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Cancer Research UK Human Cancer Genetics Research Group, Department of Oncology, University of Cambridge (A.C., F.L., S.M., J.L., S.A., C.L., P.D.P., A.M.D., B.A.J.P.), Cancer Research UK Genetic Epidemiology Group (P.L.S.), and Department of Public Health and Primary Care (R.L.), Strangeways Research Laboratories, Cambridge CB1 8RN, United Kingdom; Ranier Technology Ltd., Greenhouse Park Innovation Center (S.M.), Cambridge CB1 5AS, United Kingdom; and East Anglican Medical Genetics Service Molecular Genetics Laboratory, Addenbrooke’s Hospital (J.W.), Cambridge CB2 2FF, United Kingdom
Address all correspondence and requests for reprints to: Dr. Arancha Cebrian, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, United Kingdom. E-mail: arancha{at}srl.cam.ac.uk.
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Abstract |
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 Top Abstract IntroductionPatients and MethodsResultsDiscussionReferences |
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Objectives: The objective of this study was to explore the possibility that susceptibility in these cases results from low penetrance alleles of RET, its coreceptors, and ligands.
Design: We carried out an association study in 135 sporadic MTC (sMTC) patients and 533 controls from the United Kingdom population.
Results and Conclusions: We analyzed 33 polymorphisms in all nine genes involved in the glial cell line-derived neurotropic factor receptor-
(GFR)-RET complex. This is the first association study in which all genes involved in this complex have been investigated for susceptibility to sMTC. We did not find any association between single nucleotide polymorphisms in the exonic regions of the GFR2, GFR3, GFR4, glial cell line-derived neurotropic factor, neurturin, or persephin genes and risk of developing sMTC. We found a strong association between the disease and specific haplotypes of RET. We not only confirmed the previously described association with G691S and S904S (for heterozygotes: odds ratio, 1.85; range, 1.22–2.82; P = 0.004), but we found a novel protective effect associated with a specific haplotype (odds ratio, 0.39; range, 0.21–0.72; P = 0.005) revealing the existence of different genetic variants in the RET oncogene that either increase or decrease risk of sMTC.
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Introduction |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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The RET protooncogene encodes a cell membrane tyrosine kinase receptor protein whose ligands belong to the glial cell line-derived neurotropic factor (GDNF) family. RET functions as a multicomponent receptor complex that includes GDNF receptor- (GFR) coreceptors and RET. Four different GFR coreceptors have been characterized (GFR1 to GFR4), which determine the ligand specificity of the GFR-RET complex. The ligands are GDNF (MIM 600837), neurturin (NRTN; MIM 602018), artemin (ARTN; MIM 603886), and persephin (PSPN; MIM 602921). These bind to GFR1 to 4 with different affinities (6). Somatic RET mutations have been found in 23–69% of sMTC tumor tissues (7), but no tumor mutations have been described in any of the RET coreceptors or ligands in sMTC. However, common polymorphisms in any of the genes coding for the receptor complex could alter its function and act as low penetrance alleles for tumor susceptibility and progression. Indeed, several previous studies have reported associations between single nucleotide polymorphisms (SNPs) in RET [IV1S1–126 (8); G691S and S904S (9, 10), and S836S (11)] and GFR 1 [GFR 1 –193 (12)], and sMTC. The purpose of this study was to confirm these associations and to identify any other common variants in the genes RET (10q11.2), GFR1 (MIM 601496), GFR2 (MIM 601956), GFR3 (MIM 605710), GFR4 (20p13-p12), GDNF (5p13-p12), NRTN (19p13.3), ARTN (1p33-p32), and PSPN (19p13.3) that confer susceptibility to sMTC, using a case-control study design.
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Patients and Methods |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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Cases (n = 135) were all the individuals with histologically proven MTC and no family history elicited by the referring specialist physicians, who were referred to the National Health Service Genetic Diagnostic laboratory at Addenbrooke’s Hospital (Cambridge, UK) between 1996 and 2000 for testing for the known RET mutations associated with MEN2, and who had tested negative. All cases had been screened for mutations in exons 10, 11, 13, 14, 15, and 16. None had a previous recorded history of malignancy or endocrine disease. The median age at the diagnosis of MTC was 48 yr (range, 14–80 yr), and the median age at the time of study was 56 yr (range, 19–88 yr). The cases were all residents of the United Kingdom, the great majority within England. Gender-, age-, and ethnic-matched controls were a group of 533 anonymous individuals selected from the EPIC study (13), a population-based cohort study of diet and health based in the East Anglian region of the United Kingdom. Median age was 60 yr (range, 45–74 yr); none had a recorded history of malignancy or endocrine disease. The ethnic background of both cases and controls was similar, with more than 95% being Caucasian. Informed consent was obtained from all study participants.
Identification of SNPs
SNPs were initially identified through SNP databases (Ensembl, Database Single Nucleotide Polymorphisms, and HapMap). If the rare allele frequency of the SNP was not given by the source, we genotyped a set of 48 genomic DNA samples from the United Kingdom Caucasian population by denaturing HPLC and sequencing using standard protocols. We selected all SNPs with reported rare allele frequencies of at least 5% in Caucasian populations. When fewer than three polymorphisms with different allele frequencies were found in a gene, we screened the whole coding sequence, untranslated regions, and approximately 100 bp of the genomic sequence around the splice sites to find more variants to define the common haplotypes for each gene. However, in four of the genes, the number of available SNPs was restricted to one or two. Although the frequency of the variant at position –193 in GFR1 was lower than 5%, we investigated this polymorphism because a previous study reported an association between it and sMTC (12). In total, we analyzed 33 SNPs in the nine genes: seven SNPs in GFR1, two SNPs in GFR2, one SNP in GFR3, three SNPs in GFR4, three SNPs in GDNF, two SNPs in NRTN, two SNPs in ARTN, two SNPs in PSPN, and 10 SNPs in RET.
Genotyping
We genotyped all samples for selected polymorphisms using the ABI PRISM 7900 sequence detection system or TaqMan (Applied Biosystems, Foster City, CA). We carried out PCR on DNA (20 ng) using 1x TaqMan Universal PCR Master Mix, forward and reverse primers (900 nM), and 6-carboxyfluorescein (FAM)- and VIC-labeled probes (200 nM) in a 5-µl reaction. Amplification conditions on a Tetrad thermal cycler (Genetic Research Instrumentation, MJ Research, Cambridge, MA) were as follows: one cycle of 95 C for 10 min, followed by 40 cycles of 95 C for 15 sec and 60 C for 1 min. We read the completed PCRs on an ABI PRISM 7900 sequence detector and analyzed them using the Allelic Discrimination Sequence Detector software (Applied Biosystems). For the software to recognize the genotypes, we included four nontemplate controls in each 384-well plate. We designed TaqMan primers and probes using Primer Express Oligo Design software version 2.0 (Applied Biosystems). All TaqMan primer and probe sequences are available on the web supplement.
Statistical methods
For each polymorphism, deviation of the genotype frequencies from those expected under Hardy-Weinberg equilibrium (HWE) was assessed in the controls by 
2 tests. Genotype frequencies in cases and controls were compared by 2 tests. The genotypic-specific risks were estimated as odds ratios (ORs), with associated 95% confidence limits. Differences in the overall haplotype frequencies between cases and controls were tested using the global score test implemented in the Haploscore software (14). This software also provides estimates of haplotype frequencies and haplotype-specific score tests that can be used to evaluate individual haplotypes whenever the global test is significant. Each haplotype is compared with all other haplotypes as the reference in calculating the ORs. Haplotype specific ORs were estimated with associated confidence intervals to identify which haplotype(s) is associated with the putative causal variant.
Putative phenotypic alterations caused by SNPs (PupaSNP) Finder, a web-based search tool for SNPs with potential phenotypic effect
PupaSNP has a collection of entries from the Database Single Nucleotide Polymorphisms mapped to the Golden Path genome assembly, as implemented in the human section of Ensembl. The potential effects on the phenotype at both transcriptional and gene product levels are examined. These include alterations in 1) transcriptional factor binding sites, 2) intron/exon border consensus sequences, 3) exonic splicing enhancers (ESE) sequences, which are the binding sites for specific serine/arginine-rich (SR) proteins involved in the splicing machinery, and 4) the exons that cause an amino acid change (15).
RT-PCR
Mononuclear cells were obtained from lymphocyte reduction filters from nine of the controls (three common homozygous, three heterozygous, and three rare homozygous for SNP G691S). B Lymphocytes were enriched by immunomagnetic bead sorting cell, using CD19+ selection magnetic-operated cell sorting technology (Miltenyi Biotec, Auburn, CA), according to the manufacturer’s instructions. Total RNA was extracted from the B lymphocyte population using Tri-Reagent (Sigma-Aldrich Corp., St. Louis, MO) according to the manufacturer’s protocol, followed by deoxyribonuclease I treatment (Ambion). cDNA was prepared from 2 µg total RNA with the TaqMan Reverse Transcription Reagents kit (Applied Biosystems) using random hexamers. cDNAs were amplified using different combinations of primers to determine whether any of splice sites located after the SNP are affected (Table 1
). Fifty-microliter reactions included 10 pmol of each primer, 200 µM deoxy-NTP, and 1 U Taq Gold (Applied Biosystems). Cycling conditions were an initial denaturation step (94 C for 2 min), 40 cycles (94 C for 30 sec, 60 C for 45 sec, and 72 C for 1 min), and a final extension step (72 C for 5 min). Reaction products were resolved by electrophoresis through a 3% agarose gel and visualized by ethidium bromide staining.
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We used the PredictProtein server to assess the effect of a G691S substitution on the predicted secondary structure of RET protein. META-PP provides a single-page interface to various world-wide web services for sequence analysis, homolog retrieval, and prediction of protein structure. The algorithms accessed by META-PP include secondary structure (Jpred, PHDsec, PROFsec, PSIpred, PSSP, and SSpro), residue solvent accessibility (PHDacc and PROFacc), transmembrane helix location and topology (PHDhtm and PHDtopology), protein globularity (GLOBE), coiled-coil regions (COILS), cysteine bonds (CYSPRED), and structural switching regions (ASP).
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Results |
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The distributions of alleles at the individual SNPs in the nine candidate genes among patients and controls are shown in Table 2. No association with a risk of developing sMTC was found for GFR2, GFR3, GFR4, GDNF, NRTN, or PSPN. For the two SNPs in NRTN, the genotype frequencies observed in controls deviated from HWE. Both SNPs showed similar frequencies for rare alleles and they were in complete linkage disequilibrium (LD; D' = 1). However, when an additional 2200 controls were analyzed, genotype frequencies were close to those expected under HWE. This suggests that the initial finding was due to chance.
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Among the seven individual GFR1 SNPs, only the variant allele 312 bp beyond the last exon of the gene (STOP+946bp) showed a suggestive genotype distribution difference between cases and controls (1 df; P = 0.01). The rare g allele was overrepresented in cases and may represent a risk allele, acting in a recessive manner in the development of sMTC [OR(gg vs. cc), 2.14; 95% confidence interval (CI), 1.08–4.26]. For the variant at position –193, the rare allele was also more common in sMTC cases than controls (4.5% vs. 2.9, as reported by Gimm et al. (12). However, the difference was not significant (1 df; P = 0.17) in our bigger sample set.
ARTN
The only previously validated SNP for ARTN (R19Q) showed no association with sMTC. No more SNPs were found in the promoter, coding, or genomic sequences surrounding the splice sites; therefore, we screened the intronic regions conserved among human, mouse, and rat, because they could harbor regulatory elements. A second SNP that was not previously validated was identified 797 bp upstream of the START codon (rs3762422). This variant showed a significant association with sMTC [OR (at vs. aa), 1.89; 95% CI, 1.26–2.82; 2 df; P = 0.003].
RET
Four of 10 studied SNPs were associated with sMTC. SNPs in exon 11 (G691S), exon 15 (S904S), and exon 19 (STOP+388bp) conferred between 1.6- and 2.5-fold increased risks of developing sMTC (Table 2
). The rare allele of the SNP in exon 2 (A45A) was underrepresented (1 df; P = 0.04) in cases and may represent a protective allele against developing sMTC. All significant SNPs had a codominant mode of action. In contrast to previous studies in German and Spanish populations (11, 16), we observed no association between SNP S836S and sMTC in our population.
Haplotype analysis
Using all previously cited SNPs, we estimated all common haplotypes for GFR2, GFR4, GDNF, NRTN, and PSPN, and we did not observe any difference in haplotype frequencies between cases and controls for any of these genes (data not shown). This analysis could not be performed in GFR3 because only one SNP was found.
The same approach was used to determine whether the observed associations with GFR1, ARTN, and RET were due to one of the associated SNPs or to another polymorphism in LD with them. In Table 3 are represented all common haplotypes with frequencies higher than 5%.
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There was substantial haplotype diversity across the whole gene. However, the three SNPs located in the promoter region are all in complete LD with each other. We therefore compared haplotype frequencies using two haplotype blocks: block 1 comprises the first three SNPs, and block 2 comprises the other four SNPs (N179N, IVS6+21, T361A, and STOP+946bp). For block 1, there was no difference in haplotype frequencies between cases and controls (P = 0.34). Four common haplotypes were present in block 2 (Table 3). These common haplotypes constituted more than 85% of all the observed haplotypes. The global test score for differences in haplotype frequencies between cases and controls was not significant (P = 0.09). However, we found one haplotype significantly overrepresented in cases (TGAG;P = 0.004). This haplotype contained the rare allele of STOP+946bp, significant in the univariate analysis, but this allele was also present on a different haplotype, which shows no association with disease (CGAG; P = 0.28). This suggests that STOP+946bp is not a causal, functional variant, but is a marker for the true causal variant on the TGAG haplotype. Potential regulatory elements of GFR1 need to be investigated to confirm this.
ARTN
The two SNPs found in ARTN determined three common haplotypes. Two of them contained the risk allele for the SNP START-797bp. This SNP is a good candidate to be a functional variant because it is located in the putative promoter of the gene, but only one of the haplotypes (TG) showed a 2-fold increased risk of sMTC (Table 3). This suggests that another variant on the risk haplotype is the causal variant. However, we did not find any other common variants in conserved regions or coding and noncoding sequences of the gene, suggesting that the functional variant is in unknown regulatory elements surrounding the gene.
RET
Seven different RET haplotypes were deduced in our population (Table 3). One specific haplotype (CGGATGCCAA) was significantly overrepresented among patients (OR, 1.47; 95% CI, 1.00–2.15). This haplotype harbors the three individual SNPs associated with increased risk of developing sMTC (Table 2); all of them tag this haplotype perfectly because they are in complete LD. Because SNP G691S in exon 11 is a nonsynonymous polymorphism, it is possible that this SNP is responsible for the observed risk effect for sMTC in this haplotype. The association between the SNP G691S and increased risk of developing sMTC has been previously observed in a different population, and the researchers suggested several hypotheses to explain the functional role of this variant (9, 10). Another specific haplotype (CAGGTGGCGG; Table 3) was found to be protective (OR, 0.39; 95% CI, 0.21–0.72). The rare allele of SNP A45A, associated with a protective effect for developing sMTC, was located in this haplotype. However, the presence of the rare allele of SNP A45A in a second haplotype (CAGGGGGTAG) that showed no disease association (P = 0.31; Table 3), points to the existence of another unknown variant in the haplotype CAGGTGGCGG as responsible for the protective effect. None of the common haplotypes harbored the rare allele of SNP S836S (5% in the United Kingdom population), so we could not confirm the association between this variant and sMTC suggested by others (11, 16).
Possible effects of RET G691S polymorphism
Using the PupaSNP web-tool (see Subjects and Methods), we found that the nucleotide change g>a in codon 691 is located in an ESE. ESEs are recognized by SR proteins, which, upon binding to such an enhancer, stimulate splicing (17) by recruiting the splicing machinery to the adjacent intron. Thus, point variations in exonic regions can alter splicing by disruption of an enhancer sequence within the skipped exon. As the introduction of the g>a SNP resulted in a predicted reduction in binding of two SR proteins to the ESE (SC35 and SRp40; scores changed from 2.54 to 0.79 and from 2.87 to 2.30, respectively), we investigated whether the g>a change indeed affects the splicing pattern of RET mRNA. Common and rare alleles of RET were analyzed by RT-PCR. Amplification of the RET cDNA fragments spanning the SNP was performed using a forward primer in either exon 10 or 11 and reverse primers within exons 11, 12, 13, 14, 16, and 19. No differences were observed in any of the amplification products of RET cDNA from three common homozygotes, three heterozygotes, and three rare homozygotes (data not shown). We therefore conclude that the g>a change (G691S) does not affect the splicing of RET mRNA.
To assess whether the change in amino acid from G to S affects the secondary structure or protein folding of RET, we analyzed the whole RET protein sequence containing either a glycine or serine at position 691 using several web-based tools. Most algorithms predicted significant changes to the protein folding as a result of the G691S substitution. The change to serine modifies the content and distribution of -helical, ß-strand, and unstructured stretches, and the proportion of solvent-exposed residues decreases drastically. Taken together, the substitution of glycine for a serine at codon 691 is predicted as likely to cause significant overall variation in the secondary structure of the protein, folding, and interaction with a nonaqueous environment.
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Discussion |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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1, ARTN, and RET) and risk of developing sMTC. It is inappropriate to correct for multiple testing using standard methods such as the Bonferroni method because the 32 tests are not independent. We therefore used permutation testing, randomly assigning case-control status to determine the significance of our results. The most significant result was for ARTN(SNP1) (P = 0.00314). In 5000 permutations a P value as small or smaller than this was achieved 471 times, giving this SNP an adjusted P = 0.094. However, there were three values of P < 0.005. The permutation based probability of this occurring by chance was 0.0048. An alternative explanation for a (false) positive association is bias due to hidden population stratification. This occurs when allele frequencies differ between population subgroups, and cases and controls are drawn differentially from those subgroups. However, it seems unlikely that population stratification is relevant in this study, because the cases and controls were drawn from the same ethnic groups (>95% white). Furthermore, we found no evidence for association among 23 unlinked markers (209 tests) in the control population, which suggest that there is unlikely to be significant substructure in our population (our unpublished observations).
This analysis has enabled us to exclude the possibility that the common exonic variants identified in the GFR2, GFR3, GFR4, GDNF, NRTN, and PSPN genes confer a modest risk of sMTC. However, it is possible that there are common susceptibility variants in the intronic regulatory regions that we did not screen, because they may not have been tagged by the haplotypes identified. For example, the commonest haplotype of GFR2 (frequency, 0.58) was not associated with sMTC. It might harbor a true causal SNP (unidentified) that has a lower frequency. Nevertheless, based on the CI for the common haplotype risk, we can, for example, exclude alleles of GFR2 of frequency 0.2 having a risk of 1.5 or more.
Four SNPs in RET have been reported to be associated with sMTC: IVS1-126 (8), G691S and S904S (9, 10), and S836S (11). An overrepresentation of S836S in sMTC cases has been observed in two different population samples, one of German and U.S. patients and the other of Spanish origin (11, 16). A third case-control study in a French population did not find any association between this SNP and sMTC (18). Our results with S836S are similar to those of the French study, excluding any association with the disease. In the same way, the previous association between sMTC and SNP IVS1–126 (8) was excluded in the U.K. population.
We confirmed the association of G691S, and the two other SNPs in LD with it (S904S and STOP+388bp), with increased risk of developing sMTC previously described by Robledo et al. (9) and Elisei et al. (10). As hypothesized by these researchers, it is very likely that the nonsynonymous variant G691S is the functional one responsible for the increased risk of developing MTC observed in their and our populations. The mechanism by which this polymorphism may modify the risk of developing sMTC is unknown. Robledo et al. (9) suggested that the modifier effect could be due to the amino acid change (glycine to serine) creating a new serine phosphorylation site that may affect downstream signaling events. Nevertheless, it has not been tested experimentally by functional assays. We proposed two different hypotheses for the potential effect of SNP G691S related to RET mRNA splice recognition and to protein folding. Firstly, G691S is located in an ESE putatively recognized by two SR proteins (SC35 and SRp40), which mediate splicing stimulation by binding to enhancers and recruiting the splicing machinery to the adjacent intron (17, 19). Because G691S disrupts the ESE in which it is located, different SR proteins decrease the capacity of recognition of this sequence. However, we observed no difference between the RET cDNA from common homozygous and rare alleles carriers, excluding this hypothesis as a functional explanation for the observed association between G691S and sMTC.
We also investigated how this SNP can affect the folding of the RET protein by in silico assay. Numerous changes were predicted by computational algorithms upon substitution of G691S, in both flexibility and solvent accessibility of the protein. Consideration of protein flexibility is indispensable to the critical evaluation of ligand binding affinity (20, 21), and the conformational plasticity of the catalytic domain is a hallmark of a protein kinase (22). The RET protein is a cell membrane tyrosine kinase receptor protein and functions as a multicomponent receptor complex. Therefore, if this amino acid change is affecting the flexibility and solvent accessibility of the protein, it is very likely that this SNP can modify the on/off conformation of the receptor independently of ligand. Experimental data are needed to verify these predictions.
The analysis of RET haplotypes showed that the strongest association was with one of two haplotypes containing the SNP A45A. This haplotype confers a protective effect in our population (P = 0.003). SNP A45A has been previously associated with an increased risk of Hirschsprung disease (23), but it is unlikely that this is the functional variant responsible for the protective effect of sMTC, because it is also present in a second nonassociated haplotype. Thus, these data could reflect an association between an unknown variant in LD with A45A and sMTC. This variant could be located either in the promoter region or in regulatory elements of the gene that have not been screened in this study.
GFR1 has been previously associated with sMTC by Gimm et al. (12); they reported an association with GFR1–193 in a small case-control study (n = 30 cases). However, a second case-control study in a Spanish population sample showed no statistical differences (24). We also failed to find any association in our larger sample set. Nevertheless, we found a significant association with another variant (STOP+946bp) in the same gene. ARTN was also found to be associated with sMTC (START-797). However, both the significant variant in GFR1 and the one in ARTN were present in two different haplotypes, for in each case we observed only one of the haplotypes to increase the risk of sMTC (P = 0.004 for GFR1 and 0.00002 for ARTN). The effect observed for the ARTN TG haplotype and the GFR1 TGAG haplotype was stronger than that for any individual polymorphism. These observations suggest that the association is probably due to another functional variant(s) in LD with the tested polymorphisms. However, when we screened the whole coding region, sequences surrounding splice sites; conserved intronic sequences among human, mouse, and rat; and also the putative promoter in the case of ARTN, we were not able to find the variants responsible for this effect. We excluded the presence of more SNPs with frequencies higher than 5% in these regions. Additional studies are necessary in other regulatory regions outside of these two genes to locate the functional variants.
The putative susceptibility SNPs we have identified are of limited clinical relevance. The relative risks conferred are moderate, and given the rarity of the disease, the absolute risks associated with the high risk variants are still extremely small. Furthermore, the RET G691S variant accounts for less than 2% of the excess familial risk of sMTC, suggesting that other susceptibility variants have yet to be found. In summary, this study provides evidence that variants in ARTN and GFR1 increase sMTC risk, and those in RET can increase or decrease it depending on their locations. We found by different computational algorithms that G691S influences the flexibility and solvent accessibility of the RET receptor. If these results can be confirmed by functional studies, it will improve our understanding of the role of the GFR-RET receptor complex in medullary thyroid carcinogenesis.
Electronic database information
The URL for data presented herein is as follows: Online Mendelian Inheritance in Man (OMIM), www.ncbi.nlm.nih.gov/Omim/ (for MEN2, RET, GFR1, GFR2, GFR3, GDNF, NRTN, ARTN, and PSPN); Ensembl, www.ensembl.org; Database Single Nucleotide Polymorphisms, www.ncbi.nlm.nih.gov/SNP; HapMap, www.hapmap.org (public data release 4 at 2004-02-06); PupaSNP, pupasnp.bioinfo.cnio.es; and PredictProtein Server, www.embl-heidelberg.de/predictprotein/ submit_def.html.
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Acknowledgments |
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Footnotes |
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First Published Online August 9, 2005
1 A.C. and F.L. contributed equally to this work. 
Abbreviations: ARTN, Artemin; CI, confidence interval; ESE, exonic splicing enhancer; GDNF, glial cell line-derived neurotropic factor; GFR, glial cell line-derived neurotropic factor receptor; HWE, Hardy-Weinberg equilibrium; LD, linkage disequilibrium; MEN2, multiple endocrine neoplasia type 2; MTC, medullary thyroid carcinoma; NRTN, neurturin; OR, odds ratio; PSPN, persephin; PupaSNP, putative phenotypic alterations caused by SNP; RET, rearranged during transfection; sMTC, sporadic MTC; SNP, single nucleotide polymorphism; SR, serine/arginine rich.
Received December 13, 2004.
Accepted August 2, 2005.
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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-1 but not GFR-2 or GFR-3 in cases with sporadic medullary thyroid carcinoma. Oncogene 20:2161–2170[CrossRef][Medline]
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