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BRCP transporter and susceptibility to colorectal cancer
Mutation Research 645 (2008) 56–60
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Short communication
A gene-wide investigation on polymorphisms in the ABCG2/BRCP transporter and susceptibility to colorectal cancer Daniele Campa a,b , Barbara Pardini c , Alessio Naccarati c , Ludmila Vodickova c , Jan Novotny d , Asta Försti a,e , Kari Hemminki a,e , Roberto Barale b , Pavel Vodicka c , Federico Canzian a,∗ a
German Cancer Research Center (DKFZ), Heidelberg, Germany Department of Biology, University of Pisa, Pisa, Italy Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic d Department of Oncology, First Faculty of Medicine, Charles University, Prague, Czech Republic e Center for Family and Community Medicine, Karolinska Institute, Huddinge, Sweden b c
a r t i c l e
i n f o
Article history: Received 3 July 2008 Received in revised form 31 July 2008 Accepted 1 August 2008 Available online 19 August 2008 Keywords: ABCG2 BRCP Transporter Colorectal cancer Polymorphisms Susceptibility
a b s t r a c t ATP-binding cassette (ABC) transporters actively export a wide variety of molecules from cells, contributing to reduce the local cellular burden of toxic compounds. ABCG2/BCRP is abundantly expressed in epithelial cells of the intestine and colon. The expression and activity of this transporter in the gut differ between individuals, due at least in part to genetic polymorphisms, which may thus affect the risk of colorectal cancer (CRC). We selected 15 tagging SNPs, covering all the known genetic variation of the gene, and typed them in 680 CRC cases and 593 controls. We found that heterozygous carriers of the minor alleles of SNPs rs2622621 and rs1481012 had a decreased risk of CRC, respectively, with odds ratios of 0.73 (95% confidence interval 0.56–0.94; Pvalue = 0.017), and 0.72 (95% CI 0.53–0.97; Pvalue = 0.03). Thus, we found no strong and clearcut association between ABCG2 polymorphisms and CRC risk. To our knowledge this is the first report on ABCG2 and CRC risk. © 2008 Elsevier B.V. All rights reserved.
1. Introduction The ATP-binding cassette (ABC) transporter superfamily is among the largest and most broadly expressed protein superfamilies known. The vast majority of its members are responsible for the active transport of a wide variety of compounds across biological membranes, including phospholipids, ions, peptides, steroids, polysaccharides, amino acids, organic anions, bile acids, drugs, and other xenobiotics [1–3]. In humans, 48 ABC genes that are organized into seven subfamilies (A–G) have been described, several of which are involved in well-defined genetic disorders [1,3,4] (http://nutrigene.4t.com/humanabc.htm, http://www.gene.ucl.ac.uk/nomenclature/genefamily/abc.htm). The major role of ABC transporters is to reduce the local cellular burden of toxic compounds, giving the individual cell a protection against toxic effects. These export pumps are primarily expressed in the apical membrane of epithelial cells, such as enterocytes,
∗ Corresponding author at: Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. Tel.: +49 6221 421791; fax: +49 6221 421810. E-mail address: [email protected] (F. Canzian). 0027-5107/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.mrfmmm.2008.08.001
which are exposed to xenobiotics. In these cells the same transporters function on the one hand to reduce the entrance of harmful substances and on the other hand to eliminate their detoxification products. The first function (i.e. direct elimination of xenobiotics entering the cell) represents a first defense line against xenobiotics and can be called “phase 0 metabolism”, indicating the close connection to the activation and conjugation steps of detoxification [3]. Likewise, the latter step has been called “phase III metabolism” [5]. It should be taken into account that phase 0 results from the balance of the import of substances into cells, regulated by solute carrier transporters, and the export, regulated by ABC transporters. In particular, ABCG2/BCRP is expressed abundantly in the apical membrane of normal intestinal and colonic epithelium in vivo [6]. ABCG2 is believed to function as a component of the organism’s defense against toxicity by restricting the entrance of genotoxins from the intestinal tract into the organism and by facilitating the removal of toxic metabolites from the organism via bile or urine [7–9]. Among dietary genotoxins exported by ABCG2 is the meat-derived heterocyclic amine 2-amino-1methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) [9]. Thus, ABCG2 may prevent the intestinal epithelial cells from exposure to such genotoxins and hence provide protection against chemical-induced carcinogenesis.
D. Campa et al. / Mutation Research 645 (2008) 56–60
Though the role of this transporter in multidrug resistance has been the subject of numerous studies, the pattern of differential expression of ABCG2 in normal and cancer tissue in vivo and a possible relevance of ABCG2 to the pathophysiology of tumorigenesis and tumor progression has not yet been elucidated. ABCG2 may play a key role in the defense of the organism from exogenous substrates, the majority of which are metabolized in the gut. For this reason, a variation in the activity of the efflux pump may modify the elimination rate of toxic or carcinogenic compounds, modulating thus susceptibility to colorectal cancer (CRC). It is known that the expression and activity of this transporter in the gut may differ between individuals, due at least in part to genetic polymorphisms [10–12]. In this report we investigated the genetic variability of the ABCG2 gene. Using a tagging approach and selecting 15 SNPs we covered all the known genetic variation of the gene. We tested the impact of ABCG2 SNPs on CRC risk in a case–control study based on subjects from the Czech Republic. To our knowledge this is the first report on ABCG2 and CRC risk.
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genomic region of ABCG2 is characterized by high levels of linkage disequilibrium (LD), we postulate that such SNPs are also likely to tag any hitherto unidentified common SNPs in the gene. SNP rs2231142 was subsequently added to the list, in order to follow-up the association with rs1481012 (see Section 3). 2.3. DNA extraction and genotyping DNA was extracted from blood samples with standard proteinase K digestion followed by phenol/chloroform extraction and ethanol precipitation. The order of DNAs from cases and controls was randomized on PCR plates in order to ensure that an equal number of cases and controls could be analyzed simultaneously. All the genotyping was carried out using the Taqman assay. The MGB Taqman probes and primers were synthesized by Applied Biosystems (Foster City, CA). Primers and probes sequences are available upon request. The reaction mix included 5 ng genomic DNA, 10 pmol each primer, 2 pmol each probe and 2.5 l of 2× master mix (Applied Biosystems) in a final volume of 5 l. The thermocycling included 40 cycles with 30 s at 95 ◦ C followed by 60 s at 60 ◦ C. PCR plates were read on an ABI PRISM 7900HT instrument (Applied Biosystems). The PCR profile and reaction conditions were tested and optimized in order to contain equal amounts of template DNA, probes and primers and to be run with unique thermal conditions. All samples that did not give a reliable result in the first round of genotyping were resubmitted to up to two additional rounds of genotyping. Data points that were still not filled after this procedure were left blank. Repeated quality control genotypes (8% of the total) showed an average concordance of 99.1%.
2. Patients and methods 2.1. Study population A hospital-based case–control study was conducted to study CRC risk. Cases were CRC patients visiting nine oncological departments (two in Prague, one each in Benesov, Brno, Liberec, Ples, Pribram, Usti nad Labem, and Zlin) distributed in all geographic regions of Czech Republic and being representative of the population of the entire country. During the study period (September 2004 to February 2006), a total of 968 cases were diagnosed with CRC in these hospitals. This study includes 680 (70.2%) patients who could be interviewed and provided biological samples of sufficient quality for genetic analysis. The lost cases were similar to those enrolled with respect to age, sex, tumor location, and extent. All cases had histological confirmation of their tumor diagnosis. Genetic testing for hereditary HNPCC was recommended to four patients, who belonged to families complying with the Amsterdam criteria II. These patients were excluded from our study. Controls were selected among patients admitted to five large gastroenterological departments (Prague, Brno, Jihlava, Liberec, and Pribram) all over the Czech Republic, during the same period of the recruitment of cases. Controls were subjects undergoing colonoscopy for various gastrointestinal complaints. The reasons to proceed to colonoscopy for both cases and controls were (i) macroscopic bleeding; (ii) positive fecal occult blood test (FOBT); and (iii) abdominal pain of unknown origin. Due to the high incidence of CRC in the Czech Republic, colonoscopy is largely recommended and practiced, and it is compulsory in case of a positive FOBT. The most common findings for these subjects were hemorrhoids or idiopathic bowel diseases (IBD). Only subjects whose colonoscopic results were negative for malignancy, colorectal adenomas or IBD were chosen as controls. Among 739 invited controls, a total of 593 (80.2%) were analyzed in this study (lost controls were similar to those included with respect to sex distribution). Cases included in this study had a median age of 62 years (range 27–90), while controls had a median age of 56 years (range 28–91). Men were slightly more frequent (57.2% among cases and 53.6% of controls). Study subjects provided information on their lifestyle habits (smoking, drinking, diet, etc.), and family/personal history of cancer, with the use of structured questionnaires [13]. The genetic analyses did not interfere with diagnostic or therapeutic procedures for the subjects. All participants signed an informed written consent and the design of the study was approved by the Ethical Committee of the Institute of Experimental Medicine, Prague, Czech Republic. 2.2. Selection of tagging SNPs We aimed at surveying the entire set of common genetic variants in ABCG2. For this purpose, we used the algorithm of Carlson et al. [14] that was developed to select maximally informative sets of tagSNPs in candidate-gene association study. All polymorphisms in the region of ABCG2 (including 5 kb upstream of the first exon and 5 kb downstream of the last exon), with minor allele frequency (MAF) ≥5% in Caucasians from the International HapMap Project (version 22; http://www.hapmap.org), were included. Tagging SNPs were selected with the use of the Tagger program within Haploview (http://www.broad.mit.edu/mpg/haploview/; http://www.broad.mit.edu/mpg/tagger/) [15,16], using pairwise tagging with a minimum r2 of 0.8. This resulted in a selection of 15 tagging SNPs, with a mean r2 of the selected SNPs with the SNPs they tag of 0.963, meaning that our selection captures to a very high degree the known common variability in this gene. Considering that the
2.4. Statistical analysis The frequency distribution of genotypes was examined for the cases and the controls. Hardy–Weinberg equilibrium was tested in the cases and in the controls separately by chi square test. We used logistic regression for multivariate analyses to assess the main effects of the genetic polymorphism on CRC risk using a codominant inheritance model. The most common allele in the controls was assigned as the reference category. All analyses were adjusted for age and sex. Additionally, we performed a logistic regression stratifying for the cancer site (colon versus rectum) and smoking (smokers versus non-smokers and heavy smokers versus light smokers) or alcohol drinking (drinkers versus non-drinkers) habits. All the analyses were done with STATA software (StataCorp., College Station, TX).
3. Results The genotype frequencies among the controls and cases groups were in Hardy–Weinberg equilibrium for all the SNPs. The distribution of the genotypes and their odds ratios (ORs) for association with CRC risk are shown in Table 1 . We found that, in this sample set, heterozygotes for the G allele of rs2622621 SNP had a decreased risk of CRC, with an OR of 0.73 (95% confidence interval (95% CI) 0.56–0.94; Pvalue = 0.017), but not G/G homozygote individuals with an OR of 1.17 (95% CI 0.82–1.66; Pvalue = 0.37). When we added up all carriers of the G allele, they had an OR of 0.81 (95% CI 0.65–1.02; Pvalue = 0.07), suggesting an association with decreased risk of CRC. Moreover we found that heterozygotes for the G allele of rs1481012 SNP had a decreased risk of CRC, with an OR of 0.72 (95% CI 0.53–0.97; Pvalue = 0.03), but not G/G homozygote individuals with an OR of 1.27 (95% CI 0.47–3.42; Pvalue = 0.63). When we added up all carriers of the G allele, they had an OR of 0.77 (95% CI 0.58–1.03; Pvalue = 0.07), resulting, again, in a suggestive association with a decreased risk of CRC. SNP rs1481012 in the Hapmap database was showed to be in LD (D = 1; r2 = 0.92) with SNP rs2231142, a G/T polymorphism leading to a change from lysin to glutamin. We decided therefore to add the rs2231142 polymorphism to the tagging set, but we did not get any statistically significant association with a decreased risk of CRC, as shown in Table 1. Heterozygotes for SNP rs4148157 approached statistical significance (OR 0.74; 95% CI 0.55–1.00; Pvalue = 0.052). We did not find any statistically significant association between the other ABCG2 SNPs and CRC. Analyses stratified by cancer site (colon versus rectum), alcohol and smoking habits did not show any significant interaction with polymorphisms (data not shown).
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D. Campa et al. / Mutation Research 645 (2008) 56–60
Table 1 Associations of ABCG2 polymorphisms with CRC risk SNP
Positiona
rs9999111 A/A A/C C/C
89,292,221 (intron 1)
rs17731799 G/G G/T T/T
89,287,479 (intron 1)
rs2725248 T/T T/G G/G
89,287,031 (intron 1)
rs6857600 C/C C/T T/T
89,285,099 (intron 1)
rs3109823 T/T C/T C/C
89,283,626 (intron 1)
rs3114018 C/C A/C/ A/A
89,283,605 (intron 1)
rs2231142 C/C C/A A/A
89,271,347 (exon 5)
rs2725256 T/T C/T C/C
89,270,022 (intron 5)
rs1481012 A/A A/G G/G
89,258,106 (intron 7)
rs13120400 T/T C/T C/C
89,252,551 (intron 9)
rs2622621 C/C C/G G/G
89,249,944 (intron 9)
rs12505410 T/T T/G G/G
89,249,865 (intron 9)
rs2054576 T/T C/T C/C
89,247,799 (intron 9)
rs2231148 A/A A/T T/T
89,247,502 (intron 9)
rs4148157 C/C C/T T/T
89,239,958 (intron 9)
Cases (%)b
Controls (%)b
OR (95% CI)c
Pvalue
560 (85.8) 89 (13.6) 4 (0.6)
511 (88.9) 62 (10.8) 2 (0.3)
1 1.33 (0.94–1.91) 1.72 (0.30–9.70)
0.11 0.54
203 (31.3) 296 (45.6) 150 (23.1)
180 (30.2) 294 (49.3) 122 (20.5)
1 0.89 (0.68–1.16) 1.14 (0.82–1.57)
0.39 0.82
363 (55.3) 239 (36.4) 55 (8.4)
313 (54.1) 221 (38.2) 45 (7.8)
1 0.89 (0.69–1.14) 0.98 (0.63–1.53)
0.37 0.94
434 (65.2) 206 (30.9) 26 (3.9)
367 (65.2) 173 (30.7) 23 (4.1)
1 1.04 (0.81–1.35) 0.90 (0.49–1.66)
0.78 0.75
371 (57.9) 217 (33.9) 53 (8.3)
311 (54.1) 213 (37.0) 51 (8.9)
1 0.80 (0.62–1.03) 0.82 (0.53–1.27)
0.09 0.39
197 (29.8) 330 (49.8) 135 (20.4)
164 (27.8) 295 (50.1) 130 (22.1)
1 0.97 (0.71–1.32) 0.84 (0.61–1.76)
0.82 0.32
472 (81.1) 103 (17.7) 7 (1.2)
409 (79.1) 104 (20.1) 4 (0.8)
1 0.84 (0.62–1.16) 1.51 (0.43–5.27)
0.28 0.52
273 (42.6) 262 (40.9) 106 (16.5)
217 (39.0) 266 (47.8) 73 (13.1)
1 0.79 (0.61–1.02) 1.21 (0.83–1.72)
0.08 0.31
547 (82.6) 105 (15.9) 10 (1.5)
459 (78.6) 118 (20.2) 7 (1.2)
1 0.72 (0.53–0.97) 1.27 (0.47–3.42)
0.03 0.63
326 (51.9) 255 (40.6) 47 (7.5)
289 (50.7) 244 (42.8) 37 (6.5)
1 0.83 (0.51–1.35) 0.91 (0.56–1.47)
0.46 0.71
288 (44.6) 250 (38.7) 108 (16.7)
224 (39.5) 265 (46.7) 78 (13.8)
1 0.73 (0.56–0.94) 1.17 (0.82–1.66)
0.02 0.37
236 (35.1) 280 (41.6) 157 (23.3)
192 (33.0) 248 (42.7) 141 (24.3)
1 0.90 (0.69–1.17) 0.84 (0.62–1.14)
0.44 0.27
560 (83.2) 105 (15.6) 8 (1.2)
480 (80.8) 111 (18.7) 3 (0.5)
1 0.79 (0.60–1.07) 2.19 (0.56–8.51)
0.12 0.26
245 (38.7) 268 (42.3) 120 (19.0)
224 (39.6) 264 (46.7) 77 (13.6)
1 0.88 (0.68–1.14) 1.35 (0.95–1.93)
0.37 0.09
543 (81.9) 110 (16.6) 10 (1.5)
457 (78.5) 121 (20.8) 4 (0.7)
1 0.74 (0.55–1.00) 2.23 (0.68–7.29)
0.05 0.19
Ptrend 0.09
0.15
0.85
0.97
0.23
0.81
0.54
0.97
0.12
0.97
0.60
0.48
0.42
0.13
0.43
D. Campa et al. / Mutation Research 645 (2008) 56–60
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Table 1 (Continued)
SNP rs2728124 A/A A/T T/T
Positiona
Cases (%)b
Controls (%)b
OR (95% CI)c
Pvalue
182 (27.7) 316 (48.0) 160 (24.3)
169 (29.0) 283 (48.6) 130 (22.3)
1 0.95 (0.70–1.27) 0.95 (0.68–1.31)
0.71 0.74
Ptrend
89,225,184 (3 of exon 16) 0.43
a Position of SNP on chromosome 4, in base pairs (referred to NCBI build 36.1 of human genome and dbSNP build 128). In parentheses we report the position of the polymorphism with respect to the gene. b Numbers may not add up to 100% of subjects due to genotyping failure. All samples that did not give a reliable result in the first round of genotyping were resubmitted to up to two additional rounds of genotyping. Data points that were still not filled after this procedure were left blank. c OR: odds ratio; CI: confidence interval. Adjusted for age and gender. Values in bold are statistically significant (P < 0.05).
In addition, we performed analyses stratified by age (using the median age = 59 as cutpoint), and we found that two polymorphisms were associated with CRC in the younger subgroup, with borderline statistical support. We found that subjects homozygous for the G allele of rs2622621 had an increased risk of CRC, with an OR of 1.63 (95% CI 1.01–2.63; Pvalue = 0.044). Subjects homozygous for G allele of rs12505410 SNP had a decreased risk, with an OR of 0.63 (95% CI 0.41–0.98; Pvalue = 0.044). Finally, stratifying by gender we did not found any statistically significant association. 4. Discussion ABCG2 is a key player in the protection of the intestine from outside offence, due for example to dietary carcinogens such as PhIP. In this study we investigated the genetic variability of ABCG2 using a tagging approach and selecting 15 SNPs. Using this method we covered all the known common genetic variation of this gene. The previously published functional data and the association with other type of tumors [10,17] made the polymorphisms of this gene attractive candidates for affecting CRC risk. In our case–control study we found two associations between two ABCG2 variants and a decreased risk of CRC. The main finding of this work is that heterozygous carriers of the G allele of rs2622621 SNP and of the G allele of rs1481012 SNP had a deceased risk of CRC. Using the dominant model (i.e. by combining heterozygotes with homozygotes for the rare allele), we found a borderline, not statistically significant association with a decreased risk of CRC OR of 0.77 (95% CI 0.58–1.03; Pvalue = 0.07) for SNP rs1481012. To check whether this finding could be explained by LD with an untyped functional SNP, we typed additionally SNP rs2231142, which is in high LD with rs1481012 and whose alleles result in a change from lysine to glutamine. This change from a strongly basic amino acid to one that is not basic is predicted not to be deleterious by PolyPhen analysis (http://genetics.bwh.harvard.edu/pph/). On the other hand, this polymorphism plays a role in pharmacogenetics of many drugs such as mitoxantrone, topotecan, and doxorubicin, and is also associated with altered risk of neoplastic diseases [10,17–20], which suggests that it is functionally relevant. However, we did not find any statistically significant association with a risk of CRC for rs2231142. Thus, either our first finding was due to random chance, or one of rs2622621 and rs1481012 SNP is a real hit. In the latter case, either SNP could be the causal variant or in LD with an unknown causative variant. This hypothesis could be tested by resequencing of the region and genotyping all novel variants in a larger set of cases and controls. SNP rs2622621 is in the middle of intron 9, and rs1481012 is in the seventh intron. There is no indication that either SNP has a biological function. Moreover, the fact that we found associations only with the heterozygote individuals corroborates the hypothesis that our findings are due to random chance. Applying a multiple testing
correction, due to the many comparisons we have performed, leads to non-significant results. In addition to the data on cancer risk, our study provides information potentially relevant for pharmacogenetics. Most drugs are developed based on data from European-derived ‘reference’ populations, but clinically relevant DNA polymorphisms often demonstrate population-specific patterns of allele frequencies. The knowledge of the frequency distribution of functional polymorphisms in a population may contribute to national planning for selection of therapeutic options. To this end, data on allelic frequencies provided by our study should be complemented by pharmacokinetic characterization of the polymorphisms. Here we present, to our knowledge, the largest existing study on common polymorphisms in a key gene such as ABCG2, which is involved in determining bioavailability of many drugs. Conflict of interest The authors declare that there are no conflicts of interest. Acknowledgements The study was partially supported by grants GACR 310/07/1430, AVOZ 50390703 and 50390512 of the Czech Republic. References [1] I. Klein, B. Sarkadi, A. Varadi, An inventory of the human ABC proteins, Biochim. Biophys. Acta 1461 (1999) 237–262. [2] S. Velamakanni, S.L. Wei, T. Janvilisri, H.W. van Veen, ABCG transporters: structure, substrate specificities and physiological roles: a brief overview, J. Bioenerg. Biomembr. 39 (2007) 465–471. [3] C.G. Dietrich, A. Geier, R.P. Oude Elferink, ABC of oral bioavailability: transporters as gatekeepers in the gut, Gut 52 (2003) 1788–1795. [4] M. Dean, R. Allikmets, Complete characterization of the human ABC gene family, J. Bioenerg. Biomembr. 33 (2001) 475–479. [5] T. Ishikawa, The ATP-dependent glutathione S-conjugate export pump, Trends Biochem. Sci. 17 (1992) 463–468. [6] M. Maliepaard, G.L. Scheffer, I.F. Faneyte, M.A. van Gastelen, A.C. Pijnenborg, A.H. Schinkel, M.J. van De Vijver, R.J. Scheper, J.H. Schellens, Subcellular localization and distribution of the breast cancer resistance protein transporter in normal human tissues, Cancer Res. 61 (2001) 3458–3464. [7] A. Haimeur, G. Conseil, R.G. Deeley, S.P. Cole, The MRP-related and BCRP/ABCG2 multidrug resistance proteins: biology, substrate specificity and regulation, Curr. Drug Metab. 5 (2004) 21–53. [8] J.W. Jonker, M. Buitelaar, E. Wagenaar, M.A. Van Der Valk, G.L. Scheffer, R.J. Scheper, T. Plosch, F. Kuipers, R.P. Elferink, H. Rosing, J.H. Beijnen, A.H. Schinkel, The breast cancer resistance protein protects against a major chlorophyllderived dietary phototoxin and protoporphyria, Proc. Natl. Acad. Sci. U.S.A. 99 (2002) 15649–15654. [9] P. Pavek, G. Merino, E. Wagenaar, E. Bolscher, M. Novotna, J.W. Jonker, A.H. Schinkel, Human breast cancer resistance protein: interactions with steroid drugs, hormones, the dietary carcinogen 2-amino-1-methyl-6phenylimidazo(4,5-b)pyridine, and transport of cimetidine, J. Pharmacol. Exp. Ther. 312 (2005) 144–152. [10] L.L. Hu, X.X. Wang, X. Chen, J. Chang, C. Li, Y. Zhang, J. Yang, W. Jiang, S.M. Zhuang, BCRP gene polymorphisms are associated with susceptibility and survival of diffuse large B-cell lymphoma, Carcinogenesis 28 (2007) 1740– 1744.
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Short communication
A gene-wide investigation on polymorphisms in the ABCG2/BRCP transporter and susceptibility to colorectal cancer Daniele Campa a,b , Barbara Pardini c , Alessio Naccarati c , Ludmila Vodickova c , Jan Novotny d , Asta Försti a,e , Kari Hemminki a,e , Roberto Barale b , Pavel Vodicka c , Federico Canzian a,∗ a
German Cancer Research Center (DKFZ), Heidelberg, Germany Department of Biology, University of Pisa, Pisa, Italy Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic d Department of Oncology, First Faculty of Medicine, Charles University, Prague, Czech Republic e Center for Family and Community Medicine, Karolinska Institute, Huddinge, Sweden b c
a r t i c l e
i n f o
Article history: Received 3 July 2008 Received in revised form 31 July 2008 Accepted 1 August 2008 Available online 19 August 2008 Keywords: ABCG2 BRCP Transporter Colorectal cancer Polymorphisms Susceptibility
a b s t r a c t ATP-binding cassette (ABC) transporters actively export a wide variety of molecules from cells, contributing to reduce the local cellular burden of toxic compounds. ABCG2/BCRP is abundantly expressed in epithelial cells of the intestine and colon. The expression and activity of this transporter in the gut differ between individuals, due at least in part to genetic polymorphisms, which may thus affect the risk of colorectal cancer (CRC). We selected 15 tagging SNPs, covering all the known genetic variation of the gene, and typed them in 680 CRC cases and 593 controls. We found that heterozygous carriers of the minor alleles of SNPs rs2622621 and rs1481012 had a decreased risk of CRC, respectively, with odds ratios of 0.73 (95% confidence interval 0.56–0.94; Pvalue = 0.017), and 0.72 (95% CI 0.53–0.97; Pvalue = 0.03). Thus, we found no strong and clearcut association between ABCG2 polymorphisms and CRC risk. To our knowledge this is the first report on ABCG2 and CRC risk. © 2008 Elsevier B.V. All rights reserved.
1. Introduction The ATP-binding cassette (ABC) transporter superfamily is among the largest and most broadly expressed protein superfamilies known. The vast majority of its members are responsible for the active transport of a wide variety of compounds across biological membranes, including phospholipids, ions, peptides, steroids, polysaccharides, amino acids, organic anions, bile acids, drugs, and other xenobiotics [1–3]. In humans, 48 ABC genes that are organized into seven subfamilies (A–G) have been described, several of which are involved in well-defined genetic disorders [1,3,4] (http://nutrigene.4t.com/humanabc.htm, http://www.gene.ucl.ac.uk/nomenclature/genefamily/abc.htm). The major role of ABC transporters is to reduce the local cellular burden of toxic compounds, giving the individual cell a protection against toxic effects. These export pumps are primarily expressed in the apical membrane of epithelial cells, such as enterocytes,
∗ Corresponding author at: Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. Tel.: +49 6221 421791; fax: +49 6221 421810. E-mail address: [email protected] (F. Canzian). 0027-5107/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.mrfmmm.2008.08.001
which are exposed to xenobiotics. In these cells the same transporters function on the one hand to reduce the entrance of harmful substances and on the other hand to eliminate their detoxification products. The first function (i.e. direct elimination of xenobiotics entering the cell) represents a first defense line against xenobiotics and can be called “phase 0 metabolism”, indicating the close connection to the activation and conjugation steps of detoxification [3]. Likewise, the latter step has been called “phase III metabolism” [5]. It should be taken into account that phase 0 results from the balance of the import of substances into cells, regulated by solute carrier transporters, and the export, regulated by ABC transporters. In particular, ABCG2/BCRP is expressed abundantly in the apical membrane of normal intestinal and colonic epithelium in vivo [6]. ABCG2 is believed to function as a component of the organism’s defense against toxicity by restricting the entrance of genotoxins from the intestinal tract into the organism and by facilitating the removal of toxic metabolites from the organism via bile or urine [7–9]. Among dietary genotoxins exported by ABCG2 is the meat-derived heterocyclic amine 2-amino-1methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) [9]. Thus, ABCG2 may prevent the intestinal epithelial cells from exposure to such genotoxins and hence provide protection against chemical-induced carcinogenesis.
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Though the role of this transporter in multidrug resistance has been the subject of numerous studies, the pattern of differential expression of ABCG2 in normal and cancer tissue in vivo and a possible relevance of ABCG2 to the pathophysiology of tumorigenesis and tumor progression has not yet been elucidated. ABCG2 may play a key role in the defense of the organism from exogenous substrates, the majority of which are metabolized in the gut. For this reason, a variation in the activity of the efflux pump may modify the elimination rate of toxic or carcinogenic compounds, modulating thus susceptibility to colorectal cancer (CRC). It is known that the expression and activity of this transporter in the gut may differ between individuals, due at least in part to genetic polymorphisms [10–12]. In this report we investigated the genetic variability of the ABCG2 gene. Using a tagging approach and selecting 15 SNPs we covered all the known genetic variation of the gene. We tested the impact of ABCG2 SNPs on CRC risk in a case–control study based on subjects from the Czech Republic. To our knowledge this is the first report on ABCG2 and CRC risk.
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genomic region of ABCG2 is characterized by high levels of linkage disequilibrium (LD), we postulate that such SNPs are also likely to tag any hitherto unidentified common SNPs in the gene. SNP rs2231142 was subsequently added to the list, in order to follow-up the association with rs1481012 (see Section 3). 2.3. DNA extraction and genotyping DNA was extracted from blood samples with standard proteinase K digestion followed by phenol/chloroform extraction and ethanol precipitation. The order of DNAs from cases and controls was randomized on PCR plates in order to ensure that an equal number of cases and controls could be analyzed simultaneously. All the genotyping was carried out using the Taqman assay. The MGB Taqman probes and primers were synthesized by Applied Biosystems (Foster City, CA). Primers and probes sequences are available upon request. The reaction mix included 5 ng genomic DNA, 10 pmol each primer, 2 pmol each probe and 2.5 l of 2× master mix (Applied Biosystems) in a final volume of 5 l. The thermocycling included 40 cycles with 30 s at 95 ◦ C followed by 60 s at 60 ◦ C. PCR plates were read on an ABI PRISM 7900HT instrument (Applied Biosystems). The PCR profile and reaction conditions were tested and optimized in order to contain equal amounts of template DNA, probes and primers and to be run with unique thermal conditions. All samples that did not give a reliable result in the first round of genotyping were resubmitted to up to two additional rounds of genotyping. Data points that were still not filled after this procedure were left blank. Repeated quality control genotypes (8% of the total) showed an average concordance of 99.1%.
2. Patients and methods 2.1. Study population A hospital-based case–control study was conducted to study CRC risk. Cases were CRC patients visiting nine oncological departments (two in Prague, one each in Benesov, Brno, Liberec, Ples, Pribram, Usti nad Labem, and Zlin) distributed in all geographic regions of Czech Republic and being representative of the population of the entire country. During the study period (September 2004 to February 2006), a total of 968 cases were diagnosed with CRC in these hospitals. This study includes 680 (70.2%) patients who could be interviewed and provided biological samples of sufficient quality for genetic analysis. The lost cases were similar to those enrolled with respect to age, sex, tumor location, and extent. All cases had histological confirmation of their tumor diagnosis. Genetic testing for hereditary HNPCC was recommended to four patients, who belonged to families complying with the Amsterdam criteria II. These patients were excluded from our study. Controls were selected among patients admitted to five large gastroenterological departments (Prague, Brno, Jihlava, Liberec, and Pribram) all over the Czech Republic, during the same period of the recruitment of cases. Controls were subjects undergoing colonoscopy for various gastrointestinal complaints. The reasons to proceed to colonoscopy for both cases and controls were (i) macroscopic bleeding; (ii) positive fecal occult blood test (FOBT); and (iii) abdominal pain of unknown origin. Due to the high incidence of CRC in the Czech Republic, colonoscopy is largely recommended and practiced, and it is compulsory in case of a positive FOBT. The most common findings for these subjects were hemorrhoids or idiopathic bowel diseases (IBD). Only subjects whose colonoscopic results were negative for malignancy, colorectal adenomas or IBD were chosen as controls. Among 739 invited controls, a total of 593 (80.2%) were analyzed in this study (lost controls were similar to those included with respect to sex distribution). Cases included in this study had a median age of 62 years (range 27–90), while controls had a median age of 56 years (range 28–91). Men were slightly more frequent (57.2% among cases and 53.6% of controls). Study subjects provided information on their lifestyle habits (smoking, drinking, diet, etc.), and family/personal history of cancer, with the use of structured questionnaires [13]. The genetic analyses did not interfere with diagnostic or therapeutic procedures for the subjects. All participants signed an informed written consent and the design of the study was approved by the Ethical Committee of the Institute of Experimental Medicine, Prague, Czech Republic. 2.2. Selection of tagging SNPs We aimed at surveying the entire set of common genetic variants in ABCG2. For this purpose, we used the algorithm of Carlson et al. [14] that was developed to select maximally informative sets of tagSNPs in candidate-gene association study. All polymorphisms in the region of ABCG2 (including 5 kb upstream of the first exon and 5 kb downstream of the last exon), with minor allele frequency (MAF) ≥5% in Caucasians from the International HapMap Project (version 22; http://www.hapmap.org), were included. Tagging SNPs were selected with the use of the Tagger program within Haploview (http://www.broad.mit.edu/mpg/haploview/; http://www.broad.mit.edu/mpg/tagger/) [15,16], using pairwise tagging with a minimum r2 of 0.8. This resulted in a selection of 15 tagging SNPs, with a mean r2 of the selected SNPs with the SNPs they tag of 0.963, meaning that our selection captures to a very high degree the known common variability in this gene. Considering that the
2.4. Statistical analysis The frequency distribution of genotypes was examined for the cases and the controls. Hardy–Weinberg equilibrium was tested in the cases and in the controls separately by chi square test. We used logistic regression for multivariate analyses to assess the main effects of the genetic polymorphism on CRC risk using a codominant inheritance model. The most common allele in the controls was assigned as the reference category. All analyses were adjusted for age and sex. Additionally, we performed a logistic regression stratifying for the cancer site (colon versus rectum) and smoking (smokers versus non-smokers and heavy smokers versus light smokers) or alcohol drinking (drinkers versus non-drinkers) habits. All the analyses were done with STATA software (StataCorp., College Station, TX).
3. Results The genotype frequencies among the controls and cases groups were in Hardy–Weinberg equilibrium for all the SNPs. The distribution of the genotypes and their odds ratios (ORs) for association with CRC risk are shown in Table 1 . We found that, in this sample set, heterozygotes for the G allele of rs2622621 SNP had a decreased risk of CRC, with an OR of 0.73 (95% confidence interval (95% CI) 0.56–0.94; Pvalue = 0.017), but not G/G homozygote individuals with an OR of 1.17 (95% CI 0.82–1.66; Pvalue = 0.37). When we added up all carriers of the G allele, they had an OR of 0.81 (95% CI 0.65–1.02; Pvalue = 0.07), suggesting an association with decreased risk of CRC. Moreover we found that heterozygotes for the G allele of rs1481012 SNP had a decreased risk of CRC, with an OR of 0.72 (95% CI 0.53–0.97; Pvalue = 0.03), but not G/G homozygote individuals with an OR of 1.27 (95% CI 0.47–3.42; Pvalue = 0.63). When we added up all carriers of the G allele, they had an OR of 0.77 (95% CI 0.58–1.03; Pvalue = 0.07), resulting, again, in a suggestive association with a decreased risk of CRC. SNP rs1481012 in the Hapmap database was showed to be in LD (D = 1; r2 = 0.92) with SNP rs2231142, a G/T polymorphism leading to a change from lysin to glutamin. We decided therefore to add the rs2231142 polymorphism to the tagging set, but we did not get any statistically significant association with a decreased risk of CRC, as shown in Table 1. Heterozygotes for SNP rs4148157 approached statistical significance (OR 0.74; 95% CI 0.55–1.00; Pvalue = 0.052). We did not find any statistically significant association between the other ABCG2 SNPs and CRC. Analyses stratified by cancer site (colon versus rectum), alcohol and smoking habits did not show any significant interaction with polymorphisms (data not shown).
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Table 1 Associations of ABCG2 polymorphisms with CRC risk SNP
Positiona
rs9999111 A/A A/C C/C
89,292,221 (intron 1)
rs17731799 G/G G/T T/T
89,287,479 (intron 1)
rs2725248 T/T T/G G/G
89,287,031 (intron 1)
rs6857600 C/C C/T T/T
89,285,099 (intron 1)
rs3109823 T/T C/T C/C
89,283,626 (intron 1)
rs3114018 C/C A/C/ A/A
89,283,605 (intron 1)
rs2231142 C/C C/A A/A
89,271,347 (exon 5)
rs2725256 T/T C/T C/C
89,270,022 (intron 5)
rs1481012 A/A A/G G/G
89,258,106 (intron 7)
rs13120400 T/T C/T C/C
89,252,551 (intron 9)
rs2622621 C/C C/G G/G
89,249,944 (intron 9)
rs12505410 T/T T/G G/G
89,249,865 (intron 9)
rs2054576 T/T C/T C/C
89,247,799 (intron 9)
rs2231148 A/A A/T T/T
89,247,502 (intron 9)
rs4148157 C/C C/T T/T
89,239,958 (intron 9)
Cases (%)b
Controls (%)b
OR (95% CI)c
Pvalue
560 (85.8) 89 (13.6) 4 (0.6)
511 (88.9) 62 (10.8) 2 (0.3)
1 1.33 (0.94–1.91) 1.72 (0.30–9.70)
0.11 0.54
203 (31.3) 296 (45.6) 150 (23.1)
180 (30.2) 294 (49.3) 122 (20.5)
1 0.89 (0.68–1.16) 1.14 (0.82–1.57)
0.39 0.82
363 (55.3) 239 (36.4) 55 (8.4)
313 (54.1) 221 (38.2) 45 (7.8)
1 0.89 (0.69–1.14) 0.98 (0.63–1.53)
0.37 0.94
434 (65.2) 206 (30.9) 26 (3.9)
367 (65.2) 173 (30.7) 23 (4.1)
1 1.04 (0.81–1.35) 0.90 (0.49–1.66)
0.78 0.75
371 (57.9) 217 (33.9) 53 (8.3)
311 (54.1) 213 (37.0) 51 (8.9)
1 0.80 (0.62–1.03) 0.82 (0.53–1.27)
0.09 0.39
197 (29.8) 330 (49.8) 135 (20.4)
164 (27.8) 295 (50.1) 130 (22.1)
1 0.97 (0.71–1.32) 0.84 (0.61–1.76)
0.82 0.32
472 (81.1) 103 (17.7) 7 (1.2)
409 (79.1) 104 (20.1) 4 (0.8)
1 0.84 (0.62–1.16) 1.51 (0.43–5.27)
0.28 0.52
273 (42.6) 262 (40.9) 106 (16.5)
217 (39.0) 266 (47.8) 73 (13.1)
1 0.79 (0.61–1.02) 1.21 (0.83–1.72)
0.08 0.31
547 (82.6) 105 (15.9) 10 (1.5)
459 (78.6) 118 (20.2) 7 (1.2)
1 0.72 (0.53–0.97) 1.27 (0.47–3.42)
0.03 0.63
326 (51.9) 255 (40.6) 47 (7.5)
289 (50.7) 244 (42.8) 37 (6.5)
1 0.83 (0.51–1.35) 0.91 (0.56–1.47)
0.46 0.71
288 (44.6) 250 (38.7) 108 (16.7)
224 (39.5) 265 (46.7) 78 (13.8)
1 0.73 (0.56–0.94) 1.17 (0.82–1.66)
0.02 0.37
236 (35.1) 280 (41.6) 157 (23.3)
192 (33.0) 248 (42.7) 141 (24.3)
1 0.90 (0.69–1.17) 0.84 (0.62–1.14)
0.44 0.27
560 (83.2) 105 (15.6) 8 (1.2)
480 (80.8) 111 (18.7) 3 (0.5)
1 0.79 (0.60–1.07) 2.19 (0.56–8.51)
0.12 0.26
245 (38.7) 268 (42.3) 120 (19.0)
224 (39.6) 264 (46.7) 77 (13.6)
1 0.88 (0.68–1.14) 1.35 (0.95–1.93)
0.37 0.09
543 (81.9) 110 (16.6) 10 (1.5)
457 (78.5) 121 (20.8) 4 (0.7)
1 0.74 (0.55–1.00) 2.23 (0.68–7.29)
0.05 0.19
Ptrend 0.09
0.15
0.85
0.97
0.23
0.81
0.54
0.97
0.12
0.97
0.60
0.48
0.42
0.13
0.43
D. Campa et al. / Mutation Research 645 (2008) 56–60
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Table 1 (Continued)
SNP rs2728124 A/A A/T T/T
Positiona
Cases (%)b
Controls (%)b
OR (95% CI)c
Pvalue
182 (27.7) 316 (48.0) 160 (24.3)
169 (29.0) 283 (48.6) 130 (22.3)
1 0.95 (0.70–1.27) 0.95 (0.68–1.31)
0.71 0.74
Ptrend
89,225,184 (3 of exon 16) 0.43
a Position of SNP on chromosome 4, in base pairs (referred to NCBI build 36.1 of human genome and dbSNP build 128). In parentheses we report the position of the polymorphism with respect to the gene. b Numbers may not add up to 100% of subjects due to genotyping failure. All samples that did not give a reliable result in the first round of genotyping were resubmitted to up to two additional rounds of genotyping. Data points that were still not filled after this procedure were left blank. c OR: odds ratio; CI: confidence interval. Adjusted for age and gender. Values in bold are statistically significant (P < 0.05).
In addition, we performed analyses stratified by age (using the median age = 59 as cutpoint), and we found that two polymorphisms were associated with CRC in the younger subgroup, with borderline statistical support. We found that subjects homozygous for the G allele of rs2622621 had an increased risk of CRC, with an OR of 1.63 (95% CI 1.01–2.63; Pvalue = 0.044). Subjects homozygous for G allele of rs12505410 SNP had a decreased risk, with an OR of 0.63 (95% CI 0.41–0.98; Pvalue = 0.044). Finally, stratifying by gender we did not found any statistically significant association. 4. Discussion ABCG2 is a key player in the protection of the intestine from outside offence, due for example to dietary carcinogens such as PhIP. In this study we investigated the genetic variability of ABCG2 using a tagging approach and selecting 15 SNPs. Using this method we covered all the known common genetic variation of this gene. The previously published functional data and the association with other type of tumors [10,17] made the polymorphisms of this gene attractive candidates for affecting CRC risk. In our case–control study we found two associations between two ABCG2 variants and a decreased risk of CRC. The main finding of this work is that heterozygous carriers of the G allele of rs2622621 SNP and of the G allele of rs1481012 SNP had a deceased risk of CRC. Using the dominant model (i.e. by combining heterozygotes with homozygotes for the rare allele), we found a borderline, not statistically significant association with a decreased risk of CRC OR of 0.77 (95% CI 0.58–1.03; Pvalue = 0.07) for SNP rs1481012. To check whether this finding could be explained by LD with an untyped functional SNP, we typed additionally SNP rs2231142, which is in high LD with rs1481012 and whose alleles result in a change from lysine to glutamine. This change from a strongly basic amino acid to one that is not basic is predicted not to be deleterious by PolyPhen analysis (http://genetics.bwh.harvard.edu/pph/). On the other hand, this polymorphism plays a role in pharmacogenetics of many drugs such as mitoxantrone, topotecan, and doxorubicin, and is also associated with altered risk of neoplastic diseases [10,17–20], which suggests that it is functionally relevant. However, we did not find any statistically significant association with a risk of CRC for rs2231142. Thus, either our first finding was due to random chance, or one of rs2622621 and rs1481012 SNP is a real hit. In the latter case, either SNP could be the causal variant or in LD with an unknown causative variant. This hypothesis could be tested by resequencing of the region and genotyping all novel variants in a larger set of cases and controls. SNP rs2622621 is in the middle of intron 9, and rs1481012 is in the seventh intron. There is no indication that either SNP has a biological function. Moreover, the fact that we found associations only with the heterozygote individuals corroborates the hypothesis that our findings are due to random chance. Applying a multiple testing
correction, due to the many comparisons we have performed, leads to non-significant results. In addition to the data on cancer risk, our study provides information potentially relevant for pharmacogenetics. Most drugs are developed based on data from European-derived ‘reference’ populations, but clinically relevant DNA polymorphisms often demonstrate population-specific patterns of allele frequencies. The knowledge of the frequency distribution of functional polymorphisms in a population may contribute to national planning for selection of therapeutic options. To this end, data on allelic frequencies provided by our study should be complemented by pharmacokinetic characterization of the polymorphisms. Here we present, to our knowledge, the largest existing study on common polymorphisms in a key gene such as ABCG2, which is involved in determining bioavailability of many drugs. Conflict of interest The authors declare that there are no conflicts of interest. Acknowledgements The study was partially supported by grants GACR 310/07/1430, AVOZ 50390703 and 50390512 of the Czech Republic. References [1] I. Klein, B. Sarkadi, A. Varadi, An inventory of the human ABC proteins, Biochim. Biophys. Acta 1461 (1999) 237–262. [2] S. Velamakanni, S.L. Wei, T. Janvilisri, H.W. van Veen, ABCG transporters: structure, substrate specificities and physiological roles: a brief overview, J. Bioenerg. Biomembr. 39 (2007) 465–471. [3] C.G. Dietrich, A. Geier, R.P. Oude Elferink, ABC of oral bioavailability: transporters as gatekeepers in the gut, Gut 52 (2003) 1788–1795. [4] M. Dean, R. Allikmets, Complete characterization of the human ABC gene family, J. Bioenerg. Biomembr. 33 (2001) 475–479. [5] T. Ishikawa, The ATP-dependent glutathione S-conjugate export pump, Trends Biochem. Sci. 17 (1992) 463–468. [6] M. Maliepaard, G.L. Scheffer, I.F. Faneyte, M.A. van Gastelen, A.C. Pijnenborg, A.H. Schinkel, M.J. van De Vijver, R.J. Scheper, J.H. Schellens, Subcellular localization and distribution of the breast cancer resistance protein transporter in normal human tissues, Cancer Res. 61 (2001) 3458–3464. [7] A. Haimeur, G. Conseil, R.G. Deeley, S.P. Cole, The MRP-related and BCRP/ABCG2 multidrug resistance proteins: biology, substrate specificity and regulation, Curr. Drug Metab. 5 (2004) 21–53. [8] J.W. Jonker, M. Buitelaar, E. Wagenaar, M.A. Van Der Valk, G.L. Scheffer, R.J. Scheper, T. Plosch, F. Kuipers, R.P. Elferink, H. Rosing, J.H. Beijnen, A.H. Schinkel, The breast cancer resistance protein protects against a major chlorophyllderived dietary phototoxin and protoporphyria, Proc. Natl. Acad. Sci. U.S.A. 99 (2002) 15649–15654. [9] P. Pavek, G. Merino, E. Wagenaar, E. Bolscher, M. Novotna, J.W. Jonker, A.H. Schinkel, Human breast cancer resistance protein: interactions with steroid drugs, hormones, the dietary carcinogen 2-amino-1-methyl-6phenylimidazo(4,5-b)pyridine, and transport of cimetidine, J. Pharmacol. Exp. Ther. 312 (2005) 144–152. [10] L.L. Hu, X.X. Wang, X. Chen, J. Chang, C. Li, Y. Zhang, J. Yang, W. Jiang, S.M. Zhuang, BCRP gene polymorphisms are associated with susceptibility and survival of diffuse large B-cell lymphoma, Carcinogenesis 28 (2007) 1740– 1744.
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