). Interestingly, and consistently with the hypothesis of ADCC as an important mechanism of action of cetuximab against micrometastases, we found that carriers of 131R and/or 158F alleles had a significantly lower risk of distant failure than patients homozygous for 131H and/or 158V when cetuximab was added to the study sequential treatment. It is worth noting that additional signaling pathways beyond EGFR (i.e., IGF-1R pathway) which have been shown to cross-talk with EGFR downstream effectors and mediate the ADCC-independent therapeutic effects of cetuximab are more frequently activated and potentially more clinically relevant in rectal cancer than in colon cancer (36–38). Therefore, our findings could be potentially influenced by the specific location of the primary tumor and may not apply to a population of patients with colon cancer.

To assess the predictive value of FcγRs polymorphisms independent of the inhibitory effects of cetuximab on the EGFR signaling pathways, we analyzed treatment outcomes by RAS status (including KRAS exon 2–4 and NRAS exon 2–4). The ability of FcγRIIa-131R and FcγRIIIa-158V alleles to predict cetuximab benefit was largely independent of the status of RAS. Moreover, and in contrast with our initial hypothesis, the predictive value of these polymorphic variants seemed to be independent of TP53. However, the limited number of patients in these subgroup analyses precludes any definitive conclusion. Larger studies are needed to evaluate the role of ADCC in the adjuvant setting in relation to RAS mutations. Moreover, further investigation is necessary to assess whether enhanced ADCC may be the main mechanism underlying the increased beneficial effects of cetuximab previously observed in patients with TP53 wild-type tumors treated in this trial (9).

Our results outlining the predictive role of the 131R allelic form of FcγRIIa are in line with in vitro experiments showing that the presence of arginine at amino acid position 131 is associated with increased binding affinity for IgG1 (12). In contrast, IgG binding studies with innate immune effector cells and the anti-CD20 monoclonal antibody rituximab show that the polymorphic variant 158V has the strongest interaction with IgG and the highest ability to promote the ADCC-related therapeutic response to this agent (39, 40). However, it is reasonable to argue that given the interference from several confounding factors, including the immune-suppression effect of the accompanying chemotherapy agents, the interaction between immune effector cells, monoclonal antibodies, and cancer cells in vivo, may be by far more complex than that simulated in in vitro conditions (41, 42). Moreover, it is worth noting that preclinical studies demonstrated that the different binding affinity of the FcγRIIIa genotypes was maintained at low concentrations but abolished at saturating concentrations of IgG (15, 43), and the 158F allele was found to be predictive of cetuximab benefit in previous retrospective and prospective series (20–22, 28).

For the purpose of this study, an FcγRIIIa-specific primer was used to minimize the risk of amplifying FcγRIIIb. Indeed, the high degree of sequence homology between these genes has represented one of the major difficulties in analyzing the FcγR polymorphisms and likely one of the most important reasons of the large inconsistency between studies. Importantly, the frequencies of FcγR haplotypes and alleles found in our study population were in line with those described in 2 large datasets of the Single Nucleotide Polymorphism Database (dbSNP) of the National Center for Biotechnology Information (NCBI; ss491608261 CSAgilent and ss342007110 ESP cohort populations; ref. 44), and no deviation from the Hardy–Weinberg equilibrium was observed.

We recommend caution in the interpretation of the results of this study, which remain hypothesis-generating. Moreover, the proposed explanation of our findings is speculative and requires confirmation in future pharmacogenomic studies of cetuximab in a similar patient population. Indeed, our analysis has several limitations, including the retrospective design, the limited number of trial patients eligible for genotyping, the overall small number of patients included in the analysis, and the lack of a validation set. Moreover, the inclusion of radiotherapy into the multimodality treatment strategy may have potentially introduced significant biases in the ascertainment of the true predictive effect of FcγR polymorphisms. However, this is the first time that the clinical relevance of cetuximab-associated ADCC in early-stage colorectal cancer has been analyzed in a prospective randomized trial. The data from this study could inform and encourage further investigation of the role of the immune-mediated effects of cetuximab and other monoclonal antibodies in the adjuvant setting.

D. Cunningham reports receiving commercial research grants from Amgen, Merck Serono, Roche, and Sanofi-Aventis. I. Chau is a consultant/advisory board member for Bristol Myers Squibb, Eli-Lilly, Gilead Science, Merck-Serono, Novartis, Roche, and Sanofi Oncology; reports receiving research grants from Merck-Serono, Novartis, Roche, and Sanofi Oncology; and speakers bureau honoraria from Eli-Lilly, Roche, Sanofi-Oncology, and Taiho. No potential conflicts of interest were disclosed by the other authors.

Conception and design: F. Sclafani, D. Cunningham, I. Chau

Development of methodology: G. Brown, I. Chau

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): F. Sclafani, D. Gonzalez de Castro, D. Cunningham, J. Capdevila, B. Glimelius, S. Rosello Keränen, A. Wotherspoon, G. Brown, D. Tait, R. Begum, J. Thomas, J. Oates, I. Chau

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): F. Sclafani, D. Gonzalez de Castro, S. Hulkki Wilson, C. Peckitt, J. Capdevila, I. Chau

Writing, review, and/or revision of the manuscript: F. Sclafani, D. Gonzalez de Castro, D. Cunningham, S. Hulkki Wilson, C. Peckitt, J. Capdevila, B. Glimelius, S. Rosello Keränen, A. Wotherspoon, G. Brown, D. Tait, I. Chau

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): F. Sclafani, D. Gonzalez de Castro, S. Hulkki Wilson, R. Begum, J. Thomas, J. Oates

Study supervision: D. Cunningham

The authors thank all participating patients and staff at EXPERT-C trial sites, all principal investigators, and the Royal Marsden Hospital Research Data Management and Statistics Unit.

This work was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at the Royal Marsden NHS Foundation Trust and Institute of Cancer Research. The EXPERT-C trial was supported by Merck, which provided a research grant and cetuximab, and by Sanofi-Aventis, which provided oxaliplatin; neither was involved in study design, data analysis, or manuscript preparation or had access to study data. The EXPERT-C trial was also supported by the Pelican Cancer Foundation and endorsed by Cancer Research UK. D. Cunningham is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at the Royal Marsden NHS Foundation Trust and Institute of Cancer Research. F. Sclafani is supported by the Peter Stebbings Memorial Charity.

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

1.
Goldstein
NI
,
Prewett
M
,
Zuklys
K
,
Rockwell
P
,
Mendelsohn
J
. 
Biological efficacy of a chimeric antibody to the epidermal growth factor receptor in a human tumor xenograft model
.
Clin Cancer Res
1995
;
1
:
1311
8
.
2.
Foon
KA
,
Yang
XD
,
Weiner
LM
,
Belldegrun
AS
,
Figlin
RA
,
Crawford
J
, et al
Preclinical and clinical evaluations of ABX-EGF, a fully human anti-epidermal growth factor receptor antibody
.
Int J Radiat Oncol Biol Phys
2004
;
58
:
984
90
.
3.
Karapetis
CS
,
Khambata-Ford
S
,
Jonker
DJ
,
O'Callaghan
CJ
,
Tu
D
,
Tebbutt
NC
, et al
K-ras mutations and benefit from cetuximab in advanced colorectal cancer
.
N Engl J Med
2008
;
359
:
1757
65
.
4.
Van Cutsem
E
,
Köhne
CH
,
Láng
I
,
Folprecht
G
,
Nowacki
MP
,
Cascinu
S
, et al
Cetuximab plus irinotecan, fluorouracil, and leucovorin as first-line treatment for metastatic colorectal cancer: updated analysis of overall survival according to tumor KRAS and BRAF mutation status
.
J Clin Oncol
2011
;
29
:
2011
9
.
5.
Stintzing
S
,
Jung
A
,
Rossius
L
,
Modest
DP
,
Fischer von Weikersthal
L
,
Decker
T
, et al
Analysis of KRAS/NRAS and BRAF mutations in FIRE-3: a randomized phase III study of FOLFIRI plus cetuximab or bevacizumab as first-line treatment for wild-type (WT) KRAS (exon 2) metastatic colorectal cancer (mCRC) patients
.
Eur Cancer Congr (ECCO-ESMO-ESTRO)
2013
;
abstract nr LBA17
.
6.
Alberts
SR
,
Sargent
DJ
,
Nair
S
,
Mahoney
MR
,
Mooney
M
,
Thibodeau
SN
, et al
Effect of oxaliplatin, fluorouracil, and leucovorin with or without cetuximab on survival among patients with resected stage III colon cancer
.
JAMA
2012
;
307
:
1383
93
.
7.
Taieb
J
,
Tabernero
J
,
Mini
E
,
Subtil
F
,
Folprecht
G
,
Van
Laethem JL
, et al
Oxaliplatin, fluorouracil, and leucovorin with or without cetuximab in patients with resected stage III colon cancer (PETACC-8): an open-label, randomised phase 3 trial
.
Lancet Oncol
2014
;
15
:
862
73
.
8.
Sclafani
F
,
Gonzalez
D
,
Cunningham
D
,
Hulkki Wilson
S
,
Peckitt
C
,
Giralt
J
, et al
RAS Mutations and Cetuximab in Locally Advanced Rectal Cancer: Results of the EXPERT-C Trial
.
Eur J Cancer
2014
;
50
:
1430
6
.
9.
Sclafani
F
,
Gonzalez
D
,
Cunningham
D
,
Hulkki
Wilson S
,
Peckitt
C
,
Tabernero
J
, et al
TP53 mutational status and cetuximab benefit in rectal cancer: 5-year results of the EXPERT-C trial
.
J Natl Cancer Inst
2014
;
106(7)
.
10.
Weiner
LM
,
Surana
R
,
Wang
S
. 
Monoclonal antibodies: versatile platforms for cancer immunotherapy
.
Nat Rev Immunol
2010
;
10
:
317
27
.
11.
Mellor
JD
,
Brown
MP
,
Irving
HR
,
Zalcberg
JR
,
Dobrovic
A
. 
A critical review of the role of Fc gamma receptor polymorphisms in the response to monoclonal antibodies in cancer
.
J Hematol Oncol
2013
;
6
:
1
.
12.
Warmerdam
PA
,
van de Winkel
JG
,
Vlug
A
,
Westerdaal
NA
,
Capel
PJ
. 
A single amino acid in the second Ig-like domain of the human Fc gamma receptor II is critical for human IgG2 binding
.
J Immunol
1991
;
147
:
1338
43
.
13.
Clark
MR
,
Clarkson
SB
,
Ory
PA
,
Stollman
N
,
Goldstein
IM
. 
Molecular basis for a polymorphism involving Fc receptor II on human monocytes
.
J Immunol
1989
;
143
:
1731
4
.
14.
Clynes
RA
,
Towers
TL
,
Presta
LG
,
Ravetch
JV
. 
Inhibitory Fc receptors modulate in vivo cytoxicity against tumor targets
.
Nat Med
2000
;
6
:
443
6
.
15.
Dall'Ozzo
S
,
Tartas
S
,
Paintaud
G
,
Cartron
G
,
Colombat
P
,
Bardos
P
, et al
Rituximab-dependent cytotoxicity by natural killer cells: influence of FCGR3A polymorphism on the concentration-effect relationship
.
Cancer Res
2004
;
64
:
4664
9
.
16.
Musolino
A
,
Naldi
N
,
Bortesi
B
,
Pezzuolo
D
,
Capelletti
M
,
Missale
G
, et al
Immunoglobulin G fragment C receptor polymorphisms and clinical efficacy of trastuzumab-based therapy in patients with HER-2/neu–positive metastatic breast cancer
.
J Clin Oncol
2008
;
26
:
1789
96
.
17.
Taylor
RJ
,
Chan
SL
,
Wood
A
,
Voskens
CJ
,
Wolf
JS
,
Lin
W
, et al
FcgammaRIIIa polymorphisms and cetuximab induced cytotoxicity in squamous cell carcinoma of the head and neck
.
Cancer Immunol Immunother
2009
;
58
:
997
1006
.
18.
Dewdney
A
,
Cunningham
D
,
Tabernero
J
,
Capdevila
J
,
Glimelius
B
,
Cervantes
A
, et al
Multicenter randomized phase II clinical trial comparing neoadjuvant oxaliplatin, capecitabine, and preoperative radiotherapy with or without cetuximab followed by total mesorectal excision in patients with high-risk rectal cancer (EXPERT-C)
.
J Clin Oncol
2012
;
30
:
1620
7
.
19.
Bibeau
F
,
Lopez-Crapez
E
,
Di Fiore
F
,
Thezenas
S
,
Ychou
M
,
Blanchard
F
, et al
Impact of FcγRIIa-FcγRIIIa polymorphisms and KRAS mutations on the clinical outcome of patients with metastatic colorectal cancer treated with cetuximab plus irinotecan
.
J Clin Oncol
2009
;
27
:
1122
9
.
20.
Zhang
W
,
Gordon
M
,
Schultheis
AM
,
Yang
DY
,
Nagashima
F
,
Azuma
M
, 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
.
21.
Zhang
W
,
Azuma
M
,
Lurje
G
,
Gordon
MA
,
Yang
D
,
Pohl
A
, et al
Molecular predictors of combination targeted therapies (cetuximab, bevacizumab) in irinotecan-refractory colorectal cancer (BOND-2 study)
.
Anticancer Res
2010
;
30
:
4209
17
.
22.
Dahan
L
,
Norguet
E
,
Etienne-Grimaldi
MC
,
Formento
JL
,
Gasmi
M
,
Nanni
I
, et al
Pharmacogenetic profiling and cetuximab outcome in patients with advanced colorectal cancer
.
BMC Cancer
2011
;
11
:
496
.
23.
Paez
D
,
Pare
L
,
Espinosa
I
,
Salazar
J
,
del Rio
E
,
Barnadas
A
, et al
Immunoglobulin G fragment C receptor polymorphisms and KRAS mutations: are they useful biomarkers of clinical outcome in advanced colorectal cancer treated with anti-EGFR-based therapy?
Cancer Sci
2010
;
101
:
2048
53
.
24.
Rodriguez
J
,
Zarate
R
,
Bandres
E
,
Boni
V
,
Hernández
A
,
Sola
JJ
, et al
Fc gamma receptor polymorphisms as predictive markers of cetuximab efficacy in epidermal growth factor receptor downstream-mutated metastatic colorectal cancer
.
Eur J Cancer
2012
;
48
:
1774
80
.
25.
Etienne-Grimaldi
MC
,
Bennouna
J
,
Formento
JL
,
Douillard
JY
,
Francoual
M
,
Hennebelle
I
, et al
Multifactorial pharmacogenetic analysis in colorectal cancer patients receiving 5-fluorouracil-based therapy together with cetuximab- irinotecan
.
Br J Clin Pharmacol
2012
;
73
:
776
85
.
26.
Nakadate
Y
,
Kodera
Y
,
Kitamura
Y
,
Shirasawa
S
,
Tachibana
T
,
Tamura
T
, et al
KRAS mutation confers resistance to antibody dependent cellular cytotoxicity of cetuximab against human colorectal cancer cells
.
Int J Cancer
2014
;
134
:
2146
55
.
27.
Park
SJ
,
Hong
YS
,
Lee
JL
,
Ryu
MH
,
Chang
HM
,
Kim
KP
, et al
Genetic polymorphisms of FcγRIIa and FcγRIIIa are not predictive of clinical outcomes after cetuximab plus irinotecan chemotherapy in patients with metastatic colorectal cancer
.
Oncology
2012
;
82
:
83
9
.
28.
Pander
J
,
Gelderblom
H
,
Antonini
NF
,
Tol
J
,
van Krieken
JH
,
van der Straaten
T
, et al
Correlation of FCGR3A and EGFR germline polymorphisms with the efficacy of cetuximab in KRAS wild-type metastatic colorectal cancer
.
Eur J Cancer
2010
;
46
:
1829
34
.
29.
Calemma
R
,
Ottaiano
A
,
Trotta
AM
,
Nasti
G
,
Romano
C
,
Napolitano
M
, et al
Fc gamma receptor IIIa polymorphisms in advanced colorectal cancer patients correlated with response to anti-EGFR antibodies and clinical outcome
.
J Transl Med
2012
;
10
:
232
.
30.
Negri
FV
,
Musolino
A
,
Naldi
N
,
Bortesi
B
,
Missale
G
,
Laccabue
D
, et al
Role of immunoglobulin G fragment C receptor polymorphism-mediated antibody-dependant cellular cytotoxicity in colorectal cancer treated with cetuximab therapy
.
Pharmacogenomics J
2014
;
14
:
14
9
.
31.
Geva
R
,
Jensen
BV
,
Fountzilas
G
,
Yoshino
T
,
Paez
D
,
Montagut
C
, et al
An international consortium study in chemorefractory metastatic colorectal cancer (mCRC) patients (pts) to assess the impact of FCGR polymorphisms on cetuximab efficacy
.
J Clin Oncol
29
: 
2011
(
suppl; abstr 3528
).
32.
De Roock
W
,
De Vriendt
V
,
Normanno
N
,
Ciardiello
F
,
Tejpar
S
. 
KRAS, BRAF, PIK3CA, and PTEN mutations: implications for targeted therapies in metastatic colorectal cancer
.
Lancet Oncol
2011
;
12
:
594
603
.
33.
Barok
M
,
Isola
J
,
Pályi-Krekk
Z
,
Nagy
P
,
Juhász
I
,
Vereb
G
, et al
Trastuzumab causes antibody-dependent cellular cytotoxicity−mediated growth inhibition of submacroscopic JIMT-1 breast cancer xenografts despite intrinsic drug resistance
.
Mol Cancer Ther
2007
;
6
:
2065
72
.
34.
Abdullah
N
,
Greenman
J
,
Pimenidou
A
,
Topping
KP
,
Monson
JR
. 
The role of monocytes and natural killer cells in mediating antibody-dependent lysis of colorectal tumour cells
.
Cancer Immunol Immunother
1999
;
48
:
517
24
.
35.
Kono
K
,
Takahashi
A
,
Ichihara
F
,
Sugai
H
,
Fujii
H
,
Matsumoto
Y
. 
Impaired antibody-dependent cellular cytotoxicity mediated by herceptin in patients with gastric cancer
.
Cancer Res
2002
;
62
:
5813
7
.
36.
Hu
YP
,
Patil
SB
,
Panasiewicz
M
,
Li
W
,
Hauser
J
,
Humphrey
LE
, et al
Heterogeneity of receptor function in colon carcinoma cells determined by cross-talk between type I insulin-like growth factor receptor and epidermal growth factor receptor
.
Cancer Res
2008
;
68
:
8004
13
.
37.
Scartozzi
M
,
Mandolesi
A
,
Giampieri
R
,
Pierantoni
C
,
Loupakis
F
,
Zaniboni
A
, et al
Insulin-like growth factor 1 expression correlates with clinical outcome in K-RAS wild type colorectal cancer patients treated with cetuximab and irinotecan
.
Int J Cancer
2010
;
127
:
1941
7
.
38.
Hong
TS
,
Clark
JW
,
Haigis
KM
. 
Cancers of the colon and rectum: identical or fraternal twins?
Cancer Discov
2012
;
2
:
117
21
.
39.
Koene
HR
,
Kleijer
M
,
Algra
J
,
Roos
D
,
von dem Borne
AE
,
de Haas
M
. 
FcgRIIIa-158V/F polymorphism influences the binding of IgG by natural killer cell FcgRIIIa, independently of the FcgRIIIa-48L/R/H phenotype
.
Blood
1997
;
90
:
1109
14
.
40.
Weng
WK
,
Levy
R
. 
Two immunoglobulin G fragment C receptor polymorphisms independently predict response to rituximab in patients with follicular lymphoma
.
J Clin Oncol
2003
;
21
:
3940
7
.
41.
Correale
P
,
Marra
M
,
Remondo
C
,
Migali
C
,
Misso
G
,
Arcuri
FP
, et al
Cytotoxic drugs up-regulate epidermal growth factor receptor (EGFR) expression in colon cancer cells and enhances their susceptibility to EGFR- targeted antibody-dependent cell-mediated cytotoxicity
.
Eur J Cancer
2010
;
46
:
1703
11
.
42.
De Souza
AP
,
Bonorino
C
. 
Tumor immunosuppressive environment: effects on tumor-specific and nontumor antigen immune responses
.
Expert Rev Anticancer Ther
2009
;
9
:
1317
32
.
43.
Congy-Jolivet
N
,
Bolzec
A
,
Ternant
D
,
Ohresser
M
,
Watier
H
,
Thibault
G
. 
Fc gamma RIIIa expression is not increased on natural killer cells expressing the Fc gamma RIIIa-158V allotype
.
Cancer Res
2008
;
68
:
976
80
.
44.
Single Nucleotide Polymorphism Database (dbSNP) of the National Cancer Center for Biotechnology Information(NCBI):dbSNP [cited 2014 May 1]. Available from
: http://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?searchType=adhoc_search&type=rs&rs=rs396991.