Lung Cancer 66 (2009) 107–113
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Comprehensive analysis of EGFR signaling pathways in Japanese patients with non-small cell lung cancer Shinobu Hosokawa a , Shinichi Toyooka b , Yoshiro Fujiwara a , Masaki Tokumo b , Junichi Soh b , Nagio Takigawa a , Katsuyuki Hotta a , Tadashi Yoshino c , Hiroshi Date d , Mitsune Tanimoto a , Katsuyuki Kiura a,∗ a Department of Hematology, Oncology and Respiratory Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Okayama 700-8558, Japan b Department of Cancer and Thoracic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan c Department of Pathology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan d Department of Thoracic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
a r t i c l e
i n f o
Article history: Received 11 August 2008 Received in revised form 22 December 2008 Accepted 5 January 2009 Keywords: EGFR mutation Immunohistochemistry pAkt pMAPK EGFR protein pEGFR Non-small cell lung cancer Gefitinib Prognostic factor
a b s t r a c t Purpose: Translational approach is essentially needed to return the achievement of basic researches to oncological practice. The molecular associations among EGFR mutation and the components of EGFR signaling pathways have been extensively studied in laboratory experiments, although were still controversial. Moreover, the impact of downstream signaling of EGFR on clinical features in patients with non-small cell lung cancer (NSCLC) remains undetermined. Patients and methods: A total of 93 surgically resected NSCLC patients were recruited the study. EGFR mutation status was analyzed by direct sequence method. The protein expression levels of EGFR, phosphorylated EGFR (pEGFR), phosphorylated Akt (pAkt), and phosphorylated MAPK (pMAPK) were determined by immunohistochemistry. Results: There were 37 (40%) patients whose tumor harboring EGFR mutations (1 in exon 18, 22 in exon 19, and 14 in exon 21). Protein expression of EGFR, pEGFR, pAkt, and pMAPK was detected in 61 (66%), 27 (29%), 58 (62%), and 41 (44%) patients, respectively. The expression of pAkt was significantly associated with female gender and never-smoking history, and it was frequently upregulated in tumors harboring EGFR mutations (p < 0.05, each). Phosphorylation of EGFR was closely correlated with the EGFR protein expression (p < 0.05), but not with the EGFR mutations. In regard to patient survival, none of the molecular biomarkers was predictive for survival after surgical resection, but pMAPK expression was predictive for poor prognosis after gefitinib treatment in patients with postoperative recurrence (p < 0.05), suggesting the strong linkage between pMAPK expression and survival benefit from gefitinib. Conclusion: Our result could provide new insight into MAP kinase signaling when we treat NSCLC patients with gefitinib. © 2009 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Lung cancer is molecularly characterized by dysregulation of various signaling pathways resulting from genetic alterations. Accumulating evidence suggests that epidermal growth factor receptor (EGFR) signaling pathways are involved in the development and progression of lung cancer [1–3]. EGFR is a transmembrane tyrosine kinase receptor that regulates cell proliferation, differentiation, and survival in both normal and tumor cells. Somatic mutations of EGFR gene, found in a certain subset of non-small cell lung cancer (NSCLC)
∗ Corresponding author. Tel.: +81 86 235 7225; fax: +81 86 232 8226. E-mail address:
[email protected] (K. Kiura). 0169-5002/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.lungcan.2009.01.005
patients including female patients and those with never-smoking history and adenocarcinoma histology, constitutively enhances the EGFR tyrosine kinase activity and the receptor autophosphorylation in numerous preclinical studies [4–6]. In addition, the signalings of EGFR are transmitted into the nucleus through the two major downstream pathways, PI3K/Akt and RAS/MAPK pathways, after following the upstream EGFR phosphorylation. The expression of these intracellular mediators is frequently aberrated in NSCLC: phosphorylated Akt (pAkt) expression is observed in 20–89% of NSCLC, and phosphorylated MAPK (pMAPK) expression occurred in 22–77% of NSCLC [7–10]. Notably, among various alterations of EGFR and related intracellular mediators in lung cancer, the activating EGFR mutations strongly affected the sensitivity to EGFR tyrosine kinase inhibitors
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(EGFR-TKI), indicating the presence of “oncogene addiction” to EGFR signaling pathways in a certain fraction of NSCLC [11], but, the impact of its downstream molecular alternations on clinicopathological features and prognosis after the initiation of EGFR-TKI therapy has been extensively investigated, but still controversial. To better understand the clinical significance of EGFR-related molecular markers in NSCLC, we investigated the EGFR gene and protein status and its downstream molecules using clinical tumor specimens obtained from surgically resected patients with NSCLC, and assessed their association with clinicopathological factors and treatment outcomes. 2. Patients and methods 2.1. Patients We reviewed surgically resected patients with NSCLC who were treated at Okayama University Hospital between August 1994 and January 2005, and found that a total of 100 patients underwent complete tumor resection. Seven patients who underwent neoadjuvant therapy were excluded from the study because we focused on the original molecular status of the tumor and its associations with other molecular markers and/or clinical outcomes. Finally, 93 patients were subjected to the analysis. Among them, 32 patients received adjuvant chemotherapy (22, uracil-tegafur; 3, vinorelbine plus gemcitabine; 3, gemcitabine; 4, others), and five did adjuvant radiotherapy. The patient characteristics are summarized in Table 1. Institutional review board approved this trial and informed consents were obtained for all patients. 2.2. Mutation analysis for EGFR and K-RAS genes EGFR and K-RAS mutations were examined using PCR-based direct sequencing for four exons of the tyrosine kinase domain (exons 18–21) of EGFR gene and exon 2 of K-RAS gene as previously described [4,12,13]. PCR products for each exon were incubated using ExoSAP-IT (Amersham Biosciences Corp., Piscataway, NJ) and sequenced directly using Applied Biosystems PRISM dye terminator cycle sequencing method (Perkin-Elmer Corp., Foster City, CA) with ABI PRISM 3100 Genetic Analyzer (Applied Biosystems, Foster City, CA). Table 1 Patient characteristics. Variables
2.3. Immunohistochemistry The expressions of EGFR, pEGFR, pAkt, and pMAPK proteins were analyzed using immunohistochemistry. Tumor samples were formalin-fixed and paraffin-embedded. In brief, for epitope retrieval, the specimens were exposed to 10 mM citrate buffer (pH 6.0) in water bath (95 ◦ C, 10 min). The sections were then blocked for endogenous peroxidase with 0.3% solution hydrogen peroxide in methanol (30 min). After rinsed with PBS containing 0.1% Tween 20 solution, the sections were blocked by goat normal serum (30 min). Tumor sections were incubated at 4 ◦ C overnight with an antibody specific to the phospho-Akt (Ser473) at 1:50 dilution (Cell Signaling Technology), phospho-p44/p42 Map Kinase (Thr202/Tyr204) at 1:100 dilution (Cell Signaling Technology), EGFR (clone: 31G7) at 1:50 dilution (Zymed Laboratories, San Francisco, CA), or pEGFR at 1:50 dilution (Chemicon International, Temecula, CA). Antibody binding was detected using a VECTASTAIN Elite ABC kits (Vector Laboratories Inc.), and hematoxylin was used for counterstaining. EGFR and pEGFR protein expression were both scored as positive if ten or more percentage of the tumor cells exhibited the cytoplasmic or membranous staining. Similarly, pAkt and pMAPK were both scored as positive if ten or more percentage of the tumor cells exhibited cytoplasmic or nuclear staining [9]. Mutational and immunohistochemical analyses were carried out separately by two groups (group 1, T.Y and S.H and group 2, M.T and J.S), and finally, the data were combined for the statistical analyses (Y.F.). 2.4. Statistical analysis The differences among the categorized groups were compared using the Chi-square test or the Fisher’s exact test, as appropriate. Overall survival for resected patients or gefitinib-treated patients were defined as the time from surgery or gefitinib treatment to the time of death from any cause or to the date the patient was last known to be alive, respectively. Univariate and multivariate analyses of overall survival were carried out with the Kaplan–Meier method using the log–rank test and the Cox proportional hazards model, respectively. All data were analyzed using SPSS Program for Windows (SPSS Inc., Chicago, IL, Version 10.0). All statistical tests were two-sided, and p < 0.05 was considered statistically significant. 3. Results 3.1. Association between molecular markers and clinicopathlogical factors
No. of patients (%) (n = 93)
No. of patients treated with gefitinib (%) (n = 22)
Age Median (range) <75 ≥75
70(39–90) 69 (74.2) 24 (25.8)
71(39–79) 18 (81.8) 4 (18.2)
Gender Male Female
62 (66.7) 31 (33.3)
10 (45.5) 12 (54.5)
Smoking history Ever Never
58 (62.4) 35 (37.6)
11 (50.0) 11 (50.0)
Tumor histology Ad Sq Others
68 (73.1) 23 (24.7) 2 (2.2)
19 (86.4) 2 (9.1) 1 (4.5)
Pathological stage I II III
61 (65.6) 15 (16.1) 17 (18.3)
10 (45.5) 5 (22.7) 7 (31.8)
Abbreviations: Ad, adenocarcinoma; Sq, squamous cell carcinoma.
EGFR mutations were detected in 37 (39.8%) of 93 patients; 22 patients had exon 19 deletions, 14 patients had an exon 21 mutation (L858R), and one patient had an exon 18 mutation (G719A). In tumor specimen obtained by surgical resection, the protein expression of EGFR, pEGFR, pAkt, and pMAPK was positive in 61 (65.6%), 27 (29.0%), 58 (62.4%), and 41 (44.1%) of the 93 patients. Examples of the immunohistochemical staining patterns are shown in Fig. 1. The relationships between the clinicopathological factors and the EGFR mutation status or the immunohistochemical staining patterns are listed in Table 2. As expected, the univariate analysis indicated that female gender (p < 0.001), never-smoking history (p < 0.001), and adenocarcinoma histology (p < 0.001) were significantly related to the presence of EGFR mutation. No significant associations between the pEGFR or pMAPK expression status and any clinicopathological factors were seen. However, pAkt expression was significantly higher in never-smokers than in smokers (80% vs. 52%, p = 0.006), and in female than in male (77% vs. 55%, p = 0.034). In addition, positive EGFR expression was more frequently observed in adenocarcinoma than in non-adenocarcinoma (72% vs. 48%, p = 0.030).
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Fig. 1. Representative examples of immunohistochemically positive and negative stainings for EGFR (A) and (B), pEGFR (C) and (D), pAkt (E) and (F), and pMAPK (G) and (H) in tumor specimen, respectively.
3.2. Interactions of molecular markers The relationships among specific molecular markers are demonstrated in Table 3. Univariate analysis for total cases showed a significant relationship between EGFR mutation and pAkt (p = 0.010). The pAkt expression was also related to pMAPK expression significantly (p = 0.001). The pEGFR expression was significantly correlated to EGFR protein expression (p = 0.015), but not with EGFR mutation. No other correlations were observed between molecular markers analyzed. 3.3. Impact of molecular markers on survival from the day of surgical resection Median survival time for all patients was 10.0 years. Fig. 2 shows overall survival curves stratified according to EGFR mutation, EGFR, pEGFR, pAkt, and pMAPK protein expression status. None of the molecular markers predicted survival, although the EGFR mutation positive patients were likely to live longer than the EGFR mutation negative patients (median survival time: not reached vs. 10.0 years). 3.4. Impact of molecular markers on survival from the beginning of gefitinib treatment We examined the effects of molecular markers on treatment outcomes of gefitinib. In this study, there were 22 (23.7%) patients who were treated with gefitinib (250 mg/(body day)) for postoperative recurrence. The demographics of patients were shown in Table 1. According to the standard bidimensional response criteria, the overall response rate of gefitinib was 31.8%. No relationship of any molecular markers with response to gefitinib in this small subset existed, although patients with EGFR mutation tended to have higher response rate than those without (54.5% vs. 9.1%, p = 0.063). A univariate analysis revealed that pMAPK expression was the adverse prognostic factor for patients with gefitinib treatment (median survival time: 12.3 months vs. 24.2 months in patients with or without pMAPK expression, respectively, p < 0.01; Fig. 3), and the EGFR mutation tended to prolong survival compared with the EGFR wild-type (median survival time: 24.2 months vs. 13.3 months in patients with or without EGFR mutation, respectively). We could not find any significant differences in survival time between other molecular markers. A multivariate analysis demonstrated that pMAPK expression was the independent negative prognostic factor significantly (hazard ratio = 11.2; 95% CI,
2.3–55.3; p = 0.003), whereas any other molecular markers were not (Table 4). 4. Discussion In this study, we demonstrated using clinical samples not only specific relationships among the EGFR-related molecules, but also the linkage between molecular and clinical features: significant molecular association was found between EGFR mutation and pAkt expression, EGFR protein expression and pEGFR expression, pAkt expression and pMAPK expression. Clinical correlation was seen between EGFR mutation or pAkt expression and never-smoking history or female gender as well as adenocarcinoma histology and EGFR protein expression, respectively. Of note, our data indicated that higher expression of pMAPK was correlated with poor prognosis in NSCLC patients treated with gefitinib. To date, many investigators extensively studied the associations between EGFR mutation and the downstream molecules such as pAkt and pMAPK in lung cancer cell line, and revealed that EGFR mutation is almost always accompanied with enhanced signalings of intracellular cascades in preclinical setting [9,14–16]. Unlike their results, current study failed to demonstrate the clear connections of EGFR mutation with the downstream effecter proteins except for pAkt. The exact reason for this discordant result among basic and clinical researches is unknown. However, one of the possible explanations is that signalings from several upstream molecules other than EGFR, such as KRAS, RAF, insulin-like growth factor receptor (IGFR), and MET, could affect the activation status of pAkt and/or pMAPK because they share the common downstream pathways with EGFR [17–20]. Similar to preclinical observations, pAkt expression is significantly associated with EGFR mutation, suggesting EGFR mutation predominantly activated pAkt-mediated downstream pathways, rather than pMAPK-mediated ones. These observations were identical to other clinical studies [21,22]. In addition, pAkt is also correlated to never-smoking history and female gender, which resembles the demographics of patients whose tumor harboring EGFR mutation. Thus, as is EGFR mutation, pAkt expression might be one of the key molecular alterations for smoking unrelated lung cancer that occupy an unignorable population in all lung cancer cases. Cappuzzo et al. reported a favorable outcome of high expression levels of pAkt in NSCLC patients treated with gefitinib [9], but Hirsch et al. [15] and we failed to demonstrate it in unselected
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Table 2 Association between molecular markers and clinicopathlogical factors. Variables (no. of pts, %)
EGFR mutation
EGFR protein
Positive
Negative
Total case
37 (39.8)
56 (60.2)
Age <75 ≥75
26 (37.7) 11 (45.8)
43 (62.3) 13 (54.2)
Gender Male Female
17 (27.4) 20 (64.5)
Smoking history Ever Never
p
pEGFR Negative
61 (65.6)
32 (34.4)
0.482
45 (65.2) 16 (66.7)
24 (34.8) 8 (33.3)
45 (72.6) 11 (35.5)
<0.001
37 (59.7) 24 (77.4)
10 (17.2) 27 (77.1)
48 (82.8) 8 (22.9)
<0.001
Tumor histology Ad Non-ad
36 (52.9) 1 (4.0)
32 (47.1) 24 (96.0)
Pathological stage I–II III
31 (40.8) 6 (35.3)
45 (59.2) 11 (64.7)
p
Positive
Negative
27 (29.0)
66 (71.0)
0.898
18 (26.1) 9 (37.5)
51 (73.9) 15 (62.5)
25 (40.3) 7 (22.6)
0.090
18 (29.0) 9 (29.0)
35 (60.3) 26 (74.3)
23 (39.7) 9 (25.7)
0.170
<0.001
49 (72.1) 12 (48.0)
19 (27.9) 13 (52.0)
0.676
48 (63.2) 13 (76.5)
28 (36.8) 4 (23.5)
p
pMAPK
Positive
Negative
58 (62.4)
35 (37.6)
0.289
43 (62.3) 15 (62.5)
26 (37.7) 9 (37.5)
44 (71.0) 22 (71.0)
>0.999
34 (54.8) 24 (77.4)
20 (34.5) 7 (20.0)
38 (65.5) 28 (80.0)
0.136
0.030
18 (26.5) 9 (36.0)
50 (73.5) 16 (64.0)
0.401
21 (27.6) 6 (35.3)
55 (72.4) 11 (64.7)
p
Positive
Negative
41 (44.1)
52 (55.9)
p
0.987
32 (46.4) 9 (37.5)
37 (53.6) 15 (62.5)
0.451
28 (45.2) 7 (22.6)
0.034
27 (43.5) 14 (45.2)
35 (56.5) 17 (54.8)
0.883
30 (51.7) 28 (80.0)
28 (48.3) 7 (20.0)
0.006
26 (44.8) 15 (42.9)
32 (55.2) 20 (57.1)
0.853
0.369
46 (67.6) 12 (48.0)
22 (32.4) 13 (52.0)
0.083
30 (44.1) 11 (44.0)
38 (55.9) 14 (56.0)
0.992
0.529
49 (64.5) 9 (52.9)
27 (35.5) 8 (47.1)
0.375
35 (46.1) 6 (35.3)
41 (53.9) 11 (64.7)
0.419
Abbreviations: pts, patients; Ad, adenocarcinoma. Bold letters stand for a statistical significance.
Table 3 Association within molecular markers. Variables (no. of pts, %)
Total case EGFR mutation Positive Negative
EGFR mutation
EGFR protein
Positive
Negative
37 (39.8)
56 (60.2)
– –
– –
p
–
pEGFR
Positive
Negative
61 (65.6)
32 (34.4)
28 (75.7) 33 (58.9)
9 (24.3) 23 (41.1)
p
pAkt
Positive
Negative
27 (29.0)
66 (71.0)
0.096
10 (27.0) 17 (30.4)
27 (73.0) 39 (69.6)
–
23 (37.7) 4 (12.5)
38 (62.3) 28 (87.5)
p
Negative
58 (62.4)
35 (37.6)
0.729
29 (78.4) 29 (51.8)
8 (21.6) 27 (48.2)
0.015
41 (67.2) 17 (53.1)
–
17 (63.0) 41 (62.1)
EGFR protein Positive Negative
28 (45.9) 9 (28.1)
33 (54.1) 23 (71.9)
0.096
pEGFR Positive Negative
10 (37.0) 27 (40.9)
17 (63.0) 39 (59.1)
0.729
23 (85.2) 38 (57.6)
4 (14.8) 28 (42.4)
0.015
pAkt Positive Negative
29 (50.0) 8 (22.9)
29 (50.0) 27 (77.1)
0.010
41 (70.7) 20 (57.1)
17 (29.3) 15 (42.9)
0.183
17 (29.3) 10 (28.6)
41 (70.7) 25 (71.4)
0.939
pMAPK Positive Negative
14 (34.1) 23 (44.2)
27 (65.9) 29 (55.8)
0.324
25 (61.0) 36 (69.2)
16 (39.0) 16 (30.8)
0.405
12 (29.3) 15 (28.8)
29 (70.7) 37 (71.2)
0.964
– –
Abbreviations: pts, patients. Bold letters stand for a statistical significance.
– –
– –
– –
pMAPK
Positive
– – 33 (80.5) 25 (48.1)
Positive
Negative
41 (44.1)
52 (55.9)
0.010
14 (37.8) 27 (48.2)
23 (62.2) 29 (51.8)
0.324
20 (32.8) 15 (46.9)
0.183
25 (41.0) 16 (50.0)
36 (59.0) 16 (50.0)
0.405
10 (37.0) 25 (37.9)
0.939
12 (44.4) 29 (43.9)
15 (55.6) 37 (56.1)
0.964
–
33 (56.9) 8 (22.9)
25 (43.1) 27 (77.1)
0.001
– – 8 (19.5) 27 (51.9)
p
0.001 –
– –
–
p
–
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Positive
pAkt
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Fig. 2. Survival curves of 93 non-small cell lung cancer patients treated with surgical resection. Overall survivals of patients according to EGFR mutation status (A), EGFR protein status (B), pEGFR status (C), pAkt status (D), and pMAPK status (E). p-Values were calculated using the log–rank test.
Fig. 3. Survival curves of 22 non-small cell lung cancer patients treated with gefitinib. Overall survival of patients according to EGFR mutation status (A), EGFR protein status (B), pEGFR status (C), pAkt status (D), and pMAPK status (E). p-Values were calculated using the log–rank test.
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Table 4 Multivariate analysis for the survival of NSCLC patients treated with gefitinib. Variables
HR
Age (<75/≥75) Gender (male/female) Smoking history (ever/never) Tumor histology (Non-ad/Ad) Pathological stage (I–II/III) pMAPK expression (negative/positive) EGFR mutation (negative/positive)a EGFR protein expression (negative/positive)a pEGFR expression (negative/positive)a pAkt expression (negative/positive)a
24.29 0.334 0.403 0.154 0.142 11.17 1.530 0.344 0.420 1.907
95% CI 1.703–346.4 0.064–1.737 0.087–1.877 0.024–0.994 0.027–0.736 2.255–55.33 0.082–28.59 0.079–1.491 0.114–1.541 0.453–8.035
p 0.019 0.192 0.247 0.049 0.020 0.003 0.776 0.154 0.191 0.379
Abbreviations: NSCLC, non-small cell lung cancer; Ad, adenocarcinoma; HR, hazard ratio; CI, confidence interval. Bold letters stand for a statistical significance. a Data are shown when used as alternative to the co-variate “pMAPK expression”.
NSCLC patients. Han et al. revealed a significant survival advantage in patients harboring activating EGFR mutations with strong expression of pAkt [14]. In contrast, pAkt-positive patients without EGFR mutations tended to show a shorter survival [14]. pAkt in cancer cells with activating EGFR mutations is likely to be a predictive marker of responsiveness to gefitinib; however, a prospective trial failed to demonstrate it in EGFR FISH positive patients [16]. In our cohort treated with gefitinib, only 2 (9%) of 22 patients expressed pAkt with EGFR mutations, and 3 (14%) expressed both pAkt and pEGFR. Our cohort treated with gefitinib was too small to detect a relationship between pAkt and EGFR mutations or pEGFR. Although several previous studies have already reported a number of molecular predictors for treatment outcomes in gefitinib-treated cases, we first revealed the poor prognostic value of pMAPK expression in such patients. Our results are also supported by the evidence from preclinical studies showing that the activation of MAPK has an antiapoptic effect on tumor cells as well as intrinsic resistance to gefitinib [23]. However, contrary to ours, Cappuzzo et al. failed to demonstrate a favorable outcome of high expression levels of pMAPK in NSCLC patients treated with gefitinib[9]. Further investigations for the role of pAkt and pMAPK as a biomarker for gefitinib treatment are required. The current study had several limitations. First, our study consisted of only Japanese patients. Considering ethnic difference regarding the frequency of EGFR mutation and the efficacy of gefitinib, these findings should therefore be cautiously interpreted when our results applied to non-Japanese patients. Second, our results should be confirmed by larger prospective trials because this trial was conducted retrospectively. Third, since the associations of molecular markers and clinicopathological factors were evaluated only in surgically resectable NSCLC patients, it is unclear whether such findings are reproduced in more advanced stage NSCLC. Fourthly, we have to check the downstream signaling from EGFR during gefitinib treatment to elucidate true molecular profiles of NSCLC; however, it is very difficult to obtain the enough tumor samples before and during gefitinib treatment, especially from a primary site of the lung. Finally, we did not investigate other oncogenes, such as RAF, MET, EML4-ALK, etc. which might affect pAkt and pMAPK status. K-RAS status was evaluated in 81 of 97 NSCLC patients analyzed in this study. Only 4 (5%) of 81 patients, however, had K-RAS (codon 12) and did not accompanied with activating EGFR mutation. Moreover, only one of four patients was treated with gefitinib. It has been reported that 8–13% of NSCLC patients who underwent surgery had K-RAS mutation [12,24,25]. The reason for a low incidence of K-RAS mutations is unclear. pAkt and pMAPK statuses in four patients with K-RAS mutation are as follows: −/−, two; +/−, one and −/+, one, respectively. Patients with K-RAS mutations were too few to detect a relationship between pMAPK and K-RAS mutations in this study.
In conclusion, we characterized molecular profiles of NSCLC, with special emphasis on EGFR signaling pathways. We found that pMAPK was a negative prognostic factor when treated with gefitinib, which provide information for future researches targeting EGFR signaling pathways. Conflict of interest None declared. Acknowledgements We thank Drs. Daizo Kishino, Toshiaki Okada, and Ken Sato (Okayama University Graduate School of Medicine, Dentistry Pharmaceutical Sciences) for their support, data provision, and comments on our analysis. This work was supported in part by grants no. 19590895 from the Ministry of Education, Culture, Sports, Science, and Technology (K.K.). This work was presented in part and awarded the AACR-ITO EN, Ltd., Scholar-in-Training Award (Y.F.) at the 2008 Annual Meeting of the American Association for Cancer Research (San Diego, CA, USA). References [1] Merrick DT, Kittelson J, Winterhalder R, Kotantoulas G, Ingeberg S, Keith RL, et al. Analysis of c-ErbB1/epidermal growth factor receptor and c-ErbB2/HER-2 expression in bronchial dysplasia: evaluation of potential targets for chemoprevention of lung cancer. Clin Cancer Res 2006;12:2281–8. [2] Toyooka S, Tokumo M, Shigematsu H, Matsuo K, Asano H, Tomii K, et al. Mutational and epigenetic evidence for independent pathways for lung adenocarcinomas arising in smokers and never smokers. Cancer Res 2006;66:1371–5. [3] Soh J, Toyooka S, Ichihara S, Asano H, Kobayashi N, Suehisa H, et al. Sequential molecular changes during multistage pathogenesis of small peripheral adenocarcinomas of the lung. J Thorac Oncol 2008;3:340–7. [4] Tokumo M, Toyooka S, Kiura K, Shigematsu H, Tomii K, Aoe M, et al. The relationship between epidermal growth factor receptor mutations and clinicopathologic features in non-small cell lung cancers. Clin Cancer Res 2005;11: 1167–73. [5] Sordella R, Bell DW, Haber DA, Settleman J. Gefitinib-sensitizing EGFR mutations in lung cancer activate anti-apoptotic pathways. Science 2004;305: 1163–7. [6] Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004;350:2129–39. [7] Massion PP, Taflan PM, Shyr Y, Rahman SM, Yildiz P, Shakthour B, et al. Early involvement of the phosphatidylinositol 3-kinase/Akt pathway in lung cancer progression. Am J Respir Crit Care Med 2004;170:1088–94. [8] Mukohara T, Kudoh S, Matsuura K, Yamauchi S, Kimura T, Yoshimura N, et al. Activated Akt expression has significant correlation with EGFR and TGF-alpha expressions in stage I NSCLC. Anticancer Res 2004;24:11–7. [9] Cappuzzo F, Magrini E, Ceresoli GL, Bartolini S, Rossi E, Ludovini V, et al. Akt phosphorylation and gefitinib efficacy in patients with advanced non-smallcell lung cancer. J Natl Cancer Inst 2004;96:1133–41. [10] Sonobe M, Nakagawa M, Takenaka K, Katakura H, Adachi M, Yanagihara K, et al. Influence of epidermal growth factor receptor (EGFR) gene mutations on the expression of EGFR, phosphoryl-Akt, and phosphoryl-MAPK, and on the prognosis of patients with non-small cell lung cancer. J Surg Oncol 2007;95: 63–9. [11] Ichihara S, Toyooka S, Fujiwara Y, Hotta K, Shigematsu H, Tokumo M, et al. The impact of epidermal growth factor receptor gene status on gefitinibtreated Japanese patients with non-small-cell lung cancer. Int J Cancer 2007;120:1239–47. [12] Shigematsu H, Lin L, Takahashi T, Nomura M, Suzuki M, Wistuba I, et al. Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 2005;97:339–46. [13] Toyooka S, Tsukuda K, Ouchida M, Tanino M, Inaki Y, Kobayashi K, et al. Detection of codon 61 point mutations of the K-ras gene in lung and colorectal cancers by enriched PCR. Oncol Rep 2003;10:1455–9. [14] Han SW, Kim TY, Hwang PG, Jeong S, Kim J, Choi IS, et al. Predictive and prognostic impact of epidermal growth factor receptor mutation in nonsmall-cell lung cancer patients treated with gefitinib. J Clin Oncol 2005;23: 2493–501. [15] Hirsch FR, Varella-Garcia M, Bunn Jr PA, Franklin WA, Dziadziuszko R, Thatcher N, et al. Molecular predictors of outcome with gefitinib in a phase III placebo-controlled study in advanced non-small-cell lung cancer. J Clin Oncol 2006;24:5034–42. [16] Cappuzzo F, Ligorio C, Jänne PA, Toschi L, Rossi E, Trisolini R, et al. Prospective study of gefitinib in epidermal growth factor receptor fluorescence in situ
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