Literature DB >> 21694725

EGFR gene copy number assessment from areas with highest EGFR expression predicts response to anti-EGFR therapy in colorectal cancer.

A Ålgars1, M Lintunen, O Carpén, R Ristamäki, J Sundström.   

Abstract

BACKGROUND: Only 40-70% of metastatic colorectal cancers (mCRCs) with wild-type (WT) KRAS oncogene respond to anti-epidermal growth factor receptor (anti-EGFR) antibody treatment. EGFR amplification has been suggested as an additional marker to predict the response. However, improved methods for bringing the EGFR analysis into routine laboratory are needed.
METHODS: The material consisted of 80 patients with mCRC, 54 of them receiving anti-EGFR therapy. EGFR gene copy number (GCN) was analysed by automated silver in situ hybridisation (SISH). Immunohistochemical EGFR protein analysis was used to guide SISH assessment.
RESULTS: Clinical benefit was seen in 73% of high (≥ 4.0) EGFR GCN patients, in comparison with 59% of KRAS WT patients. Only 20% of low EGFR GCN patients responded to therapy. A high EGFR GCN number associated with longer progression-free survival (P<0.0001) and overall survival (P=0.004). Together with KRAS analysis, EGFR GCN identified the responsive patients to anti-EGFR therapy more accurately than either test alone. The clinical benefit rate of KRAS WT/high EGFR GCN tumours was 82%.
CONCLUSION: Our results show that automated EGFR SISH, in combination with KRAS mutation analysis, can be a useful and easily applicable technique in routine diagnostic practise for selecting patients for anti-EGFR therapy.

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Year:  2011        PMID: 21694725      PMCID: PMC3142805          DOI: 10.1038/bjc.2011.223

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


The major prognostic determinant for patients with advanced colorectal cancer (CRC) with non-resectable metastases is the response to systemic therapy (Cunningham ). For part of these patients, recent advances, including anti-epidermal growth factor receptor (EGFR) therapy have added clinical benefit and extended the median survival time (Cunningham ; Douillard ; Grothey, 2010; Peeters ). Tumours harbouring activating mutations of KRAS, a signalling molecule downstream of EGFR, do no benefit from the anti-EGFR monoclonal antibodies cetuximab and panitumumab (Linardou ; Allegra ). In KRAS wild-type (WT) patients, on the other hand, the addition of cetuximab to cytotoxic treatment in first line improves the response rates with 16–24% compared with cytotoxic therapy alone. However, about 40% of the previously untreated (Bokemeyer ; Chang ; Van Cutsem ) and about 60–70% of the previously treated (Moroni ; Lievre , 2008; Chang ) KRAS WT patients do not respond to anti-EGFR treatment combined with chemotherapy. Consequently, there is a need for predictive markers among the KRAS WT patients. Changes in molecules downstream of EGFR, in particular BRAF gene mutations, PIK3CA mutations and loss of expression of the PTEN tumour-suppressor protein appear to associate with resistance to anti-EGFR treatment (Laurent-Puig ; Siena ). However, even the combination of these is likely to identify only a minority of non-responsive KRAS WT patients (Laurent-Puig ). Unlike the EGFR protein expression level assessed by immunohistochemistry (IHC) (Cunningham ; Saltz ; Chung ), an increased EGFR gene copy number (GCN) has been associated with a favourable response to anti-EGFR therapy among KRAS WT patients (Moroni ; Lievre ; Sartore-Bianchi ; Cappuzzo ). Fluorescence in situ hybridisation (FISH) technique has been used in most previous studies (Moroni ; Sartore-Bianchi ; Cappuzzo ; Personeni ; Scartozzi ). The FISH results are challenging to interpret and the lack of standardisation of analytical methods and scoring systems may partly explain why the EGFR GCN evaluation has not been incorporated into the clinical practice yet (Martin ). Silver in situ hybridisation (SISH) is a technique that can be applied to automated detection of EGFR GCN and chromosome 7 (Chr-7) number. SISH-based EGFR GCN can be easily performed, because it can be analysed by conventional bright field light microscopy. In addition, the chromogen of SISH is very stable unlike fluorochromes in FISH. The aim of this study was to evaluate the predictive value of EGFR GCN and Chr-7 number assessed by SISH from areas with highest IHC reactivity in patients with metastatic or locally advanced CRC treated with anti-EGFR monoclonal antibody therapy. The correlation between EGFR GCN and EGFR protein expression, as determined by IHC, was also evaluated, since previous reports have been conflicting (Shia ; Spindler ; Frattini ; Hemmings ).

Patients and methods

Patients

This retrospective study comprises a series of 80 metastatic or locally advanced CRC patients, 62 of whom were treated with anti-EGFR therapy at the Turku University Hospital. In all, 50% of the patients had metastatic disease at the time of diagnosis. The median age of the patients at diagnosis was 60 years (range, 34–73). Patient characteristics and treatments are presented in Table 1. Ten of the treated patients had a mutation in the KRAS gene, as the anti-EGFR therapy was administered before establishment of the predictive value of KRAS testing. The treatment response could be reliably evaluated for 54 out of 62 (87%) of treated patients. Of those, 25 KRAS WT patients received cetuximab or panitumumab either as single therapy or irinotecan combination therapy in a chemorefractory phase of the disease (⩾third line therapy). The response to anti-EGFR treatment was evaluated by computed tomography or magnetic resonance imaging according to the Response Evaluation Criteria in Solid Tumours (Eisenhauer ). The study was conducted in accordance with the Declaration of Helsinki. The clinical data were retrieved and histological samples collected and analysed with the endorsement of the National Authority for Medico-Legal Affairs.
Table 1

Baseline characteristics of patients who underwent SISH for EGFR and chromosome 7 and analysis of KRAS gene mutational status (a) and the subgroup of these patients that received anti-EGFR therapy with evaluable treatment response and sufficient follow up data (b)

  (a) Eligible patients for KRAS mutational status analysis, EGFR and chromosome 7 SISH analysis (n=80) (b) Patients treated with anti-EGFR therapy (n=54)
  KRAS WT and MT, n=80 KRAS WT, n=44 KRAS MT, n=10
  n (%) n (%) n (%)
Sex
 Female34 (42)18 (40.9)6 (60)
 Male46 (58)26 (59.1)4 (40)
    
Site of primary tumour
 Colon51 (63.8)32 (72.7)6 (60)
 Rectum28 (35)12 (27.3)4 (40)
 Unknown1 (1.2)  
    
Metastatic sites
 Single28 (35)19 (43.2)2 (20)
 Multiple52 (65)25 (56.8)8 (80)
    
Tumour differentiation grade
 Grade 111 (13.8)6 (13.6)1 (10)
 Grade 250 (62.5)28 (63.7)6 (60)
 Grade 313 (16.2)6 (13.6)2 (20)
 Unknown6 (7.5)4 (9.1)1 (10)
    
Follow-up data of the patients
 Alive with disease16 (20)10 (22.7)
 Alive and free of disease5 (6.2)1 (2.3)
 Died of disease59 (73.8)33 (75)10 (100)
    
KRAS mutational status
KRAS WT54 (67.5)44 (100)
KRAS MT24 (30)10 (100)
 Not evaluable2 (2.5)
    
Anti-EGFR treatment
 Cetuximab51 (63.8)35 (79.5)10 (100)
 Panitumumab10 (12.5)8 (18.2)
 Both1 (1.2)1 (2.3)
 None18 (22.5)
    
Line of therapy
 First8 (12.9)5 (11.4)1 (10)
 Second14 (22.6)12 (27.3)
 Third or more40 (64.5)27 (61.3)9 (90)
    
Anti-EGFR combination therapy
 Anti-EGFR combined to IRI46 (74.2)32 (72.7)9 (90)
 Anti-EGFR combined to OXA10 (16.1)8 (18.2)1 (10)
 Anti-EGFR combined to CAP2 (3.2)1 (2.3)
 Single treatment4 (6.5)3 (6.8)

Abbreviations: CAP=capecitabine; EGFR=epidermal growth factor receptor; IRI=irinotecan; MT=mutated; OXA=oxaliplatin; SISH=silver in situ hybridization; WT=wild type.

Procedures

Formalin-fixed, paraffin-embedded samples with at least 30% of CRC cells were selected and analysed for KRAS point mutations within codons 12 and 13 with the DxS K-RAS mutation kit (DxS Ltd, Manchester, UK). In all, 3μm sections were stained with two monoclonal antibodies against EGFR (VentanaMedical Systems/Roche Diagnostics, Tucson, AZ, USA). EGFR (clone 3C6) mAb is directed against the extracellular domain of human EGFR, and EGFR (clone 5B7) mAb against the internal domain of human EGFR. All 80 tumour specimens were stained with the 5B7 anti-EGFR antibody and 74 tumour samples with the 3C6 anti-EGFR antibody. Stainings were performed with BenchMark XT (Ventana/Roche) using ultraVIEW Universal DAB Detection Kit (Ventana/Roche). EGFR IHC was scored independently by three observers (OC, JS, and ML) blinded of the clinical information. Three scoring parameters were recorded: the highest (covering at least 10% of the tumour area), the most common staining intensity, and the localisation of staining (membranous, cytoplasmic or both). Four categories of staining intensity were used: 0 (negative), + (weak), ++ (moderate), and +++ (strong, similar to the intensity of the epidermal basal layer). In cases of discordance, a consensus score was used. EGFR gene was detected from 5μm sections with EGFR DNA Probe (Ventana/Roche) and Chr-7 from parallel sections with Chr-7 oligonucleotide Probe (Ventana/Roche). SISH was performed with the BenchMark XT using ultraVIEW SISH Detection Kit (Ventana/Roche). From each tumour EGFR GCN (number of copies of gene per cell) and Chr-7 number (number of copies of chromosome per cell) were analysed by two observers (ML and JS) from the area of highest IHC reactivity. Forty tumour cells with the highest number of copies were analysed from the EGFR SISH slides. In addition to the average EGFR GCN and Chr-7 number, EGFR/Chr-7 copy number ratio was assessed. FISH analysis with Vysis EGFR/CEP 7 FISH Probe Kit (Abbott Molecular Inc., Des Plaines, IL, USA) was performed on nine samples selected based on EGFR SISH results (three samples with clusters, three samples with more than four copies, and three samples with normal two copies), using standard protocols.

Statistical analysis

Statistical analyses were performed with the SAS 9.2 and Enterprise Guide 4.2 programs (SAS Institute Inc., Cary, NC, USA). Frequency table data were analysed with the χ2-test or Fisher's exact test. Spearman correlation coefficients were calculated when correlations were analysed. The optimal cut-off values for EGFR GCN and Chr-7 number were defined with the receiver operating characteristic (ROC) analysis generated on response to treatment (clinical benefit vs progressive disease (PD)). Kaplan–Meier and log-rank tests as well as Cox proportional hazards regression model were used for univariate survival analysis. When analysing progression-free survival (PFS), the survival time was calculated from the onset of anti-EGFR treatment until disease progression. When evaluating the overall survival (OS), the survival time was calculated from the onset of anti-EGFR therapy until death. Multivariate survival analysis was carried out by using Cox's proportional hazards regression model. All statistical tests were two-sided. P-values <0.05 were considered to be statistically significant.

Results

EGFR IHC and EGFR and Chr-7 SISH analysis

Owing to the chromogenic detection method of EGFR GCN and EGFR protein, it was possible to assess both parameters from identical tumour areas and to compare the results. The EGFR protein expression levels and subcellular localisations were examined by two different anti-EGFR antibodies: clone 5B7 against the intracellular domain and clone 3C6 against the extracellular domain, hereafter referred to as intracellular and extracellular domain antibodies, respectively. In general, the intensity and subcellular localisation of IHC reactivity showed considerable intratumoural variation with both antibodies (Figure 1). Therefore, the following parameters were determined: localisation, highest, and most common intensity. The results obtained with the two different antibodies statistically significantly correlated with each other disregarding the parameter used (P<0.0001, Spearman). The most intense areas were scored as moderate (++) in a majority of the tumours, while only one-tenth of the tumours showed areas of strong intensity (+++). The most common EGFR staining intensity was low (+) with both antibodies. The frequencies of these parameters are presented in Table 2.
Figure 1

Epidermal growth factor receptor immunohistochemistry, EGFR, and Chr-7 SISH in colorectal cancer and normal colorectal tissues. Epidermal growth factor receptor IHC with clones 5B7 (A) and 3C6 (B). EGFR SISH revealing gene clusters (C) and the corresponding Chr-7 SISH (D). EGFR SISH with GCN ⩾4.0 (E) and the corresponding Chr-7 SISH (F). EGFR SISH (G) and Chr-7 SISH (H) in normal colorectal tissue. Scale bar 0.05 mm (A, B), 0.02 mm (C–H).

Table 2

EGFR protein expression assessed by anti-EGFR clone 5B7 (n=80) and anti-EGFR clone 3C6 antibodies (n=74)

  5B7 (H) 5B7 (C) 3C6 (H) 3C6 (C)
Intensity
 Negative0 (0)11 (13.8)9 (12.2)31 (41.9)
 1+19 (23.8)50 (62.5)20 (27.0)37 (50.0)
 2+53 (66.2)19 (23.7)38 (51.3)6 (8.1)
 3+8 (10)0 (0)7 (9.5)0 (0)
     
Localisation
 Membranous23 (28.75)11 (13.75)24 (32.4)11 (14.9)
 Cytoplasmic23 (28.75)46 (57.5)18 (24.3)28 (37.8)
 Both34 (42.5)12 (15)23 (31.1)4 (5.4)
 Negative0 (0)11 (13.75)9 (12.2)31 (41.9)

Abbreviations: C=most common staining; EGFR=epidermal growth factor receptor; H=highest staining.

Values are given n (%).

The marked variation in EGFR expression as analysed by IHC might reflect an intratumoural variation in the EGFR GCN. Therefore, we assessed the EGFR GCN and Chr-7 number from areas with strongest EGFR staining. The mean EGFR GCN was 5.5 (median 5.5) and the mean Chr-7 number 5.4 (median 5.3). The optimal cut-off values for EGFR GCN and Chr-7 number as determined with ROC curves were 4.0 (sensitivity 86%, specificity 72%, AUC 83%) and 4.5 (sensitivity 84%, specificity 79%, AUC 85%), respectively. The optimal cut-off value for EGFR GCN was in addition defined with ROC analysis for the selected patients with chemorefractory disease who received anti-EGFR therapy±irinotecan in ⩾third line. The cut-off value proved to be 4.0 (sensitivity 89%, specificity 67%, AUC 84%) in this patient group as well. In all, 51 tumours out of 80 (64%) had an EGFR GCN above cut-off value determined by ROC-analysis (⩾4.0). The EGFR GCN analysis by SISH could not be performed in 2 out of 80 (2.5%) of the cases. Chr-7 number was above the cut-off value (⩾4.5) in 48 out of 80 (60%) of the tumours. The highest EGFR/Chr-7 GCN ratio was 2.8 (mean 1.05, median 1.0). The EGFR FISH results from nine selected tumours correlated with the SISH results. An increased EGFR GCN and Chr-7 number correlated positively with EGFR IHC analysed by the intracellular domain antibody (Spearman, P=0.01 for both) (Table 3). The correlation remained statistically significant when the staining intensity (IHC) was dichotomised into categories 0 and + vs ++ and +++. A significant correlation between extracellular domain antibody reactivity and an increased Chr-7 number was seen (Spearman, P=0.04), whereas, no correlation was observed between extracellular domain antibody reactivity and EGFR GCN. The subcellular localisation of the EGFR IHC (intracellular and extracellular domain antibodies) did not correlate with EGFR GCN or the Chr-7 number. KRAS mutational status did not correlate either with EGFR and Chr-7 SISH or EGFR IHC results.
Table 3

Correlations of EGFR GCN (SISH), Chr-7 number (SISH), KRAS status and EGFR protein expression (IHC), n=74 (P-values, Spearman)

  KRAS status EGFR GCN (SISH) continuous variable Chr-7 (SISH) continuous variable
Anti-EGFR clone 5B7, intensity
 HighestNS0.01*0.01*
 Most commonNSNSNS
 Positive or negativeNS0.01*0.04*
    
Anti-EGFR clone 3C6, intensity
 HighestNSNS0.04*
 Most commonNSNSNS
 Positive or negativeNSNSNS
    
Localisation
 5B7§NSNSNS
 3C6§NSNSNS
    
EGFR GCN (SISH)
 Continuous variableNS<0.0001*
 Cut-off 4.0NS
    
Chr-7 number (SISH)
 Continuous variableNS<0.0001*
 Cut-off 4.5NS

Abbreviations: Chr-7=chromosome-7; EGFR=epidermal growth factor receptor; GCN=gene copy number; IHC=immunohistochemistry; NS=not significant; SISH=silver in situ hybridisation; *Significant P-value; †0, 1+, 2+, or 3+ ≠Positive 2+ or 3+, negative 0, or 1+ §Membranous, cytoplasmic, both cytoplasmic and membranous or negative.

EGFR SISH and treatment response

In all, 73% of high EGFR GCN (⩾4.0) patients showed clinical benefit (complete response (CR)+partial response (PR)+stable disease (SD)) from anti-EGFR therapy, whereas only 20% of low EGFR GCN (<4.0) benefited from treatment (Figure 2). In comparison, 59% of the KRAS WT patients showed clinical benefit. In KRAS WT patients with a high EGFR GCN (⩾4.0), clinical benefit was more frequent (82%) than in the overall KRAS WT or high EGFR GCN population. A high Chr-7 number (⩾4.5) was also significantly associated with an improved anti-EGFR treatment response among KRAS WT patients.
Figure 2

Response to anti-EGFR therapy according to EGFR GCN, Chr-7 number, and KRAS status (A–H).

Anti-EGFR drugs were given as first-line treatment to five KRAS WT patients, four of which (80%) showed an objective response. Interestingly, all four patients had an EGFR GCN ⩾4.0. The fifth KRAS WT patient had an EGFR GCN <4.0 and progressed during therapy. We performed the statistical analyses separately by excluding the five KRAS WT patients who received anti-EGFR therapy as first-line treatment. Improved response rates were still seen in the group of KRAS WT patients with a high EGFR GCN (⩾4.0); an objective response was observed in 25% (6 out of 24), SD in 54% (13 out of 24) and PD in 21% (5 out of 24) of the patients. In the patients with a low EGFR GCN (<4.0), progressive disease was seen in 80% (12 out of 15) of the cases (Fisher's exact test, P=0.002). In addition, the statistical analyses were performed separately for the KRAS WT chemorefractory CRC patients who received anti-EGFR therapy in ⩾third line, either as single drug therapy (n=3) or in combination with irinotecan (n=22). In all, 84% of the patients with a high EGFR GCN (⩾4.0) achieved either a SD or PR. In contrast, the clinical benefit rate was only 33% for the patients with a low EGFR GCN (<4.0) (Fisher's exact test, P=0.03). Stable disease was the best response recorded for 13 out of 25 patients in this selected patient group and of those 69% (9 out of 13) had a prolonged SD (⩾24 weeks). When excluding the patients with SD duration of <24 weeks from the analysis a significant association between treatment response and EGFR GCN status was still seen in a similar fashion (Fisher's exact test, P=0.02).

EGFR SISH and survival

In the entire treated population, the EGFR GCN associated significantly with an improved PFS when using the ROC-curve based cut-off value of 4.0. Interestingly, the PFS time of the KRAS WT patients with EGFR GCN <4.0 was indifferent from those with KRAS mutation. The median PFS time of KRAS WT/EGFR GCN ⩾4.0 was 35 weeks compared with only 12 weeks of the KRAS WT/EGFR GCN <4.0 patients. The PFS remained significantly longer in the KRAS WT patient population with a high EGFR GCN when analysing only the patients treated with anti-EGFR therapy in second line or more (log-rank test, P<0.0001). Furthermore, in the cohort of chemorefractory patients treated either with single panitumumab or cetuximab±irinotecan in ⩾third line (n=25), the median PFS time was significantly longer in the KRAS WT/EGFR GCN ⩾4.0 patients than in the KRAS WT/EGFR GCN <4.0 patients; 35 vs 10 weeks (log-rank test, P=0.003; Cox test, P=0.007, HR: 0.22, 95% CI: 0.08–0.66). Similar results were obtained when excluding the patients with a short SD duration (<24 weeks) from the analysis (log-rank test, P=0.0008; Cox test, P=0.003, HR: 0.15, 95% CI: 0.04–0.53; PFS time 42 vs 8 weeks). Other factors associated with improved PFS in the entire group of anti-EGFR treated patients were tumour differentiation grade (log-rank test, P=0.001) and the absence of KRAS gene mutation (log-rank test, P=0.01). The EGFR GCN ⩾4.0 associated significantly with improved OS (log-rank test, P=0.004) in the entire treated population and in the subgroup of KRAS WT patients (log-rank test, P=0.001). The Chr-7 number did not associate with OS. The median OS time for patients with KRAS WT/EGFR GCN ⩾4.0 tumours was 85 weeks compared with 19 weeks for those with KRAS WT/EGFR GCN below the cut-off value. When excluding the patients treated with anti-EGFR therapy in first line the OS was still significantly higher in the patients with an EGFR GCN ⩾4.0 (log-rank test, P=0.001). In the selected patient group treated with anti-EGFR antibodies±irinotecan in ⩾third line an EGFR GCN ⩾4.0 predicted a prolonged OS as well; 74 vs 16 weeks in the group of patients with a low EGFR GCN (log-rank test, P=0.0005; Cox test, P=0.003, HR: 0.13, 95% CI: 0.03–0.49). The results remained significant when the patients with a short SD duration (<24 weeks) were excluded from the analysis (log-rank test, P=0.0003; Cox test, P=0.004, HR: 0.08, 95% CI: 0.01–0.44; PFS time 89 vs 14 weeks). The responses, survival times and P-values are summarised in Table 4, survival curves shown in Figure 3.
Table 4

Tumour response of patients with KRAS WT (n=54) and KRAS MT (n=10) metastatic or locally advanced colorectal cancer treated with anti-EGFR therapy according to ROC curve based cut-off values of EGFR GCN and chromosome 7 number evaluated by SISH

  Treatment response
PFS
OS
  Total no. of patients PR SD PD P-value Fisher's exact test PFS time median (days) P-value log-rank test P-value Cox testa HR 95% CI OS time median (days) P-value log-rank test P-value Cox testa HR 95% CI
KRAS WT and MT patients 54              
KRAS status
  KRAS WT4411 (25)15 (34.1)18 (40.9)NS151 0.01 0.01 0.400.20–0.843520.30.30.670.32–1.38
  KRAS MT1003 (30)7 (70) 81    249    
                
EGFR GCN status
  EGFR GCN ⩾4.03410 (29.4)15 (44.1)9 (26.5) 0.0006 224 <0.0001 <0.0001 0.210.10–0.43483 0.004 0.006 0.410.22–0.77
  EGFR GCN <4.0201 (5)3 (15)16 (80) 84    134    
                
KRAS WT patients
EGFR GCN
  ⩾4.02810 (35.7)13 (46.4)5 (17.9) 0.0002 244 <0.0001 <0.0001 0.170.07–0.39598 0.001 0.002 0.320.16–0.66
  <4.0161 (6.2)2 (12.5)13 (81.3) 84    134    
                
 Chromosome 7 number
  ⩾4.5249 (37.5)10 (41.7)5 (20.8) 0.009 2140.20.20.670.35–1.295200.10.10.560.28–1.13
  <4.5202 (10)5 (25)13 (65) 94    225    
                
KRAS MT patients
EGFR GCN
  ⩾4.0602 (33.3)4 (66.7)NS94NS   369NS   
  <4.0401 (25)3 (75) 77    134    
                
 Chromosome 7 number
  ⩾4.5602 (33.3)4 (66.7)NS94NS   369NS   
  <4.5401 (25)3 (75) 77    134    

Abbreviations: CI=confidence interval; CR=complete response; EGFR=epidermal growth factor receptor; GCN=gene copy number; HR=hazards ratio; MT=mutated; NS=not significant; OS=overall survival; PD=progressive disease; PFS=progression-free survival; PR=partial response; ROC= receiver operating characteristic; SD=stable disease; SISH=silver in situ hybridisation; WT=wild type.

Cox proportional hazards regression model. Treatment response values are given n (%). Significant P-values are shown in bold type.

Figure 3

Kaplan–Meier curves for PFS (A–D) and OS (E–F). Progression-free survival in anti-EGFR treated patients by (A) KRAS and (B) EGFR gene copy number (GCN). (C) Progression-free survival in KRAS WT patients (n=44) according to EGFR GCN. (D) Progression-free survival according to EGFR GCN in selected chemorefractory KRAS WT patients treated with anti-EGFR therapy±irinotecan in ⩾third line (n=25). (E) Overall survival by EGFR GCN. (F) Overall survival in KRAS WT patients according to EGFR GCN.

Multivariate survival analysis

Variables that in univariate survival analysis significantly associated with PFS and OS in the anti-EGFR treated patient group were included in the Cox's multivariate analysis. The multivariate analysis for PFS included EGFR GCN, tumour differentiation grade, and KRAS status. EGFR GCN (P=0.0003, HR: 0.22, 95% CI: 0.09–0.50), tumour differentiation grade (P=0.02, HR: 0.38, 95% CI: 0.16–0.88), and KRAS (P=0.04, HR: 0.44, 95% CI: 0.20–0.97) proved to be independent predictors of PFS. When the KRAS WT patients were analysed separately, only EGFR GCN (P=0.0003, HR: 0.16, 95% CI: 0.06–0.43) independently predicted PFS. EGFR GCN and tumour differentiation grade were entered for OS analysis. Both variables predicted OS: EGFR GCN (P=0.02, HR: 0.44, 95% CI: 0.22–0.86), tumour differentiation grade (P=0.046, HR: 0.43, 95% CI: 0.19–0.99). In the KRAS WT subgroup of patients, EGFR GCN remained as a statistically significant predictor of OS (P=0.01, HR: 0.35, 95% CI: 0.16–0.78).

Discussion

This study shows that EGFR GCN analysis, when performed from areas with highest EGFR expression, is a highly promising method for predicting the efficacy of anti-EGFR therapy in locally advanced or metastatic CRC. Together with KRAS analysis EGFR GCN identifies the responsive patients more accurately than either test alone. In all, 73% of patients with a high EGFR GCN (⩾4.0) responded to anti-EGFR therapy, whereas a clear majority (80%) of the patients with a low EGFR GCN were non-responders. In comparison, 41% of the KRAS WT patients did not respond to treatment. Previous reports, in which chromogenic ISH (CISH) and FISH were used to evaluate the EGFR GCN and/or Chr-7, have provided evidence for the association of increased EGFR GCN and response to anti-EGFR treatment. However, the predictive value of our study seems to be better than those (Moroni ; Lievre ; Frattini ; Sartore-Bianchi ; Cappuzzo ; Personeni ). What could be the explanation for this difference? One potential factor may be the use of IHC to guide the selection of the area for in situ analysis. The EGFR expression showed marked intratumoural variation and therefore, IHC was used to indicate the strongest EGFR immunoreactivity for evaluation of the EGFR GCN and Chr-7 number by SISH. This protocol might also explain why the EGFR GCN values were higher in our study than in most other studies reported. Another possible explanation could be the usage of a different EGFR probe. However, as the FISH analyses of nine selected cases were in concordance with SISH results, this is an unlikely explanation. Methodological difficulties as well as reproducibility concerns have until now prevented the usage of EGFR GCN as a predictive marker in the clinic. The fully automated SISH technique offers several advantages compared with manually performed FISH and CISH. Automation improves reproducibility and compared with FISH, SISH enables morphological identification of the analysed tissue, which facilitates the interpretation (Dietel ). Several studies have indicated that EGFR IHC does not predict the response to EGFR-targeted therapies (Cunningham ; Saltz ; Chung ; Cappuzzo ). In addition, the correlation between EGFR IHC and EGFR GCN has been poor (Shia ; Spindler ; Frattini ). Here, EGFR IHC with intracellular domain 5B7 antibody showed a significant correlation with the EGFR GCN and Chr-7 number. Our results may be due to the properties of the antibodies used. The novel 5B7 antibody detects the functionally active intracellular domain of EGFR, whereas other commercially available antibodies bind to the external domain of the EGFR. However, also IHC scoring method may have a role, the highest intensity assessment providing the best correlation with EGFR GCN. Typically, a constant intensive membranous staining correlated with areas of EGFR amplification. Consequently, although IHC does not predict treatment response, it is important for guiding SISH analysis, that is, indicating tumour areas with highest degree of EGFR GCN. Currently, patients with metastatic CRC are screened for KRAS status and only those with KRAS WT tumours receive anti-EGFR therapy. This selection is not absolute and about half of the patients with KRAS WT tumours will receive the anti-EGFR monoclonal antibodies unnecessarily. Although, BRAF, PIK3CA/PTEN, and NRAS alterations explain a fraction of unresponsiveness (Laurent-Puig ; Bardelli and Siena, 2010; De Roock ) the search for further predictive markers in this setting is feasible. Improved predictive testing would minimise the risk of exposing the patients to harmful side-effects caused by EGFR targeted therapies and at the same time reduce the healthcare costs. Our results suggest that cetuximab and panitumumab should not be offered to KRAS WT patients with EGFR GCN <4.0. Furthermore, according to our results, the analysis of EGFR GCN by SISH could in certain cases be used as a substitute for KRAS analysis, for example, when only a small biopsy of the tumour has been taken and the amount of tumour tissue is insufficient for KRAS analysis.
  30 in total

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Journal:  J Clin Oncol       Date:  2010-10-04       Impact factor: 44.544

2.  Randomized phase III study of panitumumab with fluorouracil, leucovorin, and irinotecan (FOLFIRI) compared with FOLFIRI alone as second-line treatment in patients with metastatic colorectal cancer.

Authors:  Marc Peeters; Timothy Jay Price; Andrés Cervantes; Alberto F Sobrero; Michel Ducreux; Yevhen Hotko; Thierry André; Emily Chan; Florian Lordick; Cornelis J A Punt; Andrew H Strickland; Gregory Wilson; Tudor-Eliade Ciuleanu; Laslo Roman; Eric Van Cutsem; Valentina Tzekova; Simon Collins; Kelly S Oliner; Alan Rong; Jennifer Gansert
Journal:  J Clin Oncol       Date:  2010-10-04       Impact factor: 44.544

3.  EGFR antibodies in colorectal cancer: where do they belong?

Authors:  Axel Grothey
Journal:  J Clin Oncol       Date:  2010-10-04       Impact factor: 44.544

4.  Analysis of PTEN, BRAF, and EGFR status in determining benefit from cetuximab therapy in wild-type KRAS metastatic colon cancer.

Authors:  Pierre Laurent-Puig; Anne Cayre; Gilles Manceau; Emmanuel Buc; Jean-Baptiste Bachet; Thierry Lecomte; Philippe Rougier; Astrid Lievre; Bruno Landi; Valérie Boige; Michel Ducreux; Marc Ychou; Fréderic Bibeau; Olivier Bouché; Julia Reid; Steven Stone; Frédérique Penault-Llorca
Journal:  J Clin Oncol       Date:  2009-11-02       Impact factor: 44.544

5.  Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis.

Authors:  Wendy De Roock; Bart Claes; David Bernasconi; Jef De Schutter; Bart Biesmans; George Fountzilas; Konstantine T Kalogeras; Vassiliki Kotoula; Demetris Papamichael; Pierre Laurent-Puig; Frédérique Penault-Llorca; Philippe Rougier; Bruno Vincenzi; Daniele Santini; Giuseppe Tonini; Federico Cappuzzo; Milo Frattini; Francesca Molinari; Piercarlo Saletti; Sara De Dosso; Miriam Martini; Alberto Bardelli; Salvatore Siena; Andrea Sartore-Bianchi; Josep Tabernero; Teresa Macarulla; Frédéric Di Fiore; Alice Oden Gangloff; Fortunato Ciardiello; Per Pfeiffer; Camilla Qvortrup; Tine Plato Hansen; Eric Van Cutsem; Hubert Piessevaux; Diether Lambrechts; Mauro Delorenzi; Sabine Tejpar
Journal:  Lancet Oncol       Date:  2010-07-08       Impact factor: 41.316

6.  Cetuximab shows activity in colorectal cancer patients with tumors that do not express the epidermal growth factor receptor by immunohistochemistry.

Authors:  Ki Young Chung; Jinru Shia; Nancy E Kemeny; Manish Shah; Gary K Schwartz; Archie Tse; Audrey Hamilton; Dorothy Pan; Deborah Schrag; Lawrence Schwartz; David S Klimstra; Daniel Fridman; David P Kelsen; Leonard B Saltz
Journal:  J Clin Oncol       Date:  2005-01-27       Impact factor: 44.544

Review 7.  Colorectal cancer.

Authors:  David Cunningham; Wendy Atkin; Heinz-Josef Lenz; Henry T Lynch; Bruce Minsky; Bernard Nordlinger; Naureen Starling
Journal:  Lancet       Date:  2010-03-20       Impact factor: 79.321

8.  Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer.

Authors:  David Cunningham; Yves Humblet; Salvatore Siena; David Khayat; Harry Bleiberg; Armando Santoro; Danny Bets; Matthias Mueser; Andreas Harstrick; Chris Verslype; Ian Chau; Eric Van Cutsem
Journal:  N Engl J Med       Date:  2004-07-22       Impact factor: 91.245

9.  Phase II trial of cetuximab in patients with refractory colorectal cancer that expresses the epidermal growth factor receptor.

Authors:  Leonard B Saltz; Neal J Meropol; Patrick J Loehrer; Michael N Needle; Justin Kopit; Robert J Mayer
Journal:  J Clin Oncol       Date:  2004-03-01       Impact factor: 44.544

Review 10.  Molecular mechanisms of resistance to cetuximab and panitumumab in colorectal cancer.

Authors:  Alberto Bardelli; Salvatore Siena
Journal:  J Clin Oncol       Date:  2010-01-25       Impact factor: 44.544

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  24 in total

1.  EGFR gene copy number as a predictive biomarker for resistance to anti-EGFR monoclonal antibodies in metastatic colorectal cancer treatment: a meta-analysis.

Authors:  Wei-Dong Shen; Hong-Lin Chen; Peng-Fei Liu
Journal:  Chin J Cancer Res       Date:  2014-02       Impact factor: 5.087

2.  Serum levels of GFAP and EGFR in primary and recurrent high-grade gliomas: correlation to tumor volume, molecular markers, and progression-free survival.

Authors:  Aida Kiviniemi; Maria Gardberg; Janek Frantzén; Riitta Parkkola; Ville Vuorinen; Marko Pesola; Heikki Minn
Journal:  J Neurooncol       Date:  2015-06-02       Impact factor: 4.130

Review 3.  Estrogen receptor alpha gene amplification in breast cancer: 25 years of debate.

Authors:  Frederik Holst
Journal:  World J Clin Oncol       Date:  2016-04-10

4.  Urachal Carcinoma Shares Genomic Alterations with Colorectal Carcinoma and May Respond to Epidermal Growth Factor Inhibition.

Authors:  Ana Collazo-Lorduy; Mireia Castillo-Martin; Li Wang; Vaibhav Patel; Gopa Iyer; Emmet Jordan; Hikmat Al-Ahmadie; Issa Leonard; William K Oh; Jun Zhu; Russell B McBride; Carlos Cordon-Cardo; David B Solit; John P Sfakianos; Matthew D Galsky
Journal:  Eur Urol       Date:  2016-05-10       Impact factor: 20.096

5.  Gene copy number gain of EGFR is a poor prognostic biomarker in gastric cancer: evaluation of 855 patients with bright-field dual in situ hybridization (DISH) method.

Authors:  Eiji Higaki; Takeshi Kuwata; Akiko Kawano Nagatsuma; Yasunori Nishida; Takahiro Kinoshita; Masaki Aizawa; Hiroaki Nitta; Masato Nagino; Atsushi Ochiai
Journal:  Gastric Cancer       Date:  2014-12-09       Impact factor: 7.370

Review 6.  Potential biomarkers for anti-EGFR therapy in metastatic colorectal cancer.

Authors:  Jiao Yang; Shuting Li; Biyuan Wang; Yinying Wu; Zheling Chen; Meng Lv; Yayun Lin; Jin Yang
Journal:  Tumour Biol       Date:  2016-07-16

7.  Genomic gain of the PRL-3 gene may represent poor prognosis of primary colorectal cancer, and associate with liver metastasis.

Authors:  N Nakayama; K Yamashita; T Tanaka; H Kawamata; A Ooki; T Sato; T Nakamura; M Watanabe
Journal:  Clin Exp Metastasis       Date:  2015-11-12       Impact factor: 5.150

8.  EGFR alterations and response to anti-EGFR therapy: is it a matter of gene amplification or gene copy number gain?

Authors:  R Sesboüé; F Le Pessot; F Di Fiore; T Frebourg
Journal:  Br J Cancer       Date:  2011-12-20       Impact factor: 7.640

9.  Targeted therapies in colorectal cancer-an integrative view by PPPM.

Authors:  Suzanne Hagan; Maria C M Orr; Brendan Doyle
Journal:  EPMA J       Date:  2013-01-28       Impact factor: 6.543

Review 10.  EGFR gene copy number as a prognostic marker in colorectal cancer patients treated with cetuximab or panitumumab: a systematic review and meta analysis.

Authors:  Zheng Jiang; Chunxiang Li; Fuyuan Li; Xishan Wang
Journal:  PLoS One       Date:  2013-02-18       Impact factor: 3.240

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