Imaging, Diagnosis, Prognosis

Haplotypes in Matrix Cluster on 11q22 Contribute to the Risk of Lung Cancer Development andProgression Tong Sun,1Ya n g Ga o, 3 Wen Tan,1Sufang Ma,3 Xuemei Zhang,1Yonggang Wang,2 Qingrun Zhang,3 Yongli Guo,1Dan Zhao,1Changqing Zeng,3 and Dongxin Lin1

Abstract Purpose: Matrix (MMP) play important roles in cancer development and single nucleotide polymorphisms (SNP) in some MMP were shown to confer susceptibility to certain cancers.This study examined the association between genotypes and haplotypes in the MMP1-MMP3 -MMP12 gene cluster and risk of lung cancer development and metastasis. Experimental Design: A two-stage investigation was conducted. First, 35 SNPs covering these genes were selected and validated in 190 patients and 190 controls. Twenty-two validated SNPs were then analyzed in an entire case-control panel consisting of 711patients and 716 controls. Associations with the risk of lung cancer were estimated by logistic regression. Results: The investigated MMP gene region could be partitioned into two major haplotype blocks. One common haplotype in the block composed of major part of MMP1 transcription region was significantly associated with increased risk for the development [odds ratio (OR), 1.35; 95% confidence interval (95% CI), 1.11-1.63; P = 0.01; permutated P =0.134]anddistant metastasis of lung cancer (ORs for stage IV versus stages I-III,1.67; 95% CI,1.12-2.50; P =0.009; permutated P = 0.048) and the other showed a protective effect against metastasis (ORs for stage IV versus stages I-III, 0.22; 95% CI, 0.07-0.62; P = 0.001;permutated P = 0.011). Another common haplotype in the block across MMP3 was significantly associated with decreased risk for developing lung cancer (OR, 0.71;95% CI, 0.59-0.86; P = 0.003; permutated P =0.027). Conclusions: The observed multiple cancer-associated genetic variants suggested that the MMP1-MMP3-MMP12 gene cluster plays important roles in lung cancer development and progression.

Discovery and application of biomarkers that incorporate which are thought to be attractive biomarkers in cancer risk with traditional cancer diagnosis, staging, and prognosis could assessment, screening, staging, or grading (2). However, the largely help to improve early diagnosis and patient care (1). application of individual SNPs has been limited thus far With the completion of project, millions of because they are of low penetrance and the effect of risk single nucleotide polymorphisms (SNP) have been identified, alleles is relatively difficult to identify (2, 3). To date, most studies focus on ‘‘functional’’ SNPs, but the number of SNPs with clear function is limited. Therefore, how to incorporate SNPs in studies of cancer predisposition and prognosis and how to find out the true association are still challenging tasks Authors’Affiliations: Departments of1Etiology and Carcinogenesis and 2Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and (2–5). Recently, haplotype-based association study has been Peking Union Medical College; 3Beijing Genomics Institute, Chinese Academy of proposed as a powerful and comprehensive approach to Sciences, Beijing, China identify causal genetic variation underlying complex diseases Received 2/27/06; revised 8/12/06; accepted 9/14/06. (6, 7). Grant support: State Key Basic Research Program grant 2004CB518701 (D. Lin) Lung cancer is the leading cause of cancer-related death all and 2002CB512902 (W. Tan), National ‘‘863’’ High Technology Projects grant 2002BA711A06 (D. Lin) and 2002AA232031 (C. Zeng), the Program for New over the world. In many countries, including China, the Century Excellent Talents in University (W. Tan), and the Hundred Talents Program incidence and mortality rates of lung cancer have increased of Chinese Academy of Sciences (C. Zeng). rapidly in recent years. Despite significant advances have been The costs of publication of this article were defrayed in part by the payment of page made in diagnosis and treatment in the last decades, the advertisement charges. This article must therefore be hereby marked in accordance prognosis of lung cancer remains rather poor, with a 5-year with 18 U.S.C. Section 1734 solely to indicate this fact. Note: T. Sun,Y. Gao, and W. Tan contributed equally to this work. overall survival rate <10% (8). Metastatic disease eliminates Requests for reprints: Dongxin Lin, Department of Etiology and Carcinogenesis, possibility of surgical cure of lung cancer. Unlike some other Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing cancer, lung cancer lacks specific biomarkers for early detection 100021,China.E-mail:dlin@ public.bta.net.cn or Changqing Zeng, Beijing and prognosis determination at diagnosis, although many Genomics Institute, Chinese Academy of Sciences, Beijing 101300, China. E-mail: [email protected]. efforts have been made to discover potential biomarkers for F 2006 American Association for Cancer Research. lung cancer risk assessment and clinical outcome prediction doi:10.1158/1078-0432.CCR-06-0464 (9–11).

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Matrix metalloproteinases (MMP), a family of current smokers or ex-smokers if they smoked up to 1 year before the degrading and basement membrane date of cancer diagnosis or if they smoked up to 1 year before the date barriers, are not only involved in multiple steps of cancer of the interview for control subjects, otherwise were defined as development but also play important roles in cancer metas- nonsmokers. Information was collected on the number of cigarettes smoked daily, the age at which the subjects started smoking, and the tasis (12). Molecular epidemiologic studies have shown MMPs age at which ex-smokers stopped smoking. Because only 24 patients associations between genetic polymorphisms in and and 38 controls were ex-smokers, they were combined with current cancer susceptibility or prognosis, including cancers of the smokers for analysis. This study was approved by the Institutional lung (13–17), esophagus (18, 19), colorectum (20–22), and Review Board of the Chinese Academy of Medical Sciences Cancer cervix (23, 24). However, these association studies were Institute. limited to few SNPs or constructed haplotypes from two or Selection of candidate SNPs. SNPs across the 84.5-kb region three polymorphic sites. A cluster of eight MMP genes, spanning MMP1-MMP3-MMP12 loci on chromosome 11q22, from including MMP20, MMP27, MMP8, MMP10, MMP1, MMP3, 0.1 kb upstream of MMP12 transcriptional region to 7.6 kb MMP12 MMP13 downstream of MMP1 transcriptional region, were surveyed in SNP , and , is defined on chromosome 11q 22.3 4 5 (25). The aberration of this chromosome region has been database and Celera Discovery System .Wealsoreferredto International HapMap Project (reference) for genotyped SNPs in associated with risk of primary lung cancer and its metastatic Han Chinese population6. SNPs with a minor allele frequency z5% disease (26, 27). Specifically, the expression or activation of were selected and those located in coding regions were included as MMP1, MMP3, and MMP12 in this region showed significant many as possible. We selected SNPs every 1 to 3 kb across these gene correlation with advanced stages of lung cancer and poor loci to ensure a high density of markers and to provide adequate patient survival (28–31). MMP1 and MMP12 also play critical characterization of haplotype diversity within previously defined LD role in smoke-induced lung injury (32, 33). In addition, blocks. SNPs were selected in an iterative manner until reaching four functional SNPs in MMP1 and MMP3 have been associated to seven common SNPs (frequency, z5%) per LD block. The distance with susceptibility to lung cancer (13, 14, 16). These findings between adjacent markers was <5 kb, except for the MMP12 locus warrant more powerful and comprehensive studies to explore where the last two intervals between markers were 9.2 and 11.9 kb, MMP1 the relationship between genetic variations in MMPs and lung respectively. Specifically, we selected 10 SNPs in the locus (8.2-kb transcript region), 9 SNPs in the MMP3 locus (7.8-kb cancer. transcript region), and 2 SNPs in the MMP12 locus (12.3-kb In this study, we examined linkage equilibrium (LD) and transcript region). In addition, 14 SNPs located beyond the MMP1- haplotype structure of the genomic region across boundaries of these gene loci were also selected, totaling up to 35 MMP3-MMP12 loci on chromosome 11q22 and assessed the SNPs as candidate markers. These SNP markers cover an 84.5-kb roles of genotypes and haplotypes in risk for the development region in chromosome 11q22 with the average resolution of one SNP and metastasis of lung cancer. per 2.4 kb. SNP analysis and validation. SNPs were typed by the MassARRAY system (Sequenom, San Diego, CA) as described (36). To ensure the typing quality, multiple positive and negative samples were incorpo- Materials andMethods rated into every genotyping plate and genotyping data of all duplicate samples were consistent. The laboratory persons were blinded to Subject selection. This study consisted of 711 primary lung cancer sample arrangement during the process. In our two-stage study design, patients and 716 controls and all subjects were ethnical Han Chinese. the first stage was to validate above described SNPs in our study The subject characteristics have been described previously (15, 17). population. All the selected 35 SNPs were first typed among 190 Briefly, eligible patients were consecutively recruited between January controls and 190 patients. Consequently, we removed 10 SNPs that 1997 and November 2001 at the Cancer Hospital, Chinese Academy of either were monomorphic or had the minor allele frequency <2% in Medical Sciences (Beijing, China). Because we examined the relation- our study population and 3 SNPs where the successful rate for ship between MMP polymorphisms and lung cancer staging, surgically genotyping was <90% in these 380 DNA samples. Therefore, a total of resectable patients (91%) were mostly recruited, which allowed us to 22 SNPs with the minor allele frequency z2% and call rate >90% were obtain accurate tumor-node-metastasis data and histologic classifica- used for the second-stage study. The observed genotype distributions of tion at the time of diagnosis. The response rate for patients was 93%. these 22 SNPs did not differ from those expected from Hardy-Weinberg The exclusion criteria included previous cancer, metastasized cancer equilibrium in controls. from other organs, and previous radiotherapy or chemotherapy. The LD block determination and haplotype construction. LD between the pathologic stages were determined according to American Joint 22 SNPs used in haplotype analysis was measured by pairwise D¶ Committee on Cancer staging system (34) and tumor grade was statistic. The structure of LD block was examined using the method of classified into low (well differentiated), intermediate (moderately Gabriel et al. (37), using the 80% confidence bounds of D¶ to define differentiated), or high grade (poorly differentiated) according to the sites of historical recombination between SNPs. Block structure was WHO grade classification (35). Controls were cancer-free individuals assessed using SNPs with the minor allele frequency z5%. Haplotypes selected from a nutritional survey consisted of 2,500 individuals, were constructed from genotype data in the full-size case-control panel which was conducted in the same region during the same period as within blocks by using an accelerated expectation-maximization patients were collected. The selection criteria included no individual algorithm method with Haploview 3.2 software (38). Briefly, this history of cancer and frequency matching to patients on sex and age method creates highly accurate population frequency estimates of the (F5 years). The participation response rate for controls was 83%. Of phased haplotypes based on the maximum likelihood as determined the 770 patients and 777 controls who participated in the previous from unphased input (39). Haplotypes in the two LD blocks were study (15), only 711 patients and 716 controls were successfully reconstructed by either all genotyped loci or haplotype-tagging SNPs genotyped in this study because DNA samples of the rest of the subjects were no longer available. At recruitment, written informed consent was obtained from each subject and each participant was then 4 http://www.ncbi.nlm.nih.gov/SNP. interviewed to collect detailed information on demographic character- 5 http://www.allsnps.com/snpbrower. istics and lifetime history of tobacco use. Subjects were considered 6 http://www.hapmap.org.

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(htSNP). The haplotype frequencies instead of individual haplotype Results phase among controls, total patients, patients with different tumor stages, or patients with other clinical features were estimated separately Subject characteristics. As shown in Table 1, there was no for comparison. statistically significant difference in the distribution of sex and Selection of htSNPs. The htSNPs were selected with Haploview 3.2 software on a block-by-block basis using the method described by age between patients and controls. However, significantly more 2 Carlson et al. (40) with the sample size inflation factor Rh z 0.8. We smokers were present among patients compared with controls 2 P also calculated the multivariate squared correlation, Rs, an index (63.4% versus 52.0%; < 0.001). In addition, patients had a exploiting the multivariate correlation between measured and unmea- higher value of pack-years than controls; 30.4% of smokers R2 sured SNPs in a region of high LD. The s values for the two main among patients smoked >41 pack-years compared with 19.9% haplotype block were 0.980 and 0.972, respectively, indicating that our among controls (P < 0.001). Among patients, 279 (39.3%) selection of htSNPs provided a good prediction of other unmeasured were classified as squamous cell carcinoma, 217 (30.5%) as SNPs and an optimal prediction of haplotypes in the cl0uster of the adenocarcinoma, 29 (4.1%) as large cell carcinoma, 84 MMP genes. Statistical analysis. Two-sided m2 test was done to compare (11.8%) as small cell carcinoma, and 60 (8.5%) as other n differences in allele frequencies of each locus between cases and types, including bronchioalveolar carcinoma ( = 12) and controls. Logistic regression was used to analyze the association undifferentiated cancer (n = 8). Forty-two patients (5.8%) had between a single locus and lung cancer risk, adjusted for sex, age, histologic type–unknown lung cancer. Of the 711 patients, and smoking status. These statistical analyses were done with Statistical 210 (29.5%) had stage I lung cancer, 157 (22.1%) had stage II Analysis System software (version 8.0; SAS Institute, Cary, NC) and lung cancer, 212 (29.8%) had stage III lung cancer, 71 (10.0%) Haploview 3.2 software (38) separately. To assess significance, we did had stage IV lung cancer, and 61 (8.6%) had stage-unknown both Bonferroni correction (41) and permutation procedure (100 and disease. About tumor grade, 79 (11.1%) patients were classified 1,000 tests, respectively) to correct the P value of single-locus into well-differentiated lung cancer (low grade) and 341 association results. The haplotype analyses were done when its frequency was >5% in both all-loci-constructed and htSNP-constructed (48.0%) and 213 (29.9%) were classified into moderately haplotype estimates. We also used Haplo.stats (42, 43) to assess the differentiated (intermediate grade) or poorly differentiated relative effects of haplotypes and adjusted for sex, age, and smoking (high grade) lung cancer, respectively, whereas data for the rest status. of the 78 patients (11.0%) were unavailable.

Table 1. Distributions of selected characteristics by case-control status

Variable Patients (n = 711), no. (%) Controls (n = 716), no. (%) P * Sex Male 502 (70.6) 503 (70.3) 0.884 Female 209 (29.4) 213 (29.7) Age V40 53 (7.4) 51 (7.1) 0.899 41-50 132 (18.6) 141 (19.7) 51-60 229 (32.2) 231 (32.3) 61-70 248 (34.9) 252 (35.2) >70 49 (6.9) 41 (5.7) Smoking status Nonsmoker 260 (36.6) 344 (48.0) <0.0001 Smoker 451 (63.4) 372 (52.0) Smoking levels (pack-years) V20 131 (29.0) 163 (43.8) <0.0001 21-40 183 (40.6) 135 (36.3) >41 137 (30.4) 74 (19.9) Tumor stage at diagnosis I 210 (29.5) II 157 (22.1) III 212 (29.8) IV 71 (10.0) Unknown 61 (8.6) Histologic type Squamous cell carcinoma 279 (39.3) Adenocarcinoma 217 (30.5) Large cell carcinoma 29 (4.1) Small cell carcinoma 84(11.8) Others 60 (8.5) Unknown 42 (5.8) Tumor grade Low 79 (11.1) Intermediate 341 (48.0) High 213 (29.9) Unknown 78 (11.0)

*Two-sided m2 test.

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LD and haplotype structure of the MMP1-MMP3-MMP12 into the blocks. The LD plot for all samples is shown in Fig. 1B. genomic region. We assembled a high-density SNP map across We observed that within each block, the haplotype diversity the MMP1-MMP3-MMP12 genomic region on 11q22 to was low in our study population. For block 1, only four determine LD block and haplotype structure (Fig. 1A); common haplotypes were observed, which could be distin- 35 SNPs were selected using an iterative strategy (see Materials guished by three htSNPs and represented 99.9% subjects. Block and Methods) and the average distance between SNPs across 2 is much larger than block 1, but it also contained only four the 84.5-kb region was 2.4 kb. We determined this MMP gene common haplotypes that represented 97.8% subjects and could cluster region to contain two LD blocks (Fig. 1B). Block1 (SNPs be distinguished by three htSNPs. 1-4) covered 5.0 kb, spanning exons 5 to 10 and 0.2-kb Associations between individual SNPs and lung cancer 3¶-untranscriptional region of MMP1; block 2 (SNPs 7-19) risk. The allelic frequencies of 22 second-stage SNPs in the spanned 35.2 kb, encompassing the whole locus, 0.3 kb three MMP gene loci among patients and controls are shown in upstream, and 27.7 kb downstream region of MMP3. The Table 2. Among the 22 SNPs, only 5 had allelic frequency that distance between two blocks was 12.7 kb. There was a 31.0-kb differed significantly between patients and controls. In the region around the MMP12 locus that could not be included MMP1 locus, risk allelic frequencies of rs7125062, rs2075847,

Fig. 1. SNPs in the region of MMP1-MMP3-MMP12 gene cluster located in chromosome 11q22. A, MMP1-MMP3- MMP12 gene structure.White boxes, coding regions; black boxes, untranslated regions; arrows, transcription start sites. .,rs numbers denied in stage II study because the successful genotyping rate was <90% in stage I study; !, rs numbers that are htSNPs; *, rs numbers that are loci where the minor allele frequencies were <10 %. B, diagram of block structure of MMP1- MMP3-MMP12 in chromosome 11q22 generated by using Haploview. LD plots were identified by strong LD. Depth of gray color, computed pairwise D¶; deeper gray, higher D¶ value.The selected htSNPs and estimated haplotype frequencies in two major haplotype blocks of MMP1-MMP3- MMP12 gene cluster were shown. Marker numbers along with a tick beneath above haplotypes are htSNPs.The frequency of each haplotype within a block is to the right of the haplotype.The thickness of the lines connecting the haplotypes across blocks represents the relative frequency [i.e., high (thick) versus low (thin) with which a given haplotype is associated with the haplotype in the other block].

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Table 2. Allele frequencies of 22 second-stage SNPs in three MMP gene loci among 711 patients and 716 controls

SNP* Relative position Allelec Location Positionb Risk allele No. alleles (%) P x P k Patients Controls MMP1 locus rs2071231 +7614T !G Intron 102198993 T 1,130 (79.5) 1,118 (79.0) 0.602 1.000 rs7125062 +5387 C!T Intron 102201220 T 458 (32.3) 407 (28.7) 0.035 0.374 rs491152 +2847 C!T Intron 102203760 C 1,263 (88.8) 1,257 (88.1) 0.560 1.000 rs470558 +2574 G!A Coding-synon 102204033 T 1,258 (88.7) 1,253 (88.2) 0.677 1.000 rs2075847 934T !C Promoter 102207541 T 1,008 (73.1) 912 (69.5) 0.037 0.385 rs470206 2288 G!A Promoter 102208895 A 221 (15.7) 185 (12.9) 0.038 0.407 rs1144396 10162 C!A 102216769 A 491 (34.9) 490 (34.7) 0.895 1.000 Gap between MMP1 and MMP3 loci rs529381 A!G 102218554 G 592 (41.9) 585 (41.6) 0.848 1.000 rs1144397 G!T 102220002 G 900 (63.4) 864 (62.2) 0.536 1.000 rs564018 C!T 102229136 T 114(8.2) 96 (6.7) 0.126 0.845 rs495366 A!G 102232825 G 609 (43.2) 598 (41.8) 0.449 1.000 MMP3 locus rs473238 +14421 C!T3¶-UTR 102238077 T 95 (6.9) 75 (5.4) 0.226 0.965 rs3758852 +10420 G!C3¶-UTR 102242078 G 1,369 (98.2) 1,377 (97.8) 0.473 1.000 rs575027 +6867 G!A Intron 102245631 A 492 (34.8) 485 (34.0) 0.655 1.000 rs520540 +5356 G!A Coding-synon 102247142 A 387 (32.6) 386 (32.1) 0.727 1.000 rs602128 +1316 C!T Coding-synon 102251182 T 406 (33.1) 395 (31.9) 0.530 1.000 rs679620 +1161 G!A Coding-nonsynon 102251337 A 501 (35.3) 495 (34.8) 0.811 1.000 rs678815 +1004G !C Intron 102251494 C 495 (35.3) 476 (34.2) 0.548 1.000 rs522616 267 A!G Promoter 102252765 G 561 (39.8) 505 (35.3) 0.013 0.168 rs615098 5897 C!A Promoter 102258395 C 1,213 (87.5) 1,183 (85.0) 0.058 0.551 rs586701 9949 T!G 102262447 T 1,255 (88.7) 1,190 (85.0) 0.003 0.051 MMP12 locus rs2276109 82 A!G Promoter 102283508 A 1,370 (98.0) 1,377 (97.8) 0.753 1.000

Abbreviation: UTR, untranslated region. *According to National Center for Biotechnology Information SNP database rs number. cObserved major allele!minor allele. bPositions are from National Center for Biotechnology Information Build 34. xTwo-sided m2 test. kAfter 1,000 permutation tests.

and rs470206 were higher in patients than in controls from haplotype 2a only in the maker of rs522616, was (P = 0.035, 0.037, and 0.038, respectively), with the odds significantly less prevalent among patients compared with ratio (OR) being 1.22 [95% confidence interval (95% CI), controls (16% versus 23%; P = 0.000049 and turned into 1.00-1.51], 1.16 (95% CI, 0.86-1.57), or 1.21 (95% CI, 0.95- P = 0.004 after 1,000 permutation tests). Multivariate logistic 1.54), respectively. The allelic frequencies of both rs522616 regression analysis showed that haplotype 2c carriers were at and rs586701, which are located in the promoter region of a decreased risk of developing lung cancer compared with MMP3, seemed to be significantly higher in patients than in noncarriers (OR, 0.68; 95% CI, 0.56-0.83). In block 1, controls (P = 0.013 and 0.003). Subjects carrying at least one haplotype 1c had a frequency that was significantly different risk allele of corresponding polymorphisms had an OR of 1.21 between patients and controls (21% versus 17%; P = 0.01 and (95% CI, 0.99-1.51) or 1.57 (95% CI, 0.74-3.37). However, turned into P = 0.134 after 1,000 permutation tests). Subjects after Bonferroni correction or permutation test, all P values for with haplotype 1c had an increased risk of developing lung these differences between patients and controls increased cancer (OR, 1.28; 95% CI, 1.06-1.56) compared with those beyond the significant level of 0.05, despite that the without haplotype 1c. Because limited interblock recombina- rs586701 had a permutated P value of 0.051 after 1,000 tests. tion may result in long-range LD, we also evaluated whether Associations between haplotypes and lung cancer risk. We there was long-range haplotype composed of a subset of the examined the difference in frequency distribution of all common block-specific haplotypes in block 1 and block 2 and common haplotypes between patients and controls (Table 3) the potential effect of the whole candidate region. Unfortu- and found a significant haplotype effect of block 2 (P = 0.0008) nately, we did not find any common haplotypes that were more but not block 1 (P = 0.080) on lung cancer risk (Table 3). strongly associated with lung cancer, most likely due to a Within block 2, which spans the whole transcript region of relatively high recombination rate between these two blocks MMP3, we observed two haplotypes (2a and 2c) that because the D¶ value between them was 0.13. differentially distributed in patients and controls. Haplotype Associations between haplotypes and lung cancer disease 2a seemed to be more prevalent among patients than among status. We additionally evaluated whether there was an controls (40% versus 35%; P = 0.010 and turned into P = 0.140 association between SNPs in this MMP gene cluster and lung after 1,000 permutation tests), whereas haplotype 2c, differing cancer disease status at the time of diagnosis (Table 4). The

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Table 3. Haplotype frequencies of MMP1-MMP3-MMP12 loci in 711 patients and 716 controls

c Haplotype All subjects Controls Patients P * P Block 1 1a: TCCG 0.49 0.50 0.48 0.162 0.903 1b: GCCG 0.21 0.21 0.20 0.560 1.000 1c: TTCGb 0.19 0.17 0.21 0.010 0.134 1d: TTTA 0.11 0.12 0.11 0.812 1.000 Overall 0.080 Block 2 2a: CACACGGCGGG 0.37 0.35 0.40 0.010 0.140 2b: AGCGCAATACA 0.340.340.340.997 1.000 2c: CACACGGCGGAx 0.20 0.23 0.16 0.000049 0.004 2d: CGTGTGGCGGA 0.07 0.07 0.08 0.216 0.958 Overall 0.008 MMP1-MMP3-MMP12 TCCGGCACACGGGCGGGCTA 0.15 0.15 0.16 0.316 0.148 TCCGGAGCGCGAATACACTA 0.140.16 0.13 0.059 0.689 GCCGGAGCGCGAATACACTA 0.08 0.09 0.08 0.078 0.793 TCCGGCACACGGGCGGACTA 0.07 0.09 0.06 0.0040.04 8 TTCGGCACACGGGCGGGCTA 0.06 0.06 0.07 0.512 1.000 GCCGGCACACGGGCGGGCTA 0.06 0.06 0.06 0.827 1.000 TTCGGAGCGCGAATACACTA 0.05 0.040.06 0.026 0.361 TCCGACACACGGGCGGGCTA 0.03 0.03 0.03 0.770 1.000 TTTAACACACGGGCGGGCTA 0.02 0.02 0.03 0.155 0.974 TCCGGCACACGGGCGGAAGA 0.02 0.03 0.01 <0.0001 0.002 TTCGGCACACGGGCGGAAGA 0.02 0.03 0.01 <0.0001 0.002 TTTAGAGCGCGAATACACTA 0.02 0.02 0.02 0.373 1.000 TTTAACGTGTGGGCGGACTA 0.02 0.02 0.02 0.1840.991 TTTAGCACACGGGCGGGCTA 0.02 0.02 0.02 0.408 1.000 TTCGGCACACGGGCGGACGA 0.02 0.01 0.03 0.001 0.014 TCCGACGTGTGGGCGGACTA 0.02 0.01 0.02 0.137 0.961 TCCGGAGCGCGAATACAATA 0.01 0.01 0.02 0.002 0.024 TTCGGCACACGGGCGGACTA 0.01 0.01 0.02 0.470 1.000 Overall 0.843

*Two-sided m2 test, each haplotype compared with all other haplotypes. cAfter 1,000 permutation tests. bOR for carriers versus noncarriers, 1.28 (95% CI, 1.06-1.56). x OR for carriers versus noncarriers, 0.68 (95% CI, 0.56-0.83).

increased risk for distant metastasis of lung cancer seemed to be using haplotypes reconstructed with the three htSNPs in each associated with haplotype 1c in block 1. The estimated LD block (Table 5) were very similar to those obtained by using frequency of haplotype 1c among patients with distant haplotypes constructed with all second-stage SNPs (Tables 3 metastasis of lung cancer (stage IV) was 30%, which was and 4). Specifically, the frequencies of the haplotypes con- significantly higher than that among patients with stage III structed by htSNPs or all SNPs among patients, controls, and (23%), stage II (21%), or stage I (18%) lung cancer (P = 0.009; patients with different disease status were almost the same Ptrend = 0.042). Haplotype 1c carriers had an OR of 1.66 (95% and the haplotypes 1c and 1d in block 1 and haplotype 2c in CI, 1.11-2.48) for developing distant metastasis of lung cancer block 2 constructed with htSNPs remained to be significantly compared with noncarriers. In contrast with haplotype 1c, associated with lung cancer development or metastasis, haplotype 1d showed a protective effect against lung cancer respectively. These results indicate that the htSNPs represented progression. Among stage IV patients, the estimated frequency well all SNPs and may serve as simple markers. of haplotype 1d was 3%, which was significantly lower than Additional analysis with stratification of lung cancer those among stage I to III patients (10-13%; P = 0.001). subtypes using both all SNPs and htSNP-constructed haplo- Patients carrying haplotype 1d had an OR of 0.22 (95% CI, types revealed that the major histologic types did not exhibit 0.07-0.62) for developing distant metastasis of lung cancer heterogeneity in their relation to the genes studied (data not compared with noncarriers. However, we did not observe any shown). We also examined the associations of these SNPs and significant association between common haplotypes in block 2 haplotypes with lung cancer grade but the results were negative and lung cancer disease status. (data not shown). Associations between tagging SNP-constructed haplotypes and lung cancer risk. To explore the minimum SNPs that might Discussion represent the cancer-related haplotypes, the associations between SNPs in the MMP genes and risk of lung cancer In this study, we selected 35 SNPs in the region across development and metastasis were investigated using htSNP- MMP1-MMP3-MMP12 genes on chromosome 11q22.3 and constructed haplotypes. We found that the results obtained by examined their association with the development and disease

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Table 4. Frequency distributions of constructed haplotypes in 711 patients with different disease stage at the time of diagnosis

Haplotype Total patients Stage I Stage II Stage III Stage IV P * Block 1 1a: TCCG 0.48 0.48 0.47 0.51 0.51 0.681 1b: GCCG 0.20 0.240.19 0.13 0.16 0.327 1c: TTCGc 0.21 0.18 0.21 0.23 0.30 0.009 1d: TTTAb 0.11 0.10 0.13 0.13 0.03 0.001 Block 2 2a: CACACGGCGGG 0.40 0.39 0.44 0.38 0.43 0.473 2b: AGCGCAATACA 0.340.35 0.29 0.33 0.38 0.198 2c: CACACGGCGGA 0.16 0.16 0.17 0.19 0.12 0.095 2d: CGTGTGGCGGA 0.08 0.08 0.08 0.08 0.05 0.190

*Two-sided m2 test, stage IV versus stages I to III. cOR for stage IV versus stages I to III, 1.66 (95% CI, 1.11-2.48). bOR for stage IV versus stages I to III, 0.22 (95% CI, 0.07-0.62). status of lung cancer in a Chinese population. Two haplotypes population. Conflicting results also exist for the MMP3 1171 (1c and 1d) in the LD block composed of major part of MMP1 5A>6A polymorphism. Su et al. (44) reported recently a case- were identified to be significantly associated with risk of lung control study using MMP1 1607 1G>2G, MMP3 1171 cancer development and advanced disease status. We also 5A>6A, and MMP12 82A>G (rs2276109) and 1082A>G found a haplotype (2c) in the LD block across MMP3 that was (rs652438) SNPs as markers and observed an increased risk strongly associated with decreased risk of lung cancer. We among never smokers related to the MMP3 6A/6A genotype showed that as few as three htSNPs in each LD block could well and associated haplotypes, which is inconsistent with previous represent all SNPs to construct haplotypes that link to the study showing the 5A/5A genotype as risk genotype (14). disease. To our knowledge, this is the first fine-mapping These conflicting results suggest that the selected SNPs in the association study to investigate the effect of inherited variations previous studies may not be efficient markers, and gene-based in this genomic region on lung cancer development and approach instead of individual SNP-based approach should be progression. used because SNPs having opposite function may concomi- Previous studies showed that MMP1 1607 1G>2G tantly exist in a gene. By using the strategy of LD-tagging SNPs, (rs1799750) and MMP3 1171 5A>6A (rs3025058) SNPs we found that it was specific haplotypes but not an individual are associated with risk of developing lung cancer (13, 14, 16). SNP in these MMPs that play a significant role in lung cancer. However, the results are conflicting about which allele is risk In addition, we identified a haplotype profile for lung cancer allele. Zhu et al. (13) reported an increased risk associated risk in Chinese that is different from previous study in with the MMP1 2G allele, but Su et al. (16) reported an overall Caucasians (16, 44). Although we did not analyze the nonassociation for this SNP despite a positive association was ‘‘functional’’ MMP1 1607 1G>2G and MMP3 1171 observed in stratified analyses. In contrast, Fang et al. (14) 5A>6A SNPs, we found that the MMP1 1607 SNP was not showed a null association with lung cancer risk in a Chinese located in haplotype block 1. Furthermore, we found that the

Table 5. Frequency distributions of tagging SNP-constructed haplotypes in 711 patients and 716 controls and different disease stages

Haplotype All subjects Controls Patients P * Stage I Stage II Stage III Stage IV P c Block 1 1a: TCG 0.49 0.50 0.47 0.684 0.47 0.47 0.51 0.51 0.511 1b: GCG 0.21 0.21 0.20 0.997 0.240.19 0.13 0.16 0.327 1c: TTGb 0.19 0.17 0.21 0.018 0.18 0.21 0.23 0.30 0.009 1d: TTAx 0.11 0.12 0.11 0.972 0.10 0.13 0.13 0.03 0.001 Block 2 2a: CAG 0.37 0.35 0.40 0.165 0.39 0.44 0.38 0.43 0.473 2b: CGA 0.340.35 0.35 1.000 0.36 0.30 0.340.39 0.153 2c: CAAk 0.20 0.23 0.18 0.003 0.16 0.18 0.20 0.12 0.066 2d: TGA 0.07 0.07 0.07 0.952 0.08 0.08 0.08 0.040.088

*Case-control comparison after 1,000 permutation tests. cTwo-sided m2 test, stage IV versus stages I to III. bORs for developing lung cancer, 1.35 (95% CI, 1.11-1.63) and for stage IV versus stages I to III, 1.67 (95% CI, 1.12-2.50; P = 0.048 after 1,000 permutation tests). x OR for stage IV versus stages I to III, 0.22 (95% CI, 0.07-0.62; P = 0.011 after 1,000 permutation tests). k OR for developing lung cancer, 0.71 (95% CI, 0.59-0.86; P = 0.027 after 1,000 permutation tests).

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MMP1 1607 and MMP3 1612 SNPs were in weak LD and expensive than htSNP approach, our approach holds two were not in the same LD block. Therefore, the haplotypes noticeable advantages. First, with our approach, SNPs in the constructed in previous studies (14, 16) based on the selected region between LD blocks would not be left out. It has been functional SNPs may introduce inherited errors in the analysis shown that such region is abundant in human genome and and thus may not accurately reflect the association between might encompass many essential genetic loci (37, 55). In this thetruecausalgeneticvariantsandthedisease.These study, we observed a single locus (rs586701) located beyond observations warrant further studies to find out the true the two major blocks that was associated with lung cancer risk, functional variants. suggesting a need of more subtle analysis of the surround Another interesting result in the present study is that we region. Second, with our approach, high-density markers would found haplotype 1c, which is composed of unique MMP1 apply much finer map to pinpoint the disease-causal variants variants, was not only associated with increased risk of after association analysis, which is important for seeking developing lung cancer but also strongly associated with minimum number of SNPs as genetic markers for practical distant metastasis of the cancer. This observation is biologi- applications, such as clinical genotyping. In this study, we cally plausible because overexpression of MMP1, which is showed that as few as three htSNPs in each LD block could well capable of degrading interstitial type collagens resulting in represent all SNPs to construct haplotypes that link to the expanding growth and migration of cancer cells (12, 45), disease. has been correlated with tumor invasion and metastasis As the International Hapmap Project advances, more and (28, 46–50). In addition, the MMP1 1607 1G>2G SNP more information on allele frequencies and LD status of SNPs has been associated with the invasion, metastasis, and poor is available, which benefits the hypothesis-driven association prognosis of many other types of cancer (20, 22–24, 51, 52). studies for SNP selection in candidate genes or candidate For lung cancer, Fang et al. (14) reported recently that the genomic region (56). Although genotyping data for chromo- MMP3 1171 5A/5A genotype and the MMP1 1G-MMP3 5A some 11 have been completed now, we could not obtain whole haplotype were associated with increased risk of lymphatic data from Chinese population for SNP selection in the time metastasis of lung cancer. However, we found that the when this study was launched. SNPs directly chosen from haplotype in the block across MMP1 but not MMP3 was public databases tend to be fallible because a large number of associated with metastasis of the cancer. The distance between SNPs in the databases are not validated and often display MMP1 1607 and MMP3 1171 sites is f45.5 kb and, due frequencies that are dependent on ethnicity. In the present to a weak LD, these two SNPs are not located in the same LD study, 28.6% (10 of 35) of initially chosen SNPs from the SNP block. On the other hand, the risk variant (haplotype 1c) we database were verified to be monomorphic or <2% in our study identified is unlikely to be in LD with the MMP1 1607 SNP population. Therefore, even after the completion of the because this polymorphism is not located in haplotype block Hapmap Project, two-stage study design would still be 1 and LD between block 1 and MMP1 1607 site is low. necessary because limited population sizes have been geno- These results suggested that there may be functional variant(s) typed in the project (7, 56). other than 1607 1G>2G in MMP1 that determine lung In this study, we used two correction approaches to avoid cancer aggression. false-positive results in multiple tests. We did Bonferroni We have implemented an efficient stepwise approach for approach by multiplying the P value obtained in logistic searching lung cancer alleles in candidate chromosomal region regression by 22 (for each of the 22 SNPs) when analyzing in this study. This two-stage approach differs from htSNP single-locus association; meanwhile, all association results approach described in other articles (53, 54). The major underwent 1,000 permutation tests. Having relatively large drawback of the htSNP approach is that it is difficult to explore sample size, homogeneous study population, frequency- SNPs outside LD blocks and to pinpoint the true causal locus matched case-control design, solid and reproducible genotyp- (2, 6, 37). In addition, the htSNP approach may also miss ing techniques, and small P values, our results are unlikely to moderately rare SNPs and haplotypes. Although it is more be false positive.

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Tong Sun, Yang Gao, Wen Tan, et al.

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