|
Advertisement |
|
|
||
 |
|
|||||
|
|||||
|
 |
||||||
|
||||||
|
||||||
|
Journal of Clinical Oncology, Vol 24, No 31 (November 1), 2006: pp. 5034-5042 © 2006 American Society of Clinical Oncology. DOI: 10.1200/JCO.2006.06.3958 Molecular Predictors of Outcome With Gefitinib in a Phase III Placebo-Controlled Study in Advanced Non–Small-Cell Lung Cancer
From the University of Colorado Cancer Center, Aurora, CO; Medical University of Gdansk, Gdansk, Poland; Christie Hospital, Manchester; AstraZeneca, Macclesfield, United Kingdom; Johns Hopkins Singapore International Medical Center, Singapore; Tata Memorial Hospital, Mumbai, India; Arnaldo Vieira de Carvalho Cancer Institute, São Paulo, Brazil; Oncology Institute Ion Chiricuta, Cluj-Napoca, Romania; and Asklepios Fachkliniken, Gauting, Germany Address reprint requests to Fred R. Hirsch, MD, PhD, University of Colorado Cancer Center, PO Box 6511, Mail Stop 8111, Aurora, CO 80045; e-mail: Fred.Hirsch{at}UCHSC.edu
Purpose: The phase III Iressa Survival Evaluation in Lung Cancer (ISEL) trial compared gefitinib with placebo in 1,692 patients with refractory advanced non–small-cell lung cancer. We analyzed ISEL tumor biopsy samples to examine relationships between biomarkers and clinical outcome after gefitinib treatment in a placebo-controlled setting. Methods: Biomarkers included epidermal growth factor receptor (EGFR) gene copy number by fluorescence in situ hybridization (n = 370); EGFR (n = 379) and phosphorylated Akt (p-Akt) protein expression (n = 382) by immunohistochemistry; and mutations in EGFR (n = 215), KRAS (n = 152), and BRAF (n = 118). Results: High EGFR gene copy number was a predictor of a gefitinib-related effect on survival (hazard ratio [HR], 0.61 for high copy number and HR, 1.16 for low copy number; comparison of high v low copy number HR, P = .045). EGFR protein expression was also related to clinical outcome (HR for positive, 0.77; HR for negative, 1.57; comparison of high v low protein expression HR, P = .049). Patients with EGFR mutations had higher response rates than patients without EGFR mutations (37.5% v 2.6%); there were insufficient data for survival analysis. No relationship was observed between p-Akt protein expression and survival outcome, and the limited amount of data collected for KRAS and BRAF mutations prevented any meaningful evaluation of clinical outcomes in relation to these mutations. Conclusion: EGFR gene copy number was a predictor of clinical benefit from gefitinib in ISEL. Additional studies are warranted to assess these biomarkers fully for the identification of patients most likely to benefit from gefitinib treatment.
Many translational and clinical cancer research efforts aim to identify biomarkers that may predict patients most likely to respond to treatment. The epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) gefitinib and erlotinib have been studied extensively in clinical trials,1-8 and the association of EGFR-related biomarkers with EGFR-TKI clinical outcome has also been investigated. Sensitivity to novel EGFR inhibitors may be influenced by a high EGFR gene copy number, with patients reported to experience increased gefitinib or erlotinib efficacy compared with a low EGFR gene copy number.9-11 Mixed results have been reported for EGFR protein expression and response to EGFR-TKIs; no association was seen in the IRESSA Dose Evaluation in Advanced Lung Cancer (IDEAL) trials,12 whereas others observed significant correlations between EGFR protein expression and response or survival with gefitinib and erlotinib.9,11,13 Phospho-Akt expression also seems to correlate with improved clinical outcome with gefitinib, but only in the subgroup of patients who coexpress EGFR.14 Activating EGFR mutations have been reported in many patients responding to EGFR-TKIs, and seem to correlate with clinical response to EGFR-TKIs.15-19 However, some patients without an EGFR mutation responded to EGFR-TKIs and some with an EGFR mutation failed to respond.9,20-22 To date, association between EGFR mutations and survival has been demonstrated mainly in Asian studies.15,17,21 KRAS mutations have been associated with resistance to gefitinib and erlotinib, although EGFR and KRAS mutations seem mutually exclusive.23 KRAS and BRAF mutations may result in constitutive signaling through the oncogenic Ras/Raf/Mek/Erk pathway, and more than 30 BRAF mutations have been identified with human cancers.24,25 The Iressa Survival Evaluation in Lung Cancer (ISEL) trial was a double-blind, placebo-controlled, parallel-group, multicenter, phase III survival study that randomly assigned 1,692 patients with previously treated, locally advanced or metastatic non–small-cell lung cancer in a 2:1 ratio to receive gefitinib 250 mg/d or placebo, plus best supportive care.26 Gefitinib was associated with some improvement in survival in the overall (hazard ratio [HR], 0.89; 95% CI, 0.77 to 1.02; P = .087) and adenocarcinoma (HR, 0.84; 95% CI, 0.68 to 1.03; P = .089) coprimary populations, but failed to reach statistical significance in the primary analysis using a log-rank test. Preplanned subset analyses showed marked heterogeneity in survival between patient groups, and never smokers (HR, 0.67; 95% CI, 0.49 to 0.92; P = .012) or patients of Asian origin (HR, 0.66; 95% CI, 0.48 to 0.91; P = .01) achieved a significant survival improvement with gefitinib versus placebo. The ISEL study provides the first opportunity to assess the relationship between biomarkers (EGFR gene copy number; EGFR and phosphorylated Akt (p-Akt) protein expression; and EGFR, KRAS, and BRAF mutations) and clinical outcome after treatment with gefitinib in a placebo-controlled setting.
Clinical Study Design Full details of the ISEL study design have been published previously.26 Eligible patients had received one or two prior chemotherapy regimens but were refractory or intolerant to their most recent chemotherapy regimen.
Biomarker Analysis
EGFR Gene Copy Number
Other Biomarkers
Statistical Analyses Cox proportional hazards models investigated the treatment effect of gefitinib relative to placebo on survival in different subsets. HRs, 95% CIs, and P values were determined for the subgroups (positive, negative, and unknown) for each biomarker, and Kaplan-Meier curves were produced. Results in the unknown subsets were consistent with those in the overall population and therefore are not presented. Supportive analyses for time to treatment failure (TTF) and objective response rate were also conducted. If a biomarker had too few results for meaningful analysis, only a descriptive summary was produced.
Demographic and Biomarker Characteristics Demographic characteristics for patients with assessable tissue samples for biomarker analysis were generally comparable to the overall ISEL population, although there were few samples from never smokers or patients of Asian origin (Table 1). For patients assessable for EGFR gene copy number and EGFR and p-Akt protein expression, survival HRs generally were consistent with the overall population. However, the survival HRs from Cox regression analysis for patients assessable for EGFR, KRAS, and BRAF mutations were worse than the overall population, suggesting these subsets may not represent the overall population.
Of 1,692 patients randomly assigned, 460 (27.2%) had tissue samples assessable for one or more biomarker analyses: EGFR gene copy number (370 patients); EGFR protein (379 patients) and p-Akt protein expression (382 patients); EGFR (215 patients), KRAS (152 patients), and BRAF mutations (118 patients; Tables 1 and 2). The majority of patients with a high EGFR gene copy number were also positive for EGFR protein expression, and the majority of patients positive for EGFR mutation also had a high EGFR gene copy number and were positive for EGFR protein expression (Fig 1).
Biomarker Analysis and Clinical Outcome EGFR gene copy number. Altogether, 114 patients (30.8%) had a high EGFR gene copy number. They achieved significantly better survival with gefitinib compared with placebo than patients with a low EGFR gene copy number (comparison of HRs high v low copy number, P = .045; Fig 2). In patients with a high EGFR gene copy number, the risk of death during the follow-up period was 39% lower among patients receiving gefitinib compared with those receiving placebo (HR, 0.61; 95% CI, 0.36 to 1.04; P = .067).
Median survival among patients with a high EGFR gene copy number was 8.3 and 4.5 months with gefitinib and placebo, respectively. No apparent difference in survival between gefitinib and placebo was observed in patients with a low EGFR gene copy number (HR, 1.16; 95% CI, 0.81 to 1.64; P = .417). Consistent with overall survival, patients who had a high EGFR gene copy number seemed to achieve better objective response rate and TTF than those with a low EGFR gene copy number (Table 3). After the results suggesting high EGFR gene copy number is predictive of a gefitinib-related treatment effect over placebo on overall survival, additional exploratory post-hoc analyses within subgroups were undertaken. HRs in favor of gefitinib-treated patients who had a high EGFR gene copy number were observed consistently across subgroups, even in patients with clinical factors usually considered to be least likely to benefit (eg, smokers and patients with nonadenocarcinoma; Table 4). With gefitinib, longer median survival was seen in patients with a high versus low EGFR gene copy number (8.3 v 4.3 months, respectively; HR, 0.78; 95% CI, 0.54 to 1.13). In contrast, with placebo, shorter median survival was seen in patients with a high versus low EGFR gene copy number (4.5 v 6.2 months, respectively; HR, 1.41; 95% CI, 0.84 to 2.35), indicating that the longer survival in gefitinib-treated patients with a high EGFR gene copy number was unlikely to be due to a prognostic effect.
EGFR protein expression. High EGFR protein expression was present in 264 patients (69.6%), and EGFR-positive patients achieved significantly better survival with gefitinib versus placebo than patients with EGFR protein expression–negative tumors (interaction test P = .049; Fig 3). The survival benefit for patients with EGFR protein expression–positive tumors treated with gefitinib (HR, 0.77; 95% CI, 0.56 to 1.08; P = .126) was slightly greater than for the overall study population (Table 1), with no evidence of a survival benefit of gefitinib to patients with EGFR protein expression–negative tumors (HR, 1.57; 95% CI, 0.86 to 2.87; P = .140). EGFR protein expression–positive patients also seemed to achieve better response rates (8.2% v 1.5%) than EGFR protein expression–negative patients (Table 3).
p-Akt protein expression. No relationship was observed between p-Akt status and survival outcome (interaction test P = .778; Fig 4). Although differences in response rates between gefitinib and placebo were slightly larger in p-Akt–positive than p-Akt–negative patients, there was no difference in overall survival or TTF (Table 3).
EGFR mutations. Of the 215 patients assessable for mutation detection, 26 (12.1%) were positive for EGFR mutation. Sequencing detected 16 EGFR mutations and ARMS detected 17 EGFR mutations (nine exon 21 L858R and eight exon 19 G2235-A2249 deletions). Furthermore, sequencing failed to detect 10 of these 17 mutations identified by ARMS, indicating ARMS is more sensitive than sequencing. Given that ARMS is designed to detect specific mutations, the use of sequencing was able to detect an additional six types of exon 19 deletions and four other point mutations. The EGFR mutations were distributed across exons 18, 19, and 21; the most frequently observed mutations were exon 19 deletions (14 patients [53.8%] with mutations) and exon 21 point mutations L858R/L861Q (11 patients [42.3%]) including one patient who had a double mutation delL747-P753 ins Q in exon 19 and L858R in exon 21. One patient (3.8%) had a G719A mutation in exon 18. Patients who were female, never smokers, of Asian origin, or had adenocarcinoma histology were more likely to have EGFR mutations than males, smokers, those of non-Asian origin, or patients with alternative histology (Fig 5).
Objective tumor response rates with gefitinib were higher among patients positive for EGFR mutation (37.5%; six of 16 patients) than patients negative for EGFR mutation (2.6%; three of 116 patients). There were responders and nonresponders in both the patient group with exon 19 deletions and the group with exon 21 mutations. Evaluation of survival outcomes and TTF were limited because there were only 10 deaths (seven of 21 patients receiving gefitinib; three of five patients receiving placebo) and 15 treatment failures (11 of 21 patients receiving gefitinib; four of five patients receiving placebo) among the 26 patients with tumors positive for EGFR mutation. For patients with tumors negative for EGFR mutation, there were 130 deaths (93 of 132 patients receiving gefitinib; 37 of 57 patients receiving placebo) and 160 treatment failures (111 of 132 patients receiving gefitinib; 49 of 57 patients receiving placebo). However, the subgroup of patients assessable for mutation status may not represent the overall study population because the HR for this subgroup was worse than for the overall population. KRAS and BRAF mutations. Five different KRAS mutations were detected in 12 of 152 (7.9%) patients, whereas no BRAF mutations were detected in 118 patients. No KRAS mutations were found in samples with an EGFR mutation, and 11 of 12 KRAS mutations were in samples from smokers. None of the six assessable patients treated with gefitinib who had a KRAS-positive mutation had a tumor response (response rate, 0%; 95% CI, 0 to 39.3), and seven of 87 patients treated with gefitinib who were negative for KRAS mutation had a tumor response (response rate, 8%; 95% CI, 3.3 to 15.9). The limited amount of data prevents meaningful evaluation of clinical outcomes in relation to these mutations.
This article presents the largest analysis to date of the relationship between biomarkers and clinical response in a placebo-controlled study of gefitinib. We investigated six biomarkers in tumor samples from patients in the ISEL phase III study of gefitinib and found that high EGFR gene copy number measured by FISH was a predictor of a gefitinib-related effect versus placebo on overall survival (HR, 0.61; 95% CI, 0.36 to 1.04; P = .067). The statistically significant treatment by EGFR gene copy number interaction test (P = .045) indicates that the HRs for patients with high EGFR gene copy number (HR, 0.61) and low EGFR gene copy number (HR, 1.16) are different (ie, that EGFR gene copy number is a predictor of survival benefit with gefitinib compared with placebo). The possible survival benefit in patients with a high EGFR gene copy number in ISEL is consistent with the erlotinib BR21 study, in which a high EGFR gene copy number was associated with significantly longer survival while receiving erlotinib versus placebo (HR, 0.44; 95% CI, 0.23 to 0.82; P = .008) in univariate analysis.11 BR21 univariate analysis showed no significant difference in survival with erlotinib versus placebo among patients with a low EGFR gene copy number (HR, 0.85; 95% CI, 0.48 to 1.51; P = .59). Increased clinical benefit with gefitinib in patients with a high EGFR gene copy number has been reported in single-arm studies.9,10 Additional validation is required to confirm whether EGFR gene copy number could be a biomarker to identify patients most likely to benefit from gefitinib. However, in this study, patients with a high EGFR gene copy number seemed to fare worse than patients with a low EGFR gene copy number in the placebo group, supporting previous findings from surgically resected patients that high EGFR gene copy number is associated with poorer prognosis in the absence of EGFR-TKI therapy.27 Some studies have reported that increased EGFR gene copy number is not associated with outcome after gefitinib therapy.17,20 However, in these studies EGFR gene copy number was evaluated by quantitative PCR, rather than by FISH; results with the two different techniques should not be compared with each other.28 In this study, an association was observed between EGFR protein expression and clinical outcome with gefitinib. This was also seen in BR21, in which patients with EGFR expression had significantly reduced risk of death with erlotinib versus placebo (HR, 0.68; 95% CI, 0.49 to 0.95; P = .02). There was no evidence of a survival advantage for erlotinib versus placebo in patients with negative EGFR protein expression (HR, 0.93; 95% CI, 0.63 to 1.36; P = .70). These studies suggest that patients with low EGFR gene copy number or who have negative EGFR protein expression seem unlikely to benefit from EGFR-TKIs. Another study from our group has shown that this is especially true when patients have both a low EGFR gene copy number and negative immunohistochemistry results.13 In our study we have used the DAKO antibody kit system for EGFR protein expression assessment. The 10% cutoff level for a positive result was chosen at the outset as the most discriminating cutoff limit based on previous studies. The same antibody and cutoff criteria were used in the erlotinib BR21 study, and both studies showed an association between EGFR protein expression and clinical outcome.11 In agreement with previously published reports, patients with EGFR mutations had higher response rates with gefitinib, compared with patients without EGFR mutations.18,19 For patients with EGFR mutations in ISEL, the clinical characteristics overlapped those associated with greater clinical benefit with gefitinib therapy (females, Asian origin, never smokers, adenocarcinoma histology).22,29 This was also observed in BR21, although both studies identified EGFR mutations in other patient subgroups. In ISEL, EGFR mutation status was much more closely linked to clinical characteristics than high EGFR gene copy number (Fig 5). Of the two methods we used to identify EGFR mutations, the primary sequencing method was useful for detecting novel or rarely observed mutations, and the secondary ARMS method was used as a more sensitive technique for the more common mutations. Our analysis demonstrates that combined use of direct sequencing and ARMS highlight and therefore aid our understanding of false-negative results. Previous studies found an association between p-Akt and gefitinib sensitivity,9,14 but this was not seen in our study. Differences in response rates between gefitinib and placebo were slightly larger in p-Akt–positive patients than in p-Akt–negative patients, but no difference in overall survival or TTF was seen. KRAS mutations may be associated with a lack of sensitivity to EGFR-TKIs,23 but there were insufficient data from ISEL to allow meaningful evaluation of how KRAS and BRAF mutations correlate with clinical outcome. Investigators face a number of challenges when trying to analyze biomarkers, including availability of tumor samples. Although this study had assessable tissue samples from 460 patients, this represented only 27.2% of the overall ISEL population of 1,692 patients. Demographic analysis revealed that few samples were available from never smokers or patients of Asian origin. Previous studies have shown that mutations were significantly more frequent in these patients.30 Another aspect of biomarker analysis is that responsiveness to treatment with an EGFR-TKI may be due to a combination of various biologic factors. In this study, only 91 patients were assessable for all biomarkers and it was not feasible to conduct complex, multivariate analyses. In conclusion, the biomarker analysis from ISEL showed that high EGFR gene copy number was a predictive biomarker for a gefitinib effect versus placebo on overall survival in the context of the largest data set explored yet in NSCLC. This is consistent with previous reports, and future studies should determine its value in identifying patients most likely to benefit from treatment with gefitinib. EGFR protein expression may also be associated with clinical benefit; patients who had a low EGFR gene copy number or were negative for EGFR protein expression seemed unlikely to benefit from treatment with gefitinib. Additional validation work is required to confirm the predictive value of a high EGFR gene copy number for treatment with an EGFR-TKI versus chemotherapy.
Although all authors completed the disclosure declaration, the following authors or their immediate family members indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. For a detailed description of the disclosure categories, or for more information about ASCO’s conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
We thank Ann Gordon, PhD, from Complete Medical Communications, who provided medical writing support funded by AstraZeneca.
Supported in part by AstraZeneca; a National Cancer Institute-International Union Aganist Cancer Traslational Cancer Research Fellowship, funded by the National Cancer Institute (R.D.); and by Bristol-Myers Squibb and Pfizer (A.C.). Presented in part at the Annual Meeting of the American Association for Cancer Research-National Cancer Institute-European Organisation for Research and Treatment of Cancer, Philadelphia, PA, November 14-18, 2005. Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. Fukuoka M, Yano S, Giaccone G, et al: Multi-institutional randomized phase II trial of gefitinib for previously treated patients with advanced non-small-cell lung cancer. J Clin Oncol 21:2237-2246, 2003 2. Kris MG, Natale RB, Herbst RS, et al: Efficacy of gefitinib, an inhibitor of the epidermal growth factor receptor tyrosine kinase, in symptomatic patients with non-small cell lung cancer: A randomized trial. JAMA 290:2149-2158, 2003 3. Pérez-Soler R: Phase II clinical trial data with the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib (OSI-774) in non-small-cell lung cancer. Clin Lung Cancer 6:S20-S23, 2004 (suppl 1)[Medline] 4. Giaccone G, Herbst RS, Manegold C, et al: Gefitinib in combination with gemcitabine and cisplatin in advanced non–small-cell lung cancer: A phase III trial—INTACT 1. J Clin Oncol 22:777-784, 2004 5. Herbst RS, Giaccone G, Schiller JH, et al: Gefitinib in combination with paclitaxel and carboplatin in advanced non–small-cell lung cancer: A phase III trial—INTACT 2. J Clin Oncol 22:785-794, 2004 6. Herbst RS, Prager D, Hermann R, et al: TRIBUTE: A phase III trial of erlotinib hydrochloride (OSI-774) combined with carboplatin and paclitaxel chemotherapy in advanced non–small-cell lung cancer. J Clin Oncol 23:5892-5899, 2005 7. Shepherd FA, Pereira JR, Ciuleanu T, et al: Erlotinib in previously treated non-small-cell lung cancer. N Engl J Med 353:123-132, 2005 8. Gatzemeier U, Pluzanska A, Szczesna A, et al: Results of a phase III trial of erlotinib (OSI-774) combined with cisplatin and gemcitabine (GC) chemotherapy in advanced non-small cell lung cancer (NSCLC). J Clin Oncol 23:619s, 2004 (suppl; abstr 7010)[CrossRef] 9. Cappuzzo F, Hirsch FR, Rossi E, et al: Epidermal growth factor receptor gene and protein and gefitinib sensitivity in non–small-cell lung cancer. J Natl Cancer Inst 97:643-655, 2005 10. Hirsch FR, Varella-Garcia M, McCoy J, et al: Increased epidermal growth factor receptor gene copy number detected by fluorescence in situ hybridization associates with increased sensitivity to gefitinib in patients with bronchioloalveolar carcinoma subtypes: A Southwest Oncology Group study. J Clin Oncol 23:6838-6845, 2005 11. Tsao M-S, Sakurada A, Cutz J-C, et al: Erlotinib in lung cancer: Molecular and clinical predictors of outcome. N Engl J Med 353:133-144, 2005 12. Bailey LR, Kris M, Wolf M, et al: Tumor EGFR membrane staining is not clinically relevant for predicting response in patients receiving gefitinib ('Iressa', ZD1839) monotherapy for pretreated advanced non-small-cell lung cancer: IDEAL 1 and 2. Presented at the Am Assoc Cancer Res, Washington, DC, July 11-14, 2003 (Poster LB-212) 13. Hirsch FR, McCoy J, Cappuzzo F, et al: FISH and immunohistochemistry (IHC) can be used to select NSCLC patients, who will not benefit from gefitinib treatment. Lung Cancer 49:S38, 2005 (suppl 3) 14. Cappuzzo F, Magrini E, Ceresoli GL, et al: Akt phosphorylation and gefitinib efficacy in patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 96:1133-1141, 2004 15. Mitsudomi T, Kosaka T, Endoh H, et al: Mutations of the epidermal growth factor receptor gene predict prolonged survival after gefitinib treatment in patients with non–small-cell lung cancer with postoperative recurrence. J Clin Oncol 23:2513-2520, 2005 16. Taron M, Ichinose Y, Rosell R, et al: Activating mutations in the tyrosine kinase domain of the epidermal growth factor receptor are associated with improved survival in gefitinib-treated chemorefractory lung adenocarcinoma. Clin Cancer Res 11:5878-5885, 2005 17. Takano T, Ohe Y, Sakamoto H, et al: Epidermal growth factor receptor gene mutations and increased copy numbers predict gefitinib sensitivity in patients with recurrent non-small-cell lung cancer. J Clin Oncol 23:6829-6837, 2005 18. Paez JG, Jänne PA, Lee JC, et al: EGFR mutations in lung cancer: Correlation with clinical response to gefitinib therapy. Science 304:1497-1500, 2004 19. Lynch TJ, Bell DW, Sordella R, et al: Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 350:2129-2139, 2004 20. Bell DW, Lynch TJ, Haserlat SM, et al: Epidermal growth factor receptor mutations and gene amplification in non–small-cell lung cancer: Molecular analysis of the IDEAL/INTACT gefitinib trials. J Clin Oncol 23:8081-8092, 2005 21. Han SW, Kim TY, Hwang PG, et al: Predictive and prognostic impact of epidermal growth factor receptor mutation in non–small-cell lung cancer patients treated with gefitinib. J Clin Oncol 23:2493-2501, 2005 22. Tokumo M, Toyooka S, Kiura K, et al: The relationship between epidermal growth factor receptor mutations and clinicopathologic features in non-small cell lung cancers. Clin Cancer Res 11:1167-1173, 2005 23. Pao W, Wang TY, Riely GJ, et al: KRAS mutations and primary resistance of lung adenocarcinomas to gefitinib or erlotinib. PLoS Med 2:e17, 2005[CrossRef][Medline] 24. Ince WL, Jubb AM, Holden SN, et al: Association of k-ras, b-raf, and p53 status with the treatment effect of bevacizumab. J Natl Cancer Inst 97:981-989, 2005 25. Wan PT, Garnett MJ, Roe SM, et al: Mechanism of activation of the RAF-ERK signaling pathway by oncogenic mutations of B-RAF. Cell 116:855-867, 2004[CrossRef][Medline] 26. Thatcher N, Chang A, Parikh P, et al: Gefitinib plus best supportive care in previously treated patients with refractory advanced non-small-cell lung cancer: Results from a randomised, placebo-controlled, multicentre study (Iressa Survival Evaluation in Lung Cancer). Lancet 366:1527-1537, 2005[CrossRef][Medline] 27. Hirsch FR, Varella-Garcia M, Bunn PA Jr, et al: Epidermal growth factor receptor in non–small-cell lung carcinomas: Correlation between gene copy number and protein expression and impact on prognosis. J Clin Oncol 21:3798-3807, 2003 28. Dziadziuszko R, Witta SE, Cappuzzo F, et al: Epidermal growth factor receptor messenger RNA expression, gene dosage, and gefitinib sensitivity in non-small cell lung cancer. Clin Cancer Res 12:3078-3084, 2006 29. Pao W, Miller V, Zakowski M, et al: EGF receptor gene mutations are common in lung cancers from "never smokers" and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A 101:13306-13311, 2004 30. Shigematsu H, Lin L, Takahashi T, et al: Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 97:339-346, 2005 Submitted March 3, 2006; accepted August 23, 2006. Related Correspondence
This article has been cited by other articles:
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOP
ABSTRACT
INTRODUCTION
four copies in 
