Sage Journals: Discover world-class research

Abstract

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are first-choice treatments for advanced non-small-cell lung cancer patients harboring EGFR mutations. Although EGFR mutations are strongly predictive of patients’ outcomes and their response to treatment with EGFR-TKIs, early failure of first-line therapy with EGFR-TKIs in patients with EGFR mutations is not rare. Besides several clinical factors influencing EGFR-TKI efficacies studied earlier such as the Eastern Cooperative Oncology Group performance status or uncommon mutation, we would like to see whether semi-quantify EGFR mutation gene expression calculated by 2^−ΔΔct was a prognostic factor in EGFR-mutant non-small cell lung cancer patients receiving first-line EGFR-TKIs. This retrospective study reviews 926 lung cancer patients diagnosed from January 2011 to October 2013 at the Kaohsiung Chang Gung Memorial Hospital in Taiwan. Of 224 EGFR-mutant adenocarcinoma patients, 148 patients who had 2^−ΔΔct data were included. The best cutoff values of 2^−ΔΔct for in-frame deletions in exon 19 (19 deletion) and a position 858 substituted from leucine (L) to an arginine (R) in exon 21 (L858R) were determined using receiver operating characteristic curves. Patients were divided into high and low 2^−ΔΔct expression based on the above cutoff level. The best cutoff point of 2^−ΔΔct value of 19 deletion and L858R was 31.1 and 104.7, respectively. In all, 92 (62.1%) patients showed high 2^−ΔΔct expression and 56 patients (37.9%) low 2^−ΔΔct expression. The mean age was 65.6 years. Progression-free survival of 19 deletion mutant patients with low versus high expression level was 17.07 versus 12.04 months (P = 0.004), respectively. Progression-free survival of L858 mutant patients was 13.75 and 7.96 months (P = 0.008), respectively. EGFR-mutant lung adenocarcinoma patients with lower EGFR gene expression had longer progression-free survival duration without interfering overall survival.

Keywords

Lung cancer adenocarcinoma EGFR mutation tyrosine kinase inhibitors polymerase chain reaction (PCR)oncogene

Introduction

Lung cancer is the leading cause of cancer-related death worldwide and remains a major health problem, with an incidence that is increasing in Taiwan.^1,2 Non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer and accounts for 80% of all lung cancer patients, the majority of whom have disease at an advanced stage at the time of diagnosis.³ Among NSCLC patients, 60% have subtype histology corresponding to adenocarcinoma. Recently, targeted therapy with tyrosine kinase inhibitors (TKIs)—based on the presence of tumor molecular markers—has become a treatment option for patients with advanced stage NSCLC. This strategy targets the epidermal growth factor receptor (EGFR).⁴ Among the 20%–60% of NSCLC patients harboring EGFR gene mutations, the response rate to TKIs is approximately 75%. Therefore, detection of EGFR mutations is important for predicting the response to TKIs in first-line therapy.^5,6 Previous studies have shown that for patients with TKI-sensitive EGFR mutations, progression-free survival (PFS), overall survival (OS), and quality of life are better in patients treated with TKIs compared with conventional chemotherapy.^7,8 As large tumor specimens are often difficult to obtain in patients with advanced stage NSCLC, a highly sensitive method for analysis of small samples is very important.⁹ The Scorpion amplification refractory mutation system (ARMS) is a highly sensitive technique, with a sensitivity of about 1% for the detection of EGFR mutations. This method involves analysis of polymerase chain reaction (PCR) products generated from small tumor specimens, such as pleural effusion fluid or tissue samples obtained by transbronchial biopsy.¹⁰ The Scorpion-ARMS method is an effective, rapid, and unique technique that has been approved by the US Food and Drug Administration (FDA) for the detection of EGFR mutations.¹¹ The two most common EGFR mutations in NSCLCs are deletions in exon 19 and a point mutation in codon 858 of exon 21 (L858R). These two mutations have been shown to account for 90% of all EGFR mutations in those who show good response to TKI treatment.^12,13 Real-time quantitative PCR has been shown to be a better method for quantification of gene expression than immunohistochemistry and fluorescence in situ hybridization immunostaining. Using real-time semi-quantitative PCR, relative expression of target genes can be calculated as 2^−ΔΔct.^14,15 The detection of EGFR mutations may influence treatment and prognosis, especially in NSCLC patients who received TKIs as first-line tumor therapy.^16,17 The relationship between quantitative expression levels of the different mutant EGFR genes and prognosis in patients who receive TKI treatment is still unknown, and represents an area for further investigation. We therefore conducted a retrospective analysis to investigate the impact of EGFR gene expression levels in advanced stage lung adenocarcinoma patients. We also examined if baseline clinical parameters affect EGFR gene expression levels.

Materials and methods

Patient and clinical characteristics

The present retrospective study reviewed consecutive patients in the period from January 2011 to October 2013 at the Kaohsiung Chang Gung Memorial Hospital, a tertiary medical center in southern Taiwan. Patients were followed-up until March 2015. Patients eligible for this study were adults aged ≥18 years with NSCLC, confirmed histologically or cytologically as stage III or IV adenocarcinoma, with a deletion in exon 19 or L858R mutation of the EGFR gene, and who received EGFR-TKIs as first-line cancer therapy. Patients were excluded if they had received other chemotherapies, immunological therapies, or targeted therapy. All patients had to have completed assessment of the clinical parameters, blood biochemistry analysis, serum carcinoembryonic antigen (CEA), chest radiography, chest computed tomography, brain magnetic resonance imaging, and bone scintigraphy 4 weeks before initial treatment. Clinical parameters included age, sex, smoking status, body mass index (BMI), and Eastern Cooperative Oncology Group (ECOG) performance status (PS). This study was approved by the Institutional Review Board of Kaohsiung Chang Gung Memorial Hospital. The requirement to obtain informed consent from patients was waived.

EGFR mutation testing

Tumor specimens were obtained by bronchoscopy, computed tomography (CT)-guided biopsy, pleural effusion cytology, or surgical procedures. The specimens were fixed with formalin and embedded in paraffin. EGFR mutational analyses were performed using Scorpion-ARMS PCR. Using fragments amplified from genomic DNA extractions (using an EGFR RGQ PCR Kit, Qiagen), real-time PCR reactions were performed in order to detect specific EGFR gene mutations.^18,19 Deletions in exon 19 and L858R mutations were the two most common types of EGFR gene mutation. To determine the expression of target genes in different specimens, normalization based on internal reference gene expression was performed, and the average of the normalized cycle threshold value (Δct) was defined as the peak of the cycle at maximum curvature of the second derivative growth curve. For real-time semi-quantification of target gene expression, 2^−ΔΔct was calculated, where Δct = ct (target gene) − ct (internal reference gene) that was used for interpretation of the results. This calculation assumes 100% efficiency for all PCR reactions.

EGFR-TKI treatment response evaluation

To assess disease status and tumor treatment response, patients were routinely followed up by chest radiography for several weeks and chest CT was performed every 2–3 months. Disease progression was evaluated by a clinician, based on Response Evaluation Criteria in Solid Tumors (RECIST) criteria 1.1.²⁰ PFS was defined as the time interval between the first day of treatment with EGFR-TKIs and either the date on which disease progression was established, the date on which the patient died (from any cause), or the date of the final study visit at the end of follow-up. OS was defined as the time interval between the first day of treatment with EGFR-TKIs and either the date of death, the date of the final study visit at the end of follow-up, or loss to follow-up.

Statistical analyses

SPSS statistical software, version 21.0 (SPSS Inc., Chicago, IL, USA), was used for statistical analysis. The relationships between EGFR status and clinical characteristics were analyzed with Fisher’s exact test, independent t-tests, and Mc Nemar and Kappa tests. MedCalc (version 14.10.2) was used for analyses. Receiver operating characteristic (ROC) curves and Youden’s index were used to evaluate the optimal cutoff values for 2^−ΔΔct, in order to determine the prognostic value of EGFR gene expression levels. To understand the influences of baseline clinical parameters on EGFR gene expression levels, we used a chi-square test to compare categorical variables, and an independent samples t-test to compare continuous data.

The survival curves of PFS and OS were prepared using the Kaplan–Meier method, and survival for different patient subgroups was compared by the log-rank test. Statistical significance was defined as P < 0.05 (two-tailed).

Results

Patient characteristics

Of 926 patients who were diagnosed with lung cancer from January 2011 to October 2013, 442 patients with advanced lung adenocarcinoma were screened for EGFR mutations. Among these, 224 (50.7%) had EGFR gene mutations. A total of 148 patients were ultimately diagnosed with EGFR mutations that are common in advanced lung adenocarcinoma, using the Scorpion-ARMS and 2^−ΔΔct method. The clinical and pathological characteristics of these 148 patients are summarized in Table 1. The mean age of the study population was 65.6 years, 55.5% were females, and 68.2% never smoked. ECOG PS was less than 2 in 88.5% of patients, and 85.9% had cancer at stage IV. The mean CEA value was 184. Exon 19 deletions accounted for 48.6% of EGFR gene mutations, while the L858R mutation accounted for 51.4%. PFS was greater than 12 months for both subtypes of patient.

Table 1.

Clinical characteristics and therapy responses of all 148 patients.

Gender
Male	66 (44.5%)
Female	82 (55.5%)
Age	65.64 ± 11.50
Age
<70	90 (60.8%)
≥70	58 (39.2%)
BMI	23.71 ± 4.03
ECOG PS
<2	131 (88.5%)
≥2	17(11.5%)
Smoking
Never	101 (68.2%)
Current	47 (31.8%)
Stage
IIIB	21 (14.1%)
IV	127 (85.9%)
CEA	184.1 ± 533.8
PFS 12 ms
<12 ms	72 (48.6%)
≥12 ms	76 (51.4%)
EGFR test
19Del	72 (48.6%)
L858R	76 (51.4%)

BMI: body mass index; ECOG: Eastern Cooperative Oncology Group; PS: performance status; CEA: carcinoembryonic antigen; EGFR: epidermal growth factor receptor; PFS: progression-free survival; Exon 19 deletion and L858R mutations were defined as common mutations.

Median PFS for patients with a deletion in exon 19 and patients with the L858R EGFR mutation was 13.2 and 12.3 months, respectively. For this reason, we used 12 months of PFS to further analyze the best cutoff points for the 2^−ΔΔct value for exon 19 deletions and the L858R mutation; these were determined by ROC curves and Youden’s Index as 31.1 and 104.7, respectively. Patients were classified as having high or low 2^−ΔΔct values based on the above cutoff values, linked to the intensity of EGFR gene expression. In all, 92 patients (62.1%) had high 2^−ΔΔct expression and 56 (37.9%) had low 2^−ΔΔct expression. Comparisons of groups with high and low 2^−ΔΔct expression did not reveal an influence for baseline clinical parameters including sex, BMI, ECOG PS, smoking history, disease stage, and CEA values on 2^−ΔΔct expression (Table 2).

Table 2.

Univariate and multivariate analyses of clinical factors of the different 2^−ΔΔct expression.

	Low 2^−ΔΔct N: 92	High 2^−ΔΔct N: 56	UnivariateP value	Confidence interval (CI)	MultivariateP value
Gender			0.489		0.254
Male	39 (42.4%)	27 (48.2%)
Female	53 (57.6%)	29 (51.8%)
Age	67.2 ± 10.8	63.0 ± 12.2	0.039	0.862–1.007	0.076
Age			0.171		0.818
<70	52 (56.5%)	38 (67.9%)
≥70	40 (43.5%)	18 (32.1%)
BMI	23.9 ± 4.2	23.3 ± 3.5	0.449		0.909
ECOG PS			0.763		0.531
<2	82 (89.1%)	49 (87.5%)
≥2	10 (10.9%)	7 (12.5%)
Smoking			0.242		0.478
Never	66 (71.7%)	35 (62.5%)
Current	26 (28.3%)	21 (37.5%)
Stage			0.600		0.898
IIIB	15 (16.3%)	6 (10.7%)
IV	77 (83.7%)	50 (89.3%)
CEA	168.8 ± 532.8	208.4 ± 539.6	0.671		0.522
PFS 12 ms			0.022	0.069–0.663	0.008
<12 ms	38 (41.3%)	34 (60.7%)
≥12 ms	54 (58.7%)	22 (39.3%)
EGFR test			0.000	15.215–244.678	0.000
19Del	23 (25.0%)	49 (87.5%)
L858R	69 (75.0%)	7 (12.5%)

BMI: body mass index; ECOG: Eastern Cooperative Oncology Group; PS; performance status; CEA: carcinoembryonic antigen; EGFR: epidermal growth factor receptor; PFS: progression-free survival; 19Del: Exon 19 deletion; L858R: Exon 21 L858R mutations.

Relationship between PFS and clinical factors

Overall, PFS in patients with low 2^−ΔΔct was longer than in the high expression group (14.93 and 10.89 months, respectively; P = 0.01; Figure 1). The effects of specific types of EGFR gene mutation on PFS were also analyzed. For analysis of PFS, patients were allocated to one of the four groups: (1) patients with deletions in exon 19 and low 2^−ΔΔct expression, (2) patients with an L858R gene mutation and low 2^−ΔΔct expression, (3) patients with deletions in exon 19 and high 2^−ΔΔct expression, and (4) patients with an L858R gene mutation and high 2^−ΔΔct gene expression. For patients with deletions in exon 19, those in the low expression group had better PFS than those in the high expression group (17.07 vs 12.04 months; P = 0.004; Figure 2(a)). Similar effects on PFS were found for patients with the L858R mutation, with low expression associated with greater PFS, compared with high expression (13.75 and 7.96 months, respectively; P = 0.008; Figure 2(b)). Patients with low gene expression of the exon 19 deletion had greater PFS than those with low expression of the L858R mutation (17.79 vs 13.75 months, respectively; P = 0.044; Figure 2(c)). Similarly, PFS was better in patients with high expression of the exon 19 deletion, compared with those with high expression of the L858R mutation (12.04 vs 7.96 months, respectively; P = 0.019; Figure 2(d)). PFS in the high expression exon 19 and L858R mutations groups and the low expression exon 19 and L858R mutations groups was 17.07, 13.75, 12.04, and 7.96 months, respectively (P = 0.001; Figure 3).

Figure 1.

Progression-free survival according to low and high 2^−ΔΔct gene expression among patients with EGFR-mutant adenocarcinoma of lung cancer who were treated using first-line tyrosine kinase inhibitors.

Figure 2.

Progression-free survival of EGFR-mutant adenocarcinoma of lung cancer patients treated with first-line tyrosine kinase inhibitors: (a) impact of EGFR mutation gene expression on the outcome of 19 deletion patients; (b) impact of EGFR mutation gene expression on the outcome of L858R patients; (c) impact of EGFR mutation gene expression on the outcome of low gene expression patients; and (d) impact of EGFR mutation gene expression on the outcome of high gene expression patients.

Figure 3.

Combination of different kinds of EGFR mutation gene expression impacted patient’s PFS.

Discussion

Preclinical studies have shown that the EGFR-associated signaling pathway has roles in cell functions important for cancer development and progression, including activation of tumor cell proliferation, angiogenesis, induction of apoptosis, and metastasis.²¹ The anti-tumor activity of TKIs (via inhibition of EGFR phosphorylation) depends on the concentrations of the drug in tumor tissue.^22,23 Consequently, its anti-tumor effects are determined by the efficiency of drug delivery to the tumor. In this study, we found that in patients with advanced adenocarcinoma of the lung, and who have EGFR mutations, the level of EGFR expression was correlated with the response to therapy. Moreover, a previous study found that high levels of EGFR gene expression in tumors influenced EGFR autophosphorylation and enhanced the activity of downstream signaling pathways (involving Akt, ERK 1/2, STAT, Shc, etc.)^24–26 associated with cancer progression. Thus, greater drug concentrations in tumors with high EGFR expression may be needed to inhibit tumor development. Based on these findings, we hypothesized that variations in drug efficacy in tumors with the same EGFR mutations are due to differences in autophosphorylation and activation states of downstream signaling components.²⁷ This scenario is consistent with the results of this study, showing that the group with high EGFR gene expression had reduced PFS, compared with the group with low EGFR gene expression. Although previous studies found no association between EGFR gene expression, PFS, and overall survival,²⁸ but these studies were no further analyzed median level of EGFR expression and assess ROC value in both subtypes of patients. Tumor sensitivity was markedly influenced by the type of EGFR mutation, most likely as a result of the effects of different mutations on receptor structure and binding affinity for the inhibitor.^29,30 Indeed, deletions in exon 19 map to one end of the C-helix (which is sensitive to conformational changes), while the L858R mutation lies in the N-terminal portion of the activation loop A of the kinase.³¹ Differences in patterns of EGFR autophosphorylation were found between cell lines harboring deletions in exon 19 and those with an L858R point mutation in exon 21.²⁹ High intracellular adenosine triphosphate (ATP) concentration and other mechanisms may be an accurate reflection of a greater objective response rate to EGFR-TKIs.^32,33 Several studies demonstrated a consistent PFS benefit across all clinical subgroups in patients with deletions in exon 19 and those with the L858R mutation in exon 21.^34,35 Therefore, the essential diagnostic strategy was to identify EGFR-activating mutations that are closely related to the efficacy of EGFR-targeted drugs. To our knowledge, this is the first study to investigate if EGFR gene expression levels are a useful prognostic factor for advanced stage adenocarcinoma of the lung, in patients with different types of EGFR mutation receiving EGFR-TKIs. The 2^−ΔΔct method was used to calculate EGFR gene expression in order to determine the feasibility of using EGFR as a marker gene for predicting clinical outcome. Further studies are needed to validate our findings. However, this study has several limitations. First, this study is retrospective and based on a small patient population; a prospective trial with a large sample size is needed to verify our findings. Second, we have not demonstrated the mechanisms that account for differences in PFS in patients with the same mutation. In addition to the above-mentioned mechanisms that may affect tumor response, heterogeneity and complexity within the tumor microenvironment may also result in distinct biochemical characteristics and acquired resistance may affect drug efficacy.^36–38 Although it is possible that variation in outcomes is due to differences in EGFR gene expression levels, a previous cell line study did not find changes in therapeutic response with variations in phosphorylation levels of EGFR downstream signaling molecules.³⁹ Prospective studies are therefore needed to determine how EGFR alterations influence outcomes in patients with advanced NSCLC treated with EGFR-TKIs.

Conclusion

EGFR-mutant lung adenocarcinoma patients with lower EGFR gene expression had longer PFS duration without interfering OS.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Chang

Chen

Shan

. Comprehensive analysis of the incidence and survival patterns of lung cancer by histologies, including rare subtypes, in the era of molecular medicine and targeted therapy: a nation-wide cancer registry-based study from Taiwan. Medicine 2015; 94: e969.

Henley

Richards

Underwood

. Lung cancer incidence trends among men and women—United States, 2005–2009. MMWR Morb Mortal Wkly Rep 2014; 63: 1–5.

Midha

Dearden

McCormack

. EGFR mutation incidence in non-small-cell lung cancer of adenocarcinoma histology: a systematic review and global map by ethnicity (mutMapII). Am J Cancer Res 2015; 5: 2892–2911.

Mok

Thongprasert

. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N Engl J Med 2009; 361: 947–957.

Chen

Lai

Chang

. The impact of clinical parameters on progression-free survival of non-small cell lung cancer patients harboring EGFR-mutations receiving first-line EGFR-tyrosine kinase inhibitors. Lung Cancer 2016; 93: 47–54.

Yang

Schuler

. Afatinib versus cisplatin-based chemotherapy for EGFR mutation-positive lung adenocarcinoma (LUX-lung 3 and LUX-lung 6): analysis of overall survival data from two randomised, phase 3 trials. Lancet Oncol 2015; 16: 141–151.

Rosell

Carcereny

Gervais

. Spanish Lung Cancer Group in collaboration with Groupe Francais de P-C, Associazione Italiana Oncologia T: erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol 2012; 13: 239–246.

Zhou

Chen

. Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer (OPTIMAL, CTONG-0802): a multicentre, open-label, randomised, phase 3 study. Lancet Oncol 2011; 12: 735–742.

Dooms

Vliegen

Vander Borght

. Suitability of small bronchoscopic tumour specimens for lung cancer genotyping. Respiration 2014; 88: 371–377.

10.

Kimura

Kasahara

Kawaishi

. Detection of epidermal growth factor receptor mutations in serum as a predictor of the response to gefitinib in patients with non-small-cell lung cancer. Clin Cancer Res 2006; 12: 3915–3921.

11.

Shi

Thongprasert

. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol 2014; 9: 154–162.

12.

Chen

Molina-Vila

Ruan

. Coexistence of EGFR T790M mutation and common activating mutations in pretreatment non-small cell lung cancer: a systematic review and meta-analysis. Lung Cancer 2016; 94: 46–53.

13.

Park

Tan

O’Byrne

. Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial. Lancet Oncol 2016; 17: 577–559.

14.

Livak

Schmittgen

. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001; 25: 402–408.

15.

Hojati

Orangi

. HER-2/neu gene amplification assessment in breast cancer patients in Isfahan province by real time PCR, differential PCR and immunohistochemistry. Gene 2012; 497: 237–242.

16.

Haspinger

Agustoni

Torri

. Is there evidence for different effects among EGFR-TKIs? Systematic review and meta-analysis of EGFR tyrosine kinase inhibitors (TKIs) versus chemotherapy as first-line treatment for patients harboring EGFR mutations. Crit Rev Oncol Hematol 2015; 94: 213–227.

17.

Zhang

Cao

. Exon 19 deletion of epidermal growth factor receptor is associated with prolonged survival in brain metastases from non-small-cell lung cancer. Tumour Biol 2015; 36: 9251–9258.

18.

Horiike

Kimura

Nishio

. Detection of epidermal growth factor receptor mutation in transbronchial needle aspirates of non-small cell lung cancer. Chest 2007; 131: 1628–1634.

19.

Jacobson

Lundahl

Mellstedt

. Gene expression analysis using long-term preserved formalin-fixed and paraffin-embedded tissue of non-small cell lung cancer. Int J Oncol 2011; 38: 1075–1081.

20.

Eisenhauer

Therasse

Bogaerts

.New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009; 45: 228–247.

21.

Laskin

Sandler

. Epidermal growth factor receptor: a promising target in solid tumours. Cancer Treat Rev 2004; 30: 1–17.

22.

Knight

Di Nicolantonio

Whitehouse

. The in vitro effect of gefitinib (“Iressa”) alone and in combination with cytotoxic chemotherapy on human solid tumours. BMC Cancer 2004; 4: 83.

23.

Kobayashi

Togashi

Yatabe

. EGFR exon 18 mutations in lung cancer: molecular predictors of augmented sensitivity to afatinib or neratinib as compared with first- or third-generation TKIs. Clin Cancer Res 2015; 21: 5305–5313.

24.

Roskoski

Jr.

The ErbB/HER family of protein-tyrosine kinases and cancer. Pharmacol Res 2014; 79: 34–74.

25.

Chung

Rho

. Clinical and molecular evidences of epithelial to mesenchymal transition in acquired resistance to EGFR-TKIs. Lung Cancer 2011; 73: 176–182.

26.

Zhang

Fan

. Polymorphisms in epidermal growth factor receptor (EGFR) and AKT1 as possible predictors of clinical outcome in advanced non-small-cell lung cancer patients treated with EGFR tyrosine kinase inhibitors. Tumour Biol 2016; 37: 1061–1069.

27.

Kim

Apetri

Luo

. Differential effects of tyrosine kinase inhibitors on normal and oncogenic EGFR signaling and downstream effectors. Mol Cancer Res 2015; 13: 765–774.

28.

Dziadziuszko

Witta

Cappuzzo

. Epidermal growth factor receptor messenger RNA expression, gene dosage, and gefitinib sensitivity in non-small cell lung cancer. Clin Cancer Res 2006; 12: 3078–3084.

29.

Okabe

Okamoto

Tamura

. Differential constitutive activation of the epidermal growth factor receptor in non-small cell lung cancer cells bearing EGFR gene mutation and amplification. Cancer Res 2007; 67: 2046–2053.

30.

Abourbeh

Itamar

Salnikov

. Identifying erlotinib-sensitive non-small cell lung carcinoma tumors in mice using [¹¹C]erlotinib PET. EJNMMI Res 2015; 5: 4.

31.

Yun

Boggon

. Structures of lung cancer-derived EGFR mutants and inhibitor complexes: mechanism of activation and insights into differential inhibitor sensitivity. Cancer Cell 2007; 11: 217–227.

32.

Hammerman

Janne

Johnson

. Resistance to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer. Clin Cancer Res 2009; 15: 7502–7509.

33.

Wang

Huang

. Afatinib circumvents multidrug resistance via dually inhibiting ATP binding cassette subfamily G member 2 in vitro and in vivo. Oncotarget 2014; 5: 11971–11985.

34.

Kuan

Kuo

Chen

. Overall survival benefits of first-line EGFR tyrosine kinase inhibitors in EGFR-mutated non-small-cell lung cancers: a systematic review and meta-analysis. Br J Cancer 2015; 113: 1519–1528.

35.

Baek

Sun

Min

. Efficacy of EGFR tyrosine kinase inhibitors in patients with EGFR-mutated non-small cell lung cancer except both exon 19 deletion and exon 21 L858R: a retrospective analysis in Korea. Lung Cancer 2015; 87: 148–154.

36.

Murugaesu

Chew

Swanton

. Adapting clinical paradigms to the challenges of cancer clonal evolution. Am J Pathol 2013; 182: 1962–1971.

37.

Kimura

Suminoe

Kasahara

. Evaluation of epidermal growth factor receptor mutation status in serum DNA as a predictor of response to gefitinib (IRESSA). Br J Cancer 2007; 97: 778–784.

38.

Han

Zhao

. EGFR, KRAS and ROS1 variants coexist in a lung adenocarcinoma patient. Lung Cancer 2016; 95: 94–97.

39.

Carey

Garton

Romero

. Kinetic analysis of epidermal growth factor receptor somatic mutant proteins shows increased sensitivity to the epidermal growth factor receptor tyrosine kinase inhibitor, erlotinib. Cancer Res 2006; 66: 8163–8171.

Impact of epidermal growth factor receptor gene expression level on clinical outcomes in epidermal growth factor receptor mutant lung adenocarcinoma patients taking first-line epidermal growth factor receptor–tyrosine kinase inhibitors

Abstract

Keywords

Introduction

Materials and methods

Patient and clinical characteristics

EGFR mutation testing

EGFR-TKI treatment response evaluation

Statistical analyses

Results

Patient characteristics

Relationship between PFS and clinical factors

Discussion

Conclusion

Footnotes

Declaration of conflicting interests

Funding

References