A synonymous EGFR polymorphism predicting

Tumor Biol. DOI 10.1007/s13277-015-4543-3

ORIGINAL ARTICLE

A synonymous EGFR polymorphism predicting responsiveness to anti-EGFR therapy in metastatic colorectal cancer patients Serena Bonin 1 & Marisa Donada 1 & Gianni Bussolati 2 & Ermanno Nardon 1 & Laura Annaratone 2 & Martin Pichler 4 & Anna Maria Chiaravalli 5 & Carlo Capella 6 & Gerald Hoefler 3 & Giorgio Stanta 1

Received: 19 August 2015 / Accepted: 27 November 2015 # International Society of Oncology and BioMarkers (ISOBM) 2015

Abstract Genetic factors are known to affect the efficiency of therapy with monoclonal antibodies (mAbs) targeting the epidermal growth factor receptor (EGFR) in patients with metastatic colorectal cancer (mCRC). At present, the only accepted molecular marker predictive of the response to anti-EGFR mAbs is the somatic mutation of KRAS and NRAS as a marker of resistance to anti-EGFR. However, only a fraction of KRAS wild-type patients benefit from that treatment. In this study, we show that the EGFR gene polymorphism rs1050171 defines, independently of RAS mutational status, a subpopulation of 11 % of patients with a better clinical outcome after anti-EGFR treatment. Median PFS for patients with the GG genotype was 10.17 months compared to 5.37 of those with AG + AA genotypes. Taken together, our findings could be used to better define CRC populations responding to antiEGFR therapy. Further studies in larger independent cohorts are necessary to validate the present observation that a

Electronic supplementary material The online version of this article (doi:10.1007/s13277-015-4543-3) contains supplementary material, which is available to authorized users. * Giorgio Stanta [email protected] 1

Department of Medical Sciences, University of Trieste, Cattinara Hospital-Surgical Pathology Building, Strada di Fiume 447, 34149 Trieste, Italy

2

Department of Medical Sciences, University of Torino, Torino, Italy

3

Institute of Pathology—Medical University of Graz, Graz, Austria

4

Division of Oncology—Medical University of Graz, Graz, Austria

5

Unit of Anatomical Pathology, Ospedale di Circolo, Varese, Italy

6

Department of Surgical and Morphological Sciences, University of Insubria, Varese, Italy

synonymous polymorphism in EGFR gene impacts on clinical responsiveness. Keywords mCRC . RAS mutation . EGFR gene polymorphism rs1050171 . Synonymous SNP . FFPE . Survival

Background Over the last decade, factors affecting the efficiency of therapy with monoclonal antibodies (mAbs) against the epidermal growth factor receptor (EGFR) extracellular domain, such as cetuximab and panitumumab, alone or in combination with chemotherapy [1, 2], have been investigated in patients with metastatic colorectal cancer (mCRC). Initially, anti-EGFR mAbs therapy was given to mCRC patients showing positive EGFR expression by immunochemistry (IHC), but subsequently, the use of this biomarker was discontinued because of its inability in predicting response. Therefore, other biomarkers, which ensure reliability as predictor of anti-EGFR mAbs response, have been searched for [3]. At present, the only accepted molecular marker predicting response or better resistance to anti-EGFR mAbs, as validated by numerous studies, is the somatic mutation of KRAS [3]. KRAS mutations as predictors of resistance to anti-EGFR have empirically proved inefficiency of anti-EGFR mAbs in case of alterations in downstream effectors activating the EGFR transduction cascade [3]. Still, only a fraction (25 %) of KRAS wildtype patients benefit from that treatment [4], indicating that KRAS mutations are not the only determinants of the failure of clinical response to anti-EGFR in mCRC. Other biomarkers in addition to KRAS mutational status, such as NRAS mutational status [5], expression of EGFR ligands amphiregulin and epiregulin [6], or alterations of

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downstream effectors of EGFR and KRAS (such as BRAF, PTEN, or PIK3CA) have been proposed to explain the resistance to anti-EGFR monoclonal antibodies [7, 8], but this is still controversial and therefore, except for NRAS, none of those markers is now used in the clinical practice. It has been observed that inter-individual variations in drug responses among patients could also be related to single-nucleotide polymorphisms (SNPs) of the EGFR gene as shown in CRC patients receiving 5-FU-based chemotherapy [9] as well as platinum-based therapy [10]. Moreover, it has been demonstrated that EGFR polymorphisms are significantly associated with a better overall survival in mCRC patients treated with anti-EGFR mAb plus irinotecan chemotherapy [11, 12]. A synonymous polymorphism rs1050171 in exon 20 of EGFR has already been identified in CRC [13] without any implication on cancer risk or prognosis, but no data are available on its possible involvement in anti-EGFR therapy response. The aim of the present study is to investigate the predictive value of that synonymous EGFR polymorphism in mCRC patients treated with anti-EGFR therapy or with chemotherapy alone.

Patients and methods Patients This retrospective study was conducted on 98 patients (Group 1) with histologically confirmed metastatic colorectal cancer who had been treated with anti-EGFR agents (cetuximab and/or panitumumab) in the years 2004–2010 at the BMolinette^ Hospital, Turin or at the BCircolo e Fondazione Macchi^ Hospital, Varese (University of Insubria). The clinical and pathological characteristics of those patients, as well as the treatment, are reported in Table 1. Formalin-fixed paraffin-embedded (FFPE) tissue blocks from the primary tumor were collected and used to investigate the impact of genetic data on the clinical evolution of the disease. Originally, a decision on the feasibility of antiEGFR treatment was determined by the intensity of EGFR staining, by immunohistochemistry (IHC), as routinely practiced at that time. Mutation analysis of RAS genes has now been performed on the same material (Group 1). As a control of polymorphism frequency and its effect on clinical evolution, irrespective of anti-EGFR therapy, we tested material from 65 patients (Group 2) who had been treated at the University of Insubria for mCRC from February 2000 to April 2005. No genetic analysis for RAS mutations had been performed. Those patients had followed a first line chemotherapy (without monoclonal antibodies), mainly based on FOLFIRI and FOLFOX 4 regimens. The patients’ data are reported in Table 1. The censoring date for both groups of patients was set on 30th April 2012. The clinical end points of the study were progression-free survival (PFS), which was defined as the

Table 1 cohorts

Characteristics of colon cancer patients in the two treatment

Variable

Group1: Biological therapy a N = 98 N (%)

Group 2: No biological therapy N = 65 N (%)

Age, mean (SD), years

61.0 (8.8)

67.3 (10.2)

Sex Male

57 (58)

40 (62)

41 (42)

25 (38)

30 (33)

24 (38)

63 (67)

39 (62)

3 (3) 79 (81)

8 (12) 47 (73)

16 (16)

10 (15)

Tumor stage at first diagnosisa II 13 (14) III 56 (57) IV 41 (42)

41 (63) 18 (28) 6 (9)

Female Tumor location Proximal Distal Tumor grade G1 G2 G3

Line of anti-EGFR treatment I 2 (2) II 8 (8) III 70 (72) IV Missing Type of treatment Cetuximab Cetuximab + Irinotecan Cetuximab + FOLFIRI Panitumumab a

13 (13) 5 (5) 17 (18) 55 (56) 10 (10) 16 (16)

For one case information on initial stage was missing

time lapse from the start of the therapy until disease progression and withdrawal of anti-EGFR therapy, and cancerspecific survival (CSS), which was defined as the time lapse from the start of the anti-EGFR therapy until colon cancerspecific death. Patients treated with monoclonal antibodies were followed up from the start of the treatment for recurrent disease until cancer progression (PFS) or colorectal cancerspecific death. Patients without biological therapy were followed up from the standard chemotherapy administration (mostly based on FOLFIRI regimen) until colorectal cancerspecific death. For each tumor specimen, the areas of interest close to the infiltrative border of the tumor were identified on a reference H&E-stained section by a pathologist, and then mechanically microdissected on the paraffin block after ascertaining the presence of adequate normal/

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neoplastic tissue. For each sample, 10–15 sections of 6– 8 μm of thickness were cut and submitted to DNA extraction as previously reported [14, 15]. The study was approved by the ethical committee of the University of Trieste.

DNA analyses After extraction of the DNA from normal colonic mucosa, PCR amplification was carried out for exon 20 of the EGFR gene to determine the polymorphism (rs1050171, as described in the NCBI SNP database). The primers used were as follows: forward-5′-CACACTGACGTGCCTCTC-3′; reverse5′-GGATCCTGGCTCCTTATCTC-3′, amplifying a fragment of 264 bases. PCR was performed using 50 ng of DNA in 1× PCR buffer (10 mM Tris HCl, pH 8.3; 50 mM KCl, 1.5 mM MgCl2), dNTPs (each 0.2 mM), primers (15 pmol each), and 1.25 units of Taq Gold DNA Polymerase (Applied Biosystems) in a final volume of 50 μl. PCR amplifications were performed as follows: 95 °C/7 min; 5×: 95 °C/1 min, 60 °C/1 min, 72 °C/1 min; and 35×: 95 °C/30 s, 60 °C/30 s, 72 °C/30 s. PCR amplicons were then submitted to restriction analysis with the ALU I enzyme (Promega) according to the manufacturer’s instructions. Nucleotide change from G to A abolishes one restriction site for this enzyme allowing identification of different genotypes according to changes in length after enzyme cutting. Restriction fragments were resolved onto a 10 % polyacrylamide gel (Acryl:Bis 19:1) to give the following bands: GG, 107-145b; AA, 119-145b; GA107-119-145. This method was confirmed to be reliable with Sanger sequencing when it was set up by analyzing 23 FFPE CRC specimens not included in this cohort (data not shown). The cost of this assay is approximately 15 € per sample. RAS mutational status KRAS mutational status of codons 12 and 13 KRAS mutations at codons 12 and 13 were assessed by semi-nested PCR followed by Sanger sequencing of the inner PCR product using the forward primer of the second PCR round for sequencing. Standard dideoxy sequencing reaction and sequencing were performed at the BMR-genomics sequencing core facility (Padua, Italy). In detail, 100 ng of DNA extracts from FFPE tumor biopsies was amplified in 50-μl final reaction volume containing 1× PCR Buffer (10 mM Tris pH 8.3; 50 mM KCl, 1.5 mM MgCl2), 0.2 mM dNTPs, 15 pmol of each primer, and 1.25 units of Taq DNA Polymerase (GE Healthcare). PCR amplifications were performed as follows: initial denaturation step

of 95 °C for 3′; 45 cycles of 95 °C for 30 s; specific annealing temperature for 30 s; 72 °C for 30 s; and a final elongation step of 72 °C for 5′. One microliter of the first PCR reaction product was used in the second PCR round. The thermal profile of the nested run was the same as the first, although the final number of cycles was reduced (35 cycles). The list of the primers used for mutational analyses is reported in the Supplementary file. NRAS and KRAS mutation at codons 61 and 117 Pyrosequencing was used for quantitative detection of additional mutations in KRAS and NRAS genes. NRAS mutation detection at codons 12, 13, and 61 was detected by therascreen® NRAS Pyro® Kit (Ref 971530), KRAS mutation at codons 58–61 was detected by therascreen® KRAS Pyro® Kit (Ref 971460), and NRAS and KRAS mutation at codons 117 and 146 was detected by therascreen® RAS Extension Pyro® Kit (Ref 971590) all from Qiagen (Hilden, Germany). Two 10 ng of genomic DNA extracted from FFPE tissue were used in a 25-μl reaction mixture containing 12.5 μl PyroMark Master Mix (2×), 2.5 μl CoralLoad Concentrate (10×), 1-μl appropriate PCR primer, and 4-μl water. After an initial activating step of 15 min at 95 °C, 42 cycles of denaturation for 20 s at 95 °C, annealing for 30 s at 53 °C, extension for 20 s at 72 °C, and a final extension for 5 min at 72 °C were performed. PCR products were bound to Streptavidin Sepharose High Performance Beads (Qiagen, Hilden, Germany) on a plate mixer with orbital shaking for 5–10 min at 1400 rpm. Beads were released to a sequencing plate containing sequencing primers. Sequencing was performed in a PyroMark Q24 (Qiagen, Hilden, Germany). For mutation detection, the PyroMark®Q24 software (version 2.0, Qiagen, Hilden, Germany) was used. RNA analyses Total RNA was extracted from FFPE specimens of primary CRC after mechanical microdissection, as described elsewhere [16]. For each sample, 4 μg of total RNA were treated with DNase as already reported [17]. Complementary DNA synthesis was performed from 2 μg of RNA using Moloney Murine Leukemia Virus (M-MLV) reverse transcriptase (Invitrogen, Karlsruhe, Germany) and a mix of random hexamers in a final volume of 20 μl, as described in detail elsewhere [17]. Expression levels of EGFR and GAPDH were analyzed by real-time PCR using a Mastercycler® ep Realplex (Eppendorf, Hamburg, Germany), as well as primers already described [17, 18]. For each PCR reaction, 30 ng of cDNA was amplified in a final volume of 20 μl. Cycling conditions were as follows: 1 min and 30 s at 95 °C for polymerase activation and 40 cycles of denaturation for 30 s at 95 °C, primer annealing for 30 s at specific annealing temperature (54.5 °C for EGFR and 61.2 °C for GAPDH), extension for 30 s at 72 °C, and

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fluorescence detection for 20 s (78.8 °C for EGFR and 80 °C for GAPDH). The detection temperature was set very close to amplicon’s melting to avoid detection of unspecific products. Uniqueness of amplification products was checked by melting curve analysis and by 10 % polyacrylamide gel electrophoresis. EGFR expression levels were normalized against GAPDH and expressed in relation to a RNA pooled from eight normal colon tissues as already described [18]. Relative quantification was performed according to a ΔΔCt model as previously reported [18].

Results Clinical information on the two groups of patients is reported in Table 1. In patients treated with anti-EGFR therapy (Group 1), the median PFS was 5.6 months (25th–75th percentile = 2.8–8.4 months), while the median CSS was 11.8 months (25th–75th percentile = 7.9–19.2 months). In patients treated with traditional chemotherapy only (Group 2), CSS was 12.5 months (25th–75th percentile = 8.3–21.3 months). RAS mutational status

Immunohistochemical analyses IHC staining for EGFR was routinely done in an automatic slide stainer at the San Giovanni BMolinette^ Hospital, Turin and at the BCircolo e Fondazione Macchi^ Hospital, Varese (University of Insubria), according to the manufacturers’ instructions for EGFR (Dako and Ventana). EGFR staining interpretation was performed using the proposed criteria by the DAKO EGFR pharmDx kit. Intensity of EGFR reactivity was scored as 0 (background staining), +1 (mild), +2 (moderate), or +3 (strong). The sections were considered to be positive when ≥1 % of the tumor cells had membranous staining of +1 or +2 intensity. Statistical analyses Associations between clinicopathological data and categories of markers were tested for significance using the chi-square test (or Fisher’s exact test depending on the size of the groups) for categorical variables. The distribution of data within a continuous variable was tested by kurtosis test in order to establish the type of statistical tests (parametric or non-parametric). For continuous variables, the parametric Student’s t test or the nonparametric Mann–Whitney U test was used. The Spearman’s rank correlation coefficient was used to test the strength of correlation for non- parametric variables. The Cuzick nptrend test, which is an extension to the Kruskal–Wallis test, was used to perform the nonparametric test for trend across ordered groups. The effect of clinical and pathological parameters on progression-free survival (PFS) and cancer-specific survival (CSS) was studied by log rank test. A Cox regression model was used to confirm the results of the logrank test. As a post-estimation for the proportional hazards assumption, the Grambsch and Therneau test for Schoenfeld residuals was run. All p values are two-sided with values |z|

95 % confidence interval

Gender Age at diagnosis Tumor stage (IV, III, II) Tumor location (distal–proximal) Tumor grade (G3, G2, G1) Genotypes (AG and AA vs GG) Any mutation to KRAS or NRAS (no–yes) EGFR IHC (focal positive)

1.25 1.01 0.90 0.96 1.49 3.19 1.13 1.41

0.4 0.4 0.5 0.9 0.2 0.004 0.6 0.3

0.76–2.10 0.98–1.04 0.65–1.23 0.56–1.66 0.86–2.57 1.45–7.03 0.68–1.88 0.76–2.59

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the treatment with the monoclonal antibodies but only underwent curative conventional chemotherapy (see Supplementary file). In this group, the polymorphism was not associated with patients’ CSS, when the genotypes were considered separately (p = 0.7) or when genotype GG was compared to genotypes AG and AA combined (p = 0.4). This result suggests that EGFR polymorphism rs1050171 may be used as a simple predictive marker for cetuximab/ panitumumab therapeutic efficacy, independently of RAS mutational status. Interestingly enough, the proposed test is cheap and practicable on patients’ blood, with no need to get access to tumor tissue. However, we acknowledge that the number of GG patients in our cohort is low, and larger studies should be undertaken for definite validation and to define the independence of the genotype GG from RAS mutational status. To date, there are no studies reporting on biological or clinical significance of rs1050171 polymorphism in CRC and anti-EGFR therapy response. In lung cancer [22–24], only a weak association between genotypes AG and AA and worse outcome has been reported in patients submitted to gefitinib therapy [25]. In contrast, no association was detected between EGFR polymorphism rs1050171 and outcome in patients with Barrett’s adenocarcinomas [26], while in patients with esophageal squamous cell carcinoma, the SNP rs1050171 was suggested as carrying prognostic significance since AG patients had significant shorter survival [27]. Additionally, some studies on that polymorphism aimed to investigate the role of EGFR mutations or polymorphism as well as the risk of developing gastric or pancreatobiliary carcinomas [28, 29]. In our study, GG genotype of polymorphism rs1050171 seems to be highly predictive of response to anti-EGFR therapy and defines a patients’ sub-population with mCRC having a significantly longer PFS. One major question in this study is how a silent polymorphism could influence response to biological inhibiting therapy. At present, possible explanations include the activity of a putative endogenous non-coding RNA or alternative splicing or on mRNA stability. There is considerable evidence that silent mutations/polymorphisms could disrupt splicing and interfere with miRNA binding. They could also modify protein abundance by alteration in mRNA stability or could alter protein structure and activity by induction of translational pausing [30]. In head and neck’s squamous cell carcinomas, cell line genotypes AG and AA of our polymorphism have been associated with increased EGFR copy number and mRNA half-life [31]. However, further investigations on non-coding RNA and their effect on EGFR mRNA and protein in different genotypes are needed to understand the mechanism. In conclusion, our results add new insight on the antiEGFR therapy response in patients with mCRC. Patients of our cohort with genotype GG had a significantly better outcome after treatment with anti-EGFR monoclonal antibodies,

independent of sex, age, tumor grade and, apparently, RAS mutational status and EGFR IHC, as evidenced by multivariate analysis. Further studies are necessary to validate our findings in larger independent cohorts, but our original observation suggests that a simple SNP analysis, even feasible on patients’ blood, might result in a significant improvement in the selection of mCRC patients amenable to anti-EGFR therapy. Acknowledgments The authors would like to thank Dr Valentina Melita for the English revision of the manuscript. Compliance with ethical standards Funding This study was partially supported by the FRA2011 grant from the University of Trieste. Conflicts of interest None

References 1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

Jonker DJ, O’Callaghan CJ, Karapetis CS, Zalcberg JR, Tu D, Au HJ, et al. Cetuximab for the treatment of colorectal cancer. N Engl J Med. 2007;357(20):2040–8. doi:10.1056/NEJMoa071834. Van Cutsem E, Kohne CH, Hitre E, Zaluski J, Chang Chien CR, Makhson A, et al. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med. 2009;360(14): 1408–17. Di Fiore F, Sesboue R, Michel P, Sabourin JC, Frebourg T. Molecular determinants of anti-EGFR sensitivity and resistance in metastatic colorectal cancer. Br J Cancer. 2010;103(12):1765–72. doi:10.1038/sj.bjc.6606008. Bardelli A, Siena S. Molecular mechanisms of resistance to cetuximab and panitumumab in colorectal cancer. J Clin Oncol. 2010;28(7):1254–61. Meriggi F, Vermi W, Bertocchi P, Zaniboni A. The emerging role of NRAS mutations in colorectal cancer patients selected for antiEGFR therapies. Rev Recent Clin Trials. 2014. Jacobs B, De Roock W, Piessevaux H, Van Oirbeek R, Biesmans B, De Schutter J, et al. Amphiregulin and epiregulin mRNA expression in primary tumors predicts outcome in metastatic colorectal cancer treated with cetuximab. J Clin Oncol. 2009;27(30):5068– 74. doi:10.1200/JCO.2008.21.3744. Leto SM, Trusolino L. Primary and acquired resistance to EGFRtargeted therapies in colorectal cancer: impact on future treatment strategies. J Mol Med. 2014. doi:10.1007/s00109-014-1161-2. Therkildsen C, Bergmann TK, Henrichsen-Schnack T, Ladelund S, Nilbert M. The predictive value of KRAS, NRAS, BRAF, PIK3CA and PTEN for anti-EGFR treatment in metastatic colorectal cancer: a systematic review and meta-analysis. Acta Oncol. 2014. doi:10. 3109/0284186X.2014.895036. Lai CY, Sung FC, Hsieh LL, Tang R, Chiou HY, Wu FY, et al. Associations between genetic polymorphisms of epidermal growth factor receptor (EGFR) and survival of colorectal cancer (CRC) patients treated with 5-fluorouracil-based chemotherapy. Ann Surg Oncol. 2013;20 Suppl 3:S599–606. doi:10.1245/s10434013-3069-4. Zhang W, Stoehlmacher J, Park DJ, Yang D, Borchard E, Gil J, et al. Gene polymorphisms of epidermal growth factor receptor and its

Tumor Biol.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

downstream effector, interleukin-8, predict oxaliplatin efficacy in patients with advanced colorectal cancer. Clin Colorectal Cancer. 2005;5(2):124–31. Garm Spindler KL, Pallisgaard N, Rasmussen AA, Lindebjerg J, Andersen RF, Cruger D, et al. The importance of KRAS mutations and EGF61A>G polymorphism to the effect of cetuximab and irinotecan in metastatic colorectal cancer. Ann Oncol. 2009;20(5): 879–84. doi:10.1093/annonc/mdn712. Graziano F, Ruzzo A, Loupakis F, Canestrari E, Santini D, Catalano V, et al. Pharmacogenetic profiling for cetuximab plus irinotecan therapy in patients with refractory advanced colorectal cancer. J Clin Oncol. 2008;26(9):1427–34. doi:10.1200/JCO.2007.12.4602. Metzger B, Chambeau L, Begon DY, Faber C, Kayser J, Berchem G, et al. The human epidermal growth factor receptor (EGFR) gene in European patients with advanced colorectal cancer harbors infrequent mutations in its tyrosine kinase domain. BMC Med Genet. 2011;12:144. doi:10.1186/1471-2350-12-144. Basili G, Bonin S, Dotti I. DNA sequencing from PCR products. In: Stanta G, editor. Guidelines for molecular analysis in archive tissues. Berlin: Springer; 2011. p. 135–41. Hlubek F, Jung A. Fast protocol for DNA extraction from formalinfixed paraffin-embedded tissues. In: Stanta G, editor. Guidelines for molecular analyses in archive tissues. Berlin: Springer; 2011. p. 41– 3. Bonin S, Stanta G. RNA extraction from formalin-fixed paraffinembedded tissues. In: Stanta G, editor. Guidelines for molecular analysis in archive tissues. 1st ed. Berlin: Springer-Verlag; 2011. p. 57–61. Nardon E, Donada M, Bonin S, Dotti I, Stanta G. Higher random oligo concentration improves reverse transcription yield of cDNA from bioptic tissues and quantitative RT-PCR reliability. Exp Mol Pathol. 2009;87(2):146–51. doi:10.1016/j.yexmp.2009.07.005. Donada M, Bonin S, Nardon E, De Pellegrin A, Decorti G, Stanta G. Thymidilate synthase expression predicts longer survival in patients with stage II colon cancer treated with 5-flurouracil independently of microsatellite instability. J Cancer Res Clin Oncol. 2011;137(2):201–10. EGAPP WG. Recommendations from the EGAPP Working Group: can testing of tumor tissue for mutations in EGFR pathway downstream effector genes in patients with metastatic colorectal cancer improve health outcomes by guiding decisions regarding antiEGFR therapy? Genet Med. 2013;15(7):517–27. doi:10.1038/ gim.2012.184. Gil Ferreira C, Aran V, Zalcberg-Renault I, Victorino AP, Salem JH, Bonamino MH, et al. KRAS mutations: variable incidences in a Brazilian cohort of 8,234 metastatic colorectal cancer patients. BMC Gastroenterol. 2014;14:73. doi:10.1186/1471-230X-14-73.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30. 31.

De Roock W, Jonker DJ, Di Nicolantonio F, Sartore-Bianchi A, Tu D, Siena S, et al. Association of KRAS p.G13D mutation with outcome in patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab. JAMA. 2010;304(16):1812– 20. doi:10.1001/jama.2010.1535. Choi JE, Park SH, Kim KM, Lee WK, Kam S, Cha SI, et al. Polymorphisms in the epidermal growth factor receptor gene and the risk of primary lung cancer: a case-control study. BMC Cancer. 2007;7:199. Wang Y, Bao W, Shi H, Jiang C, Zhang Y. Epidermal growth factor receptor exon 20 mutation increased in post-chemotherapy patients with non-small cell lung cancer detected with patients’ blood samples. Transl Oncol. 2013;6(4):504–10. Zhang W, Stabile LP, Keohavong P, Romkes M, Grandis JR, Traynor AM, et al. Mutation and polymorphism in the EGFR-TK domain associated with lung cancer. J Thorac Oncol. 2006;1(7): 635–47. Sasaki H, Endo K, Takada M, Kawahara M, Tanaka H, Kitahara N, et al. EGFR polymorphism of the kinase domain in Japanese lung cancer. J Surg Res. 2008;148(2):260–3. Marx AH, Zielinski M, Kowitz CM, Dancau AM, Thieltges S, Simon R et al. Homogeneous EGFR amplification defines a subset of aggressive Barrett’s adenocarcinomas with poor prognosis. Histopathology. 2010. Kaneko K, Kumekawa Y, Makino R, Nozawa H, Hirayama Y, Kogo M, et al. EGFR gene alterations as a prognostic biomarker in advanced esophageal squamous cell carcinoma. Front Biosci. 2010;15:65–72. Weiss GA, Rossi MR, Khushalani NI, Lo K, Gibbs JF, Bharthuar A, et al. Evaluation of phosphatidylinositol-3-kinase catalytic subunit (PIK3CA) and epidermal growth factor receptor (EGFR) gene mutations in pancreaticobiliary adenocarcinoma. J Gastrointest Oncol. 2013;4(1):20–9. doi:10.3978/j.issn.2078-6891.2012.012. Zhang J, Zhan Z, Wu J, Zhang C, Yang Y, Tong S, et al. Association among polymorphisms in EGFR gene exons, lifestyle and risk of gastric cancer with gender differences in Chinese Han subjects. PLoS One. 2013;8(3):e59254. doi:10.1371/journal.pone.0059254. Parmley JL, Hurst LD. How do synonymous mutations affect fitness? BioEssays. 2007;29(6):515–9. doi:10.1002/bies.20592. Nakazaki K, Kato Y, Taguchi T, Inayama Y, Ishiguro Y, Kondo N, et al. Heterozygous mutation (G/G→G/A) at nt 2607 of the EGFR gene is closely associated with increases in EGFR copy number and mRNA half life, but impaired EGFR protein synthesis in squamous cell carcinomas of the head and neck—implication for gefitinib efficacy. Oncol Lett. 2010;1(6):1017–20. doi:10.3892/ol.2010.188.