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. 2019 Oct 25;21(2):170–177. doi: 10.1080/15384047.2019.1674070

Major challenges in accurate mutation detection of multifocal lung adenocarcinoma by next-generation sequencing

Tian Qiu 1,*, Weihua Li 1,*, Fanshuang Zhang 1, Bingning Wang 1, Jianming Ying 1,✉
PMCID: PMC7012153  PMID: 31651223

ABSTRACT

Background: Many patients with advanced non-small cell lung cancer manifested with metastasis, and molecular heterogeneity may exhibit between primary and metastatic tumors. We sought to investigate the clinical detection strategy of primary and metastatic tumors in Chinese patients with NSCLC.

Methods: Here, 77 paired tumors of Chinese patients with lung adenocarcinoma were analyzed, and 1836 mutation in hotspot regions of 22 genes were identified by next-generation sequencing. The expression of ALK in these paired tumors was also detected by immunohistochemistry.

Results: The results showed that the concordance rate in multiple pulmonary nodules, primary-LN metastasis pairs and primary-distant metastasis pairs was 67.7%, 94.1% and 86.7%, respectively. In multiple pulmonary nodules, the concordance rate was 100% when the pathologic diagnosis was intrapulmonary metastasis, whereas the concordance rate was 23.1% when the pathologic diagnosis was multiple primary tumors. TP53 and CTNNB1 mutations were detected as the recurrent alterations in LN metastasis. Moreover, the concordance of ALK status was observed in these pairs.

Conclusions: Our data suggested that hotspot mutations and ALK status in the primary-metastasis pairs had a high concordance in lung adenocarcinoma. Clinical detection of one lesion may be enough to identify the key alterations except that patients are diagnosed with multiple primary tumors or have disease progression after benefiting from target therapy.

KEYWORDS: Lung adenocarcinoma, mutation, next-generation sequencing, immunohistochemistry, tumor heterogeneity

Introduction

Lung cancer is one of the most common cancers in the world and has become the leading cause of cancer-related death in China.1,2 In 2015, about 0.73 million new lung cancer cases and 0.61 million deaths were estimated in China.3 Lung cancer can be further classified into two main types, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), according to histopathological diagnosis. NSCLC accounts for approximately 80–85% of lung cancer and includes adenocarcinoma, squamous-cell carcinoma, and large-cell carcinoma. Lung adenocarcinoma, comprising of more than 50% of NSCLC, is the most common histological subtype of NSCLC.4 Driver mutations in EGFR, KRAS, ALK, HER2, BRAF, MET, ROS1 and RET genes, have been observed in about 62% of lung adenocarcinoma. Target agents against these driver mutations have been studied and used both in experiment and clinic.5 For example, patients with lung adenocarcinoma harboring EGFR-sensitizing mutations benefits from EGFR tyrosine kinase inhibitors (TKIs) treatment.6 Moreover, ALK/MET/ROS1-positive lung adenocarcinoma patients gain impressive response rates after treatment with crizotinib.7,8 Therefore, molecular pathological diagnosis is recommended to determine eligibility for targeted therapy.9,10

However, a number of advanced lung adenocarcinoma exhibits two or more separate tumors, or presents with metastatic disease synchronously or metachronously. Inter- and intratumoral genetic heterogeneity has been reported in several tumors,11,12 which is considered as the major obstacle to accurate molecular pathological testing. Several studies have found that discrepancy in EGFR and KRAS mutation status between primary NSCLC and corresponding distant metastasis in western countries,13,14 however only a small set of biomarkers have been examined. Moreover, whether the primary tumor and metastasis are concordant at molecular level in Chinese lung adenocarcinoma patients is still unclear.

Next-generation sequencing (NGS) has been developed and widely used in clinical mutation detection.15 Screening of multiple genes with reasonable time and cost makes detecting specific gene panels of mutations known in the pathogenesis of lung adenocarcinoma achievable. Thus, it has an advantage in examination of concordant rate between primary and metastatic tumors.16 In our study, 77 paired tumors of Chinese patients with lung adenocarcinoma were analyzed, and 1836 hotspot mutations in 22 genes associated with lung tumor were identified by NGS. The expression of ALK in these paired tumors was also detected by IHC assay. The objectives of this study were to explore whether these hotspot mutations and ALK status are stable during metastatic progression. We hope our study may provide guidance on choosing suitable tumor samples for clinical molecular pathological detection of lung adenocarcinoma.

Results

Features of patients and ion torrent sequencing

The clinical and pathological characteristics of 51 patients with lung adenocarcinoma were listed in Supplementary Table 1. Among these patients, 33 patients had primary tumor, matched intrapulmonary metastatic and LN metastatic tumors, 18 patients had primary tumor and LN metastatic tumor. In total, 77 paired tumors were divided into three groups: the multiple pulmonary nodules (44 pairs), the primary-LN metastasis pairs (26 pairs) and the primary-distant metastasis pairs (7 pairs). The multiple pulmonary nodules and primary-LN metastasis pairs were synchronous, whereas the primary tumors and paired distant metastasis were metachronous. All samples were analyzed by Ion Torrent sequencing (Supplementary Figure 1A and 1B).

Analysis of hotspot mutations in multiple pulmonary nodules

Firstly, the hotspot mutations in 44 multiple pulmonary nodules were examined. Among these pairs, 24 pairs located in same lobe, 19 pairs located in different lobes of ipsilateral lung, 1 pair located in different lobes of contralateral lung. As shown in Table 1, the concordance rate was 67.7%. However, we found that identical mutational status was observed in 30 pairs which were diagnosed as primary cancer and matched intrapulmonary metastasis, whereas the concordance rate was 23.1% in 14 pairs which were diagnosed as multiple primary cancers (Table 2). The genetic alteration profile is shown in Figure 1.

Table 1.

Hotspot mutations in primary tumor and distant metastasis.

  Mutations in primary tumor
 Mutations in distant metastasis
  
Patient Gene cDNA mutation Protein mutation Gene cDNA mutation Protein mutation Metastatic Site
45 EGFR 2238_2252del15 L747_T751delLREAT EGFR 2238_2252del15 L747_T751delLREAT Brain
  TP53 742C>G R248G TP53 742C>G R248G  
46 TP53 856G>A E286K EGFR 2237_2251del15 E746_T751 > A Brain
  EGFR 2237_2251del15 E746_T751 > A TP53 856G>A E286K  
  CTNNB1 101G>A G34E CTNNB1 101G>A G34E  
47 EGFR 2237_2251del15 E746_T751 > A WT     Brain
48 EGFR 2239_2256del18 L747_S752delLREATS EGFR 2239_2256del18 L747_S752delLREATS Brain
  TP53 396G>C K132N TP53 396G>C K132N  
  STK11 1062C>G F354L STK11 1062C>G F354L  
49 STK11 1062C>G F354L STK11 1062C>G F354L Liver
  TP53 747G>T R249S TP53 747G>T R249S  
50 EGFR 2236_2250del15 E746_A750delELREA EGFR 2236_2250del15 E746_A750delELREA Adrenal gland
        EGFR 2369C>T T790M  
51 STK11 1062C>G F354L STK11 1062C>G F354L Adrenal gland
  TP53 725G>T C242F TP53 725G>T C242F  
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Table 2.

Concordance rate between primary tumor and matched metastasis.

  No. of mutation No. of shared pairs No. of unshared pairs Concordance Rate (%)
Multiple pulmonary nodules 62 42 20 67.7
Primary-LN metastasis pairs 34 32 2 94.1
Primary-distant metastasis pairs 15 13 2 86.7
Total 111 87 28 78.4
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Figure 1.

Figure 1.

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The genetic alteration profile of hotspot mutations in multiple pulmonary nodules. (A) The genetic alteration profile of separate tumor nodules in same lobe, (B) The genetic alteration profile of separate tumor nodules in different lobes of ipsilateral lung.

Analysis of hotspot mutations in primary and corresponding LN metastatic tumors

The mutations in 26 primary lung adenocarcinoma and corresponding LN metastasis were further detected. All these 26 patients presented with two separate nodules and were diagnosed with lung adenocarcinoma with intrapulmonary metastasis. The hotspot mutations of these 26 primary-intrapulmonary metastasis pairs were detected and no discordance mutations were observed. The LN metastasis was divided into two groups, N1 and N2. N1: Metastasis in ipsilateral peribronchial and/or ipsilateral hilar LN, and intrapulmonary LN. N2: Metastasis in ipsilateral mediastinal and/or subcarinal LN. Of the 26 primary-metastasis pairs, 24 pairs (92.3%) showed identical mutational status, including 4 primary-LN1 metastasis pairs, 19 primary-LN2 metastasis pairs, and 1 primary-LN1/2 metastasis pair. Eight of these 24 pairs (33.3%) showed no mutation while the remaining 16 pairs (66.7%) showed defining mutations (Table 3). Within the two pairs of demonstrating discordant mutations between the primary and the metastatic tumors, one discordant pair was primary-LN1 metastasis pair from patient 22. The primary and paired LN1 metastatic tumors both showed EGFR L858R mutation. However, the LN1 metastasis exerted CTNNB1 S37F mutation were not found in the primary tumor. Another discordant pair was primary-LN2 metastasis pair from patient 15. The primary and paired LN2 metastatic tumors both showed EGFR L858R mutation, whereas the LN2 metastasis exerted TP53 H168R mutation were not found in the primary tumor. The concordance rate between primary tumor and matched LN metastasis was 94.1% (Table 1).

Table 3.

Hotspot mutations in multiple pulmonary nodules.

  Mutations in tumor A
 Mutations in tumor B
  
Patient Gene cDNA mutation Protein mutation Gene cDNA mutation Protein mutation Pathologic diagnosis
Separate tumor nodules in same lobe
1 EGFR 2238_2252del15 L747_T751delLREAT EGFR 2238_2252del15 L747_T751delLREAT Metastasis
TP53 818G>T R273L TP53 818G>T R273L
2 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
3 TP53 743G>A R248Q TP53 743G>A R248Q Metastasis
4 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
PIK3CA 3139C>T H1047Y PIK3CA 3139C>T H1047Y
5 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA Metastasis
CTNNB1 133T>C S45P CTNNB1 133T>C S45P
CTNNB1 130C>G P44A CTNNB1 130C>G P44A
6 EGFR 2125G>A E709K EGFR 2125G>A E709K Metastasis
EGFR 2573T>G L858R EGFR 2573T>G L858R
TP53 722C>T S241F TP53 722C>T S241F
7 EGFR 2236_2250del15 E746_A750delELREA EGFR 2236_2250del15 E746_A750delELREA Metastasis
8 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA Metastasis
PIK3CA 3140A>T H1047L PIK3CA 3140A>T H1047L
9 WT     WT     Metastasis
10 WT     WT     Metastasis
11 TP53 461G>T G154V TP53 461G>T G154V Metastasis
AKT1 49G>A E17K AKT1 49G>A E17K
12 WT     WT     Metastasis
31 EGFR 2235_2249del15 E746_A750delELREA EGFR 2609A>G H870R Multiple primary
32 WT     WT     Multiple primary
33 EGFR 2573T>G L858R EGFR 2156G>C G719A Multiple primary
34 EGFR 2573T>G L858R EGFR 2573T>G L858R Multiple primary
35 EGFR 2236_2250del15 E746_A750delELREA EGFR 2236_2250del15 E746_A750delELREA Multiple primary
36 EGFR 2236_2250del15 E746_A750delELREA KRAS 34G>T G12C Multiple primary
38 EGFR 2236_2250del15 E746_A750delELREA EGFR 2236_2250del15 E746_A750delELREA Multiple primary
39 TP53 660T>G Y220* WT     Multiple primary
EGFR 2573T>G L858R      
40 KRAS 35G>C G12A BRAF 1742A>G N581S Multiple primary
      PIK3CA 1635G>T E545D
42 HER2 2322_2323insGCATACGTGATG M774_A775insAYVM EGFR 2239_2257 > T L747_P753 > S Multiple primary
43 WT     WT     Multiple primary
44 EGFR 2155G>T G719C EGFR 2303G>T S768I Multiple primary
EGFR 2303G>T S768I EGFR 2156G>C G719A
PIK3CA 1633G>A E545K      
Separate tumor nodules in different lobes of ipsilateral lung
13 WT     WT     Metastasis
14 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
TP53 743G>A R248Q TP53 743G>A R248Q
15 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
16 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA Metastasis
TP53 637C>T R213* TP53 637C>T R213*
TP53 396G>T K132N TP53 396G>T K132N
17 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA Metastasis
18 EGFR 2239_2256del18 L747_S752delLREATS EGFR 2239_2256del18 L747_S752delLREATS Metastasis
19 WT     WT     Metastasis
20 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA Metastasis
21 WT     WT     Metastasis
22 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
23 TP53 536A>G H179R TP53 536A>G H179R Metastasis
24 EGFR 2303G>T S768I EGFR 2303G>T S768I Metastasis
EGFR 2156G>C G719A EGFR 2156G>C G719A
25 EGFR 2310_2311insACA 770D_771NinsT EGFR 2310_2311insACA 770D_771NinsT Metastasis
26 EGFR 2253_2276del24 S752_I759delSPKANKEI EGFR 2253_2276del24 S752_I759delSPKANKEI Metastasis
27 WT     WT     Metastasis
28 WT     WT     Metastasis
29 TP53 722C>G S241C TP53 722C>G S241C Metastasis
37 KRAS 34G>A G12S KRAS 35G>A G12D Multiple primary
41 STK11 1062C>G F354L EGFR 2238_2252del15 L747_T751delLREAT Multiple primary
BRAF 1406G>C G469A STK11 1062C>G F354L
      TP53 839G>T R280I
Separate tumor nodules in contralateral lung
30 EGFR 2573T>G L858R EGFR 2573T>G L858R Metastasis
TP53 747G>T R249S TP53 747G>T R249S
STK11 1062C>G F354L STK11 1062C>G F354L
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Analysis of hotspot mutations in primary and distant metastatic tumors

Next, we examined the mutational concordance of 7 primary-distant metastasis pairs, including 4 primary-brain metastasis pairs, 1 primary-liver metastasis pair and 2 primary-adrenal gland metastasis pairs. All the 7 patients received chemotherapy therapy after resection of the primary tumors, and 2 patients received EGFR-targeted therapy (gefitinib) at the same time. The time interval between resection of the primary and the corresponding metastatic tumor was ranged from 7 to 44 months. Of these 7 pairs, 5 pairs (71.4%) showed identical mutational status, whereas 2 pairs (28.6%) showed discordant mutational status between the primary and metastatic tumors (Table 4). The first discordant pair was the brain metastasis from patient 47. The primary tumor had EGFR E746_T751 > A mutation which was not identified in the metastatic tumor. The second discordant pair was from patient 50. The primary and paired adrenal gland metastatic tumors both showed EGFR E746_A750delELREA mutation. However, the adrenal gland metastasis exerted EGFR T790M mutation was not found in the primary tumor. Both patient 47 and patient 50 received EGFR-targeted therapy (gefitinib) after resection of the primary tumors, indicating that discordant mutations were more common in patients with EGFR-targeted therapy (p = .048). The concordance rate of gene mutation between primary tumor and matched distant metastasis was 86.7% (Table 1).

Table 4.

Hotspot mutations in primary tumor and LN metastasis.

Patient Mutations in primary tumor
 Mutations in metastatic LN (N1)
 Mutations in metastatic LN (N2)
Gene cDNA mutation Protein mutation Gene cDNA mutation Protein mutation Gene cDNA mutation Protein mutation
1 EGFR 2238_2252del15 L747_T751delLREAT -     EGFR 2238_2252del15 L747_T751delLREAT
  TP53 818G>T R273L       TP53 818G>T R273L
2 EGFR 2573T>G L858R -     EGFR 2573T>G L858R
3 TP53 743G>A R248Q -     TP53 743G>A R248Q
4 EGFR 2573T>G L858R -     EGFR 2573T>G L858R
  PIK3CA 3139C>T H1047Y       PIK3CA 3139C>T H1047Y
5 EGFR 2235_2249del15 E746_A750delELREA EGFR 2235_2249del15 E746_A750delELREA -    
  CTNNB1 133T>C S45P CTNNB1 133T>C S45P      
  CTNNB1 130C>G P44A CTNNB1 130C>G P44A      
6 EGFR 2125G>A E709K EGFR 2125G>A E709K -    
  EGFR 2573T>G L858R EGFR 2573T>G L858R      
  TP53 722C>T S241F TP53 722C>T S241F      
7 EGFR 2236_2250del15 E746_A750delELREA EGFR 2236_2250del15 E746_A750delELREA -    
9 WT     -     WT    
10 WT     -     WT    
11 TP53 461G>T G154V -     TP53 461G>T G154V
  AKT1 49G>A E17K       AKT1 49G>A E17K
12 WT     -     WT    
14 EGFR 2573T>G L858R -     EGFR 2573T>G L858R
  TP53 743G>A R248Q       TP53 743G>A R248Q
15 EGFR 2573T>G L858R -     EGFR 2573T>G L858R
              TP53 503A>G H168R
16 EGFR 2235_2249del15 E746_A750delELREA -     EGFR 2235_2249del15 E746_A750delELREA
  TP53 637C>T R213*       TP53 637C>T R213*
  TP53 396G>T K132N       TP53 396G>T K132N
17 EGFR 2235_2249del15 E746_A750delELREA -     EGFR 2235_2249del15 E746_A750delELREA
18 EGFR 2239_2256del18 L747_S752delLREATS -     EGFR 2239_2256del18 L747_S752delLREATS
19 WT     -     WT    
21 WT     -     WT    
22 EGFR 2573T>G L858R EGFR 2573T>G L858R      
        CTNNB1 110C>T S37F      
23 TP53 536A>G H179R -     TP53 536A>G H179R
24 EGFR 2303G>T S768I -     EGFR 2303G>T S768I
  EGFR 2156G>C G719A       EGFR 2156G>C G719A
26 EGFR 2253_2276del24 S752_I759delSPKANKEI -     EGFR 2253_2276del24 S752_I759delSPKANKEI
27 WT     WT     -    
28 WT     -     WT    
29 TP53 722C>G S241C -     TP53 722C>G S241C
  EGFR 2573T>G L858R EGFR 2573T>G L858R EGFR 2573T>G L858R
30 TP53 747G>T R249S TP53 747G>T R249S TP53 747G>T R249S
  STK11 1062C>G F354L STK11 1062C>G F354L STK11 1062C>G F354L
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Comparison of the ALK status in matched tumors by IHC analysis

ALK status in 34 tumors was detected by IHC analysis, since ALK rearrangement cannot be detected by the Ion Ampliseq Colon and Lung Cancer Panel. ALK-positive was observed in 3 patients (8.8%). All the 3 ALK-positive patients (Patient 33, 41 and 42) presented with intrapulmonary metastasis and LN metastasis, and identical ALK-positive was observed in the primary tumor, paired intrapulmonary and LN metastasis (Figure 2).

Figure 2.

Figure 2.

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Concordance of ALK-positive was observed in the primary and metastatic tumors of patient with lung adenocarcinoma. ALK staining was observed in the cytoplasm of the cancer cells in (A) primary tumor, (B) paired intrapulmonary metastasis and (C) LN metastasis.

EGFR, BRAF, HER2 and c-MET IHC analysis

EGFR, BRAF, HER2 and c-MET IHC analysis was performed in 23 tumors. EGFR-19DEL, EGFR-L858R, BRAF-V600E, HER2 and c-MET was expressed in 8 (34.8%), 10 (43.5%), 1 (4.3%), 15 (65.2%), 20 (87.0%) tumors, respectively.

Discussion

Precision medicine for the management of advanced lung cancer has markedly developed, and targeted therapies are personalized based on driver mutations found in individual patients. Thus, precise molecular pathological diagnosis is necessary. Recently, NGS has been widely used to determine the driver mutations of lung cancer in clinical mutation detection.17 However, many patients with advanced lung adenocarcinoma have two or more tumor nodules. Sometimes, only biopsies from primary or metastatic tumor were available in patients with metastatic lung adenocarcinoma. Studies have reported that tumors can exhibit heterogeneity at the molecular level within the same tumor or between different metastatic sites.18,19 Thus, are there high discrepancies of gene mutations between primary tumor and metastasis? Should we detect the mutational status of all the separate tumor nodules in our clinical mutation testing? Some studies have found that high concordance of hotspot mutations between primary tumor and paired metastasis of western patients diagnosed with breast cancer, colon cancer and NSCLC using NGS,16,20 but little is known about Chinese patients. Therefore, we here addressed these questions in Chinese patients with lung adenocarcinoma in order to provide important information for the guidance of clinical mutation detection.

Our findings suggested that the total concordant rate of hotspot mutations is 78.4%, including more than three quarters of pairs with at least one mutation. The concordance rate in multiple pulmonary nodules, primary-LN metastasis pairs and primary-distant metastasis pairs was 67.7%, 94.1% and 86.7%, respectively. The incidence of synchronous multiple tumor nodules in lung is increasing these years.21 In this study, the mutations in 44 multiple pulmonary nodules were examined, and the concordance rate was 67.7%. Identical mutational status was observed in 30 pairs (the concordance rate was 100%), which were diagnosed as primary cancer and matched intrapulmonary metastasis. The results suggest that detection of one lesion is enough for lung adenocarcinoma patients with intrapulmonary metastasis. However, the concordance rate is 23.1% in 14 pairs diagnosed as multiple primary cancers, suggesting that detection of all tumor nodules is necessary for lung adenocarcinoma patients with multiple primary cancers to understand the biology of the lung cancer. Moreover, our findings indicate that detection of driver mutations may be helpful for distinguishing between multiple primary cancers and intrapulmonary metastasis in patients with lung cancer.

In 26 primary-LN metastasis pairs, 2 pairs demonstrated the secondary mutation in LN metastasis. One was TP53 mutation, and the other was CTNNB1 mutation. TP53 is a well-known tumor suppressor gene. TP53 mutations have been reported to contribute to the proliferation and metastasis of cancer.22,23 The CTNNB1 gene encodes for the protein of β-catenin, a key player of the canonical Wnt signaling pathway.24 CTNNB1 mutations have been implicated in carcinogenesis and tumor development.25,26 TP53 and CTNNB1 mutations both play essential roles in facilitating tumor metastasis. Thus, it is understandable that heterogeneity of TP53 and CTNNB1 mutational status is observed between primary and metastatic tumors in our study. Lung adenocarcinoma patients with EGFR-sensitizing mutations are highly responsive to first-generation EGFR TKIs, including gefitinib and erlotinib.27 However, patients received EGFR TKI treatment eventually develop drug resistance due to various mechanisms, such as the secondary mutation and loss of EGFR-sensitizing mutations.28,29 In this study, discordant mutations were observed in two primary-distant metastasis pairs. One pair showed loss of EGFR-sensitizing mutation (Exon 19 deletion) in brain metastasis, while the other pair exerted a secondary EGFR mutation (T790M) in adrenal gland metastasis. Both patients received EGFR TKI treatment after surgery of primary tumor. These data suggest that clinical detection of metastatic tumor is needed and necessary for patients whose disease progression is observed after benefiting from EGFR TKI treatment.

The Ion Ampliseq Colon and Lung Cancer Panel is unavailable for detecting the ALK fusion of lung cancer. Therefore, we further detected ALK status by Ventana IHC assay, since our previous work had proved that IHC assay was reliable for identification of ALK rearrangement in routine detection.30 The results showed that concordance of ALK status was observed in all primary-metastasis pairs.

In summary, we compared the hotspot mutations between primary tumors and different metastatic sites in Chinese patients with lung adenocarcinoma. Using NGS, we identified a high rate of concordance for gene mutations in primary-metastasis pairs, whereas a low rate of concordance for gene mutations in multiple primary tumors. Our findings suggest that clinical mutation detection of all tumor lesions is recommended when separate pulmonary nodules are evaluated as multiple primary tumors or patients show disease progression after benefiting from target therapy.

Materials and methods

Patients and samples

All 51 patients with primary lung adenocarcinoma and corresponding metastasis were surgically resected at the Cancer Hospital, Chinese Academy of Medical Sciences (CAMS), Beijing, China, between August 2008 and March 2016. The protocol of our study was approved by the Institute Review Board of the Cancer Hospital, CAMS. Clinical and pathological characteristics of the patients were obtained in the medical records and listed in Supplementary Table 1. No patient received chemoradiotherapy or molecular targeted therapy before primary lung adenocarcinoma surgery. Each sample was fixed in 10% neutral buffered formalin for 24–48 h and embedded in paraffin. Hematoxylin and eosin-stained sections were reviewed. Tumor blocks contained more than 30% of tumor components were selected and used for DNA extraction.

Criteria for identification of metastasis

All metastatic tumors were diagnosed by the pathologist in clinical pathological diagnosis and reviewed by another pathologist with histopathological and immunohistochemical analysis. Intrapulmonary metastasis was distinguished from multiple primary lung cancers with the criteria reported by Detterbeck et al.31 Briefly, the characteristics of intrapulmonary metastasis were: (1) Matching appearance on histologic assessment; (2) The same biomarker pattern of IHC staining; (3) Presenting with other metastasis; (4) Exception of lepidic-predominant adenocarcinoma, minimally invasive adenocarcinoma or adenocarcinoma in situ. The characteristics of multiple primary lung cancers were: (1) Different appearance on histologic assessment; (2) Different biomarker pattern of IHC staining; (3) Absence of nodal or systemic metastasis.

Genomic DNA isolation

QIAamp DNA Mini Kit (Qiagen, Germany) were obtained to extract DNA from the selected tumor blocks, according to the manufacturer’s instructions. NanoDrop (Thermo, USA) was used to detect the quality of DNA samples, while the Quantus™ Fluorometer was used to determine the concentration of the DNA samples with the Qubit® dsDNA HS Assay Kit.

DNA library construction and emulsion PCR

DNA library was constructed using Ion Ampliseq Library Kit 2.0. In brief, 10 ng of DNA was used as the template, and amplicon library was generated using Ion Ampliseq Colon and Lung Cancer Panel. The panel included 1836 hotspot mutations in 22 known genes associated with colon and lung tumor. The genes included in the panel are listed as follows: KRAS, EGFR, BRAF, PIK3CA, AKT1, ERBB2, PTEN, NRAS, STK11, MAP2K1, ALK, DDR2, CTNNB1, MET, TP53, SMAD4, FBXW7, FGFR3, NOTCH1, ERBB4, FGFR1 and FGFR2. All hotspot mutations are genomic base substitutions and indels (deletion or insertion). Genomic regions were amplified by PCR using the 92 primer pairs, and then ligated to barcodes to enable sample multiplexing using the Ion Xpress Barcode Adapters Kit. Next, the library of each sample with distinct barcoding was mixed, and the mixed library was clonally amplified onto the IonSpheres (ISP). Finally, the ISPs were isolated on the Ion OneTouch system, using the Ion PGM(TM) Hi-Q(TM) OT2 Kit.

Sequencing and data analysis

Enriched ISPs were added onto a 318 Chip to sequence pooled libraries using Ion PGM HI-Q SEQ Kit, following the manufacturer’s instructions. Sequence data from genomic DNA was analyzed using Ion reporter and reviewed using the Integrative Genomics Viewer. Mutations were designated when the coverage depth ≥500 reads and variant frequency ≥5%. However, variant frequencies ≥1% but <5% were considered to be mutations if the same variant frequency ≥5% was observed in the corresponding tumor.

Immunohistochemistry

Immunohistochemistry (IHC) assay was performed on Ventana Benchmark XT stainer (Ventana Medical Systems, Tucson, AZ), with monoclonal primary antibodies against ALK and the OptiView DAB IHC detection kit for ALK, as previously described30 Negative and positive controls were also stained in each round of analysis. Presence of strong granular cytoplasmic staining in tumor cells (any percentage of positive tumor cells) was deemed to be ALK positive, while absence of strong granular cytoplasmic staining in tumor cells was deemed to be ALK negative. IHC for EGFR-19DEL, EGFR-L858R, BRAF-V600E, HER2 and c-MET was performed on Ventana Benchmark XT stainer (Ventana Medical Systems, Tucson, AZ), as previously reported. Detection of BRAF mutation in Chinese tumor patients using a highly sensitive antibody immunohistochemistry assay. Overexpression of mutant EGFR protein indicates a better survival benefit from EGFR-TKI therapy in non-small cell lung cancer.

Statistical analysis

The effect of EGFR-targeted therapy (gefitinib) on the mutational status of distant metastasis was analyzed by Fisher’s exact test.

Funding Statement

This work was supported by Central Public-interest Scientific Institution Basal Research Fund [grant number 2015PT320019] and the National Natural Science Foundation of China [grant number 21703290].

Disclosure Statement

The authors declare no conflict of interest.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Supplemental Material

References

  • 1.Miller KD, Siegel RL, Lin CC, Mariotto AB, Kramer JL, Rowland JH, Stein KD, Alteri R, Jemal A.. 2016. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 66:271–289. doi: 10.3322/caac.21349. [DOI] [PubMed] [Google Scholar]
  • 2.Siegel RL, Miller KD, Jemal A.. 2016. Cancer statistics, 2016. CA Cancer J Clin. 66:7–30. doi: 10.3322/caac.21332. [DOI] [PubMed] [Google Scholar]
  • 3.Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. 2016. Cancer statistics in China, 2015. CA Cancer J Clin. 66:115–132. doi: 10.3322/caac.21338. [DOI] [PubMed] [Google Scholar]
  • 4.Hong QY, Wu GM, Qian GS, Hu CP, Zhou JY, Chen LA, Li WM, Li SY, Wang K, Wang Q, et al. 2015. Prevention and management of lung cancer in China. Cancer. 121(Suppl 17):3080–3088. doi: 10.1002/cncr.29584 [DOI] [PubMed] [Google Scholar]
  • 5.Villaruz LC, Burns TF, Ramfidis VS, Socinski MA. 2013. Personalizing therapy in advanced non-small cell lung cancer. Semin Respir Crit Care Med. 34:822–836. doi: 10.1055/s-0033-1358552. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Riely GJ, Politi KA, Miller VA, Pao W. 2006. Update on epidermal growth factor receptor mutations in non-small cell lung cancer. Clin Cancer Res. 12:7232–7241. doi: 10.1158/1078-0432.CCR-06-0658. [DOI] [PubMed] [Google Scholar]
  • 7.Solomon BJ, Cappuzzo F, Felip E, Blackhall FH, Costa DB, Kim DW, Nakagawa K, Wu YL, Mekhail T, Paolini J, et al. 2016. Intracranial efficacy of crizotinib versus chemotherapy in patients with advanced ALK-positive non-small-cell lung cancer: results from PROFILE 1014. J Clin Oncol. 34:2858–2865. doi: 10.1200/JCO.2015.63.5888. [DOI] [PubMed] [Google Scholar]
  • 8.Shaw AT, Kim DW, Nakagawa K, Seto T, Crino L, Ahn MJ, De Pas T, Besse B, Solomon BJ, Blackhall F, et al. 2013. Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. N Engl J Med. 368:2385–2394. doi: 10.1056/NEJMoa1214886. [DOI] [PubMed] [Google Scholar]
  • 9.Leighl NB, Rekhtman N, Biermann WA, Huang J, Mino-Kenudson M, Ramalingam SS, West H, Whitlock S, Somerfield MR. 2014. Molecular testing for selection of patients with lung cancer for epidermal growth factor receptor and anaplastic lymphoma kinase tyrosine kinase inhibitors: American society of clinical oncology endorsement of the College of American Pathologists/International Association for the study of lung cancer/association for molecular pathology guideline. J Clin Oncol. 32:3673–3679. doi: 10.1200/JCO.2014.57.3055. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Lindeman NI, Cagle PT, Beasley MB, Chitale DA, Dacic S, Giaccone G, Jenkins RB, Kwiatkowski DJ, Saldivar JS, Squire J, et al. 2013. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American pathologists, international association for the study of lung cancer, and association for molecular pathology. J Thorac Oncol. 8:823–859. doi: 10.1097/JTO.0b013e318290868f. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Sankin A, Hakimi AA, Mikkilineni N, Ostrovnaya I, Silk MT, Liang Y, Mano R, Chevinsky M, Motzer RJ, Solomon SB, et al. 2014. The impact of genetic heterogeneity on biomarker development in kidney cancer assessed by multiregional sampling. Cancer Med. 3:1485–1492. doi: 10.1002/cam4.293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Jesinghaus M, Pfarr N, Kloor M, Endris V, Tavernar L, Muckenhuber A, von Knebel Doeberitz M, Penzel R, Weichert W, Stenzinger A. 2016. Genetic heterogeneity in synchronous colorectal cancers impacts genotyping approaches and therapeutic strategies. Genes Chromosomes Cancer. 55:268–277. doi: 10.1002/gcc.22330. [DOI] [PubMed] [Google Scholar]
  • 13.Mansuet-Lupo A, Zouiti F, Alifano M, Tallet A, Charpentier MC, Ducruit V, Devez F, Lemaitre F, Laurent-Puig P, Damotte D, et al. 2014. Intratumoral distribution of EGFR mutations and copy number in metastatic lung cancer, what impact on the initial molecular diagnosis? J Transl Med. 12:131. doi: 10.1186/1479-5876-12-131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Cortot AB, Italiano A, Burel-Vandenbos F, Martel-Planche G, Hainaut P. 2010. KRAS mutation status in primary nonsmall cell lung cancer and matched metastases. Cancer. 116:2682–2687. doi: 10.1002/cncr.25014. [DOI] [PubMed] [Google Scholar]
  • 15.Singh RR, Patel KP, Routbort MJ, Reddy NG, Barkoh BA, Handal B, Kanagal-Shamanna R, Greaves WO, Medeiros LJ, Aldape KD, et al. 2013. Clinical validation of a next-generation sequencing screen for mutational hotspots in 46 cancer-related genes. J Mol Diagn. 15:607–622. doi: 10.1016/j.jmoldx.2013.05.003. [DOI] [PubMed] [Google Scholar]
  • 16.Goswami RS, Patel KP, Singh RR, Meric-Bernstam F, Kopetz ES, Subbiah V, Alvarez RH, Davies MA, Jabbar KJ, Roy-Chowdhuri S, et al. 2015. Hotspot mutation panel testing reveals clonal evolution in a study of 265 paired primary and metastatic tumors. Clin Cancer Res. 21:2644–2651. doi: 10.1158/1078-0432.CCR-14-2391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Friedman AA, Letai A, Fisher DE, Flaherty KT. 2015. Precision medicine for cancer with next-generation functional diagnostics. Nat Rev Cancer. 15:747–756. doi: 10.1038/nrc4015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Jiang JK, Chen YJ, Lin CH, Yu IT, Lin JK. 2005. Genetic changes and clonality relationship between primary colorectal cancers and their pulmonary metastases–an analysis by comparative genomic hybridization. Genes Chromosomes Cancer. 43:25–36. doi: 10.1002/gcc.20167. [DOI] [PubMed] [Google Scholar]
  • 19.Harbst K, Staaf J, Masback A, Olsson H, Ingvar C, Vallon-Christersson J, Ringner M, Borg A, Jonsson G. Multiple metastases from cutaneous malignant melanoma patients may display heterogeneous genomic and epigenomic patterns. Melanoma Res. 2010;20:381–391. [PubMed] [Google Scholar]
  • 20.Vignot S, Frampton GM, Soria JC, Yelensky R, Commo F, Brambilla C, Palmer G, Moro-Sibilot D, Ross JS, Cronin MT, et al. 2013. Next-generation sequencing reveals high concordance of recurrent somatic alterations between primary tumor and metastases from patients with non-small-cell lung cancer. J Clin Oncol. 31:2167–2172. doi: 10.1200/JCO.2012.47.7737. [DOI] [PubMed] [Google Scholar]
  • 21.Klempner SJ, Ou SH, Costa DB, VanderLaan PA, Sanford EM, Schrock A, Gay L, Ali SM, Miller VA. 2015. The clinical use of genomic profiling to distinguish intrapulmonary metastases from synchronous primaries in non-small-cell lung cancer: a mini-review. Clin Lung Cancer. 16:334–339 e1. doi: 10.1016/j.cllc.2015.03.004. [DOI] [PubMed] [Google Scholar]
  • 22.Powell E, Piwnica-Worms D, Piwnica-Worms H. 2014. Contribution of p53 to metastasis. Cancer Discov. 4:405–414. doi: 10.1158/2159-8290.CD-13-0136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Mogi A, Kuwano H. 2011. TP53 mutations in nonsmall cell lung cancer. J Biomed Biotechnol. 2011:583929. doi: 10.1155/2011/583929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Jamieson C, Sharma M, Henderson BR. 2014. Targeting the beta-catenin nuclear transport pathway in cancer. Semin Cancer Biol. 27:20–29. doi: 10.1016/j.semcancer.2014.04.012. [DOI] [PubMed] [Google Scholar]
  • 25.Wang H, Zhou H, Liu A, Guo X, Yang CS. 2015. Genetic analysis of colon tumors induced by a dietary carcinogen PhIP in CYP1A humanized mice: identification of mutation of beta-catenin/Ctnnb1 as the driver gene for the carcinogenesis. Mol Carcinog. 54:1264–1274. doi: 10.1002/mc.22199. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Laskin WB, Lasota JP, Fetsch JF, Felisiak-Golabek A, Wang ZF, Miettinen M. 2015. Intranodal palisaded myofibroblastoma: another mesenchymal neoplasm with CTNNB1 (beta-catenin gene) mutations: clinicopathologic, immunohistochemical, and molecular genetic study of 18 cases. Am J Surg Pathol. 39:197–205. doi: 10.1097/PAS.0000000000000299. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ahsan A. 2016. Mechanisms of resistance to EGFR tyrosine kinase inhibitors and therapeutic approaches: an update. Adv Exp Med Biol. 893:137–153. doi: 10.1007/978-3-319-24223-1_7. [DOI] [PubMed] [Google Scholar]
  • 28.Huang L, Fu L. 2015. Mechanisms of resistance to EGFR tyrosine kinase inhibitors. Acta Pharm Sin B. 5:390–401. doi: 10.1016/j.apsb.2015.07.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Tabara K, Kanda R, Sonoda K, Kubo T, Murakami Y, Kawahara A, Azuma K, Abe H, Kage M, Yoshinaga A, et al. 2012. Loss of activating EGFR mutant gene contributes to acquired resistance to EGFR tyrosine kinase inhibitors in lung cancer cells. PLoS One. 7:e41017. doi: 10.1371/journal.pone.0041017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Ying J, Guo L, Qiu T, Shan L, Ling Y, Liu X, Lu N. 2013. Diagnostic value of a novel fully automated immunochemistry assay for detection of ALK rearrangement in primary lung adenocarcinoma. Ann Oncol. 24:2589–2593. doi: 10.1093/annonc/mdt295. [DOI] [PubMed] [Google Scholar]
  • 31.Detterbeck FC, Franklin WA, Nicholson AG, Girard N, Arenberg DA, Travis WD, Mazzone PJ, Marom EM, Donington JS, Tanoue LT, et al. 2016. The IASLC lung cancer staging project: background data and proposed criteria to distinguish separate primary lung cancers from metastatic foci in patients with two lung tumors in the forthcoming eighth edition of the TNM classification for lung cancer. J Thorac Oncol. 11:651–665. doi: 10.1016/j.jtho.2016.01.025. [DOI] [PubMed] [Google Scholar]

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