Associations between polymorphisms in genes of base excision repair pathway and lung cancer risk
Original Article

Associations between polymorphisms in genes of base excision repair pathway and lung cancer risk

Shiqing Liu1,2, Yao Xiao3, Chengping Hu1,2, Min Li1,2,4

1Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China; 2Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha 410008, China; 3Department of General Surgery, Xiangya Hospital, Central South University, Changsha 410008, China; 4Center for Molecular Medicine, Xiangya Hospital, Central South University, Changsha 410008, China

Contributions: (I) Conception and design: M Li; (II) Administrative support: C Hu, M Li; (III) Provision of study materials or patients: S Liu, Y Xiao; (IV) Collection and assembly of data: S Liu; (V) Data analysis and interpretation: S Liu, Y Xiao; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Min Li. Department of Respiratory and Critical Care Medicine, Key Cite of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, China. Email: liminxy@protonmail.com; Yao Xiao. Department of Hepatobiliary and Pancreatic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China. Email: yaoxiao@csu.edu.cn.

Background: The correlation between at-risk polymorphisms in genes of base excision repair (BER) pathways and lung cancer (LC) risk was newly considered but still not clear, a systematic review and updated meta-analysis was performed in the current study.

Methods: We identified and recorded the eligible publications from Google Scholar, PubMed, Medicine and Web of Science. For all calculates, odds ratios (ORs) and 95% confidence intervals (CIs) were applied to estimate the potential relationship between these genetic variants and LC risk. Subsequently, Begg’s funnel plot and Egger’s test were used to appraising the publication bias.

Results: A total of 202 case-control studies extracted from 116 publications were enrolled. Firstly, we analyzed six polymorphisms in XRCC1, the overall analysis results of homozygote and recessive models illustrated that rs3213245 polymorphism was remarkably linked to an upgrade LC risk. Then, in the subgroup analysis stratified by ethnicity, we uncovered a meaningfully raised risk of LC in Asian population in homozygote and recessive models for rs3213245 polymorphism, as well as in the allelic contrast, heterozygous and dominant models for rs915927 polymorphism. For APEX1-rs1760944 polymorphism, the overall analysis suggested a significantly decreased risk. Another gene was OGG1, we identified a significantly upregulated risk in recessive model of OGG1-rs1052133 polymorphism for LC.

Conclusions: XRCC1-rs3213245 and OGG1-rs1052133 polymorphisms are risk factors for LC, while APEX1-rs1760944 polymorphism is a protective factor.

Keywords: Lung cancer (LC); risk; base excision repair pathway (BER pathway); polymorphism

Submitted Oct 07, 2019. Accepted for publication Feb 05, 2020.

doi: 10.21037/tcr.2020.02.44

Introduction

Lung cancer (LC) is the most prevalent cancer and the main cause of cancer-specific death around the world, with a poor prognosis and a high mortality, there are about 228,150 new cases and 142,670 deaths of LC around the USA in 2019 (1). Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancer, while small cell lung cancer (SCLC) accounts for 15–17% (2). The underlying mechanisms of LC remain unclear, however, a serious of studies indicated that tobacco smoking has been a high-risk factor (3-5). At the first years of this century, most evidence supported the notion that exposure to environmental carcinogens (6-9), including cigarette and electronic cigarette (10,11), result in alterations to the structural integrity of DNA and DNA lesions that may lead to mutations in oncogenes and tumor suppressor genes, thus initiating tumorigenesis (12-17).

The correlation between at-risk polymorphisms in genes of DNA repair pathways and LC risk was newly considered, reported from environmentally exposed workers or smokers (18-21). DNA repair pathway is a complex molecular network, which could continuously monitor and correct incorrect nucleotides after exposure to carcinogens, such as ultraviolet ray and benzene-based pollutants (22-24). There are several DNA repair pathways, which could minimize the mutant and toxic DNA sequence, including nucleotide excision repair (NER) pathway, base excision repair (BER) pathway, homologous recombination (HR) pathway, mismatch repair (MMR) pathway, as well as non-homologous end-joining (NHEJ) pathway. Among them, the BER is an essential pathway involved in genome stability maintaining and thus in human diseases’ prevention, ensuring to correct the abnormal DNA base modifications and base loss [such as apurinic/apyrimidinic (AP) sites] (25-27).

Recently, increasing studies indicated that DNA repair capacity could be influenced by genetic polymorphism in the BER pathway genes, which might also alter protein function that subsequently contributes to the unstable of gene sequence and cancer risk (28,29). Till now, numerous studies have focused on the potential relationship between genetic variants in BER pathway gene and LC risk, however, the results are discordant. In addition, many studies only focused on a few polymorphisms or neglected non-coding region genes, while other studies performed on a small number of cases. After all, we exhaustively extracted all eligible studies reported on genetic variations of BER pathway gene related to LC risk, and performing the current systematic review and meta-analysis to illustrated the overall relationship.

Methods

Obtain BER pathway gene set from KEGG

In order to obtain the whole gene set of BER pathway, we searched it on Kyoto Encyclopedia of Genes and Genomes (KEGG) website. Thirty-five genes in BER pathway were provided from online KEGG signaling database (http://software.broadinstitute.org/gsea/msigdb/geneset_page.jsp?geneSet Name=KEGG_BASE_EXCISION_REPAIR&keywords=BASE%20EXCISION%20REPAIR).

Study description

The resent study was conducted to reveal the correlation between genetic variants in BER pathway and LC risk. In current work, PubMed, Google Scholar, Medicine, EMbase and Web of Science databases were used to comprehensively enrolled and recorded all eligible publications. The retrieve formula was: (‘gene name’ OR ‘abbreviation of gene name’) AND (‘cancer’ OR ‘tumor’ OR ‘carcinoma’ OR ‘neoplasms’) AND (‘polymorphism’ OR ‘mutation’ OR ‘variant’ OR ‘SNP’ OR ‘genotype’). We also reviewed each reference of eligible articles, avoiding to missing any additional conform-to-criteria study. The entire retrieval was finished on October 5th, 2019. All enrolled studies were published in primary literature without any replication one. In addition, for these polymorphisms, whose eligible case-control studies are less than three will be excluded.

Enrolled criteria and exclusion criteria

There are several criteria which should be conformed are: (I) assessing whether the gene polymorphisms of BER pathway affect LC risk; (II) studies with specific case group and control group; and (III) genotype frequencies could be obtained directly or after calculating. Meanwhile, some other criteria should not be touched: (I) lacking control group, such as case-only study or review and (II) lacking sufficient genotype data.

Extraction of basic data

The ground on the enrollment standard mentioned above, all the basic data was extracted by two independent reviewers, accompany with an argument, discussion and reach an agreement. In each publication, several items were recorded, including the name of the first author, year of publication, ethnicity, source of control, number of each genotype group, and so on. Finally, we also estimated the quality of each enrolled study with the help of Newcastle-Ottawa Scale (NOS).

Statistical analysis

Hardy-Weinberg equilibrium (HWE) in the control group was tested, and P>0.05 means that the study does not deviate from HWE (30). Strength of the links between polymorphisms in BER pathway gene and LC risk was evaluated through calculating ORs and 95% CIs in five genetic models (W present for wild type allele; M present for mutant allele): allele contrast model (M vs. W), dominant contrast model (MM + MW vs. WW), recessive contrast model (MM vs. MW + WW), homozygous contrast model (MM vs. WW), and heterozygous contrast model (MW vs. WW). After that, subgroup analysis stratified by different items were also conducted. I2 statistics were used to evaluate the heterogeneity assumption between studies in each calculating group, aim to obtain the quantified inconsistency caused by heterogeneity (31). Among these studies, I2 value was regarded as a significant heterogeneity if it is higher than 50% (32), and random-effect model was performed the calculated the pooled OR and 95% CI; on the contrast, fixed-effect model will be hireling (33). To confirm the veracity of result, we use sensitivity analysis to assess the stability of results, use Begg’s funnel plot and Egger’s test to appraise any publication bias (34). We use STATA (version 12.0; STATA Corp.) to calculate all the results, and P<0.05 was regarded as statistically significant.

Results

The studies and meta-analysis data pool

After searching in diverse databases, we retrieved 116 publications comprising 202 case-control studies that met inclusion and exclusion criteria (at least three eligible case-control studies should be enrolled for each polymorphism). These publications concerned about five BER pathway gene, including X-Ray Repair Cross Complementing 1 (XRCC1), Apurinic/Apyrimidinic Endodeoxyribonuclease 1 (APEX1), DNA Ligase 1 (LIG1), 8-Oxoguanine DNA Glycosylase (OGG1) and MutY DNA Glycosylase (MUTYH) gene. In Table 1, characteristics and genotype frequency distributions of all enrolled studies for BER pathway gene were showed, including XRCC1-rs1799782/rs25487 (35-59), rs25489/rs3213245 (60-84), rs3547/rs915927 (85-90), PARP1-rs1136410 (87,91-94), APEX1-rs1130409/rs1760944/rs2307486 (42,43,47,74,76,79,80,89,92,95-101), LIG1-rs156641/rs20579/rs20581/rs3730931/rs439132 (64,71,102,103), OGG1-rs1052133 (43,47,49,70,72,74,84,85,89,92,104-126) and MUTYH-rs3219489 (104,115,118,127) polymorphisms, and the selection process of current work was described in Figure 1. For this study, we performed each process along with PRISMA 2009 checklist (Table 2), and with the aid of NOS, we also assessed each enrolled study, most of the enrolled study is higher than 7 star, which represented the good quality (129).

Table 1

Details of enrolled studies for current meta-analysis and systematic review

Gene-polymorphism First author Year Ethnicity Source of control Case Control
WW MW MM WW MW MM Y (HWE)
XRCC1-rs1799782 David-Beabes et al. 2001 African P-B 142 10 2 205 36 2 Y
David-Beabes et al. 2001 Caucasian P-B 158 22 0 407 54 0 Y
Chen et al. 2002 Asian P-B 48 44 11 57 40 5 Y
Ratnasinghe et al. 2003 Asian P-B 52 47 9 85 104 21 Y
Shen et al. 2005 Asian P-B 65 41 12 64 40 8 Y
Chan et al. 2005 Asian H-B 50 22 3 79 67 16 Y
Schneider et al. 2005 Caucasian H-B 389 53 4 544 75 3 Y
Hung et al. 2005 Caucasian H-B 1878 259 10 1828 292 12 Y
Hu et al. 2005 Asian H-B 335 311 64 339 308 63 Y
Zienolddiny et al. 2006 Caucasian P-B 309 26 1 368 35 2 Y
Landi et al. 2006 Caucasian H-B 263 32 1 262 53 1 Y
Matullo et al. 2006 Caucasian Mixed 98 16 2 951 141 2 Y
Hao et al. 2006 Asian P-B 524 409 91 572 459 87 Y
De Ruyck et al. 2007 Caucasian H-B 101 8 1 93 17 0 Y
Pachouri et al. 2007 Caucasian P-B 40 39 24 52 47 23 N
Improta et al. 2008 Caucasian P-B 78 9 7 104 17 0 Y
Yin et al. 2008 Asian H-B 120 98 23 119 109 21 Y
Li et al. 2008 Asian H-B 184 136 30 196 133 21 Y
Chang et al. 2009 African P-B 221 34 0 248 31 1 Y
Yin et al. 2009 Asian H-B 29 21 1 28 38 8 Y
Chang et al. 2009 Caucasian P-B 89 23 1 223 66 10 Y
Tanaka et al. 2010 Asian H-B 28 15 7 25 23 2 Y
Buch et al. 2011 Caucasian H-B 682 36 2 839 83 6 N
Mei et al. 2013 Asian P-B 138 90 23 155 119 27 Y
Du et al. 2014 Asian P-B 68 33 19 88 21 11 N
Yoo et al. 2014 Asian P-B 281 249 67 268 255 54 Y
Cătană et al. 2015 Caucasian P-B 89 3 10 197 22 3 N
Han et al. 2015 Asian P-B 99 90 21 106 87 17 Y
Zhu et al. 2015 Asian P-B 180 137 3 111 206 29 N
Singh et al. 2016 Caucasian P-B 256 72 2 267 55 3 Y
XRCC1-rs25487 Divine et al. 2001 Caucasian H-B 82 61 29 65 64 14 Y
David-Beabes et al. 2001 African P-B 105 46 3 164 70 9 Y
Ratnasinghe et al. 2001 Asian P-B 59 40 8 117 80 11 Y
David-Beabes et al. 2001 Caucasian P-B 87 76 17 186 217 58 Y
Chen et al. 2002 Asian P-B 55 43 5 52 40 7 Y
Park et al. 2002 Asian P-B 100 75 17 81 48 6 Y
Misra et al. 2003 Caucasian P-B 151 140 24 154 130 29 Y
Zhou et al. 2003 Caucasian P-B 467 468 156 551 545 143 Y
Harms et al. 2004 Caucasian H-B 59 42 9 56 55 8 Y
Vogel et al. 2004 Caucasian H-B 117 104 35 108 121 40 Y
Ito et al. 2004 Asian H-B 98 66 14 253 169 26 Y
Popanda et al. 2004 Caucasian H-B 186 214 63 171 222 67 Y
Liu et al. 2004 Caucasian H-B 400 397 138 551 539 143 Y
Li et al. 2005 Asian H-B 22 20 8 27 21 2 Y
Shen et al. 2005 Asian P-B 72 40 4 54 51 4 Y
Chan et al. 2005 Asian H-B 40 31 4 90 61 11 Y
Schneider et al. 2005 Caucasian H-B 199 198 49 264 280 78 Y
Hu et al. 2005 Asian H-B 378 284 48 370 282 58 Y
Zhang et al. 2005 Asian H-B 535 363 102 531 380 89 Y
Hung et al. 2005 Caucasian H-B 844 951 254 874 881 260 Y
Zienolddiny et al. 2006 Caucasian P-B 129 171 31 151 186 54 Y
Hao et al. 2006 Asian H-B 566 376 82 585 432 101 Y
Matullo et al. 2006 Caucasian Mixed 51 58 7 484 482 128 Y
De Ruyck et al. 2007 Caucasian H-B 38 53 18 46 50 13 Y
Yin et al. 2007 Asian H-B 138 65 2 132 52 9 Y
Pachouri et al. 2007 Caucasian P-B 53 38 12 35 70 17 Y
López-Cima et al. 2007 Caucasian H-B 222 219 75 217 234 82 Y
Improta et al. 2008 Caucasian P-B 42 41 11 53 61 7 N
Sreeja et al. 2008 Caucasian P-B 78 86 47 102 80 29 N
Li et al. 2008 Asian H-B 168 139 43 201 123 26 Y
Yin et al. 2009 Asian H-B 31 13 1 36 15 1 Y
Cote et al. 2009 African P-B 86 23 6 88 28 5 Y
Chang et al. 2009 African P-B 182 69 4 209 65 5 Y
Chang et al. 2009 Caucasian P-B 54 47 12 155 127 16 Y
Cote et al. 2009 Caucasian P-B 172 159 56 160 200 46 Y
Li et al. 2011 Asian H-B 236 193 26 220 196 27 Y
Kiyohara et al. 2012 Asian H-B 243 171 48 242 121 16 Y
Natukula et al. 2013 Caucasian P-B 40 19 41 55 10 36 N
Ouyang et al. 2013 Asian P-B 52 22 8 105 86 10 Y
Mei et al. 2013 Asian P-B 142 95 14 145 126 30 Y
Letkova et al. 2013 Caucasian P-B 138 202 42 157 185 37 Y
Du et al. 2014 Asian P-B 81 16 23 95 15 10 N
Sarlinova et al. 2014 Caucasian P-B 17 24 9 23 41 5 N
Uppal et al. 2014 Caucasian P-B 18 32 50 12 65 23 N
Saikia et al. 2014 Caucasian P-B 146 103 23 322 188 34 Y
Yoo et al. 2014 Asian P-B 344 207 47 313 245 33 Y
Han et al. 2015 Asian P-B 156 34 20 164 30 16 N
Wang et al. 2015 Asian P-B 259 24 217 273 43 184 N
Zhu et al. 2015 Asian P-B 221 80 19 269 72 5 Y
Cătană et al. 2015 Caucasian P-B 43 43 16 112 86 24 Y
Liu et al. 2016 Asian P-B 162 114 32 162 81 10 Y
Singh et al. 2016 Caucasian P-B 93 186 51 79 176 70 Y
XRCC1-rs25489 Ratnasinghe et al. 2001 Asian P-B 83 20 3 177 32 0 Y
Misra et al. 2003 Caucasian P-B 260 47 2 260 42 0 Y
Vogel et al. 2004 Caucasian H-B 229 26 1 241 28 0 Y
Shen et al. 2005 Asian P-B 76 30 5 81 28 1 Y
Schneider et al. 2005 Caucasian H-B 404 40 2 562 60 0 Y
Hung et al. 2005 Caucasian H-B 1901 181 6 1896 190 6 Y
Zienolddiny et al. 2006 Caucasian P-B 296 31 2 350 24 3 N
Hao et al. 2006 Asian H-B 848 169 7 904 204 10 Y
De Ruyck et al. 2007 Caucasian H-B 105 4 0 96 14 0 Y
Yin et al. 2008 Asian H-B 190 46 2 179 59 4 Y
Li et al. 2008 Asian H-B 266 79 5 74 72 4 N
Yin et al. 2009 Asian H-B 41 7 1 52 18 2 Y
Chang et al. 2009 Caucasian P-B 86 25 1 242 51 5 Y
Yoo et al. 2014 Asian P-B 506 88 5 448 127 5 Y
Han et al. 2015 Asian P-B 100 87 23 109 82 19 Y
Singh et al. 2016 Caucasian P-B 32 250 48 26 268 31 N
XRCC1-rs3213245 Hu et al. 2005 Asian H-B 500 198 12 558 148 4 Y
Hao et al. 2006 Asian H-B 783 223 18 924 182 12 Y
De Ruyck et al. 2007 Caucasian H-B 37 53 19 40 52 18 Y
Li et al. 2008 Asian H-B 264 75 11 291 55 4 Y
Hsieh et al. 2009 Asian P-B 251 40 3 250 37 1 Y
Tang et al. 2014 Asian P-B 212 163 45 225 181 19 N
Yoo et al. 2015 Asian P-B 494 104 4 462 111 4 Y
XRCC1-rs3547 Yin et al. 2008 Asian H-B 183 43 1 191 49 2 Y
Yin et al. 2009 Asian H-B 35 12 0 61 9 1 Y
Chang et al. 2009 Caucasian P-B 62 45 6 177 99 23 Y
Chang et al. 2009 African P-B 114 104 37 126 122 32 Y
Singh et al. 2016 Caucasian P-B 61 142 127 124 127 74 N
XRCC1-rs915927 Matullo et al. 2006 Caucasian Mixed 36 58 22 342 508 243 N
Yin et al. 2008 Asian H-B 169 68 2 203 43 0 Y
Yin et al. 2009 Asian H-B 36 14 1 66 7 0 Y
Singh et al. 2016 Caucasian P-B 134 164 32 147 139 39 Y
APEX1-rs1130409 Misra et al. 2003 Caucasian P-B 64 167 79 65 160 77 Y
Ito et al. 2004 Asian H-B 62 84 32 159 226 64 Y
Popanda et al. 2004 Caucasian H-B 135 235 89 118 233 106 Y
Shen et al. 2005 Asian P-B 30 61 26 37 61 15 Y
Zienolddiny et al. 2006 Caucasian P-B 117 67 80 138 60 122 N
Matullo et al. 2006 Caucasian P-B 33 56 27 309 526 259 Y
De Ruyck et al. 2007 Caucasian H-B 21 60 29 41 41 28 N
Agachan et al. 2009 Caucasian P-B 38 40 20 45 17 5 Y
Lu et al. 2009 Asian H-B 182 228 90 176 265 76 Y
Lo et al. 2009 Asian H-B 261 349 119 272 332 118 Y
Deng et al. 2010 Asian P-B 123 143 49 97 159 58 Y
Li et al. 2011 Asian H-B 179 199 77 172 213 58 Y
Xue et al. 2013 Asian H-B 116 183 111 130 190 90 Y
Pan et al. 2013 Asian H-B 48 273 498 25 247 531 Y
Li et al. 2014 Asian H-B 2 11 3 50 46 14 Y
Sevilya et al. 2015 Caucasian H-B 34 50 15 42 46 11 Y
APEX1-rs1760944 Lu et al. 2009 Asian H-B 184 241 75 170 238 109 Y
Lo et al. 2009 Asian H-B 271 332 122 234 341 153 Y
Li et al. 2011 Asian H-B 162 227 66 143 206 94 Y
Pan et al. 2013 Asian H-B 114 384 321 98 369 336 Y
Li et al. 2014 Asian H-B 3 10 3 36 56 18 Y
APEX1-rs2307486 Zienolddiny et al. 2006 Caucasian P-B 263 76 1 276 124 10 Y
Lo et al. 2009 Asian H-B 669 59 0 659 64 2 Y
Li et al. 2014 Asian H-B 11 2 0 103 7 0 Y
OGG1-rs1052133 Kohno et al. 1998 Asian Mixed 16 19 10 15 20 7 Y
Sugimura et al. 1999 Mixed H-B 85 115 41 63 107 27 Y
Wikman et al. 2000 Caucasian P-B 68 32 5 60 43 2 Y
Marchand et al. 2002 Mixed P-B 15 31 29 29 48 19 Y
Marchand et al. 2002 Caucasian P-B 78 39 9 98 53 8 Y
Sunaga et al. 2002 Asian H-B 54 106 38 50 66 36 Y
Marchand et al. 2002 Asian P-B 30 40 27 50 74 26 Y
Ito et al. 2002 Asian H-B 40 71 27 68 118 54 Y
Lan et al. 2004 Asian P-B 37 61 20 51 43 15 Y
Park et al. 2004 Caucasian P-B 88 60 12 255 87 8 Y
Vogel et al. 2004 Caucasian P-B 149 93 14 159 91 19 Y
Liang et al. 2005 Asian H-B 27 132 68 28 123 76 N
Hung et al. 2005 Caucasian H-B 1401 661 93 1368 716 79 Y
Loft et al. 2006 Caucasian P-B 144 93 14 154 88 19 Y
Zienolddiny et al. 2006 Caucasian P-B 182 100 44 194 117 75 N
Kohno et al. 2006 Asian H-B 285 544 268 123 190 81 Y
Sorensen et al. 2006 Caucasian P-B 254 155 22 479 284 33 Y
Matullo et al. 2006 Caucasian P-B 66 46 4 673 371 50 Y
De Ruyck et al. 2007 Caucasian H-B 74 33 3 60 46 4 Y
Hatt et al. 2008 Caucasian P-B 92 58 8 93 59 12 Y
Karahalil et al. 2008 Caucasian H-B 86 65 14 115 106 29 Y
Miyaishi et al. 2009 Asian H-B 27 55 26 39 54 28 Y
Chang et al. 2009 African P-B 170 78 6 202 70 8 Y
Chang et al. 2009 Caucasian P-B 53 47 12 135 132 29 Y
Chang et al. 2009 Asian P-B 142 518 436 154 482 361 Y
Okasaka et al. 2009 Asian H-B 117 257 141 250 544 236 Y
Liu et al. 2010 Asian H-B 68 158 132 110 294 312 N
Janik et al. 2011 Caucasian H-B 48 24 16 57 21 1 Y
Li et al. 2011 Asian H-B 83 208 164 60 219 164 Y
Qian et al. 2011 Asian H-B 100 288 193 125 291 185 Y
Cheng et al. 2012 Asian P-B 26 9 15 17 3 10 N
Ouyan et al. 2013 Asian P-B 14 42 26 40 94 67 Y
Letkova et al. 2013 Caucasian P-B 244 119 19 250 110 18 Y
Xue et al. 2013 Asian H-B 55 178 177 68 200 142 Y
Doherty et al. 2013 Caucasian P-B 440 265 39 873 519 85 Y
Wang et al. 2015 Asian P-B 77 182 241 80 165 25 N
Qin et al. 2016 Asian P-B 59 121 37 72 124 30 N
LIG1-rs20579 Landi et al. 2006 Caucasian Mixed 206 73 6 245 61 0 Y
Chang et al. 2008 Caucasian P-B 72 36 5 217 75 7 Y
Chang et al. 2008 African P-B 150 92 13 137 117 26 Y
Lee et al. 2008 Caucasian P-B 294 118 11 586 187 7 Y
Sakoda et al. 2012 Caucasian P-B 583 141 18 1126 312 36 N
LIG1-rs3730931 Landi et al. 2006 Caucasian Mixed 220 64 5 255 52 2 Y
Chang et al. 2008 Caucasian P-B 79 30 4 226 67 6 Y
Chang et al. 2008 African P-B 151 92 11 158 103 19 Y
Sakoda et al. 2012 Caucasian P-B 595 137 11 1137 313 26 Y
LIG1-rs156641 Chang et al. 2008 African P-B 189 62 4 215 60 5 Y
Chang et al. 2008 Caucasian P-B 59 43 11 143 126 30 Y
Sakoda et al. 2012 Caucasian P-B 271 352 121 596 709 164 N
LIG1-rs20581 Chang et al. 2008 African P-B 176 73 6 199 68 13 N
Chang et al. 2008 Caucasian P-B 38 48 27 89 151 59 Y
Lee et al. 2008 Caucasian P-B 78 148 86 142 346 155 Y
LIG1-rs439132 Chang et al. 2008 Caucasian P-B 108 5 0 269 29 1 Y
Lee et al. 2008 Caucasian P-B 326 39 6 585 54 2 Y
Chang et al. 2008 African P-B 129 112 14 117 91 12 Y
MUTYH-rs3219489 Al-tassan et al. 2003 Caucasian P-B 142 109 14 58 36 7 Y
Miyaishi et al. 2009 Asian P-B 22 57 29 37 69 15 N
Qian et al. 2011 Asian P-B 230 261 90 243 283 77 Y
Doherty et al. 2013 Caucasian P-B 417 279 42 825 562 79 Y
PARP1-rs1136410 Zhang et al. 2005 Asian H-B 307 509 184 359 504 137 Y
Yin et al. 2011 Mixed H-B 117 35 7 50 12 2 Y
Xue et al. 2013 Asian H-B 129 202 79 138 205 67 Y
Yu et al. 2014 Asian H-B 46 164 163 34 164 162 Y
Wang et al. 2015 Asian P-B 151 97 252 14 109 251 Y

M, mutant allele; W, wild type allele; P-B, population-based; H-B, hospital-based; Mixed, more than one ethnicity; N.A., not mentioned; Y, studies that conforms to HWE; N, study that deviates from HWE.

Figure 1 Flow chart showing the study selection process.

Table 2

PRISMA 2009 checklist

Section/topic # Checklist item Reported on page #
Title 1 Identify the report as a systematic review, meta-analysis, or both. Page 1
Abstract
   Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number. Page 2–3
Introduction
   Rationale 3 Describe the rationale for the review in the context of what is already known. Page 4–5
   Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS). Page 5
Methods
   Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number. N/A
   Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. Study selection: page 6–7
   Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched. Search strategy: page 5–6,
   Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. Search strategy: page 5
   Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis). Figure 1
   Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. Data extraction and quality assessment: page 7
   Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. Data extraction and quality assessment: page 7
   Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis. Statistical analysis: page 8
   Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). Statistical analysis: page 8
   Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis. Statistical analysis: page 8
Section/topic
   Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies). Statistical analysis: page 8
   Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified. Statistical analysis: page 8
Results
   Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram. Description of studies: page 8–9
   Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. Table 1–3
   Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Page 10–12
   Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. Page 10–12
   Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. Page 10–12
   Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Page 10–12
   Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16)]. page 10
Discussion
   Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers). Page 13–15
   Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias). Page 15
   Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. Page 17
Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. Page 17

Adapted from ref. (128).

Meta-analysis

XRCC1 polymorphisms and LC risk

We investigated six polymorphisms in XRCC1 gene and LC risk, including rs1799782, rs25487, rs25489, rs3213245, rs3547 and rs915927 polymorphisms (Table 3). Overall, rs3213245 polymorphism was observed associated with a significantly raised susceptibility of LC in homozygote contrast model and recessive contrast model (MM vs. WW: OR 2.023, 95% CI: 1.452–2.819, P=3.124×10−5, Figure 2A; MM vs. MW + WW: OR 1.926, 95% CI: 1.396–2.656, P=6.468×10−5, Figure 2B), while for other genetic polymorphisms, overall analyses uncovered no remarkable association. In addition, for rs3213245 polymorphism, in the ethnicity subgroup analysis, a meaningful upward risk of LC for Asian population was also uncovered in homozygote and recessive models. While for the subgroup analysis by source of control subgroup, we uncovered a remarkable upgrade risk of LC for H-B groups in allelic contrast, heterogeneous and dominant models. Furthermore, for rs915927 polymorphism, we also performed the subgroup analysis in different ethnicity and source of control, and identified the raised risk for Asian, H-B group in allelic contrast model, heterozygous model, as well as dominant model. For rs25487 polymorphism, overall analysis suggested a null association. We identified that HWE (N) group was associated with LC risk in allelic, homozygote, and recessive models, suggesting potential bias existed. After removing the HWE (N) studies from the pooled analyses, and the final results also suggested a negative result for XRCC1-rs25487 polymorphism.

Table 3

Significant results of the association between polymorphisms in BER pathway gene and LC risk

SNP Comparison Subgroup N PH PZ Random OR (95% CI) Fixed OR (95% CI)
XRCC1-rs3213245 MM vs. WW Overall 7 0.512 3.124*10−5 1.992 (1.422–2.791) 2.023 (1.452–2.819)
MM vs. MW + WW Overall 7 0.434 6.468*10−5 1.894 (1.365–2.627) 1.926 (1.396–2.656)
MM vs. WW Asian 6 0.720 1.169*10−5 2.260 (1.556–3.284) 2.285 (1.579–3.306)
MM vs. MW + WW Asian 6 0.730 1.660*10−5 2.208 (1.526–3.193) 2.231 (1.549–3.215)
M vs. W H-B 4 0.406 1.970*10−8 1.433 (1.263–1.625) 1.433 (1.264–1.625)
MW vs. WW H-B 4 0.820 6.322*10−7 1.446 (1.251–1.672) 1.446 (1.251–1.672)
MW + MM vs. WW H-B 4 0.723 4.140*10−8 1.485 (1.289–1.710) 1.485 (1.289–1.710)
XRCC1-rs915927 M vs. W Asian 2 0.180 9.975*10−5 2.292 (1.226–4.284) 2.071 (1.435–2.988)
MW vs. WW Asian 2 0.234 2.147*10−4 2.252 (1.280–3.962) 2.111 (1.421–3.136)
MW + MM vs. WW Asian 2 0.203 9.341*10−5 2.395 (1.287–4.455) 2.191 (1.478–3.247)
M vs. W H-B 2 0.180 9.975*10−5 2.292 (1.226–4.284) 2.071 (1.435–2.988)
MW vs. WW H-B 2 0.234 2.147*10−4 2.252 (1.280–3.962) 2.111 (1.421–3.136)
MW + MM vs. WW H-B 2 0.203 9.341*10−5 2.395 (1.287–4.455) 2.191 (1.478–3.247)
XRCC1-rs25487 M vs. W N 8 0.414 2.741*10−7 1.345 (1.199–1.508) 1.343 (1.200–1.502)
MM vs. WW N 8 0.471 4.463*10−5 1.481 (1.223–1.793) 1.486 (1.229–1.797)
MM vs. MW + WW N 8 0.102 3.663*10−7 1.758 (1.332–2.321) 1.592 (1.331–1.904)
APEX1-rs1760944 M vs. W Overall 5 0.530 7.243*10−5 0.851 (0.786–0.922) 0.851 (0.786–0.921)
MM vs. WW Overall 5 0.534 3.409*10−5 0.705 (0.598–0.832) 0.705 (0.598–0.832)
MM vs. MW + WW Overall 5 0.315 1.927*10−4 0.770 (0.663–0.895) 0.780 (0.684–0.889)
OGG1-rs1052133 MM vs. MW + WW Overall 31 0.106 2.119*10−4 1.143 (1.032–1.265) 1.157 (1.071–1.249)
M vs. W Asian 13 0.355 9.988*10−5 1.123 (1.054–1.196) 1.123 (1.059–1.191)
MM vs. WW Asian 13 0.353 3.585*10−4 1.242 (1.090–1.414) 1.244 (1.103–1.403)

M, mutant allele; W, wild type allele; P-B, population-based; H-B, hospital-based; Y, studies that conforms to HWE; N, study that deviates from HWE; PH, P value of heterogeneity test; Pz, adjusted P value of Z test [P<0.05/(17 polymorphisms * 5 genetic models)].

Figure 2 The forest plot of the meta-analysis for rs3213245 polymorphism. (A) Homozygous model and (B) recessive model, for rs1760944 polymorphism. (C) Homozygous model, and for rs1052133 polymorphism (D) recessive model.

APEX1 polymorphism and LC risk

For rs1760944 polymorphism, overall analysis suggested a sharp reduced risk of LC in allelic, homozygote and recessive models (M vs. W: OR 0.851, 95% CI: 0.786–0.922, P=7.243×10−5, Figure 2C; MM vs. WW: OR 0.705, 95% CI: 0.598–0.832, P=3.409×10−5; and MM vs. MW + WW: OR 0.780, 95% CI: 0.684–0.889, P=1.927×10−4, Table 3).

OGG1 polymorphism and LC risk

For OGG1-rs1052133 polymorphism, the recessive model showed an increased risk overall group (MM vs. MW + WW: OR 1.157, 95% CI: 1.071–1.249, P=2.119×10−4, Figure 2D). In addition, when the stratification analysis of Asian subgroup, we illustrated a significantly increased risk of LC in allelic contrast model and homozygote model (Table 3).

Other gene polymorphism and LC risk

While for other polymorphisms in genes the BER pathway, such as LIG1-rs156641, MUTYH-rs3219489, we failed to identify any significant association.

Evaluation of stability and publication bias

The test of the stability of results was assessed by sensitivity analysis, each time we separated one study form data pool, and reviewed whether it affects the ORs and 95% CIs. The results displayed that no substantial change for XRCC1-rs1799782/rs25487/rs25489/rs3213245/rs3547/rs915927, LIG1-rs156641/rs20579/rs20581/rs3730931/rs439132, APEX1-rs1130409/rs1760944/rs2307486, PARP1-rs1136410, OGG1-rs1052133 and MUTYH-rs3219489 polymorphisms.

For behalf of evaluating potential publication bias, we use Begg’s funnel plot and Egger’s test. Significant publication bias may reflect differences in control options, age distributions and other lifestyles. Finally, the shape of Begg’s funnel plot in each polymorphism is symmetrical, while the P value of Egger’s test in each polymorphism and subgroup is higher than 0.05, indicating no evidence of publication bias was found (Table 4).

Table 4

Egger’s regression test for polymorphisms in BER pathway gene

Gene Polymorphism Egger’s test (P > |t|)
XRCC1 rs1799782 0.896
rs25487 0.248
rs25489 0.99
rs3213245 0.497
rs3547 0.565
rs915927 0.115
LIG1 rs156641 0.377
rs20579 0.401
rs20581 0.388
rs3730931 0.127
rs439132 0.589
APEX1 rs1130409 0.006
rs1760944 0.312
rs2307486 0.38
PARP1 rs1136410 0.603
OGG1 rs1052133 0.337

Discussion

The stability of the general genomic sequence is sustained by a pivotal gene family, BER signaling pathway. In human cells, the inability of remove endogenous DNA damage would link with single nucleotide polymorphisms (130-132). On the other hand, the abnormal process occurs on BER pathway or the enzymes mediate it would finally lead to the instable cell chromosomal (133). Recently, increasing evidence suggested that genetic variants in the BER pathway were associated with LC risk. However, these results were inclusive or even controversial. Therefore, we presented the comprehensively updated meta-analysis, aiming to systematically screen out the LC risk or protective factors within genes of the BER pathway.

Firstly, we investigated the XRCC1, a crucial element of the BER system, it has multiple key roles in the repair process of DNA single nucleotide polymorphism (134,135). We analyzed six commonly studied polymorphisms in XRCC1, and overall analyses suggested that MM genotype of rs3213245 (−77T > C) polymorphism was linked to a sharply enhanced risk of LC compared with WW and MW/WW genotypes, and not the rs25487 and rs1799782 polymorphisms, which were proved associated with LC risk in Chen et al.’s meta-analysis work (136). In addition, rs3213245-MM genotype was also combined with an increased hazard of LC for Asian population. For XRCC1 rs3213245 polymorphism, the affinity of XRCC1 promoter region to nuclear protein Sp1 would be enhanced by T to C mutation, caused the inhibition of its transcription (40). In our study, seven studies were focused on the correlation of rs3213245 polymorphism and LC risk, and the overall results suggested that the risk in MM genotype group was 2.023 and 1.926-fold raised than WW group and MW + WW group, respectively, almost consistent with Vineis et al.’s (137) findings.

In addition, the overall calculate illustrated a negative association between XRCC1-rs915927 and LC, but we also identified that M allele, MW and MW + MM genotypes led to an enhanced risk of LC for the Asian population. For the mechanism part, rs915927 leads to a synonymous mutation, which is a kind of mutation which may not influence the translation of amino acid product, however, this kind of mutation might change the translational efficiency of mRNA, therefore, non-synonymous mutations like XRCC1 rs1799782 (Arg194Trp) and XRCC1 rs25489 (Arg280His) might regulate LC susceptibility, affecting complex assembly or repair efficiency (138). Furthermore, for another XRCC1-rs25487 polymorphism, we observed an enhanced risk of LC in allelic, homozygote, and recessive models for HWE (N) group, which tell us that there might be some potential bias caused by HWE status. Therefore, we decided to remove these HWE (N) studies from pooled analysis, and finally negative results were obtained.

Secondly, APEX1 gene was also analyzed, which specifically activates DNA repair through the identification and cleavage of phosphodiester bonds on the 5' side of the basic site (139). APEX1 can also participate in oxidative stress, control of cell cycle, and apoptosis (140,141). Recent days, several researchers reported that APEX1 gene polymorphisms would influence the cancer risks (142-144), as well as some meta-analyses (most of them only focus on a few variants) (145). In current work, we analyzed three most commonly polymorphisms reported in APEX1 (rs1130409, rs1760944 and rs2307486) and LC risk, and we found that M allele, MM genotype at rs1760944 were associated with a reduced risk of LC relative to W allele, WW and MW+WW genotypes, respectively. While for the other two polymorphisms, we failed to identify any significant correlations.

In the progression of different types of cancers, APEX1 is another key role. For APEX1-rs1130409, Zhang et al. (146) reported that the G allele and GG/TG genotype associated with the decreased risk of ovarian carcinoma. However, Yuan et al. (147) revealed that rs1130409 do not play any role in head and neck neoplasms in Chinese, another study conducted in gastric cancer reported the same conclusion (148). In our work, we obtained the result that re1130409 is not associated with LC risks. For another role polymorphism in APEX1, Lu et al. (99) first reported the potential risk of rs1760944 in LC. In a study about Korean, rs1760944 was reported associated with the risk of gastric cancer, but another study conducted in Chinese indicated that GT or GG genotypes might have a higher survival rate (148,149). Dai et al. managed a meta-analysis, the result supported the conclusion that rs1760944 acts as a protector in cancer of Asian (150). Consistent with these data, we demonstrated that M allele and MM genotype were associated with a decreased risk of LC than W allele, WW and MW + WW genotypes.

Another BER gene we analyzed here is OGG1, which plays a key role during the repair process of oxidative DNA damage. rs1052133 polymorphism had been reported could substitution Serene to Cysteine at codon 326, and influence the function of OGG1 protein (151). As reported by Wikman et al. (122), LC susceptibility might not be impacted by the OGG1 polymorphisms in Caucasians. Hung et al. (70) and Vogel et al. (84) also observed no link between OGG1 polymorphisms and LC susceptibility. Ito et al. (107) found that OGG1-rs1052133 polymorphism had no effect on the development of adenocarcinoma or small cell carcinoma. Whereas in our work, overall results suggested a null correlation for this polymorphism and LC risk.

In this meta-analysis, we comprehensively searched all available eligible studies to obtain the precise result. Some advantages of this study should be focused on. Firstly, a wide search was conducted to identify more qualified studies for each genetic variant in BER genes, therefore these analyses were persuasive and substantive. For example, several previous meta-analyses have been published concerning XRCC1 polymorphisms and LC risk, while they only focus limited polymorphisms on LC risk, and their results were not adjusted, increasing the false-positive results rate. Secondly, we evaluated the quality of each registered research by NOS scale before calculating, and eliminated low-quality studies. and adjusted all the results according to Bonferroni corrections, making the conclusions more convincing. Thirdly, according to the subgroup, we also conducted the stratification analyses by ethnicity, source of controls, tumor type or race, in order to eliminate the influence of heterogeneity. Fourthly, the sensitivity analysis was performed to confirm the stability of the obtained results, and Egger’s test and Begg’s funnel plot were performed to draw out the potential publication bias.

Several disadvantages should also be displayed to avoid any incorrect understanding of the results. First of all, there were no sufficient samples for the analyses of some variants, and it might prove an undependable association between polymorphisms and LC. For example, there are only 3 or 4 studies in APEX1-rs2307486, LIG1-rs156641 and PARP1-rs1136410, more studies conducted in these polymorphisms are needed to reveal a more convincible result in the future. Moreover, only the articles in English were enrolled, which might miss the important result in other languages and countries. Finally, the detail information about the histological result of each LC patient was missed, so the stratification analyses based on histological type and the clinical stage could not be conducted.

Conclusions

To conclude, this meta-analysis shows that XRCC1-rs3213245 and OGG1-rs1052133 polymorphisms are risk factors for LC, while APEX1-rs1760944 polymorphism is a protective factor. Future studies with larger sample size are warranted to verify these findings.

Acknowledgments

Funding: The study was supported by Natural Science Foundation of China (81903020), China Postdoctoral Science Foundation (2019M652812), National Multidisciplinary Cooperative Diagnosis and Treatment Capacity Building Project for Major Diseases (Lung Cancer)

Footnote

Conflicts of Interest: The authors have completed the ICMJE uniform disclosure from (available at http://dx.doi.org/10.21037/tcr.2020.02.44). The authors have no conflicts of interests to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019;69:7-34. [Crossref] [PubMed]
  2. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. [Crossref] [PubMed]
  3. Hosgood HD 3rd, Cosgrove C, Klugman M, et al. Lung cancer mortality among smokers and never-smokers in the United States. Epidemiology 2020; [Epub ahead of print]. [Crossref] [PubMed]
  4. Klebe S, Leigh J, Henderson DW, et al. Asbestos, Smoking and Lung Cancer: An Update. Int J Environ Res Public Health 2019; [Crossref] [PubMed]
  5. Adie Y, Kats DJ, Tlimat A, et al. Neighborhood Disadvantage and Lung Cancer Incidence in Ever-Smokers at a Safety Net Health-Care System: A Retrospective Study. Chest 2019; [Epub ahead of print]. [PubMed]
  6. Yu S, Gong LS, Li NF, et al. Galangin (GG) combined with cisplatin (DDP) to suppress human lung cancer by inhibition of STAT3-regulated NF-kappaB and Bcl-2/Bax signaling pathways. Biomed Pharmacother 2018;97:213-24. [Crossref] [PubMed]
  7. Zhao J, Wen C, Li M. Association Analysis of Interleukin-17 Gene Polymorphisms with the Risk Susceptibility to Tuberculosis. Lung 2016;194:459-67. [Crossref] [PubMed]
  8. Wang SS, Zhu XQ, Yang SD, et al. Association of p73 G4C14-to-A4T14 polymorphism with non-small cell lung cancer risk. Oncol Lett 2015;10:995-9. [Crossref] [PubMed]
  9. Barnes JL, Zubair M, John K, et al. Carcinogens and DNA damage. Biochem Soc Trans 2018;46:1213-24. [Crossref] [PubMed]
  10. Ganapathy V, Manyanga J, Brame L, et al. Electronic cigarette aerosols suppress cellular antioxidant defenses and induce significant oxidative DNA damage. PLoS One 2017;12:e0177780. [Crossref] [PubMed]
  11. Izzotti A, Balansky R, Micale RT, et al. Modulation of smoke-induced DNA and microRNA alterations in mouse lung by licofelone, a triple COX-1, COX-2 and 5-LOX inhibitor. Carcinogenesis 2019; [Epub ahead of print]. [Crossref] [PubMed]
  12. Smith LE, Denissenko MF, Bennett WP, et al. Targeting of lung cancer mutational hotspots by polycyclic aromatic hydrocarbons. J Natl Cancer Inst 2000;92:803-11. [Crossref] [PubMed]
  13. Brancato B, Munnia A, Cellai F, et al. 8-Oxo-7,8-dihydro-2'-deoxyguanosine and other lesions along the coding strand of the exon 5 of the tumour suppressor gene P53 in a breast cancer case-control study. DNA Res 2016;23:395-402. [Crossref] [PubMed]
  14. Peng Z, Wang J, Shan B, et al. Genome-wide analyses of long noncoding RNA expression profiles in lung adenocarcinoma. Sci Rep 2017;7:15331. [Crossref] [PubMed]
  15. Gan PP, Zhou YY, Zhong MZ, et al. Endoplasmic Reticulum Stress Promotes Autophagy and Apoptosis and Reduces Chemotherapy Resistance in Mutant p53 Lung Cancer Cells. Cell Physiol Biochem 2017;44:133-51. [Crossref] [PubMed]
  16. Chen J, Wu L, Wang Y, et al. Effect of transporter and DNA repair gene polymorphisms to lung cancer chemotherapy toxicity. Tumour Biol 2016;37:2275-84. [Crossref] [PubMed]
  17. Yang B, Zhao F, Zong Z, et al. Preferences for treatment of lobectomy in Chinese lung cancer patients: video-assisted thoracoscopic surgery or open thoracotomy? Patient Prefer Adherence 2014;8:1393-7. [Crossref] [PubMed]
  18. Li W, Zhang M, Huang C, et al. Genetic variants of DNA repair pathway genes on lung cancer risk. Pathol Res Pract 2019;215:152548. [Crossref] [PubMed]
  19. Lawania S, Singh A, Sharma S, et al. The multi-faceted high order polymorphic synergistic interactions among nucleotide excision repair genes increase the risk of lung cancer in North Indians. Mutat Res 2019;816-818:111673. [Crossref] [PubMed]
  20. Singh A, Singh N, Behera D, et al. Role of polymorphic XRCC6 (Ku70)/XRCC7 (DNA-PKcs) genes towards susceptibility and prognosis of lung cancer patients undergoing platinum based doublet chemotherapy. Mol Biol Rep 2018;45:253-61. [Crossref] [PubMed]
  21. Munnia A, Giese RW, Polvani S, et al. Bulky DNA Adducts, Tobacco Smoking, Genetic Susceptibility, and Lung Cancer Risk. Adv Clin Chem 2017;81:231-77. [Crossref] [PubMed]
  22. Trenner A, Sartori AA. Harnessing DNA Double-Strand Break Repair for Cancer Treatment. Front Oncol 2019;9:1388. [Crossref] [PubMed]
  23. Lee TH, Kang TH. DNA Oxidation and Excision Repair Pathways. Int J Mol Sci 2019; [Crossref] [PubMed]
  24. Zhou R, Xu T, Nguyen QN, et al. Radiation Dose, Local Disease Progression, and Overall Survival in Patients With Inoperable Non-Small Cell Lung Cancer After Concurrent Chemoradiation Therapy. Int J Radiat Oncol Biol Phys 2018;100:452-61. [Crossref] [PubMed]
  25. Whitaker AM, Schaich MA, Smith MS, et al. Base excision repair of oxidative DNA damage: from mechanism to disease. Front Biosci (Landmark Ed) 2017;22:1493. [Crossref] [PubMed]
  26. Poletto M, Legrand AJ, Dianov GL. DNA base excision repair: the Achilles' heel of tumour cells and their microenvironment? Curr Pharm Des 2017;23:4758-72. [Crossref] [PubMed]
  27. Abbotts R. Coordination of DNA single strand break repair. Free Radic Biol Med 2017;107:228-44. [Crossref] [PubMed]
  28. Alberg AJ, Jorgensen TJ, Ruczinski I, et al. DNA repair gene variants in relation to overall cancer risk: a population-based study. Carcinogenesis 2013;34:86-92. [Crossref] [PubMed]
  29. Howard MJ, Wilson SH. DNA scanning by base excision repair enzymes and implications for pathway coordination. DNA Repair (Amst) 2018;71:101-7. [Crossref] [PubMed]
  30. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-34. [Crossref] [PubMed]
  31. Lau J, Ioannidis JP, Schmid CH. Quantitative synthesis in systematic reviews. Ann Intern Med 1997;127:820-6. [Crossref] [PubMed]
  32. Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60. [Crossref] [PubMed]
  33. Yong G, Pan X, Su T, et al. Glutathione S-transferase P1 Ile105Val polymorphism and colorectal cancer risk: a meta-analysis and HuGE review. Eur J Cancer 2009;45:3303-14. [Crossref] [PubMed]
  34. Harbord RM, Egger M, Sterne JAC. A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med 2006;25:3443-57. [Crossref] [PubMed]
  35. Cătană A, Pop M, Hincu BD, et al. TheXRCC1Arg194Trp polymorphism is significantly associated with lung adenocarcinoma: a case-control study in an Eastern European Caucasian group. Onco Targets Ther 2015;8:3533-8. [Crossref] [PubMed]
  36. Chan EC, Lam SY, Fu KH, et al. Polymorphisms of the GSTM1, GSTP1, MPO, XRCC1, and NQO1 genes in Chinese patients with non-small cell lung cancers: relationship with aberrant promoter methylation of the CDKN2A and RARB genes. Cancer Genet Cytogenet 2005;162:10. [Crossref] [PubMed]
  37. David-Beabes GL, London SJ. Genetic polymorphism of XRCC1 and lung cancer risk among African-Americans and Caucasians. Lung Cancer 2001;34:333. [Crossref] [PubMed]
  38. Divine KK, Gilliland FD, Crowell RE, et al. The XRCC1 399 glutamine allele is a risk factor for adenocarcinoma of the lung. Mutat Res 2001;461:273-8. [Crossref] [PubMed]
  39. Han JC, Zhang YJ, Li XD. Association between polymorphisms in the XRCC1 gene and the risk of non-small cell lung cancer. Genet Mol Res 2015;14:12888. [Crossref] [PubMed]
  40. Hao B, Miao X, Li Y, et al. A novel T-77C polymorphism in DNA repair gene XRCC1 contributes to diminished promoter activity and increased risk of non-small cell lung cancer. Oncogene 2006;25:3613-20. [Crossref] [PubMed]
  41. Harms C, Salama SA, Sierra-Torres CH, et al. Polymorphisms in DNA repair genes, chromosome aberrations, and lung cancer. Environ Mol Mutagen 2004;44:74-82. [Crossref] [PubMed]
  42. Ito H, Matsuo K, Hamajima N, et al. Gene-environment interactions between the smoking habit and polymorphisms in the DNA repair genes, APE1 Asp148Glu and XRCC1 Arg399Gln, in Japanese lung cancer risk. Carcinogenesis 2004;25:1395. [Crossref] [PubMed]
  43. K DR. Polymorphisms in base-excision repair and nucleotide-excision repair genes in relation to lung cancer risk. Mutat Res 2007;631:101-10. [Crossref] [PubMed]
  44. Kiyohara C, Horiuchi T, Takayama K, et al. Genetic Polymorphisms Involved in Carcinogen Metabolism and DNA Repair and Lung Cancer Risk in a Japanese Population. J Thorac Oncol 2012;7:954-62. [Crossref] [PubMed]
  45. Liu G, Zhou W, Park S, et al. The SOD2 Val/Val genotype enhances the risk of nonsmall cell lung carcinoma by p53 and XRCC1 polymorphisms. Cancer 2004;101:2802. [Crossref] [PubMed]
  46. Liu HX, Li J, Ye BG. Correlation between gene polymorphisms of CYP1A1, GSTP1, ERCC2, XRCC1, and XRCC3 and susceptibility to lung cancer. Genet Mol Res 2016;15. [PubMed]
  47. Matullo G, Dunning AM, Guarrera S, et al. DNA repair polymorphisms and cancer risk in non-smokers in a cohort study. Carcinogenesis 2006;27:997-1007. [Crossref] [PubMed]
  48. Mei C, Mei H, Guo S, et al. Polymorphisms in DNA repair genes of XRCC1, XPA, XPC, XPD and associations with lung cancer risk in Chinese people. Thoracic Cancer 2014;5:232-42. [Crossref] [PubMed]
  49. Ouyang FD, Yang FL, Chen HC, et al. Polymorphisms of DNA repair genes XPD, XRCC1, and OGG1, and lung adenocarcinoma susceptibility in Chinese population. Tumour Biol 2013;34:2843-8. [Crossref] [PubMed]
  50. Park JY, Lee SY, Jeon HS, et al. Polymorphism of the DNA repair gene XRCC1 and risk of primary lung cancer. Cancer Epidemiol Biomarkers Prev 2002;11:23-7. [PubMed]
  51. Ratnasinghe D, Yao SX, Tangrea JA, et al. Polymorphisms of the DNA repair gene XRCC1 and lung cancer risk. Cancer Epidemiol Biomarkers Prev 2001;10:119-23. [PubMed]
  52. Ratnasinghe DL, Yao SX, Forman M, et al. Gene-environment interactions between the codon 194 polymorphism of XRCC1 and antioxidants influence lung cancer risk. Anticancer Res 2003;23:627-32. [PubMed]
  53. Ryk C, Kumar R, Thirumaran RK, et al. Polymorphisms in the DNA repair genes XRCC1, APEX1, XRCC3 and NBS1, and the risk for lung cancer in never- and ever-smokers. Lung Cancer 2006;54:285-92. [Crossref] [PubMed]
  54. Saikia BJ, Phukan RK, Sharma SK, et al. Interaction of XRCC1 and XPD gene polymorphisms with lifestyle and environmental factors regarding susceptibility to lung cancer in a high incidence population in North East India. Asian Pac J Cancer Prev 2014;15:1993. [Crossref] [PubMed]
  55. Schneider J, Classen V, Bernges U, et al. XRCC1 polymorphism and lung cancer risk in relation to tobacco smoking. Int J Mol Med 2005;16:709. [PubMed]
  56. Singh A, Singh N, Behera D, et al. Association and multiple interaction analysis among five XRCC1 polymorphic variants in modulating lung cancer risk in North Indian population. Dna Repair 2016;47:30-41. [Crossref] [PubMed]
  57. Tang J, Zhao J, Zhao J. The relationship between genetic variants of XRCC1 gene and lung cancer susceptibility in Chinese Han population. Med Oncol 2014;31:157. [Crossref] [PubMed]
  58. Tecmer P, Bast R, Ruud K, et al. Polymorphisms of the DNA repair genes XRCC1 and XRCC3 and risk of lung and colorectal cancer: a case-control study in a Southern Italian population. Anticancer Res 2008;28:2941-6. [PubMed]
  59. Yin J, Vogel U, Ma Y, et al. The DNA repair gene XRCC1 and genetic susceptibility of lung cancer in a northeastern Chinese population. Lung Cancer 2007;56:153-60. [Crossref] [PubMed]
  60. Yin J, Vogel U, Ma Y, et al. Association of DNA repair gene XRCC1 and lung cancer susceptibility among nonsmoking Chinese women. Cancer Genet Cytogenet 2009;188:26-31. [Crossref] [PubMed]
  61. Yin J, Vogel U, Ma Y, et al. Haplotypes of nine single nucleotide polymorphisms on chromosome 19q13.2-3 associated with susceptibility of lung cancer in a Chinese population. Mutat Res 2008;641:12. [Crossref] [PubMed]
  62. Hu Z1. A promoter polymorphism (-77T>C) of DNA repair gene XRCC1 is associated with risk of lung cancer in relation to tobacco smoking. Pharmacogenet Genomics 2005;15:457. [Crossref] [PubMed]
  63. Zhu DQ, Zou Q, Hu CH, et al. XRCC1 genetic polymorphism acts a potential biomarker for lung cancer. Tumour Biol 2015;36:3745-50. [Crossref] [PubMed]
  64. Chang JS, Wrensch MR, Hansen HM, et al. Nucleotide excision repair genes and risk of lung cancer among San Francisco Bay Area Latinos and African Americans. Int J Cancer 2008;123:2095. [Crossref] [PubMed]
  65. Chen S, Tang D, Xue K, et al. DNA repair gene XRCC1 and XPD polymorphisms and risk of lung cancer in a Chinese population. Carcinogenesis 2002;23:1321. [Crossref] [PubMed]
  66. Buch SC, Diergaarde B, Nukui T, et al. Genetic variability in DNA repair and cell cycle control pathway genes and risk of smoking-related lung cancer. Mol Carcinog 2012;51:E11. [Crossref] [PubMed]
  67. Cote ML, Yoo W, Wenzlaff AS, et al. Tobacco and estrogen metabolic polymorphisms and risk of non-small cell lung cancer in women. Carcinogenesis 2009;30:626. [Crossref] [PubMed]
  68. Du Y, He Y, Mei Z, et al. Association between genetic polymorphisms in XPD and XRCC1 genes and risks of non-small-cell lung cancer in East Chinese Han population. Clin Respir J 2016;10:311. [Crossref] [PubMed]
  69. Hsieh WC, Cheng YW, Lin CJ, et al. Prognostic significance of X-ray cross-complementing group 1 T-77C polymorphism in resected non-small cell lung cancer. Jpn J Clin Oncol 2009;39:81-5. [Crossref] [PubMed]
  70. Hung RJ, Brennan P, Canzian F, et al. Large-scale investigation of base excision repair genetic polymorphisms and lung cancer risk in a multicenter study. J Natl Cancer Inst 2005;97:567-76. [Crossref] [PubMed]
  71. Landi S, Gemignani F, Canzian F, et al. DNA repair and cell cycle control genes and the risk of young-onset lung cancer. Cancer Res 2006;66:11062. [Crossref] [PubMed]
  72. Letkova L, Matakova T, Musak L, et al. DNA repair genes polymorphism and lung cancer risk with the emphasis to sex differences. Mol Biol Rep 2013;40:5261-73. [Crossref] [PubMed]
  73. Li M, Yin Z, Guan P, et al. XRCC1 polymorphisms, cooking oil fume and lung cancer in Chinese women nonsmokers. Lung Cancer 2008;62:145. [Crossref] [PubMed]
  74. Li Z, Guan W, Li MX, et al. Genetic Polymorphism of DNA Base-excision Repair Genes (APE1, OGG1 and XRCC1) and Their Correlation with Risk of Lung Cancer in a Chinese Population. Arch Med Res 2011;42:226. [Crossref] [PubMed]
  75. Lópezcima MF, Gonzálezarriaga P, Garcíacastro L, et al. Polymorphisms in XPC, XPD, XRCC1, and XRCC3 DNA repair genes and lung cancer risk in a population of Northern Spain. BMC Cancer 2007;7:162. [Crossref] [PubMed]
  76. Misra RR, Ratnasinghe D, Tangrea JA, et al. Polymorphisms in the DNA repair genes XPD, XRCC1, XRCC3, and APE/ref-1, and the risk of lung cancer among male smokers in Finland. Cancer Lett 2003;191:171. [Crossref] [PubMed]
  77. Natukula K, Jamil K, Pingali UR, et al. The codon 399 Arg/Gln XRCC1 polymorphism is associated with lung cancer in Indians. Asian Pac J Cancer Prev 2013;14:5275-9. [Crossref] [PubMed]
  78. Pachouri SS, Sobti RC, Kaur P, et al. Contrasting impact of DNA repair gene XRCC1 polymorphisms Arg399Gln and Arg194Trp on the risk of lung cancer in the north-Indian population. DNA Cell Biol 2007;26:186-91. [Crossref] [PubMed]
  79. Popanda O, Schattenberg T, Phong CT, et al. Specific combinations of DNA repair gene variants and increased risk for non-small cell lung cancer. Carcinogenesis 2004;25:2433. [Crossref] [PubMed]
  80. Shen M, Berndt SI, Rothman N, et al. Polymorphisms in the DNA base excision repair genes APEX1 and XRCC1 and lung cancer risk in Xuan Wei, China. Anticancer Res 2005;25:537. [PubMed]
  81. Sreeja L, Syamala VS, Syamala V, et al. Prognostic importance of DNA repair gene polymorphisms of XRCC1 Arg399Gln and XPD Lys751Gln in lung cancer patients from India. J Cancer Res Clin Oncol 2008;134:645-52. [Crossref] [PubMed]
  82. Tanaka Y, Maniwa Y, Bermudez VP, et al. Nonsynonymous single nucleotide polymorphisms in DNA damage repair pathways and lung cancer risk. Cancer 2010;116:896. [Crossref] [PubMed]
  83. Uppal V, Mehndiratta M, Mohapatra D, et al. XRCC-1 Gene Polymorphism (Arg399Gln) and Susceptibility to Development of Lung Cancer in Cohort of North Indian Population: A Pilot Study. J Clin Diagn Res 2014;8:17-20. [PubMed]
  84. Vogel U, Nexø BA, Wallin H, et al. No Association Between Base Excision Repair Gene Polymorphisms and Risk of Lung Cancer. Biochem Genet 2004;42:453-60. [Crossref] [PubMed]
  85. Wang X, Ma KW, Zhao YG, et al. XRCC1 rs25487 polymorphism is associated with lung cancer risk in epidemiologically susceptible Chinese people. Genet Mol Res 2015;14:15530. [Crossref] [PubMed]
  86. Yoo SS, Jin C, Jung DK, et al. Putative functional variants of XRCC1 identified by RegulomeDB were not associated with lung cancer risk in a Korean population. Cancer Genet 2015;208:19. [Crossref] [PubMed]
  87. Zhang X, Miao X, Liang G, et al. Polymorphisms in DNA base excision repair genes ADPRT and XRCC1 and risk of lung cancer. Cancer Res 2005;65:722-6. [PubMed]
  88. Zhou W, Liu G, Miller DP, et al. Polymorphisms in the DNA repair genes XRCC1 and ERCC2, smoking, and lung cancer risk. Cancer Epidemiol Biomarkers Prev 2003;12:359. [PubMed]
  89. Zienolddiny S, Campa D, Lind H, et al. Polymorphisms of DNA repair genes and risk of non-small cell lung cancer. Carcinogenesis 2006;27:560. [Crossref] [PubMed]
  90. Sarlinova M, Majerova L, Matakova T, et al. Polymorphisms of DNA repair genes and lung cancer in chromium exposure. Adv Exp Med Biol 2015;833:1-8. [PubMed]
  91. Wang HT, Gao Y, Zhao YX, et al. PARP-1 rs3219073 Polymorphism May Contribute to Susceptibility to Lung Cancer. Genet Test Mol Biomarkers 2014;18:736-40. [Crossref] [PubMed]
  92. Xue X, Yin Z, Lu Y, et al. The joint effect of hOGG1, APE1, and ADPRT polymorphisms and cooking oil fumes on the risk of lung adenocarcinoma in Chinese non-smoking females. PLos One 2013;8:e71157. [Crossref] [PubMed]
  93. Yin M, Liao Z, Liu Z, et al. Functional polymorphisms of base excision repair genes XRCC1 and APEX1 predict risk of radiation pneumonitis in patients with non-small cell lung cancer treated with definitive radiation therapy. Int J Radiat Oncol Biol Phys 2011;81:e67. [Crossref] [PubMed]
  94. Yu P, Liu YP, Zhang JD, et al. Correlation between PARP-1 Val762Ala polymorphism and the risk of lung cancer in a Chinese population. Tumour Biol 2015;36:177. [Crossref] [PubMed]
  95. Agaçhan B, Küçükhüseyin O, Aksoy P, et al. Apurinic/apyrimidinic endonuclease (APE1) gene polymorphisms and lung cancer risk in relation to tobacco smoking. Anticancer Res 2009;29:2417-20. [PubMed]
  96. Deng Q, Sheng L, Su D, et al. Genetic polymorphisms in ATM, ERCC1, APE1 and iASPP genes and lung cancer risk in a population of southeast China. Med Oncol 2011;28:667-72. [Crossref] [PubMed]
  97. Li H, Liu G, Xia L, et al. A polymorphism in the DNA repair domain of APEX1 is associated with the radiation-induced pneumonitis risk among lung cancer patients after radiotherapy. Br J Radiol 2014;87:20140093. [Crossref] [PubMed]
  98. Shannon AM, Telfer BA, Smith PD, et al. The mitogen-activated protein/extracellular signal-regulated kinase kinase 1/2 inhibitor AZD6244 (ARRY-142886) enhances the radiation responsiveness of lung and colorectal tumor xenografts. Clin Cancer Res 2009;15:6619-29. [Crossref] [PubMed]
  99. Lu J, Zhang SD. Functional characterization of a promoter polymorphism in APE1/Ref-1 that contributes to reduced lung cancer susceptibility. Faseb J 2009;23:3459. [Crossref] [PubMed]
  100. Pan H, Niu W, He L, et al. Contributory role of five common polymorphisms of RAGE and APE1 genes in lung cancer among Han Chinese. PLos One 2013;8:e69018. [Crossref] [PubMed]
  101. Sevilya Z, Leitnerdagan Y, Pinchev M, et al. Development of APE1 enzymatic DNA repair assays: low APE1 activity is associated with increase lung cancer risk. Carcinogenesis 2015;36:982-91. [Crossref] [PubMed]
  102. Lee YC, Morgenstern H, Greenland S, et al. A case-control study of the association of the polymorphisms and haplotypes of DNA ligase I with lung and upper-aerodigestive-tract cancers. Int J Cancer 2008;122:1630-8. [Crossref] [PubMed]
  103. Sakoda LC, Loomis MM, Doherty JA, et al. Germ line variation in nucleotide excision repair genes and lung cancer risk in smokers. Int J Mol Epidemiol Genet 2012;3:1. [PubMed]
  104. Doherty JA, Sakoda LC, Loomis MM, et al. DNA repair genotype and lung cancer risk in the beta-carotene and retinol efficacy trial. Int J Mol Epidemiol Genet 2013;4:11-34. [PubMed]
  105. H S. hOGG1 Ser326Cys polymorphism and lung cancer susceptibility. Cancer Epidemiol Biomarkers Prev 1999;8:669-74. [PubMed]
  106. Hatt L, Loft S, Risom L, et al. OGG1 expression and OGG1 Ser326Cys polymorphism and risk of lung cancer in a prospective study. Mutat Res 2008;639:45-54. [Crossref] [PubMed]
  107. Ito H, Hamajima N, Takezaki T, et al. A limited association of OGG1 Ser326Cys polymorphism for adenocarcinoma of the lung. J Epidemiol 2002;12:258-65. [Crossref] [PubMed]
  108. Janik J, Swoboda M, Janowska B, et al. 8-Oxoguanine incision activity is impaired in lung tissues of NSCLC patients with the polymorphism of OGG1 and XRCC1 genes. Mutat Res 2011;709-710:21-31. [Crossref] [PubMed]
  109. Kohno T, Kunitoh H, Toyama K, et al. Association of the OGG1 -Ser326Cys polymorphism with lung adenocarcinoma risk. Cancer Sci 2006;97:724-8. [Crossref] [PubMed]
  110. Kohno T, Shinmura K, Tosaka M, et al. Genetic polymorphisms and alternative splicing of the hOGG1 gene, that is involved in the repair of 8-hydroxyguanine in damaged DNA. Oncogene 1998;16:3219-25. [Crossref] [PubMed]
  111. Lan Q, Mumford JL, Shen M, et al. Oxidative damage-related genes AKR1C3 and OGG1 modulate risks for lung cancer due to exposure to PAH-rich coal combustion emissions. Carcinogenesis 2004;25:2177. [Crossref] [PubMed]
  112. Liang G, Pu Y, Yin L. Rapid Detection of Single Nucleotide Polymorphisms Related with Lung Cancer Susceptibility of Chinese Population. Cancer Lett 2005;223:265. [Crossref] [PubMed]
  113. Liu CJ, Hsia TC, Tsai RY, et al. The joint effect of hOGG1 single nucleotide polymorphism and smoking habit on lung cancer in Taiwan. Anticancer Res 2010;30:4141. [PubMed]
  114. Loft S, Svoboda P, Kasai H, et al. Prospective study of 8-oxo-7,8-dihydro-2'-deoxyguanosine excretion and the risk of lung cancer. Carcinogenesis 2006;27:1245-50. [Crossref] [PubMed]
  115. Miyaishi A, Osawa K, Osawa Y, et al. MUTYH Gln324His gene polymorphism and genetic susceptibility for lung cancer in a Japanese population. J Exp Clin Cancer Res 2009;28:10. [Crossref] [PubMed]
  116. Okasaka T, Matsuo K, Suzuki T, et al. hOGG1 Ser326Cys polymorphism and risk of lung cancer by histological type. J Hum Genet 2009;54:739. [Crossref] [PubMed]
  117. Park J, Chen L, Tockman MS, et al. The human 8-oxoguanine DNA N-glycosylase 1 (hOGG1) DNA repair enzyme and its association with lung cancer risk. Pharmacogenetics 2004;14:103. [Crossref] [PubMed]
  118. Qian B, Zhang H, Zhang L, et al. Association of genetic polymorphisms in DNA repair pathway genes with non-small cell lung cancer risk. Lung Cancer 2011;73:138. [Crossref] [PubMed]
  119. Qin H, Zhu J, Zeng Y, et al. Aberrant promoter methylation of hOGG1 may be associated with increased risk of non-small cell lung cancer. Oncotarget 2017;8:8330-41. [PubMed]
  120. Sørensen M, Raaschou-Nielsen O, Hansen RD, et al. Interactions between the OGG1 Ser326Cys polymorphism and intake of fruit and vegetables in relation to lung cancer. Free Radic Res 2006;164:885-91. [Crossref] [PubMed]
  121. Sunaga N, Kohno T, Yanagitani N, et al. Contribution of the NQO1 and GSTT1 Polymorphisms to Lung Adenocarcinoma Susceptibility. Cancer Epidemiol Biomarkers Prev 2002;11:730-8. [PubMed]
  122. Wikman H, Risch A, Klimek F, et al. hOGG1 polymorphism and loss of heterozygosity (LOH): significance for lung cancer susceptibility in a caucasian population. Int J Cancer 2000;88:932-7. [Crossref] [PubMed]
  123. Cheng Z, Wang W, Song YN, et al. hOGG1, p53 genes, and smoking interactions are associated with the development of lung cancer. Asian Pacific J Cancer Prevention 2012;13:1803-8. [Crossref] [PubMed]
  124. Karahalil B, Emerce E, Koçer B, et al. The association of OGG1 Ser326Cys polymorphism and urinary 8-OHdG levels with lung cancer susceptibility: a hospital-based case-control study in Turkey. Arh Hig Rada Toksikol 2008;59:241-50. [Crossref] [PubMed]
  125. Le ML, Donlon T, Lumjones A, et al. Association of the hOGG1 Ser326Cys polymorphism with lung cancer risk. Cancer Epidemiol Biomarkers Prev 2002;11:409. [PubMed]
  126. Chang CH, Hsiao CF, Chang GC, et al. Interactive effect of cigarette smoking with human 8-oxoguanine DNA N-glycosylase 1 (hOGG1) polymorphisms on the risk of lung cancer: a case-control study in Taiwan. Am J Epidemiol 2009;170:695-702. [Crossref] [PubMed]
  127. Al-Tassan N, Eisen T, Maynard J, et al. Inherited variants in MYH are unlikely to contribute to the risk of lung carcinoma. Hum Genet 2004;114:207-10. [Crossref] [PubMed]
  128. Moher D, Liberati A, Tetzlaff J, et al. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 2009;6:e1000097. [Crossref] [PubMed]
  129. Wells GA, Shea BJ, O'Connell D, et al. The Newcastle–Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis. Appl Eng Agric 2012;18:727-34.
  130. de Souza MR, Rohr P, Kahl VFS, et al. The influence of polymorphisms of xenobiotic-metabolizing and DNA repair genes in DNA damage, telomere length and global DNA methylation evaluated in open-cast coal mining workers. Ecotoxicol Environ Saf 2020;189:109975. [Crossref] [PubMed]
  131. Zhang Y, Yang L, Kucherlapati M, et al. Global impact of somatic structural variation on the DNA methylome of human cancers. Genome Biol 2019;20:209. [Crossref] [PubMed]
  132. Lorenzo-Gonzalez M, Ruano-Ravina A, Torres-Duran M, et al. Residential radon, genetic polymorphisms in DNA damage and repair-related. Lung Cancer 2019;135:10-5. [Crossref] [PubMed]
  133. Degtyareva NP, Chen L, Mieczkowski P, et al. Chronic oxidative DNA damage due to DNA repair defects causes chromosomal instability in Saccharomyces cerevisiae. Mol Cell Biol 2008;28:5432-45. [Crossref] [PubMed]
  134. Shakeri M, Zakeri F, Changizi V, et al. Cytogenetic effects of radiation and genetic polymorphisms of the XRCC1 and XRCC3 repair genes in industrial radiographers. Radiat Environ Biophys 2019;58:247-55. [Crossref] [PubMed]
  135. Polo LM, Xu Y, Hornyak P, et al. Efficient Single-Strand Break Repair Requires Binding to Both Poly(ADP-Ribose) and DNA by the Central BRCT Domain of XRCC1. Cell Rep 2019;26:573-81.e5. [Crossref] [PubMed]
  136. Chen L, Zhuo D, Chen J, et al. XRCC1 polymorphisms and lung cancer risk in Caucasian populations: a meta-analysis. Int J Clin Exp Med 2015;8:14969-76. [PubMed]
  137. Vineis P, Manuguerra M, Kavvoura FK, et al. A field synopsis on low-penetrance variants in DNA repair genes and cancer susceptibility. J Natl Cancer Inst 2009;101:24-36. [Crossref] [PubMed]
  138. Huang G, Cai S, Wang W, et al. Association between XRCC1 and XRCC3 Polymorphisms with Lung Cancer Risk: A Meta-Analysis from Case-Control Studies. PLos One 2013;8:e68457. [Crossref] [PubMed]
  139. Liu ZJ, Martinez Cuesta S, van Delft P, et al. Sequencing abasic sites in DNA at single-nucleotide resolution. Nat Chem 2019;11:629-37. [Crossref] [PubMed]
  140. Kim JM, Yeo MK, Lim JS, et al. APEX1 Expression as a Potential Diagnostic Biomarker of Clear Cell Renal Cell Carcinoma and Hepatobiliary Carcinomas. J Clin Med 2019; [Crossref] [PubMed]
  141. Lu GS, Li M, Xu CX, et al. APE1 stimulates EGFR-TKI resistance by activating Akt signaling through a redox-dependent mechanism in lung adenocarcinoma. Cell Death Dis 2018;9:1111. [Crossref] [PubMed]
  142. Wang T, Wang H, Yang S, et al. Association of APEX1 and OGG1 gene polymorphisms with breast cancer risk among Han women in the Gansu Province of China. BMC Med Genet 2018;19:67. [Crossref] [PubMed]
  143. Kim H, Seo H, Park Y, et al. APEX1 Polymorphism and Mercaptopurine-Related Early Onset Neutropenia in Pediatric Acute Lymphoblastic Leukemia. Cancer Res Treat 2018;50:823-34. [Crossref] [PubMed]
  144. Xiao X, Yang Y, Ren Y, et al. rs1760944 Polymorphism in the APE1 Region is Associated with Risk and Prognosis of Osteosarcoma in the Chinese Han Population. Sci Rep 2017;7:9331. [Crossref] [PubMed]
  145. Ding G, Chen Y, Pan H, et al. Association between apurinic/apyrimidinic endonuclease 1 rs1760944 T>G polymorphism and susceptibility of cancer: a meta-analysis involving 21764 subjects. Biosci Rep 2019;39. [PubMed]
  146. Zhang X, Xin X, Zhang J, et al. Apurinic/apyrimidinic endonuclease 1 polymorphisms are associated with ovarian cancer susceptibility in a Chinese population. Int J Gynecol Cancer 2013;23:1393-9. [Crossref] [PubMed]
  147. Yuan H, Li H, Ma H, et al. Genetic polymorphisms in key DNA repair genes and risk of head and neck cancer in a Chinese population. Exp Ther Med 2012;3:719-24. [Crossref] [PubMed]
  148. Jin EH, Kim J, Lee SI, et al. Association between polymorphisms in APE1 and XRCC1 and the risk of gastric cancer in Korean population. Int J Clin Exp Med 2015;8:11484. [PubMed]
  149. Luo D, Gao Y, Wang S, et al. Genetic variation in PLCE1 is associated with gastric cancer survival in a Chinese population. J Gastroenterol 2011;46:1260. [Crossref] [PubMed]
  150. Dai ZJ, Wang XJ, Kang AJ, et al. Association between APE1 Single Nucleotide Polymorphism (rs1760944) and Cancer Risk: a Meta-Analysis Based on 6,419 Cancer Cases and 6,781 Case-free Controls. J Cancer 2014;5:253-9. [Crossref] [PubMed]
  151. Abduljaleel Z. Structural and Functional Analysis of human lung cancer risk associated hOGG1 variant Ser326Cys in DNA repair gene by molecular dynamics simulation. Noncoding RNA Res 2019;4:109-19. [Crossref] [PubMed]
Cite this article as: Liu S, Xiao Y, Hu C, Li M. Associations between polymorphisms in genes of base excision repair pathway and lung cancer risk. Transl Cancer Res 2020;9(4):2780-2800. doi: 10.21037/tcr.2020.02.44

Article Options

Download Citation

Share