Skip Navigation

TNF-α Promoter Polymorphisms and Susceptibility to Human Papillomavirus 16–Associated Cervical Cancer

  1. Alina Deshpande1,
  2. John P. Nolan1,5,
  3. P. Scott White1,
  4. Yolanda E. Valdez1,
  5. William C. Hunt2,
  6. Cheri L. Peyton3 and
  7. Cosette M. Wheeler3,4
  1. 1Bioscience Division, Los Alamos National Laboratory, Los Alamos, and
  2. 2Epidemiology and Cancer Prevention Program, and Departments of
  3. 3Molecular Genetics and Microbiology and
  4. 4Obstetrics and Gynecology, University of New Mexico Health Sciences Center, Albuquerque;
  5. 5La Jolla Bioengineering Institute, La Jolla, California
  1. Reprints or correspondence: Dr. John P. Nolan, La Jolla Bioengineering Institute, 505 Coast Blvd. South, La Jolla, CA 92037 (jnolan{at}ljbi.org)
 
Next Section

Abstract

BackgroundPolymorphisms in the TNF-α promoter region have recently been shown to be associated with susceptibility to cervical cancer. Some polymorphisms have been reported to influence transcription for this cytokine. Altered local levels in the cervix may influence an individual’s immune response, thereby affecting persistence of human papillomavirus (HPV) 16 infection, a primary etiological factor for cervical cancer

Methods and ResultsThe association of 11 TNF-α single-nucleotide polymorphisms (SNPs) with susceptibility to HPV16-associated cervical cancer was investigated. Sequencing of the TNF-α promoter region confirmed 10 SNPs, and 1 previously unreported SNP (161 bp upstream of the transcriptional start site) was discovered. Microsphere-array flow cytometry–based genotyping was performed on 787 samples from Hispanic and non-Hispanic white women (241 from randomly selected control subjects, 205 from HPV16-positive control subjects, and 341 from HPV16-positive subjects with cervical cancer). The genotype distribution of 3 SNPs (−572, −857, and −863) was significantly different between case subjects and control subjects. Analysis of haplotypes, which were computationally inferred from genotype data, also revealed statistically significant differences in haplotype distribution between case subjects and control subjects

ConclusionsWe report new associations between several TNF-α SNPs and susceptibility to cervical cancer that support the involvement of the TNF-α promoter region in development of cervical cancer

Cervical cancer is a significant problem worldwide [1, 2]. The precursor of development of cervical cancer is a persistent human papillomavirus (HPV) infection that leads to high-grade cervical intraepithelial neoplasia (CIN) [3]. Thus, an effective host immune response to HPV infection may be an important determinant of susceptibility to cervical cancer

Tumor necrosis factor (TNF)–α has been implicated in both direct and indirect control of HPV infection. HPV-harboring cervical keratinocytes constitutively produce active TNF-α [4], HPV16-positive cervical cell lines increase levels of TNF-α mRNA in vitro (compared with those in HPV-negative cervical cell lines) [5], and increased localized production of TNF-α in cervical cancer has been observed in vivo [6]

Direct control of HPV infection by TNF-α occurs by induction of apoptosis in HPV-infected cells and cervical cancer cells [7, 8], stimulation of the inflammatory response through up-regulation of vascular adhesion molecules and chemokines [9], arresting growth of HPV-infected keratinocytes, and down-regulation of HPV gene transcription [10, 11]. TNF-α–mediated up-regulation of HLA class I components in nonprofessional antigen-presenting cells represents indirect control [12]

Regulation of levels of TNF-α, locally and systemically, occurs at the genetic level [13] by posttranscriptional effects [14], and feedback inhibition occurs by TNF-α receptors [15]. The TNF-α gene is located on chromosome 6, within the major histocompatibilty complex (MHC), between HLA class I and II regions. Numerous studies have investigated the effect of single-nucleotide polymorphisms (SNPs) in the TNF-α promoter region, but results have been contradictory [16]. In the promoter region of the gene, the SNPs that affect transcription of TNF-α are −307 [17, 18], −375 [19], −863 [18, 20], and −857 [20]. Altered levels of TNF-α may influence the immune response to pathogens and contribute to an individual’s susceptibility to disease. In that regard, some polymorphisms in the TNF-α gene have been associated with susceptibility to infectious disease [17, 19, 21, 22]

Susceptibility to cervical cancer has a genetic component, and protective and risk associations of classical HLA alleles have been reported [23 –26]. A microsatellite polymorphism, TNF-α–11, has been shown to be associated with HPV16 infection and CIN, in combination with an HLA-DQB allele [27]. SNP −237 has also been shown to be associated with susceptibility to cervical cancer [28 –30]

The present study was performed to examine the role that TNF-α promoter SNPs play in susceptibility to HPV16-associated cervical cancer. HPV16-positive case subjects with cervical cancer were compared with HPV16-positive control subjects with no history of cervical disease and with randomly selected control subjects. Associations of TNF-α promoter SNPs with case-control status were investigated in Hispanic (H) and non-Hispanic white (NHW) subjects. Eleven TNF-α promoter SNPs were genotyped and were studied independently and in the context of haplotypes. Our results suggest that the TNF-α promoter region may be a determinant of both susceptibility to persistent HPV16 infection and subsequent development of cervical cancer

Previous SectionNext Section

Subjects, Materials, and Methods

Materials

Oligonucleotides (polymerase chain reaction [PCR] amplification, sequencing, and genotyping) were synthesized by Biosource International (Camarillo, CA). Deoxynucleotide triphosphates (dNTPs) were purchased from Promega, dideoxynucleotide triphosphates (ddNTPs) were purchased from MBI Fermentas, and biotinylated ddNTPs were purchased from Perkin Elmer Life Sciences. Sequencing reagents included the Big-Dye terminator mix (version 2; Applied Biosystems), Half term (Genetix), and dimethyl sulfoxide (Sigma). The enzymes (PCR amplification, sequencing, and genotyping) used were AmpliTaq Gold (Roche Molecular Systems), shrimp alkaline phosphatase (SAP) and exonuclease I (ExoI) (USB), and Thermosequenase (Amersham Biosciences). Streptavidin-conjugated phycoerythrin (PE) was purchased from Molecular Probes, carboxylated fluorescently encoded microspheres were purchased from Luminex, 2-(N-morpholino)ethanesulfonic acid was purchased from Sigma, 1-ethyl-3-(3[dimethylamino]propyl)carbodiimide-HCl was purchased from Pierce Chemical, and N-hydroxysuccinimide was purchased from Aldrich

Software

PCR and sequencing primers were designed by use of Oligo 6.4 (version 6.4; Molecular Biology Insights). Genotyping primers were designed by use of Oligo 6.4 and SBEprimer [31]. Sequence analysis was conducted by use of Phred (version 0.990722; University of Washington) [32, 33], Phrap (version 0.990319; University of Washington), and Polyphred (version 3.5 beta; University of Washington) [34]. Consed (version 8.0; University of Washington) was used to manually confirm Polyphred-identified SNPs. Haplotypes were inferred from SNP-genotype data by use of Haplotyper (Harvard University) [35]. Its output contains the likely haplotypes and their frequencies in the input data

DNA Samples

The samples in the present study were from a larger case-control study and were from subjects of 2 ethnic groups, H and NHW. They were randomly selected from 3 subsets. Three hundred forty-one samples (141 from H and 200 from NHW subjects) were selected from those collected from HPV16-positive case subjects with invasive cervical cancer, 241 samples (119 from H and 122 from NHW subjects) were selected from the entire control set, and 205 samples (122 from H and 83 from NHW subjects) were selected from those collected from the remainder of HPV16-positive control subjects. Control subjects gave informed consent before study entry. Case materials were obtained without identifiers. The Institutional Review boards at Los Alamos National Laboratory and the University of New Mexico approved the research protocols

Cases of cervical cancer were identified by use of the New Mexico Tumor Registry database. A total of 41.1% of the case subjects were 18–40 years of age, and 58.1% were >40 years of age. DNA samples were extracted from paraffin-embedded tumor biopsy specimens collected from pathology departments throughout New Mexico [36]. HPV status was determined by PCR amplification and line-blot hybridization by use of HPV type–specific oligonucleotide probes [37, 38]

Control subjects were recruited from women attending clinics (University of New Mexico Family and Women’s Health or Lovelace Women’s Health Services) for routine gynecologic care between 1996 and 2000. These 2 health-care systems provide the majority of health care for New Mexico. All control subjects were 18–40 years of age. DNA was obtained by collection of cervical swabs. HPV status was determined as described for the samples from case subjects. Overall HPV prevalence was 37% in H and 36.1% in NHW randomly selected control subjects; HPV16 prevalence was 14.3% and 9%, respectively

Amplification of the TNF-α Promoter Region

The TNF-α promoter region was amplified in 3 segments (329, 387, and 257 bp, spanning 973 bp). The Genbank reference sequence used to design PCR primers was Y14768.1 (GI#380580; complementary to the promoter sequence). PCR amplification was performed in 3 10-μL reactions (1× PCR buffer, 200 μmol/L dNTPs, 0.65 U of AmpliTaq Gold DNA polymerase, 2 mmol/L MgCl2, 250 nmol/L PCR primers, and template). Amplicons were generated by use of the following PCR cycling conditions: denaturation and polymerase activation for 10 min at 94°C and 40 cycles of annealing for 1 min at 55°C–58°C, extension for 2 min at 70°C, and denaturation for 1 min at 94°C. Amplicons were processed by treatment with SAP (1 U) and ExoI (1 U) for 60 min at 37°C and enzyme inactivation for 15 min at 72°C. Processed amplicons were sequenced or genotyped

Sequencing of the TNF-α Promoter Region

The TNF-α promoter region was sequenced, to confirm known SNPs and to discover unreported ones. Three hundred seventy-six samples (100 from randomly selected control subjects, 100 from case subjects with cervical cancer [equally distributed between the 2 ethnic groups], and 176 from National Institutes of Health–Polymorphism Discovery Resource [NIH-PDR], Coriell Cell Repository [available at: http://locus.umdnj.edu/nigms/comm/order/catprice.html]) were sequenced. Sequencing was performed in 5-μL reactions (standard Big-Dye terminator method), by use of 1 forward and 1 reverse primer. Isopropanol (80%)–precipitated sequencing reactions were run on an ABI Prism 377 DNA sequencer (Applied Biosystems). Sequence data were analyzed by use of the above-mentioned programs. A database of TNF-α promoter SNPs was generated after visual confirmation of the flagged SNPs

Genotyping for the Association Study

Genotyping was conducted by use of flow cytometry–based minisequencing [39]. A multiplexed assay was developed for genotyping of 11 TNF-α promoter SNPs (positions −76, −161, −237, −243, −307, −375, −568, −572, −575, −857, and −863 bp upstream of the transcriptional start site [40]). Amplification of the TNF-α promoter region was optimized to enable target amplification from DNA samples from case subjects. Since these samples were obtained from paraffin-embedded tissue, quantity and quality could have been compromised [36]. Allelic bias in amplification of the targets was tested. The assay was performed on targets amplified from artificially constructed heterozygotes for SNPs representing the amplicons used for genotyping and was optimized for equivalent detection of heterozygotes

Generation of address-conjugated microsphere arrays  Pairs of address and capture tags compatible with the minisequencing primers used in the TNF-α assay were selected [31], and address tags conjugated to 11 different fluorescently encoded microspheres via carbodiimide coupling. Address-conjugated microsphere arrays were generated by combining microspheres of each of the 11 types

The minisequencing reaction Eleven minisequencing primers were designed [31] and synthesized with specific capture tags on the 5′ end. The TNF-α amplicons were pooled, and minisequencing reactions were performed in 10-μL volumes containing amplicons, 7.5 μmol/L 1 biotinylated ddNTP, 7.5 μmol/L ddNTP (3 of the 4 not tagged with biotin), Thermosequenase reaction buffer (6 mmol/L Tris-HCl and 2 mmol/L MgCl2), 25 nmol/L each of the multiplexed minisequencing primers, and 0.75 U of Thermosequenase. One reaction for each of the 4 biotinylated ddNTPs was performed for each sample. Minisequencing was performed by denaturation for 30 s at 94°C followed by 99 cycles of annealing and extension for 10 s at 60°C and denaturation for 10 s at 94°C

Capture and analysis of minisequencing primers by flow-cytometric analysis Minisequenced reactions were combined with 2–3 μL of the microsphere array. The capture-tagged minisequencing primers were hybridized to their complementary address tags by heating the reactions to 80°C and then slow-cooling to 25°C. The microspheres were washed twice by centrifugation (1100 g) for 5 min with buffer (100 mmol/L Tris-HCl, 1 mmol/L EDTA, 900 mmol/L NaCl, and 0.02% Tween 20). Captured primers were stained with streptavidin-conjugated PE (33 nmol/L) for 15 min at room temperature. Reactions were transferred to 96-well flat-bottomed plates, and samples were analyzed by use of a Luminex 100 flow cytometer

Fluorescence data for each SNP were analyzed by use of base-specific background threshold values calculated for fluorescence data, and relative fluorescence intensity thresholds were calculated for the 2 bases specific for a biallelic SNP. High-throughput PCR amplification, amplicon processing, sequencing, and minisequencing were conducted by use of 96-well and 384-well plates (Marsh Bio-Products) and HYDRA-96 (Robbins Scientific) for reagent transfers

Haplotype Inference

Haplotyper [35] was used to infer haplotypes for case and control groups stratified by ethnic group. Since this program assumes Hardy-Weinberg Equilibrium (HWE), SNPs −76, −243, and −568 (which did not show HWE) were not included in the analysis of haplotypes

Statistical Methods

Genotype frequencies of each SNP and haplotype distributions were compared between case subjects and control subjects within ethnic groups by use of Pearson’s χ2 test for homogeneity of proportions. An exact P value was computed, and a significance criterion of P<.05 was used, with no correction for multiple comparisons. κ Values and exact confidence intervals were computed to quantify the level of agreement in individual SNP genotype frequencies, for 250 samples, with repeat genotyping. All analyses were performed by use of SAS (version 8.02; SAS Institute) and StatXact (version 3; Cytel)

Previous SectionNext Section

Results

PCR-based sequencing of DNA samples led to the discovery of 1 unreported SNP 161 bp upstream of the TNF-α transcriptional start site (SNP002901715 in the Human Genome Variation Database) [41]. This was confirmed by minisequencing

Minisequencing assay performance was evaluated by use of 88 NIH-PDR samples by comparing the genotypes obtained by sequencing with those obtained by minisequencing. Ten of the 11 SNPs had >95% agreement between sequencing and minisequencing, and 1 SNP had 92% agreement. Reproducibility of the minisequencing assay was evaluated by genotyping 250 samples from case subjects twice. κ Analysis was restricted to those 6 SNPs with variability in the samples sufficient to result in expected agreements <95%. κ Values were 0.66, 0.61, 0.59, 0.58, 0.44, and 0.36 for SNPs −572, −863, −375, −237, −307, and −857, respectively. All SNPs had acceptable reproducibility

The genotype frequencies of 11 SNPs in the TNF-α promoter region are reported in tables 1 (H) and 2 (NHW), for case subjects and control subjects, with P values determined by use of Pearson’s χ2 test, for comparisons of genotype frequencies between case subjects and control subjects. In the randomly selected control subjects, genotype frequencies of any of the SNPs were not significantly different between H and NHW subjects

Table 1
View larger version:
Table 1

Association analysis of TNF-α promoter single-nucleotide polymorphism (SNPs) for the Hispanic ethnic group

Table 2
View larger version:
Table 2

Association analysis of TNF-α promoter single-nucleotide polymorphism (SNPs) for the non-Hispanic, white ethnic group

The genotype distribution of 3 SNPs (−572, −857, and −863) differed significantly (P<.05) between case subjects and 1 or both of the control groups, the genotype distribution of 2 SNPs (−857 and −863) differed significantly between H case and control subjects, and the genotype distribution of 1 SNP (−572) differed significantly between NHW case and control subjects. An association for these SNPs has not been previously reported in the context of cervical cancer

Genotype data on 8 of the 11 SNPs were used to infer haplotypes. Table 3 lists haplotypes that were present at a frequency of >1% and were observed in both case subjects and control subjects. The frequencies of these haplotypes, by ethnic group and case-control status, are shown in table 4. SNPs −237, −307, −572, −857, and −863 defined commonly occurring haplotypes

Table 3
View larger version:
Table 3

TNF-α promoter haplotypes

Table 4
View larger version:
Table 4

Frequencies of TNF-α haplotypes

The overall distribution of haplotypes was significantly different between case subjects and randomly selected control subjects of both ethnic groups (H, P=.015; NHW, P=.032). Among H subjects, haplotype TN*01 was present at a significantly lower frequency in randomly selected control subjects than in case subjects (P=.001), whereas TN*04, defined by SNP −307, was present at a significantly lower frequency in HPV16-positive control subjects than in case subjects (P=.017). Among NHW subjects, TN*06 (defined by SNP −572) was present at a significantly higher frequency in randomly selected control subjects than in case subjects (P=.004)

Previous SectionNext Section

Discussion

Excess TNF-α can result in harmful inflammatory responses [42], whereas too little can contribute to persistent infection [43]. TNF-α is one of the primary cytokines released after HPV infection and up-regulates the expression of antigen-processing and -presentation pathway components for class I HLA [12, 44]. Thus, the level of expression of this cytokine could affect levels of antigen presentation. Insufficient antigen presentation to effector T cells may contribute to persistence of HPV16 infection and progression to cervical cancer. Alleles of 2 SNPs (−307 and −863) in the TNF-α promoter region that affect the transcription of TNF-α [18, 45] have been described as “high producers” and “low producers.” An optimal level of TNF-α could result from the presence of both alleles of those SNPs. The SNPs that had significantly different genotype distributions in comparisons of case subjects and control subjects (−572, −857, and −863) had a higher frequency of the rare allele (in the form of heterozygotes) in the control subjects than in the case subjects

SNP −237 has been reported to show an underrepresentation of heterozygotes in case subjects with cervical cancer [28 –30, reported as “−238” in 46]. This was seen only in H subjects, albeit without statistical significance. No transcriptional effect has been ascribed to this SNP. Moreover, the distribution of the haplotype defined by this SNP was not different between case subjects and control subjects. SNP −307, which has been shown to confer risk to both infectious and autoimmmune diseases [47 –49], was not shown to have any association with cervical cancer at the SNP level in either ethnic group. However, in H subjects, the haplotype it defined was shown to have an association with cervical cancer, by comparison of case subjects and HPV16-positive control subjects

SNP −575 has been reported to be polymorphic [50], with a frequency of minor allele (A) of 0.6%. This SNP was monomorphic in all groups in the present study, except for the HPV16-positive NHW case subjects (rare allele frequency, 0.5%). The genotype distribution was not significantly different from that in the NHW control subjects

Statistically significant protective associations were seen for SNPs −857 and −863 in H subjects. Allelic effects on transcription of the TNF-α gene and on circulating levels of TNF-α have been shown for SNP −863 [45], although this was not confirmed by Uglialoro et al. [50]. Two studies [20, 51] have suggested that the rare allele of SNP −863 is responsible for the enhanced expression of TNF-α. In the present study, the rare allele was observed at a higher frequency in control subjects, in the form of heterozygotes for this SNP. As discussed earlier, the observed protective associations seem to support the concept of “heterozygous advantage” described in the context of classic HLA antigens [52]. A protective association of SNP −572 that remained statistically significant after analysis of haplotype was observed in NHW subjects

Our association study compared 2 types of control subjects with HPV16-positive case subjects. Randomly selected control subjects represented the general population from which the case subjects were derived, in terms of geographic location (New Mexico), ethnic group, and HPV-exposure potential. They included both disease-free individuals who had been exposed to HPV16 and other HPV types and individuals who were negative for HPV DNA at the time of study enrollment. Thus, they were not homogenous with respect to the risk factor associated with cervical cancer in the present study—presence of HPV16. This control group served to represent susceptibility to the development of cervical cancer in general. The significant associations of SNPs −572 and −857 observed only in comparisons of case subjects and randomly selected control subjects could be due to their contributions to a TNF-α response that cleared infection, prevented progression of infected cells to the cancerous phenotype, or allowed for effective surveillance of tumors

The HPV16-positive control group better matched the case group in the present study, because of the presence of HPV16 in all disease-free individuals in the HPV16-positive control group. Associations observed in comparisons of case subjects and HPV16-positive control subjects may be reflective of HPV16-specific immune responses (e.g., SNP −863) that prevent progression of HPV16-infected cells to the cancerous phenotype or that eliminate dedifferentiated infected cells through surveillance of tumors

There are limitations to the present study. The control subjects were younger than the case subjects (median age, 25 and 45 years, respectively). Presence of HPV16 in control subjects makes it probable that some will develop cervical cancer during the next 2 decades, resulting in some misclassification of case-control status in the present study and an underestimation of genotype differences. A follow-up study to monitor control subjects for development of cervical cancer would help confirm the protective associations reported here

The P values have not been adjusted for multiple comparisons. A joint comparison of all 11 SNPs might fail to show any significant difference between case subjects and control subjects. However, we feel that the focus of SNP analysis should be at the level of the individual SNP and not the entire TNF-α region. Moreover, a joint comparison performed for haplotypes showed a significant difference between case subjects and randomly selected control subjects of both ethnic groups

Sample size may be another limitation. The average sample size per group (∼100 samples) yielded >80% power to detect odds ratios of 2.26, resulting in a rare-allele prevalence of ⩾5%. However, several SNPs had a rare-allele prevalence of ⩽2%. The power of the present study to detect associations for these alleles was much less than 80%

Since no HLA alleles were examined, it is not possible to determine the influence of linkage disequilibrium (LD) between the TNF-α gene and HLA class I or II genes on the observed associations. Studies of an association of HLA with cervical cancer have revealed HLA class II risk and protective haplotypes common to most ethnic groups [53]. It is possible that the associations we identified are due to linkage with ⩾1 of the known HLA alleles. However, recombination hot spots in the MHC region (e.g., the region between the genes BAT2 and LTA, which includes the TNF-α gene [54]) may influence TNF-α–HLA LD. Moreover, there was no overlap between the 2 ethnic groups, in terms of the TNF-α SNPs/haplotypes associated with cervical cancer in the present study, suggesting that the TNF-α region influences the HPV16 immune response in an HLA-independent manner. HLA-independent associations of TNF-α SNPs have been shown in certain autoimmune diseases [55, 56], infectious diseases [57], and certain cancers [58]. Studies reporting associations of TNF-α SNPs with risk of cervical cancer have either investigated specific SNPs independently [28, 29] or have not shown linkage with known HLA class I or II risk/protective alleles [30]. To date, no reports have shown an LD between the individual SNPs that were associated with risk of cervical cancer in the present study (i.e., SNPs −572, −857, and −863) and the known risk/protective HLA class I and II alleles. However, an LD between SNPs −857 and −863, which were studied in the context of a 3-SNP haplotype, and other specific HLA-B and HLA-DRB1 alleles in the Japanese population has been observed [59, 60]. An LD between TNF-α promoter microsatellite polymorphisms and specific HLA class I and II alleles has been shown to exist [61], as has an LD between these microsatellite haplotypes and specific TNF-α SNPs [62]. Recently, Posch et al. described 52 unique TNF-α LTA–HLA haplotypes that include the TNF-α promoter SNPs [63]. Interestingly, both the common protective HLA class II allele DRB1*1301 and the common risk allele DRB1*1501 are associated with the TNF-α haplotype that includes both dominant alleles of SNPs −857 and −863. The present study has shown protective associations for the recessive alleles of both of these SNPs. At the same time, other extended haplotypes reported by Posch et al. were shown to have an association between the risk allele HLA-DRB1*1501 with the haplotype defined by SNP −857 and the protective allele HLA-DRB1*1301 with the haplotype defined by SNP −863. Thus, there is no clearly defined LD between known HLA class II risk/protective alleles and the TNF-α SNPs/haplotypes associated with risk of cervical cancer in the present study. SNP −572 was not included in the haplotypes constructed by Posch et al. Analysis of HLA class I and II alleles in the samples used in the present study is in progress, and linkage analysis of data from the present study with data on HLA is planned

Finally, association studies are based on statistical comparisons between case and control groups and lack experimental evidence that unequivocally links genotype changes to phenotype changes or functional effects at the physiological level. Rather than being viewed as evidence for cause-effect relations in disease, statistically observed associations should be used to screen for determinants of susceptibility and as tools to narrow focus areas for functional studies

In summary, the present study supports a potential role for genetic variation in the TNF-α promoter region in susceptibility to cervical cancer. Comparisons of case subjects and control subjects revealed the association of 3 TNF-α promoter SNPs not previously reported in the context of risk of cervical cancer (SNPs −572, −857, and −863). Analysis of haplotypes confirmed and strengthened the identification of the TNF-α promoter region as a potential determinant of susceptibility. The present study was unique because of the use of carefully defined control groups, which enabled the elucidation of HPV16-specific versus -nonspecific associations of candidate SNPs. The inclusion of 2 ethnic groups revealed ethnic-specific associations. The present study has also demonstrated the use of a powerful technology for screening SNPs involved in susceptibility to disease. Its multiplexing capability enabled simultaneous and high-throughput screening of TNF-α SNPs in a large sample set

Previous SectionNext Section

Acknowledgments

We would like to thank Norah Torrez-Martinez for her help in the preparation of DNA samples from case and control subjects and for analyses of human papillomavirus type. We would also like to acknowledge Roche Molecular Systems for their generous contribution of AmpliTaq Gold to this project

Previous SectionNext Section

Footnotes

  • ↵Financial support: National Institutes of Health (grants RR01315, RR14101 [to J.P.N.], and RO1 AI/CA32917 [to C.M.W.]); United States Public Health Service (grant T32 AI07538)

  • Received June 15, 2004.
  • Accepted September 28, 2004.
Previous Section
 

References

  1. 1.↵
    1. Parkin DM,
    2. Whelan SL,
    3. Ferlay J,
    4. Teppo L,
    5. Thomas DB
    . Cancer incidence in five continents: volume VIII. Lyon: IARC Scientific; 1997.
  2. 2.↵
    1. Parkin DM,
    2. Pisani P,
    3. Ferlay J
    . Estimates of the worldwide incidence of 25 major cancers in 1990. Int J Cancer 1999;80:827-41.
    CrossRefMedlineWeb of Science
  3. 3.↵
    1. Ho GY,
    2. Burk RD,
    3. Klein S,
    4. et al
    . Persistent genital human papillomavirus infection as a risk factor for persistent cervical dysplasia. J Nat Cancer Inst 1995;87:1365-71.
    Abstract/FREE Full Text
  4. 4.↵
    1. Malejczyk J,
    2. Malejczyk M,
    3. Kock A,
    4. et al
    . Autocrine growth limitation of human papillomavirus type‐16 harboring keratinocytes by constitutively released tumor necrosis factor–α. J Immunol 1992;149:2702-8.
    Abstract
  5. 5.↵
    1. Bequet‐Romero M,
    2. Lopez‐Ocejo O
    . Angiogenesis modulators expression in culture cell lines positives for HPV‐16 oncoproteins. Biochem Biophys Res Commun 2000;277:55-61.
    CrossRefMedlineWeb of Science
  6. 6.↵
    1. Tjiong MY,
    2. van der Vange N,
    3. ter Schegget JS,
    4. Burger MPM,
    5. ten Kate FWJ,
    6. Out TA
    . Cytokines in cervicovaginal washing fluid from patients with cervical neoplasia. Cytokine 2001;14:357-60.
    CrossRefMedlineWeb of Science
  7. 7.↵
    1. Basile JR,
    2. Zacny V,
    3. Munger K
    . The cytokines tumor necrosis factor–α (TNF‐α) and TNF‐related apoptosis‐inducing ligand differentially modulate proliferation and apoptotic pathways in human keratinocytes expressing the human papillomavirus–16 E7 oncoprotein. J Biol Chem 2001;276:22522-8.
    Abstract/FREE Full Text
  8. 8.↵
    1. Suk K,
    2. Chang I,
    3. Kim YH,
    4. et al
    . Interferon γ (IFNγ) and tumor necrosis factor α synergism in ME‐180 cervical cancer cell apoptosis and necrosis. J Biol Chem 2001;276:13153-9.
    Abstract/FREE Full Text
  9. 9.↵
    1. Malejczyk J,
    2. Majewski S,
    3. Jablonska S
    . Cellular immunity in cutaneous and genital HPV infections. Clin Dermatol 1997;15:261-74.
    CrossRefMedlineWeb of Science
  10. 10.↵
    1. Vieira KB,
    2. Goldstein DJ,
    3. Villa LL
    . Tumor necrosis factor α interferes with the cell cycle of normal and papillomavirus‐immortalized human keratinocytes. Cancer Res 1996;56:2452-7.
    Abstract/FREE Full Text
  11. 11.↵
    1. Kyo S,
    2. Inoue M,
    3. Hayasaka N,
    4. et al
    . Regulation of early gene expression of human papillomavirus type 16 by inflammatory cytokines. Virology 1994;200:130-9.
    CrossRefMedlineWeb of Science
  12. 12.↵
    1. Hallermalm K,
    2. Seki K,
    3. Wei CH,
    4. et al
    . Tumor necrosis factor–α induces coordinated changes in major histocompatibility class I presentation pathway, resulting in increased stability of class I complexes at the cell surface. Blood 2001;98:1108-15.
    Abstract/FREE Full Text
  13. 13.↵
    1. Hajeer AH,
    2. Hutchinson IV
    . TNF‐α gene polymorphism: clinical and biological implications. Microsc Res Tech 2000;50:216-28.
    CrossRefMedlineWeb of Science
  14. 14.↵
    1. Jacob CO,
    2. Lee SK,
    3. Strassmann G
    . Mutational analysis of TNF‐α gene reveals a regulatory role for the 3′‐untranslated region in the genetic predisposition to lupus‐like autoimmune disease. J Immunol 1996;156:3043-50.
    Abstract
  15. 15.↵
    1. Peschon JJ,
    2. Torrance DS,
    3. Stocking KL,
    4. et al
    . TNF receptor–deficient mice reveal divergent roles for p55 and p75 in several models of inflammation. J Immunol 1998;160:943-52.
    Abstract/FREE Full Text
  16. 16.↵
    1. Hajeer AH,
    2. Hutchinson IV
    . Influence of TNFα gene polymorphisms on TNFα production and disease. Hum Immunol 2001;62:1191-9.
    CrossRefMedlineWeb of Science
  17. 17.↵
    1. Kroeger KM,
    2. Carville KS,
    3. Abraham LJ
    . The −308 tumor necrosis factor–α promoter polymorphism effects transcription. Mol Immunol 1997;34:391-9.
    CrossRefMedlineWeb of Science
  18. 18.↵
    1. Wilson AG,
    2. Symons JA,
    3. McDowell TL,
    4. McDevitt HO,
    5. Duff GW
    . Effects of a polymorphism in the human tumor necrosis factor α promoter on transcriptional activation. Proc Natl Acad Sci USA 1997;94:3195-9.
    Abstract/FREE Full Text
  19. 19.↵
    1. Knight JC,
    2. Udalova I,
    3. Hill AVS,
    4. et al
    . A polymorphism that affects OCT‐1 binding to the TNF promoter region is associated with severe malaria. Nat Genet 1999;22:145-50.
    CrossRefMedlineWeb of Science
  20. 20.↵
    1. Hohjoh H,
    2. Tokunaga K
    . Allele‐specific binding of the ubiquitous transcription factor OCT‐1 to the functional single nucleotide polymorphism (SNP) sites in the tumor necrosis factor–alpha gene (TNFA) promoter. Genes Immun 2001;2:105-9.
    CrossRefMedlineWeb of Science
  21. 21.↵
    1. Hohler T,
    2. Kruger A,
    3. Gerken G,
    4. Schneider PM,
    5. ZumBuschenfelde KHM,
    6. Rittner C
    . A tumour necrosis factor–alpha (TNF‐α) promoter polymorphism is associated with chronic hepatitis B infection. Clin Exp Immunol 1998;111:579-82.
    CrossRefMedlineWeb of Science
  22. 22.↵
    1. Loke H,
    2. Bethell D,
    3. Day N,
    4. White NJ,
    5. Hill AVS
    . A TNF promoter variant, HLA, and dengue in Vietnam. Hum Immunol 1996;47:124.
  23. 23.↵
    1. Wang SS,
    2. Wheeler CM,
    3. Hildesheim A,
    4. et al
    . Human leukocyte antigen class I and II alleles and risk of cervical neoplasia: results from a population‐based study in Costa Rica. J Infect Dis 2001;184:1310-4.
    Abstract/FREE Full Text
  24. 24.↵
    1. Cuzick J,
    2. Terry G,
    3. Ho L,
    4. et al
    . Association between high‐risk HPV types, HLA DRB1* and DQB1* alleles and cervical cancer in British women. Br J Cancer 2000;82:1348-52.
    CrossRefMedlineWeb of Science
  25. 25.↵
    1. Maciag PC,
    2. Schlecht NF,
    3. Souza PSA,
    4. Franco EL,
    5. Villa LL,
    6. Petzl‐Erler ML
    . Major histocompatibility complex class II polymorphisms and risk of cervical cancer and human papillomavirus infection in Brazilian women. Cancer Epidemiol Biomarkers Prev 2000;9:1183-91.
    Abstract/FREE Full Text
  26. 26.↵
    1. Madeleine MM,
    2. Brumback B,
    3. Cushing‐Haugen KL,
    4. et al
    . Human leukocyte antigen class II and cervical cancer risk: a population‐based study. J Infect Dis 2002;186:1565-74.
    Abstract/FREE Full Text
  27. 27.↵
    1. Ghaderi M,
    2. Nikitina L,
    3. Peacock CS,
    4. et al
    . Tumor necrosis factor a‐11 and DR15‐DQ6 (B*0602) haplotype increase the risk for cervical intraepithelial neoplasia in human papillomavirus 16 seropositive women in northern Sweden. Cancer Epidemiol Biomarkers Prev 2000;9:1067-70.
    Abstract/FREE Full Text
  28. 28.↵
    1. Jang WH,
    2. Yang YI,
    3. Yea SS,
    4. et al
    . The −238 tumor necrosis factor–α promoter polymorphism is associated with decreased susceptibility to cancers. Cancer Letters 2001;166:41-6.
    CrossRefMedlineWeb of Science
  29. 29.↵
    1. Calhoun ES,
    2. McGovern RM,
    3. Janney CA,
    4. et al
    . Host genetic polymorphism analysis in cervical cancer. Clin Chem 2002;48:1218-24.
    Abstract/FREE Full Text
  30. 30.↵
    1. Gostout BS,
    2. Poland GA,
    3. Calhoun ES,
    4. et al
    . TAP1, TAP2, and HLA‐DR2 alleles are predictors of cervical cancer risk. Gynecol Oncol 2003;88:326-32.
    CrossRefMedlineWeb of Science
  31. 31.↵
    1. Kaderali L,
    2. Deshpande A,
    3. Nolan JP,
    4. White PS
    . Primer design for multiplexed genotyping. Nucleic Acids Res 2003;31:1796-802.
    Abstract/FREE Full Text
  32. 32.↵
    1. Ewing B,
    2. Hillier L,
    3. Wendl MC,
    4. Green P
    . Base‐calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res 1998;8:175-85.
    Abstract/FREE Full Text
  33. 33.↵
    1. Ewing B,
    2. Green P
    . Base‐calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 1998;8:186-94.
    Abstract/FREE Full Text
  34. 34.↵
    1. Nickerson DA,
    2. Tobe VO,
    3. Taylor SL
    . PolyPhred: automating the detection and genotyping of single nucleotide substitutions using fluorescence‐based resequencing. Nucleic Acids Res 1997;25:2745-51.
    Abstract/FREE Full Text
  35. 35.↵
    1. Niu TH,
    2. Qin ZHS,
    3. Xu XP,
    4. Liu JS
    . Bayesian haplotype inference for multiple linked single‐nucleotide polymorphisms. Am J Hum Genet 2002;70:157-69.
    CrossRefMedlineWeb of Science
  36. 36.↵
    1. Greer CE,
    2. Wheeler CM,
    3. Manos MM
    . Sample preparation and PCR amplification from paraffin‐embedded tissues. PCR Methods Appl 1994;3:S113‐22.
  37. 37.↵
    1. Peyton CL,
    2. Gravitt PE,
    3. Hunt WC,
    4. et al
    . Determinants of genital human papillomavirus detection in a US population. J Infect Dis 2001;183:1554-64.
    Abstract/FREE Full Text
  38. 38.↵
    1. Gravitt PE,
    2. Peyton CL,
    3. Apple RJ,
    4. Wheeler CM
    . Genotyping of 27 human papillomavirus types by using L1 consensus PCR products by a single‐hybridization, reverse line blot detection method. J Clin Microbiol 1998;36:3020-7.
    Abstract/FREE Full Text
  39. 39.↵
    1. Cai H,
    2. White PS,
    3. Torney D,
    4. et al
    . Flow cytometry–based minisequencing: a new platform for high‐throughput single‐nucleotide polymorphism scoring. Genomics 2000;66:135-43.
    CrossRefMedlineWeb of Science
  40. 40.↵
    1. Allen RD
    . Polymorphism of the human TNF‐alpha promoter—random variation or functional diversity? Mol Immunol 1999;36:1017-27.
    CrossRefMedlineWeb of Science
  41. 41.↵
    1. Fredman D,
    2. Siegfried M,
    3. Yuan YP,
    4. Bork P,
    5. Lehväslaiho H,
    6. Brookes AJ
    . HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources. Nucleic Acids Res 2002;30:387-91.
    Abstract/FREE Full Text
  42. 42.↵
    1. Andreakos ET,
    2. Foxwell BM,
    3. Brennan FM,
    4. Maini RN,
    5. Feldmann M
    . Cytokines and anti‐cytokine biologicals in autoimmunity: present and future. Cytokine Growth Factor Rev 2002;13:299-313.
    CrossRefMedlineWeb of Science
  43. 43.↵
    1. Pfeffer K
    . Biological functions of tumor necrosis factor cytokines and their receptors. Cytokine Growth Factor Rev 2003;14:185-91.
    CrossRefMedlineWeb of Science
  44. 44.↵
    1. Ljunggren G,
    2. Anderson DJ
    . Cytokine‐induced modulation of MHC class‐I and class‐II molecules on human cervical epithelial cells. J Reprod Immunol 1998;38:123-38.
    CrossRefMedlineWeb of Science
  45. 45.↵
    1. Skoog T,
    2. van’t Hooft FM,
    3. Kallin B,
    4. et al
    . A common functional polymorphism (C→A substitution at position −863) in the promoter region of the tumour necrosis factor–α (TNF‐α) gene associated with reduced circulating levels of TNF‐α. Hum Molec Genet 1999;8:1443-9.
    Abstract/FREE Full Text
  46. 46.↵
    1. Haukim N,
    2. Bidwell J,
    3. Smith A,
    4. et al
    . Cytokine gene polymorphism in human disease: on‐line databases, supplement 2. Genes Immun 2002;3:313-30.
    CrossRefMedlineWeb of Science
  47. 47.↵
    1. McGuire W,
    2. Hill AVS,
    3. Allsop CEM,
    4. Greenwood BM,
    5. Kwiatkowski D
    . Variation in the TNF‐α promoter region associated with susceptibility to cerebral malaria. Nature 1994;371:508-11.
    CrossRefMedline
  48. 48.↵
    1. Nadel S,
    2. Newport MJ,
    3. Booy R,
    4. Levin M
    . Variation in the tumor necrosis factor–α gene promoter region may be associated with death from meningococcal disease. J Infect Dis 1996;174:878-80.
    Abstract/FREE Full Text
  49. 49.↵
    1. Sullivan KE,
    2. Wooten C,
    3. Schmeckpeper BJ,
    4. Goldman D,
    5. Petri MA
    . A promoter polymorphism of tumor necrosis factor α associated with systemic lupus erythematosus in African‐Americans. Arthritis Rheum 1997;40:2207-11.
    MedlineWeb of Science
  50. 50.↵
    1. Uglialoro AM,
    2. Turbay D,
    3. Pesavento PA,
    4. et al
    . Identification of three new single nucleotide polymorphisms in the human tumor necrosis factor–α gene promoter. Tissue Antigens 1998;52:359-67.
    MedlineWeb of Science
  51. 51.↵
    1. Udalova IA,
    2. Richardson A,
    3. Denys A,
    4. et al
    . Functional consequences of a polymorphism affecting NF‐κB p50‐p50 binding to the TNF promoter region. Molec Cell Biol 2000;20:9113-9.
    Abstract/FREE Full Text
  52. 52.↵
    1. Hill AVS
    . Immunogenetics and genomics. Lancet 2001;357:2037-41.
    CrossRefMedlineWeb of Science
  53. 53.↵
    1. Hildesheim A,
    2. Wang SS
    . Host and viral genetics and risk of cervical cancer: a review. Virus Res 2002;89:229-40.
    CrossRefMedlineWeb of Science
  54. 54.↵
    1. Cullen M,
    2. Perfetto SP,
    3. Klitz W,
    4. Nelson G,
    5. Carrington M
    . High‐resolution patterns of meiotic recombination across the human major histocompatibility complex. Am J Hum Genet 2002;71:759-76.
    CrossRefMedlineWeb of Science
  55. 55.↵
    1. Brinkman BM,
    2. Huizinga TW,
    3. Kurba SS,
    4. et al
    . Tumour necrosis factor α gene polymorphisms in rheumatoid arthritis: association with susceptibility to, or severity of, disease? Br J Rheumatol 1997;36:516-21.
    Abstract/FREE Full Text
  56. 56.↵
    1. Rood MJ,
    2. van Krugten MV,
    3. Zanelli E,
    4. et al
    . TNF‐308A and HLADR3 alleles contribute independently to susceptibility to systemic lupus erythematosus. Arthritis Rheum 2000;43:129-34.
    CrossRefMedlineWeb of Science
  57. 57.↵
    1. Yoon JK,
    2. Hyo‐Suk L,
    3. Jung‐Hwan Y,
    4. et al
    . Association of TNF‐α promoter polymorphisms with the clearance of hepatitis B virus infection. Hum Molec Genet 2003;12:2541-6.
    Abstract/FREE Full Text
  58. 58.↵
    1. Juszczynski P,
    2. Kalinka E,
    3. Bienvenu J,
    4. et al
    . Human leukocyte antigens class II and tumor necrosis factor genetic polymorphisms are independent predictors of non‐Hodgkin lymphoma outcome. Blood 2002;100:3037-40.
    Abstract/FREE Full Text
  59. 59.↵
    1. Higuchi T,
    2. Seki N,
    3. Kamizono S,
    4. et al
    . Polymorphisms of the 5′‐flanking region of the human tumor necrosis factor (TNF)–α gene in Japanese. Tissue Antigens 1998;51:605-12.
    MedlineWeb of Science
  60. 60.↵
    1. Matsushita M,
    2. Tsuchiya N,
    3. Nakayama T,
    4. et al
    . Allele typing of human TNFA 5′‐flanking region using polymerase chain reaction–preferential homoduplex formation assay (PCR‐PHFA): linkage disequilibrium with HLA class I and class II genes in Japanese. Tissue Antigens 1999;54:478-84.
    CrossRefMedlineWeb of Science
  61. 61.↵
    1. Jongeneel CV,
    2. Brinat L,
    3. Udalova IA,
    4. Sevin A,
    5. Nedospasov SA,
    6. Cambon‐Thomsen A
    . Extensive genetic polymorphism in the human tumor necrosis factor region and relation to extended HLA haplotypes. Proc Natl Acad Sci USA 1991;88:9717-21.
    Abstract/FREE Full Text
  62. 62.↵
    1. Waldron‐Lynch F,
    2. Adams C,
    3. Amos C,
    4. et al
    . Tumor necrosis factor 5′ promoter single nucleotide polymorphisms influence susceptibility to rheumatoid arthritis (RA) in immunogenetically defined multiplex RA families. Genes Immun 2001;2:82-7.
    CrossRefMedlineWeb of Science
  63. 63.↵
    1. Posch PE,
    2. Cruz I,
    3. Bradshaw D,
    4. Medhekar BA
    . Novel polymorphisms and the definition of promoter “alleles” of the tumor necrosis factor and lymphotoxin α loci: inclusion in HLA haplotypes. Genes Immun 2003;4:547-58.
    CrossRefMedlineWeb of Science
| Table of Contents

This Article

  1. J Infect Dis. (2005) 191 (6): 969-976. doi: 10.1086/427826
  1. AbstractFree
  2. » Full Text (HTML)Free
  3. Full Text (PDF)Free

Classifications

Share

  1. Email this article

Navigate This Article

Current Issue

  1. March 1, 2012 205 (5)
  1. Journal of Infectious Diseases
  1. Alert me to new issues

Most