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Carcinogenesis Advance Access originally published online on May 15, 2006
Carcinogenesis 2006 27(11):2201-2208; doi:10.1093/carcin/bgl067
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Associations of genetic variants in the estrogen receptor coactivators PPARGC1A, PPARGC1B and EP300 with familial breast cancer

Michael Wirtenberger1,2,*, Sandrine Tchatchou1,2, Kari Hemminki1,3, Julia Schmutzhard1,2, Christian Sutter4, Rita K. Schmutzler5, Alfons Meindl6, Barbara Wappenschmidt5, Marion Kiechle6, Norbert Arnold7, Bernhard H. F. Weber8, Dieter Niederacher9, Claus R. Bartram4 and Barbara Burwinkel1,2

1 Division of Molecular Genetic Epidemiology, Helmholtz-University Group Molecular Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany
2 Helmholtz-University Group Molecular Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany
3 Department of Biosciences at Novum, Karolinska Institute Huddinge, Sweden
4 Institute of Human Genetics, University of Heidelberg Heidelberg, Germany
5 Division of Molecular Gynaeco-Oncology, Department of Gynaecology and Obstetrics, Center of Molecular Medicine Cologne (CMMC) University Hospital of Cologne, Germany
6 Department of Gynaecology and Obstetrics, Klinikum rechts der Isar at the Technical University Munich, Germany
7 Division of Oncology, Department of Gynaecology and Obstetrics University Hospital Schleswig-Holstein, Kiel, Germany
8 Institute of Human Genetics, University of Regensburg Regensburg, Germany
9 Division of Molecular Genetics, Department of Gynaecology and Obstetrics, Clinical Center University of Düsseldorf Düsseldorf, Germany

*To whom correspondence should be addressed at: Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. Tel: +49 6221 421811; Email: m.wirtenberger{at}dkfz.de


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The mitogen effect of the ovarian steroid estrogen is a strong risk factor for breast cancer development. This effect is mainly mediated by the estrogen receptor {alpha}, a hormone inducible transcription factor, which activates gene expression through recruiting multiple coactivators, such as PPARGC1A, PPARGC1B and EP300. We tested the hypothesis that non-conservative, putative functional amino acid exchanges in PPARGC1A, PPARGC1B and EP300 act as low-penetrance familial breast cancer risk factors. The analysis of 816 BRCA1/2 mutation-negative familial breast cancer patients and 1012 controls revealed an association of the PPARGC1A Thr612Met polymorphism with familial breast cancer (OR = 1.35, 95% CI 1.00–1.81, P = 0.049), high-risk familial breast cancer (OR = 1.51, 95% CI 1.08–2.12, P = 0.017) and bilateral familial breast cancer (OR = 2.30, 95% CI 1.24–4.28, P = 0.009). Logistic regression analyses of the PPARGC1B Ala203Pro variant showed an increased familial breast cancer risk of heterozygous and homozygous variant allele carriers (OR = 1.48, 95% CI 1.15–1.91, P = 0.002). The genotype-combination analysis of the associated PPARGC1A Thr612Met variant and the associated PPARGC1B Ala203Pro variant suggests an allele dose-dependent breast cancer risk (Ptrend = 0.0004). Our results indicate for the first time the importance of inherited variants in the estrogen receptor coactivator genes PPARGC1A and PPARGC1B for familial breast cancer susceptibility. Owing to their impact on estrogen signaling, these polymorphisms might also influence adjuvant anti-estrogen therapy, using agents such as tamoxifen and raloxifen, and outcome of breast cancer patients.

Abbreviations: ER, estrogen receptor; ERR{gamma}, estrogen related receptor {gamma}; PPAR{gamma}, peroxisome proliferative activated receptor gamma; PPARGC1A and B, PPAR{gamma} coactivator 1 alpha and beta


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Breast cancer is the most common cause of cancer-related death in women worldwide and after lung cancer, the second most frequent cancer in the world (1). About 10% of all breast cancer patients report a family history of the disease (2). Large twin and family studies have suggested that inherited factors account for about one-quarter of the total variability in breast cancer incidence (3,4). It has been reported that familial aggregation of breast cancer risk is mainly due to heritable causes (5). BRCA1 and BRCA2, the two major high-penetrance susceptibility breast cancer genes, account for ~25% of the excess familial breast cancer risk in the investigated German study population (6). Other high-risk susceptibility genes, such as ATM, p53 and PTEN, are associated with only a small percentage of familial breast cancers (7–11). According to the polygenic model of inherited breast cancer, unfavorable combinations of polymorphic genetic variants in low-penetrance susceptibility genes jointly contribute to the excess familial breast cancer risk, and most of these genes remain to be discovered (12,13).

The ovarian steroid estrogen is a strong risk factor for the initiation and progression of breast cancer. It has been shown that reduced levels of ovarian steroids or the estrogen receptor {alpha} (ER{alpha}) result in a significant decrease in breast cancer risk (14,15). As a result, anti-estrogen therapies that inhibit estrogen synthesis or block the ER are used for breast cancer treatment (16).

The two isoforms of the ER, {alpha} and ß, are members of the nuclear receptor family, a group of hormone-inducible transcription factors, which activate gene expression through recruiting multiple coactivators. The mitogen effect of estrogen is based on the expression of genes containing an estrogen responsive element in their promoter by direct protein–protein interaction of the ER with other transcription factors. Target genes include secreted growth factors, growth factor receptors, proteases and cyclin/cdk factors that are involved in breast cancer development (reviewed in 17). Although, the association of ER{alpha} with breast cancer is well established (17,18), there are only some data showing that ERß expression is downregulated in premalignent breast cancer lesions, and it has been suggested that ERß negatively regulates the effect of ER{alpha} during carcinogenesis (19). Upon ligand binding, ER{alpha} and ß recruit a complex of diverse cofactors at the target gene promoter to initiate gene expression (20,21). The peroxisome proliferative activated receptor gamma (PPAR{gamma}) coactivator 1 alpha and beta (PPARGC1A and B) play an important role in the ER signaling pathway as nuclear receptor coactivators. PPARGC1A (alias PGC1) binds and enhances transactivation of ER{alpha} in a ligand-dependent manner (22,23). Additionally, PPARGC1A binds and activates ER{alpha} and ERß ligand independently in vitro, with a particular high binding affinity to ERß (24). In contrast, PPARGC1B (alias PERC), selectively interacts—dependent on ligand binding—with ER{alpha} to enhance its transcriptional activity (22,25).

PPARGC1A regulates multiple aspects of cellular energy metabolism in various organs, including components of adaptive thermogenesis and mitochondrial biogenesis, insulin mediated glucose homeostasis and differentiation of preadipocytes, via interaction with many transcription factors such as PPAR{gamma}, HNF4 and NRF1 (reviewed in ref. 26). Although, PPARGC1B shares significant sequence and tissue distribution with PPARGC1A, some studies suggest that the biological activities of PPARGC1B in the regulation of cellular metabolism is different from PPARGC1A, since it poorly activates the expression of gluconeogenic genes in hepatocytes, as PPARGC1A does (27,28).

Moreover, PPARGC1A and PPARGC1B bind and synergistically enhance transcriptional activity of the estrogen related receptor {gamma} (ERR{gamma}), which belongs to a novel subclass of nuclear receptors with high homology to ERs (29). These receptors mediate transcriptional activity in the absence of endogenous ligands and are designated orphan receptors (30,31). A transfection study has suggested that ERs and ERRs control overlapping regulatory pathways in breast cancer cells, as it has been reported that ERRs and ERs regulate gene expression of the same genes, like pS2, a human breast cancer prognostic marker (32).

One study has reported a reduced expression of PPAR{gamma} and its co-activator, PPARGC1A, in human breast cancer. Low levels of these proteins in cancer tissue have been associated with poor clinical prognosis (33). However, another study has recently shown an increased expression of PPAR{gamma} in breast cancer cell lines due to selective promoter usage (34). Even though the role of estrogen and the ER{alpha} in breast cancer carcinogenesis is well established, the controversial results of the two studies mentioned above show that the putative impact of PPAR{gamma} and PPARGC1A on breast cancer carcinogenesis is poorly understood. It has been suggested that this paradox might be resolved by performing more dose-dependent studies (35).

Another nuclear receptor coactivator, the tumour-suppressor gene EP300 functions as histone acetyltransferase (36,37) that regulates transcription via chromatin remodeling due to histone acetylation (38). It plays an important role in cell proliferation and differentiation (39,40). Thus, it functions as a transcriptional coactivator of nuclear hormone receptors, such as the ERs (41) and PPAR{gamma} (23,42), and other DNA binding proteins, such as transcription factors and components of the RNA polymerase II holoenzyme complex (43,44). A further important role of EP300 is the acetylation of p53 in response to DNA damage to regulate its DNA-binding and transcriptional functions (45–47). Moreover, it is implicated in the control of the cell cycle, as it is required for efficient function of transcription factors like E2F1 (48,49) and myoD (50), the cyclin-dependent kinase inhibitor p21WAF1/CIP1(51) and p53 (52) to promote cell cycle arrest. EP300 is located on chromosome 22 within a region, which exhibits frequent loss of heterozygosity in a variety of cancer types, including breast cancer (53,54). Somatic mutations of EP300 have been found in primary breast, colon and ovarian cancers and cancer cell lines (53,55,56).

In summary, the estrogen receptor coactivators PPARGC1A/B and EP300 are genes with a strong biological relevance for breast cancer carcinogenesis, which makes them good candidates as breast cancer susceptibility genes. We have shown previously a significant association of the ER coactivator NCOA3 with familial breast cancer (57).

This is the first study examining the impact of non-conservative, putative functional amino acid exchanges in PPARGC1A/B and EP300 on cancer risk. The analyses of a large German study cohort revealed a significant association of PPARGC1A Thr612Met and PPARGC1B Ala203Pro with familial breast cancer.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study population
Genotyping analyses were performed on genomic DNA of BRCA1/2 mutation negative index patients from 816 German breast cancer families, among a subset of 458 high-risk breast cancer cases (risk category A1 and B, see below) and 73 bilateral breast cancer cases, and 1012 unrelated German controls. All breast cancer cases were classified into six categories: (A1) families with two or more cases of breast cancer including at least two cases with onset under the age of 50 years; (A2) families with at least one male breast cancer case; (B) families with one or more cases of breast and at least one ovarian cancer; (C) families with two or more cases of breast cancer including one case diagnosed before the age of 50 years; (D) families with two or more cases of breast cancer diagnosed after the age of 50 years; (E) a single case of breast cancer with diagnosis before the age of 35 years. The breast cancer cases comprised unrelated women who had been tested BRCA1/2 mutation-negative by applying the denaturing high performance liquid chromatography (DHPLC) method on all exons, followed by direct sequencing of conspicuous exons (6). The samples were collected during the years 1997–2005 by six centers of the German Consortium for Hereditary Breast and Ovarian Cancer (centers of Heidelberg, Würzburg, Cologne, Kiel, Düsseldorf and Munich, see authors affiliations). Index patients were first diagnosed with breast cancer and then referred to a family registry. All breast cancer patients gave an informed consent.

The control population included healthy and unrelated female blood donors collected by the Institute of Transfusion Medicine and Immunology (Mannheim), having the same ethnic background and sex as the breast cancer patients. The age distribution of controls and cases was nearly identical (controls: mean age 45.6 years, median age 46 years; cases: mean age 45.1 years, median age 45 years). According to the German guidelines for blood donation, all blood donors were examined by a standard questionnaire and gave their informed consent. They were randomly selected during the years 2004–2005 for this study and no further inclusion criteria were applied during recruitment. The study was approved by the Ethics Committee of the University of Heidelberg (Heidelberg, Germany).

SNP verification
In order to verify annotated single nucleotide polymorphisms (SNPs) from the SNP database (NCBI) and to identify potential new SNPs in PPARGC1A/B and EP300, PCRs and sequencing of the respective regions were performed using genomic DNA of 23 randomly chosen German breast cancer cases. Primers were designed according to the GenBank sequence of PPARGC1A/B and EP300 (accession numbers NT_006316 [GenBank] , NM_133263 [GenBank] and NM_001429 [GenBank] ). Primer sequences are available upon request. PCRs were carried out according to a protocol described earlier (57).

Genotyping
Polymorphic, non-conservative amino acid exchanges of PPARGC1A (Gly482Ser and Thr612Met), of PPARGC1B (Ala203Pro and Arg292Ser), of EP300 (Ile997Val and Gln2223Pro), the intronic polymorphism 94580G->A of PPARGC1A and the synonymous polymorphism Pro388Pro of PPARGC1B were analysed using TaqMan allelic discrimination assays according to earlier descriptions (57). The primers and probes used are listed in Table I. The SNP assays were validated by re-genotyping 10% of all samples.


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  		Table I TaqMan primers and probes used for allelic discrimination assays to genotype the German study cohort

 
Statistical analysis
Hardy–Weinberg equilibrium test was undertaken using the {chi}2–‘goodness-of-fit’-test. Genotype-specific odds ratios (ORs), 95% confidence intervals (95% CIs) and P-values were computed by unconditional logistic regression using a tool offered by the Institute of Human Genetics, Technical University Munich, Munich, Germany (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl) and SAS version 9.1 (SAS Institute, Cary, NC). P-values were calculated using two-sided {chi}2-test. Given our sample size, we calculated a power of 80% ({alpha} = 0.05) to detect an OR of 1.32 (PPARGC1A, Gly482Ser), 1.53 (PPARGC1A, Thr612Met), 1.38 (PPARGC1A, 94580G>A), 1.46 (PPARGC1B, Ala203Pro), 1.67 (PPARGC1B, Arg292Ser), 1.36 (PPARGC1B, Pro388Pro), 1.32 (EP300, Ile997Val) and 1.65 (EP300, Gln2223Pro) using the power and sample size calculation software PS version 2.1.31 (http://www.mc.vanderbilt.edu/prevmed/ps/index.htm) (58). {chi}2-test for trend (Mantel extension) and the associated P-values were calculated using the software Epi Info 2000 version 3.2 (http://www.cdc.gov/epiinfo/). Haplotypes of PPARGC1A/B and EP300 polymorphisms were determined using SNPHAP 1.3 software by David Clayton (http://archimedes.well.ox.ac.uk/pise/snphap-simple.html). Each individual was assumed to carry the most likely pair of haplotypes. The distribution of each haplotype was compared relative to the most common one between cases and controls.

SNP verification and selection
In order to verify SNPs in PPARGC1A, PPARGC1B and EP300, which were derived from the NCBI SNP database and from the literature (59), we sequenced a randomly chosen set of 23 German breast cancer cases (46 chromosomes, Table II). Three coding and one intronic SNPs in PPARGC1A were confirmed in the 23 breast cancer samples. One new, synonymous, coding SNP was discovered in PPARGC1A (Thr528Thr). Regarding PPARGC1B, all three investigated coding variants were present in the 23 cancer samples. From the four tested coding polymorphisms in EP300, two could be confirmed. The present case–control study mainly focused on the possible impact of non-conservative, putative functional amino acid exchanges in PPARGC1A/B and EP300 on familial breast cancer risk. PPARGC1A Gly482Ser and Thr612Met were chosen, since these two SNPs were non-synonymous and exhibited the highest frequencies among the 23 tested individuals. Additionally, the intronic variant 94580G->A was tested, since a previous study has shown that a two loci haplotype of this variant and Gly482Ser were associated with obesity (59). Regarding PPARGC1B, the non-synonymous SNP Ala203Pro, which was confirmed in the 23 sample set with an appropriate frequency, and the frequent Arg292Ser (rs11959820), which was directly chosen from the NCBI SNP database without prior sequencing, were taken into account for further investigations. The synonymous Pro388Pro was additionally considered because of its high frequency in order to perform haplotype analyses. Concerning EP300, the two non-synonymous SNPs, Ile997Val and Gln2223Pro, which were confirmed among our 23 test samples, were chosen for subsequent genotyping.


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  		Table II Polymorphisms in PPARGC1A, PPARGC1B and EP300, which were sequenced in a subset of 23 German breast cancer samples

 

   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
We performed a case–control study using genomic DNA of BRCA1/2 mutation-negative female index patients from 816 unrelated families, among a subset of 458 high-risk and 73 bilateral breast cancer cases, and 1012 female unrelated German controls. Genotype distributions in cases and controls were consistent with the HWE. The SNP assays were validated by re-genotyping 10% of all samples, and concordance rates >99% were attained for all investigated SNPs.

Given our large sample size, we achieved a power of 80% ({alpha} = 0.05) to detect the effects with an OR between 1.32 and 1.67 for the eight examined polymorphisms.

PPARGC1A Gly482Ser and 94580G->A showed no association with familial breast cancer (Table III). Logistic regression analyses of Thr612Met (76873C->T) revealed a significant association with familial breast cancer (OR = 1.35, 95% CI 1.00–1.81, P = 0.049), high-risk familial breast cancer (OR = 1.51, 95% CI 1.08–2.12, P = 0.017) and bilateral familial breast cancer (OR = 2.30, 95% CI 1.24–4.28, P = 0.009). The results of the {chi}2-test for trend indicated an allele dose-dependent association of the rare allele T of Thr612Met with an increased familial breast cancer risk (all cases Ptrend = 0.028, Table III, high-risk cases Ptrend = 0.014, bilateral cases Ptrend = 0.005).


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  		Table III Genotype frequencies of PPARGC1A (Gly482Ser, Thr612Met and 94580G>A), PPARGC1B (Ala203Pro, Arg292Ser and Pro388Pro) and EP300 (Ile997Val and Gln2223Pro) in the German study population

 
Genotype frequencies of the PPARGC1B polymorphisms Arg292Ser and Pro388Pro were similar in cases and controls showing no significant association with familial breast cancer (Table III). The genotypes GC and CC of Ala203Pro (649G->C) were more frequent among cases than among controls, resulting in a significant association with familial breast cancer (OR = 1.48, 95% CI 1.15–1.91, P = 0.002, Table III). The OR of high-risk cases was 1.32 and the OR of bilateral cases was 1.63, but not significant. The results of the {chi}2-test for trend showed an allele dose-dependent association of the Ala203Pro C risk allele with increased familial breast cancer risk (Ptrend = 0.002, Table III).

The results of the {chi}2-test for trend point to an allele dose-dependent association with familial breast cancer risk of carriers with an increasing number of C risk alleles of Thr612Met and T risk alleles of Ala203Pro (Ptrend = 0.0001). Owing to the small number of samples, which carried the rare homozygous genotypes of both SNP, we combined carriers of the heterozygous and rare homozygous genotypes of both SNPs resulting in a Ptrend of 0.0004, (Table IV). ORs were calculated by comparing the distribution of each genotype-combination with the most common one between cases and controls. The {chi}2-test for trend was determined by dividing all genotype-combinations in three ranking groups according to an increasing number of T risk alleles of PPARGC1A Thr612Met (76873C->T) and C risk alleles of PPARGC1B Ala203Pro (649G->C).


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  		Table IV Joint analysis of the PPARGC1B Ala203Pro and PPARGC1A Thr612Met in the German study population

 
The genotype distribution of EP300 Ile997Val and Gln2223Pro was similar in cases and controls revealing no significant association with familial breast cancer (Table III).

Haplotype analyses of all investigated polymorphisms did not show any additional association with familial breast cancer.

Stratification of cases and controls according to different age groups (<50 years or ≥50 years) did not influence the risk of all investigated polymorphisms and age adjustment had no appreciable effect on the ORs.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
PPARGC1A, PPARGC1B and EP300 function as coactivators of the ERs in concert with other factors to enhance their transactivation activity (22–25,41,42). A persistent estrogen mediated mitogen signaling of the ER{alpha} is a well-known risk factor for developing breast cancer (17,18,60,61). The present study mainly focused on the effect of non-conservative, putative functional amino acid exchanges in PPARGC1A, PPARGC1B and EP300 on familial breast cancer risk. The strength of the present study is the large sample size and the resulting high power, which was achieved by exclusively using selected familial breast cancer cases. Thus, the high power of this study was further enhanced, since it has been shown that the power of association studies based on cases with a familial history of the disease is at least twice as high as the power of a study using unselected cases (62,63). Only BRCA1/2 mutation-negative familial breast cancer cases were included in the study to avoid the effects derived from mutations in these high- penetrance susceptibility genes (6).

The variants PPARGC1A Gly482Ser and 94580G->A, PPARGC1B Arg292Ser, EP300 Ile997Val and Gln2223Pro showed no significant association with familial breast cancer.

Some studies have shown PPARGC1A Gly482Ser to be associated with a higher risk for Type II diabetes mellitus and hypertension (64–66). Although Type II diabetes mellitus has been noted as one of the epidemiological risk factors of breast cancer (67), our results revealed that PPARGC1A Gly482Ser is not associated with familial breast cancer. However, these opposite results might be due to the versatile role of PPARGC1A as coactivator of many transcription factors, such as e.g. PPARG{gamma}, HNF4, ERs and ERRs, regulating different pathways involved in the pathogenesis of these diseases. The analysis of PPARGC1A Thr612Met resulted in an allele dose-dependent risk association with familial breast cancer (Table III). The association was stronger in high-risk and bilateral familial breast cancer cases. The breast cancer categories A1 and B were chosen as high-risk categories, since these categories are based on the most stringent family history inclusion criteria. Additionally, they have shown the highest BRCA1/2 mutation frequencies in a German study population, 35% for A1 and 52% for B (6). Recent case–control studies have reported an increase in genotype effects when high-risk or bilateral breast cancer cases have been examined (68–71). However, the results of bilateral cases must be interpreted with caution, since this subgroup consisted of only 73 cases.

Thr612Met represents a non-conservative exchange from a non-aromatic hydroxyl-containing amino acid to a sulphur containing, non-polar and hydrophobic amino acid. The high conservation of threonine 612 among orthologous genes in most diverse species points to the putative impact of this amino acid on the function and integrity of the protein. Only the chicken PPARGC1A protein contains the very small amino acid alanine instead of the also very small amino acid threonine at this position. Thr612 is located in the RS (arginine and serine rich) domain in the C-terminus of PPARGC1A. Together with the C-terminal RRM domain (RNA-recognition motif), this region is required for maintaining the interaction of RNA Polymerase II and other factors involved in transcription elongation, such as cyclin-dependent kinase 9 and cyclin T with PPARGC1A. Furthermore, PPARGC1A physically interacts with several splicing factors in nuclear speckles through its C-terminal domains. Moreover, it modulates expression and RNA processing of a target fibrionectin mini-gene, suggesting that this cofactor can participate in the RNA splicing process of its target genes (72,73). According to the ‘SNPeffect’ database (Molecular phenotyping of coding non-synonymous SNPs, EMBL; http://snpeffect.vib.be/contact.php) the Thr612Met amino acid substitution alters the solvent accessibility of PPARGC1A. The Thr612Met variant in the RS domain of PPARGC1A might interfere with its regulatory function during the expression and processing of target gene RNA, sensitizing the cells for carcinogenesis.

The allele frequency of PPARGC1A Thr612Met has been shown to be significantly lower among Type II diabetic patients than among normal glucose-tolerant control subjects (64), which points to the potential functional role of this polymorphism as protective factor in the pathogenesis of the disease. Our results indicated PPARGC1A Thr612Met to be a risk factor for familial breast cancer. Since Type II diabetes mellitus has been revealed as one of the epidemiological risk factors of breast cancer (67), these findings might appear as a contrariety. However, the distinct roles of PPARGC1A as coactivator of the transcription factor PPAR{gamma}, which mediates pathways associated with glucose uptake and gluconeogenesis (26) and ERs and ERRs involved in pathways mediating breast development (17), might be the causation of the reverse effect of this polymorphism in the two different diseases. The association of PPARGC1A Thr612Met with different diseases and study cohorts provides additional evidence for the putative functional relevance of this polymorphism.

Carriers of the PPARGC1B polymorphism Ala203Pro C risk allele are at a significantly higher breast cancer risk compared with the control population following an allele dose-dependent mode. Ala203Pro represents a conservative amino acid exchange from a tiny aliphatic non-polar amino acid to a cyclic non-polar amino acid. Alanine 203 is highly conserved among the homologous gene PPARGC1A in most diverse species, but is not conserved in the orthologous gene PPARGC1B of mouse and rat. The very small amino acid alanine is replaced by the also very small amino acid threonine in these species. Alanine 203 is in close proximity (43 amino acids downstream) to the first LXXLL motif of PPARGC1B. The LXXLL motif, also referred to as nuclear receptor box 1 (NR1), interacts with the hydrophobic pocket of the ligand-activated ligand binding domain (LBD) of the nuclear receptors (ER{alpha}/ß or PPAR{gamma}), thereby, recruiting a complex of coactivators to target DNA sites (74,75). According to the 'SNPeffect' database Ala203Pro is predicted to influence the solvent accessibility of PPARGC1B. Owing to the close proximity of Ala203Pro to the NR1 domain (22), the variant might interfere with the interaction of PPARGC1B with ERs and ERRs, leading to an altered transactivation of target genes.

A recent study has shown that the rare PPARGC1B 203Pro allele was significantly reduced in obese patients (76). Although obesity is a risk factor for breast cancer, our results indicated that the variant allele 203Pro was more frequent among breast cancer patients than controls. These findings suggest that Ala203Pro plays a functional role in both diseases. However, this polymorphism might have different effects in the distinct pathways involved in the development of these diseases. Ala203Pro might interfere with the transactivation activity of different transcription factors such as PPAR{gamma}, which is involved in adipocyte differentiation (26) and transcription factors such as ER{alpha} and ERRs, which are involved in breast development (17,29), resulting in the distinct risk pattern observed for obesity and breast cancer. Moreover, the existence of different PPARGC1B isoforms in various tissues may alter major pathways affected in obesity versus breast cancer, e.g. the splice variant PPARGC1B1A involved in fatty acid oxidation is the most abundant isoform in skeletal muscle, heart and brain (27,28).

Haplotype analyses of the three polymorphisms in PPARGC1A and in PPARGC1B did not reveal any new association with breast cancer, except the one of the haplotypes that contain the A risk allele of the associated PPARGC1A variant Thr612Met and the C risk allele of the associated PPARGC1B variant Ala203Pro.

We investigated the putative impact of PPARGC1A and PPARGC1B risk variant genotype-combinations on familial breast cancer. Indeed, the results of the chi-square trend test of the combined analysis of the associated PPARGC1A Thr612Met variant and the associated PPARGC1B Ala203Pro variant point to an allele dose-dependent risk (Ptrend = 0.0001).

Owing to the small number of samples, which carried the rare homozygous genotypes of both SNP, we followed a more conservative calculation strategy and combined carriers of the heterozygous and rare homozygous genotypes of both SNP resulting in a Ptrend of 0.0004 (Table IV).

Owing to the relatively high minor allele frequencies of PPARGC1A Thr612Met and PPARGC1B Ala203Pro among the control population, and since these polymorphisms may modulate the transactivation activity of ER{alpha}, these variants may also have an impact on the development of sporadic breast cancer.

The influence of known breast cancer risk factors (e.g. age at menarche, age at menopause and BMI, which might be possible confounding covariates) on the association of the investigated polymorphisms could not be addressed since these data were not available for the present study cohort. We adjusted our result for age, but age adjustment had no appreciable effect on the ORs. We did not adjust for sex, since only women were investigated in our study.

In the present study we investigated the effect of putative functional candidate SNPs in genes with a strong a priori biological relevance and probability to be involved in carcinogenesis. Thus, adjustment for multiple comparisons was not taken into account even though eight different SNPs were analysed. The consistency of the effects of the associated variants Ala203Pro and Thr612Met in the genotype and haplotype analyses, the allele dose dependency of the associations, the strongest effects in high-risk and/or bilateral breast cancer cases and, finally, the strong and biologically plausible interaction of PPARGC1A and PPARGC1B argue against a chance finding.

In conclusion, our results show for the first time a significant association of PPARGC1A Thr612Met and PPARGC1B Ala203Pro with familial breast cancer. Carriers of the associated polymorphisms are at an increased risk for developing breast cancer, which is further enhanced through the combination of these two variants.

Owing to the impact of PPARGC1A and PPARGC1B in estrogen signaling, these polymorphisms might also influence adjuvant anti-estrogen therapy, using agents such as tamoxifen and raloxifen, and outcome of breast cancer patients.


   Acknowledgments
 
The authors are grateful to Bowang Chen and Justo L. Bermejo for statistical analyses and also to Dagmar Beisse for performing TaqMan assays. The German breast cancer samples were collected within a project funded by the Deutsche Krebshilfe, supported by the Center of Molecular Medicine, Cologne (CMMC) and coordinated by R.K.S. This study was supported by the EU, LSHC-CT-2004-503465.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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Received February 14, 2006; revised April 25, 2006; accepted April 29, 2006.


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