Skip to main content
Diagnostic Pathology logoLink to Diagnostic Pathology
. 2019 Feb 11;14:18. doi: 10.1186/s13000-019-0789-1

Analysis of the frequency of oncogenic driver mutations and correlation with clinicopathological characteristics in patients with lung adenocarcinoma from Northeastern Switzerland

Alexandra Grosse 1, Claudia Grosse 2,, Markus Rechsteiner 3, Alex Soltermann 1
PMCID: PMC6371584  PMID: 30744664

Abstract

Background

Molecular testing of lung adenocarcinoma for oncogenic driver mutations has become standard in pathology practice. The aim of the study was to analyze the EGFR, KRAS, ALK, RET, ROS1, BRAF, ERBB2, MET and PIK3CA mutational status in a representative cohort of Swiss patients with lung adenocarcinoma and to correlate the mutational status with clinicopathological patient characteristics.

Methods

All patients who underwent molecular testing of newly diagnosed lung adenocarcinoma during a 4-year period (2014–2018) were included. Molecular analyses were performed with Sanger sequencing (n = 158) and next generation sequencing (n = 311). ALK, ROS1 and RET fusion gene analyses were also performed with fluorescence in situ hybridization and immunohistochemistry/immunocytochemistry. Demographic and clinical data were obtained from the medical records.

Results

Of 469 patients with informative EGFR mutation analyses, 90 (19.2%) had EGFR mutations. KRAS mutations were present in 33.9% of the patients, while 6.0% of patients showed ALK rearrangement. BRAF, ERBB2, MET and PIK3CA mutations and ROS1 and RET rearrangements were found in 2.6%, 1.9%, 1.9%, 1.5%, 1.7% and 0.8% of the patients, respectively. EGFR mutation was significantly associated with female gender and never smoking status. ALK translocations were more frequent in never smokers, while KRAS mutations were more commonly found in ever smokers. The association between KRAS mutational status and female gender was statistically significant only on multivariate analysis after adjusting for smoking.

Conclusion

The EGFR mutation rate in the current study is among the higher previously reported mutation rates, while the frequencies of KRAS, BRAF, ERBB2 and PIK3CA mutations and ALK, ROS1 and RET rearrangements are similar to the results of previous reports. EGFR and KRAS mutations were significantly associated with gender and smoking. ALK rearrangements showed a significant association with smoking status alone.

Electronic supplementary material

The online version of this article (10.1186/s13000-019-0789-1) contains supplementary material, which is available to authorized users.

Keywords: Lung adenocarcinoma, EGFR, KRAS, ALK, RET, ROS1, BRAF, ERBB2, MET, PIK3CA, Non-small cell lung cancer

Background

Lung cancer is the leading cause of cancer-related mortality worldwide [1]. Non-small cell lung cancer (NSCLC) is the most common histological subtype of lung cancer, accounting for approximately 80–85% of lung cancer cases [2, 3]. Molecular testing for epidermal growth factor receptor gene (EGFR) mutations and ALK receptor tyrosine kinase (ALK) translocations has become the evidence-based standard of care for the management of advanced NSCLC. In the past, pivotal clinical trials have demonstrated clinical benefit from targeting EGFR mutations and ALK translocations, and currently a number of effective EGFR and ALK inhibitors are available for targeted therapy of NSCLC harboring the relevant aberrations [4]. More recently, new molecular profiling technologies have permitted the identification of other potential oncogenic drivers including mutations in the KRAS proto-oncogene (KRAS), B-Raf proto-oncogene (BRAF), erb-b2 receptor tyrosine kinase 2 gene (ERBB2), MET proto-oncogene (MET) and phosphatidylinositol-3 kinase catalytic subunit alpha gene (PIK3CA) as well as ROS proto-oncogene 1 (ROS1) and ret proto-oncogene (RET) rearrangements [4]. While a number of studies have already evaluated the frequencies of these genetic alterations in NSCLC patients from different countries, information on the prevalence of oncogenic driver mutations in the Swiss population are scarce and limited to population based epidemiological data derived from cancer registries and molecular test results based exclusively on Sanger sequencing rather than next generation sequencing (NGS) [5, 6].

In Switzerland lung cancer is the most common cause of cancer-related death among men (approximately 2000 deaths per year) and the second most common cause of cancer-related death among women (approximately 1100 deaths per year) [7]. Adenocarcinoma is the predominant histological subtype with distinct molecular features, and incidence rates of lung adenocarcinoma are increasing among both sexes [8, 9]. The aim of the study was to analyze the frequencies of ALK, RET and ROS1 gene rearrangements and EGFR, KRAS, BRAF, ERBB2, MET and PIK3CA mutations in a representative cohort of Swiss patients with lung adenocarcinoma using NGS as testing method in the majority of cases and to correlate the molecular findings with clinicopathological patient characteristics.

Methods

Patients

A total of 475 consecutive patients who underwent molecular testing of newly diagnosed lung adenocarcinoma at the Institute of Pathology and Molecular Pathology, University Hospital Zurich (Zurich, Switzerland), between January 2014 and January 2018, were included in the study, independent of tumor stage. Molecular analyses were performed at the University Hospital Zurich according to National Comprehensive Cancer Network (NCCN) and Swiss Society of Pathology (SSPath) guidelines. Inclusion criteria were histologically and/or cytologically confirmed lung adenocarcinoma, chemotherapy, targeted therapy and radiotherapy naïve, and tissue blocks/cell blocks with adequate tumor cellularity. Exclusion criteria were non-adenocarcinoma histology, previous chemotherapy, targeted therapy or radiotherapy, and insufficient tumor material. Of the initial study population, 469 patients had adequate tumor material for molecular testing, while 6 patients had insufficient tumor samples and were not further evaluated. The results of molecular analysis were recorded for each patient and correlated with demographic and tumor related data such as gender, age, smoking status, clinical stage, and TNM stage (as defined by the Union for International Cancer Control (UICC) TNM classification of malignant tumors, 8th edition [10]). Smoking status was defined as never smokers (< 100 lifetime cigarettes), ex-smokers (≥100 lifetime cigarettes and currently not smoking) and current smokers (≥100 lifetime cigarettes and currently smoking). The cutoff date for data collection was 15 May 2018. The study was approved by the Cantonal Ethics Committee of Zurich (StV-No. 2009/14–0029).

Molecular analysis

Nucleic acids (DNA and RNA) were isolated from formalin-fixed paraffin-embedded (FFPE) tissue blocks or FFPE cell blocks using the Maxwell 16 FFPE Tissue LEV DNA/RNA Purification Kit (Promega, Fitchburg, WI, USA). The obtained nucleic acids were quantified with NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA) and Qubit 2.0 (Thermo Fisher Scientific/Life Technologies, Eugene, OR, USA) using the dsDNA/RNA HS Assay Kit (Thermo Fisher Scientific/Life Technologies, Zug, Switzerland). Mutation analysis was performed using Sanger sequencing (n = 158) or NGS (n = 311). For DNA- and RNA-based NGS, customer panels including the Ion AmpliSeq Colon and Lung Cancer panel 2 (CLP2), Ion AmpliSeq Fusion Lung Cancer Research panel (LFP), and Oncomine DNA panel for Solid Tumors and Fusion Transcripts (Thermo Fisher Scientific/Life Technologies, Carlsbad, California, USA) were applied, as previously described [11, 12]. Briefly, we used the Ion Library Quantitation kit (Thermo Fisher Scientific) for quantification of DNA and RNA libraries, the Ion One Touch 200 Template Kit v2 DL (lately replaced by the Ion Hi-Q Chef Kit and the Ion Chef System) (Thermo Fisher Scientific) for emulsion polymerase chain reaction (PCR) and template preparation, and the Ion Personal Genome Machine 200 Kit v2 (lately replaced by the Ion Personal Genome Machine Hi-Q Sequencing Kit) (Thermo Fisher Scientific) as the sequencing platform. For Sanger sequencing, we used the Illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare Life Sciences, Buckinghamshire, UK) for purification of amplified DNA fragments, the Genetic Analyzer 3130 × 1 (Applied Biosystems, Foster City, CA, USA) for sequencing and the Sequencher 5.1 (Gene Code Corporation, Ann Arbor, MI, USA) for data analysis. ALK and ROS1 immunohistochemistry (IHC)/immunocytochemistry (ICC) was performed on the automated immunostainer DiscoveryUltra (Roche Ventana) using a mouse anti-human ALK monoclonal antibody (clone 5A4, Leica Biosystems) and a rabbit anti-human ROS1 monoclonal antibody (clone D4D6, Cell Signaling Technology). ALK or ROS1 IHC/ICC positive cases were confirmed by fluorescence in situ hybridization (FISH) using the Vysis LSI ALK Dual Color Break Apart Rearrangement Probe (Abbott Molecular, Baar, Switzerland) and the ZytoLight SPEC ROS1 Dual Color Break Apart Probe (Zytovision GmbH, Bremerhaven, Germany). FISH testing for RET rearrangement was performed using the ZytoLight SPEC RET Dual Break Apart Probe (Zytovision GmbH, Bremerhaven, Germany). For each case, a board certified pathologist analyzed 50–100 tumor nuclei. A sample was considered positive, if split signals were detected in ≥15% of tumor nuclei according to the manufacturer’s evaluation guidelines (Abbott Molecular, Des Plaines, IL, USA).

Statistical analysis

Descriptive statistics were employed to describe the patient characteristics of the study cohort. The results are presented as frequencies and percentages for categorical variables and as mean ± standard deviation, median and range for continuous variables. Associations between mutation status and clinicopathological characteristics were tested using univariate and multivariate analyses. Univariate analysis was performed by chi-square test or Fisher exact test for categorical variables and by t test or nonparametric Mann-Whitney test for continuous variables. Multivariate analysis was performed by logistic regression. P-values < 0.05 were considered statistically significant. All statistical analyses were performed using SPSS Statistics software (version 24.0, IBM, Ehningen, Germany).

Results

The diagnosis of lung adenocarcinoma was based on histology (with or without cytology) in 91.7% (430/469) and on cytology alone in 8.3% (39/469) of the patients. Samples submitted for molecular testing were obtained from primary tumors, lymph node metastases or distant metastases in 79.7% (374/469), 10.7% (50/469) and 9.6% (45/469) of the patients, respectively. There were 191 (40.7%) resection specimens, 224 (47.8%) biopsy specimens, 48 (10.2%) fine needle aspiration/bronchial brushing/bronchoalveolar lavage specimens and 6 (1.3%) cell blocks from pleural effusions. Table 1 summarizes the demographic and clinicopathological patient characteristics. The study population consisted of 235 men and 234 women (mean age at diagnosis, 64.1 ± 11.4 years; range, 27–94 years). The majority of patients were ever smokers (current smokers and ex-smokers) (354/469, 75.5%) and had clinical stage IV lung adenocarcinoma (299/469, 63.8%) at diagnosis. Females were more likely to be never smokers than males (70/234, 29.9% vs 45/235, 19.1%, p = 0.007, beta 0.589, OR 1.802, CI 95% 1.174–2.767). Overall 127 patients received targeted treatment. Stage IV patients (both at diagnosis and during follow-up) with EGFR mutation and ALK rearrangement received targeted treatment in 75.4% and 61.9%, respectively. The majority (91.7%) of stage IV patients with EGFR mutation who did not receive targeted therapy were treated with chemotherapy and/or radiotherapy. Likewise, all stage IV patients with ALK translocation who were not treated with targeted therapy received chemotherapy and/or radiotherapy. Median patient follow-up was 17 months (range, 1–52 months). 268/469 (57.1%) patients were alive at the time of last follow-up, including 165/469 (35.2%) patients with stable disease and 103/469 (22.0%) patients with progressive disease. 147/469 (31.3%) patients died of disease during follow-up, and 54/469 (11.5%) patients were lost to follow-up. Median overall survival for the entire study cohort was 38 months.

Table 1.

Patient characteristics

Variable Study population Variable Study population
(n = 469) (n = 469)
Age (years) 64.1 ± 11.4 N stage
Gender N0 117 (24.9)
 Male 235 (50.1) N1 65 (13.9)
 Female 234 (49.9) N2 134 (28.6)
Smoking status N3 153 (32.6)
 Never smokers 115 (24.5) Extrathoracic metastasis/−es 213 (45.4)
 Ex-smokers 160 (34.1) M stage
 Current smokers 194 (41.4) M0 168 (35.8)
Clinical stage M1a 88 (18.8)
 I 34 (7.2) M1b 72 (15.4)
 II 36 (7.7) M1c 141 (30.1)
 III 100 (21.3) Localization
 IV 299 (63.8) Right upper lobe 121 (25.8)
T stage Right lower lobe 65 (13.9)
 T1 68 (14.5) Middle lobe 19 (4.1)
  T1a 9 (1.9) Left upper lobe 88 (18.8)
  T1b 28 (6.0) Left lower lobe 73 (15.6)
  T1c 31 (6.6) Lingula 14 (3.0)
 T2 120 (25.6) Involvement of two lobes 89 (19.0)
  T2a 81 (17.3) Distribution
  T2b 39 (8.3) Central 96 (20.5)
 T3 93 (19.8) Peripheral 323 (68.9)
 T4 188 (40.1) Central and peripheral 50 (10.7)
Lymph node metastasis/−es 352 (75.1) Size (mm) 45 ± 25

Data are mean values ± standard deviations for continuous variables and number of patients with percentages in parentheses for categorical variables

EGFR mutation analysis

A total of 95 EGFR mutations were detected in 90/469 (19.2%) patients. The most common EGFR mutations were exon 19 deletions (49/90, 54.4%, most frequent subtype: E746_A750del, 33/90, 36.7%) and exon 21 L858R missense mutations (35/90, 38.9%) (Table 2). Doublet EGFR mutations were found in 5 (5/90, 5.6%) tumors, including 2 tumors with L858R and non-L858R missense mutations, 2 tumors with two non-L858R missense mutations and 1 tumor with non-L858R missense mutation and T854A primary resistant mutation (Additional file 1: Table S1). The analysis of the distribution of EGFR mutations among men and women showed a predominance of EGFR mutations in the female group: 55/234 (23.5%) women had a total of 59 EGFR mutations (most frequent: exon 19 deletion, 31/55, 56.4%). By contrast, 35/235 (14.9%) males had a total of 36 EGFR mutations, the most common of which – as in the female group – were exon 19 deletions (18/35, 51.4%). The highest prevalence of EGFR mutations was observed in never smokers (69/115, 60.0%) and was considerably lower in ex-smokers (10/160, 6.3%) and current smokers (11/194, 5.7%). The association between EGFR mutational status and either gender or smoking status was statistically significant on univariate (p = 0.019 and p < 0.001, respectively) and multivariate analyses (p = 0.033 and p < 0.001, respectively) (Tables 3 and 4). No statistically significant differences were found between EGFR mutated and EGFR wildtype tumors with respect to clinical stage (except for stage III, p = 0.040), T stage (except for T2a, p = 0.001), N stage, M stage (except for M1c, p = 0.011), tumor location, mean tumor size and mean patient age (Table 3).

Table 2.

EGFR mutations in 90 lung cancers

cDNA change Amino acid change Frequency Percentage
Exon 21 c.2573 T > G p.L858R 35 38.9
Exon 19 c.2235_2249del/c.2236_2250dela p.E746_A750del 33 36.7
Exon 19 c.2240_2257del p.L747_P753delinsS 6 6.7
Exon 19 c.2254_2277del p.S752_I759del 3 3.3
Exon 19 c.2239_2253del p.L747_T751del 2 2.2
Exon 19 c.2239_2248delinsC p.L747_A750delinsP 2 2.2
Exon 19 c.2238_2252delinsGCA p.L747_T751delinsQ 1 1.1
Exon 19 c.2239_2256del p.L747_S752del 1 1.1
Exon 19 c.2237_2255delinsT p.E746_S752delinsV 1 1.1
Exon 18 c.2126A > C p.E709A 2 2.2
Exon 18 c.2126A > G p.E709G 1 1.1
Exon 18 c.2156G > C p.G719A 1 1.1
Exon 18 c.2155G > T p.G719C 1 1.1
Exon 20 c.2303G > T p.S768I 2 2.2
Exon 20 c.2320G > A p.V774 M 1 1.1
Exon 21 c.2497 T > G p.L833 V 1 1.1
Exon 21 c.2560A > G p.T854A 1 1.1

ac.2235_2249del: n = 25; c.2236_2250del: n = 8  

Table 3.

Associations between clinicopathological features and EGFR mutational status

Variable EGFR wt (n = 379) EGFR mt (n = 90) p-value
Age (years) 64.1 ± 10.9 64.2 ± 13.1 0.946
Gender 0.020
 Male 200 (52.8) 35 (38.9)
 Female 179 (47.2) 55 (61.1)
Smoking status
 Never smokers 46 (12.1) 69 (76.7) < 0.001
 Ex-smokers 150 (39.6) 10 (11.1) < 0.001
 Current smokers 183 (48.3) 11 (12.2) < 0.001
Clinical stage
 I 25 (6.6) 9 (10.0) 0.263
 II 32 (8.4) 4 (4.4) 0.200
 III 88 (23.2) 12 (13.3) 0.040
 IV 234 (61.7) 65 (72.2) 0.063
T stage
 T1 55 (14.5) 13 (14.4) 0.987
  T1a 7 (1.8) 2 (2.2) 0.685
  T1b 26 (6.9) 2 (2.2) 0.095
  T1c 22 (5.8) 9 (10.0) 0.150
 T2 90 (23.7) 30 (33.3) 0.061
  T2a 55 (14.5) 26 (28.9) 0.001
  T2b 35 (9.2) 4 (4.4) 0.139
 T3 77 (20.3) 16 (17.8) 0.587
 T4 157 (41.4) 31 (34.4) 0.224
LN metastasis/−es 289 (76.3) 63 (70.0) 0.218
N stage
 N0 90 (23.7) 27 (30.0) 0.218
 N1 57 (15.0) 8 (8.9) 0.129
 N2 114 (30.1) 20 (22.2) 0.138
 N3 118 (31.1) 35 (38.9) 0.158
Extrathoracic metastasis−/es 164 (43.3) 49 (54.4) 0.056
M stage
 M0 143 (37.7) 25 (27.8) 0.077
 M1a 72 (19.0) 16 (17.8) 0.790
 M1b 60 (15.8) 12 (13.3) 0.555
 M1c 104 (27.4) 37 (41.1) 0.011
Localization
 Right upper lobe 95 (25.1) 26 (28.9) 0.456
 Right lower lobe 57 (15.0) 8 (8.9) 0.129
 Middle lobe 15 (4.0) 4 (4.4) 0.770
 Left upper lobe 72 (19.0) 16 (17.8) 0.790
 Left lower lobe 60 (18.8) 13 (14.4) 0.744
 Lingula 13 (3.4) 1 (1.1) 0.487
 Involvement of two lobes 67 (17.7) 22 (24.4) 0.141
Distribution
 Central 74 (19.5) 22 (24.4) 0.298
 Peripheral 267 (70.4) 56 (62.2) 0.130
 Central and peripheral 38 (10.0) 12 (13.3) 0.361
Size (mm) 45.5 ± 26.3 44.7 ± 20.3 0.744

Data are mean values ± standard deviations for continuous variables and number of patients with percentages in parentheses for categorical variables

Bold numbers indicate significant p-values (< 0.05)

Table 4.

Logistic regression analysis of EGFR mutational status

Univariate logistic regression Multivariate logistic regression
OR 95% CI Beta p-value OR 95% CI Beta p-value
Sex 0.019 0.033
 Male 1.00 1.00
 Female 1.756 1.10–2.81 0.563 1.328 0.75–2.37 0.284
Smoking status < 0.001 < 0.001
 Ever smokers 1.00 1.00
 Never smokers 23.786 13.35–42.38 3.169 23.069 12.92–41.20 3.139

KRAS mutation analysis

Of 443 patients with informative KRAS mutation analysis, 159 (35.9%) harbored KRAS mutations. KRAS mutations were most frequently located in exon 2 (154/159, 96.9%), and the most common mutations were G12C (72/159, 45.3%) and G12 V (26/159, 16.4%) (Table 5). Of 443 patients with informative KRAS and EGFR mutation analyses, 2 patients (0.5%) had coexistent KRAS and EGFR mutations (one with G13S and E746_A750del and one with G12 V and E709A). KRAS mutations tended to be more frequent in females (86/217, 39.6%) than in males (73/226, 32.3%) and were more commonly found in ever smokers (152/353, 43.1%) than in never smokers (7/90, 7.8%). The association between KRAS mutation and smoking status was statistically significant on both univariate and multivariate analyses after stratification by gender (p < 0.001 and p < 0.001, beta −2.285, OR 0.102, CI 95% 0.045–0.228), while gender was significantly associated with KRAS mutation only on multivariate analysis after adjusting for smoking (p = 0.016, beta 0.507, OR 1.660, CI 95% 1.099–2.507) (Tables 6 and 7). Among the patients with informative KRAS mutation analysis, males were significantly more likely to be ever smokers (current smokers or ex-smokers) than females (190/226, 84.1% vs 163/217, 75.1%, p = 0.020, beta 0.559, OR 1.748, CI 95% 1.092–2.800). No statistically significant differences were found between KRAS mutated and KRAS wildtype tumors with respect to clinical stage, T stage (except for T2, p = 0.043), N stage, M stage, tumor location (except for the left lower lobe, p = 0.006), mean tumor size and mean patient age (Table 6).

Table 5.

KRAS mutations in 159 lung cancers

cDNA change Amino acid change Frequency Percentage
Codon 12/Exon 2 c.34G > T p.G12C 72 45.3
Codon 12/Exon 2 c.35G > T p.G12 V 26 16.4
Codon 12/Exon 2 c.35G > A p.G12D 20 12.6
Codon 12/Exon 2 c.35G > C p.G12A 15 9.4
Codon 12/Exon 2 c.34_35del p.G12F 3 1.9
Codon 12/Exon 2 c.34G > C p.G12R 2 1.3
Codon 12/Exon 2 c.34G > A p.G12S 1 0.6
Codon 13/Exon 2 c.37G > T p.G13C 10 6.3
Codon 13/Exon 2 c.37G > A p.G13S 2 1.3
Codon 13/Exon 2 c.38G > A p.G13D 2 1.3
Codon 13/Exon 2 c.37G > C p.G13R 1 0.6
Codon 61/Exon 3 c.183A > C p.Q61H 3 1.9
Codon 61/Exon 3 c.182A > T p.Q61L 2 1.3

Table 6.

Associations between clinicopathological features and KRAS mutational status

Variable KRAS wt (n = 284) KRAS mt (n = 159) p-value
Age (years) 64.7 ± 12.0 63.3 ± 9.4 0.193
Gender 0.108
 Male 153 (53.9) 73 (45.9)
 Female 131 (46.1) 86 (54.1)
Smoking status
 Never smokers 83 (29.2) 7 (4.4) < 0.001
 Ex-smokers 99 (34.9) 61 (38.4) 0.461
 Current smokers 102 (35.9) 91 (57.2) < 0.001
Clinical stage
 I 19 (6.7) 11 (6.9) 0.927
 II 24 (8.5) 10 (6.3) 0.412
 III 60 (21.1) 38 (23.9) 0.500
 IV 181 (63.7) 100 (62.9) 0.860
T stage
 T1 39 (13.7) 26 (16.4) 0.455
  T1a 7 (2.5) 2 (1.3) 0.499
  T1b 16 (5.6) 11 (6.9) 0.588
  T1c 16 (5.6) 13 (8.2) 0.299
 T2 78 (27.5) 30 (18.9) 0.043
  T2a 51 (18.0) 18 (11.3) 0.065
  T2b 27 (9.5) 12 (7.5) 0.485
 T3 52 (18.3) 37 (23.3) 0.211
 T4 115 (40.5) 66 (41.5) 0.835
LN metastasis/−es 212 (74.6) 121 (76.1) 0.734
N stage
 N0 72 (25.4) 38 (23.9) 0.734
 N1 33 (11.6) 27 (17.0) 0.114
 N2 82 (28.9) 48 (30.2) 0.771
 N3 97 (34.2) 46 (28.9) 0.259
Extrathoracic metastasis/−es 124 (43.7) 74 (46.5) 0.559
M stage
 M0 101 (35.6) 59 (37.1) 0.746
 M1a 59 (20.8) 26 (16.4) 0.257
 M1b 37 (13.0) 30 (18.9) 0.100
 M1c 87 (30.6) 44 (27.7) 0.512
Localization
 Right upper lobe 71 (25.0) 44 (27.7) 0.538
 Right lower lobe 45 (15.8) 17 (10.7) 0.134
 Middle lobe 11 (3.9) 6 (3.8) 0.958
 Left upper lobe 52 (18.3) 31 (19.5) 0.759
 Left lower lobe 33 (11.6) 34 (21.4) 0.006
 Lingula 11 (3.9) 3 (1.9) 0.252
 Involvement of two lobes 61 (21.5) 24 (15.1) 0.102
Distribution
 Central 64 (22.5) 27 (17.0) 0.165
 Peripheral 189 (66.5) 117 (73.6) 0.124
 Central and peripheral 31 (10.9) 15 (9.4) 0.624
Size (mm) 45.8 ± 25.8 45.6 ± 25.8 0.937

Data are mean values ± standard deviations for continuous variables and number of patients with percentages in parentheses for categorical variables

Bold numbers indicate significant p-values (< 0.05)

Table 7.

Logistic regression analysis of KRAS mutational status

Univariate logistic regression Multivariate logistic regression
OR 95% CI Beta p-value OR 95% CI Beta p-value
Sex 0.108 0.016
 Male 1.00 1.00
 Female 1.376 0.93–2.03 0.319 1.660 1.10–2.51 0.507
Smoking status < 0.001 < 0.001
 Ever smokers 1.00 1.00
 Never smokers 0.112 0.05–0.25 −2.194 0.102 0.05–0.23 −2.285

ALK rearrangement analysis

ALK rearrangement was detected by FISH (n = 20) or NGS (n = 8) in 28/376 (7.4%) tumors, including one with coexistent KRAS mutation (G12 V). Of the 8 cases with ALK rearrangement diagnosed by NGS, EML4 exon 13-ALK exon 20 fusion gene variant was found in 4 (50.0%) cases, EML4 exon 6-ALK exon 20 fusion gene variant was detected in 3 (37.5%) cases, and EML4 exon 18-ALK exon 20 fusion gene variant was detected in 1 (12.5%) case. There was no significant difference in the frequency of ALK rearrangement between males and females (15/198, 7.6% vs 13/178, 7.3%, univariate analysis, p = 0.920, multivariate logistic regression, p = 0.669) (Tables 8 and 9). By contrast, ALK rearrangement was significantly more common in never smokers than in ever smokers (12/84, 14.3% vs 16/292, 5.5%, p = 0.007) (Table 8). The association between ALK rearrangement and smoking status remained statistically significant on multivariate analysis after adjusting for gender (p = 0.008, beta 1.081, OR 2.948, CI 95% 1.323–6.567) (Table 9). Among the patients tested for ALK rearrangement, females were more likely to be never smokers than males (49/178, 27.5% vs 35/198, 17.7%, p = 0.023, beta 0.570, OR 1.769, CI 95% 1.082–2.892). No statistically significant differences were found between ALK-rearranged and ALK wildtype tumors with respect to clinical stage (except for stage III, p = 0.038), T stage (except for T1b, p = 0.025), N stage (except for N2, p = 0.003), M stage (except for M1b, p = 0.013), tumor location (except for the right upper lobe, p = 0.001, and the middle lobe, p = 0.019), mean tumor size and mean patient age (Table 8).

Table 8.

Associations between clinicopathological features and ALK rearrangement

Variable ALK neg. (n = 348) ALK pos. (n = 28) p-value
Age (years) 64.4 ± 11.2 61.7 ± 14.1 0.229
Gender 0.920
 Male 183 (52.6) 15 (53.6)
 Female 165 (47.4) 13 (46.4)
Smoking status
 Never smokers 72 (20.7) 12 (42.9) 0.007
 Ex-smokers 124 (35.6) 9 (32.1) 0.710
 Current smokers 152 (43.7) 7 (25.0) 0.054
Clinical stage
 I 22 (6.3) 2 (7.1) 0.697
 II 29 (8.3) 2 (7.1) 0.822
 III 67 (19.3) 10 (35.7) 0.038
 IV 230 (66.1) 14 (50.0) 0.086
T stage
 T1 47 (13.5) 6 (21.4) 0.258
  T1a 8 (2.3) 0 (0.0) 0.263
  T1b 19 (5.5) 5 (17.9) 0.025
  T1c 20 (5.7) 1 (3.6) 0.608
 T2 88 (25.3) 7 (25.0) 0.973
  T2a 59 (17.0) 4 (14.3) 0.711
  T2b 29 (8.3) 3 (10.7) 0.721
 T3 70 (20.1) 4 (14.3) 0.455
 T4 143 (41.1) 11 (39.3) 0.852
LN metastasis/−es 259 (74.4) 24 (85.7) 0.183
N stage
 N0 89 (25.6) 4 (14.3) 0.183
 N1 50 (14.4) 1 (3.6) 0.151
 N2 93 (26.7) 15 (53.6) 0.003
 N3 116 (33.3) 8 (28.6) 0.606
Extrathoracic metastasis/−es 161 (46.3) 7 (25.0) 0.029
M stage
 M0 116 (33.3) 14 (50.0) 0.074
 M1a 71 (20.4) 7 (25.0) 0.564
 M1b 56 (16.1) 0 (0.0) 0.013
 M1c 105 (30.2) 7 (25.0) 0.565
Localization
 Right upper lobe 96 (27.6) 0 (0.0) 0.001
 Right lower lobe 51 (14.7) 5 (17.9) 0.587
 Middle lobe 11 (3.2) 4 (14.3) 0.019
 Left upper lobe 66 (19.0) 6 (21.4) 0.750
 Left lower lobe 43 (12.4) 6 (21.4) 0.236
 Lingula 11 (3.2) 1 (3.6) 0.611
 Involvement of two lobes 70 (20.1) 6 (21.4) 0.868
Distribution
 Central 70 (20.1) 8 (28.6) 0.288
 Peripheral 244 (70.1) 16 (57.1) 0.153
 Central and peripheral 34 (9.8) 4 (14.3) 0.508
Size (mm) 44.5 ± 24.4 46.0 ± 31.7 0.761

Data are mean values ± standard deviations for continuous variables and number of patients with percentages in parentheses for categorical variables

Bold numbers indicate significant p-values (< 0.05)

Table 9.

Logistic regression analysis of ALK rearrangement

Univariate logistic regression Multivariate logistic regression
OR 95% CI Beta p-value OR 95% CI Beta p-value
Sex 0.920 0.669
 Male 1.00 1.00
 Female 0.961 0.44–2.08 −0.040 0.842 0.38–1.85 −0.172
Smoking status 0.009 0.008
 Ever smokers 1.00 1.00
 Never smokers 2.875 1.30–6.35 1.056 2.948 1.32–6.57 1.081

KRAS mutation analysis was not performed in 26 patients with proven EGFR mutation, and ALK rearrangement testing was not performed in 93 patients including 62 patients with KRAS mutation and 31 patients with EGFR mutation. Because genetic alterations in EGFR, KRAS and ALK are generally mutually exclusive, it can be concluded that 90/469 (19.2%) patients had EGFR mutations, 159/469 (33.9%) had KRAS mutations, and 28/469 (6.0%) had ALK gene rearrangement (Table 10). 195/469 (41.6%) patients had triple-negative (EGFR-negative/KRAS-negative/ALK-negative) lung adenocarcinomas.

Table 10.

Frequency of oncogenic driver mutation in our study cohort

Study population (n = 469) Patients testeda
EGFR 90/469 (19.2) 90/469 (19.2)
KRAS 159/469 (33.9) 159/443 (35.9)
ALK 28/469 (6.0) 28/376 (7.4)
BRAF 12/469 (2.6) 12/309 (3.9)
ERBB2 9/469 (1.9) 9/286 (3.1)
MET 9/469 (1.9) 9/234 (3.8)
PIK3CA 7/469 (1.5) 7/163 (4.3)
RET 4/469 (0.8) 4/208 (1.9)
ROS1 8/469 (1.7) 8/248 (3.2)

Data are absolute number of patients with percentages in parentheses

aPercentages in parentheses refer to the number of tested patients

EGFR, KRAS and ALK comparative analyses

Comparative analyses of EGFR and KRAS mutated tumors, EGFR mutated and ALK rearranged tumors and KRAS mutated and ALK rearranged tumors are summarized in Additional file 1: Tables S2–S4. Of note, EGFR mutated tumors were more likely to have multiple extrathoracic metastases (M1c) compared with KRAS mutated tumors (37/90, 41.1% vs 44/159, 27.7%, p = 0.030) (Additional file 1: Table S2). EGFR mutated tumors were also more likely to be clinical stage IV and have single or multiple extrathoracic metastases (M1b or M1c) compared with ALK rearranged tumors (65/90, 72.2% vs 14/28, 50.0%, p = 0.029 and 49/90, 54.4% vs 7/28, 25.0%, p = 0.006) (Additional file 1: Table S3). ALK rearranged tumors were more frequently associated with clinical stage III than EGFR mutated tumors (10/28, 35.7% vs 12/90, 13.3%, p = 0.008) and more commonly showed ipsilateral mediastinal or subcarinal lymph node metastasis (N2) compared with EGFR and KRAS mutated lung adenocarcinomas (15/28, 53.6% vs 20/90, 22.2%, p = 0.002 and 15/28, 53.6% vs 48/159, 30.2%, p = 0.016).

Other mutations and rearrangements

RET fusions were detected by FISH in 4 (1.9%) of 208 tested patients, including 1 patient with coexistent PIK3CA mutation (E545K). ROS1 fusions were detected by FISH (n = 5) or NGS (n = 3) in 8 (3.2%) of 248 tested patients. No statistically significant differences were found between RET/ROS1 rearranged and non-rearranged tumors with respect to gender, smoking status, clinical stage, TNM stage, tumor location, mean tumor size and mean patient age. 12/309 (3.9%) tumors harbored BRAF mutations. The majority of BRAF mutations were located in exon 15 (10/12, 83.3%); the most common BRAF mutation was V600E (9/12, 75.0%) (Table 11). No statistically significant differences were found between BRAF mutated and BRAF wildtype tumors with respect to the clinicopathological parameters evaluated. ERBB2 mutations were detected in 9/286 (3.1%) tumors (Table 12), including 7 insertion/duplication mutations in exon 20, 1 nonsense mutation in exon 13 and 1 missense mutation in exon 8 of the ERBB2 gene; the most frequent ERBB2 mutation was p.A775_G776insYVMA (alternative nomenclature p.Y772_A775dup, c.2313_2324dup) (5/9, 55.6%). ERBB2 mutations were more common in never smokers than in ex−/current smokers (5/64, 7.8% vs 4/222, 1.8%, chi-square test, p = 0.029, multivariate logistic regression, p = 0.020, beta 1.621, OR 5.059, CI 95% 1.296–19.747), while no significant differences were found between ERBB2 mutated and ERBB2 wildtype tumors with respect to the other clinicopathological parameters analyzed. Nine MET exon 14 skipping mutations were detected in 234 (3.8%) tumors, including one with coexistent BRAF (V600E) and PIK3CA (E542K) mutation and one with coexistent KRAS (G13C) mutation. PIK3CA mutations were detected in 7/163 (4.3%) tumors (3 x E542K, 2 x E545K, 1 x R38H, 1 x H1047R), including one with coexistent BRAF (V600E) and MET exon 14 skipping mutation, two with coexistent EGFR mutations (L858R and L747_P753delinsS, respectively), one with coexistent KRAS (G12A) mutation and one with coexistent RET rearrangement. No statistically significant differences were found between MET/PIK3CA mutated and MET/PIK3CA wildtype tumors with respect to gender, smoking status, clinical stage, TNM stage, mean tumor size and mean patient age. While MET mutated tumors were more likely to be located in the right upper lobe than MET wildtype tumors (6/9, 66.7% vs 50/225, 22.2%, p = 0.007), PIK3CA mutated tumors were less likely peripheral in location and involved more frequently both the central and peripheral portions of the lung compared with PIK3CA wildtype tumors (2/7, 28.6% vs 107/156, 68.6%, p = 0.041 and 3/7, 42.9% vs 10/156, 6.4%, p = 0.012). Among the 469 study patients, 154 (32.8%) had lung adenocarcinomas that were negative for all oncogenic driver mutations evaluated in the current study.

Table 11.

BRAF mutations in 12 lung cancers

cDNA change Amino acid change Frequency Percentage
Exon 15 c.1799 T > A p.V600E 9 75.0
Exon 15 c.1781A > G p.D594G 1 8.3
Exon 11 c.1406G > T p.G469 V 1 8.3
Exon 11 c.1406G > C p.G469A 1 8.3

Table 12.

ERBB2 mutations in 9 lung cancers

ERBB2 mutation type Mutation Alternate nomenclature
(based on HGVS guidelines)
Frequency Percentage
Exon 20 insertion p.A775_G776insYVMA
(c.2324_2325ins12)
p.Y772_A775dup
(c.2313_2324dup)
5 55.6
Exon 20 insertion p.P780_Y781insGSP
(c.2339_2340insGGCTCCCCA)
p.G778_P780dup
(c.2331_2339dup)
1 11.1
Exon 20 insertion p.G776 > VC
(c.2326_2327insTGT)
p.G776delinsVC
(c.2326_2327insTGT)
1 11.1
Exon 8 missense mutation p.Q527*
(c.1579C > T)
p.Gln527Ter
(c.1579C > T)
1 11.1
Exon 13 nonsense mutation p.S310Tyr
(c.929C > A)
p.Ser310Tyr
(c.929C > A)
1 11.1

HGVS Human Genome Variation Society

Discussion

This study presents for the first time data on the EGFR, KRAS, ALK, ROS1, RET, BRAF, ERBB2, MET and PIK3CA mutation frequencies in a representative Swiss cohort of patients with stage I-IV lung adenocarcinoma using NGS as testing method in the majority of patients. Molecular testing was performed in all patients at the time of initial diagnosis during a 4-year period at a primary referral center for lung diseases in Northeastern Switzerland. We also comprehensively studied types of mutations and associations of mutational status with demographic and clinicopathological patient characteristics.

The reported EGFR mutation rate in patients with lung adenocarcinoma varies widely between different populations worldwide, ranging from 10 to 20% in European and North American cohorts [5, 6, 1323] to more than 50% in Asian populations [24, 25]. The wide range of reported EGFR mutation rates among European cohorts might be explained by differences between the published studies with respect to patient selection criteria and methods used for molecular analysis. In a French study by Vallee et al. [19], one of the largest single center studies in Europe, EGFR mutations were detected in 13.5% of patients with NSCLC and in 14.7% of patients with lung adenocarcinomas. The authors used allele-specific PCR for evaluation of L858R point mutation and DNA fragment analysis to detect exon 19 deletions. Because other EGFR mutations were not evaluated, the true prevalence of EGFR mutations in this study remains unknown. The INSIGHT study, a large multicenter study comprising 1785 NSCLC patients (including 1393 patients with lung adenocarcinoma), showed an EGFR mutation frequency of 13.8% in NSCLC patients and of 15.4% in patients with lung adenocarcinoma [14]. The study analyzed tumor samples from 14 cancer centers in six Central European countries, each with different patient inclusion criteria and testing methods, which makes comparison with other studies more difficult. In addition, mutation testing was not performed at a fixed time point, which could induce bias as mutations may arise during the disease course [23]. Our study results show a prevalence of EGFR mutations that is similar to that reported by Moiseyenko et al. [20] (19.8%) in a Russian cohort and by Hlinkova et al. [22] (20%) in a Slovakian cohort, but lower than the EGFR mutation rates reported in two previous studies from Switzerland [5, 6]. Ess et al. [5] retrospectively analyzed population based data on the frequency of molecular testing, factors affecting testing and the prevalence of EGFR mutations and ALK rearrangements in patients with stage IV or relapsed non-squamous NSCLC (including adenocarcinoma, large cell carcinoma and NOS histology) from 2008 to 2014. Using direct sequencing (EGFR exons 18–21) for EGFR mutation analysis and FISH with a break-apart probe for ALK rearrangement testing, EGFR mutations (exclusively exon 19 deletions and exon 21 L858R mutations!) were detected in 11% of patients with advanced non-squamous NSCLC and in 13% of patients with lung adenocarcinoma, while 12% of patients with non-squamous NSCLC and 10% of patients with lung adenocarcinoma harbored ALK rearrangements. Other oncogenic driver mutations or associations between EGFR mutation/ALK rearrangement status and clinicopathological characteristics of patients with lung adenocarcinoma were not evaluated. More recently, Schwegler et al. [6] prospectively analyzed population based epidemiological data on overall survival of patients with mutated stage IV lung adenocarcinoma, mostly residents in rural areas of Central Switzerland, from 2010 to 2014. EGFR mutations were detected with Sanger sequencing in 14% of the patients, while KRAS, ERBB2, BRAF and MET mutations and ALK and RET translocations were found in 20%, 2%, 1%, 0.5%, 6% and 0.5%, respectively [6]. In contrast to our study, the types of mutations were not analyzed, and mutational status was not correlated with demographic or clinicopathological features. Possible reasons for the reported lower EGFR mutation rates compared with that of our study may be different modes of patient selection (selection from the molecular database of University Hospital Zurich vs selection from cancer registries), different patient selection criteria (patients with stage I-IV lung adenocarcinoma vs patients with stage IV or relapsed non-squamous NSCLC [5] and patients with stage IV lung adenocarcinoma [6]) and different methods used for mutational analysis (NGS and Sanger sequencing vs Sanger sequencing alone). In contrast to the studies by Ess et al. [5] and Schwegler et al. [6], the majority of patients in our study underwent molecular testing with NGS, which has been shown to demonstrate high analytic sensitivity, accurate detection of complex indel mutations, and broad reportable ranges with simultaneous detection of doublet EGFR mutations and concomitant KRAS and BRAF mutations in the clinical diagnostic setting [2, 26]. In addition, in the study by Schwegler et al. [6] patients with stage I-III lung adenocarcinoma were excluded from the analysis, and 20% of stage IV lung cancer patients were not tested for oncogenic driver mutations, while in the study by Ess et al. [5] 38% of patients did not receive molecular analysis. Although we did not assess mutation testing rates at our institution, it can be assumed that the molecular testing rates in the period from 2014 to 2018 were higher than those of previous years and that patients treated at an institution active in clinical research are more regularly tested for predictive biomarkers than patients treated at an institution not participating in clinical research [5]. In accordance with published literature [1316, 23], we found a significant association of EGFR mutation status with female gender and never smoking status. When we restricted the analysis to female never smokers, we achieved a high EGFR mutation rate of 65.7% (46/70), a finding consistent with previous reports [13, 24, 25].

KRAS mutation is one of the most frequent mutations in NSCLC, at least in Caucasian populations, with reported frequencies reaching up to 30% of lung adenocarcinomas [13, 23, 27, 28], while its prevalence in Asian populations is approximately 10% [2931]. KRAS mutations are predominantly found in smokers [32], but they may occur in up to 15% of non-smokers [27]. To date, no effective anti-KRAS agent has been released, although a number of preclinical studies and clinical trials are currently underway, exploring novel therapeutic approaches to target KRAS mutated NSCLC [3336]. The KRAS mutation rate in our study was slightly higher than was previously reported for Caucasian populations (which might be related to different smoking habits in this Swiss cohort), but was almost identical to the KRAS mutation rate reported by Brcic et al. [13] in a Croatian cohort. The presence of KRAS mutation in our study was significantly associated with a history of smoking on both univariate and multivariate analyses, while the association of KRAS mutation with gender was statistically significant only on multivariate analysis after adjusting for smoking. This finding adds to a mixed body of literature. Some studies have shown increased incidence of KRAS mutations among females [23], while others found equal frequencies in both men and women [13, 37, 38].

ALK rearrangements are detected in 3–7% of NSCLC [3944]. They predominantly occur in non-smokers, lung adenocarcinomas and non-Asian vs Asian populations, while men and women seem to be equally affected [3]. The frequency of ALK rearrangement in our study is consistent with previous reports, as is the association with smoking status (higher frequency in never smokers). Interestingly, our study showed a higher frequency of ipsilateral mediastinal or subcarinal lymph node metastasis (N2) in ALK-rearranged tumors compared with non-rearranged, EGFR mutated and KRAS mutated tumors, while no significant differences were found between ALK-rearranged and non-rearranged/EGFR mutated/KRAS mutated tumors with regard to N0, N1 and N3 stages. In addition, ALK rearranged lung adenocarcinomas were more frequently pT1 tumors compared with ALK-non rearranged lung cancer. In a previous study, evaluating surgically resected stage I-III NSCLCs, Paik et al. [45] found that ALK FISH-positive NSCLC cases showed lower tumor stage (pT1), but had more frequently lymph node metastases compared with ALK FISH-negative NSCLC cases. The authors suggested that ALK-rearranged lung cancer might have unique biological features with a tendency to early lymph node metastasis despite the small primary tumor size, which could explain higher incidences of ALK rearrangement in advanced NSCLC compared with surgically resectable lung cancer [45].

The frequency of BRAF mutations in the current study seems to be among the higher previously reported mutation rates [4648], but is still lower than the mutation rate reported by Illei et al. [26] (6.3%), who analyzed 1006 lung cancers with NGS. Other targetable genomic alterations in NSCLC, including RET and ROS1 rearrangements and ERBB2, MET exon 14 skipping and PIK3CA mutations, are present only in a small percentage of NSCLC patients (~ 1–2% [49], ~ 2% [50], 2–4% [5153], 3–4% [5457] and 2–5% [26, 58, 59], respectively). While our study with a limited sample size of RET and ROS1 rearranged lung cancer showed no significant differences between RET or ROS1 rearranged and non-rearranged tumors regarding clinicopathological characteristics, previous investigations have reported a higher incidence of RET and ROS1 rearrangements in younger age group and never smokers [60, 61] as well as a significant association of RET rearranged NSCLC with small primary tumor size and lymph node involvement [60, 62]. According to previous reports [63], ERBB2 mutations in NSCLC are more common in females, Asian cohorts and never-smokers. While our study showed no significant association of ERBB2 mutation with female gender, we could confirm the higher prevalence of ERBB2 mutations in never smoking patients. PIK3CA mutations are more commonly encountered in squamous NSCLC [58, 59, 64] and seem to confer inferior prognosis in lung adenocarcinoma [65]. Interestingly, PIK3CA mutations have been reported to occur in parallel with other oncogenic driver mutations [66, 67], as was the case in 5 of 7 PIK3CA mutated tumors in the present study. Regarding the clinicopathological characteristics of MET exon 14 skipping mutation-positive tumors, three retrospective studies showed that MET exon 14 skipping positivity in NSCLC patients is significantly associated with advanced age [6870]. In the current study, we found no significant difference in mean age between patients with and those without MET exon 14 mutated tumors. However, we acknowledge that the sample size of MET exon 14 mutated tumors was too small to draw meaningful conclusions.

Conclusion

Our study presents data on the frequency of oncogenic driver mutations in a Northeastern Swiss population with stage I-IV lung adenocarcinoma using NGS as testing method in the majority of cases. A number of studies already analyzed oncogenic driver mutation frequencies, notably EGFR, KRAS and ALK mutation rates, in different populations from European countries. However, based on the available data, the true prevalence of mutations in lung adenocarcinoma is often difficult to determine due to patient selection bias, different testing platforms used for analysis and the histological heterogeneity of tumors included in the studies. Although we cannot exclude some selection toward patients with higher likelihood of mutated tumors in the current study, a major selection bias is unlikely to have occurred because the epidemiological characteristics of our study population are similar to those of the INSIGHT study and other previous investigations. We found a relatively high EGFR mutation rate, while KRAS, BRAF, ERBB2, MET and PIK3CA mutation and ALK, RET and ROS1 rearrangement frequencies were similar to those of previous reports. EGFR and KRAS mutation was significantly associated with gender and smoking status, while ALK rearrangement was significantly associated with smoking status alone.

Additional file

Additional file 1: (30.7KB, docx)

Table S1. Doublet EGFR mutations in 90 lung cancers. Table S2. Comparison of EGFR and KRAS mutated tumors. Table S3. Comparison of EGFR mutated and ALK rearranged tumors. Table S4. Comparison of KRAS mutated and ALK rearranged tumors. (DOCX 30 kb)

Acknowledgements

The authors would like to thank Prof. Dieter Zimmermann from the Institute of Pathology and Molecular Pathology, University Hospital Zurich, for providing information about molecular analyses.

Funding

The authors received no specific funding for this work.

Availability of data and materials

The datasets supporting the conclusions of this article are available from the corresponding author on reasonable request.

Abbreviations

ALK

Anaplastic lymphoma kinase

BRAF

B rapidly accelerated fibrosarcoma

EGFR

Epidermal growth factor receptor

ERBB2

Erb-b2 tyrosine kinase 2

FISH

Fluorescence in situ hybridization

HGVS

Human Genome Variation Society

ICC

Immunocytochemistry

IHC

Immunohistochemistry

KRAS

Kirsten rat sarcoma

MET

Mesenchymal epithelial transition proto-oncogene

NGS

Next generation sequencing

NSCLC

Non-small cell lung cancer

PCR

Polymerase chain reaction

PIK3CA

Phosphatidylinositol-3 kinase catalytic subunit alpha

RET

Rearranged during transfection proto-oncogene

ROS1

ROS proto-oncogene 1

TKI

Tyrosine kinase inhibitor

Authors’ contributions

AS was responsible for the conceptualization of this study and the project administration. AG, CG and MR were responsible for data collection and literature analysis. AG and CG were responsible for analysis and data interpretation. AG wrote the manuscript. All authors critically revised the manuscript and approved the final version.

Ethics approval and consent to participate

The study was approved by the Cantonal Ethics Committee of Zurich (StV-No. 2009/14–0029). Formal patient consent was not required because of the retrospective study design.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Alexandra Grosse, Email: alexandra.grosse@usz.ch.

Claudia Grosse, Email: claudiagrosse@gmx.at.

Markus Rechsteiner, Email: rechsteiner.markus@gmx.ch.

Alex Soltermann, Email: alex.soltermann@usz.ch.

References

  • 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424. doi: 10.3322/caac.21492. [DOI] [PubMed] [Google Scholar]
  • 2.Jing C, Mao X, Wang Z, Sun K, Ma R, Wu J, et al. Next-generation sequencing-based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her-2 and TP53 mutations in patients with non-small cell lung cancer. Mol Med Rep. 2018;18:2191–2197. doi: 10.3892/mmr.2018.9210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Zhao F, Xu M, Lei H, Zhou Z, Wang L, Li P, et al. Clinicopathological characteristics of patients with non-small-cell lung cancer who harbor EML4-ALK fusion gene: a meta-analysis. PLoS One. 2015;10:e0117333. doi: 10.1371/journal.pone.0117333. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Gkolfinopoulos S, Mountzios G. Beyond EGFR and ALK: targeting rare mutations in advanced non-small cell lung cancer. Ann Transl Med. 2018;6:142. doi: 10.21037/atm.2018.04.28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Ess SM, Herrmann C, Frick H, Krapf M, Cerny T, Jochum W, et al. Epidermal growth factor receptor and anaplastic lymphoma kinase testing and mutation prevalence in patients with advanced non-small cell lung cancer in Switzerland: a comprehensive evaluation of real world practices. Eur J Cancer Care. 2017;26:e12721. doi: 10.1111/ecc.12721. [DOI] [PubMed] [Google Scholar]
  • 6.Schwegler C, Kaufmann D, Pfeiffer D, Aebi S, Diebold J, Gautschi O. Population-level effect of molecular testing and targeted therapy in patients with advanced pulmonary adenocarcinoma: a prospective cohort study. Virchows Arch. 2018;472:581–588. doi: 10.1007/s00428-017-2268-y. [DOI] [PubMed] [Google Scholar]
  • 7.Arndt V, Feller A, Hauri D, Heusser R, Junker C, Kuehni C, Lorez M, Pfeiffer V, Roy E, Schindler M. Swiss cancer report 2015. Neuchatel: Federal Statistical Office; 2016. [Google Scholar]
  • 8.Oberli LS, Valeri F, Korol D, Rohrmann S, Dehler S. 31 years of lung cancer in the canton of Zurich, Switzerland: incidence trends by sex, histology and laterality. Swiss Med Wkly. 2016;146:w14327. doi: 10.4414/smw.2016.14327. [DOI] [PubMed] [Google Scholar]
  • 9.Lorez M, Rohrmann S, Heusser R, Volker A, NICER Working Group. Lung cancer trends by histologic subtype in Switzerland: Schweizer Krebsbulletin. 2017;37:179–85.
  • 10.Brierley JD, Gospodarowicz MK, Wittekind C, editors. TNM classification of malignant tumours. UK: John Wiley & Sons, Ltd; 2017. [Google Scholar]
  • 11.Velizheva NP, Rechsteiner MP, Valtcheva N, Freiberger SN, Wong CE, Vrugt B, et al. Targeted next-generation-sequencing for reliable detection of targetable rearrangements in lung adenocarcinoma – a single center retrospective study. Pathol Res Pract. 2018;214:572–8. doi: 10.1016/j.prp.2018.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Velizheva NP, Rechsteiner MP, Wong CE, Zhong Q, Rössle M, Bode B, et al. Cytology smears as excellent starting material for next-generation sequencing-based molecular testing of patients with adenocarcinoma of the lung. Cancer Cytopathol. 2017;125:30–40. doi: 10.1002/cncy.21771. [DOI] [PubMed] [Google Scholar]
  • 13.Brcic L, Jakopovic M, Misic M, Seiwerth F, Kern I, Smojver-Jezek S, et al. Analysis of the frequency of EGFR, KRAS and ALK mutations in patients with lung adenocarcinoma in Croatia. Diagn Pathol. 2016;11:90. doi: 10.1186/s13000-016-0544-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Ramlau R, Cufer T, Berzinec P, Dziadziuszko R, Olszewski W, Popper H, et al. Epidermal growth factor receptor mutation-positive non-small-cell lung cancer in the real-world setting in Central Europe: the INSIGHT study. J Thorac Oncol. 2015;10:1370–4. doi: 10.1097/JTO.0000000000000621. [DOI] [PubMed] [Google Scholar]
  • 15.Milella M, Nuzzo C, Bria E, Sperduti I, Visca P, Buttitta F, et al. EGFR molecular profiling in advanced NSCLC: a prospective phase II study in molecularly/clinically selected patients pretreated with chemotherapy. J Thorac Oncol. 2012;7:672–680. doi: 10.1097/JTO.0b013e31824a8bde. [DOI] [PubMed] [Google Scholar]
  • 16.Zaric B, Stojsic V, Kovacevic T, Sarcev T, Tepavac A, Jankovic R, et al. Clinical characteristics, tumor, node, metastasis status, and mutation rate in domain of epidermal growth factor receptor gene in serbian patients with lung adenocarcinoma. J Thorac Oncol. 2014;9:1406–1410. doi: 10.1097/JTO.0000000000000242. [DOI] [PubMed] [Google Scholar]
  • 17.Helland Å, Skaug HM, Kleinberg L, Iversen ML, Rud AK, Fleischer T, et al. EGFR gene alterations in a Norwegian cohort of lung cancer patients selected for surgery. J Thorac Oncol. 2011;6:947–950. doi: 10.1097/JTO.0b013e31820db209. [DOI] [PubMed] [Google Scholar]
  • 18.Berg J, Fjellbirkeland L, Suhrke P, Jebsen P, Lund-Iversen M, Kleinberg L, et al. EGFR mutation testing of lung cancer patients - experiences from Vestfold hospital trust. Acta Oncol. 2016;55:149–155. doi: 10.3109/0284186X.2015.1062537. [DOI] [PubMed] [Google Scholar]
  • 19.Vallee A, Sagan C, Le Loupp AG, Bach K, Dejoie T, Denis MG. Detection of EGFR gene mutations in non-small cell lung cancer: lessons from a single-institution routine analysis of 1,403 tumor samples. Int J Oncol. 2013;43:1045–1051. doi: 10.3892/ijo.2013.2056. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Moiseyenko VM, Procenko SA, Levchenko EV, Barchuk AS, Moiseyenko FV, Iyevleva AG, et al. High efficacy of first-line gefitinib in non-Asian patients with EGFR-mutated lung adenocarcinoma. Onkologie. 2010;33:231–238. doi: 10.1159/000302729. [DOI] [PubMed] [Google Scholar]
  • 21.Midha A, Dearden S, McCormack R. EGFR mutation incidence in non-small-cell lung cancer of adenocarcinoma histology: a systematic review and global map by ethnicity (mutMapII) Am J Cancer Res. 2015;5:2892–2911. [PMC free article] [PubMed] [Google Scholar]
  • 22.Hlinkova K, Babal P, Berzinec P, Majer I, Mikle-Barathova Z, Piackova B, et al. Evaluation of 2-year experience with EGFR mutation analysis of small diagnostic samples. Diagn Mol Pathol. 2013;22:70–75. doi: 10.1097/PDM.0b013e31827e6984. [DOI] [PubMed] [Google Scholar]
  • 23.Bauml J, Mick R, Zhang Y, Watt CD, Vachani A, Aggarwal C, et al. Frequency of EGFR and KRAS mutations in patients with non small cell lung cancer by racial background: do disparities exist? Lung Cancer. 2013;81:347–353. doi: 10.1016/j.lungcan.2013.05.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Xia N, An J, Jiang QQ, Li M, Tan J, Hu CP. Analysis of EGFR, EML4-ALK, KRAS, and c-MET mutations in Chinese lung adenocarcinoma patients. Exp Lung Res. 2013;39:328–335. doi: 10.3109/01902148.2013.819535. [DOI] [PubMed] [Google Scholar]
  • 25.Gao B, Sun Y, Zhang J, Ren Y, Fang R, Han X, et al. Spectrum of LKB1, EGFR, and KRAS mutations in chinese lung adenocarcinomas. J Thorac Oncol. 2010;5:1130–1135. doi: 10.1097/JTO.0b013e3181e05016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Illei PB, Belchis D, Tseng LH, Nguyen D, De Marchi F, Haley L, et al. Clinical mutational profiling of 1006 lung cancers by next generation sequencing. Oncotarget. 2017;8:96684–96. doi: 10.18632/oncotarget.18042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Riely GJ, Kris MG, Rosenbaum D, Marks J, Li A, Chitale DA, et al. Frequency and distinctive spectrum of KRAS mutations in never smokers with lung adenocarcinoma. Clin Cancer Res. 2008;14:5731–5734. doi: 10.1158/1078-0432.CCR-08-0646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Dogan S, Shen R, Ang DC, Johnson ML, D'Angelo SP, Paik PK, et al. Molecular epidemiology of EGFR and KRAS mutations in 3,026 lung adenocarcinomas: higher susceptibility of women to smoking-related KRAS-mutant cancers. Clin Cancer Res. 2012;18:6169–6177. doi: 10.1158/1078-0432.CCR-11-3265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Takamochi K, Oh S, Suzuki K. Differences in EGFR and KRAS mutation spectra in lung adenocarcinoma of never and heavy smokers. Oncol Lett. 2013;6:1207–1212. doi: 10.3892/ol.2013.1551. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Bae NC, Chae MH, Lee MH, Kim KM, Lee EB, Kim CH, et al. EGFR, ERBB2, and KRAS mutations in Korean non-small cell lung cancer patients. Cancer Genet Cytogenet. 2007;173:107–113. doi: 10.1016/j.cancergencyto.2006.10.007. [DOI] [PubMed] [Google Scholar]
  • 31.Liu L, Liu J, Shao D, Deng Q, Tang H, Liu Z, et al. Comprehensive genomic profiling of lung cancer using a validated panel to explore therapeutic targets in east Asian patients. Cancer Sci. 2017;108:2487–2494. doi: 10.1111/cas.13410. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ahrendt SA, Decker PA, Alawi EA, Zhu Yr YR, Sanchez-Cespedes M, Yang SC, et al. Cigarette smoking is strongly associated with mutation of the K-ras gene in patients with primary adenocarcinoma of the lung. Cancer. 2001;92:1525–1530. doi: 10.1002/1097-0142(20010915)92:6&#x0003c;1525::AID-CNCR1478&#x0003e;3.0.CO;2-H. [DOI] [PubMed] [Google Scholar]
  • 33.Ferrer I, Zugazagoitia J, Herbertz S, John W, Paz-Ares L, Schmid-Bindert G. KRAS-mutant non-small cell lung cancer: from biology to therapy. Lung Cancer. 2018;124:53–64. doi: 10.1016/j.lungcan.2018.07.013. [DOI] [PubMed] [Google Scholar]
  • 34.Wood K, Hensing T, Malik R, Salgia R. Prognostic and predictive value in KRAS in non-small-cell lung cancer: a review. JAMA Oncol. 2016;2:805–812. doi: 10.1001/jamaoncol.2016.0405. [DOI] [PubMed] [Google Scholar]
  • 35.Jänne PA, Shaw AT, Pereira JR, Jeannin G, Vansteenkiste J, Barrios C, et al. Selumetinib plus docetaxel for KRAS-mutant advanced non-small-cell lung cancer: a randomised, multicentre, placebo-controlled, phase 2 study. Lancet Oncol. 2013;14:38–47. doi: 10.1016/S1470-2045(12)70489-8. [DOI] [PubMed] [Google Scholar]
  • 36.A Study of Abemaciclib (LY2835219) in participants with previously treated KRAS mutated lung cancer (JUNIPER). Avalaible online: https://clinicaltrials.gov/ct2/show/NCT02152631. Accessed 10 Nov 2018.
  • 37.Bacchi CE, Ciol H, Queiroga EM, Benine LC, Silva LH, Ojopi EB. Epidermal growth factor receptor and KRAS mutations in Brazilian lung cancer patients. Clinics (Sao Paulo). 2012;67:419–24. https://doi.org/papers2://publication/uuid/F04AA1B0-F128-493A-A47B-F45F7553371A [DOI] [PMC free article] [PubMed]
  • 38.Rouquette I, Lauwers-Cances V, Allera C, Brouchet L, Milia J, Nicaise Y, et al. Characteristics of lung cancer in women: importance of hormonal and growth factors. Lung Cancer. 2012;76:280–285. doi: 10.1016/j.lungcan.2011.11.023. [DOI] [PubMed] [Google Scholar]
  • 39.Kwak EL, Bang YJ, Camidge DR, Shaw AT, Solomon B, Maki RG, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363:1693–1703. doi: 10.1056/NEJMoa1006448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Takeuchi K, Choi YL, Soda M, Inamura K, Togashi Y, Hatano S, et al. Multiplex reverse transcription-PCR screening for EML4-ALK fusion transcripts. Clin Cancer Res. 2008;14:6618–6624. doi: 10.1158/1078-0432.CCR-08-1018. [DOI] [PubMed] [Google Scholar]
  • 41.Wong DW, Leung EL, So KK, Tam IY, Sihoe AD, Cheng LC, et al. The EML4-ALK fusion gene is involved in various histologic types of lung cancers from nonsmokers with wild-type EGFR and KRAS. Cancer. 2009;115:1723–33. 10.1002/cncr.24181. [DOI] [PubMed]
  • 42.Soda M, Choi YL, Enomoto M, Takada S, Yamashita Y, Ishikawa S, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature. 2007;448:561–566. doi: 10.1038/nature05945. [DOI] [PubMed] [Google Scholar]
  • 43.Shinmura K, Kageyama S, Tao H, Bunai T, Suzuki M, Kamo T, et al. EML4-ALK fusion transcripts, but no NPM-, TPM3-, CLTC-, ATIC-, or TFG-ALK fusion transcripts, in non-small cell lung carcinomas. Lung Cancer. 2008;61:163–169. doi: 10.1016/j.lungcan.2007.12.013. [DOI] [PubMed] [Google Scholar]
  • 44.Koivunen JP, Mermel C, Zejnullahu K, Murphy C, Lifshits E, Holmes AJ, et al. EML4-ALK fusion gene and efficacy of an ALK kinase inhibitor in lung cancer. Clin Cancer Res. 2008;14:4275–4283. doi: 10.1158/1078-0432.CCR-08-0168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Paik JH, Choi CM, Kim H, Jang SJ, Choe G, Kim DK, et al. Clinicopathologic implication of ALK rearrangement in surgically resected lung cancer: a proposal of diagnostic algorithm for ALK-rearranged adenocarcinoma. Lung Cancer. 2012;76:403–409. doi: 10.1016/j.lungcan.2011.11.008. [DOI] [PubMed] [Google Scholar]
  • 46.Pratilas CA, Hanrahan AJ, Halilovic E, Persaud Y, Soh J, Chitale D, et al. Genetic predictors of MEK dependence in non-small cell lung cancer. Cancer Res. 2008;68:9375–9383. doi: 10.1158/0008-5472.CAN-08-2223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Cardarella S, Ogino A, Nishino M, Butaney M, Shen J, Lydon C, et al. Clinical, pathologic, and biologic features associated with BRAF mutations in non-small cell lung cancer. Clin Cancer Res. 2013;19:4532–4540. doi: 10.1158/1078-0432.CCR-13-0657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Paik PK, Arcila ME, Fara M, Sima CS, Miller VA, Kris MG, et al. Clinical characteristics of patients with lung adenocarcinomas harboring BRAF mutations. J Clin Oncol. 2011;29:2046–51. 10.1200/JCO.2010.33.1280. [DOI] [PMC free article] [PubMed]
  • 49.Nikiforov YE. Thyroid carcinoma: molecular pathways and therapeutic targets. Mod Pathol. 2008;21(Suppl 2):S37–S43. doi: 10.1038/modpathol.2008.10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Gainor JF, Shaw AT. Novel targets in non-small cell lung cancer: ROS1 and RET fusions. Oncologist. 2013;18:865–875. doi: 10.1634/theoncologist.2013-0095. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Arcila ME, Chaft JE, Nafa K, Roy-Chowdhuri S, Lau C, Zaidinski M, et al. Prevalence, clinicopathologic associations, and molecular spectrum of ERBB2 (HER2) tyrosine kinase mutations in lung adenocarcinomas. Clin Cancer Res. 2012;18:4910–4918. doi: 10.1158/1078-0432.CCR-12-0912. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Buttitta F, Barassi F, Fresu G, Felicioni L, Chella A, Paolizzi D, et al. Mutational analysis of the HER2 gene in lung tumors from Caucasian patients: mutations are mainly present in adenocarcinomas with bronchioloalveolar features. Int J Cancer. 2006;119:2586–91. 10.1002/ijc.22143. [DOI] [PubMed]
  • 53.Shigematsu H, Takahashi T, Nomura M, Majmudar K, Suzuki M, Lee H, et al. Somatic mutations of the HER2 kinase domain in lung adenocarcinomas. Cancer Res. 2005;65:1642–1646. doi: 10.1158/0008-5472.CAN-04-4235. [DOI] [PubMed] [Google Scholar]
  • 54.Frampton GM, Ali SM, Rosenzweig M, Chmielecki J, Lu X, Bauer TM, et al. Activation of MET via diverse exon 14 splicing alterations occurs in multiple tumor types and confers clinical sensitivity to MET inhibitors. Cancer Discov. 2015;5:850–859. doi: 10.1158/2159-8290.CD-15-0285. [DOI] [PubMed] [Google Scholar]
  • 55.Seo JS, Ju YS, Lee WC, Shin JY, Lee JK, Bleazard T, et al. The transcriptional landscape and mutational profile of lung adenocarcinoma. Genome Res. 2012;22:2109–2119. doi: 10.1101/gr.145144.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Cancer Genome Atlas Research Network Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511:543–550. doi: 10.1038/nature13385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Onozato R, Kosaka T, Kuwano H, Sekido Y, Yatabe Y, Mitsudomi T. Activation of MET by gene amplification or by splice mutations deleting the juxtamembrane domain in primary resected lung cancers. J Thorac Oncol. 2009;4:5–11. doi: 10.1097/JTO.0b013e3181913e0e. [DOI] [PubMed] [Google Scholar]
  • 58.Kawano O, Sasaki H, Endo K, Suzuki E, Haneda H, Yukiue H, et al. PIK3CA mutation status in Japanese lung cancer patients. Lung Cancer. 2006;54:209–215. doi: 10.1016/j.lungcan.2006.07.006. [DOI] [PubMed] [Google Scholar]
  • 59.Yamamoto H, Shigematsu H, Nomura M, Lockwood WW, Sato M, Okumura N, et al. PIK3CA mutations and copy number gains in human lung cancers. Cancer Res. 2008;68:6913–6921. doi: 10.1158/0008-5472.CAN-07-5084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Qian Y, Chai S, Liang Z, Wang Y, Zhou Y, Xu X, et al. KIF5B-RET fusion kinase promotes cell growth by multilevel activation of STAT3 in lung cancer. Mol Cancer. 2014;13:176. doi: 10.1186/1476-4598-13-176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Shaw AT, Ou SH, Bang YJ, Camidge DR, Solomon BJ, Salgia R, et al. Crizotinib in ROS1-rearranged non-small-cell lung cancer. N Engl J Med. 2014;371:1963–1971. doi: 10.1056/NEJMoa1406766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Wang R, Hu H, Pan Y, Li Y, Ye T, Li C, et al. RET fusions define a unique molecular and clinicopathologic subtype of non-small-cell lung cancer. J Clin Oncol. 2012;30:4352–4359. doi: 10.1200/JCO.2012.44.1477. [DOI] [PubMed] [Google Scholar]
  • 63.Liu L, Shao X, Gao W, Bai J, Wang R, Huang P, et al. The role of human epidermal growth factor receptor 2 as a prognostic factor in lung cancer: a meta-analysis of published data. J Thorac Oncol. 2010;5:1922–1932. doi: 10.1097/JTO.0b013e3181f26266. [DOI] [PubMed] [Google Scholar]
  • 64.Spoerke JM, O'Brien C, Huw L, Koeppen H, Fridlyand J, Brachmann RK, et al. Phosphoinositide 3-kinase (PI3K) pathway alterations are associated with histologic subtypes and are predictive of sensitivity to PI3K inhibitors in lung cancer preclinical models. Clin Cancer Res. 2012;18:6771–6783. doi: 10.1158/1078-0432.CCR-12-2347. [DOI] [PubMed] [Google Scholar]
  • 65.Zhang L, Shi L, Zhao X, Wang Y, Yue W. PIK3CA gene mutation associated with poor prognosis of lung adenocarcinoma. Onco Targets Ther. 2013;6:497–502. doi: 10.2147/OTT.S41643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Chaft JE, Arcila ME, Paik PK, Lau C, Riely GJ, Pietanza MC, et al. Coexistence of PIK3CA and other oncogene mutations in lung adenocarcinoma-rationale for comprehensive mutation profiling. Mol Cancer Ther. 2012;11:485–491. doi: 10.1158/1535-7163.MCT-11-0692. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Wang L, Hu H, Pan Y, Wang R, Li Y, Shen L, et al. PIK3CA mutations frequently coexist with EGFR/KRAS mutations in non-small cell lung cancer and suggest poor prognosis in EGFR/KRAS wildtype subgroup. PLoS One. 2014;9:e88291. doi: 10.1371/journal.pone.0088291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Lee GD, Lee SE, Oh DY, Yu DB, Jeong HM, Kim J, et al. MET exon 14 skipping mutations in lung adenocarcinoma: clinicopathologic implications and prognostic values. J Thorac Oncol. 2017;12:1233–1246. doi: 10.1016/j.jtho.2017.04.031. [DOI] [PubMed] [Google Scholar]
  • 69.Awad MM, Oxnard GR, Jackman DM, Savukoski DO, Hall D, Shivdasani P, et al. MET exon 14 mutations in non-small-cell lung cancer are associated with advanced age and stage-dependent MET genomic amplification and c-met overexpression. J Clin Oncol. 2016;34:721–730. doi: 10.1200/JCO.2015.63.4600. [DOI] [PubMed] [Google Scholar]
  • 70.Zheng D, Wang R, Ye T, Yu S, Hu H, Shen X, et al. MET exon 14 skipping defines a unique molecular class of non-small cell lung cancer. Oncotarget. 2016;7:41691–41702. doi: 10.18632/oncotarget.9541. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1: (30.7KB, docx)

Table S1. Doublet EGFR mutations in 90 lung cancers. Table S2. Comparison of EGFR and KRAS mutated tumors. Table S3. Comparison of EGFR mutated and ALK rearranged tumors. Table S4. Comparison of KRAS mutated and ALK rearranged tumors. (DOCX 30 kb)

Data Availability Statement

The datasets supporting the conclusions of this article are available from the corresponding author on reasonable request.


Articles from Diagnostic Pathology are provided here courtesy of BMC

RESOURCES