Background: Genome-wide association studies have shown that the 8q24 region harbours multiple independent cancer susceptibility loci and it was also defined as the “susceptibility cancer region.” Thus, it could be hypothesized that genetic variants within this region could play a role in the risk of differentiated thyroid carcinoma (DTC).

Methods: Six single-nucleotide polymorphisms within 8q24 were analyzed, previously associated with the risk of cancer (i.e., rs6983267, rs1447295, rs10808556, rs7000448, rs13254738, and rs13281615) in a population of 1,250 patients affected by DTC and 1,250 controls from Central and Southern Italy.

Results: A strong association between smoking habit and risk of DTC was found [OR, 1.63; 95% confidence interval (CI), 1.39–1.91; P < 10−6]. The polymorphisms rs10808556 and rs1447295 showed an association with the risk of DTC (the strongest were the heterozygotes with OR, 1.38; 95% CI, 1.13–1.68 and OR, 1.35; 95% CI, 1.02–1.78, respectively), but, overall, they were unable to reach the statistically significant threshold following Bonferroni's correction.

Conclusions: Present study suggested a limited involvement of polymorphisms within 8q24 region in relation to the risk of DTC in Central and Southern Italians.

Impact: The exclusion of a relationship between DTC and 8q24 among Italians further highlights the tissue-specificity of this chromosomal segment in relation to human cancer and stresses the importance of other population-specific cofactors. Cancer Epidemiol Biomarkers Prev; 22(11); 2121–5. ©2013 AACR.

In the human genome a segment of 1Mb within 8q24, thereafter termed “susceptibility cancer region of 8q24” (SR8q24), was associated with increased risk of prostate, colon, breast, and ovarian cancer, in genome-wide association studies (GWAS). However, SR8q24 did not reach the genome-wide statistical significance threshold in previous GWAS conducted on differentiated thyroid carcinoma (DTC; refs. 1, 2). Then, several authors conducted hypothesis-driven case–control studies to verify specific single-nucleotide polymorphisms (SNP) within SR8q24 in relation to DTC. Positive associations were found among Polish (3) and British (4), whereas lack of associations was found in Spanish (5) and Texans (6). In summary, the findings were poorly reproducible also because a limited statistical power of some studies. Here, a study carried out on 1,250 patients with DTC and 1,250 healthy controls living in regions of central and southern Italy is presented. It has the adequate statistical power to evaluate six haplotype tagging SNPs to ascertain whether SR8q24 could constitute a genomic risk region also among Italians.

Study population

Cases and controls, all Caucasians, were volunteers collected at the University Hospital of Cisanello (Pisa, Italy), as described elsewhere (7). They gave their written informed consent and the study was cleared by the local Ethical Committee.

SNP selection, statistical power calculations, DNA extraction, and genotyping

rs6983267 and rs1447295 were chosen because they were previously associated with DTC. The inclusion criteria for the other SNPs were: (i) haplotype tagging SNP of linkage disequilibrium blocks as described in ref. (8), (ii) associated with the risk of human cancer in at least five independent studies, and (iii) minor allele frequency (MAF) more than 0.05 in Caucasians. The rs10808556, rs7000448, rs13254738, and rs13281615 passed these criteria.

The study had the statistical power of 80% to detect an expected OR of 1.36 for rs6983267 (the one described by; ref. 3), considering a type I error α = 0.05 and a MAF = 0.4, in a recessive model. For SNPs with lower MAF, for example rs1447295, a minimal OR = 1.27 on per allele basis could be detected.

DNA was extracted from peripheral blood and genotyped by personnel blinded for the case/control status with the use of Predesigned TaqMan Genotyping Assays (Life Technologies, Inc.). Three percent of samples did not elicit an appropriate amount of DNA, thus the genotyping could be conducted on 1,212 cases and 1,208 controls. Two percent of DNA samples were repeated as quality control.

Statistical analyses

Hardy–Weinberg equilibrium (HWE) was tested in controls by the χ2 test. Multiple logistic regression (MLR) was used to calculate the adjusted OR (ORadj) and their 95% confidence intervals (CI), as described elsewhere (7). The Cochran-Armitage trend test was used to evaluate the best inheritance model. Bonferroni's correction was used and the novel statistical significance threshold was 8.3 × 10−3.

A minimal call rate of 98.7% was obtained (for rs13254738). The quality control was satisfactory (>99.5% of correspondence). The genotypes followed HWE. The characteristics of cases and controls are reported in Table 1. A positive association was observed between the smoking habit and the risk of DTC (OR, 1.63; 95% CI, 1.39–1.91; P < 10−6). The ORadj, the 95% CIs, and their Pass following MLR analysis of the additive models are reported in Table 2.

Table 1.

Characteristics of patients with DTC and controls

Controls n (%)Cases n (%)ORa (95% CI)P
Sex 
 Male 800 (64.0%) 317 (25.4%) Ref.  
 Female 450 (36.0%) 933 (74.6%) 5.15 (4.24–6.26) <10−6 
Age, y 
 Average 51.5 ± 11.8 45.0 ± 12.8  9.3 × 10−6 
 Median 49.0 45.0   
Body mass index 
 Average 25.7 ± 4.91 25.9 ± 3.99  0.20 
 Median 25.0 25.4   
Smoking 
 Nonsmokers 898 (71.85%) 764 (61.10%) Ref  
 Smokers + ex-smokers 352 (28.15%) 486 (38.90%) 1.63 (1.39–1.91) <10−6 
Total 1,250 1,250   
Diagnosis 
 PTC  1,130 (93.4%)   
 FTC  80 (6.6%)   
Controls n (%)Cases n (%)ORa (95% CI)P
Sex 
 Male 800 (64.0%) 317 (25.4%) Ref.  
 Female 450 (36.0%) 933 (74.6%) 5.15 (4.24–6.26) <10−6 
Age, y 
 Average 51.5 ± 11.8 45.0 ± 12.8  9.3 × 10−6 
 Median 49.0 45.0   
Body mass index 
 Average 25.7 ± 4.91 25.9 ± 3.99  0.20 
 Median 25.0 25.4   
Smoking 
 Nonsmokers 898 (71.85%) 764 (61.10%) Ref  
 Smokers + ex-smokers 352 (28.15%) 486 (38.90%) 1.63 (1.39–1.91) <10−6 
Total 1,250 1,250   
Diagnosis 
 PTC  1,130 (93.4%)   
 FTC  80 (6.6%)   

NOTE: The P-values for continuous variables are calculated with the Student's t-test. Volunteers exposed to passive cigarette smoke are grouped with nonsmokers.

Abbreviations: PTC, papillary thyroid carcinoma; FTC, follicular thyroid carcinoma.

aOR from logistic regression analysis.

Table 2.

Statistical analyses for SNPs within 8q24

ControlsDTCORb (95% CI)PcPTCORb (95% CI)PcFTCORb (95% CI)Pc
rs6983267 
T-allelea 0.49 0.49 1.01 (0.89–1.14) 0.920 0.49 1.01 (0.89–1.14) 0.888 0.48 0.96 (0.67–1.39) 0.843 
Genotypes 
 G/G 307 (25.7%) 292 (24.3%) Ref.  272 (24.3%) Ref.  20 (25.0%) Ref.  
 G/T 599 (50.1%) 630 (52.5%) 1.10 (0.84–1.43) 0.482 588 (52.4%) 1.10 (0.84–1.44) 0.488 43 (53.3%) 1.19 (0.58–2.43) 0.634 
 T/T 290 (24.2%) 278 (23.2%) 0.94 (0.69–1.28) 0.695 260 (23.3%) 0.93 (0.69–1.26) 0.637 17 (21.7%) 1.03 (0.45–2.38) 0.944 
Best modeld Dominant; Ptrend = 0.484 Dominant; Ptrend = 0.469 Dominant; Ptrend = 0.906 
 Total 1,196 1,200   1,120   80   
rs7000448 
T-allelea 0.40 0.41 1.05 (0.93–1.18) 0.455 0.41 1.05 (0.93–1.19) 0.447 0.41 1.03 (0.71–1.49) 0.883 
Genotypes 
 C/C 429 (35.8%) 423 (35.3%) Ref  395 (35.3%) Ref  28 (34.4%) Ref  
 C/T 572 (47.7%) 557 (46.5%) 1.01 (0.80–1.27) 0.993 518 (46.4%) 1.01 (0.80–1.27) 0.933 39 (49.2%) 1.06 (0.57–2.00) 0.856 
 T/T 197 (16.5%) 218 (18.2%) 1.12 (0.82–1.52) 0.472 205 (18.3%) 1.13 (0.83–1.54) 0.438 13 (16.4%) 0.95 (0.40–2.23) 0.910 
Best modeld Recessive; Ptrend = 0.282 Recessive; Ptrend = 0.265 Recessive; Ptrend = 0.993 
 Total 1,198 1,198   1,118   80   
rs10808556 
C-allelea 0.37 0.38 1.04 (0.93–1.17) 0.465 0.38 1.05 (0.93–1.18) 0.460 0.35 0.92 (0.64–1.30) 0.628 
Genotypes 
 T/T 481 (40.2%) 430 (36.0%) Ref  399 (35.7%) Ref  33 (41.8%) Ref  
 T/C 536 (44.7%) 612 (51.1%) 1.38 (1.13–1.68) 0.001 576 (51.6%) 1.38 (1.13–1.70) 0.002 36 (45.6%) 1.14 (0.66–1.96) 0.637 
 C/C 180 (15.1%) 154 (12.9%) 0.98 (0.74–1.31) 0.890 142 (12.7%) 0.97 (0.72–1.30) 0.840 10 (12.6%) 0.89 (0.39–2.02) 0.781 
Best modeld Dominant; Ptrend = 0.033 Dominant; Ptrend = 0.027 Dominant; Ptrend = 0.635 
 Total 1,197 1,196   1,117   79   
rs1447295 
A-allelea 0.06 0.066 1.10 (0.88–1.38) 0.421 0.07 1.10 (0.87–1.38) 0.418 0.05 0.83 (0.40–1.73) 0.622 
Genotypes 
 C/C 1063 (88.6%) 1043 (87.0%) Ref  973 (86.8%) Ref  71 (89.9%) Ref  
 C/A 129 (10.8%) 154 (12.8%) 1.35 (1.02–1.78) 0.035 145 (13.0%) 1.39 (1.05–1.85) 0.023 8 (10.1%) 1.02 (0.47–2.23) 0.960 
 A/A 8 (0.6%) 2 (0.2%) 0.09 (0.01–0.71) 0.027 2 (0.2%) 0.09 (0.01–0.76) 0.029 0 (0.0%)  
Best modeld Recessive; Ptrend = 0.055 Recessive; Ptrend = 0.069 Recessive; Ptrend = 0.476 
Total 1,200 1,199   1,120   79   
rs13254738 
C-allelea 0.346 0.340 0.97 (0.86–1.09) 0.635 0.345 0.99 (0.88–1.12) 0.930 0.254 0.69 (0.47–1.02) 0.06 
Genotypes 
 A/A 499 (41.7%) 525 (44.0%) Ref  489 (43.5%) Ref  36 (52.2%) Ref  
 A/C 567 (47.4%) 522 (43.8%) 0.86 (0.67–1.12) 0.250 493 (43.9%) 0.87 (0.67–1.13) 0.296 29 (42.0%) 0.75 (0.37–1.59) 0.439 
 C/C 131 (10.9%) 145 (12.2%) 0.99 (0.68–1.49) 0.960 141(12.6%) 1.04 (0.70–1.57) 0.849 4 (5.8%) 0.38 (0.10–2.02) 0.207 
Best modeld Dominant; Ptrend = 0.228 Recessive; Ptrend = 0.228 Additive; Ptrend = 0.054 
Total 1,197 1,192   1,123   69   
rs13281615 
G-allelea 0.458 0.459 1.00 (0.90–1.13) 0.934 0.460 1.01 (0.90–1.13) 0.901 0.449 0.96 (0.68–1.36) 0.833 
Genotypes 
 A/A 367 (30.7%) 326 (27.3%) Ref  313 (27.8%) Ref  13 (19.1%) Ref  
 A/G 564 (47.1%) 641 (53.6%) 1.27 (0.94–1.73) 0.125 592 (52.5%) 1.22 (0.90–1.67) 0.207 49 (72.1%) 2.22 (0.96–5.57) 0.075 
 G/G 266 (22.2%) 228 (19.1%) 0.84 (0.60–1.23) 0.341 222 (19.7%) 0.86 (0.60–1.26) 0.426 6 (8.8%) 0.47 (0.14–2.33) 0.292 
Best modeld Recessive; Ptrend = 0.058 Dominant; P-trend = 0.126 Recessive; P-trend = 0.009 
 Total 1,197 1,195   1,127   68   
ControlsDTCORb (95% CI)PcPTCORb (95% CI)PcFTCORb (95% CI)Pc
rs6983267 
T-allelea 0.49 0.49 1.01 (0.89–1.14) 0.920 0.49 1.01 (0.89–1.14) 0.888 0.48 0.96 (0.67–1.39) 0.843 
Genotypes 
 G/G 307 (25.7%) 292 (24.3%) Ref.  272 (24.3%) Ref.  20 (25.0%) Ref.  
 G/T 599 (50.1%) 630 (52.5%) 1.10 (0.84–1.43) 0.482 588 (52.4%) 1.10 (0.84–1.44) 0.488 43 (53.3%) 1.19 (0.58–2.43) 0.634 
 T/T 290 (24.2%) 278 (23.2%) 0.94 (0.69–1.28) 0.695 260 (23.3%) 0.93 (0.69–1.26) 0.637 17 (21.7%) 1.03 (0.45–2.38) 0.944 
Best modeld Dominant; Ptrend = 0.484 Dominant; Ptrend = 0.469 Dominant; Ptrend = 0.906 
 Total 1,196 1,200   1,120   80   
rs7000448 
T-allelea 0.40 0.41 1.05 (0.93–1.18) 0.455 0.41 1.05 (0.93–1.19) 0.447 0.41 1.03 (0.71–1.49) 0.883 
Genotypes 
 C/C 429 (35.8%) 423 (35.3%) Ref  395 (35.3%) Ref  28 (34.4%) Ref  
 C/T 572 (47.7%) 557 (46.5%) 1.01 (0.80–1.27) 0.993 518 (46.4%) 1.01 (0.80–1.27) 0.933 39 (49.2%) 1.06 (0.57–2.00) 0.856 
 T/T 197 (16.5%) 218 (18.2%) 1.12 (0.82–1.52) 0.472 205 (18.3%) 1.13 (0.83–1.54) 0.438 13 (16.4%) 0.95 (0.40–2.23) 0.910 
Best modeld Recessive; Ptrend = 0.282 Recessive; Ptrend = 0.265 Recessive; Ptrend = 0.993 
 Total 1,198 1,198   1,118   80   
rs10808556 
C-allelea 0.37 0.38 1.04 (0.93–1.17) 0.465 0.38 1.05 (0.93–1.18) 0.460 0.35 0.92 (0.64–1.30) 0.628 
Genotypes 
 T/T 481 (40.2%) 430 (36.0%) Ref  399 (35.7%) Ref  33 (41.8%) Ref  
 T/C 536 (44.7%) 612 (51.1%) 1.38 (1.13–1.68) 0.001 576 (51.6%) 1.38 (1.13–1.70) 0.002 36 (45.6%) 1.14 (0.66–1.96) 0.637 
 C/C 180 (15.1%) 154 (12.9%) 0.98 (0.74–1.31) 0.890 142 (12.7%) 0.97 (0.72–1.30) 0.840 10 (12.6%) 0.89 (0.39–2.02) 0.781 
Best modeld Dominant; Ptrend = 0.033 Dominant; Ptrend = 0.027 Dominant; Ptrend = 0.635 
 Total 1,197 1,196   1,117   79   
rs1447295 
A-allelea 0.06 0.066 1.10 (0.88–1.38) 0.421 0.07 1.10 (0.87–1.38) 0.418 0.05 0.83 (0.40–1.73) 0.622 
Genotypes 
 C/C 1063 (88.6%) 1043 (87.0%) Ref  973 (86.8%) Ref  71 (89.9%) Ref  
 C/A 129 (10.8%) 154 (12.8%) 1.35 (1.02–1.78) 0.035 145 (13.0%) 1.39 (1.05–1.85) 0.023 8 (10.1%) 1.02 (0.47–2.23) 0.960 
 A/A 8 (0.6%) 2 (0.2%) 0.09 (0.01–0.71) 0.027 2 (0.2%) 0.09 (0.01–0.76) 0.029 0 (0.0%)  
Best modeld Recessive; Ptrend = 0.055 Recessive; Ptrend = 0.069 Recessive; Ptrend = 0.476 
Total 1,200 1,199   1,120   79   
rs13254738 
C-allelea 0.346 0.340 0.97 (0.86–1.09) 0.635 0.345 0.99 (0.88–1.12) 0.930 0.254 0.69 (0.47–1.02) 0.06 
Genotypes 
 A/A 499 (41.7%) 525 (44.0%) Ref  489 (43.5%) Ref  36 (52.2%) Ref  
 A/C 567 (47.4%) 522 (43.8%) 0.86 (0.67–1.12) 0.250 493 (43.9%) 0.87 (0.67–1.13) 0.296 29 (42.0%) 0.75 (0.37–1.59) 0.439 
 C/C 131 (10.9%) 145 (12.2%) 0.99 (0.68–1.49) 0.960 141(12.6%) 1.04 (0.70–1.57) 0.849 4 (5.8%) 0.38 (0.10–2.02) 0.207 
Best modeld Dominant; Ptrend = 0.228 Recessive; Ptrend = 0.228 Additive; Ptrend = 0.054 
Total 1,197 1,192   1,123   69   
rs13281615 
G-allelea 0.458 0.459 1.00 (0.90–1.13) 0.934 0.460 1.01 (0.90–1.13) 0.901 0.449 0.96 (0.68–1.36) 0.833 
Genotypes 
 A/A 367 (30.7%) 326 (27.3%) Ref  313 (27.8%) Ref  13 (19.1%) Ref  
 A/G 564 (47.1%) 641 (53.6%) 1.27 (0.94–1.73) 0.125 592 (52.5%) 1.22 (0.90–1.67) 0.207 49 (72.1%) 2.22 (0.96–5.57) 0.075 
 G/G 266 (22.2%) 228 (19.1%) 0.84 (0.60–1.23) 0.341 222 (19.7%) 0.86 (0.60–1.26) 0.426 6 (8.8%) 0.47 (0.14–2.33) 0.292 
Best modeld Recessive; Ptrend = 0.058 Dominant; P-trend = 0.126 Recessive; P-trend = 0.009 
 Total 1,197 1,195   1,127   68   

aMinor allele frequency.

bAdjusted by age, gender, body mass index, and smoke.

cP association of the OR from multivariate logistic regression analysis adjusted for covariates.

dBest model for DTC, according to the Cochran–Armitage trend test. Genotypes could not sum up to the full sample set due to less than 100% genotyping call rates.

For rs13254738 and rs13281615, a marginal statistical significance association was observed for the follicular type (FTC), but it did not accomplish with the statistical threshold set after Bonferroni's correction. For rs10808556, the heterozygotes showed an increased risk (OR, 1.38; 95% CI, 1.13–1.68; Pass = 0.001), whereas the homozygotes did not showed any association. The best model (dominant) showed a Ptrend = 0.033 and the carriers of the C allele had an ORadj = 1.28 (95% CI, 1.06–1.54; Pass = 0.010). For rs1447295, the heterozygotes showed an OR, 1.35 (95% CI, 1.02–1.78; Pass = 0.035). However, all the associations were not statistically significant following Bonferroni's correction.

In the present study, a positive association between the risk of DTC and smoking habit was found. This is conceivable given that cigarette smoke was associated with DTC predisposing conditions such as goiter, thyrotoxicosis, increased serum thyroglobulin, thyroid volume, and multiple nodules. Concerning SR8q24, no evidence of associations was found between specific haplotype tagging SNPs and the risk of DTC or papillary thyroid carcinoma (PTC). Thus, at least among Italians, SR8q24 seems not to be involved in the etiology of thyroid carcinomas. When looking more attentively to differences among studies, it should be noticed that the associations between SR8q24 and risk were detectable in populations with low incidences of DTC [in Poland and United Kingdom the age-standardized rates are 4.1 and 3.8 cases out of 100,000, respectively; International Agency for Research on Cancer (IARC), EUCAN database], whereas they were lacking in Texans and Italians where the incidence is much higher (10.8, data from Center for Disease Control and Prevention database, and 13.5, EUCAN database, respectively). Thus, it could be hypothesized that, when other environmental risk factors are prevailing, the small-size effect of SR8q24 is not measurable.

No potential conflicts of interest were disclosed.

Conception and design: M. Cipollini, D. Landi, R. Elisei, F. Gemignani, S. Landi

Development of methodology: M. Cipollini, F. Gnudi, F. De Paola

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): G. Figlioli, S. Bramante, L. Maiorano, A. Cecchini, L. Damicis, T. Frixa, D. Landi, L. Cancemi, C. De Santi, A. Cristaudo, A. Bonotti, C. Romei, R. Elisei, G. Pellegrini

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Cipollini, S. Garritano, F. Gnudi, F. De Paola, T. Frixa, R. Foddis, C. Romei, S. Landi

Writing, review, and/or revision of the manuscript: M. Cipollini, G. Figlioli, O. Melaiu, A. Cristaudo, R. Elisei, S. Landi

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): S. Garritano, A. Cecchini, L. Damicis, T. Frixa, D. Landi, C. Romei

Study supervision: R. Elisei, R. Barale, S. Landi

This study was financially supported by a grant from the Istituto Toscano Tumori (ITT; year 2010) and AIRC (Associazione Italiana Ricerca Cancro) that supported the study with an investigator grant (year 2008). ITT and MIUR (Italian Ministry of the Research, PRIN) financed the costs of the reagents and AIRC and MIUR financed the costs of the fellowships.

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