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Keywords:

  • lung adenocarcinoma;
  • driver mutation;
  • multimutational profiling;
  • molecular-targeted therapeutics;
  • personalized cancer medicine

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

BACKGROUND

Integration of mutational profiling to identify driver genetic alterations in a clinical setting is necessary to facilitate personalized lung cancer medicine. A tumor genotyping panel was developed and the Shizuoka Lung Cancer Mutation Study was initiated as a prospective tumor genotyping study. This study reports the frequency of driver genetic alterations in Japanese lung adenocarcinoma patients, and clinicopathologic correlations with each genotype.

METHODS

Between July 2011 and January 2013, 411 lung adenocarcinoma patients admitted to the Shizuoka Cancer Center were included in this study with their written informed consent. Surgically resected tissues, tumor biopsies, and/or body cavity fluids were collected and tested for 23 hotspot sites of driver mutations in 9 genes (EGFR, KRAS, BRAF, PIK3CA, NRAS, MEK1, AKT1, PTEN, and HER2), gene amplifications in 5 genes (EGFR, MET, PIK3CA, FGFR1, and FGFR2), and ALK, ROS1, and RET fusions.

RESULTS

Genetic alterations were detected in 54.3% (223 of 411) of all patients. The most common genetic alterations detected in this study were EGFR mutations (35.0%) followed by KRAS mutations (8.5%) and ALK fusions (5.0%). Concurrent genetic alterations were detected in 22 patients (5.4%), and EGFR mutations were observed in 16 patients as the most common partner for concurrent genetic alteration. Significantly more concurrent genetic alterations were observed in older patients.

CONCLUSIONS

This is one of the largest reports of a prospective tumor genotyping study on Japanese patients with adenocarcinoma. These data suggest that mutational profiling data using a multimutational testing platform would be valuable for expanding the range of molecular-targeted therapeutics in lung cancer. Cancer 2014;120:1471–1481. © 2014 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Over the last decade, genetic alterations in oncogenic driver genes such as KRAS, EGFR, HER2, PIK3CA, ALK, MET, AKT1, MEK1, BRAF, ROS1, RET, and NRAS have been identified in lung adenocarcinoma, the most common histological type of lung cancer.[1-3] These findings have added a new dimension to the classification of lung adenocarcinoma, which now consists of molecular subgroups based on the mutational profile of the tumor, which is often used as a companion diagnostic tool for selecting molecular-targeted therapeutics.[1, 4, 5]

In particular, the clinical use of epidermal growth factor receptor (EGFR)- and anaplastic lymphoma kinase (ALK)-targeted therapies has led to a paradigm shift in lung adenocarcinoma treatment.[6] EGFR-activating mutations are valid predictive biomarkers to identify patients who are likely to benefit from the EGFR-tyrosine kinase inhibitors (TKIs) gefitinib and erlotinib, which show response rates (RR) of 58% to 83% and progression-free survival times of 9 to 13 months.[6] Similarly, the ALK-TKI crizotinib shows promising clinical benefits, with an RR in excess of 60% and a progression-free survival of 8 to 10 months in ALK fusion–positive non–small cell lung cancer (NSCLC) patients.[6-8] The prevalence of those targetable oncogenic driver genetic alterations has been intensively investigated.[9-14] EGFR-activating mutations are found in 30% to 40% and 10% to 20% of patients with NSCLC in East Asia and North America, respectively, demonstrating that ethnicity plays a role in the prevalence of oncogenic mutations in this gene.[4] On the contrary, no clear ethnic difference has been recognized in the prevalence of ALK-positive NSCLC, which accounts for 1% to 7% of all NSCLC cases.[4] There are a number of ongoing clinical trials to assess the clinical efficacy of novel molecular-targeted therapeutics against tumors with oncogenic genetic alterations in genes such as KRAS, BRAF, PIK3CA, MEK1, HER2, ROS1, and RET.[1-3] Therefore, the integration of multimutational profiling into lung cancer clinical studies to determine the genotype of driver genetic alterations is necessary to further validate the effectiveness of molecular-targeted therapies and to assign patients to appropriate treatments.[4, 5, 9, 10, 13] In addition, the impact of ethnic differences on the prevalence of uncommon genetic alterations should be investigated and elucidated.

We developed a tumor genotyping panel to screen patients with lung cancer for genetic alterations relevant to novel molecular-targeted therapeutics in ongoing clinical trials.[1-3, 15] (Supporting Table 1; see online supporting information). Multimutational analysis was implemented in the Shizuoka Lung Cancer Mutation Study, which is a new, prospective tumor genotyping study for patients with thoracic malignancies who have been admitted to Shizuoka Cancer Center. This is the first report on a prospective tumor genotyping study in Japan, which describes the frequency of driver genetic alterations in 411 Japanese patients with lung adenocarcinoma and clinicopathologic correlations with each genotype.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Patients and Tissues

This study was approved by the Institutional Review Board of the Shizuoka Cancer Center (Ref #22-34-22-1-7). Between July 2011 and January 2013, written informed consent was obtained from 845 consecutive patients with a pathological diagnosis of lung cancer who were admitted to Shizuoka Cancer Center. Surgically resected tissue specimens were macrodissected by pathologists to enrich the tumor content. Tumor biopsy specimens containing 10% or more tumor content evaluated by hematoxylin-eosin staining were used for this study. Consequently, specimens from 411 patients with lung adenocarcinoma were considered adequate for mutational testing. Surgically resected tissues and tumor biopsies were snap-frozen on dry ice immediately after resection and stored at −80°C until use. Formalin-fixed paraffin-embedded (FFPE) specimens were sectioned with a thickness of 10 μm. Cells from body-cavity fluids (pleural or pericardial effusions) were isolated by density-gradient centrifugation with Lymphocyte Separation Media (MP Biomedicals, Irvine, Calif) and stored at −80°C to be used later. All the clinicopathologic information, including smoking history, used for this study was retrieved from the medical records of the patients.

Multimutational Profiling

Tumor genotyping panel (Supporting Table 1) was designed to assess 23 hotspot sites of genetic alterations in 9 genes (EGFR, KRAS, BRAF, PIK3CA, NRAS, MEK1, AKT1, PTEN, and HER2), gene amplifications in EGFR, MET, PIK3CA, FGFR1, and FGFR2, and ALK, ROS1, and RET fusions using pyrosequencing plus capillary electrophoresis, quantitative polymerase chain reaction (PCR), and reverse transcription PCR, respectively. These genetic alterations were selected by reference to articles listed in Supporting Table 1. Immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH) were also used for the detection of ALK fusions. Detailed methods are described in the Supporting Methods (see online supporting information).

Statistical Analysis

Associations between each genotype and clinical characteristics were analyzed by a 2-sided Student t test and Fisher's exact test with GraphPad Prism 5 (GraphPad Software, Inc., San Diego, Calif), and by multivariate logistic regression analysis, which was done with JMP 9.0 (SAS Institute, Cary, NC). The significance level was set at P < .05.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Patient Characteristics

Between July 2011 and January 2013, 502 adequate tissue samples for tumor genotyping were obtained from 411 lung adenocarcinoma patients, with 73 patients having multiple samples (Supporting Table 2). Table 1 and Supporting Table 3 show the summary of clinical characteristics of the patients. Patients had a median age of 68 years old (range = 29-89 years) and 38% were female. Stages I, II, III and IV were present in 25%, 7%, 21%, and 46%, respectively. One hundred thirty-two patients (32%) had never smoked before (never-smokers). Significant differences between females and males were observed in stage IA, IIIA, and IIIB, as well as heavy smokers and never-smokers, but not according to age, or in stage IB, IIA, IIB, and IV, and light smokers (Supporting Table 3).

Table 1. Demographics of Patients With Common Genetic Alterations
CharacteristicOverall GroupEGFRKRASALK Fusions aPIK3CAEGFR AmpMET AmpHER2 InsertionPIK3CA AmpConcurrent Alterations
  1. Numbers in parentheses indicate percentages. Data in bold indicate statistically significant differences between genetic alteration-positive and wild-type genes. (*P < .05; **P < .01; ***P < .001; ****P < .0001).

  2. NS indicates not statistically significant.

  3. a

    ALK fusion genes were tested in 238 patients.

  4. b

    Fisher's exact test.

  5. c

    Two-sided Student t test.

  6. d

    No information about smoking history was available in 2 patients.

  7. e

    Heavy smoker, Brinkman index ≧600.

  8. f

    Light smoker, Brinkman index <600.

Proportion411(100)144(35)35(9)12(5)11(3)10(2)9(2)7(2)7(2)22(5)
Sex
Female158(38)84(58)8(23)3(25)2(18)4(40)3(33)3(43)2(29)10(45)
Male253(62)60(42)27(77)9(75)9(82)6(60)6(67)4(57)5(71)12(55)
P value b  <.0001NSNSNSNSNSNSNSNS
Age, y
Median (range) c68(29-89)69(33-89) *69(33-80)52(29-85) **71(55-82)71(57-85)71(40-79)70(58-82)71(50-74)71(57-85) *
>70153(37)60(42)15(43)1(8)6(55)5(50)4(44)3(43)4(57)13(59)
≦70258(63)84(58)20(57)11(92)5(45)5(50)5(56)4(57)3(43)9(41)
P value b  NSNS.0344NSNSNSNSNS.0399
Stage
IA62(15)29(20)8(23)0 1(9)1(10)0 1(14)0 1(5)
IB42(10)19(13)6(17)0 1(9)3(30)0 4(57)1(14)2(9)
IIA21(5)8(6)1(3)1(8)0 1(10)2(22)0 2(29)3(14)
IIB9(2)2(1)1(3)0 1(9)0 0 0 0 1(5)
IIIA50(12)11(8)4(11)4(33)2(18)1(10)1(11)1(14)3(43)4(18)
IIIB38(9)7(5)3(9)2(17)0 0 1(11)0 0 0 
IV189(46)68(47)12(34)5(42)6(55)4(40)5(56)1(14)1(14)11(50)
Early (I-II) vs Advanced (III-IV)P value b  .0157NS.0308NSNSNS.0399NSNS
Smoking status d
Heavy smoker e179(44)29(20)24(69)3(25)6(55)3(30)5(56)1(14)4(57)8(36)
Light smoker f98(24)38(26)7(20)5(42)3(27)3(30)2(22)1(14)0 7(32)
Never-smoker132(32)77(53)3(9)4(33)1(9)4(40)2(22)5(71)3(43)7(32)
Smoker vs never-smoker P value b  <.0001.0017NSNSNSNS.0381NSNS
Brinkman Index
Median (range) c440(0-3900)0 (0-3000) ****820 (0-2400) ***178 (0-820) **820 (0-2280)185 (0-2080)700 (0-3000)0 (0-800) *660 (0-1200)275 (0-3000)

Results of Multimutational Profiling

Genetic alterations were detected in 54.3% of all patients (Fig. 1A; Supporting Table 4). The most common genetic alterations were EGFR mutations (35.0%), followed by KRAS mutations (8.5%) and ALK fusions (5.0%), consistent with previous studies.[16] Mutation frequencies in all patients are shown in Figure 1A and Supporting Table 4. ALK fusions, HER2 insertions, MEK1 mutations, KIF5B-RET, and CD74-ROS1 were mutually exclusive with other genetic alterations (Fig. 1B). There was no significant difference in the detection rate of genetic alterations among fresh-frozen tissues, FFPE tissues, and cells extracted from body cavity fluids (P = .0940; data not shown).

image

Figure 1. (A) Relative frequency of genetic alterations is shown for 411 patients with lung adenocarcinoma. Genetic alterations were detected in 54.3% (223/411) of all patients. *ALK fusions were tested in 238 patients. ROS1 and RET fusions were tested in 182 patients for whom fresh frozen tissues and/or the body cavity fluids were available. (B) Concurrent genetic alterations were identified in 22 patients (5.4%). The dimension of each circle is proportionate to the frequency of each genetic alteration and concurrent genetic alteration. Lines that connect the circles indicate the identity of concurrent genetic alterations.

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Concurrent Genetic Alterations

Concurrent genetic alterations were identified in 22 patients. EGFR mutations were observed in 16 patients as the most common partner for concurrent genetic alterations, (Fig. 1B; Supporting Table 5), indicating that EGFR mutations were not necessarily mutually exclusive with other driver genetic alterations. Among 18 patients with PIK3CA genetic alterations, which included 11 mutations and 7 amplifications, 11 patients (61%) had concurrent genetic alterations with other mutations in EGFR, KRAS, and MET (Fig. 1B; Supporting Table 5).

Clinicopathologic Correlations With Genotype

Clinicopathologic associations with genotype are shown in Tables 1 and 2. Patients with EGFR mutations were significantly more likely to be female. ALK fusion-positive patients were significantly younger than wild-type ALK patients (median, 52 versus 68; P = .0052), and this fusion was associated with advanced stage of disease. HER2 insertions correlated with early-stage lung cancer. Never-smokers were significantly associated with EGFR mutations and HER2 insertions, whereas a significant correlation between smoking history and KRAS mutations was observed. These clinicopathologic correlations with each genotype were confirmed by multivariate logistic regression analysis (Table 2) and were consistent with previous reports.[9, 13, 17, 18] The number of concurrent genetic alterations was found to significantly increase with age (median, 71 versus 68, P = .0450, Table 1), and patients > 70 years of age had more concurrent genetic alterations than those who were 70 years of age or younger (Tables 1 and 2). Figure 2 represents the mutational profile based on smoking status. These profiles reflect the associations between genotype, especially EGFR and KRAS, and smoking status. Genetic alterations were detected in 40%, 58%, and 71% of heavy, light, and never-smokers, respectively, suggesting that never-smokers could potentially benefit from treatment with molecular-targeted therapies compared with smokers, especially heavy smokers.

Table 2. Evaluation of Association Between Genotype and Clinicopathological Characteristics by Logistic Regression Analysis
Characteristic EGFRKRASALK FusionsaHER2 InsertionConcurrent Alterations
  1. Data in bold indicate statistically significant differences (P < .05).

  2. Abbreviations: CI, confidence interval; NS, not statistically significant; OR, odds ratio.

  3. a

    ALK fusion genes were tested in 238 patients.

Sex P value0.0156NSNSNSNS
(female/male)OR [95% CI]1.99 [1.14-3.45]    
AgeP valueNSNS0.0249NS0.0223
(>70/≦70)OR [95% CI]  0.15 [0.01-0.82] 2.81 [1.16-7.13]
StageP valueNSNS0.02350.0371NS
(early/advanced)OR [95% CI]  0.15 [0.01-0.80]5.54 [1.11-41.14] 
Smoking statusP value0.00040.0036NS0.0101NS
(smoker/never-smoker)OR [95% CI]0.36 [0.21-0.63]6.26 [1.76-29.89] 0.07 [0.01-0.52] 
image

Figure 2. Relative frequency of genetic alterations is shown, based on smoking status in (A) heavy, (B) light, and (C) never-smokers. Genetic alterations were detected in 71 (39.7%) heavy smokers (N = 179), 57 (58.2%) light smokers (N = 98), and 93 (70.5%) never-smokers (N = 132). *ALK fusions were tested in 238 patients. †ROS1 and RET fusions were tested in 182 patients.

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A Case With Multiple Genetic Alterations Without a Smoking History

Our study included a 74-year-old male never-smoker patient with postoperative recurrence who harbored 5 different genetic alterations (Fig. 3A-C). At recurrence, the patient was initially wild-type EGFR, as determined by central laboratory testing. The patient then went on to receive a series of chemotherapeutic agents (Supporting Table 6). Tumor samples were tested for multiple genetic alterations upon his entry into this study and EGFR exon 19 deletion, AKT1 mutation, and PIK3CA amplification were identified (Fig. 3A-C). EGFR exon 19 deletion, EGFR amplification, and FGFR1 amplification were also detected using tumor cells isolated form pleural effusion (Fig. 3A-C). After the failure of fourth-line eribulin treatment, the patient was given erlotinib as fifth-line treatment and showed durable responses in lung and liver tumors (Fig. 3D; Supporting Table 6). What should be emphasized in this particular case is that if the patient fails erlotinib treatment, he has opportunities to enter clinical trials with anticancer agents that target other mutant genes present in the tumor, which was one of the pivotal aims of our study.

image

Figure 3. Results of mutational testing in a 74-year-old male never-smoker patient with lung adenocarcinoma. (A) EGFR exon 19 deletion was assessed by capillary electrophoresis. (B) AKT1 mutation was detected with pyrosequencing. (C) Gene amplifications in EGFR, PIK3CA, and FGFR1 were examined by qPCR using DNA extracted from surgically resected tissues (FFPE) and cells isolated from pleural effusion (PE). Each value is the average of triplicate measurements, and each error bar indicates the standard deviation (SD) in triplicate experiments. ND indicates “not detected.” Lung adenocarcinoma cell lines A549 and H1975, which do not show amplifications in these genes (data not shown), were used as negative controls. (D) Computed tomographic (CT) scans of chest and abdomen were conducted at baseline and after 6 months of erlotinib therapy, and show significant shrinkage because of treatment.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Tumor mutational profiling is critically needed for the facilitation of personalized medicine for lung adenocarcinoma, as well as for the development of molecular-targeted therapeutics. To address these needs, considerable efforts have been made to determine the prevalence of driver genetic alterations in lung adenocarcinoma. Supporting Table 7 exhibits the comparison between the results of the present study and those of previous reports.[10-13] Kohno et al[11] recently reported the tumor mutational profile in Japanese lung adenocarcinoma patients. Comparatively, the overall detection rate of genetic alterations in our study was lower (48% in the current study versus 70% in Kohno et al[11]), especially in EGFR mutations (35% versus 53%). One of the most likely reasons for this difference is that we had significantly more smokers in our study (68% versus 51%, P < .0001), which probably reflects the characteristics of our local patient cohort. Importantly, there was no significant difference in the overall detection rate or frequency of EGFR mutations in never-smoker patients between these studies, which supports our hypothesis that differences in mutation rates were affected by the smoking status of the study cohort. Li et al[12] reported the mutational profile of Chinese never-smokers with lung adenocarcinoma and showed that 89% of patients had driver genetic alterations, which is a markedly high detection rate compared to our results. This may be due to their use of only archival, surgically resected tissues, on top of the fact that tissues were from an enriched cohort such as never-smokers.[12] There was no significant difference observed in the overall detection rate of mutations in surgically resected tissues from never-smoker patients between our study and Li et al[12] (data not shown). As stated above, our results appear to be different from previous Asian reports at first glance. However, our results on the detection of genetic alterations clearly hold up when adjusted based on the study cohort used for previous studies, indicating that our study was successful in reflecting the nature of the local patient population.

We also compared our data with 2 reports on prospective tumor genotyping studies conducted in North America[10, 13] (Supporting Table 7). Our study and Johnson et al[10] had the same proportion of never-smoker patients (68% versus 66%); therefore, significant differences seen in the frequencies of EGFR and KRAS mutations between the 2 studies were certainly due to ethnic differences within the study cohorts.[10] Similar discrepancies in EGFR and KRAS mutations were also found between our study and Sequist et al.[13] There was no significant difference between our study and Johnson et al in overall detection rate (52% versus 54%, P = 0.4272).[10] BRAF mutations were also detected less frequently in our study (0.7% versus 1.8% in Sequist et al[13]; 2.1% in Johnson et al[10]). BRAF mutations have been reported to occur in approximately 3% of lung adenocarcinomas in North America.[19] In Chinese lung adenocarcinomas, BRAF mutations were detected in 3% of patients with a smoking history,[20] but were not found in never-smoker patients.[21] In our study, BRAF mutations were also detected only in patients with a smoking history (data not shown). Therefore, further investigation is needed to explore the association between BRAF mutations, smoking status, and ethnic differences in lung adenocarcinoma. The identification of BRAF mutations in lung adenocarcinoma is also important because patients with BRAF genetic alterations are highly likely to benefit from BRAF inhibitors.[22, 23]

We identified 48 patients with uncommon genetic alterations in PIK3CA, HER2, BRAF, NRAS, MEK1, AKT1, MET, FGFR1, ROS1, and RET oncogenes. Clinical trials of novel anticancer agents targeting these genetic alterations are in progress.[1-3] Promising compounds for HER2 insertions (detected in 1.7% of patients in our study; Fig. 1) are irreversible EGFR/HER2 TKIs such as afatinib, neratinib, and dacomitinib. In a phase 2 trial, afatinib alone showed promising activity in 2 of 5 patients with HER2-mutant lung adenocarcinoma.[24] Approved TKIs such as vandetanib, sunitinib, and sorafenib show activity against RET fusions,[11] including mutations that were detected in 1.1% of our study cohort (Fig. 1). As well, a multi-institutional phase 2 clinical trial with vandetanib for RET fusion-positive patients is ongoing in Japan (UMIN000010095).[25] In order to enroll a sufficient number of patients for clinical trials of molecular-targeted agents against uncommon genetic alterations, multimutational profiling in routine clinical practice is crucial. As more molecular-targeted therapies are developed, there will be a need for more comprehensive and sensitive genotyping technologies with higher throughput to determine genotype using a limited amount of tissue. Next-generation sequencing (NGS) technology can allow us to further pursue this direction,[4] and we are currently working with this platform to identify mutations in NSCLC.[26]

Concurrent genetic alterations have been reported in 3% to 9% of lung adenocarcinoma by other groups.[10, 14] Chaft et al[27] reported that 70% of lung adenocarcinoma patients with PIK3CA mutations in North America had coexisting genetic alterations, suggesting that PIK3CA mutations are one of the most common partners for concurrent genetic alterations regardless of ethnicity. However, appropriate therapeutic approaches for patients with coexisting oncogenic mutations have not been established. Our study included a 74-year-old male never-smoker patient with 5 different genetic alterations, including EGFR mutations, who showed durable responses to erlotinib treatment (Fig. 3D). This may be an unusual case, because patients with coexistence of EGFR mutations and ALK fusions do not necessarily respond to treatment with EGFR-TKIs.[28] These differential responses to EGFR-TKIs in patients with concurrent genetic alterations including EGFR mutation remain elusive, and presumably, some tumors may be driven by genetic alterations other than EGFR-activating mutations. In order to investigate the molecular and biological features of tumors with concurrent genetic alterations and to develop appropriate treatments, multimutational testing, combined with more comprehensive testing platforms such as next-generation sequencing technology, should be incorporated. Routine patient screening with these technologies would greatly facilitate the assessment of tumor heterogeneity.

There are limitations in this study. ROS1 and RET fusions were tested only with reverse transcription PCR in 182 patients for whom fresh frozen tissues and/or the body cavity fluids were available. For future studies, implementation of FISH for detection of these fusions in FFPE tissues will be necessary. Detection of gene amplification may also require consideration of incorporating FISH for future studies.

To our knowledge, this is one of the largest tumor genotyping studies in lung adenocarcinoma conducted as a prospective single-institution trial in East Asia.[5] Our results revealed the frequency of genetic alterations in lung adenocarcinoma and identified clinicopathologic correlations with genotype, which reflect current practices in lung cancer clinics compared with reported retrospective studies.[11, 12] We anticipate that multimutational analysis in lung cancer clinics will be crucial for the expansion of the range of molecular-targeted therapeutics available to treat this disease.

FUNDING SUPPORT

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

This work was supported by the Japanese Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers 24591186 (N.Y.) and 24501363 (Y.K.).

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

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cncr28604-sup-0001-suppinfo.docx21KSupplementary Information
cncr28604-sup-0002-supptables.docx58KSupplementary Information Tables.

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