Hotspot mutations in common oncogenes are infrequent in nasopharyngeal carcinoma

  • Authors:
    • Ning Jiang
    • Na Liu
    • Fan Yang
    • Qiming Zhou
    • Ruixue Cui
    • Wei Jiang
    • Qingmei  He
    • Wenfei Li
    • Ying Guo
    • Jing Zeng
    • Jingping Yun
    • Xinchun Chen
    • Boping Zhou
    • Ying Sun
    • Huiyun Wang
    • Zhuo G. Chen
    • Jun Ma
  • View Affiliations

  • Published online on: August 1, 2014     https://doi.org/10.3892/or.2014.3376
  • Pages: 1661-1669
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Abstract

Oncogene mutations contribute to carcinogenesis and can provide potential therapeutic targets for clinical anticancer management. However, oncogene mutation patterns in nasopharyngeal carcinoma (NPC) have yet to be fully elucidated. To gain insight into mutation patterns in NPC, a high-throughput OncoCarta panel assay was used to determine 238 hotspot mutations across 19 common oncogenes in 8 NPC cell lines and 160 NPC patient samples from southern China. Statistical analyses were further conducted to identify associations between oncogene mutations and selected clinicopathological characteristics. In total, we identified 24 mutations across 11 oncogenes in 17 (10.6%) NPC patients. Four patients exhibited mutations in at least one oncogene. We also identified a PIK3CA H1047R mutant in 7 NPC cell lines. In addition, oncogene mutations showed no correlation with either risk habits (smoking and drinking) or other clinical characteristics except for TNM stage. KIT mutations were associated with poorer overall and relapse-free survival. Furthermore, KIT mutations together with age and N stage were independent prognostic factors in NPC. Taken together, the present study is the first report on mutations in multiple oncogenes in NPC. We found that hotspot oncogene mutations are infrequent in NPC patients from southern China. The lack of hotspot mutations requires a comprehensive characterization of gene mutations in NPC for developing new therapeutic targets in the future.

Introduction

Nasopharyngeal carcinoma (NPC) is an endemic disease in southern China and Southeast Asia, with a global incidence of 84,400 new cases annually and a mortality of 51,600 in 2008 (1). After primary treatment with radiotherapy or chemoradiotherapy, a significant proportion of endemic NPC patients, particularly those with stage III or IV, relapsed locoregionally and/or systemically (2,3). The median overall survival after recurrence is generally poor and ranges from 7.2 to 22 months (46). Therefore, new therapeutic strategies are required.

Cancer derives from the progressive accumulation of abnormalities in cellular DNA which provides growth advantages to cancer cells (7). Somatic mutations become useful targets and biomarkers in selecting personalized therapy for many solid tumors. For example, molecular driven therapeutic targets such as epidermal growth factor receptor (EGFR) and abnormal fusion of echinoderm microtubule-associated protein-like 4 and anaplastic lymphoma kinase (EML4-ALK) genes have resulted in a paradigm shift in the treatment of lung adenocarcinoma (8,9). Furthermore, KRAS (Kirsten rat sarcoma viral oncogene homolog) and BRAF (v-raf murine sarcoma viral oncogene homolog B) oncogene mutations are positively associated with resistance to anti-EGFR drugs (10,11). Hence, current anticancer therapy depends more on the knowledge of genetic alterations in specific tumors.

Lifestyle exposure such as salted fish, EBV infection, smoking and drinking has consistently been linked to NPC risk (12), predicate on the hypothesis that genomic alternations as a result of lifestyle exposure may be a reason for NPC oncogenesis. Despite the fact that chromosomal abnormalities (13) together with amplification of certain oncogenes have been identified in NPC (14,15), information regarding oncogene mutations in NPC is limited (16). Several studies demonstrated that oncogene phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit α (PIK3CA) mutation was an uncommon event in NPC patients (1719). No EGFR kinase domain mutation was found in 60 Moroccan NPC patients (20). BRAF and RAS mutants were observed to be absent in 65 NPC samples (17). KIT (v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog) intron mutation was reported in NPC cell lines (21). Therefore, hotspot mutations in a group of actionable oncogenes remain to be investigated in larger studies.

In the present study, a high throughput OncoCarta™ ver. 1.0 mutation profiling panel was used to determine the prevalence of 238 hotspot mutations across 19 oncogenes in 8 NPC cell lines and 160 NPC patients. This panel interrogates with oncogenes with known targeted drugs or genes that interact with oncogenic pathways (2224). Furthermore, the association between oncogene mutations and clinicopathological factors of NPC patients was also investigated in our study.

Materials and methods

Patient samples

The present study included 160 formalin-fixed paraffin-embedded (FFPE) tumor samples and matched peripheral blood cell samples from adult patients with newly diagnosed NPC. All samples were obtained from the Sun Yat-sen University Cancer Center between January 2006 and December 2009 and were collected before patients underwent treatment (radiotherapy or chemotherapy). All tissue slides were pathologically diagnosed by at least two independent pathologists according to the World Health Organization (WHO) classification (J.Z. and J.Y.).

The clinicopathological characteristics of all patients, including age, gender and clinical staging were collected and summarized in Table I. Clinical staging was classified according to the criteria of the 7th edition of the AJCC Cancer Staging Manual. The follow-up duration was calculated from the first day of treatment to either the day of death or the day of last examination. The median follow-up time was 40.0 months (range, 1.87–67.33). This study was approved by the Institutional Ethics Review Boards of Sun Yat-sen University Cancer Center and written informed consent was obtained from all patients.

Table I

Clinicopathological characteristics of NPC patients (n=160).

Table I

Clinicopathological characteristics of NPC patients (n=160).

Mutation

CharacteristicsNo. of patients (n=160)Absent n (%)Present n (%)P-valuea
Age (years)b16047.4±12.147.9±11.50.86c
Gender
 Female3632 (88.9)4 (11.1)1.00
 Male124111 (89.5)13 (10.5)
Histology
 Differentiated65 (83.3)1 (16.7)1.00
 Undifferentiated154138 (89.6)16 (10.4)
Smokers
 Yes8173 (90.1)8 (9.9)0.58
 No7162 (87.3)9 (12.7)
Alcohol consumption
 Yes2928 (96.6)1 (3.4)0.25
 No123107 (87.0)16 (13.0)
VCA-IgA
 <1:801815 (83.3)3 (16.7)0.64
 ≥1:80141127 (90.1)14 (9.9)
EA-IgA
 <1:102319 (82.6)4 (17.4)0.45
 ≥1:10136123 (90.4)13 (9.6)
T stage
 T1-23730 (81.1)7 (18.9)0.12
 T3-4123113 (91.9)10 (8.1)
N stage
 N0-17162 (87.3)9 (12.7)0.62
 N2-38981 (91.0)8 (9.0)
TNM stage
 I–II1510 (66.7)5 (33.3)0.01
 III–IV145133 (91.7)12 (8.3)

a Fisher’s exact test.

b Mean ± SD.

c Student’s t-test.

{ label (or @symbol) needed for fn[@id='tfn4-or-32-04-1661'] } TNM, tumor-node-metastasis.

Cell lines

The NPC cell lines SUNE-1, CNE-1, C666-1, CNE-2, HONE-1, HNE-1, 5-8F and 6-10B were obtained and maintained in RPMI-1640 (Invitrogen, Beijing, China) supplemented with 10% fetal bovine serum (Gibco, Montevideo, Uruguay) as previously described (25). The immortalized nasopharyngeal epithelial cell line (NP69) was cultured in keratinocyte serum-free medium (Invitrogen, NY, USA) supplemented with bovine pituitary extract (BD Biosciences, San Jose, CA, USA) (25). All cell lines were passaged for less than ten generations and incubated at 37°C in a 5% CO2 incubator.

DNA extraction

For all FFPE tumor samples, hematoxylin and eosin (H&E) stained slides were reviewed by two pathologists (Z.J. and J.Y.) to ensure a percentage of tumor cells >70% as previously described (26,27). Eight 10 μm unstained FFPE tissue sections of each sample were deparaffinized by xylene wash (20 min) followed by two 100% ethanol washes. DNA was extracted from the pellets, cell lines and matched peripheral blood cell samples using the Qiagen DNA extraction Kits (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions. The quality and quantity of DNA was determined using the NanoDrop ND1000 Spectrophotometer and gel agarose electrophoresis.

Oncogene mutation detection and analysis

DNA samples were amplified using the OncoCarta™ v1.0 Kit (Sequenom, San Diego, CA, USA) containing 24 pools of PCR primers and extension primers that allow the detection of 238 pathogenic mutations in 19 oncogenes (ABL1, AKT1, AKT2, BRAF, CDK4, EGFR, ERBB2, FGFR1, FGFR3, FLT3, JAK2, KIT, MET, HRAS, KRAS, NRAS, PDGFA, PIK3CA and RET) (Table II) (23,28). The extension products were analyzed based on the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF) technology on the Sequenom MassArray platform (28). The experiments were conducted according to the manufacturer’s instructions, as previously described (28,29). The spectra were analyzed by MassArray Typer Analyzer® ver. 4.0.4.20 Software (Sequenom) which automates the identification of mutants by comparing ratios of wild-type (WT) peaks to all suspected mutants and adjusting these peaks when adducts are detected in the spectrum. All mutations detected were manually reviewed by three different persons (N.J., N.L. and F.Y.). Mutation peaks that appeared in both tumor and matched blood cell DNA were not considered as somatic mutations and were excluded from further analysis.

Table II

Mutations detected with the OncoCarta™ ver. 1.0 kit.

Table II

Mutations detected with the OncoCarta™ ver. 1.0 kit.

No.GenesTargeted mutations
1ABL1D276G, E255K, E255V, F311L, F317L, F359V, G250E, H396R, M351T, Q252H, T315I, Y253F, Y253H
2AKT1E17del, E319G, L357P, P388T, Q43X, V167A, V167A, V461L
3AKT2R371H, S302G
4BRAFD594V, D594G, F468C, F595L, G464R, G464V, G464E, G466R, G469S, G469E, G469A, G469V, G469R, G596R, K601E, K601N, L597Q, L597V, L597S, L597R, T599I, V600E, V600K
5CDK4R24C, R24H
6EGFRA289V, D770_N771>AGG, D770_N771insG, E709A, E709G, E709V, E709K, E709H, E746_A750del, E746_A750del, V ins, E746_A750del, T751A, E746_T751del, I ins, E746_T751del, S752D, E746_T751del, V ins, G598V, G719A, G719S, G719C, H773_V774insH, H773_V774insNPH, H773>NPY, L747_E749del, A750P, L747_S752del, P753S, L747_S752del, Q ins, L747_T750del, P ins, L747_T751del, L858R, L861Q, M766_A767insAI, N771_P772>SVDNR, P772_H773insV, R108K, S752_I759del, S768I, SNP C2255T, T263P, T751A, T790M, V769_D770insASV, V769_D770insCV, V774_C775insHV
7ERBB2A775_G776 insYVMA, G776S, G776LC, G776VC, L755P, P780_Y781 insGSP, S779_P780 insVGS
8FGFR1P252T, S125L
9FGFR3A391E, G370C, K650Q, K650E, K650T, K650M, Y373C
10FLT3D835H, D835Y, I836del
11HRASG12V, G12D, G13C, G13R, G13S, Q61H, Q61H, Q61K, Q61L, Q61R, Q61P
12JAK2V617F
13KITD52N, D579del, D816H, D816Y, D816V, E561K, E839K, F584S, K550_K558del, K558_E562del, K558_V560del, K642E, L576P, M552L, P551_V555del, P585P, V559_V560del, V559D, V559A, V559G, V559del, V559I, V560D, V560G, V560del, V825A, W557R, W557R, W557G, Y503_F504insAY, Y553_Q556del, Y568D, Y570_L576del
14KRASA59T, G12A, G12C, G12D, G12F, G12R, G12S, G12V, G13V, G13D, Q61E, Q61K, Q61H, Q61H, Q61L, Q61R, Q61P
15METM1250T, R970C, T992I, Y1230C, Y1235D
16NRASA18T, G12C, G12R, G12S, G12V, G12A, G12D, G13C, G13R, G13S, G13V, G13A, G13D, Q61E, Q61K, Q61H, Q61L, Q61R, Q61P
17PDGFRAD1071N, D842_H845del, D842V, D846Y, F808L, I843_D846del, I843_S847>T, N870S, S566_E571>K, T674I, V561D
18PIK3CAC420R, C901F, E542K, E545K, H1047R, H1047L, H701P, M1043I, M1043I, N345K, P539R, Q546K, R38H, R88Q
19RETA664D, C634R, C634W, C634Y, E632_L633del, M918T
Statistical analysis

Statistical analyses were conducted using SPSS ver. 20 Software. The χ2 test and Fisher’s exact test were used to assess differences in the distribution of clinical variables and oncogene mutation status. Kaplan-Meier analysis was used to determine survival; the differences between genotypes were compared using the log-rank test. HR values were calculated using univariate Cox regression analysis. Multivariate Cox regression analysis was used to test the independent significance, in which KIT mutation, age, gender, T and N stages were used as covariates. All tests were two-tailed, and P-values <0.05 were considered to indicate a statistically significant difference.

Results

Oncogene mutations detected in NPC

Of the 160 NPC patients, 17 (10.6%) had at least one oncogene mutation and 4 (23.5%) of them had two or more mutations. In total, we identified 24 mutations located in 11 genes by Sequenom OncoCarta kit (Table III). EGFR variants were detected in 5 tumors, followed by CDK4, KIT and PDGFRA mutations in 3 patients and KRAS, BRAF and MET (MET proto-oncogene) mutations in 2 patients. FGFR3 (fibroblast growth factor receptor 3), AKT1 (v-akt murine thymoma viral oncogene homolog 1), PIK3CA and NRAS mutations were only detected in one sample (Table III). We did not detect any mutations in the remaining eight oncogenes. Patients with BRAF mutations were WT in KRAS, which was consistent with previous findings in colon cancer (30). Direct sequencing was adopted to validate the MassArray findings. Representative figures of detected mutations are shown in Fig. 1A and B.

Table III

Summary of specific mutations detected in NPC samples using MassArray.

Table III

Summary of specific mutations detected in NPC samples using MassArray.

Alele frequency

GeneMutationAlleleWTMutSample
AKT1E17KG0.60.456
BRAFL597SG0.770.2317
G469RT0.9110.089104
CDK4R24HT0.730.2717
R24CA0.570.4326
R24CA0.8680.132116
EGFR N771_P772>SVDNRGCGT0.910.0948
N771_P772>SVDNRGCGT0.830.17106
T790MT0.9240.076100
H773_V774insNPHAA..AC0.9090.091104
R108KA0.910.09149
FGFR3Y373CG0.850.1526
KITV559IA0.7240.27612
E839KA0.9010.099104
K558_V560delDEL0.8990.101157
KRASA59TT0.890.1113
G12DT0.6390.287105
METR970CT0.920.0817
R970CT0.8950.105129
NRASA18TT0.890.1213
PDGFRAT674IT0.850.1514
T674IT0.690.3117
T674IT0.940.0696
PIK3CAE545KA0.8940.106153

[i] Mutations are represented as amino acidic changes found for each gene and the proportions between the wild type (WT) and mutated (Mut) alleles frequency for each alteration.

We next determined the 238 hotspot mutations in 8 NPC cell lines: 5-8F, 6-10B, SUNE-1, CNE-1, C666-1, CNE-2, HONE-1 and HNE-1. PIK3CA c.3140A>G (H1047R) was the only mutation observed in 7 NPC cell lines, but not in C666-1 (Fig. 2). The results were confirmed by direct sequencing (Fig. 3). Notably, the PIK3CA c.3140A>G mutation was also found absent in an immortalized nasopharyngeal epithelial cell line NP69 by direct sequencing (Fig. 3).

Taken together, hotspot oncogene mutations which are common in other solid tumors are infrequent events in NPC.

Correlation between mutational profile and clinicopathological characteristics

The relationship between clinicopathological factors and mutation patterns were assessed. As shown in Table I, oncogene mutations were significantly associated with the TNM stage of NPC patients (P=0.01). However, there was no association between oncogene mutations and clinical characteristics such as age, gender, histopathological grade, EBV-related antigen levels, tumor (T) and lymph node (N) stage of NPC patients (P>0.05, Table I). We also did not find any difference in risk habits (smoking or alcohol consumption) in patients with or without oncogene mutations (P>0.05, Table I).

Furthermore, Kaplan-Meier analysis did not show significant differences in overall survival (OS) and relapse-free survival (RFS) between patients with and without oncogene mutations (P>0.05) (Fig. 4A). Patients with KIT mutation were associated with poorer OS (HR, 8.34; 95% CI, 2.47–28.21; P<0.001) and RFS (HR, 8.20; 95% CI, 1.03–64.92; P=0.02) (Fig. 4B). Furthermore, we performed multivariate analyses with KIT mutation, age, gender, T and N stages as covariates (P<0.05). We found that the KIT mutation (HR, 5.94; 95% CI, 1.73–20.42; P<0.01), age (HR, 1.69; 95% CI, 1.11–2.58; P=0.01) and N stage (HR, 1.56; 95% CI, 1.02–2.41; P=0.04) were independent prognostic factors associated with OS in NPC patients (Table IV).

Table IV

Summary of the multivariable analysis of prognostic factors for overall survival and risk score in NPC.

Table IV

Summary of the multivariable analysis of prognostic factors for overall survival and risk score in NPC.

VariablesP-valueHR95% CI
Age group (years) (≤47 vs. >47)0.011.691.11–2.58
Gender (Male vs. female)0.060.580.32–1.02
T stage (T3-T4 vs. T1-T2)0.181.420.85–2.37
N stage (N2-N3 vs. N1-N0)0.041.561.02–2.41
KIT mutation<0.015.941.73–20.42

Discussion

In recent years, identification of somatic mutations as key perturbations that promote tumorigenesis has become an essential component in determining the management of certain malignancies. For example, oncogenic mutations in EGFR, KRAS have been clinically used as target and sensitivity biomarkers in the treatment of non-small cell lung carcinoma (31). However, knowledge regarding oncogene mutational patterns in NPC remains limited, especially in patients from NPC prevalent southern China. Thus, a high-throughput OncoCarta panel was adopted in the current study to determine 238 hotspot mutations across 19 oncogenes in NPC. This panel provides a cost effective and efficient technology for detecting known hotspot mutations in FFPE samples (23,32). Moreover, information concerning 10 of the 19 oncogenes investigated by the OncoCarta™ ver. 1.0 assay is either limited or absent in COSMIC database in NPC (http://www.sanger.ac.uk/cosmic).

The present study demonstrated that oncogene mutations were uncommon in NPC with 10.6% of patients carrying one or more mutations across 11 oncogenes. There was no difference between patients with or without oncogene mutations in risk habits (tobacco and alcohol consumption) and EBV infection status, both of which are historically associated with NPC. Consistent with previous reports, known PIK3CA mutations were detected in both NPC cell lines and tissues with similar mutation frequency compared to COSMIC database (Table V) (17,33). Furthermore, we found a correlation between KIT mutation and poorer survival in NPC patients. KIT mutation together with age and N stage were independent prognostic factors for NPC. The identification of mutated oncogenes in NPC is encouraging as it may provide insight into the etiology of NPC and influence future clinical management.

Table V

Mutations detected in the present study compared with the COSMIC database.

Table V

Mutations detected in the present study compared with the COSMIC database.

GenesCOSMIC database
Mut/total cases (%)a
Present study
Mut cases (%; n=168)a
AKT1N1 (0.6)
BRAF0/65 (0)2 (1.2)
CDK4N3 (1.8)
EGFR0/78 (0)5 (3.0)
FGFR3N1 (0.6)
KIT0/3 (0)3 (1.8)
KRAS0/74 (0)2 (1.2)
MET0/5 (0)2 (1.2)
NRAS0/18 (0)1 (0.6)
PDGFRA0/3 (0)3 (1.8)
PIK3CA8/105 (7.6)9 (5.4)

a Including data of NPC cell lines.

{ label (or @symbol) needed for fn[@id='tfn7-or-32-04-1661'] } N, not determined.

PIK3CA, BRAF, EGFR, KIT, KRAS, HRAS, NRAS, PDGFRA and MET (34) oncogenes have been previously reported to be absent in NPC according to the COSMIC database, whereas mutations in gene AKT1, CDK4, FGFR3 and ABL1 have not yet been studied in NPC (Table V) (35). In the present study, mutations in these oncogenes were reported in NPC for the first time. This could be explained by the use of a more sensitive MALDI-TOF technology which is as sensitive as next generation sequencing, and more sensitive than Sanger sequencing, as Su et al demonstrated (36). Secondly, according to the COSMIC database, most of the previous studies were based on cohorts <100 samples (Table V). Furthermore, this difference may also be due to different pathological characteristics or population background.

The PIK3CA gene encodes the 110 kDa catalytic subunit of PI3K. Upon activation, PIK3CA generates an activating signaling cascade involved in cell growth, survival, proliferation, motility and morphology (37,38). A study by Or et al previously reported a one base substitution of c.3140A>G (H1047R) in the PIK3CA gene in CNE-2 and HONE-1, but not in C666-1 cells line (33). We confirmed the same mutant in 7 NPC cell lines, including CNE-2 and HONE-1. However, EBV positive C666-1 and an immortalized nasopharyngeal epithelial cell line NP69 showed absence of this mutation. Since the c.3140A>G mutant acts as a gain-of-function mutation in PIK3CA kinase domain (39) and appears only in EBV negative NPC cell lines, we speculate that this mutation may play an important role in the transformation of EBV-negative NPC cell lines, which deserves further investigation. We did not find this mutant in 160 patient samples among which 98.1% of patients showed detectable EBV-related antigens. Instead, a PIK3CA c.1633G>A (E545K) mutation was detected in one NPC patient. This mutant was previously reported by Chou et al in 4 NPC patients (17). Moreover, in comparison with the mutation rate of 7.6% (8/105) reported by COSMIC database (including cell line data), this study found a similar mutation frequency of 5.6% (8/168) in PIK3CA oncogene (Table V) (18,33,40).

The proto-oncogene c-KIT encodes a transmembrane tyrosine kinase receptor which plays important roles in the hematogenous system, placenta, heart, lung, and midgestational kidney (41,42). Gain-of-function mutations of the c-KIT gene promote constitutive phosphorylation of KIT and, consequently, activation of downstream PI3K/AKT, Src family kinases and MAPK pathways (42). In our study, we found KIT K558_V560del, E839K and V559I mutations in three NPC patients. K558_V560del and V559I are juxtamembrane mutations located in exon 11 of KIT oncogene which have been observed in GISTs (43,44) and aggressive systemic mastocytosis (ASM), respectively (44). These two mutants showed spontaneous KIT phosphorylation (45) and could transform IL-3-dependent Ba/F3 cells into IL-3-independent growth in the absence of KIT ligand stem cell factor (SCF) (46). In contrast, KITE839K was not spontaneously phosphorylated in response to exogenous SCF and thus lacked cell transforming ability (45). KIT phosphorylated mutants could be inhibited by KIT inhibitors such as imatinib and dasatinib (47). These data together with our findings that KIT mutation correlated with poor survival in NPC, suggest that targeting KIT could be a potential therapeutic strategy in the treatment of NPC. We did not find any KIT mutation in NPC cell lines. This is consistent with a study by Huang et al (21) in which no KIT exon 9–21 hotspot mutation was found in 5 NPC cell lines. However, the fact that KIT mutation was only detected in 3/160 NPC patients requires broader studies in the future. KIT DNA amplification, protein overexpression and their clinical relevance also warrants further investigation in NPC.

Mutations in exon 18–21 of EGFR tyrosine kinase domain are present in lung cancer, and some of them are related to response to anti-EGFR agents such as gefitinib or erlotinib (8,24). EGFR tyrosine kinase domain mutations have been previously found absent in 60 Moroccan patients (20) and four NPC cell lines (48). In our series, we detected five NPC cases carrying four EGFR mutants (Table III). EGFR T790M, H773_V774insNPH and N771_P772>SVDNR mutations located in EGFR exon 20 could change the crystal structures of EGFR which lead to resistance to EGFR inhibitors (49). EGFR R108K is a gain-of-function mutation in EGFR exon 3 which has been reported in glioma. It would be of interest to determine whether these mutants affect the response to EGFR-TKIs in NPC patients in the future.

In the present study, we first reported three CDK4 mutations in NPC. Cyclin-dependent kinase 4 (CDK4) is the chief catalytic subunit of the regulatory cyclin D that governs G1-to-S phase cell cycle progression (50). Dominant activating mutations affecting codon 24 of the CDK4 gene (R24H or R24C) render CDK4 insensitive to p16INK4 inhibition and are responsible for multiple neoplasia developing (50,51). Collectively, these data indicated that CDK4 mutation may play a role in oncogenesis in a subset of NPC patients. Moreover, mutations affect the RAS/RAF pathway and growth factor receptors such as MET, PDGFRA, FGFR3 were also found in NPC in our study. Since all these molecules are popular targets in anticancer treatment, NPC patients with these mutations may benefit from therapies targeting these oncogenes

In summary, this study provided evidence for understanding oncogenic mutational patterns in NPC. Our data showed lower oncogene mutation frequencies in NPC compared to other solid tumors (5255). The presence of mutations in a few key oncogenes may ultimately be important in clinical management of NPC and requires future verification.

Acknowledgements

The authors thank Professor Feng Chen (Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China) for helpful discussion and assistance. This research was supported by grants from the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2010), the National Natural Science Foundation of China (no. 81230056), the Innovation Team Development Plan of the Ministry of Education (no. IRT1297), the Science and Technology Project of Guangzhou City, China (no. 12BppZXaa2060002) and Guangdong Translational Medicine Public Platform (no. 4202037).

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October 2014
Volume 32 Issue 4

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Spandidos Publications style
Jiang N, Liu N, Yang F, Zhou Q, Cui R, Jiang W, He Q, Li W, Guo Y, Zeng J, Zeng J, et al: Hotspot mutations in common oncogenes are infrequent in nasopharyngeal carcinoma. Oncol Rep 32: 1661-1669, 2014
APA
Jiang, N., Liu, N., Yang, F., Zhou, Q., Cui, R., Jiang, W. ... Ma, J. (2014). Hotspot mutations in common oncogenes are infrequent in nasopharyngeal carcinoma. Oncology Reports, 32, 1661-1669. https://doi.org/10.3892/or.2014.3376
MLA
Jiang, N., Liu, N., Yang, F., Zhou, Q., Cui, R., Jiang, W., He, Q., Li, W., Guo, Y., Zeng, J., Yun, J., Chen, X., Zhou, B., Sun, Y., Wang, H., Chen, Z. G., Ma, J."Hotspot mutations in common oncogenes are infrequent in nasopharyngeal carcinoma". Oncology Reports 32.4 (2014): 1661-1669.
Chicago
Jiang, N., Liu, N., Yang, F., Zhou, Q., Cui, R., Jiang, W., He, Q., Li, W., Guo, Y., Zeng, J., Yun, J., Chen, X., Zhou, B., Sun, Y., Wang, H., Chen, Z. G., Ma, J."Hotspot mutations in common oncogenes are infrequent in nasopharyngeal carcinoma". Oncology Reports 32, no. 4 (2014): 1661-1669. https://doi.org/10.3892/or.2014.3376