Association of CFTR gene polymorphisms with papillary thyroid cancer
- Authors:
- Published online on: November 15, 2011 https://doi.org/10.3892/ol.2011.479
- Pages: 455-461
Abstract
Introduction
Thyroid cancer originates from either follicular or non-follicular thyroid cells (1). Follicular cancers represent the majority of cases of thyroid cancer, and are divided into papillary thyroid cancer (PTC), follicular thyroid cancer (FTC), Hürthle cell cancer (HCC) and anaplastic thyroid cancer (ATC). Among them, PTC accounts for the majority of cases recorded (1). Thyroid cancer is the most common endocrine neoplasm in the United States (1) and its incidence is on the increase, although most of this increase is attributed to a growth in detection rates (2). In Korea, the situation is similar to that of the United States. In 2007, thyroid cancer became the most common type of cancer in females (73.5 individuals per 100,000) (3). Improvements in diagnostic techniques are regarded as the main reason for this sharp increase. Similarly, PTC accounts for the majority of increased incidence (2,4).
Due to its high incidence, numerous efforts have been made to elucidate the cause of PTC. Previous studies suggested the role of genetic factors (5). In PTC, many genetic mutations have been correlated with the mitogen-activated protein kinase (MAPK) signaling pathway (5).
The cystic fibrosis transmembrane conductance regulator (CFTR) gene encodes the protein acting as the Cl− channel and as a regulator of other transporters (6). The mutation of this gene results in cystic fibrosis, which is an autosomal recessive disorder (7). Cystic fibrosis affects the epithelial tissue of various organ systems, including the respiratory, gastrointestinal and urogenital system (8). Cystic fibrosis is also associated with subclinical hypothyroidism and the expression of CFTR in the thyroid (6,9). In addition, studies have suggested the presence of CFTR-dependent iodine fluxes (6). A cohort study of cystic fibrosis revealed an increased risk of thyroid cancer in cystic fibrosis patients in addition to lymphoma and kidney neoplasms (10).
Thus, CFTR expression may be associated with the risk and/or progression of PTC. In this study, we investigated the genetic association between CFTR single nucleotide polymorphisms (SNPs) and PTC in a Korean population.
Patients and methods
Patients
In the present study, normal controls (n=323, 134 males and 189 females) and PTC patients (n=105, 30 males and 75 females) were analyzed. The PTC patients were enrolled, with their agreement, from the patients who visited Kyung Hee University Medical Center, Seoul, Republic of Korea, between October 2007 and December 2010. The control group was recruited from healthy individuals, without any thyroidal disease, who visited the same institution for health examinations. The diagnosis of PTC and nodal metastasis was confirmed by pathological examination. The average age of the studied groups was 55.7 in the patient group and 56.5 in the control group. Written informed consent was obtained from all subjects. The study was approved by the Ethics Review Committee of the Medical Research Institute, Kyung Hee University Medical Center, Seoul, Republic of Korea.
Subgroups of patients
Patients were subgrouped by size, focality, location, extranodal, cervical lymph node and angio- lymphatic invasion of cancer to investigate the possible association between clinical characteristics and SNPs of CFTR. Of the 105 PTC patients, the size of cancer was ≥1 cm in 54 patients, whereas 65 patients were found to have unifocality, but 36 patients showed multifocality. In addition, in 65 patients, the location of cancer was limited to one lobe, whereas in 36 patients, cancer was found in both lobes. Extranodal invasion waws detected in 53 patients, 29 had cervical lymph node invasion and 5 patients were diagnosed with angiolymphatic invasion (Table I).
SNP selection and genotyping
We searched for the promoter and coding SNPs of the CFTR gene. The search was conducted using the SNP database of the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/SNP, BUILD 132). SNPs were selected from the promoter regions within −1000 bp from the transcriptional start sites and coding region. The SNPs with unknown heterozygosity, with a heterozygosity ≤0.1 or with a minor allele frequency ≤0.1 in the Han Chinese and Japanese populations were excluded from the analysis. Two SNPs (rs4148682, promoter; rs213950, missense, Val470Met) were selected. DNA was isolated from peripheral blood samples, using the DNA isolation kit for blood (Roche, Indianapolis, IN, USA). Genotyping of the CFTR polymorphism was performed by direct sequencing. Polymerase chain reactions (PCRs) were performed using primers for rs4148682 (promoter) and rs213950 (missense) (Table II). The ABI PRISM 3730XL analyzer (PE Applied Biosystems, Foster City, CA, USA) was used to sequence the PCR products and SeqManII software (DNASTAR, Madison, WI, USA) was used to analyze the sequence.
Statistical analysis
For the two selected SNPs, Hardy-Weinberg equilibrium (HWE) was analyzed using the SNP Stats software (http://bioinfo.iconcologia.net/index.php?module=Snpstats) in both PTC patients and controls, and adjusted for gender and age. In addition, Helixtree (Golden Helix Inc., Bozeman, MT, USA), SNP Analyzer (ISTECH Inc., Goyang, Republic of Korea) and SPSS (SPSS Inc., Chicago, IL, USA) were used to analyze the genetic data. Linkage disequilibrium (LD) analysis was conducted using Haploview version 4.2 (Broad Institute, Cambridge, MA, USA), and Gabriel’s methods were used to construct the LD block (11). Multiple logistic regression models were used to reflect the co-dominant, dominant and recessive models. The odds ratio (OR), 95% confidence intervals (CIs) and P-value were calculated, controlling gender and age as covariates. P<0.05 was considered to be statistically significant.
Results
Table III shows the distribution of the genotypes and allele of CFTR SNPs in the study group. In addition, the multiple logistic regression model, adjusting for age and gender, was used to investigate the possible association with PTC. Various models were applied in the multiple logistic regression analysis (co-dominant 1, major allele homozygotes and heterozygotes; co-dominant 2, major allele homozygotes and minor allele homozygotes; dominant, major allele homozygotes and heterozygotes + minor allele homozygotes; recessive, major allele homozygotes + heterozygotes and minor allele homozygotes). We found that none of the SNPs [i.e., the promoter SNP (rs4148682) and the missense SNP (rs213950)] were associated with PTC. When the minor allele was used as a risk factor, no association was observed.
The association between the CFTR SNPs and the clinical characteristics of PTC are analyzed in Tables IV–VIII. We did not analyze the angiolymphatic invasion of PTC using multiple logistic regression due to the small number of angiolymphatic invasion cases (n=5). In Table IV, the CFTR SNPs were not associated with cancer size. In addition, the extranodal invasion was not associated with either genotypes or allele frequencies (Table VIII). However, the focality, location and cervical node invasion of PTC were all associated with SNPs (Tables V–VII).
Therefore, rs4148682 was associated with the risk of multifocality in PTC patients [co-dominant model 1 (T/T vs. T/G), OR=0.21, 95% CI=0.08–0.60; dominant model (T/T and T/G vs. G/G) OR=0.26, 95% CI=0.10–0.65]. In addition, the T allele positively correlated with the risk of multifocality (OR=1.92, 95% CI=1.07–3.43). Furthermore, rs213950 (missense SNP) was found to correlate with the risk of multifocality, by the logistic regression analysis. The genotypes of rs213950 decreased the risk of multifocality in the co-dominant 2 model (G/G vs. A/G, p=0.002) and the dominant model (G/G and A/G vs. A/A, p=0.002). In addition, the G allele of rs213950 correlated with an increased risk of multifocality (OR=2.00, 95% CI=1.01–3.62) (Table V). In Table VI, the genotype and allele frequencies of SNPs were analyzed by location of the cancer. rs4148682 (dominant model, p=0.049) and rs213950 (co-dominant 1 model, p=0.048; dominant model, p=0.026) correlated with the risk of bilateral lobe incidence. The G allele of rs213950 (OR=1.83, 95% CI=1.02–3.29) was also found to increase the risk of bilateral lobe thyroid cancer.
In addition, the risk of cervical lymph node invasion was associated with SNPs of CFTR. Rs4148682 was associated with an increased risk of cervical lymph node invasion of PTC in the co-dominant 2 model (p=0.024) and the dominant model (p=0.023). Similar to rs4148682, rs213950 showed an association with the risk of cervical node invasion (co-dominant 2 model, p=0.028; dominant model, p=0.044).
However, the G allele, rather than the T allele, increased the risk of cervical lymph node invasion of PTC (OR=2.13, 95% CI=1.14–3.99). In addition, the A allele of rs213950 was associated with an increased risk of cervical lymph node invasion in PTC patients (OR=2.07, 95% CI=1.11–3.87).
Genotype distributions of the two SNPs analyzed, other than for the distribution of rs213950 with multifocality, were in HWE (P>0.05, data not shown). In the case of rs213950 with multifocality, the P-value of the HWE test was 0.027 and showed deviation from HWE [G/G (50.0%), A/G (27.8%), A/A (22.2%); A (36.1%), G (63.9%)].
The results of LD testing and of haplotype testing using Haploview 4.2 are shown in Fig. 1. The LD block was constructed between rs213950 and rs4148682 (D’≥0.95, r2≥0.8) (Fig. 1).
Our findings suggest a possible association between CFTR and the clinical characteristics of PTC in a Korean population. The T allele of rs4148682 and the G allele of rs213950 were correlated with the risk of multifocality and bilateral location of the PTC. Conversely, the G allele of rs4148682 and the A allele of rs213950 were associated with cervical lymph node metastasis.
Discussion
The aim of the present study was to evaluate the genetic association between the CFTR gene and PTC development in a Korean population. We also analyzed the relationship between the clinical characteristics of PTC and the CFTR gene.
The prognosis of thyroid cancer is generally good (2); however, it is crucial to identify patients at higher risk of recurrence in order to provide appropriate monitoring and treatment. The association between various factors, such as tumor size, multifocality and clinical outcomes have been reported in patients with PTC (12). We performed analyses to identify independent correlations between the CFTR mutation status and PTC. We found no significant relationship between the CFTR gene and the development of PTC. However, the CFTR gene correlated with the clinical characteristics. Thus, the promoter SNP (rs4148682, −175T/G) and the missense SNP (rs213950, Val470Met) were associated with multifocality, bilateral location in the thyroid lobes and cervical lymph node metastasis of the PTC. Multifocality correlated with LN metastasis and predicted tumor recurrence in previous studies. Therefore, the significant association between the CFTR gene and clinical characteristics of PTC suggest that the genetic mutation of CFTR is capable of affecting the outcome of PTC patients (13,14).
The best known mutations in PTC are the point mutation of the v-raf murine sarcoma viral oncogene homolog B1 (BRAF), the rat sarcoma proto-oncogenes (RAS genes) and the rearrangement of RET/PTC, which is capable of triggering the MAPK signaling pathway (5). These genetic alternations were observed in more than 70% of PTC patients. The point mutation of BRAF is the most common genetic alternation and is present in approximately 45% of cases of PTC. Some of the other genetic alternations, such as the point mutation of RET/PTC3 rearrangement and the V600E mutation of the BRAF gene, suggest an aggressive phenotype and poor outcome in PTC patients (5,12,15). The BRAF mutation was even considered a predictor of recurrence in PTC patients with extra-thyroid invasion and lymph node metastasis (12).
A defect of the CFTR gene results in cystic fibrosis, which affects the epithelial tissue of several organs, such as the sweat duct, airway, pancreas, vas deference and intestine, although lung disease is the most significant cause of mortality in cystic fibrosis (16,17). The most noteworthy feature of cystic fibrosis is the chronic bacterial infection of the airways, which results in bronchiectasis. Cystic fibrosis is also correlated with an increased risk of cancer, including thyroid cancer (10). The mutation of the CFTR gene was significantly associated with lung and pancreatic cancer in previous reports (18,19). Although the increased risk of thyroid cancer (OR=9.8, 95% CI=1.2–35.5) may result from either frequent exposure to X-ray or from surveillance bias due to intensive follow up (10), the findings of the present study showed a possible association between genetic factors and thyroid cancer in cystic fibrosis patients.
The CFTR protein regulates various channels and transporters and the thyroid hormones stimulate the expression of the CFTR gene in the kidney (20). Subclinical hypothyroidism was observed in cystic fibrosis patients and CFTR appears to mediate the iodide ion fluxes. Therefore, the CFTR protein may affect thyroid hormone production (6). This effect may explain the association that we found between the clinical features of PTC and CFTR SNPs. To the best of our knowledge, this is the first study on the association between the CFTR gene and PTC in a Korean population.
However, the present study has certain limitations. The number of participants was relatively small; therefore, the power of this study may be limited. The observed insignificant association between CFTR SNPs and PTC may result from the relatively small sample size. In addition, the control group was not investigated with thyroid ultrasound and possible undiagnosed PTC may therefore exist in this group. However, the incidence of thyroid cancer was 43.1 per 100,000 individuals in Korea in 2007 (3), and the possible size of misclassification is likely to be limited.
In this study, the association between the CFTR gene and PTC development, and the relationship between the clinical characteristics of PTC and CFTR were analyzed. No significant correlation was found between the CFTR gene and the development of PTC.
However, the T allele of rs4148682 and the G allele of rs213950 were correlated with the risk of multifocality and bilateral location of the cancer (i.e., in both thyroid lobes) in PTC. On the other hand, the G allele of rs4148682 and the A allele of rs213950 showed an association with cervical lymph node metastasis. This result suggested that CFTR potentially affects the clinical features and prognosis of PTC.
References
Brown RL, de Souza JA and Cohen EE: Thyroid cancer: burden of illness and management of disease. J Cancer. 2:193–199. 2011. View Article : Google Scholar : PubMed/NCBI | |
Davies L and Welch HG: Increasing incidence of thyroid cancer in the United States, 1973–2002. JAMA. 295:2164–2167. 2006. | |
Jung KW, Park S, Kong HJ, et al: Cancer statistics in Korea: incidence, mortality and survival in 2006–2007. J Korean Med Sci. 25:1113–1121. 2010. | |
Lee JI, Kim SH, Tan AH, et al: Decreased health-related quality of life in disease-free survivors of differentiated thyroid cancer in Korea. Health Qual Life Outcomes. 8:1012010. View Article : Google Scholar : PubMed/NCBI | |
Nikiforov YE: Thyroid carcinoma: molecular pathways and therapeutic targets. Mod Pathol. 21(Suppl 2): S37–S43. 2008. View Article : Google Scholar : PubMed/NCBI | |
Li H, Ganta S and Fong P: Altered ion transport by thyroid epithelia from CFTR(−/−) pigs suggests mechanisms for hypothyroidism in cystic fibrosis. Exp Physiol. 95:1132–1144. 2010.PubMed/NCBI | |
Gene: ENTREZ GENE. http://www.ncbi.nlm.nih.gov/sites/entrez?.db:gene. | |
Wilschanski M and Durie PR: Patterns of GI disease in adulthood associated with mutations in the CFTR gene. Gut. 56:1153–1163. 2007. View Article : Google Scholar : PubMed/NCBI | |
Devuyst O, Golstein PE, Sanches MV, et al: Expression of CFTR in human and bovine thyroid epithelium. Am J Physiol. 272:C1299–C1308. 1997.PubMed/NCBI | |
Johannesson M: Cancer risk among patients with cystic fibrosis and their first-degree relatives. Int J Cancer. 125:2953–2956. 2009. View Article : Google Scholar : PubMed/NCBI | |
Gabriel SB, Schaffner SF, Nguyen H, et al: The structure of haplotype blocks in the human genome. Science. 296:2225–2229. 2002. View Article : Google Scholar : PubMed/NCBI | |
Xing M, Westra WH, Tufano RP, et al: BRAF mutation predicts a poorer clinical prognosis for papillary thyroid cancer. J Clin Endocrinol Metab. 90:6373–6379. 2005. View Article : Google Scholar : PubMed/NCBI | |
Baudin E, Travagli JP, Ropers J, et al: Microcarcinoma of the thyroid gland: the Gustave-Roussy Institute experience. Cancer. 83:553–559. 1998. View Article : Google Scholar : PubMed/NCBI | |
Sampson RJ, Oka H, Key CR, Buncher CR and Iijima S: Metastases from occult thyroid carcinoma. An autopsy study from Hiroshima and Nagasaki, Japan. Cancer. 25:803–811. 1970. View Article : Google Scholar : PubMed/NCBI | |
Romei C, Ciampi R, Faviana P, et al: BRAFV600E mutation, but not RET/PTC rearrangements, is correlated with a lower expression of both thyroperoxidase and sodium iodide symporter genes in papillary thyroid cancer. Endocr Relat Cancer. 15:5112008. View Article : Google Scholar : PubMed/NCBI | |
Scholte BJ: Thyroid glands from pigs with cystic fibrosis, old issues new ways. Exp Physiol. 95:11312010. View Article : Google Scholar : PubMed/NCBI | |
Davis PB: Cystic fibrosis since 1938. Am J Respir Crit Care Med. 173:4752006. View Article : Google Scholar : PubMed/NCBI | |
McWilliams RR, Petersen GM, Rabe KG, et al: Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutations and risk for pancreatic adenocarcinoma. Cancer. 116:203–209. 2010.PubMed/NCBI | |
Li Y, Sun Z, Wu Y, et al: Cystic fibrosis transmembrane conductance regulator gene mutation and lung cancer risk. Lung Cancer. 70:14–21. 2010. View Article : Google Scholar : PubMed/NCBI | |
De Andrade Pinto AC, Barbosa CM, Ornellas DS, et al: Thyroid hormones stimulate renal expression of CFTR. Cell Physiol Biochem. 20:83–90. 2007.PubMed/NCBI |