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ADH1B and CDH1 polymorphisms predict prognosis in male patients with non-metastatic laryngeal cancer

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Oncotarget. 2016; 7:73216-73228. https://doi.org/10.18632/oncotarget.12301

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Daxu Li, Ruizhi Zhang, Tianbo Jin, Na He, Le Ren, Zhe Zhang, Qingna Zhang, Ran Xu, Hong Tao, Guang Zeng and Jing Gao _

Abstract

Daxu Li1,*, Ruizhi Zhang2,*, Tianbo Jin3, Na He3, Le Ren1, Zhe Zhang1, Qingna Zhang1, Ran Xu1, Hong Tao1, Guang Zeng4, Jing Gao5

1Department of Stomatology, First Affiliated Hospital, Xi’an Jiaotong University School of Medicine, Xi’an, Shaanxi 710061, China

2Department of Stomatology, Ankang Central Hospital, Ankang 725000, Shaanxi, China

3School of Medicine, Xizang Minzu University, Xianyang, Shaanxi 712082, China

4Department of Plastic and Burn Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi 710038, China

5State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi 710032, China

*These authors contributed equally to this work

Correspondence to:

Jing Gao, email: [email protected]

Guang Zeng, email: [email protected]

Keywords: laryngeal cancer, polymorphism, prognosis, ADH1B, CDH1

Received: May 31, 2016     Accepted: September 20, 2016     Published: September 28, 2016

ABSTRACT

In this study, we assessed the association between single nucleotide polymorphisms (SNPs) in candidate genes and the prognosis of laryngeal cancer (LC) patients. Thirty-seven SNPs in 26 genes were genotyped in 170 male Han Chinese patients with LC. The effects of the candidate genes on the prognosis of LC patients were evaluated using Kaplan-Meier curves and Cox proportional hazards regression models. The GA genotype of rs1229984 (hazard ratio [HR], 0.537; 95% confidence interval [CI], 0.340–0.848; p = 0.008) in alcohol dehydrogenase 1B (ADH1B), and the AA genotype of rs9929218 (HR, 6.074; 95% CI, 1.426–25.870; p = 0.015) in CDH1 were associated with overall survival. Our data suggest that polymorphisms in ADH1B and CDH1 may be prognostic indicators in LC.


INTRODUCTION

Laryngeal cancer (LC) is a common type of malignant head and neck tumor, and the incidence is increasing yearly [1]. However, the etiology of LC remains unclear and the prognosis is poor. LC can result from both environmental and genetic factors [2, 3]. While the majority of LC patients have a history of smoking and alcohol consumption [4], only a small percentage of individuals with similar histories eventually develop LC. This suggests that genetic susceptibility underlies LC [5].

Host genetic factors may influence the prognosis of cancer patients. Recently, various genetic polymorphisms were associated with a risk of LC [69]. Polymorphisms may contribute to cancer susceptibility, progression, and response to therapy. Previous studies have primarily assessed associations between single nucleotide polymorphisms (SNPs) and LC risk using case-control models. Rare host genetic factors that influence the prognosis of advanced LC patients have been reported. Long-term longitudinal studies are required to evaluate the impact of SNPs on disease progression, treatment response, and patient survival.

In this study, we investigated 37 SNPs in 27 genes that were previously associated with head and neck cancers to determine whether they were associated with the prognosis of LC patients.

RESULTS

The demographic and clinical characteristics of the LC patients are shown in Table 1. The median age of the patients was 60 years (range, 32–82). All of the patients were men who were metastasis-free. The mean follow-up period was 38 months (range: 3–122). There were 100 deaths at the time of the last observation. Overall, the median survival time was 48 months.

Table 1: Characteristics of patients included in this study

Variables

N (%)

p value

Total number of patients enrolled

170

Age

> 0.05

 < 60

80 (47.06)

 ≥ 60

90 (52.94)

Tumor differentiation

> 0.05

 Well

31 (18.24)

 Moderate

125 (73.53)

 Poor

14 (8.23)

pT

< 0.001

 T1

40 (23.53)

 T2

62 (36.47)

 T3

50 (29.41)

 T4

18 (10.59)

pN

< 0.001

 N0

116 (68.23)

 N1

30 (17.65)

 N2

24 (14.12)

WHO grade

< 0.001

 I

37 (21.76)

 II

36 (21.18)

 III

61 (35.88)

 IV

36 (21.18)

Surgery method

< 0.001

 Partial laryngectomy

104 (61.18)

 Total laryngectomy

66 (38.82)

Cervical lymph node dissection

> 0.05

 Yes

37 (21.76)

 No

133 (78.24)

No. patients with follow-up information available

170

 Median follow-up time, months

38

 Median survival time, months

48

Status at last observation

 Alive

70 (41.18)

 Death

100 (58.82)

T, pathologic tumor stage; N, pathologic nodal stage.

Clinical factors including age, pT, pN, WHO grade, degree of tumor differentiation, surgical method, and whether the patient underwent cervical lymph node dissection were assessed in a univariate analysis (Table 2). The distribution of the studied SNPs in the WHO grade was listed in Supplementary Table S1. We identified significant associations between clinical factors including the degree of tumor differentiation, pT, pN, WHO grade, and surgical method and LC patient prognosis. All of these factors increased the risk of mortality. Compared to patients with T1–T2 stage disease, N0, I–II grade, and who underwent partial laryngectomy, patients with T3–T4 stage, N1–N2, III–IV grade, and who underwent total laryngectomy had elevated risks of death, with HRs and 95% CIs of 2.17 (1.448–3.253), 2.394 (1.582–3.623), 3.298 (2.100–5.180) and 2.346 (1.576–3.492), respectively (Figure 1).

Table 2: Univariate analysis of the impact of clinical factors on prognosis for LC patients

Variables

Overall survival

Event/total

MST (months)

HR (95% CI)

Log-rank p

Age

 < 60

47/80

59.0

Ref

 ≥ 60

53/90

48.0

1.161 (0.782–1.722)

0.456

Tumor differentiation

 Well

18/31

71.0

Ref

 Moderate

70/125

59.0

0.933 (0.556–1.567)

0.008

 Poor

12/14

15.0

2.397 (1.150–4.997)

pT

 T1–T2

52/102

77.0

Ref

 T3–T4

48/68

32.0

2.170 (1.448–3.253)

< 0.001

pN

 N0

61/116

71.0

Ref

 N1-N2

39/54

26.0

2.394 (1.582–3.623)

< 0.001

WHO grade

 I–II

30/73

98.0

Ref

 III–IV

70/97

32.0

3.298 (2.100–5.180)

< 0.001

Surgery method

 Partial laryngectomy

50/104

73.0

Ref

 Total laryngectomy

50/66

30.0

2.346 (1.576–3.492)

< 0.001

Cervical lymph node dissection

 Yes

19/37

36.0

Ref

 No

81/133

56.0

0.711 (0.425–1.189)

0.188

T, pathologic tumor stage; N, pathologic nodal stage;

MST, median survival time; HR, hazard ratio; 95% CI, 95% confidence interval.

Kaplan-Meier analysis of LC patient overall survival according to the pT, pN, WHO grade, and surgical method.

Figure 1: Kaplan-Meier analysis of LC patient overall survival according to the pT, pN, WHO grade, and surgical method.

The basic characteristics of all candidate SNPs that were analyzed in the study, including chromosome, position, band, alleles A/B, gene(s), and role(s), are shown in Table 3. Two of the 37 candidate SNPs evaluated showed statistically significantly correlations with overall survival (Table 4) according to Log-rank tests and Cox regression analysis. The A/G genotype of alcohol dehydrogenase 1B (ADH1B) rs1042026 (HR, 0.538; 95% CI, 0.345–0.839) and G/A genotype of rs1229984 (HR, 0.659; 95% CI, 0.438–0.991) were associated with increased overall survival. Kaplan-Meier curves of overall survival for the different genotypes of rs1042026 and rs1229984 are shown in Figure 2.

Table 3: Candidate SNP data

SNP ID

Chr

Position

Band

Alleles A/B

Gene(s)

Role

rs13130787

4

94887031

4q22.2

T/C

rs3805322

4

100056998

4q23

G/A

ADH4

Intron

rs1042026

4

100228466

4q23

A/G

ADH1B

3′ UTR

rs1229984

4

100239319

4q23

G/A

ADH1B

Coding exon

rs1789924

4

100274286

4q23

T/C

ADH1C

Promoter

rs971074

4

100341861

4q23

A/G

ADH7

Coding exon

rs1000589

13

64141913

13q21.31

G/T

rs1585440

13

66481815

13q21.32

A/C

rs9573163

13

73908846

13q22.1

C/G

rs9543325

13

73916628

13q22.1

T/C

rs1886449

13

73932114

13q22.1

T/C

rs2039553

13

80299722

13q31.1

G/A

rs944289

14

36649246

14q13.3

T/C

rs4444235

14

54410919

14q22.2

C/T

BMP4

Downstream

rs4779584

15

32994756

15q13.3

C/T

SCG5

Downstream

rs4785204

16

50103734

16q12.1

T/C

HEATR3

Intron

rs9929218

16

68820946

16q22.1

A/G

CDH1

Intron

rs17761864

17

2171637

17p13.3

A/C

SMG6

Intron

rs4924935

17

18753870

17p11.2

C/T

PRPSAP2

Promoter

rs225190

17

30877658

17q11.2

G/A

MYO1D

Intron

rs6503659

17

39897264

17q21.2

A/T

HAP1

Promoter

rs2257205

17

56448297

17q22

A/G

RNF43

Coding exon

rs2847281

18

12821593

18p11.21

C/T

PTPN2

Intron

rs12456874

18

13366862

18p11.21

G/A

C18orf1

Intron

rs4939827

18

46453463

18q21.1

T/C

SMAD7

Intron

rs7504990

18

50517776

18q21.2

T/C

DCC

Intron

rs961253

20

6404281

20p12.3

A/C

rs2423279

20

7812350

20p12.3

C/T

rs4925386

20

60921044

20q13.33

T/C

LAMA5

Intron (boundary)

rs372883

21

30717737

21q21.3

G/A

BACH1

Intron

rs455804

21

31146169

21q21.3

T/G

NCRNA00110

Downstream

rs2014300

21

36357861

21q22.12

A/G

RUNX1

Intron

rs1547374

21

43778895

21q22.3

G/A

TFF1

Downstream

rs4822983

22

29115066

22q12.1

T/C

CHEK2

Intron

rs738722

22

29130012

22q12.1

T/C

HSCB

Promoter

rs2239815

22

29192670

22q12.1

T/C

XBP1

Intron

rs5768709

22

48929569

22q13.32

A/G

FAM19A5

Intron

A/B, minor/major alleles; Chr, chromosome.

Table 4: Univariate analysis of the associations between the candidate SNPs and LC patient survival

SNP ID

Genotype

Event/total

MST (months)

HR (95% CI)

Log-rank p

rs13130787

C/C

19/38

98

Ref

T/C

71/113

39

1.638 (0.986–2.722)

0.152

T/T

10/19

62

1.414 (0.656–3.049)

rs3805322

A/A

22/39

73

Ref

G/A

59/98

44

0.982 (0.601–1.604)

0.997

G/G

19/33

50

0.981 (0.529–1.818)

rs1042026

G/G

30/40

31

Ref

A/G

58/114

81

0.538 (0.345–0.839)

0.001

A/A

3/4

8

2.344 (0.709–7.741)

rs1229984

A/A

39/54

36

Ref

G/A

57/104

48

0.659 (0.438–0.991)

0.043

G/G

2/9

0.291(0.070-1.206)

rs1789924

C/C

95/158

46

Ref

T/C

4/11

84

0.542 (0.198–1.481)

0.222

T/T

rs971074

G/G

73/125

50

Ref

A/G

26/44

46

1.118 (0.714–1.751)

0.624

A/A

rs1000589

T/T

42/66

38

Ref

G/T

38/77

68

0.691 (0.444–1.075)

0.003

G/G

20/26

22

1.711 (0.997-2.937)

rs1585440

C/C

23/33

62

Ref

A/C

75/134

48

0.803 (0.502–1.286)

0.595

A/A

1/2

11

1.299 (0.174–9.683)

rs9573163

G/G

30/59

62

Ref

C/G

56/92

40

1.397 (0.896–2.180)

0.113

C/C

14/19

36

1.882 (0.996–3.558)

rs9543325

C/C

33/47

35

Ref

T/C

47/86

66

0.691 (0.443–1.080)

0.200

T/T

20/37

59

0.674 (0.386–1.176)

rs1886449

C/C

6/11

77

Ref

T/C

75/131

48

1.193 (0.518–2.746)

0.898

T/T

2/2

20

1.365 (0.266–6.991)

rs2039553

A/A

32/58

81

Ref

G/A

19/32

32

1.474 (0.832–2.612)

0.389

G/G

19/36

62

1.075 (0.607–1.902)

rs944289

C/C

16/26

62

Ref

T/C

79/137

50

0.712 (0.414–1.223)

0.068

T/T

2/3

6

2.792 (0.638–12.221)

rs4444235

T/T

25/34

40

Ref

C/T

63/115

59

0.762 (0.479–1.211)

0.506

C/C

6/11

84

0.859 (0.352–2.098)

rs4779584

T/T

65/103

48

Ref

C/T

30/57

62

0.805 (0.521–1.242)

0.611

C/C

5/10

44

0.905 (0.363–2.256)

rs4785204

C/C

51/87

46

Ref

T/C

32/54

59

1.002 (0.643–1.560)

0.803

T/T

10/16

37

1.248 (0.631–2.467)

rs9929218

G/G

70/118

48

Ref

A/G

27/48

73

0.855 (0.548–1.334)

0.081

A/A

2/2

14

3.931 (0.946–16.324)

rs17761864

C/C

75/120

46

Ref

A/C

16/37

0.660 (0.384–1.133)

0.087

A/A

3/4

7

2.282 (0.714–7.297)

rs4924935

T/T

80/130

44

Ref

C/T

13/28

98

0.596 (0.331–1.074)

0.110

C/C

5/7

32

1.578 (0.635–3.920)

rs225190

A/A

54/96

62

Ref

G/A

40/65

44

1.137 (0.754–1.715)

0.634

G/G

4/6

18

1.528 (0.551–4.238)

rs6503659

T/T

73/123

56

Ref

A/T

23/42

36

0.981 (0.614–1.569)

0.634

A/A

2/3

22

1.935 (0.473–7.918)

rs2257205

G/G

26/41

44

Ref

A/G

55/102

62

0.647 (0.403–1.039)

0.152

A/A

16/24

48

0.891 (0.477–1.664)

rs2847281

T/T

75/129

56

Ref

C/T

24/38

44

1.095 (0.690–1.739)

0.698

C/C

rs12456874

A/A

91/158

48

Ref

G/A

9/12

26

1.327 (0.667–2.638)

0.415

G/G

rs4939827

C/C

72/118

48

Ref

T/C

23/46

91

0.920 (0.575–1.473)

0.772

T/T

1/1

36

1.818 (0.251–13.145)

rs7504990

C/C

60/99

44

Ref

T/C

36/62

62

0.889 (0.587–1.347)

0.729

T/T

4/9

71

0.720 (0.261–1.982)

rs961253

C/C

87/146

44

Ref

A/C

13/24

68

0.928 (0.518–1.663)

0.801

A/A

rs2423279

T/T

65/117

48

Ref

C/T

30/47

59

0.976 (0.632–1.508)

0.912

C/C

0/1

rs4925386

C/C

59/107

62

Ref

T/C

17/25

40

1.160 (0.676–1.991)

0.608

T/T

2/5

0.574 (0.139–2.370)

rs372883

A/A

7/15

Ref

G/A

82/137

56

0.993 (0.457–2.159)

0.958

G/G

1/2

11

1.331 (0.163–10.863)

rs455804

G/G

47/84

62

Ref

T/G

42/69

44

1.228 (0.809–1.863)

0.126

T/T

8/12

22

2.115 (0.989–4.520)

rs2014300

G/G

73/127

48

Ref

0.522

A/G

25/38

39

1.113 (0.706–1.755)

A/A

1/1

26

2.793 (0.385–20.276)

rs1547374

A/A

22/38

56

Ref

G/A

61/106

59

0.994 (0.610–1.623)

0.330

G/G

16/24

35

1.493 (0.777–2.866)

rs4822983

C/C

66/114

50

Ref

T/C

29/45

44

1.051 (0.678–1.628)

0.976

T/T

3/5

32

1.008 (0.312–3.257)

rs738722

C/C

17/27

66

Ref

T/C

65/119

59

0.713 (0.417–1.218)

0.370

T/T

3/4

5

1.113 (0.315–3.933)

rs2239815

C/C

34/65

56

Ref

T/C

50/77

44

1.300 (0.840–2.012)

0.325

T/T

6/11

114

1.113 (0.332–1.915)

rs5768709

G/G

18/31

59

Ref

A/G

77/132

48

1.025 (0.613–1.715)

0.951

A/A

5/7

35

1.173 (0.430–3.200)

MST, median survival time; HR, hazard ratio; 95% CI, 95% confidence interval;

Long-rank p values were calculated using the Chi-Square test.

The individual effects of rs1042026 and rs1229984 on overall survival.

Figure 2: The individual effects of rs1042026 and rs1229984 on overall survival.

After adjusting for the various clinical factors, multivariate Cox regression analysis demonstrated that SNP genotype was an independent prognostic factor for overall survival. We identified significant correlations between two SNPs (ADH1B rs1229984 and CDH1 rs9929218) and the prognosis of LC patients (Table 5). The G/A genotype of ADH1B rs1229984 was associated with increased overall survival (HR, 0.537; 95% CI, 0.340–0.848; p = 0.008), and the A/A genotype of CDH1 rs9929218 with reduced overall survival (HR, 6.074; 95% CI, 1.426–25.870; p = 0.0015).

Table 5: Multivariate analysis of the associations between candidate SNPs and LC patient survival

SNP ID

Genotype

HR (95% CI)

p

rs13130787

C/C

Ref

T/C

1.641 (0.975–2.760)

0.062

T/T

1.868 (0.856–4.073)

0.116

rs1042026

G/G

Ref

A/G

0.668 (0.420–1.060)

0.087

A/A

1.898 (0.550–6.543)

0.310

rs1229984

A/A

Ref

G/A

0.537 (0.340–0.848)

0.008

G/G

0.352 (0.084–1.477)

0.154

rs1000589

T/T

Ref

G/T

0.773 (0.483–1.236)

0.282

G/G

1.734 (0.999–3.010)

0.050

rs9573163

G/G

Ref

C/G

1.515 (0.958–2.394)

0.075

C/C

1.573 (0.811–3.050)

0.180

rs9543325

C/C

Ref

T/C

0.791 (0.505–1.240)

0.307

T/T

0.673 (0.378–1.200)

0.180

rs944289

C/C

Ref

T/C

0.831 (0.477–1.448)

0.514

T/T

2.391 (0.513–11.139)

0.267

rs9929218

G/G

Ref

A/G

0.998 (0.637–1.565)

0.994

A/A

6.074 (1.426–25.870)

0.015

rs17761864

C/C

Ref

A/C

0.577 (0.328–1.018)

0.058

A/A

1.82 (0.523–6.338)

0.347

rs4924935

T/T

Ref

C/T

0.692 (0.380–1.261)

0.229

C/C

1.334 (0.501–3.549)

0.564

rs2257205

G/G

Ref

A/G

0.783 (0.478–1.284)

0.333

A/A

0.863 (0.454–1.642)

0.654

rs455804

G/G

Ref

T/G

1.199 (0.783–1.838)

0.404

T/T

1.872 (0.812–4.312)

0.141

HR, hazard ratio; 95% CI, 95% confidence interval.

All p values were calculated using the Wald test.

A p < 0.05 indicates statistical significance.

DISCUSSION

We evaluated the effects of 37 SNPs in 26 genes on the prognosis of 170 Han Chinese male LC patients. We demonstrated that ADH1B rs1042026, ADH1B rs1229984, and CDH1 rs9929218 were significantly associated with overall survival. Our data shed new light on the association between genetic variations in the ADH1B and CDH1 genes and LC prognosis in the Han Chinese population.

The ADH1B gene is located on chromosome 4q21-q23. The rs1229984 variant in the ADH1B gene causes a missense mutation (R48H) which increases the activity of the ADH1B enzyme (i.e. faster acetaldehyde production generated by ethanol oxidation) [10, 11]. Following alcohol consumption, elevated ADH1B activity is thought to transiently increase the level of acetaldehyde, which leads to unpleasant effects that limit the desire to continue drinking. A meta-analysis of this variant in Asian, European, and African Americans populations (where the rs1229984 A allele is common) demonstrated a strong association with alcohol-related disorder risk [1214].

The CDH1 gene encodes the E-cadherin protein, which is a 120 kDa glycoprotein that consists of an extracellular domain containing five tandem repeats, a cytoplasmic domain, and a single transmembrane domain [15, 16]. CDH1 hypermethylation is one of the mechanisms by which E-cadherin expression is silenced. Abnormal CDH1 expression has been linked to many human diseases including cancer, nephrolithiasis, pre-eclampsia, and ectopic pregnancy [17, 18]. Association between rs9929218 and both colorectal cancer risk and survival have also been observed [1921]. Our results demonstrated that CDH1 rs9929218 AA genotype was associated with reduced overall survival in the Chinese Han population. However, additional studies with larger cohorts derived from other populations are necessary.

Differences in survival were most apparent in individuals with T stage. There are several possible explanations for this finding. First, because individuals with T stage have already acquired many somatic mutations that could drive tumor growth or therapeutic resistance, subtle variations that alter the DNA repair capacity will not have a significant impact. Second, the differences in survival may reflect radiation-related outcomes, given that most T stage individuals received radiation treatment for the primary tumor, whereas only a minority of T stage individuals received radiation for treatment of the primary tumor. However, the latter explanation does not account for the common occurrence of relapsed metastatic disease outside the field of radiation.

In summary, our data raise the possibility that three polymorphisms may be one of major driving forces of LC progression, and could be valuable prognostic markers for LC patients. Further studies will focus on the functional experiments based on the relevant genes on animal models, to investigate detailed mechanism involved.

MATERIALS AND METHODS

Study participants

A total of 170 male patients (median age 60 years, range 32–82) who were diagnosed with LC at the First Affiliated Hospital of the Medical College of Xi’an Jiaotong University before 2002 and who were followed-up from January 2002 to April 2013 were included in the study. All patients underwent resection for LC at the same hospital. Additionally, all patients were Han Chinese from Xi’an city and the surrounding regions. The research protocol was performed according to the Declaration of Helsinki and was approved by the Human Research Committee of the First Affiliated Hospital of the Medical College of Xi’an Jiaotong University for the Approval of Research Involving Human Subjects. Informed consent was obtained from all patients.

Demographic and clinical data

Patient demographic and clinical data including age, sex, ethnicity, residential region, smoking status, alcohol use, education status, body mass index, and family history of cancer were collected through in-person interviews using a standardized epidemiological questionnaire. Detailed clinical information including the time of diagnosis, time of surgery and/or treatment with chemotherapy, time of recurrence and/or death, tumor stage, degree of differentiation, location, whether lymph node dissection was performed, and the treatment protocol was collected through medical chart review or physician consultation. Standard follow-up was performed by a trained specialist through on-site interviews, direct calls, or written communication with either patients or family members. The most recent follow-up data in this analysis were obtained in April 2013. No patients were lost during follow-up.

SNP selection and genotyping

We selected 37 SNPs with a minor allele frequency (MAF) > 5% in the HapMap Han Chinese population in Beijing that were previously associated with head and neck cancer [2224] for genotyping. Genomic DNA was extracted from peripheral blood leukocytes using GoldMag® nanoparticles (GoldMag Ltd. Xi’an, China) according to the manufacturer’s instructions. DNA concentrations were estimated using a NanoDrop 2000 (Thermo Scientific, Waltham, Massachusetts, USA). The Sequenom MassARRAY Assay Design 3.0 Software was used to design Multiplexed SNP MassEXTEND assays [25]. Genotyping was performed using a Sequenom MassARRAY RS1000 [25]. Data management and analysis were performed using the Sequenom Typer 4.0 software as previously described [25, 26].

Data analysis

All follow-up survey and experimental data were analyzed using SPSS 17.0 (SPSS, Chicago, IL, USA). Survival time was defined as the time between the date of diagnosis and either the date of death (deceased patients) or last contact date (living patients). The Kaplan-Meier method was used to estimate overall survival. The survival curves were compared using Log-rank tests. Univariate analysis included the following factors: age, degree of tumor differentiation, pathologic tumor stage (pT), pathologic nodal stage (pN), WHO grade, surgical method, whether cervical lymph node dissection was performed, and the 37 candidate SNPs. Univariate and multivariable Cox proportional hazard models were used to calculate hazard ratio (HRs) and 95% confidence intervals (CIs). Two-sided p values < 0.05 were considered statistically significant and were calculated using the Wald test.

CONFLICTS OF INTEREST

The authors declare that there are no conflicts of interest.

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