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Genomics Inform > Volume 10(3); 2012 > Article
Sung, Park, Kim, and Kim: Discovery and Evaluation of Polymorphisms in the AKT2 and AKT3 Promoter Regions for Risk of Korean Lung Cancer

Abstract

AKT is a signal transduction protein that plays a central role in the tumorigenesis. There are 3 mammalian isoforms of this serine/threonine protein kinase-AKT1, AKT2, and AKT3-showing a broad tissue distribution. We first discovered 2 novel polymorphisms (AKT2 -9826 C/G and AKT3 -811 A/G), and we confirmed 6 known polymorphisms (AKT2 -9473 C/T, AKT2 -9151 C/T, AKT2 -9025 C/T, AKT2 -8618G/A, AKT3 -675 A/-, and AKT3 -244 C/T) of the AKT2 and AKT3 promoter region in 24 blood samples of Korean lung cancer patients using direct sequencing. To evaluate the role of AKT2 and AKT3 polymorphisms in the risk of Korean lung cancer, genotypes of the AKT2 and AKT3 polymorphisms (AKT2 -9826 C/G, AKT2 -9473 C/T, AKT2 -9151 C/T, AKT2 -9025 C/T, AKT2 -8618G/A, and AKT3 -675 A/-) were determined in 360 lung cancer patients and 360 normal controls. Statistical analyses revealed that the genotypes and haplotypes in the AKT2 and AKT3 promoter regions were not significantly associated with the risk of lung cancer in the Korean population. These results suggest that polymorphisms of the AKT2 and AKT3 promoter regions do not contribute to the genetic susceptibility to lung cancer in the Korean population.

Introduction

Lung cancer has been the leading cause of cancer-related deaths in Korea, and its incidence continues to rise [1]. Despite therapeutic advances, the overall 5-year survival remains only 15% [2]. Lung cancer is a multicellular and multistage process that involves a number of genetic changes in oncogenes and tumor suppressor genes. Nevertheless, the prognosis of lung cancer has remained poor despite innovations in diagnostic testing and surgical technique and the development of new chemotherapeutic agents. Recently introduced targeted agents show different responses according to histological subtype, and the efficiency of treatment modalities for lung cancer depends on the time of diagnosis [3]. Therefore, there is a great need for rapid and efficient early detection methods. For developing improved molecular biomarkers for the early detection and prediction of response to chemotherapy, it is important to identify genetic alterations specific to each subtype of lung cancer. Single-nucleotide polymorphisms (SNPs) represent an important class of genetic variations and affect an individual's susceptibility to disease in certain circumstances [4-6].
Activation of the intracellular survival signal transduction protein AKT, known as protein kinase B, has been proposed as a central signaling event in carcinogenesis and has been shown in experimental models to confer resistance to chemotherapy and radiation [7, 8]. AKT is activated by phosphatidylinositol 3 phosphates, the products of phosphoinositide 3-kinase (PI3K) activity [9]. Additionally, AKT activity is commonly dysregulated in a variety of human tumors because of frequent inactivation of the PTEN tumor suppressor gene, which negatively regulates phosphatidylinositol 3 phosphate levels, and alterations of this gene have been identified in various cancers, including lung cancer [10, 11]. To date, 3 human isoforms of AKT have been identified, AKT1, AKT2, and AKT3, which are expressed in lung, breast, colon, and prostate tumor tissues [12].
Somatic mutations of AKTs have been reported in endometrial carcinomas, hypoglycemia, and breast cancer [13, 14]. However, somatic mutations in AKT families are rare in lung cancer [15, 16]. Previously, it was reported that an AKT1 polymorphism was not associated with schizophrenia [17, 18]. AKT1 and AKT2 polymorphisms have been reported to be related to survival of esophageal cancer [19], and it was reported that an AKT1 polymorphism was associated with survival in surgically resected non-small cell lung cancer [20]. However, the association between AKT2 and AKT3 polymorphisms and the risk of lung cancer has not yet been clarified. This study discovered polymorphisms of the AKT2 and AKT3 promoter regions and their relation with the risk of lung cancer in a Korean population.

Methods

Study subjects

Between August 2001 and November 2010, blood samples were collected from 720 subjects, including 360 lung cancer patients and 360 normal controls without cancer. Lung cancer patients were recruited from the patient pool at the Genomic Research Center for Lung and Breast/Ovarian Cancer, and control subjects were randomly selected from a pool of healthy volunteers who had visited the Cardiovascular Genome Center and Genomic Research Center for Allergy and Respiratory Diseases. Detailed information on diet, smoking status, drinking status, lifestyle, and medical history were collected by trained interviewers using a structured questionnaire. Out of 360 cases, information was available for 352 on smoking status, 317 on stage, and 343 on cell type, while information was available for 272 on smoking status of 360 controls. All study subjects provided written consent and were ethnic Koreans, and all participating Institutional Review Boards approved the study protocol.

Preparation of genomic DNA and direct sequencing

Genomic DNA was prepared from peripheral blood samples using a Puregene blood DNA kit (Gentra, Minneapolis, MN, USA), following the manufacturer's protocol.
To identify polymorphisms in the promoter of the AKT2 and AKT3 genes, human genomic DNA was isolated from the whole blood of 24 lung cancer patients for direct sequencing, and the promoter region of the AKT2 and AKT3 genes was amplified. Polymerase chain reaction (PCR) amplifications were performed on a PTC-225 Peltier Thermal cycler (MJ Research Inc., Waltham, MA, USA) using Ampli-TagGold (Roche, Branchburg, NJ, USA). All amplifications were performed using 35 cycles of 30 s at 95℃, 1 min at 64℃, and 1 min at 72℃, followed by a single 10-min extension at 72℃. PCR products were purified using the Montage PCR96 Cleanup kit (Millipore, Bedford, MA, USA) and eluted in 20 µL of nuclease-free H2O. DNA cycle sequencing was carried out using the BigDye Terminator V 3.1 Cycle Sequencing kit (Perkin Elmer, Foster City, CA, USA). Multiscreen SEQ 384-well filter plates were used for dye removal, and sequences were then analyzed on an Applied Biosystems 3700 (ABI, Foster City, CA, USA). All polymorphisms and sequence alignments were analyzed using Polyphred.

Genotyping

After direct sequencing of the AKT2 and AKT3 genes, we performed genotyping for the 8 polymorphisms of the AKT2 and AKT3 genes. The genotypes of the AKT2 and AKT3 polymorphisms were screened by TaqMan fluorogenic 5' nuclease assay (ABI). The final volume of the PCR was 5 µL, containing 10 ng of genomic DNA, and 2.5 µL TaqMan Universal PCR Master Mix, with 0.13 µL of 40 × Assay Mix. Thermal cycle conditions were as follows: 50℃ for 2 min to activate uracil N-glycosylase and prevent carryover contamination, 95℃ for 10 min to activate the DNA polymerase, and 45 cycles of 95℃ for 15 s and 60℃ for 1 min. All PCRs were performed using 384-well plates on a Dual 384-Well GeneAmp PCR System 9700 (ABI), and the endpoint fluorescent readings were performed on an ABI PRISM 7900 HT Sequence Detection System (ABI). Duplicate samples and negative controls were included to ensure accuracy of genotyping.

Statistical analysis

Allele frequencies, genotype frequencies, and departures of genotype distributions from Hardy-Weinberg equilibrium (HWE) for each SNP were analyzed using chi-square test or Fisher's exact test. A p-value of <0.05 was considered statistically significant. Linkage disequilibrium (LD) was tested on pairwise combinations of polymorphisms using the absolute value of the standardized measure of LD, D', calculated by Haploview version 3.2. The haplotypes and their frequencies were estimated by Haploview version 3.2. Genotype-specific risks were estimated as odds ratios with associated 95% confidence intervals by unconditional logistic regression (SAS Institute Inc., Cary, NC, USA) and adjusted for age, gender, and smoking status.

Results

Table 1 shows the clinicopathological features of cases and controls. All the clinical characteristics, except for smoking status, were not significantly different between the cases and controls. This difference of smoking status was controlled in the multiple logistic regression analysis, adjusted for age, gender, and smoking status.
By direct sequencing of the AKT2 promoter region in 24 lung cancer patient samples, we identified 1 novel polymorphism (-9826 C/G) and 4 known polymorphisms (-9473 C/T, -9151 C/T, -9025 C/T, and -8618 G/A). Also, we identified 1 novel polymorphism (-811 A/G) and 2 known polymorphisms (-675 A/- and -244 C/T) by direct sequencing in the AKT3 promoter region (Table 2). The genotype distributions of the polymorphisms were in HWE. Also, LD and haplotypes in the polymorphisms of AKT2 were calculated. However, the LD and haplotype block in AKT3 polymorphisms were unidentified because of the low frequency of the AKT3-811 G allele and AKT3-244 T allele (2.1% and 2.2%, respectively) (Fig. 1). Accordingly, we focused on the -675 A/- polymorphism in the AKT3 promoter region. Further analyses were then performed on the samples from 460 lung cancer patients and 460 controls.
Association of lung cancer risk with AKT polymorphisms was then analyzed, revealing no association of the polymorphisms with the risks of lung cancer (Table 3). The association of the polymorphisms with the risk of lung cancer was further examined after stratifying the subjects according to gender and smoking status. However, the subsequent analysis revealed no significant association. Furthermore, the haplotypes of the AKT2 polymorphisms were not associated with the risks of lung cancer in 3 alternative models (data not shown).

Discussion

V-akt murine thymoma viral oncogene homolog (AKT) is a serine/threonine protein kinase that is activated by PI3K-α and mediates PI3L signaling [21]. A major recurrent mutation (Glu17Lys) in the AKT1 gene, which encodes protein kinase B, has been identified in several solid tumors, including breast, colon, and ovarian cancers [22]. Overall, the frequency of AKT1 mutations in non-small cell lung carcinoma (NSCLC) is about 1%, and they have only been identified in squamous cell carcinoma [23]. Also, mutations in the AKT2 and AKT3 genes are rare in several tumors, including lung cancer [15].
Recently, several polymorphisms in the AKT1 gene have been reported in relation to human disease [24-26]. Kim et al. [20] first reported that the AKT1 polymorphisms could be used as prognostic markers for patients with early-stage NSCLC. However, there has been no study on the association between lung cancer risk and polymorphisms of AKT2 and AKT3. In this study, we investigated the association between AKT2 and AKT3 polymorphisms and the risk of lung cancer in the Korean population. The genotypes and haplotypes of the AKT2 and AKT3 genes were determined in 720 Koreans to evaluate the role of the AKT2 and AKT3 polymorphisms in the risk of lung cancer; however, the results revealed no significant difference between lung cancer patients and normal controls. Also, by TFSEARCH (version 1.3) analysis of the AKT2 and AKT3 polymorphism regions, the location of these variants did not have sequences for transcription factor binding sites. This result suggests that polymorphisms of the AKT2 and AKT3 promoter region are unlikely to play an important role in the susceptibility to lung cancer.
Polymorphisms often show ethnic variation [6, 27]. In the present study, we observed the frequencies of 5 polymorphisms in the AKT2 promoter region, and we observed frequencies of 3 polymorphisms in the AKT3 promoter region in 24 Korean populations using direct sequencing. In the direct sequencing result, we detected no frequencies in another known polymorphisms (AKT2: rs11666690, rs11665880, rs35814223, rs34408497, rs35408040, rs10418387; AKT3: rs11588441, rs6679386, rs41267521). The frequencies of AKT2 promoter polymorphisms showed similar frequencies in the Asian ethnic groups (Han Chinese and Japanese) of the dbSNP database (www.ncbi.nlm.nih.gov/SNP). The frequency of the minor allele of rs35835614 in the AKT3 gene was 0.275; however, the frequency of this polymorphism has not been reported in the dbSNP database (www.ncbi.nlm.nih.gov/SNP). A series of our previous studies showed that polymorphisms of oncogenes, tumor suppressor genes, and receptor tyrosine kinases are related to lung cancer risk [6, 28, 29]. Recently, we reported that STK11 and PIK3CA polymorphisms are not related to genetic susceptibility to lung cancer [30, 31]. The genotypes of the AKT2 and AKT3 promoter polymorphisms, determined in 720 Koreans in the present study, revealed no significant difference between lung cancer patients and normal controls. To our best knowledge, this is the first study on the association of AKT2 and AKT3 promoter polymorphisms and the risk of lung cancer in a Korean population.

Acknowledgments

This study was supported by the Korea Healthcare Technology R&D Project, Ministry of Health, Welfare and Family Affairs, Republic of Korea (Grant No. A010250).

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Fig. 1
Polymorphism location in promoter region and linkage disequilibrium (LD). Coding exons are marked by black blocks, and untranslated regions are marked by white blocks. The first base of the translational site is denoted as nucleotide +1. (A) AKT2 location of promoter polymorphisms and LD block. (B) AKT3 location of promoter polymorphisms. The LD of AKT3 polymorphisms was not identified. aFurther analyses polymorphism sites.
gni-10-167-g001.jpg
Table 1.
Characteristics of the study subjects
Variables Cases (%) Controls (%) p-value
Age (y) 60.14 ± 9.39 60.56 ± 10.28 0.552
Gender
 Male 262 (72.8) 264 (73.3) 0.933
 Female 98 (27.2) 96 (26.7)
Smoking status
 Smoker 253 (71.9) 127 (46.7) <0.001
 Non-smoker 99 (28.1) 145 (53.3)
Stage
 1-3a 76 (24.0)
 3b-4 241 (76.0)
Cell type
 Adenocarcinoma (Adcc) 148 (43.1)
 Squamous carcinoma (Sqcc) 110 (32.1)
 Other carcinoma 85 (24.8)

Other carcinomas include small cell, large cell, mixed cell carcinomas, and undifferentiated carcinomas.

Table 2.
Polymorphism confirmation of the AKT2 and AKT3 promoter region by direct sequencing
Gene SNP location rs no. Frequency
AKT2 -9826 C/G Novel C : G = 0.957 : 0.043
-9473 C/T rs9636120 C : T = 0.636 : 0.364
-9151 T/C rs1991823 T : C = 0.543 : 0.457
-9025 C/T rs4239505 C : T = 0.935 : 0.065
-8618 G/A rs11669332 G : A = 0.937 : 0.063
AKT3 -811 A/G Novel A : G = 0.979 : 0.021
-675 A/- rs35835614 A:- = 0.688:0.312
-244 C/T rs12043115 C : T = 0.978 : 0.022

SNP, single-nucleotide polymorphisms.

Table 3.
Association between AKT2 and AKT3 promoter polymorphisms and the risk of lung cancer
Group Gene Locus Genotype Case (%) Control (%) Dominant
Recessive
Co-dominant
aOR (95% CI) p-value aOR (95% CI) p-value aOR (95% CI) p-value
Overall AKT2 -9826 C/G CC 318 (91.12) 328 (91.88)
CG 30 (8.6) 26 (7.28) 1.18 (0.65-2.14) 0.58 1.24 (0.70-2.20) 0.470
GG 1 (0.29) 3 (0.84)
-9473 C/T CC 133 (37.68) 141 (41.23)
CT 161 (45.61) 142 (41.52) 0.93 (0.66-1.31) 0.666 0.95 (0.61-1.49) 0.83 0.95 (0.75-1.21) 0.682
TT 59 (16.71) 59 (17.25)
-9151 C/T CC 127 (35.88) 117 (32.5)
CT 172 (48.59) 158 (43.89) 0.97 (0.69-1.38) 0.875 0.80 (0.51-1.24) 0.31 0.92 (0.73-1.17) 0.513
TT 55 (15.54) 85 (23.61)
-9025 C/T CC 333 (93.28) 338 (94.68)
CT 23 (6.44) 18 (5.04) 1.21 (0.61-2.41) 0.592 0.45 (0.03-7.25) 0.572 1.13 (0.59-2.16) 0.706
TT 1 (0.28) 1 (0.28)
-8618 G/A GG 313 (87.43) 319 (90.63)
GA 44 (12.29) 29 (8.24) 1.23 (0.75-2.12) 0.385 0.71 (0.06-7.94) 0.778 1.21 (0.74-1.96) 0.449
AA 1 (0.28) 4 (1.14)
AKT3 -675 A/- AA 181 (50.84) 193 (56.76)
A- 154 (43.26) 115 (33.82) 1.07 (0.77-1.50) 0.673 0.57 (0.30-1.10) 0.094 0.96 (0.73-1.25) 0.734
-- 21 (5.9) 32 (9.41)
Male AKT2 -9826 C/G CC 235 (92.16) 242 (92.72)
CG 20 (7.84) 16 (6.13) 1.40 (0.62-3.15) 0.423 1.40 (0.62-3.15) 0.423
GG 0 (0) 3 (1.15)
-9473 C/T CC 95 (36.96) 103 (41.7)
CT 114 (44.36) 97 (39.27) 0.89 (0.58-1.37) 0.598 1.02 (0.60-1.74) 0.933 0.96 (0.72-1.27) 0.760
TT 48 (18.68) 47 (19.03)
-9151 C/T CC 98 (38.28) 94 (35.61)
CT 120 (46.88) 105 (39.77) 0.96 (0.63-1.46) 0.841 0.78 (0.50-1.36) 0.387 0.92 (0.68-1.23) 0.555
TT 38 (14.84) 65 (24.62)
-9025 C/T CC 239 (91.92) 249 (95.4)
CT 20 (7.69) 11 (4.21) 1.90 (0.77-4.71) 0.167 0.42 (0.03-6.70) 0.535 1.59 (0.70-3.66) 0.271
TT 1 (0.38) 1 (0.38)
-8618 G/A GG 231 (88.51) 236 (91.83)
GA 30 (11.49) 19 (7.39) 1.31 (0.66-2.60) 0.443 1.31 (0.66-2.60) 0.443
AA 0 (0) 2 (0.78)
AKT3 -675 A/- AA 125 (48.26) 138 (56.56)
A- 117 (45.17) 77 (31.56) 1.26 (0.83-1.90) 0.281 0.54 (0.23-1.12) 0.096 1.02 (0.74-1.41) 0.901
- 17 (6.56) 29 (11.89)
Female AKT2 -9826 C/G CC 83 (88.3) 86 (89.58)
CG 10 (10.64) 10 (10.42) 1.06 (0.41-2.73) 0.906 0.991 1.14 (0.47-2.77) 0.768
GG 1 (1.06) 0 (0)
-9473 C/T CC 38 (39.58) 38 (40)
CT 47 (48.96) 45 (47.37) 1.10 (0.60-2.04) 0.760 1.02 (0.41-2.56) 0.960 1.06 (0.67-1.67) 0.803
TT 11 (11.46) 12 (12.63)
-9151 C/T CC 29 (29.59) 23 (23.96)
CT 52 (53.06) 53 (55.21) 0.78 (0.40-1.52) 0.466 0.79 (0.36-1.71) 0.550 0.83 (0.53-1.29) 0.405
TT 17 (17.35) 20 (20.83)
-9025 C/T CC 94 (96.91) 89 (92.71)
CT 3 (3.09) 7 (7.29) 0.39 (0.09-1.61) 0.192 0.39 (0.09-1.61) 0.192
TT 0 (0) 0 (0)
-8618 G/A GG 82 (84.54) 83 (87.37)
GA 14 (14.43) 10 (10.53) 1.17 (0.50-2.74) 0.718 0.50 (0.04-5.74) 0.575 1.05 (0.51-2.17) 0.897
AA 1 (1.03) 2 (2.11)
AKT3 -675 A/- AA 56 (57.73) 55 (57.29)
A- 37 (38.14) 38 (39.58) 0.92 (0.50-1.67) 0.778 1.02 (0.21-5.03) 0.984 0.94 (0.56-1.56) 0.811
-- 4 (4.12) 3 (3.13)
Smoker AKT2 -9826 C/G CC 226 (92.24) 119 (95.2)
CG 19 (7.76) 6 (4.8) 1.60 (0.61-4.20) 0.337 1.60 (0.61-4.20) 0.337
GG 0 (0) 0 (0)
-9473 C/T CC 90 (36.29) 45 (36.29)
CT 115 (46.37) 53 (42.74) 0.98 (0.62-1.55) 0.935 0.85 (0.49-1.49) 0.572 0.95 (0.70-1.28) 0.720
TT 43 (17.34) 26 (20.97)
-9151 C/T CC 95 (38.46) 48 (37.8)
CT 116 (46.96) 56 (44.09) 0.97 (0.62-1.52) 0.885 0.70 (0.39-1.27) 0.239 0.89 (0.65-1.22) 0.476
TT 36 (14.57) 23 (18.11)
-9025 C/T CC 229 (91.6) 122 (97.6)
CT 20 (8) 2 (1.6) 3.36 (0.98-11.54) 0.055 0.40 (0.03-6.44) 0.517 2.35 (0.82-6.76) 0.113
TT 1 (0.4) 1 (0.8)
-8618 G/A GG 222 (88.1) 116 (92.06)
GA 30 (11.9) 10 (7.94) 1.43 (0.67-3.07) 0.356 1.43 (0.67-3.07) 0.356
AA 0 (0) 0 (0)
AKT3 -675 A/- AA 120 (48) 71 (56.35)
A- 114 (45.6) 39 (30.95) 1.44 (0.93-2.23) 0.105 0.48 (0.23-1.02) 0.055 1.07 (0.76-1.51) 0.682
-- 16 (6.4) 16 (12.7)
Non-smoker AKT2 -9826 C/G CC 87 (88.78) 128 (88.28)
CG 10 (10.2) 17 (11.72) 0.97 (0.43-2.18) 0.947 0.991 1.06 (0.50-2.27) 0.875
GG 1 (1.02) 0 (0)
-9473 C/T CC 39 (40.21) 52 (36.36)
CT 43 (44.33) 72 (50.35) 0.85 (0.50-1.45) 0.556 1.15 (0.55-2.40) 0.712 0.96 (0.65-1.40) 0.818
TT 15 (15.46) 19 (13.29)
-9151 C/T CC 30 (30.3) 45 (31.03)
CT 52 (52.53) 73 (50.34) 1.09 (0.62-1.91) 0.773 0.92 (0.47-1.81) 0.816 1.01 (0.70-1.45) 0.950
TT 17 (17.17) 27 (18.62)
-9025 C/T CC 96 (96.97) 133 (91.72)
CT 3 (3.03) 12 (8.28) 0.35 (0.10-1.28) 0.114 0.35 (0.10-1.28) 0.114
TT 0 (0) 0 (0)
-8618 G/A GG 85 (85.86) 125 (86.81)
GA 13 (13.13) 17 (11.81) 1.11 (0.52-2.33) 0.792 0.74 (0.07-8.29) 0.806 1.06 (0.55-2.04) 0.871
AA 1 (1.01) 2 (1.39)
AKT3 -675 A/- AA 58 (59.18) 73 (51.05)
A- 36 (36.73) 64 (44.76) 0.72 (0.42-1.20) 0.206 0.91 (0.25-3.35) 0.888 0.77 (0.50-1.21) 0.255
-- 4 (4.08) 6 (4.2)

Adjusted odds ratio (aOR) and p-values were calculated by unconditional logistic regression, adjusted for age, gender, and smoking history.

Logistic regression models were used to calculate the aORs, 95% confidence intervals (CIs), and the corresponding p-values of co-dominant (minor allele homozygotes vs. heterozygotes vs. major allele homozygotes), dominant (minor allele homozygotes + heterozygotes vs. major allele homozygotes), and recessive (minor allele homozygotes vs. heterozygotes + major allele homozygotes) models after controlling for age, gender, and smoking status.

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