Oncotarget

Research Papers:

The TERT rs2736100 polymorphism increases cancer risk: A meta-analysis

PDF |  HTML  |  How to cite  |  Order a Reprint

Oncotarget. 2017; 8:38693-38705. https://doi.org/10.18632/oncotarget.16309

Metrics: PDF 1394 views  |   HTML 1596 views  |   ?  

Hui Li, Yanyan Xu, Hua Mei, Liang Peng, Xiaojie Li and Jianzhou Tang _

Abstract

Hui Li1,*, Yanyan Xu2,*, Hua Mei3, Liang Peng4, Xiaojie Li5 and Jianzhou Tang4,5

1Department of Microbiology and Immunology, Medical School of Jishou University, Jishou 416000, Hunan, China

2Department of Molecular Pathology, Guangzhou Kingmed Center for Clinical Laboratory, Guangzhou 510000, China

3Department of Somatic Stem Cell, Hunan Guangxiu Hospital, Changsha 410002, Hunan, China

4Department of Biological and Environmental Engineering, Changsha University, Changsha 410003, Hunan, China

5College of Animal Science and Technology of Hunan Agriculture University, Changsha 410128, Hunan, China

*These authors have contributed equally to this work and should be considered as co-first authors

Correspondence to:

Jianzhou Tang, email: Z20050711@ccsu.edu.cn

Keywords: TERT, cancer, risk, meta-analysis, telomerase

Received: December 27, 2016    Accepted: February 15, 2017    Published: March 17, 2017

ABSTRACT

Abnormal telomerase activity is implicated in cancer initiation and development. The rs2736100 T > G polymorphism in the telomerase reverse transcriptase (TERT) gene, which encodes the telomerase catalytic subunit, has been associated with increased cancer risk. We conducted a meta-analysis to more precisely assess this association. After a comprehensive literature search of the PubMed and EMBASE databases up to November 1, 2016, 61 articles with 72 studies comprising 108,248 cases and 161,472 controls were included in our meta-analysis. Studies were conducted on various cancer types. The TERT rs2736100 polymorphism was associated with increased overall cancer risk in five genetic models [homozygous model (GG vs. TT): odds ratio (OR) = 1.39, 95% confidence interval (95% CI) = 1.26-1.54, P < 0.001; heterozygous model (TG vs. TT): OR = 1.16, 95% CI = 1.11-1.23, P < 0.001; dominant model (TG + GG vs. TT): OR = 1.23, 95% CI = 1.15-1.31, P < 0.001; recessive model (GG vs. TG + TT): OR = 1.25, 95% CI = 1.16-1.35, P < 0.001; and allele contrast model (G vs. T): OR = 1.17, 95% CI = 1.12-1.23, P < 0.001]. A stratified analysis based on cancer type associated the polymorphism with elevated risk of thyroid cancer, bladder cancer, lung cancer, glioma, myeloproliferative neoplasms, and acute myeloid leukemia. Our results confirm that the TERT rs2736100 polymorphism confers increased overall cancer risk.


INTRODUCTION

Cancer is a major public health problem worldwide, with an estimated 14.1 million new cancer cases and 8.2 million deaths in 2012 [1]. Carcinogenesis is a complex process, influenced by various genetic and environmental factors, such as smoking, poor diet, physical inactivity, reproductive changes and the growth and aging of the population [1, 2]. Telomeres, composed of the TTAGGG repeat sequence, are special chromatin structures located at each end of a chromosome. Telomeres maintain chromosomal integrity by protecting chromosome ends from DNA damage and end-to-end fusions [3]. Abnormally short telomeres may cause chromosomal instability, and consequentially contribute to cancer development. Telomerase (also known as terminal transferase), a reverse transcriptase enzyme, extends the 3′ end of chromosomal DNA by catalyzing the telomere synthesis reaction. Defects in telomerase activity have been observed in many human tumor cells, and telomere length was inversely associated with cancer incidence and mortality [4]. Telomerase reverse transcriptase (TERT), the telomerase catalytic subunit, maintains telomere stability [5]. In a previous genome-wide association study (GWAS), Shete, et al. discovered that certain TERT gene variants increase glioma susceptibility [6]. Since then, TERT variants have been associated with various cancers, including breast, lung, colorectal, ovarian, prostate, and gastric cancers [7, 8].

The TERT gene is located in 5p15.33. The rs2736100 T > G polymorphism in the second intron of the TERT gene has been associated with shortened telomere length in gastric cancer [9]. The association of this SNP with cancer susceptibility has been extensively explored, although the findings are as yet inconclusive. Several meta-analyses published in 2014 associated the TERT rs2736100 polymorphism with increased glioma and lung cancer susceptibility [10-14]. In 2012, Zou, et al. observed an association between this polymorphism and overall cancer risk [15], although their meta-analysis involved only 11 articles. However, between 2015 and 2016, more than 27 studies were published with large sample sizes [9, 16-37]. Thus, we performed an updated meta-analysis to more precisely assess the TERT rs2736100 polymorphism-cancer association, including 72 studies derived from 61 articles with 269,720 total subjects [6, 9, 16-74].

RESULTS

Study characteristics

We initially identified 432 records from the PubMed and EMBASE databases (Figure 1). After screening titles and abstracts, 268 articles were excluded and the full texts of the remaining 164 articles were further assessed. Articles were excluded for the following reasons: irrelevant association (87 articles), meta-analysis (7), and lacking sufficient raw data for further evaluation (12). Three additional articles were identified by manually screening the references of relevant articles. Finally, 72 studies extracted from 61 articles met our study inclusion criteria and were included in the current meta-analysis [6, 9, 16-74].

Flowchart of articles included in our meta-analysis.

Figure 1: Flowchart of articles included in our meta-analysis.

In most of the included studies, the TERT rs2736100 polymorphism genotypic distribution followed Hardy-Weinberg equilibrium (HWE) in controls, except for seven studies [6, 28, 43, 51, 63, 66, 72]. Since the genotype distributions of other polymorphisms were in compliance with HWE in these seven studies, we included these studies in the meta-analysis. In total, 72 studies with 108,248 cases and 161,472 controls were included in our pooled analysis. Studies were conducted on various cancer types, including lung (28 studies), glioma (5), colorectal (4), bladder (4), myeloproliferative neoplasms (MPN) (4), gastric (3), acute myeloid leukemia (AML) (2), breast (2), melanoma (2), and thyroid (2). The remaining 16 studies focused on different types of cancer, with one study for each type of cancer, and were grouped together as “other cancer” in our analyses. There were 37 studies conducted in Asians and 35 in Caucasians. Twenty-three studies included fewer than 500 controls, and 49 had 500 or more controls. Sixteen studies were categorized as low quality and 56 were high quality. The main characteristics of all the studies are summarized in Table 1.

Table 1: The main characteristics of all the studies included in the meta-analysis

Surname

Year

Country

Ethnicity

Cancer type

Cases

Controls

HWE

Score

All

TT

TG

GG

All

TT

TG

GG

Zhou

2016

China

Asian

ESCC

588

165

275

148

600

215

287

108

0.472

11

Zhang

2016

China

Asian

NC

855

265

428

162

1036

365

516

155

0.211

13

Yuan

2016

China

Asian

UTUC

212

83

81

48

289

86

144

59

0.928

10

Xing

2016

China

Asian

Lung cancer

418

216

164

38

410

268

124

18

0.452

10

Wang

2016

China

Asian

Lung cancer

500

131

257

112

500

178

242

80

0.881

11

Trifa

2016

Romania

Caucasian

MPN

529

76

255

198

433

124

213

96

0.802

13

Krahling 1

2016

Hungary

Caucasian

PMN

584

77

282

225

400

111

188

101

0.235

8

Krahling 2

2016

Hungary

Caucasian

CML

86

25

43

18

400

111

188

101

0.235

8

Krahling 3

2016

Hungary

Caucasian

AML

308

71

153

84

400

111

188

101

0.235

7

Gong

2016

China

Asian

Thyroid cancer

452

142

214

96

452

156

222

74

0.738

11

Ge

2016

China

Asian

Thyroid cancer

2300

644

1093

563

2300

875

1056

369

0.093

12

Dahlstrom 1

2016

Sweden

Caucasian

MPN

126

15

64

47

756

167

377

212

0.980

9

Dahlstrom 2

2016

China

Asian

MPN

101

17

52

32

101

33

50

18

0.722

8

Bayram

2016

Turkey

Caucasian

Gastric cancer

104

16

44

44

209

61

82

66

0.002

9

Li

2016

China

Asian

Lung cancer

391

109

201

81

337

117

159

61

0.587

9

Shiraishi

2016

Japan

Asian

Lung cancer

6830

2057

3386

1387

15155

5723

7133

2299

0.323

13

Wei

2015

China

Asian

Lung cancer

702

190

353

159

2520

814

1269

437

0.130

12

Shadrina 1

2015

Russia

Caucasian

Prostate cancer

360

102

183

75

358

105

165

88

0.150

11

Shadrina 2

2015

Russia

Caucasian

Breast cancer

642

192

310

140

523

132

280

111

0.097

12

Mosrati

2015

Sweden

Caucasian

AML

226

48

113

65

788

201

406

181

0.382

10

Liu

2015

China

Asian

Lung cancer

288

72

139

77

317

92

173

52

0.052

9

Du

2015

China

Asian

Gastric cancer

1105

360

557

188

994

346

464

184

0.197

11

de Martino

2015

Austria

Caucasian

RCC

241

61

120

60

375

97

181

97

0.502

10

Choi

2015

South Korea

Asian

Gastric cancer

243

34

107

102

246

38

122

86

0.625

8

Campa

2015

Germany

Caucasian

Pancreatic cancer

1724

445

861

418

3512

817

1763

932

0.764

13

Campa

2015

Germany

Caucasian

Multiple myeloma

2052

535

958

559

2633

634

1285

714

0.237

13

Adel Fahmideh

2015

Sweden

Caucasian

Brain tumor

240

61

103

76

478

109

256

113

0.120

12

Yin

2014

China

Asian

Lung cancer

524

139

273

112

524

186

255

83

0.777

11

Wang

2014

China

Asian

Lung cancer

1552

455

764

333

1605

549

780

276

0.971

12

Liorca-Cardenosa

2014

Spain

Caucasian

Melanoma

629

146

297

186

371

94

177

100

0.380

9

Zhao

2013

China

Asian

Lung cancer

1759

596

1163a

1163a

1804

674

1130a

1130a

/

9

Sheng

2013

China

Asian

ALL

569

178

270

121

656

233

323

100

0.490

13

Pellatt

2013

USA

Caucasian

Breast cancer

3698

1450

1934

314

3534

1179

1674

681

0.047

11

Pellatt 1

2013

USA

Caucasian

Colon cancer

1555

410

798

347

1956

493

956

507

0.321

12

Pellatt 2

2013

USA

Caucasian

Rectal cancer

754

214

356

184

959

270

465

224

0.386

12

Myneni

2013

China

Asian

Lung cancer

352

122

141

89

447

157

212

78

0.659

8

Ma

2013

China

Asian

Bladder Cancer

177

55

87

35

961

340

455

166

0.516

10

Lan

2013

China

Asian

Lung cancer

193

43

109

41

197

70

103

24

0.137

9

Wang

2012

China

Asian

Cervical Cancer

1010

322

462

226

1006

352

480

174

0.637

11

Rajaraman b

2012

USA

Caucasian

Glioma

1854

/

/

/

4949

/

/

/

/

12

Kinnersley

2012

UK

Caucasian

Colorectal cancer

16039

4191

8105

3743

16430

4090

8082

4258

0.039

12

Ito

2012

Japan

Asian

Lung cancer

716

248

340

128

716

279

329

108

0.496

12

Hofer

2012

Austria

Caucasian

Colorectal cancer

137

38

68

31

1705

458

859

388

0.700

11

Chen

2012

China

Asian

Lung cancer

196

45

101

50

229

69

112

48

0.838

10

Shiraishi

2012

Japan

Asian

Lung cancer

4648

1386

2265

997

12364

4650

5856

1858

0.838

13

Bae

2012

Korea

Asian

Lung cancer

1094

402

501

191

1100

422

522

156

0.790

10

Pande b

2011

USA

Caucasian

Lung cancer

1681

/

/

/

1235

/

/

/

/

10

Nan 1

2011

USA

Caucasian

Melanoma

210

55

91

64

831

215

399

217

0.252

11

Nan 2

2011

USA

Caucasian

SCC

277

57

125

95

831

215

399

217

0.252

11

Nan 3

2011

USA

Caucasian

BCC

274

68

116

90

831

215

399

217

0.252

11

Kohno

2011

Japan

Asian

Lung cancer

377

142

175

53

325

116

165

39

0.090

9

Hu

2011

China

Asian

Lung cancer

8559

2393

4294

1872

9378

3231

4533

1614

0.724

13

Ding

2011

China

Asian

HC

1269

428

633

208

1322

449

651

222

0.591

12

Chen

2011

China

Asian

Glioma

953

244

515

194

1036

334

542

160

0.014

10

Jaworowsk 1

2011

Poland

Caucasian

Lung cancer

855

247

403

205

844

263

425

156

0.494

11

Jaworowsk 2

2011

Poland

Caucasian

Bladder Cancer

431

134

216

81

439

134

226

79

0.335

10

Jaworowsk 3

2011

Poland

Caucasian

Laryngeal cancer

413

124

211

78

406

130

199

77

0.956

10

Gago-Dominguez 1

2011

USA

Caucasian

Bladder Cancer

471

86

239

146

547

127

262

158

0.361

11

Gago-Dominguez 2

2011

USA

Asian

Bladder Cancer

499

141

260

98

525

174

274

77

0.064

10

Wang

2010

UK

Caucasian

Lung cancer

239

42

115

82

553

136

259

158

0.146

8

Turnbull

2010

UK

Caucasian

TGCT

1588

520

767

301

7683

1904

3718

2061

0.005

10

Miki

2010

Japan

Asian

Lung cancer

2086

622

1048

416

1103

4093

5246

1695

0.835

13

Kohno

2010

Japan

Asian

Lung cancer

1656

488

796

372

968

373

460

135

0.719

13

Hsiung

2010

China

Asian

Lung cancer

2308

599

1187

522

2321

852

1132

337

0.211

12

Yoon

2010

Korea

Asian

Lung cancer

1425

467

696

262

3011

1187

1405

419

0.921

11

Truong 1

2010

France

Caucasian

Lung cancer

9126

1878

4526

2722

11812

2853

5817

3142

0.116

13

Truong 2

2010

France

Asian

Lung cancer

1686

538

836

312

2101

775

1014

312

0.506

12

Schoemaker

2010

UK

Caucasian

Glioma

216

30

114

72

241

54

127

60

0.397

9

Shete

2009

USA

Caucasian

Glioma

4344

781

2213

1350

6457

1623

3122

1712

0.008

11

Landi b

2009

USA

Caucasian

Lung cancer

5739

/

/

/

5848

/

/

/

/

11

Jin

2009

China

Asian

Lung cancer

1212

353

627

232

1339

450

658

231

0.719

13

Wrensch

2009

USA

Caucasian

Glioma

691

95

354

242

3981

1021

1904

1056

0.006

12

Abbreviations: ESCC: esophageal squamous cell carcinoma; NC: nasopharyngeal carcinoma; UTUC: upper tract urothelial carcinomas; MPN: myeloproliferative neoplasms; CML: chronic myeloid leukemia; AML: acute myeloid leukemia; RCC: renal cell carcinoma; ALL: acute lymphoblastic leukemia; SCC: squamous cell carcinoma; BCC: basal cell carcinoma; HC: hepatocellular carcinoma; TGCT: testicular germ cell tumor; HWE: Hardy-Weinberg equilibrium

a: Number of cases and controls for TG and GG genotypers. b: The allele frequence in the three studies was provided to estimate the association under allele contrast model (G vs. T).

Meta-analysis results

Heterogeneity among studies was observed for all five genetic models. Consequently, the random effect model was applied to calculate odds ratios (ORs). Risk estimates indicated that the TERT rs2736100 polymorphism was associated with overall cancer risk via all five genetic models [homozygous model (GG vs. TT): OR=1.39, 95% confidence interval (CI)=1.26–1.54, P<0.001; heterozygous model (TG vs. TT): OR=1.16, 95% CI=1.11–1.23, P<0.001; dominant model (TG + GG vs. TT): OR=1.23, 95% CI=1.15–1.31, P<0.001; recessive model (GG vs. TG + TT): OR=1.25, 95% CI=1.16–1.35, P<0.001; and allele contrast model (G vs. T): OR=1.17, 95% CI=1.12–1.23, P<0.001 (Figure 2, Table 2)]. The stratified analysis by cancer type associated the TERT rs2736100 polymorphism with lung cancer risk (homozygous model: OR=1.60, 95% CI=1.49–1.71, P<0.001; heterozygous model: OR=1.25, 95% CI=1.20–1.31, P=0.008; dominant model: OR=1.33, 95% CI 1.26–1.39, P<0.001; recessive model: OR=1.40, 95% CI=1.32–1.48, P<0.001; and allele contrast model: OR=1.24, 95% CI=1.17–1.31, P<0.001). This polymorphism was also associated with increased risk for thyroid cancer, bladder cancer, glioma, MPN and AML. Inversely, the TERT rs2736100 polymorphism was associated with decreased colorectal cancer risk (homozygous model: OR=0.86, 95% CI=0.82–0.91, P=0.512; dominant model: OR=0.94, 95% CI=0.90–0.98, P=0.970; recessive model: OR=0.88, 95% CI=0.82–0.96, P=0.279; and allele contrast model: OR=0.93, 95% CI=0.90–0.96, P=0.548). Stratified analysis was also performed by patient ethnicity, sample size of controls, and quality score. Elevated cancer risk was found among Asians in all five genetic models and among Caucasians under all five genetic models except for the recessive model. Our results also associated the TERT rs2736100 polymorphism with elevated overall cancer risk in all subgroups divided by sample size of controls and quality score in all the five genetic models.

Forest plot of the association between the TERT rs2736100 polymorphism and overall cancer susceptibility in the allele contrast model.

Figure 2: Forest plot of the association between the TERT rs2736100 polymorphism and overall cancer susceptibility in the allele contrast model.

Table 2: Meta-analysis of TERT rs2736100 T>G polymorphism on cancer risk

Variables

Homozygous

Heterozygous

Recessive

Dominant

Allele

GG vs. TT

TG vs. TT

GG vs. (TG + TT)

(TG +GG) vs. TT

G vs. T

OR (95% CI)

Phet

I2 (%)

OR (95% CI)

Phet

I2 (%)

OR (95% CI)

Phet

I2 (%)

OR (95% CI)

Phet

I2 (%)

OR (95% CI)

Phet

I2 (%)

All

1.39 (1.26-1.54)

<0.001

93.3

1.16 (1.11-1.23)

<0.001

80.0

1.25 (1.16-1.35)

<0.001

91.1

1.23 (1.15-1.31)

<0.001

88.9

1.17 (1.12-1.23)

<0.001

93.4

Cancer type

 Lung

1.60 (1.49-1.71)

<0.001

65.7

1.25 (1.20-1.31)

0.008

45.5

1.40 (1.32-1.48)

<0.001

61.2

1.33 (1.26-1.39)

<0.001

58.6

1.24 (1.17-1.31)

<0.001

89.4

 MPN

3.17 (2.51-4.00)

0.854

0.0

2.03 (1.64-2.51)

0.972

0.0

1.89 (1.59-2.24)

0.616

0.0

2.40 (1.97-2.94)

0.957

0.0

1.74 (1.56-1.95)

0.679

0.0

 AML

1.40 (1.04-1.88)

0.631

0.0

1.22 (0.94-1.59)

0.744

0.0

1.23 (0.97-1.56)

0.411

0.0

1.28 (1.00-1.64)

0.970

0.0

1.18 (1.02-1.37)

0.658

0.0

 Thyroid

1.79 (1.25-2.56)

0.076

68.3

1.26 (0.96-1.65)

0.085

66.2

1.62 (1.37-1.92)

0.266

19.3

1.38 (1.02-1.88)

0.041

76.0

1.33 (1.08-1.64)

0.040

76.4

 Gastric

1.39 (0.82-2.33)

0.028

72.1

1.22 (0.90-1.66)

0.204

37.2

1.19 (0.83-1.70)

0.044

68.1

1.31 (0.90-1.90)

0.085

59.4

1.22 (0.94-1.58)

0.023

73.5

 Breast

0.56 (0.25-1.28)

<0.001

95.0

0.88 (0.73-1.07)

0.158

49.8

0.63 (0.24-1.64)

<0.001

97.3

0.78 (0.71-0.85)

0.892

0.0

0.80 (0.61-1.04)

0.003

88.8

 Melanoma

1.18 (0.90-1.54)

0.890

0.0

1.00 (0.78-1.27)

0.444

0.0

1.18 (0.95-1.47)

0.700

0.0

1.06 (0.85-1.33)

0.570

0.0

1.09 (0.95-1.26)

0.922

0.0

 Colorectal

0.86 (0.82-0.91)

0.512

0.0

0.98 (0.93-1.03)

0.989

0.0

0.88 (0.82-0.96)

0.279

21.9

0.94 (0.90-0.98)

0.970

0.0

0.93 (0.90-0.96)

0.548

0.0

 Bladder

1.31 (1.08-1.59)

0.481

0.0

1.15 (0.98-1.34)

0.498

0.0

1.18 (1.00-1.39)

0.598

0.0

1.19 (1.02-1.38)

0.436

0.0

1.13 (1.03-1.25)

0.507

0.0

 Glioma

1.89 (1.52-2.35)

0.028

67.0

1.55 (1.30-1.84)

0.055

60.0

1.35 (1.21-1.49)

0.241

28.5

1.65 (1.37-1.99)

0.020

69.4

1.33 (1.25-1.42)

0.089

50.4

 Others

1.09 (0.89-1.32)

<0.001

86.7

0.97 (0.88-1.07)

0.002

58.4

1.11 (0.95-1.29)

<0.001

84.3

1.01 (0.89-1.13)

<0.001

78.2

1.04 (0.94-1.15)

<0.001

87.0

Ethnicity

 Asian

1.56 (1.46-1.67)

<0.001

65.0

1.22 (1.17-1.28)

0.001

49.5

1.39 (1.32-1.46)

<0.001

50.4

1.30 (1.28-1.36)

<0.001

62.1

1.25 (1.20-1.29)

<0.001

67.7

 Caucasian

1.22 (1.04-1.44)

<0.001

94.4

1.12 (1.02-1.22)

<0.001

83.6

1.11 (0.99-1.25)

<0.001

92.5

1.16 (1.04-1.29)

<0.001

90.7

1.11 (1.03-1.19)

<0.001

94.2

Sample Size

 ≥ 500

1.34 (1.19-1.51)

<0.001

95.1

1.16 (1.09-1.23)

<0.001

83.7

1.22 (1.11-1.33)

<0.001

93.6

1.21 (1.13-1.30)

<0.001

91.5

1.15 (1.09-1.22)

<0.001

95.1

 <500

1.52 (1.26-1.82)

<0.001

72.5

1.19 (1.04-1.37)

<0.001

66.2

1.34 (1.19-1.51)

0.001

55.1

1.29 (1.11-1.49)

<0.001

73.3

1.23 (1.12-1.35)

<0.001

74.1

Score

 High

1.33 (1.18-1.48)

<0.001

94.5

1.15 (1.09-1.21)

<0.001

82.7

1.22 (1.12-1.33)

<0.001

92.8

1.20 (1.12-1.28)

<0.001

90.8

1.15 (1.09-1.21)

<0.001

94.5

 Low

1.72 (1.40-2.10)

0.001

60.5

1.30 (1.10-1.54)

0.003

57.0

1.41 (1.26-1.59)

0.154

27.4

1.40 (1.20-1.63)

<0.001

65.7

1.30 (1.18-1.43)

<0.001

60.5

Abbreviations: MPN, Myeloproliferative neoplasms; AML, Acute myeloid leukemia

Heterogeneity and sensitivity analyses

Heterogeneity was detected amongst studies with respect to the association between the TERT rs2736100 polymorphism and overall cancer risk (homozygous model: P<0.001; heterozygous model: P<0.001; dominant model: P<0.001; recessive model: P<0.001; and allele contrast model: P<0.001). Therefore, we used the random effects model to generate pooled ORs and 95% CIs. Sensitivity analyses indicated that no single study could change the between-study heterogeneity and the results of meta-analysis.

Publication bias

The Begg’s funnel plot and Egger’s linear regression analysis did not reveal any evidence of publication bias in the meta-analysis (homozygous model: P=0.183; heterozygous model: P=0.805; dominant model: P=0.406; recessive model: P=0.085; and allele model: P=0.122; Figure 3).

Funnel plot analysis to evaluate publication bias.

Figure 3: Funnel plot analysis to evaluate publication bias.

False positive report probability (FPRP) analyses

We calculated FPRP values for associations between the TERT rs2736100 T>G polymorphism and overall cancer risk using the five genetic models. FPRP values were all <0.20, suggesting that these associations were noteworthy (Table 3).

Table 3: False-positive report probability values for associations between the TERT rs2736100 T>G polymorphism and overall cancer risk

Genetic models

OR (95% CI)

P

Power

Prior Probability

0.25

0.1

0.01

0.001

0.0001

0.00001

Homozygous (GG vs. TT)

1.39 (1.26-1.54)

<0.001

0.555

0.000

0.000

0.000

0.000

0.000

0.000

Heterozygous (TG vs. TT)

1.16 (1.11-1.23)

<0.001

0.872

0.000

0.000

0.000

0.001

0.008

0.073

Recessive (GG vs. TG + TT)

1.25 (1.16-1.35)

<0.001

0.841

0.000

0.000

0.000

0.000

0.000

0.002

Dominant (TG +GG vs. TT)

1.23 (1.15-1.31)

<0.001

0.957

0.000

0.000

0.000

0.000

0.000

0.000

Allele (G vs. T)

1.17 (1.12-1.23)

<0.001

0.839

0.000

0.000

0.000

0.000

0.000

0.000

DISCUSSION

Telomeres are special structures at the ends of eukaryotic chromosomes, and are responsible for protecting chromosomes from degradation, end-to-end fusion, and rearrangement [10]. Telomerase maintains proper telomere length by adding repetitive telomeric sequences to the 3’ ends of telomeres. Abnormal telomerase activity is implicated in the initiation and development of cancer and other age-associated diseases [75]. The TERT subunit of telomerase consists of three highly conserved domains: the RNA-binding domain (TRBD), the reverse transcriptase domain, and a carboxy-putative extension (CTE) proposed to constitute the putative thumb domain [75]. TERT is overexpressed in many human cancers [76]. The TERT rs2736100 polymorphism, localized in the second intron of the TERT gene, has been wildly studied with respect to cancer risk [7, 8]. However, the functional significance of the TERT rs2736100 polymorphism was not clear. Preliminary studies in gastric cancer suggested that this SNP is associated with decreased telomere length [9].

The present meta-analysis, comprising 108,248 cases and 161,472 controls, found that the TERT rs2736100 polymorphism increased overall cancer risk by 16–39%, suggesting that this SNP may contribute to carcinogenesis. A previous meta-analysis conducted by Zou, et al. in 2012 [15] also concluded that this polymorphism was associated with increased cancer risk. However, this analysis included only 11 case-control articles with 23,032 cases and 38,274 controls, which studied only lung cancer, glioma, and bladder cancer. Our stratified analysis by cancer type showed that the TERT rs2736100 polymorphism correlated with increased risk of lung cancer and glioma. Such associations were also observed in lung cancer- and glioma-specific meta-analyses published in 2014 [10-15, 77]. Between 2015 and 2016, at least 27 studies (6 studies on lung cancer) were published investigating the association between the TERT rs2736100 polymorphism and overall cancer susceptibility. To the best of our knowledge, ours is the largest meta-analysis of this association, with the strongest statistical power. Apart from lung cancer, glioma, and bladder cancer, our meta-analysis also investigated the association between the TERT rs2736100 polymorphism and risk of colorectal cancer (4 studies), MPN (4), gastric cancer (3), AML (2), breast cancer (2), melanoma (2), and thyroid cancer (2) as well as “other cancers” (16). We observed that this polymorphism was associated with decreased colorectal cancer risk. Since only four colorectal cancer studies were included in our meta-analysis, such an association might be a false positive, and validation will require further study.

The current meta-analysis had several limitations. First, there were substantial heterogeneities in the pooled study investigating the association between the TERT rs2736100 polymorphism and overall cancer risk. We reduced the degree of heterogeneity through stratified analyses by cancer type, patient ethnicity, sample size, and study quality score. Some cross-study heterogeneity might be attributed to differences among ethnic groups [78]. However, other sources of heterogeneity were not identified, such as control sources and genotyping methods. Second, the studies in this meta-analysis focused on Asian and Caucasian populations only, so we may not have had sufficient statistical power to evaluate associations based on ethnicity. Third, our results were based on unadjusted ORs due to the unavailability of confounding factor information for cases and controls (e.g., age, sex, smoking status, drinking status, and environmental exposure). Finally, lacking the original data from eligible studies limited our ability to explore gene-environment interactions.

In conclusion, our meta-analysis indicated that the TERT rs2736100 polymorphism was associated with increased overall cancer risk, especially lung cancer risk. Larger studies involving patients of different ethnicities are needed to confirm our findings.

MATERIALS AND METHODS

Identification of eligible studies

A comprehensive literature search of the PubMed and EMBASE databases was performed up to November 1, 2016. To find all eligible case-control studies that assessed the association between the TERT rs2736100 polymorphism and cancer risk, we used the following keywords: “TERT or telomerase reverse transcriptase”, “polymorphism or variant”, and “cancer or tumor or neoplasm or carcinoma”. We also evaluated additional studies by manually screening the references of both primary articles and reviews.

Inclusion and exclusion criteria

Eligible studies included in our analysis met the following criteria: (i) the TERT rs2736100 polymorphism-cancer risk association was assessed; (ii) case-control studies or cohort studies; (iii) sufficient data to calculate an OR with 95% CI; (iv) studies in English. Exclusion criteria were as follows: (i) case only studies; (ii) overlapping publications; (iii) abstract, case report, editorial comment, and review. Studies that deviated from HWE in controls were excluded, unless further evidence showed that another polymorphism was in HWE.

Data extraction

Two investigators independently extracted available data from each eligible study. The following information was collected: first author’s surname, year of publication, country of origin, patient ethnicity, cancer type, numbers of cases and controls, genotype counts of cases and controls, results of the HWE test, and quality scores (low quality studies with score ≤9, high quality studies with score >9) [79]. Any disagreements were solved by discussion until a consensus was reached between the two investigators. If no consensus was reached, another investigator joined the discussion, and a final decision was made by a majority.

FPRP analysis

FPRP values were applied to assess the statistical power of our significant findings [80, 81]. An FPRP value of 0.20 was set as the criterion for noteworthiness. A prior probability of 0.1 was assigned to detect an OR of 0.67/1.50 (protective/risk effects) for an association with genotypes under investigation.

Statistical analysis

HWE in control subjects was assessed by chi-squared test. The strength of association between the TERT rs2736100 polymorphism and cancer risk was estimated by calculating crude ORs and their 95% CIs using all five genetic models: homozygous (GG vs. TT), heterozygous (TG vs. TT), dominant (GG vs. TG + TT), and recessive (TG + GG vs. TT), as well as the allele contrast model (G vs. T). Q-test was used to quantify heterogeneity among all eligible studies, and P>0.10 suggested a lack of heterogeneity among studies. Generally, the fixed effects model (Mantel–Haenszel method) or the random effects model (DerSimonian–Laird method) was employed in the absence (P≥0.10) or presence (P<0.10) of heterogeneity, respectively [82-84]. Heterogeneity was also estimated using the I2 test [85]. Subgroup analyses were conducted by patient ethnicity, cancer type, and study sample size. The Begg’s funnel plot and the Egger’s linear regression test were used to evaluate publication bias [86]. All statistical analyses were performed using STATA version 12.0 software (STATA Corporation, College Station, TX). All statistical analyses were two-sided. P<0.05 was considered statistically significant.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

REFERENCES

1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015; 65: 87-108. doi: 10.3322/caac.21262.

2. Song M, Lee KM, Kang D. Breast cancer prevention based on gene-environment interaction. Mol Carcinog. 2011; 50: 280-90. doi: 10.1002/mc.20639.

3. Blasco MA. Telomeres and human disease: ageing, cancer and beyond. Nat Rev Genet. 2005; 6: 611-22. doi: 10.1038/nrg1656.

4. Willeit P, Willeit J, Mayr A, Weger S, Oberhollenzer F, Brandstatter A, Kronenberg F, Kiechl S. Telomere length and risk of incident cancer and cancer mortality. JAMA. 2010; 304: 69-75. doi: 10.1001/jama.2010.897.

5. Blackburn EH. Switching and signaling at the telomere. Cell. 2001; 106: 661-73.

6. Shete S, Hosking FJ, Robertson LB, Dobbins SE, Sanson M, Malmer B, Simon M, Marie Y, Boisselier B, Delattre JY, Hoang-Xuan K, El Hallani S, Idbaih A, et al. Genome-wide association study identifies five susceptibility loci for glioma. Nat Genet. 2009; 41: 899-904. doi: 10.1038/ng.407.

7. Zhang C, Doherty JA, Burgess S, Hung RJ, Lindstrom S, Kraft P, Gong J, Amos CI, Sellers TA, Monteiro AN, Chenevix-Trench G, Bickeboller H, Risch A, et al. Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study. Hum Mol Genet. 2015; 24: 5356-66. doi: 10.1093/hmg/ddv252.

8. Liu T, Yuan X, Xu D. Cancer-Specific Telomerase Reverse Transcriptase (TERT) Promoter Mutations: Biological and Clinical Implications. Genes (Basel). 2016; 7. doi: 10.3390/genes7070038.

9. Choi BJ, Yoon JH, Kim O, Choi WS, Nam SW, Lee JY, Park WS. Influence of the hTERT rs2736100 polymorphism on telomere length in gastric cancer. World J Gastroenterol. 2015; 21: 9328-36. doi: 10.3748/wjg.v21.i31.9328.

10. Zhou P, Wei L, Xia X, Shao N, Qian X, Yang Y. Association between telomerase reverse transcriptase rs2736100 polymorphism and risk of glioma. J Surg Res. 2014; 191: 156-60. doi: 10.1016/j.jss.2014.03.043.

11. Yuan Y, Lu C, Xue L, Ge D. Association between TERT rs2736100 polymorphism and lung cancer susceptibility: evidence from 22 case-control studies. Tumour Biol. 2014; 35: 4435-42. doi: 10.1007/s13277-013-1583-4.

12. Yang J, Jiao S. Increased lung cancer risk associated with the TERT rs2736100 polymorphism: an updated meta-analysis. Tumour Biol. 2014; 35: 5763-9. doi: 10.1007/s13277-014-1765-8.

13. Wu H, Zhu R. Quantitative assessment of common genetic variants on chromosome 5p15 and lung cancer risk. Tumour Biol. 2014; 35: 6055-63. doi: 10.1007/s13277-014-1802-7.

14. Nie W, Zang Y, Chen J, Xiu Q. TERT rs2736100 polymorphism contributes to lung cancer risk: a meta-analysis including 49,869 cases and 73,464 controls. Tumour Biol. 2014; 35: 5569-74. doi: 10.1007/s13277-014-1734-2.

15. Zou P, Gu A, Ji G, Zhao L, Zhao P, Lu A. The TERT rs2736100 polymorphism and cancer risk: a meta-analysis based on 25 case-control studies. BMC Cancer. 2012; 12: 7. doi: 10.1186/1471-2407-12-7.

16. Zhou L, Fu G, Wei J, Shi J, Pan W, Ren Y, Xiong X, Xia J, Shen Y, Li H, Yang M. The identification of two regulatory ESCC susceptibility genetic variants in the TERT-CLPTM1L loci. Oncotarget. 2016; 7: 5495-506. doi: 10.18632/oncotarget.6747.

17. Zhang Y, Zhang X, Zhang H, Zhai Y, Wang Z, Li P, Yu L, Xia X, Zhang Y, Zeng Y, He F, Zhou G. Common variations in TERT-CLPTM1L locus are reproducibly associated with the risk of nasopharyngeal carcinoma in Chinese populations. Oncotarget. 2016; 7: 759-70. doi: 10.18632/oncotarget.6397.

18. Yuan X, Meng Y, Li P, Ge N, Kong F, Yang L, Bjorkholm M, Zhao S, Xu D. The association between the TERT rs2736100 AC genotype and reduced risk of upper tract urothelial carcinomas in a Han Chinese population. Oncotarget. 2016; 7: 31972–31979. doi: 10.18632/oncotarget.7777.

19. Xing YL, Liu F, Li JF, Lin JC, Zhu GD, Li M, Zhang CR, Niu YY. Case-Control Study on Impact of the Telomerase Reverse Transcriptase Gene Polymorphism and Additional Single Nucleotide Polymorphism (SNP)- SNP Interaction on Non-Small Cell Lung Cancers Risk in Chinese Han Population. J Clin Lab Anal. 2016. doi: 10.1002/jcla.21982.

20. Wang X, Ma K, Chi L, Cui J, Jin L, Hu JF, Li W. Combining Telomerase Reverse Transcriptase Genetic Variant rs2736100 with Epidemiologic Factors in the Prediction of Lung Cancer Susceptibility. J Cancer. 2016; 7: 846-53. doi: 10.7150/jca.13437.

21. Trifa AP, Banescu C, Tevet M, Bojan A, Dima D, Urian L, Torok-Vistai T, Popov VM, Zdrenghea M, Petrov L, Vasilache A, Murat M, Georgescu D, et al. TERT rs2736100 A>C SNP and JAK2 46/1 haplotype significantly contribute to the occurrence of JAK2 V617F and CALR mutated myeloproliferative neoplasms - a multicentric study on 529 patients. Br J Haematol. 2016; 174: 218-26. doi: 10.1111/bjh.14041.

22. Shiraishi K, Okada Y, Takahashi A, Kamatani Y, Momozawa Y, Ashikawa K, Kunitoh H, Matsumoto S, Takano A, Shimizu K, Goto A, Tsuta K, Watanabe S, et al. Association of variations in HLA class II and other loci with susceptibility to EGFR-mutated lung adenocarcinoma. Nat Commun. 2016; 7: 12451. doi: 10.1038/ncomms12451.

23. Li X, Xu X, Fang J, Wang L, Mu Y, Zhang P, Yao Z, Ma Z, Liu Z. Rs2853677 modulates Snail1 binding to the TERT enhancer and affects lung adenocarcinoma susceptibility. Oncotarget. 2016; 7: 37825–37838. doi: 10.18632/oncotarget.9339.

24. Krahling T, Balassa K, Kiss KP, Bors A, Batai A, Halm G, Egyed M, Fekete S, Remenyi P, Masszi T, Tordai A, Andrikovics H. Co-occurrence of Myeloproliferative Neoplasms and Solid Tumors Is Attributed to a Synergism Between Cytoreductive Therapy and the Common TERT Polymorphism rs2736100. Cancer Epidemiol Biomarkers Prev. 2016; 25: 98-104. doi: 10.1158/1055-9965.EPI-15-0805.

25. Gong L, Xu Y, Hu YQ, Ding QJ, Yi CH, Huang W, Zhou M. hTERT gene polymorphism correlates with the risk and the prognosis of thyroid cancer. J Back Musculoskelet Rehabil. 2016. doi: 10.3233/BMR-160631.

26. Ge M, Shi M, An C, Yang W, Nie X, Zhang J, Lv Z, Li J, Zhou L, Du Z, Yang M. Functional evaluation of TERT-CLPTM1L genetic variants associated with susceptibility of papillary thyroid carcinoma. Sci Rep. 2016; 6: 26037. doi: 10.1038/srep26037.

27. Dahlstrom J, Liu T, Yuan X, Saft L, Ghaderi M, Wei YB, Lavebratt C, Li P, Zheng C, Bjorkholm M, Xu D. TERT rs2736100 genotypes are associated with differential risk of myeloproliferative neoplasms in Swedish and Chinese male patient populations. Ann Hematol. 2016. doi: 10.1007/s00277-016-2787-7.

28. Bayram S, Ulger Y, Sumbul AT, Kaya BY, Genc A, Rencuzogullari E, Dadas E. Polymorphisms in human telomerase reverse transcriptase (hTERT) gene and susceptibility to gastric cancer in a Turkish population: Hospital-based case-control study. Gene. 2016; 585: 84-92. doi: 10.1016/j.gene.2016.03.030.

29. Wei R, Cao L, Pu H, Wang H, Zheng Y, Niu X, Weng X, Zhang H, Favus MJ, Zhang L, Jia W, Zeng Y, Amos CI, et al. TERT Polymorphism rs2736100-C Is Associated with EGFR Mutation-Positive Non-Small Cell Lung Cancer. Clin Cancer Res. 2015; 21: 5173-80. doi: 10.1158/1078-0432.CCR-15-0009.

30. Shadrina AS, Boyarskikh UA, Oskina NA, Sinkina TV, Lazarev AF, Petrova VD, Filipenko ML. TERT polymorphisms rs2853669 and rs7726159 influence on prostate cancer risk in Russian population. Tumour Biol. 2015; 36: 841-7. doi: 10.1007/s13277-014-2688-0.

31. Mosrati MA, Willander K, Falk IJ, Hermanson M, Hoglund M, Stockelberg D, Wei Y, Lotfi K, Soderkvist P. Association between TERT promoter polymorphisms and acute myeloid leukemia risk and prognosis. Oncotarget. 2015; 6: 25109-20. doi: 10.18632/oncotarget.4668.

32. Liu SG, Ma L, Cen QH, Huang JS, Zhang JX, Zhang JJ. Association of genetic polymorphisms in TERT-CLPTM1L with lung cancer in a Chinese population. Genet Mol Res. 2015; 14: 4469-76. doi: 10.4238/2015.May.4.4.

33. Du J, Zhu X, Xie C, Dai N, Gu Y, Zhu M, Wang C, Gao Y, Pan F, Ren C, Ji Y, Dai J, Ma H, et al. Telomere length, genetic variants and gastric cancer risk in a Chinese population. Carcinogenesis. 2015; 36: 963-70. doi: 10.1093/carcin/bgv075.

34. de Martino M, Taus C, Lucca I, Hofbauer SL, Haitel A, Shariat SF, Klatte T. Association of human telomerase reverse transcriptase gene polymorphisms, serum levels, and telomere length with renal cell carcinoma risk and pathology. Mol Carcinog. 2015. doi: 10.1002/mc.22388.

35. Campa D, Rizzato C, Stolzenberg-Solomon R, Pacetti P, Vodicka P, Cleary SP, Capurso G, Bueno-de-Mesquita HB, Werner J, Gazouli M, Butterbach K, Ivanauskas A, Giese N, et al. TERT gene harbors multiple variants associated with pancreatic cancer susceptibility. Int J Cancer. 2015; 137: 2175-83. doi: 10.1002/ijc.29590.

36. Campa D, Martino A, Varkonyi J, Lesueur F, Jamroziak K, Landi S, Jurczyszyn A, Marques H, Andersen V, Jurado M, Brenner H, Petrini M, Vogel U, et al. Risk of multiple myeloma is associated with polymorphisms within telomerase genes and telomere length. Int J Cancer. 2015; 136: E351-8. doi: 10.1002/ijc.29101.

37. Adel Fahmideh M, Lavebratt C, Schuz J, Roosli M, Tynes T, Grotzer MA, Johansen C, Kuehni CE, Lannering B, Prochazka M, Schmidt LS, Feychting M. CCDC26, CDKN2BAS, RTEL1 and TERT Polymorphisms in pediatric brain tumor susceptibility. Carcinogenesis. 2015; 36: 876-82. doi: 10.1093/carcin/bgv074.

38. Yin Z, Cui Z, Ren Y, Zhang H, Yan Y, Zhao Y, Ma R, Wang Q, He Q, Zhou B. Genetic polymorphisms of TERT and CLPTM1L, cooking oil fume exposure, and risk of lung cancer: a case-control study in a Chinese non-smoking female population. Med Oncol. 2014; 31: 114. doi: 10.1007/s12032-014-0114-5.

39. Wang F, Fu P, Pang Y, Liu C, Shao Z, Zhu J, Li J, Wang T, Zhang X, Liu J. TERT rs2736100T/G polymorphism upregulates interleukin 6 expression in non-small cell lung cancer especially in adenocarcinoma. Tumour Biol. 2014; 35: 4667-72. doi: 10.1007/s13277-014-1611-z.

40. Llorca-Cardenosa MJ, Pena-Chilet M, Mayor M, Gomez-Fernandez C, Casado B, Martin-Gonzalez M, Carretero G, Lluch A, Martinez-Cadenas C, Ibarrola-Villava M, Ribas G. Long telomere length and a TERT-CLPTM1 locus polymorphism association with melanoma risk. Eur J Cancer. 2014; 50: 3168-77. doi: 10.1016/j.ejca.2014.09.017.

41. Zhao Z, Li C, Yang L, Zhang X, Zhao X, Song X, Li X, Wang J, Qian J, Yang Y, Jin L, Chen H, Lu D. Significant association of 5p15.33 (TERT-CLPTM1L genes) with lung cancer in Chinese Han population. Exp Lung Res. 2013; 39: 91-8. doi: 10.3109/01902148.2012.762436.

42. Sheng X, Tong N, Tao G, Luo D, Wang M, Fang Y, Li J, Xu M, Zhang Z, Wu D. TERT polymorphisms modify the risk of acute lymphoblastic leukemia in Chinese children. Carcinogenesis. 2013; 34: 228-35. doi: 10.1093/carcin/bgs325.

43. Pellatt AJ, Wolff RK, Torres-Mejia G, John EM, Herrick JS, Lundgreen A, Baumgartner KB, Giuliano AR, Hines LM, Fejerman L, Cawthon R, Slattery ML. Telomere length, telomere-related genes, and breast cancer risk: the breast cancer health disparities study. Genes Chromosomes Cancer. 2013; 52: 595-609. doi: 10.1002/gcc.22056.

44. Pellatt AJ, Wolff RK, Herrick J, Lundgreen A, Slattery ML. TERT’s role in colorectal carcinogenesis. Mol Carcinog. 2013; 52: 507-13. doi: 10.1002/mc.21885.

45. Myneni AA, Chang SC, Niu R, Liu L, Ochs-Balcom HM, Li Y, Zhang C, Zhao B, Shi J, Han X, Li J, Su J, Cai L, et al. Genetic polymorphisms of TERT and CLPTM1L and risk of lung cancer--a case-control study in a Chinese population. Lung Cancer. 2013; 80: 131-7. doi: 10.1016/j.lungcan.2013.01.021.

46. Ma Z, Hu Q, Chen Z, Tao S, Macnamara L, Kim ST, Tian L, Xu K, Ding Q, Zheng SL, Sun J, Xia G, Xu J. Systematic evaluation of bladder cancer risk-associated single-nucleotide polymorphisms in a Chinese population. Mol Carcinog. 2013; 52: 916-21. doi: 10.1002/mc.21932.

47. Lan Q, Cawthon R, Gao Y, Hu W, Hosgood HD 3rd, Barone-Adesi F, Ji BT, Bassig B, Chow WH, Shu X, Cai Q, Xiang Y, Berndt S, et al. Longer telomere length in peripheral white blood cells is associated with risk of lung cancer and the rs2736100 (CLPTM1L-TERT) polymorphism in a prospective cohort study among women in China. PLoS One. 2013; 8: e59230. doi: 10.1371/journal.pone.0059230.

48. Wang S, Wu J, Hu L, Ding C, Kan Y, Shen Y, Chen X, Shen H, Guo X, Hu Z. Common genetic variants in TERT contribute to risk of cervical cancer in a Chinese population. Mol Carcinog. 2012; 51 Suppl 1: E118-22. doi: 10.1002/mc.21872.

49. Shiraishi K, Kunitoh H, Daigo Y, Takahashi A, Goto K, Sakamoto H, Ohnami S, Shimada Y, Ashikawa K, Saito A, Watanabe S, Tsuta K, Kamatani N, et al. A genome-wide association study identifies two new susceptibility loci for lung adenocarcinoma in the Japanese population. Nat Genet. 2012; 44: 900-3. doi: 10.1038/ng.2353.

50. Rajaraman P, Melin BS, Wang Z, McKean-Cowdin R, Michaud DS, Wang SS, Bondy M, Houlston R, Jenkins RB, Wrensch M, Yeager M, Ahlbom A, Albanes D, et al. Genome-wide association study of glioma and meta-analysis. Hum Genet. 2012; 131: 1877-88. doi: 10.1007/s00439-012-1212-0.

51. Kinnersley B, Migliorini G, Broderick P, Whiffin N, Dobbins SE, Casey G, Hopper J, Sieber O, Lipton L, Kerr DJ, Dunlop MG, Tomlinson IP, Houlston RS, et al. The TERT variant rs2736100 is associated with colorectal cancer risk. Br J Cancer. 2012; 107: 1001-8. doi: 10.1038/bjc.2012.329.

52. Ito H, McKay JD, Hosono S, Hida T, Yatabe Y, Mitsudomi T, Brennan P, Tanaka H, Matsuo K. Association between a genome-wide association study-identified locus and the risk of lung cancer in Japanese population. J Thorac Oncol. 2012; 7: 790-8. doi: 10.1097/JTO.0b013e3182475028.

53. Hofer P, Baierl A, Bernhart K, Leeb G, Mach K, Micksche M, Gsur A. Association of genetic variants of human telomerase with colorectal polyps and colorectal cancer risk. Mol Carcinog. 2012; 51 Suppl 1: E176-82. doi: 10.1002/mc.21911.

54. Chen XF, Cai S, Chen QG, Ni ZH, Tang JH, Xu DW, Wang XB. Multiple variants of TERT and CLPTM1L constitute risk factors for lung adenocarcinoma. Genet Mol Res. 2012; 11: 370-8. doi: 10.4238/2012.February.16.2.

55. Bae EY, Lee SY, Kang BK, Lee EJ, Choi YY, Kang HG, Choi JE, Jeon HS, Lee WK, Kam S, Shin KM, Jin G, Yoo SS, et al. Replication of results of genome-wide association studies on lung cancer susceptibility loci in a Korean population. Respirology. 2012; 17: 699-706. doi: 10.1111/j.1440-1843.2012.02165.x.

56. Pande M, Spitz MR, Wu X, Gorlov IP, Chen WV, Amos CI. Novel genetic variants in the chromosome 5p15.33 region associate with lung cancer risk. Carcinogenesis. 2011; 32: 1493-9. doi: 10.1093/carcin/bgr136.

57. Nan H, Qureshi AA, Prescott J, De Vivo I, Han J. Genetic variants in telomere-maintaining genes and skin cancer risk. Hum Genet. 2011; 129: 247-53. doi: 10.1007/s00439-010-0921-5.

58. Kohno T, Kunitoh H, Mimaki S, Shiraishi K, Kuchiba A, Yamamoto S, Yokota J. Contribution of the TP53, OGG1, CHRNA3, and HLA-DQA1 genes to the risk for lung squamous cell carcinoma. J Thorac Oncol. 2011; 6: 813-7. doi: 10.1097/JTO.0b013e3181ee80ef.

59. Jaworowska E, Trubicka J, Lener MR, Masojc B, Zlowocka-Perlowska E, McKay JD, Renard H, Oszutowska D, Wokolorczyk D, Lubinski J, Grodzki T, Serwatowski P, Nej-Wolosiak K, et al. Smoking related cancers and loci at chromosomes 15q25, 5p15, 6p22.1 and 6p21.33 in the Polish population. PLoS One. 2011; 6: e25057. doi: 10.1371/journal.pone.0025057.

60. Hu Z, Wu C, Shi Y, Guo H, Zhao X, Yin Z, Yang L, Dai J, Hu L, Tan W, Li Z, Deng Q, Wang J, et al. A genome-wide association study identifies two new lung cancer susceptibility loci at 13q12.12 and 22q12.2 in Han Chinese. Nat Genet. 2011; 43: 792-6. doi: 10.1038/ng.875.

61. Gago-Dominguez M, Jiang X, Conti DV, Castelao JE, Stern MC, Cortessis VK, Pike MC, Xiang YB, Gao YT, Yuan JM, Van Den Berg DJ. Genetic variations on chromosomes 5p15 and 15q25 and bladder cancer risk: findings from the Los Angeles-Shanghai bladder case-control study. Carcinogenesis. 2011; 32: 197-202. doi: 10.1093/carcin/bgq233.

62. Ding CY, Hu LM, Hu ZB, Shen HB. The relationship between gene polymorphism of telomerase reverse transcriptase and susceptibility to hepatocellular carcinoma. [Article in Chinese] Zhonghua Yu Fang Yi Xue Za Zhi. 2011; 45: 593-6.

63. Chen H, Chen Y, Zhao Y, Fan W, Zhou K, Liu Y, Zhou L, Mao Y, Wei Q, Xu J, Lu D. Association of sequence variants on chromosomes 20, 11, and 5 (20q13.33, 11q23.3, and 5p15.33) with glioma susceptibility in a Chinese population. Am J Epidemiol. 2011; 173: 915-22. doi: 10.1093/aje/kwq457.

64. Yoon KA, Park JH, Han J, Park S, Lee GK, Han JY, Zo JI, Kim J, Lee JE, Takahashi A, Kubo M, Nakamura Y, Lee JS. A genome-wide association study reveals susceptibility variants for non-small cell lung cancer in the Korean population. Hum Mol Genet. 2010; 19: 4948-54. doi: 10.1093/hmg/ddq421.

65. Wang Y, Broderick P, Matakidou A, Eisen T, Houlston RS. Role of 5p15.33 (TERT-CLPTM1L), 6p21.33 and 15q25.1 (CHRNA5-CHRNA3) variation and lung cancer risk in never-smokers. Carcinogenesis. 2010; 31: 234-8. doi: 10.1093/carcin/bgp287.

66. Turnbull C, Rapley EA, Seal S, Pernet D, Renwick A, Hughes D, Ricketts M, Linger R, Nsengimana J, Deloukas P, Huddart RA, Bishop DT, Easton DF, et al. Variants near DMRT1, TERT and ATF7IP are associated with testicular germ cell cancer. Nat Genet. 2010; 42: 604-7. doi: 10.1038/ng.607.

67. Truong T, Hung RJ, Amos CI, Wu X, Bickeboller H, Rosenberger A, Sauter W, Illig T, Wichmann HE, Risch A, Dienemann H, Kaaks R, Yang P, et al. Replication of lung cancer susceptibility loci at chromosomes 15q25, 5p15, and 6p21: a pooled analysis from the International Lung Cancer Consortium. J Natl Cancer Inst. 2010; 102: 959-71. doi: 10.1093/jnci/djq178.

68. Schoemaker MJ, Robertson L, Wigertz A, Jones ME, Hosking FJ, Feychting M, Lonn S, McKinney PA, Hepworth SJ, Muir KR, Auvinen A, Salminen T, Kiuru A, et al. Interaction between 5 genetic variants and allergy in glioma risk. Am J Epidemiol. 2010; 171: 1165-73. doi: 10.1093/aje/kwq075.

69. Miki D, Kubo M, Takahashi A, Yoon KA, Kim J, Lee GK, Zo JI, Lee JS, Hosono N, Morizono T, Tsunoda T, Kamatani N, Chayama K, et al. Variation in TP63 is associated with lung adenocarcinoma susceptibility in Japanese and Korean populations. Nat Genet. 2010; 42: 893-6. doi: 10.1038/ng.667.

70. Kohno T, Kunitoh H, Shimada Y, Shiraishi K, Ishii Y, Goto K, Ohe Y, Nishiwaki Y, Kuchiba A, Yamamoto S, Hirose H, Oka A, Yanagitani N, et al. Individuals susceptible to lung adenocarcinoma defined by combined HLA-DQA1 and TERT genotypes. Carcinogenesis. 2010; 31: 834-41. doi: 10.1093/carcin/bgq003.

71. Hsiung CA, Lan Q, Hong YC, Chen CJ, Hosgood HD, Chang IS, Chatterjee N, Brennan P, Wu C, Zheng W, Chang GC, Wu T, Park JY, et al. The 5p15.33 locus is associated with risk of lung adenocarcinoma in never-smoking females in Asia. PLoS Genet. 2010; 6. doi: 10.1371/journal.pgen.1001051.

72. Wrensch M, Jenkins RB, Chang JS, Yeh RF, Xiao Y, Decker PA, Ballman KV, Berger M, Buckner JC, Chang S, Giannini C, Halder C, Kollmeyer TM, et al. Variants in the CDKN2B and RTEL1 regions are associated with high-grade glioma susceptibility. Nat Genet. 2009; 41: 905-8. doi: 10.1038/ng.408.

73. Landi MT, Chatterjee N, Yu K, Goldin LR, Goldstein AM, Rotunno M, Mirabello L, Jacobs K, Wheeler W, Yeager M, Bergen AW, Li Q, Consonni D, et al. A genome-wide association study of lung cancer identifies a region of chromosome 5p15 associated with risk for adenocarcinoma. Am J Hum Genet. 2009; 85: 679-91. doi: 10.1016/j.ajhg.2009.09.012.

74. Jin G, Xu L, Shu Y, Tian T, Liang J, Xu Y, Wang F, Chen J, Dai J, Hu Z, Shen H. Common genetic variants on 5p15.33 contribute to risk of lung adenocarcinoma in a Chinese population. Carcinogenesis. 2009; 30: 987-90. doi: 10.1093/carcin/bgp090.

75. Gillis AJ, Schuller AP, Skordalakes E. Structure of the Tribolium castaneum telomerase catalytic subunit TERT. Nature. 2008; 455: 633-7. doi: 10.1038/nature07283.

76. Stewart SA, Weinberg RA. Telomeres: cancer to human aging. Annu Rev Cell Dev Biol. 2006; 22: 531-57. doi: 10.1146/annurev.cellbio.22.010305.104518.

77. Wang HM, Zhang XY, Jin B. TERT genetic polymorphism rs2736100 was associated with lung cancer: a meta-analysis based on 14,492 subjects. Genet Test Mol Biomarkers. 2013; 17: 937-41. doi: 10.1089/gtmb.2013.0322.

78. Xue WQ, He YQ, Zhu JH, Ma JQ, He J, Jia WH. Association of BRCA2 N372H polymorphism with cancer susceptibility: a comprehensive review and meta-analysis. Sci Rep. 2014; 4: 6791. doi: 10.1038/srep06791.

79. He J, Liao XY, Zhu JH, Xue WQ, Shen GP, Huang SY, Chen W, Jia WH. Association of MTHFR C677T and A1298C polymorphisms with non-Hodgkin lymphoma susceptibility: evidence from a meta-analysis. Sci Rep. 2014; 4: 6159. doi: 10.1038/srep06159.

80. Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst. 2004; 96: 434-42.

81. He J, Wang MY, Qiu LX, Zhu ML, Shi TY, Zhou XY, Sun MH, Yang YJ, Wang JC, Jin L, Wang YN, Li J, Yu HP, et al. Genetic variations of mTORC1 genes and risk of gastric cancer in an Eastern Chinese population. Mol Carcinog. 2013; 52 Suppl 1: E70-9. doi: 10.1002/mc.22013.

82. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959; 22: 719-48.

83. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7: 177-88.

84. Tang J, Li H, Luo J, Mei H, Peng L, Li X. The LSP1 rs3817198 T > C polymorphism contributes to increased breast cancer risk: a meta-analysis of twelve studies. Oncotarget. 2016; 7:63960-63967. doi: 10.18632/oncotarget.11741.

85. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002; 21: 1539-58. doi: 10.1002/sim.1186.

86. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997; 315: 629-34.


Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.
PII: 16309