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Interleukin gene polymorphisms and breast cancer: a case control study and systematic literature review

Interleukin gene polymorphisms and breast cancer: a case control study and systematic literature... Background: Interleukins and cytokines play an important role in the pathogenesis of many solid cancers. Several single nucleotide polymorphisms (SNPs) identified in cytokine genes are thought to influence the expression or function of these proteins and many have been evaluated for their role in inflammatory disease and cancer predisposition. The aim of this study was to evaluate any role of specific SNPs in the interleukin genes IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 in predisposition to breast cancer susceptibility and severity. Methods: Candidate single nucleotide polymorphisms (SNPs) in key cytokine genes were genotyped in breast cancer patients and in appropriate healthy volunteers who were similar in age, race and sex. Genotyping was performed using a high throughput allelic discrimination method. Data on clinico-pathological details and survival were collected. A systematic review of Medline English literature was done to retrieve previous studies of these polymorphisms in breast cancer. Results: None of the polymorphisms studied showed any overall predisposition to breast cancer susceptibility, severity or to time to death or occurrence of distant metastases. The results of the systematic review are summarised. Conclusion: Polymorphisms within key interleukin genes (IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 do not appear to play a significant overall role in breast cancer susceptibility or severity. especially breast cancer [2]. Many cytokine polymor- Background The role of cytokines in cancer immunity and carcinogen- phisms have been studied for associations with suscepti- esis in general has been well established [1]. Single bility to gastric cancer [3-5], liver cancer [6,7], lung nucleotide polymorphisms in specific candidate genes are cancer[8], prostate cancer [9] and ovarian cancer [10] with thought to influence expression and/or activity of the mixed results. encoding proteins thereby predisposing to solid cancers Page 1 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 The cytokines of the IL-1 family [11], IL-4 and its receptor This seems to alter the signalling function of the receptor, [12,13], IL-6 [14,15] and IL-10 [16,17] are important can- thereby predisposing carriers to disease [38]. Preliminary didate genes as they play an important role in breast can- studies show some association of this polymorphism with cer pathogenesis. IL1-alpha promotes growth of breast Crohn's disease [39] and adult asthma [40]. The polymor- cancer cells and cachexia [18]. In breast cancer cells, IL1- phism has also been associated with an increased risk of beta increases the transcriptional activity of ER-alpha [19] renal cancer [41]. The IL6 -174G>C polymorphism in the which is a prognostic factor in breast cancer and the 5' flanking region of the gene was initially reported in expression and stabilisation of IL-8 RNA [20] which is a 1998 to influence IL6 expression and plasma levels (the - potent angiogenic factor. IL-4 inhibits tumour growth by 174C allele associated with lower expression and lower its anti-angiogenic effect [21] and inhibits growth and levels) [42]. Subsequent studies of this polymorphism induces apoptosis of breast cancer cell lines in the pres- show that the -174C allele decreases susceptibility to sys- ence of IL-4R [12]. Circulating IL6 levels have been found temic juvenile idiopathic arthritis [43] and increases the to be higher in breast cancer patients compared to healthy risk of coronary artery disease presumably through controls and among those with breast cancer, correlate inflammatory mechanisms [44,45]. It also has been with the stage of the disease [14]. IL10 is over expressed in shown to increase the risk of bladder cancer [46], colorec- breast tumours [16] and exogenous administration can tal cancer [47] and Kaposi's sarcoma in HIV infected men mediate regression of tumour growth and breast cancer [48]. The IL10 -1082G>A polymorphism, situated in the metastases in mice models [17]. promoter region of the gene, has been shown to influence IL10 protein production in vitro by concanavalin-A stimu- The polymorphisms studied were selected in the light of lated peripheral mononuclear cells [49]. The G allele is previous reports of their effect on differential gene expres- associated with an increased risk of Crohn's disease [50] sion and/or disease susceptibility. The IL1A +4845 G>T and thought to increase predisposition to lung cancer polymorphism situated in exon 5 of the IL1A gene was [51]. The AA genotype has been shown to be associated described in 1993 [22] and results in an Ala to Ser amino with decreased survival in melanoma [52]. acid substitution at residue 114 of the proIL1α molecule. Pro IL1α is cleaved between amino acids 112 and 113 and The aim of this study was to evaluate polymorphisms in it has been suggested that this polymorphism may affect specific cytokine genes [IL1A +4845G>T, IL1B -511C>T, the proteolytic process [23]. The polymorphism is IL1B +3954C>T, IL1RN +2018T>C, IL4R -1902A>G, IL6- thought to influence C reactive protein levels in patients 174G>C and IL10-1082G>A] in a case control model to referred for coronary angiography [24] and influence the determine any associations with breast cancer susceptibil- development of aggressive periodontitis in Chinese males ity, severity and survival. A systematic review of the Eng- [25]. Three polymorphisms commonly studied in the lish language Medline literature through PubMed was IL1B gene include -511 and -31 in the promoter region performed to summarise all previous breast cancer related and the +3954 in exon 5, all representing a C>T single studies of the polymorphisms characterised in the current nucleotide change. The -511C>T and the +3954C>T SNPs study. are thought to influence C reactive protein levels in healthy individuals [26] and the +3954C>T polymor- Methods phism has been shown to influence IL1β production by Case-control study The design and methodology of this case control study monocytes in vitro [27]. The -511 polymorphism has been shown to be associated with vascular diseases such as have previously been described [53,54]. Briefly, recruit- stroke [28] and along with the +3954 polymorphisms has ment started in November 1998 and is ongoing. The cases been extensively studied in gastric cancer [29-31]. The include women diagnosed with breast cancer and being IL1RN +2018T>C polymorphism in exon 2 of the gene is followed up at the Royal Hallamshire Hospital in Shef- in complete linkage disequilibrium with a penta-allelic 86 field and Rotherham District General Hospital and con- bp variable number of tandem repeat polymorphism in trols were recruited from women attending the Sheffield intron 2 of the gene which is strongly linked to increased Breast Screening Service. The study was restricted to white production of IL1RA [32] and IL1β in vitro [33]. The Caucasians, as there were insufficient individuals from penta-allelic polymorphism has been studied in several other ethnic groups, for meaningful analysis. The South cancers including gastric cancer [29-31], lung cancer [34], Sheffield Research Ethics Committee approved the study ovarian cancer [35] and cervical cancer [36]. The +2018 [Ref. no. SS98/137] and informed written consent was SNP itself has been linked with Barrett's oesophagus and obtained from all subjects. Demographic, environmental oesophageal cancer [37]. The IL4R 1902A>G polymor- risk factors and family history data were recorded for all phism is an A to G transition at nucleotide 1902, causing breast cancer cases and mammography screening con- a change in amino acid from glutamine to arginine at trols, using a standard questionnaire. Pathological data codon 576 in the interleukin-4 receptor alpha protein. (including tumour grade, lymph node status and presence Page 2 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 of vascular invasion) were obtained from medical records shown in Tables 2 and 3. Levels of FAM and TET fluores- and validated by an experienced histopathologist (SSC). cence were determined and allelic discrimination was car- Data on disease recurrence and overall survival were ried out using the ABI 7200 Sequence Detector. Quality obtained from the hospital records and the Trent Cancer control for the genotyping results was achieved by using Registry. The data was entered by trained personnel and only 72 of the 96 wells in each of the plates for the indi- stored in a Microsoft Access database and maintained by vidual DNA samples subjected to PCR. Six to eight wells a dedicated database administrator. The data was vali- were allotted to 'no sample' controls, 'common dated for all the records (by SPB and database manager). homozygous' controls and 'rare homozygous' controls each, in addition to retesting of samples with indetermi- Genotyping methods nate results. The common and rare homozygous controls Genomic DNA was extracted from frozen EDTA preserved included samples tested before and shown to be 'common peripheral venous blood from all individuals, as homozygous' and 'rare homozygous' respectively. described previously [55]. The polymorphisms studied, along with the genes, location and unique ID is shown in Methodology for systematic review th A Medline search was conducted on 26 September 2005 Table 1. Genotyping of the polymorphisms was per- formed by the 5'nuclease PCR method, using the ABI/PE with the following search strategy: (("interleukins"[TIAB] Biosystems Taqman™ system, essentially as described ear- NOT Medline [SB]) OR "interleukins"[MeSH Terms] OR lier [55]. Using specific primer and probe sequences interleukin[Text Word]) OR (("cytokines"[TIAB] NOT (Table 1), PCR amplification was carried out separately Medline[SB]) OR "cytokines"[MeSH Terms] OR for the different polymorphisms. The final concentrations cytokine[Text Word]) AND ("genetic polymor- of the different constituents of the PCR mixture and the phism"[Text Word] OR "polymorphism, genetic"[MeSH cycling temperatures for the various SNPs studied are Terms] OR polymorphism[Text Word]) OR SNP[All Table 1: Candidate single nucleotide polymorphisms (SNPs) and their respective probes and primers Gene Location SNP ID Forward primer Reverse primer FAM probe TET probe IL-1A +4845 G>T rs17561 TGCACTTGTGATCAT TCCTCATAAAGTTGT CAAGCCTAGGTCATC AAGCCTAGGTCAGCA GGTTTTAGA ATTTCACATTGC ACCTTTTAGCTTCC CCTTTTAGCTTCC IL-1B -511 C>T rs16944 TTGAGGGTGTGGGTC AGGAGCCTGAACCCT TTCTCTGCCTCGGGA TTCTCTGCCTCAGGA TCTACCT GCATAC GCTCTCTGT GCTCTCTGTCA IL-1B +3954 C>T rs1143634 GCCTGCCCTTCTGAT CATCGTGCACATAAG TTCAGAACCTATCTT CAGAACCTATCTTCT TTTATACC CCTCGTTA CTTTGACACATGGGA TCGACACATGGGA IL-1RN +2018 T>C rs419598 GGGATGTTAACCAGA CAACCACTCACCTTC AACAACCAACTAGTT ACAACCAACTAGTTG AGACCTTCTATCT TAAATTGACATT GCTGGATACTTGCAA CCGGATACTTGC IL-4R +1902 A>G rs1801275 AGGCTTGAGAAGGC CCGAAATGTCCTCCA CATGTACAAACTCCT CATGTACAAACTCCC CTTGTAA GCAT GATAGCCACTGGTG GATAGCCACTGG IL-6 -174 G>C rs1800795 GCTGATTGGAAACCT AATGACGACCTAAGC ACGTCCTTTAGCATC ACGTCCTTTAGCATG TATTAAGATTGT TGCACTTT GCAAGACACAAC GCAAGACACAAC IL-10 -1082 G>A rs1800896 GATAGGAGGTCCCTT CACACACAAATCCAA CTACTTCCCCCTCCC CCTACTTCCCCTTCC ACTTTCCTCTTA GACAACACTAC AAAGAAGCCT CAAAGAAGCC Note: All sequences are from 5' end to 3' end. Table 2: Final concentration of the different constituents of the PCR mixture PCR constituents Final concentrations for the various SNPs IL1A +4845 IL1B -511 IL1B +3954 IL1RN +2018 IL4R +1902 IL6 -174 IL10 -1082 Taqman mastermix (2X) 1X 1X 1X 1X 1X 1X 1X Forward primer (10 μM) 500 nM 100 nM 300 nM 250 nM 50 nM 50 nM 50 nM Reverse primer (10 μM) 500 nM 100 nM 300 nM 250 nM 500 nM 50 nM 300 nM FAM probe (5 μM) 50 nM 50 nM 50 nM 30 nM 30 nM 30 nM 50 nM TET probe (5 μM) 100 nM 100 nM 75 nM 150 nM 120 nM 60 nM 150 nM Template (20 ng/μl) 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl Taqman mastermix: Universal PCR mastermix (PE Biosystems) containing MgCl , dNTPs, Taq polymerase, optimised buffer components and Rox reference dye; FAM probe: 6-carboxy-fluorescein-labelled probe; TET: 6-carboxy-4,7,2',7'-tetrechlorofluorescein-labelled probe. Page 3 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 3: Cycling conditions for the PCRs for the different polymorphisms Steps Time Temperature for the various SNPs IL1A +4845 IL1B -511 IL1B +3954 IL1RN +2018 IL4R +1902 IL6 -174 IL10 -1082 1 2 minutes 50°C 50°C 50°C 50°C 50°C 50°C 50°C 2 10 minutes 95°C 95°C 95°C 95°C 95°C 95°C 95°C 3 15 seconds 95°C 95°C 95°C 95°C 95°C 95°C 95°C 41 minutes 59°C 59°C 61°C 64°C 61°C 62°C 62°C 5 40 times Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 6 Hold 15°C 15°C 15°C 15°C 15°C 15°C 15°C Fields] AND (("neoplasms"[TIAB] NOT Medline[SB]) OR Table 4 shows the total numbers, the observed frequencies "neoplasms"[MeSH Terms] OR cancer[Text Word]) AND and the expected genotype frequencies (expected geno- English[Lang]. Only articles on the polymorphisms evalu- type frequencies were calculated from the respective allele ated in this study were included for the purposes of the frequencies) in the control population and the testing for review and their results are summarised in the discussion. the Hardy Weinberg Equilibrium. The observed frequen- cies of the genotypes for all polymorphisms are not signif- Data processing and analysis icantly different from the expected frequencies except for All data were entered initially into a Microsoft Access data- the IL1A +4845 and the IL4R +1902 polymorphisms. base and exported to SPSS (version 12.0.1 for Windows) for statistical analyses. Chi-square test for trend was per- The comparison of genotype frequencies between the con- formed to compare the genotype frequencies (1:1, 1:2 and trol and cancer groups for each of the polymorphisms 2:2 representing the common homozygous, heterozygous (along with the actual numbers studied) are shown in and the rare heterozygous respectively) between cases and Table 5. In addition to overall comparisons, the genotype controls and also for comparison of the genotype frequen- frequencies were compared in subgroups classified cies among the various subgroups of breast cancer. Kaplan according to family history and age at diagnosis. Table 6 Meier curves and the log rank test was used for the survival shows the genotype frequencies for the seven polymor- analyses. All tests were two sided. Haplotype analysis was phisms within subgroups of invasive breast cancer then performed on the genotype data of the four polymor- (defined by tumour grade, nodal status and vascular inva- phisms (IL1A +4845G>T, IL1B +3954C>T, IL1B -511C>T sion). Figures 1, 2, 3, 4, 5, 6, 7, 8 show survival curves and IL1RN +2018T>C) in chromosomal region 2q13 demonstrating that none of the polymorphisms had any using Haploview [56]. impact on time to death or development of metastases in those with invasive breast cancer. Results The demographic characteristics and comparability of Further analyses of the four polymorphisms in the Inter- case and control cohorts have been reported previously leukin-1 gene cluster (IL1A +4845G>T, IL1B +3954C>T, [53,54]. Briefly, the case and control groups were all Cau- IL1B -511C>T and IL1RN +2018T>C) were done using casian and female. There were no significant differences in Haploview. These four polymorphisms are situated a the percentage of postmenopausal women, age at region of size 360 kb. The LD (linkage disequilibrium) menarche and age at menopause between the cancer and values for the four pairs of SNPs (Figure 8) and the prob- control groups. The women in the control groups were able haplotypes with their frequencies (Table 7) have however younger [median (IQR) of 57 (53–61) in the been calculated. None of the estimated haplotypes was control group vs. 63 (54–70) in the cancer group; p < associated with breast cancer in this cohort. 0.001; Mann-Whitney U test], were younger when first pregnant [median (IQR) of 23 (20–26) in the control The literature search demonstrated two previous studies group vs. 24 (21–27) in the cancer group; p < 0.001; on the IL1B -511C>T polymorphism [57,58], one on the Mann-Whitney U test], had more children [median (IQR) IL1B +3954C>T polymorphism [58], six on the IL6 - of 2 (2–3) in the control group vs. 2 (1–3) in the cancer 174G>C polymorphism Smith, 2004 #877} [58-62] and group; p < 0.001; Mann-Whitney U test], were less likely four on the IL10 -1082G>A polymorphism [57,59,63,64]. to have a family history of breast cancer [22.2% in con- The results of the previously published studies are dis- trols vs. 27.4% in cancers; p = 0.007; Chi-square test] and cussed in the context of the results from the current study were more likely not to have smoked [63.1% in controls in the next section. vs. 53.4% in cancers; p < 0.001; Chi-square test]. Page 4 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 4: Observed and Expected genotype frequencies and the HardyWeinberg Equilibrium in the control population SNP Controls Observed Genotype Frequency Allele Frequency Expected Genotype Chi-square Goodness (n) (in %) Frequency of fit test statistic (p value) 1:1 1:2 2:2 1 2 1:1 1:2 2:2 2:2 IL1A +4845 498 215 245 38 67.8 32.2 229 217 52 χ = 7.49; p = 0.01 IL1B -511 489 232 206 51 66.5 31.5 230 211 48 χ = 0.20; p = 0.66 IL1B +3954 420 231 167 22 74.9 25.1 235 158 27 χ = 1.13; p = 0.29 IL1RN +2018 490 247 202 41 71 29 247 202 41 χ = 0; p = 0.95 IL4R +1902 767 451 288 28 77.6 22.4 461 267 39 χ = 4.45; p = 0.03 IL6 -174 490 168 235 87 58.3 41.7 167 238 85 χ = 0.06; p = 0.81 IL10 -1082 498 117 260 121 49.6 50.4 123 249 126 χ = 0.85; p = 0.36 Hardy Weinberg equilibrium, this may be an artefactual Discussion Cytokines play varied roles in cancer pathogenesis with association which would need confirmation in other pop- increasing evidence suggesting their involvement in ulations. There was no association of this polymorphism tumour initiation, growth and metastasis [1]. Cytokine with tumour grade, vessel invasion or survival. gene polymorphisms have been studied for associations with many inflammatory and neoplastic diseases. Numer- IL1B polymorphisms and breast cancer IL1β levels are high in breast cancer tissue and correlate ous reports have evaluated the association of individual candidate SNPs in cytokine genes in breast cancer, some with invasiveness and an aggressive phenotype [68]. They of which are included in this study. seem to regulate cancer cell proliferation through oestro- gen production by steroid-catalyzing enzymes in the tis- IL1A polymorphisms and breast cancer sue [69]. The IL1B gene is mapped to 2q13 [70] and the IL1A is thought to contribute to breast cancer expression commonly described genetic variants include the - by up-regulating pro-metastatic genes in breast cancer 511C>T and the -31C>T in the 5'UTR and the +3954C>T cells and stromal cells [65]. IL1A levels in breast tissue polymorphism in exon 5 of the gene. Our data for the - homogenates correlates inversely with ER levels [66], 511 and the +3954 SNPs show that overall; neither of which is an established prognostic marker in breast can- these SNPs is associated with breast cancer susceptibility, cer. The IL1A gene is mapped to chromosome 2q13 and severity or survival. As table 4c shows, in women with a includes several polymorphisms, of which one in the positive family history of breast cancer, the IL1B +3954T 5'UTR regulatory region (-889C>T) and one in exon 5 of allele was associated with a reduced risk of breast cancer. the gene (+4845G>T) have been commonly studied. The The significance of this association on exploratory sub- IL1A -889 polymorphism has been studied in two differ- group analysis is however limited. Tables 8 and 9 show ent cohorts and not shown to be associated with breast data from two other studies confirming our findings that cancer [58,67]. However, to date, there are no published these polymorphisms do play a significant role in breast studies on the role of the IL1A +4845 polymorphism in cancer susceptibility or severity. breast cancer. The current study has shown that there is a trend for the rare allele to confer a protective effect against IL1RN polymorphisms and breast cancer cancer (p = 0.05) and for the common allele to be signifi- It has been shown that IL1RA levels are increased in breast cantly associated with lymph node positive cancers (p = cancer tissue and that IL1RA levels correlate with ER levels 0.03). This effect is more apparent when the rare allele car- [66]. At least 18 sequence variants exist around the IL1RN riage rates (carriers of rare alleles) are assessed instead of gene [71] located in chromosome 2q13 [70]. Of these, the genotype frequencies (p = 0.005 and p = 0.007 respec- penta-allelic variant in intron 2 and the +2018T>C have tively). The positive finding however has not been subject been commonly studied. There are no prior reports of the to corrections for multiple testing in view of the explora- IL1RN +2018 polymorphism in breast cancer. The tory nature of these studies. In addition, given that the intronic polymorphism described however has however genotype frequencies of this polymorphism were not in been studied in breast cancer without any significant asso- Page 5 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 5: Genotype frequencies of the seven polymorphisms in subgroups of breast cancer and control populations Subsets Case/control Genotype Frequencies (%) Chi square test for trend (p value) 1:1 1:2 2:2 IL1A +4845 G>T Overall Cancers (n = 697) 360 (51.6%) 275 (39.5%) 62 (8.9%) X = 3.71; p = 0.05 Controls (n = 498) 215 (43.2%) 245 (49.2%) 38 (7.6%) Positive Family History Cancers (n = 192) 106 (55.2%) 71 (37%) 15 (7.8%) X = 2.74; p = 0.10 Controls (n = 104) 44 (42.3%) 52 (50%) 8 (7.7%) Negative Family History Cancers (n = 505) 254 (50.3%) 204 (40.4%) 47 (9.3%) X = 1.47; p = 0.23 Controls (n = 394) 171 (43.4%) 193 (49%) 30 (7.6%) Young cancers vs. controls Cancers (n = 113) 55 (48.7%) 43 (38%) 15 (13.3%) X = 0; p = 0.98 Controls (n = 498) 215 (43.2%) 245 (49.2%) 38 (7.6%) IL1B -511 C>T Overall Cancers (n = 703) 339 (48.2%) 294 (41.8%) 70 (10%) X = 0.10; p = 0.75 Controls (n = 489) 232 (47.4%) 206 (42.1%) 51 (10.4%) Positive Family History Cancers (n = 195) 96 (49.2%) 85 (43.6%) 14 (7.2%) X = 0.45; p = 0.51 Controls (n = 103) 48 (46.6%) 45 (43.7%) 10 (9.7%) Negative Family History Cancers (n = 508) 243 (47.8%) 209 (41.1%) 56 (11%) X = 0.003; p = 0.96 Controls (n = 386) 184 (47.7%) 161 (41.7%) 41 (10.6%) Young cancers vs. controls Cancers (n = 115) 55 (47.8%) 49 (42.6%) 11 (9.6%) X = 0.033; p = 0.86 Controls (n = 489) 232 (47.4%) 206 (42.1%) 51 (10.4%) IL1B +3954 C>T Overall Cancers (n = 691) 410 (59.3%) 242 (35%) 39 (5.6%) X = 1.12; p = 0.29 Controls (n = 420) 231 (55%) 167 (39.8%) 22 (5.2%) Positive Family History Cancers (n = 193) 129 (66.8%) 55 (28.5%) 9 (4.7%) X = 8.75; p = 0.003* Controls (n = 91) 43 (47.3%) 41 (45.1%) 7 (7.7%) Negative Family History Cancers (n = 498) 281 (56.4%) 187 (37.6%) 30 (6%) X = 0.26; p = 0.61 Controls (n = 329) 188 (57.1%) 126 (38.3%) 15 (4.6%) Young cancers vs. controls Cancers (n = 112) 64 (57.1%) 41 (36.6%) 7 (6.3%) X = 0.03; p = 0.86 Controls (n = 420) 231 (55%) 167 (39.8%) 22 (5.2%) IL1RN +2018 T>C Overall Cancers (n = 697) 349 (50.1%) 286 (41%) 62 (8.9%) X = 0.05; p = 0.82 Controls (n = 490) 247 (50.4%) 202 (41.2%) 41 (8.4%) Positive Family History Cancers (n = 193) 94 (48.7%) 84 (43.5%) 15 (7.8%) X = 0.074; p = 0.79 Controls (n = 103) 48 (46.6%) 47 (45.6%) 8 (7.8%) Negative Family History Cancers (n = 504) 255 (50.6%) 202 (40.1%) 47 (9.3%) X = 0.14; p = 0.71 Controls (n = 387) 199 (51.4%) 155 (40.1%) 33 (8.5%) Young cancers vs. controls Cancers (n = 113) 61 (54%) 44 (38.9%) 8 (7.1%) X = 0.53; p = 0.47 Controls (n = 490) 247 (50.4%) 202 (41.2%) 41 (8.4%) IL4R +1902 A>G Overall Cancers (n = 775) 493 (63.6%) 249 (32.1%) 33 (4.3%) X = 2.1; p = 0.15 Controls (n = 767) 451 (58.8%) 288 (37.5%) 28 (3.7%) Positive Family History Cancers (n = 212) 133 (62.7%) 70 (33%) 9 (4.2%) X = 0.19; p = 0.66 Controls (n = 168) 98 (58.3%) 66 (39.3%) 4 (2.4%) Negative Family History Cancers (n = 563) 360 (63.9%) 179 (31.8%) 24 (4.3%) X = 2.00; p = 0.16 Controls (n = 599) 353 (58.9%) 222 (37.1%) 24 (4.0%) Young cancers vs. controls Cancers (n = 122) 85 (69.7%) 36 (29.5%) 1 (0.8%) X = 6.36; p = 0.012* Controls (n = 767) 451 (58.8%) 288 (37.5%) 28 (3.7%) IL6 -174 G>C Page 6 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 5: Genotype frequencies of the seven polymorphisms in subgroups of breast cancer and control populations (Continued) Overall Cancers (n = 497) 170 (34.2%) 244 (49.1%) 83 (16.7%) X = 0.05; p = 0.83 Controls (n = 490) 168 (34.3%) 235 (48%) 87 (17.8%) Positive Family History Cancers (n = 127) 47 (37%) 55 (43.3%) 25(19.7%) X = 0.20; p = 0.66 Controls (n = 102) 38 (37.3%) 48 (47.1%) 16(15.7%) Negative Family History Cancers (n = 370) 123 (33.2%) 189 (51.1%) 58 (15.7%) X = 1.22; p = 0.64 Controls (n = 388) 130 (33.5%) 187 (48.2%) 71 (18.3%) Young cancers vs. controls Cancers (n = 85) 36 (42.4%) 31 (36.5%) 18 (21.2%) X = 0.31; p = 0.58 Controls (n = 490) 168 (34.3%) 235 (48%) 87 (17.8%) IL10 -1082 G>A Overall Cancers (n = 497) 121 (24.3%) 253 (50.9%) 123 (24.7%) X = 0.01; p = 0.93 Controls (n = 498) 117 (23.5%) 260 (52.2%) 121 (24.3%) Positive Family History Cancers (n = 126) 31 (24.6%) 69 (54.8%) 26 (20.6%) X = 0.39; p = 0.54 Controls (n = 104) 31 (29.8%) 52 (50%) 21 (20.2%) Negative Family History Cancers (n = 371) 90 (24.3%) 184 (49.6%) 97 (26.1%) X = 0.11; p = 0.74 Controls (n = 394) 86 (21.8%) 208 (52.8%) 100 (25.4%) Young cancers vs. controls Cancers (n = 84) 17 (20.2%) 44 (52.4%) 23 (27.4%) X = 0.60; p = 0.44 Controls (n = 498) 117 (23.5%) 260 (52.2%) 121 (24.3%) Note: Family history: either first or second degree relative with breast cancer. Young cancer patients: </=50 years of age ciation with susceptibility or prognosis [58]. Our data been localised to chromosome 7p21. Although several shows no association of the +2018T>C polymorphism polymorphisms exist in the promoter region of IL-6 and with breast cancer risk, severity or survival from the dis- are thought to have a complex interactive effect on IL6 ease. expression [75], the polymorphism at -174 has been most extensively studied and shown to have significant ethnic In addition to the analysis of the individual polymor- variation [74]. Table 10 shows the various studies of this phisms in the IL1A, IL1B and IL1RN genes, comparison of polymorphism in breast cancer to date. Only one study the probable haplotype frequencies in the breast cancer demonstrated an association with breast cancer suscepti- and control cohorts did not show any significant differ- bility [58], which showed a significant Odds ratio of 1.5 ences between the two groups. and 2.0 for the heterozygotes (GC) and the rare homozy- gotes (CC) when compared to the common homozygotes IL4R polymorphisms and breast cancer (GG). The study however included a non-healthy control IL4 receptor is significantly expressed in breast cancer [72] population (women attending outpatient departments for and it has been shown that IL4R is required for actions of various reasons) and a lack of correction for multiple test- IL4 on breast cancer cells [12] including the inhibition of ing. Our data shows that the IL6 -174G>C polymorphism growth and induction of apoptosis. The IL4R gene has was not associated with either breast cancer risk or severity been localised to 16p12. Several coding and regulatory and prognosis as assessed by tumour grade, lymph nodal region polymorphisms exist in the IL4R gene and are status, vascular invasion or survival. thought to influence signal transduction on the IL4 signal- ling pathway [73]. Our data on the IL4R polymorphism IL10 polymorphisms and breast cancer +1902A>G has shown no overall association with breast IL10 has been shown to have anti-metastatic and anti- cancer susceptibility, severity or survival. In the subgroup tumour effects in murine breast cancer models [17]. of young cancer patients (those </=50 years at diagnosis), Mononuclear cells from breast cancer patients exhibit we found that the G allele was significantly associated increased IL10 production [76] and IL10 serum levels cor- with breast cancer. There are no other studies of this pol- relate with stage of the disease [77]. Several single nucleo- ymorphism in breast cancer. tide polymorphisms exist in the promoter region of the IL10 gene (localised to chromosome 1q31-q32) including IL6 polymorphisms and breast cancer -1082, -819 and -592 [78]. Table 11 shows the studies of The circulating level of interleukin 6 is thought to be ele- the IL10 -1082G>A polymorphism in breast cancer. Of vated in the development and progression of many the three studies reported, only one suggests a role for the tumours including breast cancer and its up-regulation is G allele in reducing breast cancer risk [63]. Our data, associated with invasiveness and increased metastatic which includes larger numbers of individuals, however potential of ER negative tumours [74]. The IL6 gene has shows no association with breast cancer susceptibility, Page 7 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 6: Genotype frequencies of the seven polymorphisms in subgroups of invasive breast cancer. Tumour Severity Subgroups Genotype frequencies (%) Chi square test for trend (P value) 1:1 1:2 2:2 IL1A +4845 G>T Tumour Grade Grade 1 (n = 122) 62 (50.8%) 50 (41%) 10 (8.2%) X = 0.037; p = 0.85 Grade 2 (n = 283) 151 (53.4%) 109 (38.5%) 23 (8.1%) Grade 3 (n = 216) 115 (53.2%) 82 (38%) 19 (8.8%) Nodal Involvement Absent (n = 430) 204 (47.4%) 118 (43.7%) 38 (8.8%) X = 4.75; p = 0.03* Present (n = 117) 117 (59.4%) 63 (32%) 17 (8.6%) Vascular Invasion Absent (n = 467) 243 (52%) 185 (39.6%) 39 (8.4%) X = 0.058; p = 0.81 Present (n = 117) 64 (54.7%) 42 (35.9%) 11 (9.4%) IL1B -511 C>T Tumour Grade Grade 1 (n = 126) 51 (40.5%) 59 (46.8%) 16 (12.7%) X = 0.12; p = 0.73 Grade 2 (n = 284) 150 (52.8%) 111 (39.1%) 23 (8.1%) Grade 3 (n = 216) 98 (45.4%) 93 (43.1%) 25 (11.6%) Nodal Involvement Absent (n = 434) 214 (49.3%) 179 (41.2%) 41 (9.4%) X = 0.79; p = 0.37 Present (n = 198) 90 (45.5%) 87 (43.9%) 21 (10.6%) Vascular Invasion Absent (n = 473) 224 (47.4%) 201 (42.5%) 48 (10.1%) X = 0.38; p = 0.54 Present (n = 116) 57 (49.1%) 50 (43.1%) 9 (7.8%) IL1B +3954 C>T Tumour Grade Grade 1 (n = 121) 68 (56.2%) 48 (39.7%) 5 (4.1%) X = 0.053; p = 0.82 Grade 2 (n = 279) 173 (62%) 90 (32.3%) 16 (5.7%) Grade 3 (n = 215) 131 (60.9%) 70 (32.6%) 14 (6.5%) = 0.37; p = 0.54 Nodal Involvement Absent (n = 427) 244 (57.1%) 161 (37.7%) 22 (5.2%) X Present (n = 194) 120 (61.9%) 61 (31.4%) 13 (6.7%) Vascular Invasion Absent (n = 464) 283 (61%) 157 (33.8%) 24 (5.2%) X = 0.43; p = 0.51 Present (n = 114) 66 (57.9%) 41 (36%) 7 (6.1%) IL1RN +2018 T>C Tumour Grade Grade 1 (n = 125) 55 (44%) 55 (44%) 15 (12%) X = 0.73; p = 0.40 Grade 2 (n = 280) 150 (53.6%) 107 (38.2%) 23 (8.2%) Grade 3 (n = 215) 108 (50.2%) 86 (40%) 21 (9.8%) Nodal Involvement Absent (n = 429) 216 (50.3%) 180 (42%) 33 (7.7%) X = 0.11; p = 0.74 Present (n = 196) 102 (52%) 72 (36.7%) 22 (11.2%) Vascular Invasion Absent (n = 463) 232 (50.1%) 191 (41.3%) 40 (8.6%) X = 1.34; p = 0.25 Present (n = 118) 67 (56.8%) 42 (35.6%) 9 (7.6%) IL4R +1902 A>G Tumour Grade Grade 1 (n = 137) 87 (63.5%) 44 (32.1%) 6 (4.4%) X = 0.14; p = 0.71 Grade 2 (n = 308) 195 (63.3%) 97 (31.5%) 16 (5.2%) Grade 3 (n = 228) 146 (64%) 75 (32.9%) 7 (3.1%) Nodal Involvement Absent (n = 477) 313 (65.6%) 144 (30.2%) 20 (4.2%) X = 0.11; p = 0.75 Present (n = 212) 135 (63.7%) 69 (32.5%) 8 (3.8%) Vascular Invasion Absent (n = 508) 316 (62.2%) 170 (33.5%) 22 (4.3%) X = 0.002; p = 0.96 Present (n = 129) 82 (63.6%) 40 (31%) 7 (5.4%) IL6 -174 G>C Tumour Grade Grade 1 (n = 80) 26 (32.5%) 38 (47.5%) 16 (20%) X = 0.04; p = 0.84 Grade 2 (n = 204) 78 (38.2%) 95 (46.6%) 31 (15.2%) Grade 3 (n = 159) 49 (30.8%) 83 (52.2%) 27 (17%) Page 8 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 6: Genotype frequencies of the seven polymorphisms in subgroups of invasive breast cancer. (Continued) Nodal Involvement Absent (n = 293) 100 (34.1%) 141 (48.1%) 52 (17.7%) X = 0.20; p = 0.66 Present (n = 143) 52 (36.4%) 67 (46.9%) 24 (16.8%) Vascular Invasion Absent (n = 325) 112 (34.5%) 159 (48.9%) 54 (16.6%) X = 0.001; p = 0.98 Present (n = 85) 29 (34.1%) 42 (49.4%) 14 (16.5%) IL10 -1082 G>A Tumour Grade Grade 1 (n = 80) 23 (28.8%) 37 (46.3%) 20 (25%) X = 0.37; p = 0.54 Grade 2 (n = 205) 39 (19%) 113 (55.1%) 53 (25.9%) Grade 3 (n = 158) 44 (27.8%) 79 (50%) 35 (22.2%) Nodal Involvement Absent (n = 293) 69 (23.5%) 148 (50.5%) 76 (25.9%) X = 0.84; p = 0.36 Present (n = 143) 38 (26.6%) 73 (51%) 32 (22.4%) Vascular Invasion Absent (n = 325) 87 (26.8%) 156 (48%) 82 (25.2%) X = 3.3; p = 0.07 Present (n = 85) 12 (14.1%) 49 (57.6%) 24 (28.2%) severity or survival for this polymorphism. A study on the Abbreviations related polymorphism (-592C>A) in the promoter region IL: interleukin; ER: oestrogen receptor; SNP: single was associated with a reduced breast cancer risk, although nucleotide polymorphism; UTR: untranslated region; in breast cancer patients, there was no association with PCR: polymerase chain reaction; DNA: deoxyribonucleic severity of the disease [79]. acid. Limitations Competing interests Although our study had more than twice the number of The author(s) declare that they have no competing inter- subjects than the similar studies on cytokine polymor- ests. phisms in breast cancer, it could still be argued that asso- ciations of a minor degree (Odds Ratio < 1.5) of the Authors' contributions SPB, IAFA and SEH carried out patient recruitment, the genetic markers studied or other related markers may have been missed. For example, to detect a rare marker (of fre- molecular genetic studies and drafted the manuscript. SSC quency 10%) associated with a 1.3 times increased risk of reviewed the pathology and drafted the manuscript. SPB breast cancer (Odds Ratio = 1.3) with a power of 80% and and AC participated in the design of the study and per- type I error of 0.5%, we would need a sample size of 2400 formed the statistical analysis. AGW, NJB and MWR con- patients and controls. The second limitation is that a ceived of the study, and participated in its design and small proportion of our control population would coordination and helped to draft the manuscript. All develop breast cancer in their lifetime. However, it is gen- authors read and approved the final manuscript. erally considered difficult to obtain an ideal control cohort for genetic epidemiologic studies in solid cancers Acknowledgements We would like to thank Helen Cramp, Jane McDaid and Claire Greaves for mainly due to the delayed onset of the disease. The prog- help with recruitment and genotyping, Dan Connley for data management, nostic markers used for assessing breast cancer severity in and all the people who took part in the study. AC is funded by the York- this study were limited to grade, lymph nodal status and shire Cancer Research. We would also like to thank the Royal College of vascular invasion due to limited information available on Surgeons of Edinburgh who provided financial assistance towards consum- other indices such as hormone receptor status and tumour ables for this study. size. Conclusion The results from our study do not support the hypothesis that the cytokine polymorphisms studied [IL1A +4845G>T, IL1B -511C>T, IL1B +3954C>T, IL1RN +2018T>C, IL4R -1902A>G, IL6-174G>C and IL10- 1082G>A] are associated with breast cancer susceptibility and severity. Minor influences and associations with sub- groups of phenotypes may exist, but are unlikely to be of any major clinical significance. Page 9 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 1 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1A +4845 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1A +4845 polymorphism. Log Rank test statistic = 1.52; df = 2; p = 0.47 (n = 482). Page 10 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 2 th or metastases in invasive breast cancer for the genotypes of the IL1B -511 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B -511 polymorphism. Log Rank test statistic = 5.07; df = 2; p = 0.08 (n = 484). Page 11 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 3 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B +3954 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B +3954 polymorphism. Log Rank test statistic = 2.71; df = 2; p = 0.26 (n = 479). Page 12 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 4 th or metastases in invasive breast cancer for the genotypes of the IL1RN +2018 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1RN +2018 polymorphism. Log Rank test statistic = 4.32; df = 2; p = 0.12 (n = 481). Page 13 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 5 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL4R +1902 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL4R +1902 polymorphism. Log Rank test statistic = 2.07; df = 2; p = 0.35 (n = 528). Page 14 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 6 th or metastases in invasive breast cancer for the genotypes of the IL6 -174 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL6 -174 polymorphism. Log Rank test statistic = 0.16; df = 2; p = 0.92 (n = 333). Page 15 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 7 th or metastases in invasive breast cancer for the genotypes of the IL10 -1082 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL10 -1082 polymorphism. Log Rank test statistic = 1.34; df = 2; p = 0.51 (n = 332). Page 16 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 show iew four polymorph Figure 8 ) sho s the wing pai linkage isms on chromosome 2q13 rw di is sequi e D' valu libriu es m (in percentage) be plot (obtained using Ha tween the plov- shows the linkage disequilibrium plot (obtained using Haplov- iew) showing pairwise D' values (in percentage) between the four polymorphisms on chromosome 2q13. The markers 1, 2, 3 and 4 are IL1A +4845G>T, IL1B +3954C>T, IL1B -511 C>T and IL1RN +2018T>C respectively. Table 7: Probable frequencies of the common haplotypes in the interleukin-1 gene cluster in breast cancer and screening control cohorts. Haplotype* Frequency Case, Control Ratios Chi-square P value GCCT 0.330 471.5 : 938.5, 321.5 : 674.5 0.352 0.5529 TTCT 0.165 220.7 : 1189.3, 176.8 : 819.2 1.865 0.1720 GCTC 0.133 182.1 : 1227.9, 138.3 : 857.7 0.469 0.4934 GCTT 0.112 169.0 : 1241.0, 99.9 : 896.1 2.239 0.1346 GCCC 0.099 145.8 : 1264.2, 91.3 : 904.7 0.913 0.3392 TCCT 0.032 42.1 : 1367.9, 35.4 : 960.6 0.602 0.4376 TCTT 0.026 32.4 : 1377.6, 30.1 : 965.9 1.202 0.2729 GTCT 0.024 36.1 : 1373.9, 22.6 : 973.4 0.214 0.6440 TTCC 0.022 33.5 : 1376.5, 19.9 : 976.1 0.377 0.5394 TTTT 0.017 21.2 : 1388.8, 19.8 : 976.2 0.817 0.3661 TCCC 0.016 24.6 : 1385.4, 14.1 : 981.9 0.4 0.5271 TCTC 0.013 16.7 : 1393.3, 14.3 : 981.7 0.295 0.5873 * The haplotypes represent the four polymorphisms (IL1A +4845G>T, IL1B +3954C>T, IL1B -511C>T and IL1RN +2018T>C) in that order. Page 17 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 8: Studies of the IL1B -511C>T polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 2004 [57] 141 261 Bone marrow and solid organ donors – No association No association mixed male and female Hefler LA et al, 2005 [58] 269 227 Women visiting outpatient dept for No association No association Caucasian various reasons Our study 703 489 Women with normal mammograms No association No association British Caucasian from screening population Table 9: Studies of the IL1B +3954C>T polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Hefler LA et al, 2005 [58] 269 227 Women visiting outpatient dept for No association No association Caucasian various reasons Our study 691 420 Women with normal mammograms No association No association British Caucasian from screening population Table 10: Studies of the IL6 -174G>C polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 144 224 Bone marrow and solid organ No association No association mixed 2004 [57] donors – male and female Hefler LA et al, 269 227 Women visiting outpatient OR = 1.5 (1.04– No association Caucasian 2005 [58] dept for various reasons 2.3)* for GC vs. GG OR = 2 (1.1– 3.6)* for CC vs. GG Skerrett DL et al, 88 102 Maternal cord blood samples No association No association mixed 2005 [59] Saha A et al, 2003 26 95 Unknown No association Not studied Asian Indian [60] DeMichelle A et al, 80 0 - Not studied C allele associated with 4 mixed 2003 [61] year disease free survival (p = 0.02) and overall survival (p = 0.01) in node positive patients Iacopetta B et al, 256 0 - Not studied C allele associated with high mixed 2004 [62] grade (p = 0.04) and CC genotype associated with poor survival (p = 0.03) Our study 497 490 Women with normal No association No association British Caucasian mammograms from screening population OR: Odds Ratio Page 18 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 11: Studies of the IL10 -1082G>A polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 2004 [57] 129 223 Bone marrow and solid No association No association Mixed organ donors – male and female Giordani L et al, 2003 125 100 Female outpatients without OR = 0.58 (0.32–1.07) for Not studied unknown [63] breast cancer AG vs. AA OR = 0.38 (0.14–0.99) for GG vs. AA Skerrett DL et al, 2005 88 102 Maternal cord blood No association No association mixed [59] samples Wu JM et al, 2005 [64] 87 0 - Not studied No association mixed Our study 497 498 Women with normal No association No association British Caucasian mammograms from screening population OR: Odds Ratio 13. Obiri NI, Siegel JP, Varricchio F, Puri RK: Expression of high-affin- References ity IL-4 receptors on human melanoma, ovarian and breast 1. Smyth MJ, Cretney E, Kershaw MH, Hayakawa Y: Cytokines in can- carcinoma cells. Clin Exp Immunol 1994, 95(1):148-155. cer immunity and immunotherapy. 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Alamartine E, Berthoux P, Mariat C, Cambazard F, Berthoux F: Inter- leukin-10 promoter polymorphisms and susceptibility to skin squamous cell carcinoma after renal transplantation. J Invest Dermatol 2003, 120(1):99-103. Publish with Bio Med Central and every 79. Langsenlehner U, Krippl P, Renner W, Yazdani-Biuki B, Eder T, Kop- scientist can read your work free of charge pel H, Wascher TC, Paulweber B, Samonigg H: Interleukin-10 pro- moter polymorphism is associated with decreased breast "BioMed Central will be the most significant development for cancer risk. Breast Cancer Res Treat 2005, 90(2):113-115. disseminating the results of biomedical researc h in our lifetime." 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Interleukin gene polymorphisms and breast cancer: a case control study and systematic literature review

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Springer Journals
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2006 Balasubramanian et al; licensee BioMed Central Ltd.
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1471-2407
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1471-2407
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10.1186/1471-2407-6-188
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Abstract

Background: Interleukins and cytokines play an important role in the pathogenesis of many solid cancers. Several single nucleotide polymorphisms (SNPs) identified in cytokine genes are thought to influence the expression or function of these proteins and many have been evaluated for their role in inflammatory disease and cancer predisposition. The aim of this study was to evaluate any role of specific SNPs in the interleukin genes IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 in predisposition to breast cancer susceptibility and severity. Methods: Candidate single nucleotide polymorphisms (SNPs) in key cytokine genes were genotyped in breast cancer patients and in appropriate healthy volunteers who were similar in age, race and sex. Genotyping was performed using a high throughput allelic discrimination method. Data on clinico-pathological details and survival were collected. A systematic review of Medline English literature was done to retrieve previous studies of these polymorphisms in breast cancer. Results: None of the polymorphisms studied showed any overall predisposition to breast cancer susceptibility, severity or to time to death or occurrence of distant metastases. The results of the systematic review are summarised. Conclusion: Polymorphisms within key interleukin genes (IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 do not appear to play a significant overall role in breast cancer susceptibility or severity. especially breast cancer [2]. Many cytokine polymor- Background The role of cytokines in cancer immunity and carcinogen- phisms have been studied for associations with suscepti- esis in general has been well established [1]. Single bility to gastric cancer [3-5], liver cancer [6,7], lung nucleotide polymorphisms in specific candidate genes are cancer[8], prostate cancer [9] and ovarian cancer [10] with thought to influence expression and/or activity of the mixed results. encoding proteins thereby predisposing to solid cancers Page 1 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 The cytokines of the IL-1 family [11], IL-4 and its receptor This seems to alter the signalling function of the receptor, [12,13], IL-6 [14,15] and IL-10 [16,17] are important can- thereby predisposing carriers to disease [38]. Preliminary didate genes as they play an important role in breast can- studies show some association of this polymorphism with cer pathogenesis. IL1-alpha promotes growth of breast Crohn's disease [39] and adult asthma [40]. The polymor- cancer cells and cachexia [18]. In breast cancer cells, IL1- phism has also been associated with an increased risk of beta increases the transcriptional activity of ER-alpha [19] renal cancer [41]. The IL6 -174G>C polymorphism in the which is a prognostic factor in breast cancer and the 5' flanking region of the gene was initially reported in expression and stabilisation of IL-8 RNA [20] which is a 1998 to influence IL6 expression and plasma levels (the - potent angiogenic factor. IL-4 inhibits tumour growth by 174C allele associated with lower expression and lower its anti-angiogenic effect [21] and inhibits growth and levels) [42]. Subsequent studies of this polymorphism induces apoptosis of breast cancer cell lines in the pres- show that the -174C allele decreases susceptibility to sys- ence of IL-4R [12]. Circulating IL6 levels have been found temic juvenile idiopathic arthritis [43] and increases the to be higher in breast cancer patients compared to healthy risk of coronary artery disease presumably through controls and among those with breast cancer, correlate inflammatory mechanisms [44,45]. It also has been with the stage of the disease [14]. IL10 is over expressed in shown to increase the risk of bladder cancer [46], colorec- breast tumours [16] and exogenous administration can tal cancer [47] and Kaposi's sarcoma in HIV infected men mediate regression of tumour growth and breast cancer [48]. The IL10 -1082G>A polymorphism, situated in the metastases in mice models [17]. promoter region of the gene, has been shown to influence IL10 protein production in vitro by concanavalin-A stimu- The polymorphisms studied were selected in the light of lated peripheral mononuclear cells [49]. The G allele is previous reports of their effect on differential gene expres- associated with an increased risk of Crohn's disease [50] sion and/or disease susceptibility. The IL1A +4845 G>T and thought to increase predisposition to lung cancer polymorphism situated in exon 5 of the IL1A gene was [51]. The AA genotype has been shown to be associated described in 1993 [22] and results in an Ala to Ser amino with decreased survival in melanoma [52]. acid substitution at residue 114 of the proIL1α molecule. Pro IL1α is cleaved between amino acids 112 and 113 and The aim of this study was to evaluate polymorphisms in it has been suggested that this polymorphism may affect specific cytokine genes [IL1A +4845G>T, IL1B -511C>T, the proteolytic process [23]. The polymorphism is IL1B +3954C>T, IL1RN +2018T>C, IL4R -1902A>G, IL6- thought to influence C reactive protein levels in patients 174G>C and IL10-1082G>A] in a case control model to referred for coronary angiography [24] and influence the determine any associations with breast cancer susceptibil- development of aggressive periodontitis in Chinese males ity, severity and survival. A systematic review of the Eng- [25]. Three polymorphisms commonly studied in the lish language Medline literature through PubMed was IL1B gene include -511 and -31 in the promoter region performed to summarise all previous breast cancer related and the +3954 in exon 5, all representing a C>T single studies of the polymorphisms characterised in the current nucleotide change. The -511C>T and the +3954C>T SNPs study. are thought to influence C reactive protein levels in healthy individuals [26] and the +3954C>T polymor- Methods phism has been shown to influence IL1β production by Case-control study The design and methodology of this case control study monocytes in vitro [27]. The -511 polymorphism has been shown to be associated with vascular diseases such as have previously been described [53,54]. Briefly, recruit- stroke [28] and along with the +3954 polymorphisms has ment started in November 1998 and is ongoing. The cases been extensively studied in gastric cancer [29-31]. The include women diagnosed with breast cancer and being IL1RN +2018T>C polymorphism in exon 2 of the gene is followed up at the Royal Hallamshire Hospital in Shef- in complete linkage disequilibrium with a penta-allelic 86 field and Rotherham District General Hospital and con- bp variable number of tandem repeat polymorphism in trols were recruited from women attending the Sheffield intron 2 of the gene which is strongly linked to increased Breast Screening Service. The study was restricted to white production of IL1RA [32] and IL1β in vitro [33]. The Caucasians, as there were insufficient individuals from penta-allelic polymorphism has been studied in several other ethnic groups, for meaningful analysis. The South cancers including gastric cancer [29-31], lung cancer [34], Sheffield Research Ethics Committee approved the study ovarian cancer [35] and cervical cancer [36]. The +2018 [Ref. no. SS98/137] and informed written consent was SNP itself has been linked with Barrett's oesophagus and obtained from all subjects. Demographic, environmental oesophageal cancer [37]. The IL4R 1902A>G polymor- risk factors and family history data were recorded for all phism is an A to G transition at nucleotide 1902, causing breast cancer cases and mammography screening con- a change in amino acid from glutamine to arginine at trols, using a standard questionnaire. Pathological data codon 576 in the interleukin-4 receptor alpha protein. (including tumour grade, lymph node status and presence Page 2 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 of vascular invasion) were obtained from medical records shown in Tables 2 and 3. Levels of FAM and TET fluores- and validated by an experienced histopathologist (SSC). cence were determined and allelic discrimination was car- Data on disease recurrence and overall survival were ried out using the ABI 7200 Sequence Detector. Quality obtained from the hospital records and the Trent Cancer control for the genotyping results was achieved by using Registry. The data was entered by trained personnel and only 72 of the 96 wells in each of the plates for the indi- stored in a Microsoft Access database and maintained by vidual DNA samples subjected to PCR. Six to eight wells a dedicated database administrator. The data was vali- were allotted to 'no sample' controls, 'common dated for all the records (by SPB and database manager). homozygous' controls and 'rare homozygous' controls each, in addition to retesting of samples with indetermi- Genotyping methods nate results. The common and rare homozygous controls Genomic DNA was extracted from frozen EDTA preserved included samples tested before and shown to be 'common peripheral venous blood from all individuals, as homozygous' and 'rare homozygous' respectively. described previously [55]. The polymorphisms studied, along with the genes, location and unique ID is shown in Methodology for systematic review th A Medline search was conducted on 26 September 2005 Table 1. Genotyping of the polymorphisms was per- formed by the 5'nuclease PCR method, using the ABI/PE with the following search strategy: (("interleukins"[TIAB] Biosystems Taqman™ system, essentially as described ear- NOT Medline [SB]) OR "interleukins"[MeSH Terms] OR lier [55]. Using specific primer and probe sequences interleukin[Text Word]) OR (("cytokines"[TIAB] NOT (Table 1), PCR amplification was carried out separately Medline[SB]) OR "cytokines"[MeSH Terms] OR for the different polymorphisms. The final concentrations cytokine[Text Word]) AND ("genetic polymor- of the different constituents of the PCR mixture and the phism"[Text Word] OR "polymorphism, genetic"[MeSH cycling temperatures for the various SNPs studied are Terms] OR polymorphism[Text Word]) OR SNP[All Table 1: Candidate single nucleotide polymorphisms (SNPs) and their respective probes and primers Gene Location SNP ID Forward primer Reverse primer FAM probe TET probe IL-1A +4845 G>T rs17561 TGCACTTGTGATCAT TCCTCATAAAGTTGT CAAGCCTAGGTCATC AAGCCTAGGTCAGCA GGTTTTAGA ATTTCACATTGC ACCTTTTAGCTTCC CCTTTTAGCTTCC IL-1B -511 C>T rs16944 TTGAGGGTGTGGGTC AGGAGCCTGAACCCT TTCTCTGCCTCGGGA TTCTCTGCCTCAGGA TCTACCT GCATAC GCTCTCTGT GCTCTCTGTCA IL-1B +3954 C>T rs1143634 GCCTGCCCTTCTGAT CATCGTGCACATAAG TTCAGAACCTATCTT CAGAACCTATCTTCT TTTATACC CCTCGTTA CTTTGACACATGGGA TCGACACATGGGA IL-1RN +2018 T>C rs419598 GGGATGTTAACCAGA CAACCACTCACCTTC AACAACCAACTAGTT ACAACCAACTAGTTG AGACCTTCTATCT TAAATTGACATT GCTGGATACTTGCAA CCGGATACTTGC IL-4R +1902 A>G rs1801275 AGGCTTGAGAAGGC CCGAAATGTCCTCCA CATGTACAAACTCCT CATGTACAAACTCCC CTTGTAA GCAT GATAGCCACTGGTG GATAGCCACTGG IL-6 -174 G>C rs1800795 GCTGATTGGAAACCT AATGACGACCTAAGC ACGTCCTTTAGCATC ACGTCCTTTAGCATG TATTAAGATTGT TGCACTTT GCAAGACACAAC GCAAGACACAAC IL-10 -1082 G>A rs1800896 GATAGGAGGTCCCTT CACACACAAATCCAA CTACTTCCCCCTCCC CCTACTTCCCCTTCC ACTTTCCTCTTA GACAACACTAC AAAGAAGCCT CAAAGAAGCC Note: All sequences are from 5' end to 3' end. Table 2: Final concentration of the different constituents of the PCR mixture PCR constituents Final concentrations for the various SNPs IL1A +4845 IL1B -511 IL1B +3954 IL1RN +2018 IL4R +1902 IL6 -174 IL10 -1082 Taqman mastermix (2X) 1X 1X 1X 1X 1X 1X 1X Forward primer (10 μM) 500 nM 100 nM 300 nM 250 nM 50 nM 50 nM 50 nM Reverse primer (10 μM) 500 nM 100 nM 300 nM 250 nM 500 nM 50 nM 300 nM FAM probe (5 μM) 50 nM 50 nM 50 nM 30 nM 30 nM 30 nM 50 nM TET probe (5 μM) 100 nM 100 nM 75 nM 150 nM 120 nM 60 nM 150 nM Template (20 ng/μl) 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl 0.8 ng/μl Taqman mastermix: Universal PCR mastermix (PE Biosystems) containing MgCl , dNTPs, Taq polymerase, optimised buffer components and Rox reference dye; FAM probe: 6-carboxy-fluorescein-labelled probe; TET: 6-carboxy-4,7,2',7'-tetrechlorofluorescein-labelled probe. Page 3 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 3: Cycling conditions for the PCRs for the different polymorphisms Steps Time Temperature for the various SNPs IL1A +4845 IL1B -511 IL1B +3954 IL1RN +2018 IL4R +1902 IL6 -174 IL10 -1082 1 2 minutes 50°C 50°C 50°C 50°C 50°C 50°C 50°C 2 10 minutes 95°C 95°C 95°C 95°C 95°C 95°C 95°C 3 15 seconds 95°C 95°C 95°C 95°C 95°C 95°C 95°C 41 minutes 59°C 59°C 61°C 64°C 61°C 62°C 62°C 5 40 times Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 Go to step 3 6 Hold 15°C 15°C 15°C 15°C 15°C 15°C 15°C Fields] AND (("neoplasms"[TIAB] NOT Medline[SB]) OR Table 4 shows the total numbers, the observed frequencies "neoplasms"[MeSH Terms] OR cancer[Text Word]) AND and the expected genotype frequencies (expected geno- English[Lang]. Only articles on the polymorphisms evalu- type frequencies were calculated from the respective allele ated in this study were included for the purposes of the frequencies) in the control population and the testing for review and their results are summarised in the discussion. the Hardy Weinberg Equilibrium. The observed frequen- cies of the genotypes for all polymorphisms are not signif- Data processing and analysis icantly different from the expected frequencies except for All data were entered initially into a Microsoft Access data- the IL1A +4845 and the IL4R +1902 polymorphisms. base and exported to SPSS (version 12.0.1 for Windows) for statistical analyses. Chi-square test for trend was per- The comparison of genotype frequencies between the con- formed to compare the genotype frequencies (1:1, 1:2 and trol and cancer groups for each of the polymorphisms 2:2 representing the common homozygous, heterozygous (along with the actual numbers studied) are shown in and the rare heterozygous respectively) between cases and Table 5. In addition to overall comparisons, the genotype controls and also for comparison of the genotype frequen- frequencies were compared in subgroups classified cies among the various subgroups of breast cancer. Kaplan according to family history and age at diagnosis. Table 6 Meier curves and the log rank test was used for the survival shows the genotype frequencies for the seven polymor- analyses. All tests were two sided. Haplotype analysis was phisms within subgroups of invasive breast cancer then performed on the genotype data of the four polymor- (defined by tumour grade, nodal status and vascular inva- phisms (IL1A +4845G>T, IL1B +3954C>T, IL1B -511C>T sion). Figures 1, 2, 3, 4, 5, 6, 7, 8 show survival curves and IL1RN +2018T>C) in chromosomal region 2q13 demonstrating that none of the polymorphisms had any using Haploview [56]. impact on time to death or development of metastases in those with invasive breast cancer. Results The demographic characteristics and comparability of Further analyses of the four polymorphisms in the Inter- case and control cohorts have been reported previously leukin-1 gene cluster (IL1A +4845G>T, IL1B +3954C>T, [53,54]. Briefly, the case and control groups were all Cau- IL1B -511C>T and IL1RN +2018T>C) were done using casian and female. There were no significant differences in Haploview. These four polymorphisms are situated a the percentage of postmenopausal women, age at region of size 360 kb. The LD (linkage disequilibrium) menarche and age at menopause between the cancer and values for the four pairs of SNPs (Figure 8) and the prob- control groups. The women in the control groups were able haplotypes with their frequencies (Table 7) have however younger [median (IQR) of 57 (53–61) in the been calculated. None of the estimated haplotypes was control group vs. 63 (54–70) in the cancer group; p < associated with breast cancer in this cohort. 0.001; Mann-Whitney U test], were younger when first pregnant [median (IQR) of 23 (20–26) in the control The literature search demonstrated two previous studies group vs. 24 (21–27) in the cancer group; p < 0.001; on the IL1B -511C>T polymorphism [57,58], one on the Mann-Whitney U test], had more children [median (IQR) IL1B +3954C>T polymorphism [58], six on the IL6 - of 2 (2–3) in the control group vs. 2 (1–3) in the cancer 174G>C polymorphism Smith, 2004 #877} [58-62] and group; p < 0.001; Mann-Whitney U test], were less likely four on the IL10 -1082G>A polymorphism [57,59,63,64]. to have a family history of breast cancer [22.2% in con- The results of the previously published studies are dis- trols vs. 27.4% in cancers; p = 0.007; Chi-square test] and cussed in the context of the results from the current study were more likely not to have smoked [63.1% in controls in the next section. vs. 53.4% in cancers; p < 0.001; Chi-square test]. Page 4 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 4: Observed and Expected genotype frequencies and the HardyWeinberg Equilibrium in the control population SNP Controls Observed Genotype Frequency Allele Frequency Expected Genotype Chi-square Goodness (n) (in %) Frequency of fit test statistic (p value) 1:1 1:2 2:2 1 2 1:1 1:2 2:2 2:2 IL1A +4845 498 215 245 38 67.8 32.2 229 217 52 χ = 7.49; p = 0.01 IL1B -511 489 232 206 51 66.5 31.5 230 211 48 χ = 0.20; p = 0.66 IL1B +3954 420 231 167 22 74.9 25.1 235 158 27 χ = 1.13; p = 0.29 IL1RN +2018 490 247 202 41 71 29 247 202 41 χ = 0; p = 0.95 IL4R +1902 767 451 288 28 77.6 22.4 461 267 39 χ = 4.45; p = 0.03 IL6 -174 490 168 235 87 58.3 41.7 167 238 85 χ = 0.06; p = 0.81 IL10 -1082 498 117 260 121 49.6 50.4 123 249 126 χ = 0.85; p = 0.36 Hardy Weinberg equilibrium, this may be an artefactual Discussion Cytokines play varied roles in cancer pathogenesis with association which would need confirmation in other pop- increasing evidence suggesting their involvement in ulations. There was no association of this polymorphism tumour initiation, growth and metastasis [1]. Cytokine with tumour grade, vessel invasion or survival. gene polymorphisms have been studied for associations with many inflammatory and neoplastic diseases. Numer- IL1B polymorphisms and breast cancer IL1β levels are high in breast cancer tissue and correlate ous reports have evaluated the association of individual candidate SNPs in cytokine genes in breast cancer, some with invasiveness and an aggressive phenotype [68]. They of which are included in this study. seem to regulate cancer cell proliferation through oestro- gen production by steroid-catalyzing enzymes in the tis- IL1A polymorphisms and breast cancer sue [69]. The IL1B gene is mapped to 2q13 [70] and the IL1A is thought to contribute to breast cancer expression commonly described genetic variants include the - by up-regulating pro-metastatic genes in breast cancer 511C>T and the -31C>T in the 5'UTR and the +3954C>T cells and stromal cells [65]. IL1A levels in breast tissue polymorphism in exon 5 of the gene. Our data for the - homogenates correlates inversely with ER levels [66], 511 and the +3954 SNPs show that overall; neither of which is an established prognostic marker in breast can- these SNPs is associated with breast cancer susceptibility, cer. The IL1A gene is mapped to chromosome 2q13 and severity or survival. As table 4c shows, in women with a includes several polymorphisms, of which one in the positive family history of breast cancer, the IL1B +3954T 5'UTR regulatory region (-889C>T) and one in exon 5 of allele was associated with a reduced risk of breast cancer. the gene (+4845G>T) have been commonly studied. The The significance of this association on exploratory sub- IL1A -889 polymorphism has been studied in two differ- group analysis is however limited. Tables 8 and 9 show ent cohorts and not shown to be associated with breast data from two other studies confirming our findings that cancer [58,67]. However, to date, there are no published these polymorphisms do play a significant role in breast studies on the role of the IL1A +4845 polymorphism in cancer susceptibility or severity. breast cancer. The current study has shown that there is a trend for the rare allele to confer a protective effect against IL1RN polymorphisms and breast cancer cancer (p = 0.05) and for the common allele to be signifi- It has been shown that IL1RA levels are increased in breast cantly associated with lymph node positive cancers (p = cancer tissue and that IL1RA levels correlate with ER levels 0.03). This effect is more apparent when the rare allele car- [66]. At least 18 sequence variants exist around the IL1RN riage rates (carriers of rare alleles) are assessed instead of gene [71] located in chromosome 2q13 [70]. Of these, the genotype frequencies (p = 0.005 and p = 0.007 respec- penta-allelic variant in intron 2 and the +2018T>C have tively). The positive finding however has not been subject been commonly studied. There are no prior reports of the to corrections for multiple testing in view of the explora- IL1RN +2018 polymorphism in breast cancer. The tory nature of these studies. In addition, given that the intronic polymorphism described however has however genotype frequencies of this polymorphism were not in been studied in breast cancer without any significant asso- Page 5 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 5: Genotype frequencies of the seven polymorphisms in subgroups of breast cancer and control populations Subsets Case/control Genotype Frequencies (%) Chi square test for trend (p value) 1:1 1:2 2:2 IL1A +4845 G>T Overall Cancers (n = 697) 360 (51.6%) 275 (39.5%) 62 (8.9%) X = 3.71; p = 0.05 Controls (n = 498) 215 (43.2%) 245 (49.2%) 38 (7.6%) Positive Family History Cancers (n = 192) 106 (55.2%) 71 (37%) 15 (7.8%) X = 2.74; p = 0.10 Controls (n = 104) 44 (42.3%) 52 (50%) 8 (7.7%) Negative Family History Cancers (n = 505) 254 (50.3%) 204 (40.4%) 47 (9.3%) X = 1.47; p = 0.23 Controls (n = 394) 171 (43.4%) 193 (49%) 30 (7.6%) Young cancers vs. controls Cancers (n = 113) 55 (48.7%) 43 (38%) 15 (13.3%) X = 0; p = 0.98 Controls (n = 498) 215 (43.2%) 245 (49.2%) 38 (7.6%) IL1B -511 C>T Overall Cancers (n = 703) 339 (48.2%) 294 (41.8%) 70 (10%) X = 0.10; p = 0.75 Controls (n = 489) 232 (47.4%) 206 (42.1%) 51 (10.4%) Positive Family History Cancers (n = 195) 96 (49.2%) 85 (43.6%) 14 (7.2%) X = 0.45; p = 0.51 Controls (n = 103) 48 (46.6%) 45 (43.7%) 10 (9.7%) Negative Family History Cancers (n = 508) 243 (47.8%) 209 (41.1%) 56 (11%) X = 0.003; p = 0.96 Controls (n = 386) 184 (47.7%) 161 (41.7%) 41 (10.6%) Young cancers vs. controls Cancers (n = 115) 55 (47.8%) 49 (42.6%) 11 (9.6%) X = 0.033; p = 0.86 Controls (n = 489) 232 (47.4%) 206 (42.1%) 51 (10.4%) IL1B +3954 C>T Overall Cancers (n = 691) 410 (59.3%) 242 (35%) 39 (5.6%) X = 1.12; p = 0.29 Controls (n = 420) 231 (55%) 167 (39.8%) 22 (5.2%) Positive Family History Cancers (n = 193) 129 (66.8%) 55 (28.5%) 9 (4.7%) X = 8.75; p = 0.003* Controls (n = 91) 43 (47.3%) 41 (45.1%) 7 (7.7%) Negative Family History Cancers (n = 498) 281 (56.4%) 187 (37.6%) 30 (6%) X = 0.26; p = 0.61 Controls (n = 329) 188 (57.1%) 126 (38.3%) 15 (4.6%) Young cancers vs. controls Cancers (n = 112) 64 (57.1%) 41 (36.6%) 7 (6.3%) X = 0.03; p = 0.86 Controls (n = 420) 231 (55%) 167 (39.8%) 22 (5.2%) IL1RN +2018 T>C Overall Cancers (n = 697) 349 (50.1%) 286 (41%) 62 (8.9%) X = 0.05; p = 0.82 Controls (n = 490) 247 (50.4%) 202 (41.2%) 41 (8.4%) Positive Family History Cancers (n = 193) 94 (48.7%) 84 (43.5%) 15 (7.8%) X = 0.074; p = 0.79 Controls (n = 103) 48 (46.6%) 47 (45.6%) 8 (7.8%) Negative Family History Cancers (n = 504) 255 (50.6%) 202 (40.1%) 47 (9.3%) X = 0.14; p = 0.71 Controls (n = 387) 199 (51.4%) 155 (40.1%) 33 (8.5%) Young cancers vs. controls Cancers (n = 113) 61 (54%) 44 (38.9%) 8 (7.1%) X = 0.53; p = 0.47 Controls (n = 490) 247 (50.4%) 202 (41.2%) 41 (8.4%) IL4R +1902 A>G Overall Cancers (n = 775) 493 (63.6%) 249 (32.1%) 33 (4.3%) X = 2.1; p = 0.15 Controls (n = 767) 451 (58.8%) 288 (37.5%) 28 (3.7%) Positive Family History Cancers (n = 212) 133 (62.7%) 70 (33%) 9 (4.2%) X = 0.19; p = 0.66 Controls (n = 168) 98 (58.3%) 66 (39.3%) 4 (2.4%) Negative Family History Cancers (n = 563) 360 (63.9%) 179 (31.8%) 24 (4.3%) X = 2.00; p = 0.16 Controls (n = 599) 353 (58.9%) 222 (37.1%) 24 (4.0%) Young cancers vs. controls Cancers (n = 122) 85 (69.7%) 36 (29.5%) 1 (0.8%) X = 6.36; p = 0.012* Controls (n = 767) 451 (58.8%) 288 (37.5%) 28 (3.7%) IL6 -174 G>C Page 6 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 5: Genotype frequencies of the seven polymorphisms in subgroups of breast cancer and control populations (Continued) Overall Cancers (n = 497) 170 (34.2%) 244 (49.1%) 83 (16.7%) X = 0.05; p = 0.83 Controls (n = 490) 168 (34.3%) 235 (48%) 87 (17.8%) Positive Family History Cancers (n = 127) 47 (37%) 55 (43.3%) 25(19.7%) X = 0.20; p = 0.66 Controls (n = 102) 38 (37.3%) 48 (47.1%) 16(15.7%) Negative Family History Cancers (n = 370) 123 (33.2%) 189 (51.1%) 58 (15.7%) X = 1.22; p = 0.64 Controls (n = 388) 130 (33.5%) 187 (48.2%) 71 (18.3%) Young cancers vs. controls Cancers (n = 85) 36 (42.4%) 31 (36.5%) 18 (21.2%) X = 0.31; p = 0.58 Controls (n = 490) 168 (34.3%) 235 (48%) 87 (17.8%) IL10 -1082 G>A Overall Cancers (n = 497) 121 (24.3%) 253 (50.9%) 123 (24.7%) X = 0.01; p = 0.93 Controls (n = 498) 117 (23.5%) 260 (52.2%) 121 (24.3%) Positive Family History Cancers (n = 126) 31 (24.6%) 69 (54.8%) 26 (20.6%) X = 0.39; p = 0.54 Controls (n = 104) 31 (29.8%) 52 (50%) 21 (20.2%) Negative Family History Cancers (n = 371) 90 (24.3%) 184 (49.6%) 97 (26.1%) X = 0.11; p = 0.74 Controls (n = 394) 86 (21.8%) 208 (52.8%) 100 (25.4%) Young cancers vs. controls Cancers (n = 84) 17 (20.2%) 44 (52.4%) 23 (27.4%) X = 0.60; p = 0.44 Controls (n = 498) 117 (23.5%) 260 (52.2%) 121 (24.3%) Note: Family history: either first or second degree relative with breast cancer. Young cancer patients: </=50 years of age ciation with susceptibility or prognosis [58]. Our data been localised to chromosome 7p21. Although several shows no association of the +2018T>C polymorphism polymorphisms exist in the promoter region of IL-6 and with breast cancer risk, severity or survival from the dis- are thought to have a complex interactive effect on IL6 ease. expression [75], the polymorphism at -174 has been most extensively studied and shown to have significant ethnic In addition to the analysis of the individual polymor- variation [74]. Table 10 shows the various studies of this phisms in the IL1A, IL1B and IL1RN genes, comparison of polymorphism in breast cancer to date. Only one study the probable haplotype frequencies in the breast cancer demonstrated an association with breast cancer suscepti- and control cohorts did not show any significant differ- bility [58], which showed a significant Odds ratio of 1.5 ences between the two groups. and 2.0 for the heterozygotes (GC) and the rare homozy- gotes (CC) when compared to the common homozygotes IL4R polymorphisms and breast cancer (GG). The study however included a non-healthy control IL4 receptor is significantly expressed in breast cancer [72] population (women attending outpatient departments for and it has been shown that IL4R is required for actions of various reasons) and a lack of correction for multiple test- IL4 on breast cancer cells [12] including the inhibition of ing. Our data shows that the IL6 -174G>C polymorphism growth and induction of apoptosis. The IL4R gene has was not associated with either breast cancer risk or severity been localised to 16p12. Several coding and regulatory and prognosis as assessed by tumour grade, lymph nodal region polymorphisms exist in the IL4R gene and are status, vascular invasion or survival. thought to influence signal transduction on the IL4 signal- ling pathway [73]. Our data on the IL4R polymorphism IL10 polymorphisms and breast cancer +1902A>G has shown no overall association with breast IL10 has been shown to have anti-metastatic and anti- cancer susceptibility, severity or survival. In the subgroup tumour effects in murine breast cancer models [17]. of young cancer patients (those </=50 years at diagnosis), Mononuclear cells from breast cancer patients exhibit we found that the G allele was significantly associated increased IL10 production [76] and IL10 serum levels cor- with breast cancer. There are no other studies of this pol- relate with stage of the disease [77]. Several single nucleo- ymorphism in breast cancer. tide polymorphisms exist in the promoter region of the IL10 gene (localised to chromosome 1q31-q32) including IL6 polymorphisms and breast cancer -1082, -819 and -592 [78]. Table 11 shows the studies of The circulating level of interleukin 6 is thought to be ele- the IL10 -1082G>A polymorphism in breast cancer. Of vated in the development and progression of many the three studies reported, only one suggests a role for the tumours including breast cancer and its up-regulation is G allele in reducing breast cancer risk [63]. Our data, associated with invasiveness and increased metastatic which includes larger numbers of individuals, however potential of ER negative tumours [74]. The IL6 gene has shows no association with breast cancer susceptibility, Page 7 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 6: Genotype frequencies of the seven polymorphisms in subgroups of invasive breast cancer. Tumour Severity Subgroups Genotype frequencies (%) Chi square test for trend (P value) 1:1 1:2 2:2 IL1A +4845 G>T Tumour Grade Grade 1 (n = 122) 62 (50.8%) 50 (41%) 10 (8.2%) X = 0.037; p = 0.85 Grade 2 (n = 283) 151 (53.4%) 109 (38.5%) 23 (8.1%) Grade 3 (n = 216) 115 (53.2%) 82 (38%) 19 (8.8%) Nodal Involvement Absent (n = 430) 204 (47.4%) 118 (43.7%) 38 (8.8%) X = 4.75; p = 0.03* Present (n = 117) 117 (59.4%) 63 (32%) 17 (8.6%) Vascular Invasion Absent (n = 467) 243 (52%) 185 (39.6%) 39 (8.4%) X = 0.058; p = 0.81 Present (n = 117) 64 (54.7%) 42 (35.9%) 11 (9.4%) IL1B -511 C>T Tumour Grade Grade 1 (n = 126) 51 (40.5%) 59 (46.8%) 16 (12.7%) X = 0.12; p = 0.73 Grade 2 (n = 284) 150 (52.8%) 111 (39.1%) 23 (8.1%) Grade 3 (n = 216) 98 (45.4%) 93 (43.1%) 25 (11.6%) Nodal Involvement Absent (n = 434) 214 (49.3%) 179 (41.2%) 41 (9.4%) X = 0.79; p = 0.37 Present (n = 198) 90 (45.5%) 87 (43.9%) 21 (10.6%) Vascular Invasion Absent (n = 473) 224 (47.4%) 201 (42.5%) 48 (10.1%) X = 0.38; p = 0.54 Present (n = 116) 57 (49.1%) 50 (43.1%) 9 (7.8%) IL1B +3954 C>T Tumour Grade Grade 1 (n = 121) 68 (56.2%) 48 (39.7%) 5 (4.1%) X = 0.053; p = 0.82 Grade 2 (n = 279) 173 (62%) 90 (32.3%) 16 (5.7%) Grade 3 (n = 215) 131 (60.9%) 70 (32.6%) 14 (6.5%) = 0.37; p = 0.54 Nodal Involvement Absent (n = 427) 244 (57.1%) 161 (37.7%) 22 (5.2%) X Present (n = 194) 120 (61.9%) 61 (31.4%) 13 (6.7%) Vascular Invasion Absent (n = 464) 283 (61%) 157 (33.8%) 24 (5.2%) X = 0.43; p = 0.51 Present (n = 114) 66 (57.9%) 41 (36%) 7 (6.1%) IL1RN +2018 T>C Tumour Grade Grade 1 (n = 125) 55 (44%) 55 (44%) 15 (12%) X = 0.73; p = 0.40 Grade 2 (n = 280) 150 (53.6%) 107 (38.2%) 23 (8.2%) Grade 3 (n = 215) 108 (50.2%) 86 (40%) 21 (9.8%) Nodal Involvement Absent (n = 429) 216 (50.3%) 180 (42%) 33 (7.7%) X = 0.11; p = 0.74 Present (n = 196) 102 (52%) 72 (36.7%) 22 (11.2%) Vascular Invasion Absent (n = 463) 232 (50.1%) 191 (41.3%) 40 (8.6%) X = 1.34; p = 0.25 Present (n = 118) 67 (56.8%) 42 (35.6%) 9 (7.6%) IL4R +1902 A>G Tumour Grade Grade 1 (n = 137) 87 (63.5%) 44 (32.1%) 6 (4.4%) X = 0.14; p = 0.71 Grade 2 (n = 308) 195 (63.3%) 97 (31.5%) 16 (5.2%) Grade 3 (n = 228) 146 (64%) 75 (32.9%) 7 (3.1%) Nodal Involvement Absent (n = 477) 313 (65.6%) 144 (30.2%) 20 (4.2%) X = 0.11; p = 0.75 Present (n = 212) 135 (63.7%) 69 (32.5%) 8 (3.8%) Vascular Invasion Absent (n = 508) 316 (62.2%) 170 (33.5%) 22 (4.3%) X = 0.002; p = 0.96 Present (n = 129) 82 (63.6%) 40 (31%) 7 (5.4%) IL6 -174 G>C Tumour Grade Grade 1 (n = 80) 26 (32.5%) 38 (47.5%) 16 (20%) X = 0.04; p = 0.84 Grade 2 (n = 204) 78 (38.2%) 95 (46.6%) 31 (15.2%) Grade 3 (n = 159) 49 (30.8%) 83 (52.2%) 27 (17%) Page 8 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 6: Genotype frequencies of the seven polymorphisms in subgroups of invasive breast cancer. (Continued) Nodal Involvement Absent (n = 293) 100 (34.1%) 141 (48.1%) 52 (17.7%) X = 0.20; p = 0.66 Present (n = 143) 52 (36.4%) 67 (46.9%) 24 (16.8%) Vascular Invasion Absent (n = 325) 112 (34.5%) 159 (48.9%) 54 (16.6%) X = 0.001; p = 0.98 Present (n = 85) 29 (34.1%) 42 (49.4%) 14 (16.5%) IL10 -1082 G>A Tumour Grade Grade 1 (n = 80) 23 (28.8%) 37 (46.3%) 20 (25%) X = 0.37; p = 0.54 Grade 2 (n = 205) 39 (19%) 113 (55.1%) 53 (25.9%) Grade 3 (n = 158) 44 (27.8%) 79 (50%) 35 (22.2%) Nodal Involvement Absent (n = 293) 69 (23.5%) 148 (50.5%) 76 (25.9%) X = 0.84; p = 0.36 Present (n = 143) 38 (26.6%) 73 (51%) 32 (22.4%) Vascular Invasion Absent (n = 325) 87 (26.8%) 156 (48%) 82 (25.2%) X = 3.3; p = 0.07 Present (n = 85) 12 (14.1%) 49 (57.6%) 24 (28.2%) severity or survival for this polymorphism. A study on the Abbreviations related polymorphism (-592C>A) in the promoter region IL: interleukin; ER: oestrogen receptor; SNP: single was associated with a reduced breast cancer risk, although nucleotide polymorphism; UTR: untranslated region; in breast cancer patients, there was no association with PCR: polymerase chain reaction; DNA: deoxyribonucleic severity of the disease [79]. acid. Limitations Competing interests Although our study had more than twice the number of The author(s) declare that they have no competing inter- subjects than the similar studies on cytokine polymor- ests. phisms in breast cancer, it could still be argued that asso- ciations of a minor degree (Odds Ratio < 1.5) of the Authors' contributions SPB, IAFA and SEH carried out patient recruitment, the genetic markers studied or other related markers may have been missed. For example, to detect a rare marker (of fre- molecular genetic studies and drafted the manuscript. SSC quency 10%) associated with a 1.3 times increased risk of reviewed the pathology and drafted the manuscript. SPB breast cancer (Odds Ratio = 1.3) with a power of 80% and and AC participated in the design of the study and per- type I error of 0.5%, we would need a sample size of 2400 formed the statistical analysis. AGW, NJB and MWR con- patients and controls. The second limitation is that a ceived of the study, and participated in its design and small proportion of our control population would coordination and helped to draft the manuscript. All develop breast cancer in their lifetime. However, it is gen- authors read and approved the final manuscript. erally considered difficult to obtain an ideal control cohort for genetic epidemiologic studies in solid cancers Acknowledgements We would like to thank Helen Cramp, Jane McDaid and Claire Greaves for mainly due to the delayed onset of the disease. The prog- help with recruitment and genotyping, Dan Connley for data management, nostic markers used for assessing breast cancer severity in and all the people who took part in the study. AC is funded by the York- this study were limited to grade, lymph nodal status and shire Cancer Research. We would also like to thank the Royal College of vascular invasion due to limited information available on Surgeons of Edinburgh who provided financial assistance towards consum- other indices such as hormone receptor status and tumour ables for this study. size. Conclusion The results from our study do not support the hypothesis that the cytokine polymorphisms studied [IL1A +4845G>T, IL1B -511C>T, IL1B +3954C>T, IL1RN +2018T>C, IL4R -1902A>G, IL6-174G>C and IL10- 1082G>A] are associated with breast cancer susceptibility and severity. Minor influences and associations with sub- groups of phenotypes may exist, but are unlikely to be of any major clinical significance. Page 9 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 1 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1A +4845 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1A +4845 polymorphism. Log Rank test statistic = 1.52; df = 2; p = 0.47 (n = 482). Page 10 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 2 th or metastases in invasive breast cancer for the genotypes of the IL1B -511 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B -511 polymorphism. Log Rank test statistic = 5.07; df = 2; p = 0.08 (n = 484). Page 11 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 3 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B +3954 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1B +3954 polymorphism. Log Rank test statistic = 2.71; df = 2; p = 0.26 (n = 479). Page 12 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 4 th or metastases in invasive breast cancer for the genotypes of the IL1RN +2018 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL1RN +2018 polymorphism. Log Rank test statistic = 4.32; df = 2; p = 0.12 (n = 481). Page 13 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Figure 5 shows the time to death or metastases in invasive breast cancer for the genotypes of the IL4R +1902 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL4R +1902 polymorphism. Log Rank test statistic = 2.07; df = 2; p = 0.35 (n = 528). Page 14 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 6 th or metastases in invasive breast cancer for the genotypes of the IL6 -174 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL6 -174 polymorphism. Log Rank test statistic = 0.16; df = 2; p = 0.92 (n = 333). Page 15 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 shows the time to dea Figure 7 th or metastases in invasive breast cancer for the genotypes of the IL10 -1082 polymorphism shows the time to death or metastases in invasive breast cancer for the genotypes of the IL10 -1082 polymorphism. Log Rank test statistic = 1.34; df = 2; p = 0.51 (n = 332). Page 16 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 show iew four polymorph Figure 8 ) sho s the wing pai linkage isms on chromosome 2q13 rw di is sequi e D' valu libriu es m (in percentage) be plot (obtained using Ha tween the plov- shows the linkage disequilibrium plot (obtained using Haplov- iew) showing pairwise D' values (in percentage) between the four polymorphisms on chromosome 2q13. The markers 1, 2, 3 and 4 are IL1A +4845G>T, IL1B +3954C>T, IL1B -511 C>T and IL1RN +2018T>C respectively. Table 7: Probable frequencies of the common haplotypes in the interleukin-1 gene cluster in breast cancer and screening control cohorts. Haplotype* Frequency Case, Control Ratios Chi-square P value GCCT 0.330 471.5 : 938.5, 321.5 : 674.5 0.352 0.5529 TTCT 0.165 220.7 : 1189.3, 176.8 : 819.2 1.865 0.1720 GCTC 0.133 182.1 : 1227.9, 138.3 : 857.7 0.469 0.4934 GCTT 0.112 169.0 : 1241.0, 99.9 : 896.1 2.239 0.1346 GCCC 0.099 145.8 : 1264.2, 91.3 : 904.7 0.913 0.3392 TCCT 0.032 42.1 : 1367.9, 35.4 : 960.6 0.602 0.4376 TCTT 0.026 32.4 : 1377.6, 30.1 : 965.9 1.202 0.2729 GTCT 0.024 36.1 : 1373.9, 22.6 : 973.4 0.214 0.6440 TTCC 0.022 33.5 : 1376.5, 19.9 : 976.1 0.377 0.5394 TTTT 0.017 21.2 : 1388.8, 19.8 : 976.2 0.817 0.3661 TCCC 0.016 24.6 : 1385.4, 14.1 : 981.9 0.4 0.5271 TCTC 0.013 16.7 : 1393.3, 14.3 : 981.7 0.295 0.5873 * The haplotypes represent the four polymorphisms (IL1A +4845G>T, IL1B +3954C>T, IL1B -511C>T and IL1RN +2018T>C) in that order. Page 17 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 8: Studies of the IL1B -511C>T polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 2004 [57] 141 261 Bone marrow and solid organ donors – No association No association mixed male and female Hefler LA et al, 2005 [58] 269 227 Women visiting outpatient dept for No association No association Caucasian various reasons Our study 703 489 Women with normal mammograms No association No association British Caucasian from screening population Table 9: Studies of the IL1B +3954C>T polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Hefler LA et al, 2005 [58] 269 227 Women visiting outpatient dept for No association No association Caucasian various reasons Our study 691 420 Women with normal mammograms No association No association British Caucasian from screening population Table 10: Studies of the IL6 -174G>C polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 144 224 Bone marrow and solid organ No association No association mixed 2004 [57] donors – male and female Hefler LA et al, 269 227 Women visiting outpatient OR = 1.5 (1.04– No association Caucasian 2005 [58] dept for various reasons 2.3)* for GC vs. GG OR = 2 (1.1– 3.6)* for CC vs. GG Skerrett DL et al, 88 102 Maternal cord blood samples No association No association mixed 2005 [59] Saha A et al, 2003 26 95 Unknown No association Not studied Asian Indian [60] DeMichelle A et al, 80 0 - Not studied C allele associated with 4 mixed 2003 [61] year disease free survival (p = 0.02) and overall survival (p = 0.01) in node positive patients Iacopetta B et al, 256 0 - Not studied C allele associated with high mixed 2004 [62] grade (p = 0.04) and CC genotype associated with poor survival (p = 0.03) Our study 497 490 Women with normal No association No association British Caucasian mammograms from screening population OR: Odds Ratio Page 18 of 21 (page number not for citation purposes) BMC Cancer 2006, 6:188 http://www.biomedcentral.com/1471-2407/6/188 Table 11: Studies of the IL10 -1082G>A polymorphism in breast cancer. Reference Numbers studied Type of controls Susceptibility Severity Ethnicity Cancer Controls Smith KC et al, 2004 [57] 129 223 Bone marrow and solid No association No association Mixed organ donors – male and female Giordani L et al, 2003 125 100 Female outpatients without OR = 0.58 (0.32–1.07) for Not studied unknown [63] breast cancer AG vs. AA OR = 0.38 (0.14–0.99) for GG vs. AA Skerrett DL et al, 2005 88 102 Maternal cord blood No association No association mixed [59] samples Wu JM et al, 2005 [64] 87 0 - Not studied No association mixed Our study 497 498 Women with normal No association No association British Caucasian mammograms from screening population OR: Odds Ratio 13. Obiri NI, Siegel JP, Varricchio F, Puri RK: Expression of high-affin- References ity IL-4 receptors on human melanoma, ovarian and breast 1. Smyth MJ, Cretney E, Kershaw MH, Hayakawa Y: Cytokines in can- carcinoma cells. Clin Exp Immunol 1994, 95(1):148-155. cer immunity and immunotherapy. 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Alamartine E, Berthoux P, Mariat C, Cambazard F, Berthoux F: Inter- leukin-10 promoter polymorphisms and susceptibility to skin squamous cell carcinoma after renal transplantation. J Invest Dermatol 2003, 120(1):99-103. Publish with Bio Med Central and every 79. Langsenlehner U, Krippl P, Renner W, Yazdani-Biuki B, Eder T, Kop- scientist can read your work free of charge pel H, Wascher TC, Paulweber B, Samonigg H: Interleukin-10 pro- moter polymorphism is associated with decreased breast "BioMed Central will be the most significant development for cancer risk. Breast Cancer Res Treat 2005, 90(2):113-115. disseminating the results of biomedical researc h in our lifetime." Sir Paul Nurse, Cancer Research UK Pre-publication history Your research papers will be: The pre-publication history for this paper can be accessed available free of charge to the entire biomedical community here: peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central http://www.biomedcentral.com/1471-2407/6/188/pre yours — you keep the copyright pub BioMedcentral Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp Page 21 of 21 (page number not for citation purposes)

Journal

BMC CancerSpringer Journals

Published: Dec 1, 2006

Keywords: cancer research; oncology; surgical oncology; health promotion and disease prevention; biomedicine, general; medicine/public health, general

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