Journal of Cancer Prevention 2018; 23(3): 147-152
Published online September 30, 2018
https://doi.org/10.15430/JCP.2018.23.3.147
© Korean Society of Cancer Prevention
Thaís da Rocha Boeira1, Janaina Coser2,3, Jonas Michel Wolf1, Bruna Klahr Manggini Cardinal2, Ivana Grivicich1, Daniel Simon1, and Vagner Ricardo Lunge1
1Graduate Program in Cellular and Molecular Biology Applied to Health, Lutheran University of Brazil (ULBRA), Canoas, Brazil, 2Biomedicine Course, University of Cruz Alta (UNICRUZ), Cruz Alta, Brazil, 3Graduate Program in Integral Health Care, University of Cruz Alta/Regional University of the Northwestern Rio Grande do Sul state (UNICRUZ/UNIJUÍ), Cruz Alta/Ijuí, Brazil
Correspondence to :
Jonas Michel Wolf, Graduate Program in Cellular and Molecular Biology Applied to Health, Lutheran University of Brazil (ULBRA), Av. Farroupilha, 8001 - São José, Canoas - RS, 96923-101, Brazil, Tel: +55-51-34774000 (ext. 2433), Fax: +55-51-34774000 (ext. 2433), E-mail: jonasmwolf@gmail.com, ORCID: Jonas Michel Wolf,
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cervical cancer (CC) is caused by persistent human papillomavirus (HPV) infection and affects women worldwide. The progression of an HPV persistent infection to CC is influenced by genetic factors. Three single nucleotide polymorphisms (SNPs) in
Keywords: Cervical cancer, Single nucleotide polymorphisms, Case-control study
Cervical cancer (CC) is the fourth most common cancer in women, with approximately 528,000 new cases in the world each year.1 In 2016, 16,340 new cases of CC were reported in Brazil. It is one of the top five most common cancer types in all states of the country.2 Human papillomavirus (HPV) persistence is a key factor in the development of CC, inducing carcinogenesis by the integration of the whole genome into the cell host chromosome, transformation of the cervical cells and appearance of intraepithelial lesions that progress to CC.3 However, most HPV-infected women do not progress to CC, suggesting that other factors are related to this outcome. Socio-demographic (e.g., income, educational level, age, and multiparity) and behavioral (e.g., age at first intercourse, number of sexual partners) factors were already demonstrated to have a direct relationship to HPV exposure and persistence in the uterine cervix and progression to precancerous lesions.3 In addition, human genetic factors have also a pivotal influence in the development of CC.4,5 Several single nucleotide polymorphisms (SNPs) of the human genome have been associated with CC in the last years.4,5 These SNPs are present in genes of different cell pathways, such as tumor suppression, inflammation, apoptosis and cell cycle regulation, DNA repair, cell migration, cell signaling and viral entry into the cell.4,5
The
Few studies investigated the association of SNPs with CC in South America populations. Recently, we investigated some other SNPs previously associated to CC in genes related to immune response (
The CC patients (n = 106) were recruited at the Center of High Complexity in Oncology (
All women underwent cell sampling with buccal (case group) or cervical (control group) exfoliation using cytobrush and stored in a buffer solution (EDTA pH 8.0 0.01M, SDS 0.03 M) at −20°C until analysis. DNA extraction and HPV detection/typing were performed as described in previous studies.10,11
A fragment of 199 bp of the
Data were analyzed using the Statistical Package for Social Sciences ver. 18.0 (PASW; IBM Co., Armonk, NY, USA). The Student
Socio-demographic and behavioral data in the sample studied are presented in Table 1. In the comparison of these characteristics, cases and controls did not present statistically significant differences, except for parity (94.3% in cases vs. 55.5% in controls;
Allele frequencies of the SNPs rs1042522, rs1800566, and rs2305809 are shown in Table 2. It is noteworthy that MAF were 28.9% of Pro allele (nucleotide G) for rs1042522, 25.3% of Ser allele (nucleotide T) for the rs1800566, and 49.8% of T allele/nucleotide for rs2305809. The allele frequencies did not show statistically significant differences between the groups evaluated. The frequencies observed in the population for these three SNPs are in Hardy-Weinberg equilibrium.
Genetic models analysis of the SNPs rs1042522, rs1800566, and rs2305809 are shown in Table 3. Additive, dominant and recessive models analysis for rs1042522 and rs1800566 SNPs did not present significant differences between CC cases and control group in bivariate and logistic regression analysis (Table 3). However, the recessive genetic model (C/C + C/T) for rs2305809 located in the upstream region of the
In the analysis of the patient’s data, CC women presented a mean age of 50.5 years, consistent with the incidence peak of this disease in Brazil.2 MAF were evaluated for the three SNPs, demonstrating similar data to other women populations from Latin America (32% for Pro in rs1042522, 33% for Ser in rs1800566, 43% for T in rs2305809) and Europe (29% for Pro in rs1042522, 21% for Ser in rs1800566, 47% for C in rs2305809).13 The small differences between the MAF are probably related to the ethnic profile of the samples evaluated in these different populations. In the comparative analysis between cases and controls, we detected an association between the recessive genetic model (C/C + C/T) in rs2305809 and protection for CC. Further, the presence of allele T demonstrated a trend of risk for CC. The other SNPs studied were not associated with CC.
Our results suggest non-association between SNP rs1042522 in
We also have not found an association between SNP rs1800566 and CC. Studies associating rs1800566 in the
Finally, there are two previous reports demonstrating significant associations of the SNP rs2305809 in
Other polymorphisms are located in non-coding and coding regions of the
In conclusion, it was detected a protective association of the SNP rs2305809 in the recessive genetic model (C/C + C/T) with CC in women from southern Brazil. Prospective cohort studies will be necessary to ascertain this association observed in the present case-control study as well as to define the relative risk of this SNP for CC. In addition, studies in populations with different genetic backgrounds will be needed to confirm our findings since genetic influences of CC are complex.
The authors thank the staff of the Center of High Complexity in Oncology of the Ijuí, RS, and participants for their collaboration. We also thank the technicians of the Universidade de Cruz Alta (Cytopathology Laboratory), Universidade Luterana do Brasil (Molecular Diagnostics Laboratory) who performed technical support and Simbios Biotecnologia for the partial financial support. This work was also supported by Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS; Grant 1265-2551/13-4) and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES; Finance Code 001).
Financial resources to perform the laboratory analyses were obtained in the project “Study of human and viral genetic factors associated with the persistence of genital papillomavirus and progression to cervical cancer” submitted and approved in the FAPERGS/MS/CNPq/SESRS Notice n. 002/2013–Research Program for SUS: Shared health management PPSUS–2013/2015.
No potential conflicts of interest were disclosed.
Table 1. Bivariate analysis of socio-demographic and behavioral data of the case and control groups.
Variable | Case | Control | |
---|---|---|---|
Age (yr)a | 50.45 ± 14.38 | 48.12 ± 14.38 | 0.15 |
Educational levelb | |||
Complete primary education or less | 72 (68.6) | 188 (69.1) | 0.92 |
Secondary or higher education | 33 (31.4) | 84 (30.9) | |
Total household income (in Brazilian minimum monthly wage)b | |||
Household income ≥2 minimum salary | 51 (48.6) | 98 (51.0) | 0.68 |
Household income ≤1 minimum salary | 54 (51.4) | 94 (49.0) | |
Smokingb | |||
No | 81 (77.1) | 169 (85.8) | 0.06 |
Yes | 24 (22.9) | 28 (14.2) | |
Parityb | |||
No | 6 (5.7) | 142 (44.5) | < 0.01 |
Yes | 100 (94.3) | 177 (55.5) | |
Contraceptive oral useb | |||
No | 87 (82.1) | 217 (65.9) | < 0.01 |
Yes | 19 (17.9) | 107 (32.5) | |
Condom use in all sexual relationsb | |||
No | 83 (78.3) | 152 (77.6) | 0.88 |
Yes | 23 (21.7) | 44 (22.4) | |
No. of lifetime sexual partners ≥2b | |||
No | 54 (50.9) | 92 (38.0) | 0.02 |
Yes | 52 (49.1) | 150 (62.0) | |
Sexual debut at ≤18 years-oldb | |||
No | 35 (33.3) | 99 (51.8) | < 0.01 |
Yes | 70 (66.7) | 92 (48.2) |
Values are presented as mean ± SD or number (%)..
bTotals do not coincide due to the lack of data.
Table 2. Allelic frequencies of gene
Variable | Casea | Controla | Total | |
---|---|---|---|---|
Arg | 135 (70.3) | 441 (71.4) | 576 (71.1) | 0.78 |
Pro | 57 (29.7) | 177 (28.6) | 234 (28.9) | |
Pro | 131 (76.20) | 434 (72.6) | 565 (69.8) | 0.35 |
Ser | 41 (23.8) | 164 (27.4) | 205 (25.3) | |
C | 103 (48.6) | 364 (55.3) | 467 (57.7) | 0.09 |
T | 109 (51.4) | 294 (44.7) | 403 (49.8) |
Value are presented as number (%)..
bPearson’s chi-squared test.
Table 3. Analysis of genotypes and alleles of gene
Genetic model | Casea | Controla | crudeOR (95% CI) | adjustedOR (95% CI)b | ||
---|---|---|---|---|---|---|
Additive | ||||||
Arg/Arg | 47 (49.0) | 161 (52.1) | 1.00 | 1.00 | ||
Arg/Pro | 41 (42.7) | 119 (38.5) | 1.18 (0.73–1.91) | 0.50 | 1.11 (0.56–1.59) | 0.83 |
Pro/Pro | 8 (8.3) | 29 (9.4) | 0.94 (0.40–2.20) | 0.89 | 0.94 (0.36–2.43) | 0.90 |
Recessivec | ||||||
Arg/Arg + Arg/Pro | 88 (91.6) | 280 (90.6) | 1.13 (0.50–2.58) | 0.75 | 1.38 (0.68–2.79) | 0.35 |
Dominantd | ||||||
Arg/Pro + Pro/Pro | 49 (51.0) | 148 (47.9) | 1.13 (0.72–1.79) | 0.59 | 1.22 (0.58–1.60) | 0.89 |
Additive | ||||||
Pro/Pro | 49 (57.0) | 164 (54.9) | 1.00 | 1.00 | ||
Pro/Ser | 33 (38.4) | 106 (35.4) | 1.04 (0.63–1.73) | 0.87 | 1.05 (0.61–1.81) | 0.84 |
Ser/Ser | 4 (4.7) | 29 (9.7) | 0.46 (0.16–1.37) | 0.16 | 0.37 (0.12–1.19) | 0.09 |
Recessivec | ||||||
Pro/Pro + Pro/Ser | 82 (95.3) | 270 (90.3) | 2.20 (0.75–6.44) | 0.15 | 1.39 (0.75–2.58) | 0.30 |
Dominantd | ||||||
Pro/Ser + Ser/Ser | 37 (43.0) | 135 (45.1) | 0.92 (0.56–1.49) | 0.73 | 0.75 (0.44–1.26) | 0.28 |
Additive | ||||||
CC | 29 (27.4) | 101 (30.7) | 1.00 | 1.00 | ||
CT | 45 (42.5) | 162 (49.2) | 0.96 (0.57–1.64) | 0.90 | 0.64 (0.38–1.35) | 0.49 |
TT | 32 (30.2) | 66 (20.1) | 1.68 (0.93–3.04) | 0.08 | 1.82 (0.91–3.61) | 0.09 |
Recessivec | ||||||
CC + CT | 74 (69.8) | 263 (79.9) | 0.58 (0.35–0.95) | 0.03* | 0.49 (0.27–0.90) | 0.02* |
Dominantd | ||||||
CT + TT | 77 (72.6) | 228 (69.3) | 1.17 (0.72–1.91) | 0.51 | 1.07 (0.61–1.89) | 0.80 |
Value are presented as number (%)..
bAdjusted OR for parity, contraceptive oral use, age at first intercourse ≤ 18, number of lifetime sexual partners ≥2 and smoking in logistic regression analysis.
*
cRecessive genetic model (Arg/Arg + Arg/Pro vs. Pro/Pro for rs1042522, Pro/Pro + Pro/Ser vs. Ser/Ser for rs1800566, and CC + CT vs. TT for rs2305809).
dDominant genetic model (Arg/Pro + Pro/Pro vs. Arg/Arg for rs1042522, Pro/Ser + Ser/Ser vs. Pro/Pro for rs1800566, and CT + TT vs. CC for rs2305809).
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