Open Access

Next‑generation sequencing‑based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her‑2 and TP53 mutations in patients with non‑small cell lung cancer

  • Authors:
    • Changwen Jing
    • Xuhua Mao
    • Zhuo Wang
    • Kejing Sun
    • Rong Ma
    • Jianzhong Wu
    • Haixia Cao
  • View Affiliations

  • Published online on: June 22, 2018     https://doi.org/10.3892/mmr.2018.9210
  • Pages: 2191-2197
  • Copyright: © Jing et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

In recent years, the incidence of non‑small cell lung cancer (NSCLC) has become the highest lethal rate of cancer worldwide. Molecular assays of EGFR, KRAS, BRAF, NRAS, PIK3CA and Her‑2 are widely used to guide individualized treatment in NSCLC patients. Somatic mutations in 112 NSCLC patients, including 7 oncogenic driver genes, were detected by Iontorrent personal genome machine (PGM). Sanger sequencing was used to test and verify the results of PGM. Apart from uncommon mutations of EGFR, 101 NSCLC specimens were tested by droplet digital PCR (ddPCR). According to NGS results, mutations were detected in EGFR (58/112, 51.79% of tumors), KRAS (10/112, 8.93%), BRAF (2/112, 1.79%), NRAS (2/112, 1.79%), Her‑2 (2/112, 1.79%), PIK3CA (6/112, 5.36%) and TP53 (31/112, 27.69%). There were 27 samples without any somatic mutations in all genes while 24 samples harboured mutations in two or more genes. A total of 61 samples had one or more mutations in a single gene. All alterations of 7 genes were presented and the overall detection rate of NGS and Sanger sequencing was determined to be 51.79% (58/112) and 37.50% (42/112), respectively (χ2=5.88, P=0.015). Compared with Sanger sequencing, the total sensitivity and specificity of NGS assays was 95.24% (40/42) and 77.14% (54/70), respectively. The overall detection rate of NGS and ddPCR was 45.54% (46/101) and 47.52% (48/101), respectively (χ2=0.000598, P=0.98). Compared with ddPCR, the overall sensitivity and specificity of NGS assays was 95.83% (46/48) and 98.11% (52/53), respectively. The findings indicated that the positive mutation rate of EGFR tested by NGS was significantly lower than that by Sanger sequencing, but the difference between ddPCR and NGS was not statistically significant. The high degree of agreement of reportable variants is proposed in both NGS and ddPCR analysis, suggesting the performance of NGS assays in routine clinical detection may be useful in determining the treatment decisions in NSCLC patients.

Introduction

Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer, accounting for about 80–85% of total lung cancer. In recent years, the incidence of NSCLC continues to increase and has become the highest lethal rate of cancer all over the world (1). The application of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib, has improved the treatment of NSCLC (2). Detection of sensitive mutations to EGFR-TKIs has stimulated the interest in studying multiple oncogenic drivers. Previous results suggested that somatic mutations in EGFR, KRAS, BRAF, NRAS, PIK3CA, Her-2 and TP53 have been associated with efficacy of EGFR-TKIs, metastasis or overall survival (36). Therefore, molecular assays of EGFR, KRAS, BRAF, NRAS, PIK3CA and Her-2 are widely used to guide individualized treatment in NSCLC patients.

Commonly used technologies for oncogenic driver detection include direct sequencing, next-generation sequencing (NGS), amplification refractory mutation system (ARMS) and droplet digital PCR (ddPCR). Sanger sequencing is used as standard for detecting EGFR mutations because of accurate results and low throughput. However, it is limited by high cost, time consuming and low sensitivity, for detecting low frequency mutant alleles in a specimen mixed with normal alleles. ddPCR is a new generation of absolute quantification PCR technique, realizing the independent amplification and fluorescence reading of thousands of individual droplets in one well. It has an extremely high sensitivity (0.04%-0.1%) and each well can only detect one site, limiting its use in multiple assays (7). Next Generation Sequencing (NGS) is a method that can detect multiple genetic variations simultaneously and can detect tumor mutations efficiently and economically. The scientists had a blinded comparison of NGS and quantitative real-time PCR (qPCR) assays to detect mutations in EGFR, KRAS, PIK3CA and BRAF in Chinese patients with NSCLC. Sanger sequencing was used to verify the inconsistent results of qPCR and NGS assays. The high consistency between NGS and qPCR has shown clinical application prospects of NGS (8).

In the present study, we detect somatic mutations in NSCLC by a small panel including 7 genes using the Iontorrent personal genome machine (PGM), to evaluate the efficacy of NGS by comparison to ddPCR assay and Sanger sequencing.

Patients and methods

Patient characteristics

Non-small lung tumor tissues were obtained from 112 Chinese patients in Jiangsu Cancer Hospital (Nanjing, China) between June 2015 and June 2016. Clinical characteristics of all patients were recorded with detailed information summarized in Table I. The histological diagnosis of all samples was confirmed by the pathologists. TNM classification of malignant tumors was used to determine tumor stage. All patients participated in the study signed informed consent. The ethics approval was awarded by the Cancer Institute of Jiangsu Province Ethics Committee.

Table I.

Patient characteristics (n=112).

Table I.

Patient characteristics (n=112).

VariablesNumber of patients
Sex
  Male67
  Female45
Age
  <60 years35
  ≥60 years77
Histological type
  Adenocarcinoma82
  Squamous cell carcinoma24
  Adenosquamous carcinoma  1
  Others  5
Histopathological grading
  High-median33
  Low79
TNM staging
  I–II34
  III–IV78
DNA extraction from formalin-fixed paraffin-embedded (FFPE) tissue

Tumor-rich samples were obtained when the patient underwent surgery. DNA was extracted with DNA FFPE tissue kit (Omega, Norcross, GA, USA) according to the guidebook and the concentrations were detected by Qubit® 2.0 fluorometer dsDNA HS assay kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA).

Mutation analysis by NGS

The Lung panel (including BRAF, EGFR, KRAS, NRAS, PIK3CA, Her-2 and TP53) on Iontorrent system was generally provided by Thermo Fisher Scientific, Inc. DNA was extracted and purified after microdissection using Agencourt® AMPure XP beads (Beckman Coulter, Brea, CA, USA). After DNA concentration detection, 15 ng of DNA was then amplified, fragmented, ligated to adapters, barcoded, and clonally amplified onto beads to create DNA libraries, using Iontorrent ampliSeq kit 2.0 and IonXpress barcode adapters kit (Thermo Fisher Scientific, Inc.) by user guidebook. After quantification, library mixtures were amplified with Iontorrent Onetouch template kit (Thermo Fisher Scientific, Inc.) and enriched on Iontorrent Onetouch system according to the protocol. Finally, the library pool was sequenced with Iontorrent PGM sequencing supplies 200 v2 kit (Thermo Fisher Scientific, Inc.) using Iontorrent PGM system. The mutation site was analyzed by the Iontorrent variant caller plugin v4.0 according to the reference genome hg19. The threshold of mutation frequency for mutation was 1%. The overall median coverage of depth was >1000X. The sequencing coverage of amplicons is >1,000 and the uniformity was >90%.

Sanger sequencing

Firstly, PCR was performed in a PCR Amplifier (Biometra, GmbH, Göttingen, Germany) for Sanger sequencing. Primers used for exon 18–21 of EGFR were listed in Table II. Secondly, PCR products were purified by Axyprep PCR cleanup kit (Axygen, Hangzhou, China). Thirdly, sequencing reaction was performed with big dye terminator v3.1 (Thermo Fisher Scientific, Inc.). Finally, the products were denatured and analysed by a DNA sequencer (Applied Biosystems 3500; Thermo Fisher Scientific, Inc.). Sequencing analysis v5.4 software was used to analyze the results.

Table II.

Primers for direct sequencing.

Table II.

Primers for direct sequencing.

ExonPrimer nameSequence
18EGFR 18S F 5′-AGCATGGTGAGGGCTGAGGTGAC-3′
EGFR 18S R 5′-ATATACAGCTTGCAAGGACTCTGG-3′
19EGFR 19S F 5′-CCAGATCACTGGGCAGCATGTGGCACC-3′
EGFR 19S R 5′-AGCAGGGTCTAGAGCAGAGCAGCTGCC-3
20EGFR 20S F 5′-GATCGCATTCATGCGTCTTCACC-3′
EGFR 20S R 5′-TTGCTATCCCAGGAGCGCAGACC-3′
21EGFR 21S F 5′-TCAGAGCCTGGCATGAACATGACCCTG-3′
EGFR 21S R 5′-GGTCCCTGGTGTCAGGAAAATGCTGG-3′

[i] F, Forward; R, Reverse; EGFR, epidermal growth factor receptor.

Droplet digtal PCR

Genotypes with L858R, exon 19 deletion, T790M or G719S were conducted by ddPCR. 20 µl of PCR reaction mixtures were prepared. After droplets generation, the products were shifted to a 96-well plate for amplification. The amplified products were analyzed on QX200™ Droplet Digital PCR (BioRad Laboratories, Inc., Hercules, CA, USA). The samples which contained at least 2 droplets in the FAM positive area were called positive.

Statistical analysis

The ability of NGS and ddPCR platforms to detect EGFR mutations was analyzed using χ2 test with IBM SPSS Statistics for Windows (v19.0. IBM Corp., Armonk, NY, USA). P<0.05 represents statistically significant differences. All figures were produced with GraphPad Prism (v6.0; GraphPad Software, Inc., La Jolla, CA, USA).

Results

The patient mutation profile

There were 86 FFPE specimens, 26 fresh resection specimens, 13 fine needle aspiration specimens and 4 pleural effusion specimens. Finally, 17 specimens failed to pass quality control. The remaining 112 specimens were successful submitted to NGS. As shown in Fig. 1A, mutations were detected in EGFR (58/112, 51.79% of tumors), KRAS (10/112, 8.93%), BRAF (2/112, 1.79%), NRAS (2/112, 1.79%), Her-2 (2/112, 1.79%), PIK3CA (6/112, 5.36%) and TP53 (31/112, 27.69%). Fig. 1B showed that there were 27 samples without any somatic mutations in all genes while 24 samples harboured mutations in two or more genes. 61 samples had mutations in single gene. Concomitant EGFR and TP53 mutations accounted for 54.17% (13/24) of samples with multiply gene mutations including two specimens with triple gene alterations (EGFR, KRAS, TP53/EGFR, PIK3CA, TP53). There were 3 samples occupied KRAS and TP53 mutations. Concomitant TP53 and PIK3CA mutations occurred in 2 NSCLC patients. Doublet mutations of EGFR and PIK3CA, EGFR and KRAS, EGFR and NRAS, EGFR and Her-2, BRAF and TP53, BRAF and PIK3CA occurred in 1 NSCLC each.

Genetic alterations of 7 genes

EGFR mutations. All genetic alterations of EGFR gene were illustrated in Table III. Mutations were found in 6 samples in exon 18, 29 in exon 19 including 21 samples of 19 deletions, 2 in exon 20 and 34 in exon 21. There are 56 cases with EGFR mutations in adenocarcinoma and two in squamous cell carcinoma. Ten samples have doublet mutations in EGFR gene. The distribution of doublet EGFR mutations was one with L858R and E746_S752del, one with L858R and E746_A750del, one with C781S and E746_T751delinsE, one with L858R and V834L, one with L747_P753delinsS and T790M, one with E746_R748del and A750P, one with E746_R748del and K754E, one with E749Q and A750P and two with G719S and E709K. One sample harboured quadruple mutations with L861Q, L858R, E745_A750del and G729A.

Table III.

EGFR mutations detected by NGS.

Table III.

EGFR mutations detected by NGS.

ExonEGFR mutation siteProtein positionNumber of mutations
Exon 18c.2155G>Ap.G719S  3
c.2125G>Ap.E709K  2
c.2127_2129del p.E709_T710delinsD  1
Exon 19c.2245G>Cp.E749Q  1
c.2248G>Cp.A750P  5
c.2260A>Gp.K754E  1
c.2186G>Cp.G729A  1
c.2238_2252del p.E746_T751delinsE  3
c.2236_2244delp.E746_R748del  2
c.2239_2256delp.L747_S752del  1
c.2236_2250delp.E746_A750del  3
c.2236_2256delp.E746_S752del  1
c.2235_2249delp.E746_A750del  5
c.2236_2249delp.E746_A750del  1
c.2237_2251delp.E746fs  1
c.2240_2257del p.L747_P753delinsS  4
Exon 20c.2369C>Tp.T790M  1
c.2341T>Ap.C781S  1
Exon 21c.2573T>Gp.L858R30
c.2471G>Cp.G824A  1
c.2582T>Ap.L861Q  1
c.2588G>Ap.G863D  1
c.2500G>Tp.V834L  1

[i] NGS, next-generation sequencing.

KRAS mutations. KRAS, BRAF, Her-2, NRAS and PIK3CA mutations were shown in Table IV. Representative types of genetic alterations in KRAS were six, with all of these located in exon 2. One sample harboured doublet KRAS mutations with G12C and G12A.

Table IV.

KRAS, BRAF, Her-2, NRAS and PIK3CA mutations detected by NGS sequencing.

Table IV.

KRAS, BRAF, Her-2, NRAS and PIK3CA mutations detected by NGS sequencing.

GeneMutation siteProtein positionNumber of mutations
KRASc.34G>Tp.G12C2
c.37G>Tp.G13C1
c.35G>Ap.G12D4
c.34G>Ap.G12C1
c.35G>Tp.G12V2
c.35G>Cp.G12A1
BRAFc.1799T>Ap.V600E1
c.1854G>Tp.L618F1
Her-2c.2282C>Ap.P761H2
NRASc.99T>Gp.D33E1
c.35G>Ap.G12D1
PIK3CAc.1624G>Ap.E542K2
c.1633G>Ap.E545K3
c.3140A>Tp.H1047L2
TP53c.338G>Tp.G113V2
c.128G>Ap.R43H2
c.422G>Tp.R141L1
c.337G>Tp.G113C1
c.431C>Gp.A144G2
c.105delGp.Q35fs1
c.437C>Ap.P146H1
c.443G>Cp.R148T1
c.329G>Ap.C110Y1
c.335G>Ap.G112D2
c.422G>Ap.R141H1
c.98C>Gp.P33R5
c.415G>Tp.E139X1
c.326C>Tp.S109F1
c.448C>Tp.R150W1
c.320delAp.N107fs1
c.422G>Cp.R141P1
c.401G>Tp.G134V2
c.353 C>Tp.P118L1
c.419_439 delp.140_147 del1
c.436 C>Tp.P146S1
c.326 C>Ap.S109Y1
c.305 A>Cp.Y102S1
c.428 G>Tp.C143F1
c.424 G>Tp.V142F1

[i] NGS, next-generation sequencing.

BRAF mutations. Two samples carried BRAF mutations were p.V600E and p.L618F.

NRAS mutations. One patient carried NRAS D33E mutations plus EGFR 19 deletion while another patient carried NRAS G12D alteration.

Her-2 mutations. Both of the patients with Her-2 mutations were P761H mutation.

PIK3CA mutations. There were 6 cases of PIK3CA mutations, with 4 located in exon 9 and 2 in exon 20. One sample carried doublet PIK3CA mutations with E545K and E542K. The remaining patients with PIK3CA mutations all have other gene mutations such as BRAF, EGFR or TP53.

TP53 mutations. The tumour suppressor gene TP53 mutations are diverse. 25 classes of mutations occurred in Tp53.

Comparison of NGS, Sanger sequencing and ddPCR for detecting EGFR mutations

Sanger sequencing, as golden standard, were performed all 112 specimens. The overall detection rate of NGS and Sanger sequencing was 51.79% (58/112) and 37.50% (42/112), respectively (χ2=5.88, P=0.015). There were 18 samples owning low frequency of mutations according to NGS results. In 58 positive samples, 40 samples were identified both by NGS and Sanger sequencing. 16 mutation-positive samples in NGS results became negative by Sanger sequencing and two negative samples were identified as positive by Sanger sequencing (Table V). Compared to Sanger sequencing, the total sensitivity and specificity of NGS assays was 95.24% (40/42) and 77.14% (54/70), respectively. Fig. 2 showed that rare mutations with 19 deletion and E-20 c.2341T>A mutation were also found in Sanger sequencing. Apart from uncommon mutations of EGFR, ddPCR was conducted in 101 NSCLC specimens. As shown in Table VI, the overall positive rate of NGS and ddPCR was 45.54% (46/101) and 47.52% (48/101), respectively (χ2=0.000598, P=0.98). Compared to ddPCR, the overall sensitivity and specificity of NGS assays was 95.83% (46/48) and 98.11% (52/53), respectively. The advantages and disadvantages of the NGS, Sanger and ddPCR were presented in Table VII.

Table V.

Performance of NGS and Sanger sequencing platforms for detection of epidermal growth factor receptor mutation.

Table V.

Performance of NGS and Sanger sequencing platforms for detection of epidermal growth factor receptor mutation.

Sanger sequencing (+)Sanger sequencing (−)
NGS (+)4016
NGS (−)254

[i] NGS, next-generation sequencing.

Table VI.

Performance of NGS and ddPCR platforms for detection of EGFR mutation.

Table VI.

Performance of NGS and ddPCR platforms for detection of EGFR mutation.

VariableddPCR (+)ddPCR (−)
NGS (+)46  1
NGS (−)  252

[i] NGS, next-generation sequencing; ddPCR, droplet digital polymerase chain reaction.

Table VII.

Characteristics of the NGS, Sanger sequencing and ddPCR.

Table VII.

Characteristics of the NGS, Sanger sequencing and ddPCR.

FeaturesSanger sequencingddPCRNGS
Frequency quantityNoYesYes
Sensitivity10%0.04–0.1%0.1%
Coverage areaCommon/uncommon mutationsCommon mutationsCommon/uncommon mutations
Time for results2-3 days1 day2-3 days
Technical characteristicsHigh accuracy, only suitable for tissuesVery high sensitivity but questioned by false-positive errorHigh output

[i] NGS, next-generation sequencing; ddPCR, droplet digital polymerase chain reaction.

Discussion

In lung cancer, the mutational status of oncogenic driver can implicate the efficacy of EGFR-TKIs and future survival for patients. It has been reported that EGFR mutation status resulted in the structural changes in the tyrosine kinase domain of EGFR. The main types of EGFR mutations were in exon19 deletions and exon21 (L858R) (9). Consistent with previous research (10), more EGFR mutations were detected in adenocarcinomas compared with squamous cell carcinoma. The positive rate of EGFR was 68.29% (56/82) in adenocarcinoma vs. 8.33% (2/24) in squamous cell carcinoma. The patients with KRAS mutations may not respond to EGFR antibodies and EGFR kinase inhibitors (11). A study in 5125 samples from NSCLC patients revealed that 8.0% of KRAS mutations were located in exon 2 and exon 3 (12). In this investigation, all genetic alterations in KRAS were found in exon 2. The quantity of samples attributed to the different results. Moreover, additional targeted drugs for NSCLC patients include BRAF inhibitors. Melanomas with BRAF mutations have been reported to be highly sensitive to BRAF inhibitors (13). Dabrafenib, a BRAF inhibitor is currently undergoing phase 2 trial for treatment of V600E BRAF-mutant lung adenocarcinomas, which may become another new drug in individualized therapy for lung cancer patients. BRAF V600E mutated lung cancer is a genetically distinct subtype that occurs in 1.7% of non-small cell lung carcinomas and 2.3% among 646 adenocarcinomas (14). However, we found only 1 sample (1/112) with p.V600E and 1 with p.L618F. One of the BRAF-positive samples was also PIK3CA-mutated, and one had a TP53 mutation. HER2, a member of the human EGFR (ErbB) family, is a receptor tyrosine kinase is encoded by the Her-2 gene. It is involved in PI3K-Akt and MEK/ERK signaling pathways, associated with cell proliferation and migration (15). Her-2 mutations have been found in 2–4% of lung adenocarcinomas (16,17). The frequency of Her-2 mutation was 1.8% in our present studies, all in exon 19 mutations not exon 20. The results are different from the previous reports, probably due to geographical area and sample size.

Our investigation found 2 patients with three types of gene mutations and 22 patients with two types. It is rare that mutations in NRAS and KRAS occur along with other driver-driven genetic alterations. Although concomitant mutations of some double genes seem paradox theoretically, we found TKI-sensitive and TKI-resistant variants co-existed. Overlap mutations in driver genes may puzzle clinical doctors in making individualized treatment for lung cancer. The sensitivity analysis of these patients to EGFR-TKIs requires follow-up. Advanced lung cancer patients with EGFR mutations or KRAS mutations and PIK3CA mutations have a poor prognosis. Patients with concurrent PIK3CA and EGFR mutations can not benefit from EGFR-TKIs (18). One study reported the mutation characteristics of patients with stage 1b lung adenocarcinoma in China. The results showed that only one patient had EGFR T790M mutation and KRAS mutation. No other EGFR mutation coexisting with KRAS was found (19). We believe there will be more reports of concurrent mutations in driver genes in the future, and the clinical detection of multiple oncogene mutations can help determine the optimal treatment regimen.

High throughput sequencing has not only provided us with rich genetic information, but also greatly reduced the cost and time of sequencing, with high output and high resolution. This technology has been applied wildly in cancer research. Previous reports have shown that though the frequency of single gene mutations in lung cancer may be low, the mutation rate of multiple oncogenic driver genes was really high. Individuals with oncogenic driver gene mutations receiving targeted therapy lived longer (20). In this study, we carried out NGS in NSCLC patients to evaluate the efficacy of NGS by comparison to ddPCR assay and Sanger sequencing. Our results showed NGS-based methods have demonstrated performance sensitivity but low specificity of NGS due to 18 low frequency mutant specimens compared to Sanger sequencing. Among them, 16 specimens were EGFR wildtype by Sanger sequencing. In addition, the results of NGS and ddPCR test were highly consistent. The high clinical sensitivity and specificity support the routine use of NGS detection in clinical trials to promote the treatment of patients with lung cancer. The detection rate of NGS for EGFR was significantly higher than that of Sanger sequencing. However, there was no significant statistical difference between ddPCR and NGS results. Besides, NGS can detect both hotspot and non-hotspot mutations. In general, ddPCR diagnostic kits are commonly used to detect common mutations or hotspots. However, rare mutations in EGFR are also important for predicting the efficacy of EGFR-TKI drugs, so the identification of non-hotspot mutations is essential for clinical research and treatment (2,21). In EMSO 2017, AURA17 studies initiated by Zhou et al (22) demonstrated the objective response rates (ORR) of ochitinib in patients with T790M mutations detected by the three detection methods were 56% (Cobas; Roche Diagnostics, Basel, Switzerland), 64% (SuperARMS) and 56% ddPCR, respectively. Furthermore, ORR of ochitinib in patients without T790M mutations detected by Cobas and ddPCR was higher than that in positive patients. Whether there is false-negative and false-positive error made by ddPCR is also needed for further study. However, NGS has its limitation. In the process of high-throughput sequencing, there are many problems that need to be solved: the role of data in clinical diagnosis, storage and analysis of sequencing data, data security and information privacy.

In conclusion, our results show that NGS has the advantages of high sensitivity and multiplexed testing. More data should be required to evaluate sensitivity, stability and clinical applicability. Each detection method has its advantages and disadvantages. Practice is the sole criterion for testing truth, and the benefit of cancer patients after treatment is the only criterion for judging methods. Detection methods should complement each other to achieve balance and coexistence, maximizing benefit of patients. In daily work, Sanger sequencing and ddPCR, as supplement of NGS results, are suggested to confirm uncommon mutations and low frequency mutations, respectively.

Acknowledgements

Not applicable.

Funding

The present study was supported by the program from the Health Department of Jiangsu Province (grant no. Z201602) and from the Science Foundation of Jiangsu Province (grant no. BE2016795).

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

CJ, XM and ZW wrote the manuscript and designed the study. KS performed the ddCPR experiments. RM performed NGS and Sanger sequencing. JW and HC contributed to the design of the study. All authors read and approved the final version of the manuscript.

Ethics approval and consent to participate

The research using human tissue was approved by the Cancer Institute of Jiangsu Province Ethics Committee. All patients participated in the study signed informed consent.

Patient consent for publication

All patients participated in the study signed informed consent.

Competing interests

The authors declare that they have no competing interests.

References

1 

Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China, 2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI

2 

Baek JH, Sun JM, Min YJ, Cho EK, Cho BC, Kim JH, Ahn MJ and Park K: Efficacy of EGFR tyrosine kinase inhibitors in patients with EGFR-mutated non-small cell lung cancer except both exon 19 deletion and exon 21 L858R: A retrospective analysis in Korea. Lung Cancer. 87:148–154. 2015. View Article : Google Scholar : PubMed/NCBI

3 

Tomasini P, Serdjebi C, Khobta N, Metellus P, Ouafik L, Nanni I, Greillier L, Loundou A, Fina F, Mascaux C and Barlesi F: EGFR and KRAS Mutations Predict the incidence and outcome of brain metastases in non-small cell lung cancer. Int J Mol Sci. 17:pii: E2132. 2016. View Article : Google Scholar : PubMed/NCBI

4 

Smit E: BRAF mutations in non-small-cell lung cancer. J Thorac Oncol. 9:1594–1595. 2014. View Article : Google Scholar : PubMed/NCBI

5 

Scheffler M, Bos M, Gardizi M, König K, Michels S, Fassunke J, Heydt C, Künstlinger H, Ihle M, Ueckeroth F, et al: PIK3CA mutations in non-small cell lung cancer (NSCLC): Genetic heterogeneity, prognostic impact and incidence of prior malignancies. Oncotarget. 6:1315–1326. 2015. View Article : Google Scholar : PubMed/NCBI

6 

Lee SY, Jeon HS, Hwangbo Y, Jeong JY, Park JY, Lee EJ, Jin G, Shin KM, Yoo SS, Lee J, et al: The influence of TP53 mutations on the prognosis of patients with early stage non-small cell lung cancer may depend on the intratumor heterogeneity of the mutations. Mol Carcinog. 54:93–101. 2015. View Article : Google Scholar : PubMed/NCBI

7 

Zhu G, Ye X, Dong Z, Lu YC, Sun Y, Liu Y, McCormack R, Gu Y and Liu X: Highly sensitive droplet digital PCR method for detection of EGFR-activating mutations in plasma cell-free DNA from patients with advanced non-small cell lung cancer. J Mol Diagn. 17:265–272. 2015. View Article : Google Scholar : PubMed/NCBI

8 

Xu X, Yang Y, Li H, Chen Z, Jiang G and Fei K: Assessment of the clinical application of detecting EGFR, KRAS, PIK3CA and BRAF mutations in patients with non-small cell lung cancer using next-generation sequencing. Scand J Clin Lab Invest. 76:386–392. 2016. View Article : Google Scholar : PubMed/NCBI

9 

Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, Gemma A, Harada M, Yoshizawa H, Kinoshita I, et al: Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. Engl J Med. 362:2380–2388. 2010. View Article : Google Scholar

10 

Maheswaran S, Sequist LV, Nagrath S, Ulkus L, Brannigan B, Collura CV, Inserra E, Diederichs S, Iafrate AJ, Bell DW, et al: Detection of mutations in EGFR in circulating lung-cancer cells. Engl J Med. 359:366–377. 2008. View Article : Google Scholar

11 

Jackman DM, Miller VA, Cioffredi LA, Yeap BY, Jänne PA, Riely GJ, Ruiz MG, Giaccone G, Sequist LV and Johnson BE: Impact of epidermal growth factor receptor and KRAS mutations on clinical outcomes in previously untreated non-small cell lung cancer patients: Results of an online tumor registry of clinical trials. Clin Cancer Res. 15:5267–5273. 2009. View Article : Google Scholar : PubMed/NCBI

12 

Li S, Li L, Zhu Y, Huang C, Qin Y, Liu H, Ren-Heidenreich L, Shi B, Ren H, Chu X, et al: Coexistence of EGFR with KRAS, or BRAF, or PIK3CA somatic mutations in lung cancer: A comprehensive mutation profiling from 5125 Chinese cohorts. Br J Cancer. 110:2812–2820. 2014. View Article : Google Scholar : PubMed/NCBI

13 

Flaherty KT, Puzanov I, Kim KB, Ribas A, McArthur GA, Sosman JA, O'Dwyer PJ, Lee RJ, Grippo JF, Nolop K and Chapman PB: Inhibition of mutated, activated BRAF in metastatic melanoma. N Engl J Med. 363:809–819. 2010. View Article : Google Scholar : PubMed/NCBI

14 

Brustugun OT, Khattak AM, Trømborg AK, Beigi M, Beiske K, Lund-Iversen M and Helland Å: BRAF-mutations in non-small cell lung cancer. Lung Cancer. 84:36–38. 2014. View Article : Google Scholar : PubMed/NCBI

15 

Yarden Y and Sliwkowski MX: Untangling the ErbB signalling network. Nat Rev Mol Cell Biol. 2:127–137. 2001. View Article : Google Scholar : PubMed/NCBI

16 

Cancer Genome Atlas Research Network: Comprehensive molecular profiling of lung adenocarcinoma. Nature. 511:543–550. 2014. View Article : Google Scholar : PubMed/NCBI

17 

Mazières J, Peters S, Lepage B, Cortot AB, Barlesi F, Beau-Faller M, Besse B, Blons H, Mansuet-Lupo A, Urban T, et al: Lung cancer that harbors an HER2 mutation: Epidemiologic characteristics and therapeutic perspectives. J Clin Oncol. 31:1997–2003. 2013. View Article : Google Scholar : PubMed/NCBI

18 

Eng J, Woo KM, Sima CS, Plodkowski A, Hellmann MD, Chaft JE, Kris MG, Arcila ME, Ladanyi M and Drilon A: Impact of concurrent PIK3CA mutations on response to EGFR tyrosine kinase inhibition in EGFR-mutant lung cancers and on prognosis in oncogene-driven lung adenocarcinomas. J Thorac Oncol. 10:1713–1719. 2015. View Article : Google Scholar : PubMed/NCBI

19 

Wen YS, Cai L, Zhang XW, Zhu JF, Zhang ZC, Shao JY and Zhang LJ: Concurrent oncogene mutation profile in Chinese patients with stage Ib lung adenocarcinoma. Medicine (Baltimore). 93:e2962014. View Article : Google Scholar : PubMed/NCBI

20 

Kris MG, Johnson BE, Berry LD, Kwiatkowski DJ, Iafrate AJ, Wistuba II, Varella-Garcia M, Franklin WA, Aronson SL, Su PF, et al: Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA. 311:1998–2006. 2014. View Article : Google Scholar : PubMed/NCBI

21 

Keam B, Kim DW, Park JH, Lee JO, Kim TM, Lee SH, Chung DH and Heo DS: Rare and complex mutations of epidermal growth factor receptor, and efficacy of tyrosine kinase inhibitor in patients with non-small cell lung cancer. Int J Clin Oncol. 19:594–600. 2014. View Article : Google Scholar : PubMed/NCBI

22 

Zhou C, et al: Phase II Single Arm Study of AZD9291 to Treat NSCLC Patients in Asia Pacific (AURA17). https://clinicaltrials.gov/ct2/show/study/NCT02442349April 25–2017

Related Articles

Journal Cover

August-2018
Volume 18 Issue 2

Print ISSN: 1791-2997
Online ISSN:1791-3004

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Jing C, Mao X, Wang Z, Sun K, Ma R, Wu J and Cao H: 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 18: 2191-2197, 2018.
APA
Jing, C., Mao, X., Wang, Z., Sun, K., Ma, R., Wu, J., & Cao, H. (2018). Next‑generation sequencing‑based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her‑2 and TP53 mutations in patients with non‑small cell lung cancer. Molecular Medicine Reports, 18, 2191-2197. https://doi.org/10.3892/mmr.2018.9210
MLA
Jing, C., Mao, X., Wang, Z., Sun, K., Ma, R., Wu, J., Cao, H."Next‑generation sequencing‑based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her‑2 and TP53 mutations in patients with non‑small cell lung cancer". Molecular Medicine Reports 18.2 (2018): 2191-2197.
Chicago
Jing, C., Mao, X., Wang, Z., Sun, K., Ma, R., Wu, J., Cao, H."Next‑generation sequencing‑based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her‑2 and TP53 mutations in patients with non‑small cell lung cancer". Molecular Medicine Reports 18, no. 2 (2018): 2191-2197. https://doi.org/10.3892/mmr.2018.9210