Impact of Serum Hepatocyte Growth Factor on Treatment

Published OnlineFirst August 2, 2010; DOI: 10.1158/1078-0432.CCR-10-0383

Clinical Imaging, Diagnosis, Prognosis Cancer Research Impact of Serum Hepatocyte Growth Factor on Treatment Response to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients with Non–Small Cell Lung Adenocarcinoma

Kazuo Kasahara1, Tokuzo Arao2, Kazuko Sakai2, Kazuko Matsumoto2, Asao Sakai1, Hideharu Kimura1, Takashi Sone1, Atsushi Horiike4, Makoto Nishio4, Tatsuo Ohira5, Norihiko Ikeda5, Takeharu Yamanaka6, Nagahiro Saijo3, and Kazuto Nishio2

Abstract Purpose: The epidermal growth factor receptor (EGFR) mutation status has emerged as a validated biomarker for predicting the response to treatment with EGFR-tyrosine kinase inhibitors (EGFR-TKI) in patients with non–small cell lung cancer. However, the responses to EGFR-TKIs vary even among patients with EGFR mutations. We studied several other independently active biomarkers for EGFR-TKI treatment. Experimental Design: We retrospectively analyzed the serum concentrations of 13 molecules in a cohort of 95 patients with non–small cell lung adenocarcinoma who received EGFR-TKI treatment at three centers. The pretreatment serum concentrations of amphiregulin, β-cellulin, EGF, EGFR, epiregulin, fibroblast growth factor-basic, heparin-binding EGF-like growth factor, hepatocyte growth factor (HGF), platelet-derived growth factor β polypeptide, placental growth factor, tenascin C, transforming growth factor-α, and vascular endothelial growth factor (VEGF) were measured using enzyme-linked immunosorbent assay and a multiplex immunoassay system. The associations between clinical outcomes and these molecules were evaluated. Results: The concentrations of HGF and VEGF were significantly higher among patients with progressive disease than among those without progressive disease (P < 0.0001). HGF and VEGF were strongly associated with progression-free survival (PFS) and overall survival (OS) in a univariate Cox analysis (all tests for hazard ratio showed P < 0.0001). A stratified multivariate Cox model according to EGFR mutation status (mutant, n = 20; wild-type, n = 23; unknown, n = 52) showed that higher HGF levels were significantly associated with a shorter PFS and OS (P < 0.0001 for both PFS and OS). These observations were also consistent in the subset analyses. Conclusions: Serum HGF was strongly related to the outcome of EGFR-TKI treatment. Our results sug- gest that the serum HGF level could be used to refine the selection of patients expected to respond to EGFR-TKI treatment, warranting further prospective study. Clin Cancer Res; 16(18); 4616–24. ©2010 AACR.

Selective epidermal growth factor receptor tyrosine ki- non–small cell lung carcinoma (NSCLC, refs. 4–6). To nase inhibitors (EGFR-TKI) block signal transduction date, four populations are known to have a better pathways implicated in the proliferation and survival response to EGFR-TKIs: females, never-smokers, adeno- of cancer cells (1–3), and show clinical activity against carcinoma histology, and patients of East Asian ethnicity (4–6). Active EGFR mutation apparently confers a Authors' Affiliations: 1Respiratory Medicine, School of Medicine, hyperresponsiveness to gefitinib among NSCLC patients Kanazawa University, Kanazawa, Ishikawa, Japan; 2Department of (7, 8). Such mutations affect the ATP-binding cleft Genome Biology, 3Kinki University School of Medicine, Osaka-Sayama, Osaka, Japan; 4Thoracic Oncology Center, Cancer Institute Hospital, of EGFR, and EGFR mutants exhibit constitutive tyrosine Japanese Foundation for Cancer Research, and 5Department of kinase activity. Most reported EGFR mutations are either Thoracic Surgery and Oncology, Tokyo Medical University, Tokyo, point mutations in exons 18 (G719A/C) and 21 (L858R Japan; and 6Institute for Clinical Research, National Kyushu Cancer Center, Fukuoka, Japan and L861Q) or in-frame deletions in exon 19 that eliminate five amino acids (ELREA) located at position Note: T. Arao and K. Sakai contributed equally to this work. 745 (9). Corresponding Author: Kazuto Nishio, Department of Genome Biology, Kinki University School of Medicine, 377-2 Ohno-higashi, Osaka-Sayama, A large-scale randomized study, the IRESSA Pan-Asia Osaka 589-8511, Japan. Phone: 81-72-366-0221 ext. 3150; Fax: 81-72- study (IPASS), comparing gefitinib monotherapy with 367-6369; E-mail: [email protected]. carboplatin/paclitaxel for 1,217 previously untreated doi: 10.1158/1078-0432.CCR-10-0383 patients with lung adenocarcinoma, was recently completed, ©2010 American Association for Cancer Research. and the results showed that the progression-free survival

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Response Evaluation Criteria in Solid Tumors; the response Translational Relevance was then classified as a complete response (CR), a partial response (PR), stable disease (SD), or progressive disease A high pretreatment serum HGF concentration was (PD). Clinicopathologic features including age, gender, strongly associated with poor treatment outcomes, in- Eastern Cooperative Oncology Group (ECOG) perfor- cluding tumor response, progression-free survival, and mance status (PS), tumor-node-metastasis stage, smoking – overall survival, in patients with non small cell lung status, and EGFR mutation status were recorded. Direct adenocarcinoma treated with epidermal growth factor sequencing of a tumor sample was done to detect active receptor tyrosine kinase inhibitors (EGFR-TKI). Com- EGFR mutations in 43 patients; 20 of these samples were bined with the EFGR mutation status, measurement found to harbor an EGFR mutation (exon 19, n = 14; exon of the serum HGF level might further refine the selec- 21, n =6),whereastheremaining23samplesexhibited tion of patients likely to respond to EGFR-TKI treat- wild-type EGFR. The mutation status of the other 52 ment, especially in the wild-type EGFR subgroup, patients was not evaluated. The present study was ap- thereby increasing the clinical benefit of EGFR-TKI proved by the institutional review boards of all the centers. treatment. Preparation of serum samples Blood samples were collected before the initiation of EGFR-TKI treatment. Separated serum was stocked at (PFS) curves of the two arms crossed each other. A subset -80°C until use. analysis of the 437 patients whose EGFR mutation status was known revealed that the presence of an EGFR Serum HGF levels mutation in the tumor was a strong predictor of a better Serum HGF concentrations were determined using a outcome after gefitinib treatment (10). Two recent Human HGF Quantikine ELISA Kit (R&D Systems) accord- phase III trials targeting adenocarcinoma patients with ing to the manufacturer's instructions. A 50-μL aliquot of EGFR mutations showed that the gefitinib group had serum per well was examined in duplicate, and the average a significantly longer PFS than the platinum-doublet was used for subsequent analysis. The absorbance of the therapy group (11, 12). These data indicated EGFR mu- samples at 450 nm was measured using VERSAmax (Japan tation status as a powerful predictor of the tumor re- Molecular Devices). sponse to EGFR-TKIs. Even among patients with EGFR mutations, however, Antibody suspension bead array system not all patients respond to EGFR-TKI treatment in like Antibody suspension bead arrays for determining the se- manner; the objective response to EGFR-TKI treatment rum concentrations of 12 molecules were obtained commer- has remained at 62% to 75% (11–13). In addition, no cially (WideScreen Human Cancer Panel 2, Merck). The effective biomarker is currently available for patients with markers used in this panel were as follows: amphiregulin, wild-type EGFR tumors (14). These facts motivated us to β-cellulin, epidermal growth factor (EGF), EGFR, epiregulin, investigate molecular biomarkers that can be utilized inde- fibroblast growth factor-basic (FGF-basic), heparin-binding pendently of EGFR status to predict the efficacy of EGFR- EGF-like growth factor (HB-EGF), platelet-derived growth TKIs. Identifying such a marker would contribute to the factor β polypeptide (PDGF-BB), placental growth factor further individualization of treatment for NSCLC. In this (PIGF), tenascin C (TnC), transforming growth factor α report, we retrospectively studied the serum concentra- (TGF-α), and vascular endothelial growth factor (VEGF). tions of several molecules in patients with non–small cell Data were obtained using a Bio-Plex suspension array system lung adenocarcinoma who underwent treatment with (Bio-Rad Laboratories). The assay was done according to the EGFR-TKIs. manufacturer's instructions and a previously described method (15). Serum samples were diluted 1:4 with the ap- Materials and Methods propriate diluents prior to assay. The samples were tested in duplicate, and the averages were used for analysis. Patients A total of 104 patients with histologically confirmed Statistical analysis non–small cell lung adenocarcinoma who had been trea- The primary objective was to investigate novel markers ted with EGFR-TKIs at three centers (Kanazawa University, correlated with efficacy independently of EGFR-status. If Japan; Cancer Institute Hospital, Japan; and Tokyo Medical a molecule was very strongly associated with survival after University, Japan) between 2002 and 2009 were included adjustments for the EGFR status and important prognostic in this study. Six patients were excluded because their factors, then that molecule was deemed as warranting tumor response was not evaluated. A complete clinical further prospective study to determine whether it is a data set was not available for three additional patients. predictive factor, a prognostic factor, or both. Thus, 95 patients were included in the final analysis The distributions of the clinical factors and molecules (Fig. 1A). The tumor response was evaluated every 2 to 3 were compared between patients with PD and those with- months using computerized tomography according to the out PD using the Wilcoxon test. In terms of the analysis

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Fig. 1. A, flow diagram of analyzed patients. B to D, box-whisker plots of serum concentrations of HGF (pg/mL) and VEGF (pg/mL) in patients with progressive disease (PD) and those without progressive disease (PR+SD). The plots are drawn for all patients (top; n = 95), those with a known EGFR status (middle; n = 43), and those with wild-type EGFR (bottom; n = 23).

for survival time [PFS and overall survival (OS)], clinical association between the molecules and PFS/OS, as any factors including age, gender, ECOG PS, clinical stage, determination of the optimal cutoff point for the mole- and smoking status were examined using the Cox propor- cules relative to the PFS/OS was beyond the scope of the tional hazards model. After selecting the important clinical present study. All the statistical analyses were done using variables, we considered these variables fixedly in a Cox SAS for Windows (ver. 9.1.3) and Medcalc for Windows proportional hazards model and then determined which, (ver. 11.1.1). if any, of the molecules was associated with survival using the backward selection method; thus, any molecules Results remaining in the final model were significant in a manner that was independent of the important clinical variables Patient results at a two-sided level of 0.05 using the Wald test. Log- Of the 95 patients evaluated in this study, all the pa- transformed values were used for the molecules in the tients were of Asian ethnicity and had been treated with Cox models. The proportional hazards assumption was as- an EGFR-TKIs (gefitinib, n = 91; erlotinib, n = 4). Seventy- sessed graphically, and an individual time-dependent five (79%) and eight (8%) patients had received prior component was included for each covariate. In the chemotherapy and radiotherapy, respectively. After multivariate Cox models, EGFR status (wild-type/ the start of EGFR-TKI treatment, a PR was observed mutant/unknown) was treated as a stratified variable. in 37 (39%) patients, SD in 25 (26%) patients, and We applied the above analyses to all the cases, to the cases PD in 33 (35%) patients; none of the patients exhib- in which the EGFR status was evaluated, and to the cases ited a CR. The median follow-up period was 29 months. with wild-type EGFR to check the robustness of the con- The patient characteristics are shown in Table 1. Re- clusions. The survival curves for PFS and OS were estimat- garding tumor response, male gender (P = 0.0002), a ed using the Kaplan-Meier method. The Kaplan-Meier PS of 2 to 4 (P = 0.0498), a positive smoking history curves were shown just to visualize the trends of the (P = 0.0010), and a wild-type EGFR status (P < 0.0001)

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Table 1. Patient characteristics and response to EGFR-TKIs

Total (n = 95) Response to EGFR-TKIs PR+SD (n = 62) PD (n = 33) P

Age (y) Median 64 64 65 0.58 Range 29-89 35-89 29-79 Gender Male 53 26 (42%) 27 (82%) 0.0002 Female 42 36 (58%) 6 (18%) Histology Adenocarcinoma 95 62 (100%) 33 (100%) - Other 0 0 (0%) 0 (0%) PS 0-1 70 50 (81%) 20 (61%) 0.0498 2-4 25 12 (19%) 13 (39%) Stage III 11 7 (11%) 4 (12%) 1.00 IV 84 55 (89%) 29 (88%) Smoking Yes 56 29 (47%) 27 (82%) 0.0010 No 39 33 (53%) 6 (18%) EGFR status Wild-type 23 9 (15%) 14 (42%) <0.0001* Mutant 20 20 (32%) 0 (0%) Unknown 52 33 (53%) 19 (58%)

*Comparison between wild-type and mutant. P values are calculated using the t-test for age and Fisher's exact test for other variables. were significantly less sensitive to EGFR-TKI treatment FGF-basic, HB-EGF, HGF, PDGF-BB, PIGF, TnC, TGF-α, (Table 1). These results are consistent with those of a and VEGF. Among them, many samples (>80%) showed previous report (16). a value that could not be measured or that was below the standard range for amphiregulin, β-cellulin, epiregu- Serum concentrations of 13 molecules lin, FGF-basic, and TGF-α; these molecules were omitted We measured the serum concentrations of 13 mole- from subsequent analyses. Therefore, only the correlations cules: amphiregulin, β-cellulin, EGF, EGFR, epiregulin, between clinical outcome and the serum concentrations of

Table 2. Distributions of serum concentrations according to response status to EGFR-TKIs

All cases (n = 95) EGFR status known (n = 43) EGFR wild-type (n = 23) Median P Median P Median P PR+SD PD PR+SD PD PR+SD PD

EGF 199.1 252.0 0.0334 235.2 268.7 0.23 252.8 268.7 0.87 EGFR 2,100.8 2,092.0 0.58 2,096.0 2,030.6 0.89 2,083.6 2,030.6 0.97 HB-EGF 74.6 114.8 0.0066 79.0 129.9 0.0277 71.8 129.9 0.14 HGF 1,150.8 1,580.0 <0.0001 1,136.5 1,810.9 0.0002 1,116.4 1,810.9 0.0009 PDGF-BB 15,574.3 14,388.8 0.53 14,228.0 19,031.5 0.12 13,385.2 19,031.5 0.11 PIGF 3.8 7.0 0.25 9.0 11.4 0.39 2.5 11.4 0.58 TnC 643.2 979.0 0.0278 557.0 1,211.6 0.0233 614.5 1,211.6 0.07 VEGF 808.8 1,787.0 <0.0001 800.5 2023.0 0.0006 984.5 2023.0 0.0107

NOTE: Median values of eight serum concentrations are tabulated according to the response status. The Wilcoxon test was used to assess the difference in the median values between PR+SD and PD.

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Table 3. Univariate analysis of clinical molecular factors for progression-free and overall survival

All cases (n = 95) Progression-free survival Overall survival HR (95% CI) P HR (95% CI) P

Age 65< vs. ≤65 y 0.93 (0.60-1.43) 0.74 1.22 (0.76-1.96) 0.42 Gender Male vs. Female 1.85 (1.19-2.88) 0.0061 2.36 (1.43-3.88) 0.0007 PS 2-4 vs. 0-1 1.66 (1.04-2.67) 0.0356 2.55 (1.53-4.25) 0.0003 Stage IV vs. III 0.66 (0.34-1.25) 0.20 1.27 (0.61-2.67) 0.53 Smoking Yes vs. No 1.65 (1.06-2.58) 0.0270 2.19 (1.33-3.62) 0.0022 EGF 1.17 (0.90-1.51) 0.24 1.15 (0.86-1.53) 0.34 EGFR 1.37 (0.68-2.79) 0.38 1.37 (0.62-3.05) 0.44 HB-EGF 1.49 (1.09-2.03) 0.0116 1.55 (1.10-2.18) 0.0124 HGF 10.24 (5.48-19.2) <0.0001 5.57 (3.28-9.46) <0.0001 PDGF-BB 1.11 (0.80-1.54) 0.53 1.16 (0.82-1.65) 0.39 PIGF 1.10 (0.87-1.38) 0.44 1.29 (1.01-1.66) 0.04 TnC 1.74 (1.30-2.34) 0.0002 2.19 (1.56-3.06) <0.0001 VEGF 3.54 (2.33-5.38) <0.0001 3.52 (2.25-5.50) <0.0001

(Continued on the following page)

EGF, EGFR, HB-EGF, HGF, PDGF-BB, PIGF, TnC, and PFS and OS (Table 3). Similar to the results for tumor VEGF were analyzed. response, HGF and VEGF were associated with both PFS and OS when all the cases were analyzed, with all tests Tumor response and serum concentrations exhibiting a hazard ratio (HR) with a P value <0.0001. The serum concentrations of EGF, HB-EGF, HGF, TnC, Similar results were obtained when subsets of patients and VEGF were significantly higher among patients with with a known EGFR status and patients with wild-type PD than among those without PD (Table 2). Among these EGFR were analyzed (data not shown). Figure 2 shows molecules, HGF and VEGF exhibited marked differences the Kaplan-Meier estimates for PFS and OS with regard in tumor response. These results were unchanged when to the concentrations of serum HGF and VEGF. Although subsets of patients with a known EGFR status (n = 43) a determination of the optimal cutoff values was beyond as well as patients with wild-type EGFR (n = 23) were the scope of this study, all the patients were divided into analyzed (Fig. 1B-D). These observations suggested that one of four groups according to the quartile values for HGF and VEGF were significantly associated with tumor each molecule. The curves provided a clear trend indicat- response, independent of the EGFR mutation status. The ing that the outcomes became poorer as the concentra- sensitivity and specificity of HGF and VEGF for discrimi- tions of these molecules increased. To compare these nating PD from PR plus SD were determined using the results with those for patients with a known EGFR status cutoff values according to a previously reported method- in Table 3, we calculated the univariate HRs for the EGFR ology (17). The cutoff values for HGF and VEGF for dis- status (wild-type versus mutant) in the subset of patients criminating PD from PR plus SD were 1,228 pg/mL and with a known EGFR status. These HRs were 3.49 [95% 1,187 pg/mL, respectively. The sensitivity and specificity confidence interval (95% CI), 1.76-6.92; P = 0.0004] of HGF for discriminating PD from PR plus SD were and 3.32 (95% CI, 1.52-7.24; P = 0.0026) for PFS and 0.848 and 0.677, and those for VEGF were 0.788 and OS, respectively. 0.710, respectively. Multivariate analysis stratified according to EGFR Univariate analysis of clinical molecular factors for mutation status for PFS and OS PFS and OS The purpose of this study was to investigate novel mar- The numbers of observed events were 85 cases for PFS kers correlated with the response to EGFR-TKI treatment in- and 70 cases for OS. The median PFS and OS were 4.0 and dependently of the EGFR status. However, the EGFR status 8.9 months, respectively. Among the clinical factors that (wild-type/mutant/unknown) did not satisfy the assump- were examined, a male gender, a poor PS, and a positive tion of proportional hazards in our data. Hence, we smoking history were significantly related with a poor PFS adopted a stratified model, and the multivariate Cox anal- and OS (Table 3). Regarding the serum concentrations of yses always included the EGFR status as a stratification fac- the molecules, higher concentrations of HGF, HB-EGF, tor when estimating the adjusted HRs (ref. 18; Table 4). TnC, and VEGF were significantly associated with a shorter Gender and PS remained statistically significant at a level

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Table 3. Univariate analysis of clinical molecular factors for progression-free and overall survival (Cont'd)

EGFR status known (n = 43) Progression-free survival Overall survival HR (95% CI) P HR (95% CI) P

0.73 (0.36-1.47) 0.37 1.01 (0.47-2.16) 0.99 1.86 (0.94-3.69) 0.07 1.78 (0.84-3.76) 0.13 1.59 (0.74-3.44) 0.2365 2.90 (1.26-6.66) 0.0123 0.66 (0.25-1.72) 0.39 1.85 (0.55-6.15) 0.32 2.38 (1.17-4.87) 0.0174 3.01 (1.31-6.93) 0.0096 1.22 (0.75-1.98) 0.42 1.46 (0.79-2.69) 0.23 1.25 (0.52-2.98) 0.62 1.38 (0.50-3.83) 0.54 1.30 (0.81-2.07) 0.277 1.64 (0.89-3.01) 0.11 11.71 (3.78-36.3) <0.0001 18.17 (4.93-67.0) <0.0001 1.22 (0.79-1.89) 0.38 1.58 (0.84-2.99) 0.16 1.21 (0.87-1.68) 0.25 1.34 (0.92-1.96) 0.12 1.55 (1.05-2.28) 0.0275 1.89 (1.21-2.96) 0.0055 3.03 (1.63-5.62) 0.0005 3.19 (1.65-6.17) 0.0006

NOTE: Univariate analysis was done for all the patients and in a subset of patients with a known EGFR mutation status. Log- transformed values are used for all the molecules. of 0.05 in a multivariate model that included the three was highly correlated with gender (P < 0.0001, Fisher's clinical variables with a small P value (<0.20) in a univariate exact test). Thus, we fixed gender and PS in the Cox model analysis. Smoking status was no longer significant (P = 0.46 and identified significant molecules by backward selection and P = 0.40 for PFS and OS, respectively) because it with P ≥ 0.05 as a removal criterion. Table 4 shows the final

Fig. 2. Kaplan-Meier curves for PFS and OS. Patients were divided into four groups according to the quartile values of each molecule. For HGF (A), red group, patients with <1,061 pg/mL; yellow, with 1,061 to 1,231 pg/mL; green, with 1,232 to 1,521 pg/mL; blue, with >1,522 pg/mL. For VEGF (B), red group, patients with <700 pg/mL; yellow, with 700 to 1,115 pg/mL; green, with 1,116 to 1,769 pg/mL; blue, with >1,769 pg/mL.

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Table 4. Final multivariate model for progression-free survival and overall survival

Progression-free survival Overall survival HR (95% CI) P HR (95% CI) P

Gender Male vs. Female 1.29 (0.76-2.20) 0.34 1.92 (1.06-3.47) 0.0303 PS 2-4 vs. 0-1 0.61 (0.34-1.09) 0.10 1.55 (0.87-2.75) 0.14 HGF 6.31 (2.60-15.3) <0.0001 4.01 (2.20-7.32) <0.0001 VEGF 2.01 (1.14-3.57) 0.0165

NOTE: Gender and PS are fixed in the model. Molecular markers were then selected using the backward selection procedure with a removal probability of 0.05. In all the steps, a Cox model stratified according to the EGFR status (wild-type/mutant/unknown) was applied. Log-transformed values are used for all the molecules.

model using this procedure. HGF (HR, 6.31; 95% CI, 2.60- established predictor of poor prognosis. Ishikawa et al. have 15.3; P < 0.0001) and VEGF (HR, 2.01; 95% CI, 1.14-3.57; shown that, besides HGF, amphiregulin and TGF-α are pre- P = 0.0165) were significant for PFS, whereas only HGF dictors of a poor response to gefitinib in EGFR status- (HR, 4.01; 95% CI, 2.20-7.32; P < 0.0001) was significant unknown advanced non–small cell lung cancer (17). for OS; a high concentration of HGF showed a shorter Although we did not obtain similar results, these molecules PFS and OS independently of the clinical variables of EGFR are expected to be noninvasive predictive biomarkers. status, gender, and PS (Table 4). In the final model, no On the other hand, few reports have examined the predic- interaction was shown between the EGFR status and tive value of HGF with regard to the clinical outcomes of HGF (P = 0.84 and P = 0.20 for PFS and OS, respectively). chemotherapy or molecular-targeting drugs. A recent study The results shown in Table 4 were also stable in analyses of showed that the pretreatment HGF concentrations in the subsetsofpatientswithaknownEGFRstatusaswellas peripheral blood plasma as well as in the bone marrow patients with wild-type EGFR (data not shown). plasma of patients who achieved a complete or very good partial response were significantly lower than those Discussion in patients who had a partial or worse response (28). In this study, we showed, for the first time, that a high pre- HGF was identified as a natural ligand of the MET recep- treatment serum HGF level was associated with poor tor and belongs to the plasminogen family (19). It contains clinical outcomes, including tumor response and survival a hairpin loop followed by four kringle domains flanked by time, in patients treated with EGFR-TKIs. The robust as- an activation portion and a serine protease domain devoid sociation of this parameter with outcome regardless of of proteolytic activity (20). In cancer cells, activation of the the EGFR mutation status clearly suggests that the serum Met receptor increases invasion and metastasis, and allows HGF level could be useful for predicting the response to the survival of cancer cells in the bloodstream in the ab- EGFR-TKI treatment on an individual basis. The direct sence of anchorage (20). In addition, HGF is well known sequencing for EGFR mutations could have produced as a potent angiogenic cytokine, and Met activation can false-negative results, presenting a bias for the relevance modify the microenvironment to facilitate cancer progres- of HGF in patients with supposed wild-type EGFR. sion (21). Therefore, HGF-MET signaling is regarded as an We plan to evaluate EGFR mutations using a highly oncogenic signaling pathway, and intensive therapeutic ap- sensitive detection method in a future study. proaches focusing on this signaling pathway are ongoing in Although we do not have any definitive biological data the field of cancer treatment (22). to address the question of why a high pretreatment se- Meanwhile, a high serum HGF concentration has been rum HGF level is associated with a poor clinical outcome associated with a poor prognosis in many malignant neo- after EGFR-TKI treatment, several studies are worth not- plastic diseases, including colorectal, esophageal, gastric, ing. Engelman et al. showed that the amplification of and prostate cancer, as well as malignant myeloma (23– MET causes gefitinib resistance by driving the ERBB3 25). Where cancer treatment is concerned, high peripheral (HER3)-dependent activation of phosphoinositide 3- and portal HGF serum levels are related to a poor prognosis kinase, and they proposed that MET amplification may after hepatic resection in hepatocellular carcinoma (HCC) promote drug resistance in other ERBB-driven cancers patients (26). The HGF level is also elevated in patients with (29). Yano et al. clearly showed that HGF-mediated myeloma, and patients with higher HGF levels tend to have MET activation is involved in gefitinib resistance in lung a poorer prognosis; furthermore, treatment with high-dose adenocarcinoma with EGFR-activating mutations (30). chemotherapy reduced the serum HGF level in the majority In addition, a recent study has clearly shown that HGF of these patients (27). The above-mentioned evidence accelerates the development of MET amplification both suggests that a high serum HGF level is a relatively well- in vitro and in vivo, mediating the EGFR kinase inhibitor

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Serum HGF and EGFR-TKIs

resistance caused by either MET amplification or auto- Disclosure of Potential Conflicts of Interest crine HGF production (31). These studies indicate that the activation of HGF-MET signaling confers resistance No potential conflicts of interest were disclosed. to EGFR-TKIs. Therefore, lung cancer cells producing high amounts of HGF might mediate drug resistance Acknowledgments to EGFR-TKIs, leading to poor treatment outcomes. In this study, a multivariate analysis revealed that the We thank Ms. Tomoko Kitayama for technical assistance. serum HGF level was independently associated with a poor treatment outcome. This finding indicates the possi- Grant Support bility of using the serum HGF level to refine the indica- tions for patients who are likely to respond to EGFR-TKI Third-Term Comprehensive 10-Year Strategy for Cancer Control, a treatment. In particular, patients with wild-type EGFR are Grant-in-Aid for Scientific Research, the Program for the Promotion of Fun- considered to be less sensitive to EGFR-TKIs, but our re- damental Studies in Health Sciences of the National Institute of Biomedical Innovation (NiBio), a Grant-in-Aid for Cancer Research (H20-20-9) from sults might allow the identification of a selective subgroup the Ministry of Health, Labour and Welfare and a Grant-in-Aid for Scientific of these patients who might actually benefit from this Research from the Ministry of Education, Culture, Sports, Science and Tech- nology of Japan (19209018). treatment. When used in combination with EGFR muta- The costs of publication of this article were defrayed in part by the tion status, the serum HGF level might increase the clinical payment of page charges. This article must therefore be hereby marked benefit of EGFR-TKIs by allowing the further individuali- advertisement in accordance with 18 U.S.C. Section 1734 solely to zation of this treatment. We plan to conduct a prospective indicate this fact. study to validate the ability of the serum HGF level to Received 02/16/2010; revised 06/29/2010; accepted 07/11/2010; predict the response to EGFR-TKI treatment. published OnlineFirst 08/02/2010.

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4624 Clin Cancer Res; 16(18) September 15, 2010 Clinical Cancer Research

Impact of Serum Hepatocyte Growth Factor on Treatment Response to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients with Non−Small Cell Lung Adenocarcinoma

Kazuo Kasahara, Tokuzo Arao, Kazuko Sakai, et al.

Clin Cancer Res 2010;16:4616-4624. Published OnlineFirst August 2, 2010.

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