Abstract
Background
To assess the role of various epidermal growth factor receptor (EGFR) mutations and HER2/3 protein expression as predictive markers of responsiveness to gefitinib therapy in Chinese patients with advanced non-small cell lung cancer (NSCLC).
Methods
A total of 106 Chinese NSCLC patients who had failed at least one chemotherapy regimen received gefitinib 250 mg once daily. All the 106 tumors from these patients were screened for mutations in the EGFR exons 18–24, and 84 tumors were studied by immunohistochemistry for HER2/3 expression and correlated with clinical treatment outcome.
Results
Patients with EGFR mutations had a significantly higher overall response rate (ORR), longer time to progression (TTP) and overall survival (OS) compared with those with wild-type receptor. No difference in ORR was observed between patients with exon 19 deletion and patients with other EGFR mutations. ORR in HER2-positive patients was significantly higher than in the HER2-negative group, irrespective of EGFR mutational status, and a trend for better ORR was observed for HER3-positive patients. HER2 and HER3 expression levels were not associated with any difference in terms of TTP and OS. Nevertheless, when considering the subgroups of non-responders to gefitinib, median TTP in patients with mutated EGFR was significantly longer than in those with no mutations (8.0 vs. 3.0 months, P = 0.0065). EGFR-mutated patients had no significant difference in ORR, TTP and OS according to HER2 and/or HER3 expression.
Conclusions
EGFR mutations are effective predictors for gefitinib efficacy in Chinese patients with advanced NSCLC. HER2 and HER3 expression does not provide any additional information for selecting patients most likely to benefit from gefitinib treatment.
Keywords: Non-small cell lung cancer, Epidermal growth factor receptor, Mutation, Gefitinib, HER2, HER3
Introduction
Non-small cell lung cancer (NSCLC) represents a major cause of cancer death worldwide (Jemal et al. 2006), with platinum-based chemotherapy being the standard treatment for patients with advanced disease (Schiller et al. 2002). Although new chemotherapy strategies have been developed, the prognosis of patients with inoperable disease remains extremely poor (Schiller et al. 2002). Several new molecules interfering with specific cancer-related pathways have been studied in the last few years, and promising results have been observed with agents targeting the epidermal growth factor receptor (EGFR) (Mendelsohn and Baselga 2000). The EGFR family includes four distinct transmembrane receptors, EGFR/erbB-1, HER2/erbB-2, HER3/erbB-3, and HER4/erbB-4 (Mendelsohn and Baselga 2000; Salomon et al. 1995). Ligand-induced EGFR activation triggers phosphorylation of the intracellular EGFR tyrosine kinase domain and ultimately results in tumor cell survival, proliferation and invasion (Asahina et al. 2006; Cappuzzo et al. 2003). Gefitinib (ZD 1839, Iressa®, AstraZeneca, UK) and erlotinib (OSI 774, Tarceva®, Genentech, US) are orally active EGFR tyrosine kinase inhibitors (TKIs) that have been extensively studied in NSCLC (Arteaga 2002), with erlotinib gaining Food and Drug Administration approval for the monotherapy treatment of NSCLC patients who have failed at least one chemotherapy regimen.
EGFR-TKIs have demonstrated significant antitumor activity in approximately 10% of unselected pretreated NSCLC patients (Thatcher et al. 2005; Shepherd et al. 2005). Retrospective analyses of large phase II and III trials with either gefitinib or erlotinib have shown a significant association between the response to EGFR-TKIs and female gender, adenocarcinoma histology, Asian ethnicity and, most of all, never-smoking history (Thatcher et al. 2005; Shepherd et al. 2005).
Biological mechanisms underlying TKI sensitivity and resistance have been extensively investigated. Several reports indicate that the presence of EGFR gene mutations, particularly exon 19 deletions, and EGFR gene gain, both of which are associated with a never-smoking history, predict response to TKIs (Lynch et al. 2004; Paez et al. 2004; Tsao et al. 2005). Whereas assessment of the relationship between EGFR protein expression and response has generated conflicting reports (Hirsch et al. 2006; Cappuzzo et al. 2003; Pao et al. 2005). Conversely, the presence of mutations in the K-ras gene and in EGFR exon 20 have been linked with resistance to these agents (Pao et al. 2005; Kobayashi et al. 2005).
HER2 is the major partner for EGFR, and preclinical studies have shown that HER2-overexpressing cancer cell lines or xenografts are sensitive to the inhibitory effects of gefitinib (Lenferink et al. 1998; Moasser et al. 2001). However, in a small retrospective study of gefitinib in NSCLC patients, no association was observed between HER2 expression, assessed by immunohistochemistry (IHC), and efficacy of the drug (Cappuzzo et al. 2003). Nevertheless, a recent Italian retrospective study in a cohort of NSCLC patients treated with gefitinib has shown that increased HER2 gene copy number, evaluated by fluorescence in situ hybridization (FISH), is associated with a higher response rate and prolonged time to progression (TTP), with a trend toward longer survival (Cappuzzo et al. 2005a, b, c).
HER3 is commonly overexpressed together with HER2 in a variety of cancers (Naidu et al. 1998; Krahn et al. 2001), and has been found to modulate drug resistance in HER2-overexpressing tumors (Chen et al. 2000). In addition, Anido et al. (2003) have demonstrated that gefitinib inhibits the growth of HER2-overexpressing cancer cells, possibly by sequestration of HER2 and HER3 receptors in an inactive heterodimer configuration with the EGFR. Nevertheless, Engelman et al. (2007) recently highlighted an additional mechanism of acquired or pre-existing resistance to gefitinib treatment in NSCLC. This involves proto-oncogene c-MET amplification loading to a HER3-dependent PI3K/Akt persistent activation. In this model, beyond the number of c-MET copies, the levels of phosphorylated HER3 and Akt following gefitinib treatment would be negatively related to the clinical outcome. Therefore it appears that no convincing data are available on HER3 protein expression as a possible predictor for TKI activity in the clinical setting.
Based on the above data, we performed a retrospective study aimed at identifying the role of different EGFR gene mutations and HER2 and HER3 expression as predictive factors for gefitinib sensitivity in a cohort of Chinese pretreated NSCLC patients.
Patients and methods
Patients and treatment
Advanced NSCLC patients from two institutions (Beijing 307 Hospital Cancer Center and The 2nd Affiliated Hospital Cancer Center, Da Lian Medical University) received gefitinib monotherapy at a daily dose of 250 mg until disease progression or unacceptable toxicity. All patients were pretreated with at least one chemotherapy regimen. The drug was provided by AstraZeneca within the Expanded Access Program, on a compassionate use basis. All patients had pathologically confirmed, measurable, locally advanced or metastatic NSCLC with normal baseline blood counts, and renal and hepatic functions. Patients were classified as smokers or never-smokers (less than 100 lifetime cigarettes).
Patients were evaluated for response according to the RECIST criteria (Therasse et al. 2000). Tumor response was assessed at week 4, with a confirmatory evaluation repeated in non-progressing patients 4 weeks later, and re-evaluated every subsequent 4 weeks. The study was approved by the ethics committee, and written informed consent was obtained from each patient.
DNA sequencing
Primary tumor samples were obtained from each patient before systemic treatment, and consisted of paraffin-embedded and frozen tumor tissue. Tumor specimens were prepared from paraffin-embedded sections using xylene deparaffinization and ethanol precipitation. Hematoxylin–eosin stained tissue slides of each tumor specimen were reviewed by pathologists and only specimens with >80% tumor component were used for DNA extraction. Genomic DNA was extracted from five paraffin sections of 5 μm thickness tumor blocks or 30 mg frozen tumor tissues using E.Z.N.A. SQ Tissue DNA kit (OMEGA, USA), according to the manufacturer’s protocols. EGFR tyrosine kinase exons 18–24 were amplified by nested PCR (Table 1). Each PCR reaction contained 5 ng of DNA, 10× KOD plus Buffer, 1 mM dNTPs, 0.4 mM MgSO4, 0.5 U KOD plus Enzyme (TOYOBO, JAP), and 0.2 μM forward and reverse primers in a 25 μL reaction volume. PCR cycling parameters were: one cycle of 94°C for 2 min and 30 s, 30 cycles of 94°C for 30 s, 55°C for 30 s and 68°C for 30 s, followed by one cycle of 68°C for 7 min. PCR products were sequenced using the ABI PRISM BigDye Terminator Cycle Sequencing Ready Reaction kit and the ABI PRISM3100 Genetic Analyzer (PE Applied Biosystems, Foster City, CA) and analyzed in both sense and antisense directions. Sequences of PCR amplicons were compared with the cDNA sequence of EGFR obtained from Genbank (accession no. NM 005228.3) by BLAST2 sequence. At least three independent experiments were performed for all analyses.
Table 1.
Primers for EGFR tyrosine kinase exons
| Exon | F external | R external | F nested | R nested |
|---|---|---|---|---|
| 18 | TCCAAATGAGCTGGCAAGTG | TCCCAAACACTCAGTGAAACAAA | AACAGCTATGACCATGGCTTGTGGAGCCTCTTACAC | GTTTTCCCAGTCACGACCTTATACACCGTGCCGAACG |
| 19 | GTGCATCGCTGGTAACATCC | TGTGGAGATGAGCAGGGTCT | AACAGCTATGACCATGGGACTCTGGATCCCAGAAGGTG | GTTTTCCCAGTCACGACATCGAGGATTTCCTTGTTGGC |
| 20 | ATCGCATTCATGCGTCTTCA | ATCCCCATGGCAAACTCTTG | AACAGCTATGACCATGGAAGCCTACGTGATGGCCAGCG | GTTTTCCCAGTCACGACCTTTGCGATCTGCACACACCAG |
| 21 | GCTCAGAGCCTGGCATGAA | CATCCTCCCCTGCATGTGT | AACAGCTATGACCATGGGCATGAACTACTTGGAGGACC | GTTTTCCCAGTCACGACTTTGCCTCCTTCTGCATGGTATTC |
| 22 | TGGCTCGTCTGTGTGTGTCA | CGAAAGAAAATACTTGCATGTCAGA | AACAGCTATGACCATGGGTGCCT ATCAAGTGGA TGGC | GTTTTCCCAGTCACGACCGTAGCTCCAGACATCACTC |
| 23 | TGAAGCAAATTGCCCAAGAC | TGACATTTCTCCAGGGATGC | AACAGCTATGACCATGGGGTGACTGTTTGGGAGTTGATG | GTTTTCCCAGTCACGACACTTGACCATGATCATGTAGAC |
| 24 | AAGTGTCGCATCACCAATGC | ATGCGATCTGGGACACAGG | AACAGCTATGACCATGGGCTGGA TGATAGACGC AG | GTTTTCCCAGTCACGACCTGAATGACAAGGTAGCGCTG |
F Forward, R reverse
Immunohistochemical analysis
HER2 and HER3 expression was evaluated on tissue specimens collected before gefitinib treatment. The level of HER2 expression was determined by IHC using the Dako Herceptest (DAKO, Copenhagen, Denmark), and HER3 expression was evaluated by IHC using a c-erbB3 monoclonal antibody (Clone SGP1, Neomarkers). Staining was performed according to the protocol described in the manufacturer’s guide. HER2 and HER3 were scored by widely accepted criteria that assess the intensity and completeness of membrane staining (DAKO HercepTest package insert 1998). Staining was assessed on the area of maximum staining intensity as follows: 0 = no staining; +1 = weak, incomplete membranous staining; +2 = moderate, complete membranous staining of at least 10% of invasive tumor cells; and +3 = strong membranous staining of at least 10% of invasive tumor cells. Cases interpreted as 0 or +1 were considered negative, and cases interpreted as +2 or +3 were considered positive.
Statistical analyses
Univariate analysis of patient characteristics and tumor response was performed using the χ2 test and the Fisher’s exact test where appropriate. Multivariate analysis was performed using a logistic regression model. The median durations of overall survival (OS) and TTP were calculated using the Kaplan–Meier method (Kaplan and Meier 1985). Comparisons between different groups were made using the log-rank test. Multivariate analysis was carried out using the stepwise Cox regression model. Two-sided P values of less than 0.05 were considered to be significant. All analyses were performed using SPSS for Windows, version 12.0 (SPSS Inc, Chicago, IL).
Results
Patient characteristics
Between May 2002 and March 2005, tumor specimens suitable for genetic analysis were available from 106 patients (25 frozen and 81 formalin-fixed paraffin-embedded tumor samples). Patient clinical characteristics are listed in Table 2. The cohort was well balanced according to gender (51.9% male vs. 48.1% female), with a median age of 63 years (range 31–78). The majority of patients had adenocarcinoma (73.6%), while the remainder had squamous cell carcinoma (22.6%) or other histologies (3.8%). Importantly, most of the patients were never-smokers (67%) and were pretreated with at least two chemotherapy regimens prior to gefitinib treatment (88.7%). Gefitinib was administered orally, with a median treatment duration of 6.4 months (range 1–26 months). The objective response rate (ORR) was 31.1% (33/106, 95% CI = 23–39%). With a median follow-up of approximately 8.6 months, median TTP for the entire population was 5.0 months (95% CI = 4.1–5.9 months), and median OS was 11.4 months (95% CI = 6.2–16.5 months). Using univariate analyses, objective response (P < 0.0001) and adenocarcinoma histology (P = 0.003) significantly correlated with longer TTP, while objective response (P = 0.001) and never-smoker status (P = 0.009) predicted improved OS.
Table 2.
Patient characteristics
| Characteristic | N = 106 |
|---|---|
| No (%) | |
| Age (years) | |
| Median | 62 |
| Range | 31–78 |
| Gender | |
| Male | 55 (51.9) |
| Female | 51 (48.1) |
| Stage | |
| IIIB | 23 (21.7) |
| IV | 83 (78.3) |
| ECOG performance status | |
| 0–1 | 62 (58.5) |
| 2 | 36 (34) |
| 3 | 8 (7.5) |
| Histology | |
| Adenocarcinoma | 78 (73.6) |
| Squamous cell carcinoma | 24 (22.6) |
| Others | 4 (3.8) |
| Prior chemotherapy | |
| 1 regimen | 12 (11.3) |
| ≥2 regimens | 94 (88.7) |
| Smoking history | |
| Never smokersa | 71 (67) |
| Smokers | 35 (33) |
ECOG Eastern Cooperative Oncology Group
aLifetime smoking history of less than 100 cigarettes
HER2/HER3 expression and clinical characteristics
Among the enrolled 106 patients, 84 had sufficient tumor tissue for IHC analysis. A total of 38 patients (45.2%) had HER2 overexpression and 17 patients (20.2%) were HER3-positive. A total of 41 patients (48.8%) had tumors that were negative for both HER2 and HER3, while co-overexpression of both markers was detected in 12 patients (14.2%).
When evaluating the association between HER2 and HER3 expression status and clinical characteristics, we observed that HER3 overexpression was associated with performance status 0–1 (28.6 vs. 8.6%, P = 0.024), while no significant association was observed with age, gender, smoking history, histology, number of prior chemotherapy regimens, or tumor stage. HER2 expression status was not associated with any clinical feature (Table 3).
Table 3.
Patient characteristics and EGFR/HER2/HER3 status
| Variable | EGFR | HER2 | HER3 | |||
|---|---|---|---|---|---|---|
| Mutation, N/% | Wild-type, N/% | Positive, N/% | Negative, N/% | Positive, N/% | Negative, N/% | |
| All cases | 32/30.2 | 74/69.8 | 38/45.2 | 46/54.8 | 17/20.2 | 67/79.8 |
| Sex | ||||||
| Male | 13/23.6 | 42/76.4 | 17/38.6 | 27/61.4 | 8/18.2 | 36/81.8 |
| Female | 19/37.3 | 32/62.7 | 21/52.5 | 19/47.5 | 9/22.5 | 31/77.5 |
| P | 0.127‡ | 0.202‡ | 0.707‡ | |||
| Age | ||||||
| <65 | 18/30 | 42/70 | 20/44.4 | 25/55.6 | 12/26.7 | 33/73.3 |
| ≥65 | 14/30.4 | 32/69.6 | 18/46.2 | 21/53.8 | 5/12.8 | 34/87.2 |
| P | 0.961‡ | 0.875‡ | 0.115‡ | |||
| ECOG | ||||||
| 0–1 | 19/30.6 | 43/69.4 | 25/51.0 | 24/49.0 | 14/28.6 | 35/71.4 |
| 2–3 | 13/29.5 | 31/70.5 | 13/37.1 | 22/62.9 | 3/8.6 | 32/91.4 |
| P | 0.903‡ | 0.208‡ | 0.024‡ | |||
| Histology | ||||||
| Ade | 28/35.9 | 50/64.1 | 28/45.9 | 33/54.1 | 12/19.7 | 49/80.3 |
| Non-ade | 4/14.3 | 24/85.7 | 10/43.5 | 13/56.5 | 5/21.7 | 18/78.3 |
| P | 0.033‡ | 0.842‡ | 1.000† | |||
| Smoking history | ||||||
| Never smokers | 25/35.2 | 46/64.8 | 26/45.6 | 31/54.4 | 7/25.9 | 20/74.1 |
| Smokers | 7/20 | 28/80 | 12/44.4 | 15/55.6 | 10/17.5 | 47/82.5 |
| P | 0.109‡ | 0.920‡ | 0.372‡ | |||
| Prior chemotherapy | ||||||
| 1 regimen | 5/41.7 | 7/58.3 | 5/41.7 | 7/58.3 | 4/33.3 | 8/67.7 |
| ≥2 regimens | 27/28.7 | 67/71.3 | 33/45.8 | 39/54.2 | 13/18.1 | 59/81.9 |
| P | 0.358‡ | 0.788‡ | 0.251† | |||
| Stage | ||||||
| IIIB | 5/21.7 | 18/78.3 | 7/35.0 | 13/65.0 | 3/15.0 | 17/85.0 |
| IV | 27/32.5 | 56/67.5 | 31/48.4 | 33/51.6 | 14/21.9 | 50/78.1 |
| P | 0.319‡ | 0.292‡ | 0.751† | |||
ECOG Eastern Cooperative Oncology Group, Ade adenocarcinoma
†P values (two-sides) calculated using Fisher’s exact test
‡P values (two-sides) calculated using Pearson’s chi-square test
HER2/HER3 expression and clinical outcome
The ORR, including complete responses and partial responses (PR), was 36.8% (95% CI = 31.5–42.1%) in patients with HER2 overexpression and 17.4% (95% CI = 9.3–25.5%) in those negative for HER2. This difference was statistically significant (P = 0.044). On the contrary, no significant differences in terms of ORR was observed for HER3-positive patients (41.2%, 95% CI = 35.8–46.6%) when compared with HER3-negative (22.4%, 95% CI = 17.9–26.9%), When performing Kaplan–Meier survival analyses, TTP and OS did not differ according to HER2 and HER3 expression status.
Combining both tests, we observed a marginally significant advantage in terms of ORR for HER2-positive/HER3-positive patients when compared with those negative for both markers (50.0 vs. 17.1%, P = 0.05). However, such advantage did not reach statistical significance when comparing HER2-positive/HER3-positive tumors with those negative for only one marker (P = 0.071). No difference in terms of TTP and OS was observed between subgroups according to combined HER2 and HER3 expression status (Table 4).
Table 4.
Association between tumor response and prognosis according to EGFR/HER2/HER3 status
| Markers | N/% | OR/% | Median TTP (months) | Median OS (months) | 1-year survival ± SD,% |
|---|---|---|---|---|---|
| HER2+/HER3+ | 12/14.2 | 6/50.0 | 4.0 | 13.0 | 53 ± 2 |
| HER2−/HER3+ | 5/6.0 | 1/20.0 | 7.0 | 9.3 | 60 ± 2 |
| HER2+/HER3− | 26/31.0 | 8/30.8 | 5.0 | 13.5 | 54 ± 1 |
| HER2−/HER3− | 41/48.8 | 7/17.1 | 3.0 | 7.0 | 39 ± 1 |
| Any negative | 72/85.7 | 16/22.2 | 4.0 | 8.0 | 42 ± 1 |
| P (Any −vs +/+) | 0.071† | 0.960‡ | 0.636‡ | 0.119‡ | |
| EGFR mutation+/HER2+ | 13/15.5 | 11/84.6 | 18.1 | 26.0 | 75 ± 2 |
| EGFR mutation+/HER2− | 8/9.5 | 3/37.3 | 15.1 | 21.2 | 58 ± 2 |
| EGFR mutation−/HER2+ | 25/29.8 | 3/12.0 | 3.0 | 6.4 | 23 ± 1 |
| EGFR mutation−/HER2− | 38/45.2 | 5/13.2 | 3.4 | 6.0 | 29 ± 1 |
| Any negative | 71/84.5 | 11/15.5 | 3.0 | 7.0 | 30 ± 1 |
| P (Any −vs +/+) | <0.0001† | <0.000‡ | <0.000‡ | <0.0001‡ | |
| EGFR mutation+/HER3+ | 7/8.3 | 5/71.4 | 8.5 | 18.3 | 85 ± 2 |
| EGFR mutation+/HER3− | 14/16.7 | 9/64.3 | 18.1 | 26.0 | 79 ± 1 |
| EGFR mutation−/HER3+ | 10/11.9 | 2/20 | 3.0 | 5.4 | 18 ± 2 |
| EGFR mutation−/HER3− | 53/63.1 | 6/11.3 | 3.0 | 6.4 | 29 ± 1 |
| Any negative | 77/91.7 | 17/22.1 | 3.4 | 15.2 | 42 ± 1 |
| P (Any −vs +/+) | 0.012† | 0.027‡ | 0.013‡ | <0.0001‡ | |
| EGFR mutation+/HER2+/HER3+ | 4/4.8 | 4/100 | 8.0 | 13.0 | 75 ± 2 |
| EGFR mutation+/HER2−/HER3− | 5/6.0 | 2/40.0 | 6.4 | 15.2 | 80 ± 2 |
| EGFR mutation−/HER2+/HER3+ | 8/9.5 | 2/25.0 | 3.0 | 9.0 | 23 ± 2 |
| EGFR mutation−/HER2−/HER3− | 36/42.9 | 5/13.9 | 3.0 | 6.4 | 31 ± 1 |
| Any negative | 80/95.2 | 18/22.5 | 4.0 | 9.0 | 44 ± 1 |
| P (Any −vs +/+/+) | 0.004† | 0.325‡ | 0.722‡ | <0.0001‡ |
OR Objective response; OS overall survival; TTP time to progression
†P values (two-sides) calculated using Fisher’s exact test
‡P values (two-sides) calculated using the log-rank test
EGFR mutations and clinical characteristics
EGFR mutational analysis was successfully performed in 106 patients, with an overall mutation rate of 30.2% (n = 32). EGFR mutations mainly involved exons 19 (53.1%, n = 17), 21 (21.9%, n = 7), and 18 (18.8%, n = 6) (Table 5). Exon 23 and exon 20 substitutions were observed in one and three patients, respectively. Among EGFR-mutated patients, 30 carried a single mutation, while two patients had a double mutation.
Table 5.
Clinical and biological characteristics of patients with EGFR mutations
| No. | Sex | SM | H | HER2† | HER3† | Nucleotide change | Amino acid change | Exon | OR | TTP | OS |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | F | N | SQU | + | − | 2104G>T | A702S | 18 | PR | 8.5 | 14.0+ |
| 2 | F | N | ADE | + | + | 2104G>T | A702S | 18 | PR | 7.0+ | 7.0+ |
| 3 | M | Y | ADE | + | + | 2123A>T | K708 M | 18 | PR | 16.3+ | 16.3+ |
| 4 | F | N | SQU | + | + | 2162G>C | G721A | 18 | CR | 7.0 | 11.0+ |
| 5 | M | N | ADE | NA | NA | 2162G>C | G721A | 18 | PR | 6.0 | 9.0 |
| 6 | F | N | ADE | NA | NA | 2108T>C | L703P | 18 | SD | 15.0 | 15.7 |
| 7 | F | N | ADE | + | − | 2230A>G | I744 V | 19 | PR | 5.0 | 26.0+ |
| 8 | F | N | ADE | + | − | 2219T>C | V740A | 19 | PR | 12.0+ | 12.0+ |
| 9 | M | Y | ADE | + | − | del2236–2250 | del E746-A750 | 19 | PR | 13.0+ | 13.0+ |
| 10 | F | N | ADE | + | − | del2235–2249 | delK745-A750insK | 19 | PR | 17.4+ | 17.4+ |
| 11 | F | N | ADE | − | − | 2218G>C | V740L | 19 | PR | 3.0 | 28.0+ |
| 12 | F | N | ADE | + | + | 2219T>C | V740A | 19 | PR | 8.5 | 16.7+ |
| 13 | M | Y | ADE | + | + | del2235–2249 | delK745-A750insK | 19 | PR | 8.0 | 13.0+ |
| 14 | M | Y | ADE | NA | NA | del2235–2249 | delK745-A750insK | 19 | PR | 2.7+ | 2.7+ |
| 15 | M | N | ADE | NA | NA | del2236–2250 | del E746-A750 | 19 | PR | 8.1 | 13.9 |
| 16 | F | N | ADE | − | − | 2218G>C | V740L | 19 | CR | 4.6+ | 4.6+ |
| 17 | F | Y | ADE | NA | NA | del2236–2250 | del E746-A750 | 19 | PR | 6.0+ | 6.0+ |
| 18 | F | N | ADE | NA | NA | 2242A>T | R748 W | 19 | SD | 7.3+ | 7.3+ |
| 19 | M | N | SQU | − | − | del2235–2249 | delK745-A750insK | 19 | SD | 11.0+ | 11.0+ |
| 20 | F | N | ADE | − | − | del2237–2251 | delE746-T751insA | 19 | SD | 9.2+ | 9.2+ |
| 21 | F | N | ADE | + | − | del2235–2246 | delK745-E749insK | 19 | SD | 18.1 | 18.5 |
| 22 | M | N | ADE | + | − | del2239–2256 | delL747-S752 | 19 | SD | 26.0+ | 26.0+ |
| 23 | F | N | ADE | NA | NA | 2350T>C | S784P | 20 | PR | 13.0 | 14.0+ |
| 24 | M | N | ADE | − | − | 2495G>T | R832L | 21 | SD | 7.0+ | 7.0+ |
| 25 | F | N | ADE | + | − | 2573T>G | L858R | 21 | CR | 20.0 | 24.0+ |
| 26 | M | Y | AS | NA | NA | 2573T>G | L858R | 21 | PR | 5.3+ | 5.3+ |
| 27 | F | N | ADE | NA | NA | 2573T>G | L858R | 21 | PR | 6.0+ | 6.0+ |
| 28 | F | N | ADE | NA | NA | 2573T>G | L858R | 21 | PR | 8.2 | 15.3 |
| 29 | M | Y | ADE | NA | NA | 2573T>G | L858R | 21 | SD | 10.0 | 16.0 |
| 30 | M | N | ADE | − | − | 2763C>A | S921R | 23 | SD | 4.6+ | 4.6 |
| 31 | F | N | ADE | − | + | 2404G>T | V802F | 20 | PR | 16.0+ | 16.0+ |
| del2236–2250 | delE746-A750 | 19 | |||||||||
| 32 | M | N | ADE | − | − | 2404G>T | V802F | 20 | PR | 15.1 | 15.2+ |
| 2573T>G | L858R | 21 |
M Male; F female; SM smoking history; H histology; OR objective response; SQU squamous cell carcinoma; ADE adenocarcinoma; AS squamous cell carcinoma and adenocarcinoma; NA not available; CR complete response; PR partial response; SD stable disease; PD progressive disease; OS overall survival; TTP time to progression
The presence of EGFR mutations was significantly associated with adenocarcinoma histology, while no association was observed with smoking status, age, gender, performance status, number of prior chemotherapy regimens, or tumor stage (Table 3).
EGFR mutations and clinical outcome
EGFR-mutated patients had a significantly higher ORR when compared with those carrying wild-type receptor (71.9 vs. 13.5%, P < 0.0001). In accordance with this finding, mutations were present in 23 (69.7%) of the 33 responders and in 9 (12.3%) of the 73 non-responders (P < 0.0001). Interestingly, none of the patients with EGFR mutations had progressive disease, indicating a significant reduction in the risk of disease progression in this subgroup of patients (χ 2 = 5.852, P = 0.016).
Median TTP was significantly longer in patients with EGFR mutations compared with subjects with wild-type tumors (15.0 vs. 3.0 months, P < 0.0001, Fig. 1a). The reduction in the risk of disease progression apparently remained unchanged during the overall treatment duration. When considering the subgroup of non-responders to gefitinib, median TTP in patients with mutated EGFR was significantly longer than in those with no mutations (8.0 vs. 3.0 months, P = 0.0065, Fig. 2).
Fig. 1.
Kaplan–Meier curves for time to disease progression (a) and survival (b). Median time to progression was 15.0 months (95% CI = 6.0–23.9 months) for EGFR mutant patients and 3.0 months (95% CI = 2.6–3.3 months) for EGFR wild-type patients. Median survival was 18.5 months (95% CI = 8.3–28.6 months) for EGFR mutant patients and 6.0 months (95% CI = 5.0–6.9 months) for EGFR wild-type patients. Statistical significance of differences between groups was evaluated with the log-rank test
Fig. 2.
Kaplan–Meier curves for time to progression for the subgroup of non-responders to gefitinib. Median TTP in patients with mutated EGFR was significantly longer than in those with no mutations (8.0 vs. 3.0 months, P = 0.0065). Statistical significance of differences between groups was evaluated with the log-rank test
Patients with mutated EGFR experienced improved OS in comparison with subjects without mutations (18.5 vs. 6.0 months, P < 0.0001). As seen with TTP, the survival benefit associated with EGFR mutations was maintained throughout the overall treatment duration (Fig. 1b). Consistent with TTP, OS of non-responders to gefitinib harboring EGFR mutations was significantly longer than for those with wild-type receptor (11.0 vs. 5.3 months, P = 0.0392).
We attempted to determine whether different types of EGFR mutations play a different role in predicting sensitivity to gefitinib. When directly comparing exon 19 deletions and L858R substitution, neither mutation resulted in a better predictor for gefitinib sensitivity over the other, although a trend for improved TTP favoring exon 19 mutations was observed (Table 6). Moreover, we found a significantly longer TTP for patients with exon 19 deletions than seen in those harboring other classes of mutations (18.1 vs. 10.0 months, P = 0.032), although this difference did not translate in prolonged survival (P = 0.415). Conversely, when comparing L858R substitution in exon 21 with other types of mutations we found no difference in patient outcome in terms of ORR, TTP and OS.
Table 6.
Patient outcome according to EGFR mutational classes
| Exon 19 Del (n = 11) | Other mutations (n = 21) | P | |
|---|---|---|---|
| RR (%) | 63.6 | 76.2 | 0.681 |
| TTP (months, 95% CI) | 18.1 (3.8–32.3) | 10.0 (7.9–12.0) | 0.032 |
| OS (months, 95% CI) | 18.5 (11.8–25.1) | 16.0 (7.0–24.9) | 0.415 |
| L858R (n = 6) | Other mutations (n = 26) | P | |
|---|---|---|---|
| RR (%) | 83.3 | 69.2 | 0.648 |
| TTP (months, 95% CI) | 10.0 (3.2–16.7) | 15.0 (4.9–25.0) | 0.913 |
| OS (months, 95% CI) | 15.3 (14.5–16.0) | 26.0 (10.5–41.4) | 0.286 |
| Exon 19 Del (n = 11) | L858R (n = 6) | P | |
|---|---|---|---|
| RR (%) | 63.6 | 83.3 | 0.600 |
| TTP (months, 95% CI) | 18.1 (3.8–32.3) | 10.0 (3.2–16.7) | 0.235 |
| OS (months, 95% CI) | 18.5 (11.8–25.1) | 15.3 (14.5–16.0) | 0.378 |
RR Response rate; TTP time to progression; OS overall survival
EGFR mutations and HER2/HER3 expressions
Combining mutational and IHC data, we observed that EGFR-mutated/HER2-positive patients had a significantly higher ORR, higher 1-year survival rate (P < 0.0001), longer TTP (P < 0.0001), and longer OS (P < 0.0001) than did patients who had no EGFR mutations and/or were HER2 negative. Similar findings were observed when HER3 data were combined with EGFR mutational status. However, HER2 and HER3 expression did not influence patient outcome in terms of ORR, TTP and OS in EGFR-mutated patients. Similarly, when both HER2 and HER3 data were combined with EGFR mutation results, patients with EGFR mutations and HER2-positive/HER3-positive did not differ in terms of ORR (P = 0.167), TTP (P = 0.795), 1-year survival rate (P = 0.397), and OS (P = 0.264) from patients with EGFR mutations and HER2-negative/HER3-negative (Table 4).
Multivariate analysis of clinical outcome
In order to determine which variables were predictive for response, TTP and OS, those factors that were statistically significant in the univariate analysis were included in a multivariate model. A step-wise logistic regression analysis was performed to identify significant factors that might predict response to gefitinib, with presence of EGFR mutations emerging as the strongest predictor for response (RR 13.8, 95% CI = 4.3–44.4). When the Cox regression model was used to determine significant factors that might influence TTP and OS, presence of EGFR mutations (RR 4.7, P < 0.0001) and adenocarcinoma histology (RR 2.1, P = 0.005) were significantly associated with longer TTP, while mutations (RR 5.2, P < 0.0001) and never-smoker status (RR 2.0, P = 0.0161) predicted longer survival.
Discussion
EGFR TKIs have shown remarkable activity in subsets of NSCLC patients, with a clear benefit being observed in women, adenocarcinomas, Asian ethnicities and, most of all, never-smokers (Thatcher et al. 2005; Shepherd et al. 2005; Lynch et al. 2004; Paez et al. 2004). The molecular mechanisms underlying sensitivity to these agents have been extensively investigated. In particular, the presence of EGFR activating mutations has been associated with response to either gefitinib or erlotinib (Lynch et al. 2004; Paez et al. 2004; Tsao et al. 2005). Not surprisingly, the incidence of these mutations was significantly higher in clinical subgroups who were more likely to respond to TKIs (Lynch et al. 2004; Paez et al. 2004; Tsao et al. 2005).
In this study, EGFR mutations were observed in about one-third of our cohort of unselected NSCLC patients, this is within the range previously reported in Asian populations treated with TKIs, and exon 19 deletions were the most common subtype (Lynch et al. 2004; Paez et al. 2004; Hirsch et al. 2006). We found a significant association between EGFR mutations and adenocarcinoma histology, while never-smoking status did not predict the presence of EGFR genetic alterations, an observation supported by other investigators (Huang et al. 2004). These data might indicate that selected Asian populations present a high incidence of EGFR activating mutations regardless of smoking status.
As previously reported by several other authors (Lynch et al. 2004; Paez et al. 2004; Tsao et al. 2005), we observed a significant association between EGFR mutations and higher ORR, longer TTP and OS. However, although available data suggest that patients with EGFR mutations are sensitive to TKIs, some observations indicate that such genetic alterations may have a prognostic rather than a predictive value. Retrospective analyses of the largest trials with TKIs showed no survival benefit for patients harboring EGFR mutations receiving a TKI (Shepherd et al. 2005; Eberhard et al. 2005). In addition, retrospective analyses of the INTACT trials, which compared chemotherapy plus gefitinib versus chemotherapy alone in advanced NSCLC patients, showed a significant survival advantage for patients with EGFR mutations treated with chemotherapy alone compared to individuals with EGFR wild-type, suggesting a possible better natural history for tumors harboring EGFR mutations. Indeed, Shepherd and Tsao remarked a growing evidence that EGFR mutations are favorable prognostic markers of survival and that they are predictive markers of response, in terms of tumor shrinkage. Therefore, the subgroup of patients with mutations, clearly appears biologically distinct (Shepherd and Tsao 2006). Indeed Haneda et al. showed that patients affected by adenocarcinoma with bronchioloalveolar carcinoma components with EGFR gene mutation have a significantly better survival than those with adenocarcinoma with wild type (Haneda et al. 2006).
In our study TTP was longer in patients with EGFR/HER1 mutant as compared to wild type gene also in non-responders to gefitinib. These results appears to cast doubts whether EGFR/HER mutations have a prognostic value rather than predictive on the response to gefitinib.
Both patient’s clinical characteristics and molecular tumor markers may be used to predict the likelihood of response to EGFR TKIs therapy. In fact, in almost all studies, mutations were seen more frequently in females, lifetime non-smokers, and patients with adenocarcinoma (Shepherd 2008). Nevertheless, at this time, molecular selection of patients for therapy with EGFR TKIs is not quite ready. The results of prospectively designed randomized trials are awaited.
Moreover, retrospective studies suggested that different mutations might play different roles in patients exposed to TKIs in terms of response and survival. Particularly, patients with deletions have been reported to have a better response to TKIs when compared with other mutations (Jackman et al. 2006; Riely et al. 2006). In addition, longer TTP and OS have been observed for patients with exon 19 deletions over those with exon 21 substitution (Jackman et al. 2006; Riely et al. 2006). In our study, no difference in terms of response and survival was observed across the different mutational classes, although patients with exon 19 deletions had significantly longer TTP than those with other types of mutations, with a trend for prolonged TTP favoring exon 19 deletions over L858R substitution. Prospective trials should be performed to further define the prognostic and predictive roles of different EGFR mutations.
Existing data indicate that a significant fraction of patients with EGFR mutations (12–84%) does not respond to TKIs (Hirsch et al. 2006; Cappuzzo et al. 2005a). Moreover, dramatic responses can be achieved in patients with wild-type receptor (Shepherd et al. 2005). In our study, ten patients with wild-type EGFR achieved PR. These observations suggest that mechanisms other than EGFR mutations can be involved in sensitivity to TKIs. Several studies reported an improved outcome for patients with EGFR gene gain, regardless of the methods adopted for its assessment (Tsao et al. 2005; Hirsch et al. 2006; Cappuzzo et al. 2005a; Cappuzzo 2008). Furthermore, preclinical data indicate that other members of the EGFR family play a critical role in driving sensitivity to TKIs (Naidu et al. 1998; Krahn et al. 2001; Hirata et al. 2005).
In our study we observed an higher evidence of EGFR/HER1 mutation in non-smokers (20 vs. 35.2%) and female patients (37.7 vs. 23.6%) even these difference did not reach statistical significance, probably as a consequence of the limited number of patients differently from the findings of a recent paper with a more consistent number of patients (Wu et al. 2007).
Overexpression of HER2 has been associated with increased gefitinib activity in preclinical models (Moasser et al. 2001). Moreover, Hirata et al. (2005) have recently demonstrated that effects of gefitinib are influenced by HER2 levels rather than EGFR expression in one NSCLC cell line transfected with HER2 gene. Increased HER2 gene copy number assessed by FISH has been associated with significantly better ORR and prolonged TTP, and with a trend toward longer survival, in a cohort of NSCLC patients exposed to gefitinib (Cappuzzo et al. 2005a). To the best of our knowledge, only one small Italian study investigated HER2 protein expression assessed by IHC in NSCLC patients treated with gefitinib, observing no influence of HER2 levels on clinical outcome (Cappuzzo et al. 2003). In our study, HER2-positive patients had significantly better ORR than those negative for HER2 expression, regardless of EGFR mutational status, suggesting a possible key role of HER2 in driving TKI sensitivity.
HER3, which is commonly overexpressed together with HER2 in a variety of malignancies, has been implicated with TKI sensitivity due to its ability to couple EGFR to the PI3K-Akt pathway (Naidu et al. 1998; Krahn et al. 2001; Engelman et al. 2005). However, increased HER3 gene copy number assessed by FISH did not predict a better response or a longer survival in NSCLC patients who received gefitinib (Cappuzzo et al. 2005a). Fujimoto et al. (2005) evaluated HER3 protein expression by IHC in 42 NSCLC patients treated with gefitinib. The authors reported higher levels of HER3 in patients who responded or achieved disease stabilization to gefitinib as compared with those who had disease progression. Similarly, in the present study we observed a higher ORR for HER3-positive patients when compared with HER3-negative, although the difference was not statistically significant. Finally, when combining EGFR mutational status with HER2 and/or HER3 expression, we observed that EGFR mutated patients had a better outcome compared with patients with wild-type EGFR regardless of HER2 and/or HER3 protein levels. Taken together, these data indicate that presence of EGFR mutations represents the most powerful biological predictor for sensitivity to TKIs.
A significant fraction of patients who achieve initial tumor response to TKIs will ultimately develop progressive disease. Molecular mechanisms involved in resistance to TKIs are currently under investigation. The threonine-to-methionine substitution at amino acid position 790 (T790M) in exon 20 of the EGFR gene has been described in progressing lesions under gefitinib or erlotinib treatment (Kobayashi et al. 2005). The T790M substitution seems to modify the structure of the EGFR tyrosine kinase domain, thus conferring resistance in EGFR mutant cell lines usually sensitive to TKIs (Kobayashi et al. 2005; Greulich et al. 2005). We examined three patients whose primary tumors had an EGFR mutation and had developed resistance to gefitinib after exhibiting an initial response to the drug, we did not find any secondary mutation (data not shown). This finding suggests that mechanisms of acquired resistance to gefitinib in patients with EGFR-mutant NSCLC requires additional investigation.
Overall, our data confirm that the presence of EGFR mutations is a useful marker for selecting advanced NSCLC patients who are likely to benefit from gefitinib regardless of their subtype. These findings are emphasized by recent results of perspective trials (Asahina et al. 2006; Inoue et al. 2006; Paz-Ares et al. 2006; Sutani et al. 2006; Yoshida et al. 2007; Cappuzzo et al. 2007; Sunaga et al. 2007; Sequist et al. 2008). Evaluation of either HER2 or HER3 expression does not add significantly predictive power to EGFR mutation analysis.
Conflict of interest
None.
References
- Anido J, Matar P, Albanell J, Guzman M, Rojo F, Arribas J, Averbuch S, Baselga J (2003) ZD1839, a specific epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, induces the formation of inactive EGFR/HER2 and EGFR/HER3 heterodimers and prevents heregulin signaling in HER2-overexpressing breast cancer cells. Clin Cancer Res 9:1274–1283 [PubMed] [Google Scholar]
- Arteaga C (2002) Overview of epidermal growth factor receptor biology and its role as a therapeutic target in human neoplasia. Semin Oncol 29:3–9 [DOI] [PubMed] [Google Scholar]
- Asahina H, Yamazaki K, Kinoshita I, Sukoh N, Harada M, Yokouchi H, Ishida T, Ogura S, Kojima T, Okamoto Y, Fujita Y, Dosaka-Akita H, Isobe H, Nishimura M (2006) A phase II trial of gefitinib as first-line therapy for advanced non-small cell lung cancer with epidermal growth factor receptor mutations. Br J Cancer 95(8):998–1004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cappuzzo F (2008) EGFR FISH versus mutation: different tests. Different end-points. Lung Cancer 60:160–165. doi:10.1016/j.lungcan.2008.02.008 [DOI] [PubMed] [Google Scholar]
- Cappuzzo F, Gregorc V, Rossi E, Cancellieri A, Magrini E, Paties CT, Ceresoli G, Lombardo L, Bartolini S, Calandrio C, de Rosa M, Villa E, Crino L (2003) Gefitinib in pretreated non-small-cell lung cancer (NSCLC): analysis of efficacy and correlation with HER2 and epidermal growth factor receptor expression in locally advanced or metastatic NSCLC. J Clin Oncol 21:2658–2663. doi:10.1200/JCO.2003.01.039 [DOI] [PubMed] [Google Scholar]
- Cappuzzo F, Varella-Garcia M, Shigematsu H, Domenichini I, Bartolini S, Ceresoli GL, Rossi E, Ludovini V, Gregorc V, Toschi L, Franklin WA, Crino L, Gazdar AF, Bunn PA Jr, Hirsch FR (2005a) Increased HER2 gene copy number is associated with response to gefitinib therapy in epidermal growth factor receptor-positive non-small-cell lung cancer patients. J Clin Oncol 23:5007–5018. doi:10.1200/JCO.2005.09.111 [DOI] [PubMed] [Google Scholar]
- Cappuzzo F, Hirsch FR, Rossi E, Bartolini S, Ceresoli GL, Bemis L et al (2005b) Epidermal growth factor receptor gene and protein and gefitinib sensitivity in non-small cell lung cancer. J Natl Cancer Inst 97:643–655 [DOI] [PubMed] [Google Scholar]
- Cappuzzo F, Toschi L, Domenichini I, Bartolini S, Ceresoli GL, Rossi E et al (2005c) HER3 genomic gain and sensitivity to gefitinib in advanced non-small-cell lung cancer patients. Br J Cancer 93:1334–1340. doi:10.1038/sj.bjc.6602865 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cappuzzo F, Ligorio C, Jänne PA, Toschi L, Rossi E, Trisolini R et al (2007) Prospective study of gefitinib in epidermal growth factor receptor fluorescence in situ hybridization-positive/phospho-Akt-positive or never smoker patients with advanced non-small-cell lung cancer: the ONCOBELL trial. J Clin Oncol 25(16):2248–2255. doi:10.1200/JCO.2006.09.4300 [DOI] [PubMed] [Google Scholar]
- Chen X, Yeung TK, Wang Z (2000) Enhanced drug resistance in cells coexpressing ErbB2 with EGF receptor or ErbB3. Biochem Biophys Res Commun 277:757–763. doi:10.1006/bbrc.2000.3731 [DOI] [PubMed] [Google Scholar]
- DAKO HercepTest package insert (1998) Carpinteria. DAKO Corp, California
- Eberhard DA, Johnson BE, Amler LC, Goddard AD, Heldens SL, Herbst RS et al (2005) Mutations in the epidermal growth factor receptor and in KRAS are predictive and prognostic indicators in patients with non-small-cell lung cancer treated with chemotherapy alone and in combination with erlotinib. J Clin Oncol 23:5900–5909. doi:10.1200/JCO.2005.02.857 [DOI] [PubMed] [Google Scholar]
- Engelman JA, Janne PA, Mermel C, Pearlberg J, Mukohara T, Fleet C et al (2005) ErbB-3 mediates phosphoinositide 3-kinase activity in gefitinib-sensitive non-small cell lung cancer cell lines. Proc Natl Acad Sci USA 102:3788–3793. doi:10.1073/pnas.0409773102 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Engelman JA, Zejnullahu K, Mitsudomi T, Song Y, Hyland C, Park JO, Lindeman N, Gale CM, Zhao X, Christensen J, Kosaka T, Holmes AJ, Rogers AM, Cappuzzo F, Mok T, Lee C, Johnson BE, Cantley LC, Jänne PA (2007) MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science 316(5827):1039–1043 [DOI] [PubMed] [Google Scholar]
- Fujimoto N, Wislez M, Zhang J, Iwanaga K, Dackor J, Hanna AE et al (2005) High expression of ErbB family members and their ligands in lung adenocarcinomas that are sensitive to inhibition of epidermal growth factor receptor. Cancer Res 65:11478–11485. doi:10.1158/0008-5472.CAN-05-1977 [DOI] [PubMed] [Google Scholar]
- Greulich H, Chen TH, Feng W, Janne PA, Alvarez JV, Zappaterra M et al (2005) Oncogenic transformation by inhibitor-sensitive and -resistant EGFR mutants. PLoS Med 2:e313. doi:10.1371/journal.pmed.0020313 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Haneda H, Sasaki H, Lindeman N, Kawano O, Endo K, Suzuki E, Shimizu S, Yukiue H, Kobayashi Y, Yano M, Fujii Y (2006) A correlation between EGFR gene mutation status and bronchioloalveolar carcinoma features in Japanese patients with adenocarcinoma. Jpn J Clin Oncol 36(2):69–75 [DOI] [PubMed] [Google Scholar]
- Hirata A, Hosoi F, Miyagawa M, Ueda S, Naito S, Fujii T et al (2005) HER2 overexpression increases sensitivity to gefitinib, an epidermal growth factor receptor tyrosine kinase inhibitor, through inhibition of HER2/HER3 heterodimer formation in lung cancer cells. Cancer Res 65:4253–4260. doi:10.1158/0008-5472.CAN-04-2748 [DOI] [PubMed] [Google Scholar]
- Hirsch FR, Varella-Garcia M, Bunn PA Jr, Franklin WA, Dziadziuszko R, Thatcher N, Chang A, Parikh P, Pereira JR, Ciuleanu T, von Pawel J, Watkins C, Flannery A, Ellison G, Donald E, Knight L, Parums D, Botwood N, Holloway B (2006) Molecular predictors of outcome with gefitinib in a phase III placebo-controlled study in advanced non-small-cell lung cancer. J Clin Oncol 24:5034–5042. doi:10.1200/JCO.2006.06.3958 [DOI] [PubMed] [Google Scholar]
- Huang SF, Liu HP, Li LH, Ku YC, Fu YN, Tsai HY et al (2004) High frequency of epidermal growth factor receptor mutations with complex patterns in non-small-cell lung cancers related to gefitinib responsiveness in Taiwan. Clin Cancer Res 10:8195–8203. doi:10.1158/1078-0432.CCR-04-1245 [DOI] [PubMed] [Google Scholar]
- Inoue A, Suzuki T, Fukuhara T, Maemondo M, Kimura Y, Morikawa N et al (2006) Prospective phase II study of gefitinib for chemotherapy-naïve patients with advanced non-small-cell lung cancer with epidermal growth factor receptor gene mutations. J Clin Oncol 20:3340–3346. doi:10.1200/JCO.2005.05.4692 [DOI] [PubMed] [Google Scholar]
- Jackman DM, Yeap BY, Sequist LV, Lindeman N, Holmes AJ, Joshi VA et al (2006) Exon 19 deletion mutations of epidermal growth factor receptor are associated with prolonged survival in non-small cell lung cancer patients treated with gefitinib or erlotinib. Clin Cancer Res 12:3908–3914. doi:10.1158/1078-0432.CCR-06-0462 [DOI] [PubMed] [Google Scholar]
- Jemal A, Siegel R, Ward E, Murray T, Xu J, Smigal C et al (2006) Cancer statistics. CA Cancer J Clin 56:106–130 [DOI] [PubMed] [Google Scholar]
- Kaplan EL, Meier P (1985) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481. doi:10.2307/2281868 [Google Scholar]
- Kobayashi S, Boggon TJ, Dayaram T, Janne PA, Kocher O, Meyerson M et al (2005) EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N Engl J Med 352:786–792. doi:10.1056/NEJMoa044238 [DOI] [PubMed] [Google Scholar]
- Krahn G, Leiter U, Kaskel P, Udart M, Utikal J, Bezold G et al (2001) Coexpression patterns of EGFR, HER2, HER3 and HER4 in nonmelanoma skin. Eur J Cancer 37:251–259. doi:10.1016/S0959-8049(00)00364-6 [DOI] [PubMed] [Google Scholar]
- Lenferink AE, Pinkas-Kramarski R, van de Poll ML, van Vugt MJ, Klapper LN, Tzahar E et al (1998) Differential endocytic routing of homo- and hetero-dimeric ErbB tyrosine kinases confers signaling superiority to receptor heterodimers. EMBO J 17:3385–3397. doi:10.1093/emboj/17.12.3385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW et al (2004) 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. doi:10.1056/NEJMoa040938 [DOI] [PubMed] [Google Scholar]
- Mendelsohn J, Baselga J (2000) The EGF receptor family as targets for cancer therapy. Oncogene 19:6550–6565. doi:10.1038/sj.onc.1204082 [DOI] [PubMed] [Google Scholar]
- Moasser MM, Basso A, Averbuch SD, Rosen N (2001) The tyrosine kinase inhibitor ZD1839 (“Iressa”) inhibits HER2-driven signaling and suppresses the growth of HER2-overexpressing tumor cells. Cancer Res 61:7184–7188 [PubMed] [Google Scholar]
- Naidu R, Yadav M, Nair S, Kutty MK (1998) Expression of c-erbB3 protein in primary breast carcinomas. Br J Cancer 78:1385–1390 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paez JG, Janne PA, Lee JC, Tracy S, Greulich H, Gabriel S et al (2004) EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304:1497–1500. doi:10.1126/science.1099314 [DOI] [PubMed] [Google Scholar]
- Pao W, Wang TY, Riely GJ, Miller VA, Pan Q, Ladanyi M et al (2005) KRAS mutations and primary resistance of lung adenocarcinomas to gefitinib or erlotinib. PLoS Med 2:e17. doi:10.1371/journal.pmed.0020017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paz-Ares L, Sanchez JM, Garc′ıa-Velasco A, Massuti B, L′opez-Vivanco G, Provencio M et al (2006) A prospective phase II trial of erlotinib in advanced non-small cell lung cancer (NSCLC) patients (p) with mutations in the tyrosine kinase (TK) domain of the epidermal growth factor receptor (EGFR). Proc Am Soc Clin Oncol 24:18s–7020a [Google Scholar]
- Riely GJ, Pao W, Pham D, Li AR, Rizvi N, Venkatraman ES et al (2006) Clinical course of patients with non-small cell lung cancer and epidermal growth factor receptor exon 19 and exon 21 mutations treated with gefitinib or erlotinib. Clin Cancer Res 12(3 Pt 1):839–844. doi:10.1158/1078-0432.CCR-05-1846 [DOI] [PubMed] [Google Scholar]
- Salomon DS, Brandt R, Ciardiello F, Normanno N (1995) Epidermal growth factor-related peptides and their receptors in human malignancies. Crit Rev Oncol Hematol 19:183–232. doi:10.1016/1040-8428(94)00144-I [DOI] [PubMed] [Google Scholar]
- Schiller JH, Harrington D, Belani CP, Langer C, Sandler A, Krook J, Eastern Cooperative Oncology Group et al (2002) Comparison of four chemotherapy regimens for advanced non-small-cell lung cancer. N Engl J Med 346:92–98. doi:10.1056/NEJMoa011954 [DOI] [PubMed] [Google Scholar]
- Sequist LV, Martins RG, Spigel D, Grunberg SM, Spira A, Jänne PA et al (2008) First-line gefitinib in patients with advanced non-small-cell lung cancer harboring somatic EGFR mutations. J Clin Oncol 26(15):2442–2449 [DOI] [PubMed] [Google Scholar]
- Shepherd FA (2008) Molecular selection of patients for first-line treatment of advanced non-small-cell lung cancer with epidermal growth factor inhibitors: not quite ready for prime time. J Clin Oncol 26(15):2426–2427 [DOI] [PubMed] [Google Scholar]
- Shepherd FA, Tsao MS (2006) Unraveling the mystery of prognostic and predictive factors in epidermal growth factor receptor therapy. J Clin Oncol 24(7):1219–1220 [DOI] [PubMed] [Google Scholar]
- Shepherd FA, Pereira J, Ciuleanu TE, Tan EH, Hirsh V, Thongprasert S, National Cancer Institute of Canada Clinical Trials Group et al (2005) Erlotinib in previously treated non-small cell lung cancer. N Engl J Med 353:123–132. doi:10.1056/NEJMoa050753 [DOI] [PubMed] [Google Scholar]
- Sunaga N, Tomizawa Y, Yanagitani N, Iijima H, Kaira K, Shimizu K et al (2007) Phase II prospective study of the efficacy of gefitinib for the treatment of stage III/IV non-small cell lung cancer with EGFR mutations, irrespective of previous chemotherapy. Lung Cancer 56(3):383–389. doi:10.1016/j.lungcan.2007.01.025 [DOI] [PubMed] [Google Scholar]
- Sutani A, Nagai Y, Udagawa K, Uchida Y, Koyama N, Murayama Y, Tanaka T, Miyazawa H, Nagata M, Kanazawa M, Hagiwara K, Kobayashi K (2006) Gefitinib for non-small-cell lung cancer patients with epidermal growth factor receptor gene mutations screened by peptide nucleic acid-locked nucleic acid PCR clamp. Br J Cancer 95(11):1483–1489 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thatcher N, Chang A, Parikh P, Rodrigues Pereira J, Ciuleanu T, von Pawel J et al (2005) 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. doi:10.1016/S0140-6736(05)67625-8 [DOI] [PubMed] [Google Scholar]
- Therasse P, Arbuck SG, Eisenhauer EA, Wanders J, Kaplan RS, Rubinstein L et al (2000) New guidelines to evaluate the response to treatment in solid tumors. J Natl Cancer Inst 92:205–216. doi:10.1093/jnci/92.3.205 [DOI] [PubMed] [Google Scholar]
- Tsao MS, Sakurada A, Cutz JC, Zhu CQ, Kamel-Reid S, Squire J et al (2005) Erlotinib in lung cancer—molecular and clinical predictors of outcome. N Engl J Med 353:133–144. doi:10.1056/NEJMoa050736 [DOI] [PubMed] [Google Scholar]
- Wu YL, Zhong WZ, Li LY, Zhang XT, Zhang L, Zhou CC, Liu W, Jiang B, Mu XL, Lin JY, Zhou Q, Xu CR, Wang Z, Zhang GC, Mok T (2007) Epidermal growth factor receptor mutations and their correlation with gefitinib therapy in patients with non-small cell lung cancer: a meta-analysis based on updated individual patient data from six medical centers in mainland China. J Thorac Oncol 2(5):430–439 [DOI] [PubMed] [Google Scholar]
- Yoshida K, Yatabe Y, Park JY, Shimizu J, Horio Y, Matsuo K et al (2007) Prospective validation for prediction of gefitinib sensitivity by epidermal growth factor receptor gene mutation in patients with non-small cell lung cancer. J Thorac Oncol 2(1):22–28. doi:10.1097/01243894-200701000-00006 [PubMed] [Google Scholar]


