| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Priority Reports |
Departments of 1 Laboratory Medicine and Pathology, 2 Health Sciences Research, and 3 Urology, Mayo Clinic College of Medicine, Rochester, Minnesota
Requests for reprints: Stephen N. Thibodeau, Division of Laboratory Genetics, 200 First Street Southwest, 920 Hilton Building, Rochester, MN 55905. Phone: 507-284-4696; Fax: 507-284-0670; E-mail: sthibodeau{at}mayo.edu.
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
7, respectively). For the microsatellite marker DG8S737, the –8 allele was significantly more frequent in familial PC (OR, 1.68; 95% CI, 1.09–2.60; P = 0.031), whereas the –10 allele was more frequent in aggressive PC (OR, 2.85; 95% CI, 1.52–5.36; P = 0.0004). Haplotype analysis showed significant differences in haplotype frequencies between the familial PC (P = 0.006) and aggressive PC (P = 0.005) cases versus controls. The –8/A haplotype showed the strongest association with familial PC (P = 0.008), whereas the –10/A haplotype was most strongly associated with aggressive PC (P = 0.00005). These results further confirm the importance of these two polymorphic variants (rs1447295 and DG8S737) as risk factors for PC. However, the mechanism explaining this increased risk has not yet been established. [Cancer Res 2007;67(7):2944–50] |
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
A limitation of linkage studies is their weak power to find susceptibility genes of small to moderate effects. Association studies, in contrast, tend to have greater power to detect genes of small risk (12). Recently, Amundadottir et al. (13) identified a region on chromosome 8q24 showing suggestive linkage to PC in Icelandic families. Further analysis of this region led to the identification of several common variants associated with PC in European and African populations. Two representative markers, DG8S737 (microsatellite) and rs1447295 (single nucleotide polymorphism, SNP), showed the strongest association with PC in three case-control series of European ancestry from Iceland, Sweden, and the U.S.
In an attempt to replicate these findings, we compared the genotype and allele frequencies for these two markers (DG8S737 and rs1447295) in 1,121 Caucasian men with PC to 545 population-based controls. The 1,121 men with PC were composed of three groups: cases with familial PC (n = 435), sporadic cases with a negative family history of PC (n = 491), and cases with more aggressive disease (as defined by a Gleason score 8) without regard for family history of PC (n = 195).
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
8). These patients with PC were also identified through the Mayo Clinic radical prostatectomy database, but were selected from those men who did not receive a family history survey and were selected without regard to family history. Because of differences in ascertainment criteria, these three case groups were treated separately for subsequent statistical analyses. The unaffected control group has also been described in our previous publications (14, 15). These men were randomly selected from a sampling frame of Olmsted County, Minnesota provided by the Rochester Epidemiology Project, and has been described previously (16). These men underwent clinical urologic examination that included digital rectal examination, transrectal ultrasound of the prostate, residual urine volume, measurement of serum prostate-specific antigen, physical examination, and cryopreservation of serum for subsequent sex hormone assays. Any samples with abnormal digital rectal examination, elevated prostate-specific antigen, or suspicious lesion by transrectal ultrasound were further evaluated for PC. If digital rectal examination and transrectal ultrasound were unremarkable and serum prostate-specific antigen levels were elevated (>4 ng/mL), a sextant biopsy (three cores each side) of the prostate was done. These men have been followed with biennial examinations. Men without PC on the basis of this work-up and any follow-up exams were used in the control sample.
All individuals included in this report were Caucasians. Because of limited power, all non–Caucasians, including 9 Hispanic, 5 African-American, 1 Native American, 1 Asian, 3 other, and 12 men with unknown race (among 3 familial PC, 8 sporadic PC, 16 aggressive PC, and 4 controls) were excluded. The research protocol and informed consent forms were approved by the Mayo Clinic Institutional Review Board.
Genotyping. For the SNP marker rs1447295, we used a predesigned TaqMan SNP genotyping assay (Assay ID C_2160574_30; Applied Biosystems, Foster City, CA). PCR reactions were carried out in a final reaction volume of 5 µL consisting of 2.5 µL of 2x TaqMan Universal PCR Master Mix, 0.5 µL of 10x Allelic Discrimination Assay Mix, and 2 µL of DNA (10 ng). PCR was done on an ABI PRISM 7900HT SDS with the following conditions: initial denaturation at 95°C for 10 min, followed by 40 cycles at 92°C for 15 s, and 60°C for 60 s. The genotypes were called automatically and verified manually.
For the microsatellite marker DG8S737, the primers described by Amundadottir et al. (13) were used. The PCR primers are as following (from 5' to 3'): FAM-TGATGCACCACAGAAACCTG (forward) and CAAGGATGCAGCTCACAACA (reverse). PCR reactions were carried out in a final reaction volume of 12.5 µL consisting of 1x GoTaq reaction buffer with 1.5 mmol/L of MgCl2, 200 µmol/L of each deoxynucleotide triphosphate, 10 pmol of each primer, 0.3 units of GoTaq DNA polymerase (Promega, Madison, WI), and 12.5 ng of template DNA. PCR was done using a Tetrad thermal cycler (MJ Research, Waltham, MA) with the following conditions: initial denaturation at 95°C for 2 min, followed by 30 cycles at 94°C for 30 s, 58°C for 30 s, and 72°C for 30 s. The PCR products were diluted with water at a ratio of 1:10. One microliter of the diluted product was mixed with 9 µL of formamide containing ROX dye size standard (GeneScan 400HD; Applied Biosystems) and was analyzed on an ABI 3100 Genetic Analyzer (Applied Biosystems). The genotype of each sample was called automatically by the instrument, but then evaluated manually for potential misclassification.
Statistical analyses. The association of the SNP genotype with disease status was evaluated by Armitage's test for trend in allele counts. When performing comparisons with familial cases, the variance of the trend test and the variance of the odds ratios (OR) accounted for familial correlations (17).
To analyze the DG8S737 marker, a global 
2 statistic that generalizes Armitage's test for trend to more than two alleles was used. Each allele was given a "dosage" score of 0, 1, or 2 for each subject, and the averages of these scores were compared between cases and controls. For the comparisons with familial cases, a global test of association was calculated using a robust score statistic which simultaneously considers all alleles and accounts for correlations among family members (18). This global test is a 2 statistic with many degrees of freedom due to the large number of DG8S737 alleles, resulting in weak power if just one or two alleles are associated with disease. To increase power for this situation, we also computed Armitage's test for trend for each allele versus the pool of all others, and used the maximum, over all allelic tests, as the summary statistic. Simulations were used to compute P values for this maximum statistic, by randomly permuting case-control status. In addition, we calculated OR and 95% confidence intervals (95% CI) comparing carriers of one allele to all other alleles.
To determine whether specific DG8S737 or rs1447295 genotypes were associated with PC, as opposed to alleles, we also did analyses with genotypes. For marker DG8S737, we constructed a three-allele marker with DG8S737 alleles: –10, –8, and X, where X includes all other DG8S737 alleles. ORs and 95% CIs were calculated comparing subjects with genotypes containing alleles –8 and –10 to subjects with the X/X genotype as baseline. In order to account for familial correlations, we averaged the individual genotype counts for each pedigree, resulting in a single observation per pedigree.
In order to adjust for the potential confounding effect of age, we fit logistic regression models including age as a covariate. For these analyses, age was defined as age at diagnosis for patients and age at blood draw for control subjects. When comparing familial cases to controls, we calculated a robust score statistic which accounts for correlations among patients from the same family and allows for covariate adjustment (18). To adjust for the potential of population stratification, we used 741 SNPs scattered across the genome to create principal components for statistical adjustments, as outlined by Price et al. (19).
Haplotype frequencies were estimated using the expectation/maximization algorithm (20). On the basis of all possible pairs of haplotypes for each subject, given their observed genotypes, posterior probabilities for each individual were used to estimate the expected haplotype counts. These expected results were then used in a haplotype trend regression model (21). All rare haplotypes (frequencies <1%) were collapsed into a single haplotype group, and the most frequent haplotype was considered as the reference in the analyses. Global tests were conducted to assess the significance of all haplotypes, as well as individual tests for each haplotype. Simulated P values are reported.
To account for the correlation among multiple affected men from the same family, we first used the posterior probabilities to estimate the expected haplotype counts per subject. We then averaged these expected haplotype counts for each pedigree, resulting in a single observation per pedigree. P values based on 1,000 simulations are reported.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
45 to 85 years. Although the distribution of age at diagnosis was similar between the familial and sporadic cases, patients with aggressive PC and the controls tend to be younger than both case groups, because a relatively large part of these groups was <60 years old. Because of this difference, additional analyses were done including age as a covariate to statistically adjust for its potential confounding effects.
|
|
|
Analysis of rs1447295 genotypes is presented in Table 4 . Both heterozygote (A/C) and homozygote (A/A) genotypes were significantly more common among men with aggressive PC (OR, 1.77; 95% CI, 1.19–2.62; P = 0.005; OR, 3.71; 95% CI, 1.11–12.37; P = 0.03). The heterozygote A/C genotype was also more common among men with familial PC (OR, 2.05; 95% CI, 1.36–3.10; P = 0.0007). Although not statistically significant, the homozygote genotype was also more common in this group, with an OR of similar magnitude as that for heterozygotes, although the CIs were quite wide due to the small number of homozygote carriers. For marker DG8S737, genotype X/–8 was significantly more common among men with familial PC, whereas genotype X/–10 was more common among men with aggressive PC (OR, 2.04; 95% CI, 1.22–3.42 and OR, 2.51; 95% CI, 1.30–4.84, respectively).
|
7) was further evaluated within both the familial and sporadic PC groups. That is, the allele frequency in cases with a high Gleason score was compared with the allele frequency in cases with a low Gleason score. In both the familial and sporadic PC group, the allele frequencies for both markers were similar among high-grade and low-grade PC (data not shown). No statistically significant differences were observed. Results of the haplotype analyses are presented in Table 5 . When considering all haplotypes, a significant association was observed with both familial and aggressive PC (global P = 0.006 and 0.005, respectively; Table 5). The haplotype containing both the –8 allele and the A allele showed the strongest association with familial PC (P = 0.008), whereas the haplotype containing the –10 allele and the A allele was most strongly associated with aggressive PC (P = 0.00005).
|
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Overall, the allele frequencies observed for cases and controls in this current study were quite similar to those reported by Amundadottir et al. (13). The frequency of the –8 allele in our control group was 5.7%, compared with 4.1% observed in the European-American control group of Amundadottir et al. The Icelandic and Swedish controls had frequencies of 7.8% and 7.9%, respectively. The frequency of the SNP marker rs1447295 minor allele (A) among our controls (10.3%) was also similar to the previously reported estimates (8.1%, European-American; 10.6%, Icelandic; and 13.3%, Swedish; ref. 13). For the cases, the frequency of the DG8S737 (–8) allele ranged from 5.7% to 8.8% (OR, 1.05–1.68) for the Mayo groups compared with 8.2% to 13.1% (OR, 1.38–2.10) reported by Amundadottir et al. In the combined samples of Amundadottir et al., the OR for carriers of the –8 allele (1.62) was similar to that observed for our familial PC cases (OR, 1.68), but was larger than what we observed for our aggressive cases (OR, 1.23). These differences, however, are within statistical variability of the ORs. For rs1447295 (A), the frequency among cases ranged from 11.9% to 17.2% (OR, 1.16–1.93) for the Mayo groups compared with 12.7% to 16.9% (OR of 1.29–1.72) in Amundadottir et al. As before, the differences observed are within statistical variability of the ORs.
Amundadottir et al. postulated that either the –8 allele confers risk, or it is closely correlated through linkage disequilibrium with a risk variant. Our findings that the –10 allele had a larger OR (2.85) than the –8 allele (1.23) for aggressive PC cases suggests that the causative variant may not reside at DG8S737, but rather with a variant in high linkage disequilibrium near this marker. Additionally, our findings of a stronger association of the –10/A haplotype with aggressive PC compared with that of the –8/A haplotype further supports this notion. Finally, although there is compelling evidence that these variants increase the risk for PC, our data does not support a difference in risk between cases with low Gleason score and those with a high Gleason score.
These general findings have also now been recently replicated by several other groups. Freedman et al. (22) used admixture mapping in 1,597 African-Americans to identify a locus at 8q24 that substantially affects risk for PC in African-Americans, the same region reported by Amundadottir et al. (13). In additional analyses, however, the admixture signal detected in this region could not be explained by the SNP alleles identified by Amundadottir et al. (13), suggesting the presence of other unmapped risk alleles at this locus for African-Americans. Freedman et al. (22) extended their replication analysis of the rs1447295 SNP association identified by Amundadottir et al. (13) to four other ethnic groups. In each group, the previously described association was replicated; Japanese-Americans (P < 0.00034), Native Hawaiians (P < 0.00015), Latino-Americans (P < 0.0014), European-Americans (P < 0.022), and all four groups together (P < 4.2 x 10–9). Finally, the Cancer Genetic Markers of Susceptibility project (http://cgems.cancer.gov) released results from the first phase of the PC genome-wide association scan. In this study, >500,000 SNPs were genotyped in 1,177 cases and 1,105 controls. In this data set, the rs1447295 SNP showed a significant association (P = 0.000408) and was ranked among the top 315 most significant SNP's genome-wide. Of note, other SNPs within this region also showed significant associations, again suggesting the presence of unmapped risk alleles.
The functional significance of the two polymorphic variants reported by Amundadottir et al. (13) is, at this point, unclear. The two markers are 8.4 kb apart from each other and are located in an intronic region of a putative gene, which seems to have at least four alternative transcripts (ranging from 8 to 2 exons). However, only the short forms seem to be expressed in normal prostate tissue (13). Surprisingly, the putative gene does not possess a long stretch of open reading frames and the predicted short protein sequences do not match any existing protein domain. In addition to the putative gene, however, there are several other transcripts with unknown function in this chromosomal region.
The closest characterized gene is the proto-oncogene c-MYC, approximately 264 kb from rs1447295. It has been known for some time that amplification, or gain, of chromosome 8q24 (including the c-MYC region) is a frequent event in PC (23). Using array-CGH, Saramaki et al. recently reported four segments of 8q amplification showing frequent gain in >30% of PC cases (24). One of these segments includes these two markers as well as the c-MYC gene. This coamplification may indicate some functional relevance of these markers or of this region. Whether the risk alleles are preferentially amplified in these cases remains to be established. In another recent report using 50 patients with histologically different prostate tissues, gain at 8q24 was present in 10% of normal tissues, 19% of atrophy lesions, 21% of prostatic intraepithelial neoplasia, and 27% of cancer tissues (25). These results suggest that gain of chromosome 8q24 is very common in normal tissues and may predispose to the development of PC. Thus, it will be important to determine if the polymorphic risk alleles identified by Amundadottir et al. (or other alterations in linkage disequilibrium with these markers) are involved in the regulation of c-MYC expression or if they are involved in promoting the amplification, or gain, of the 8q24/c-MYC region. Clearly, further analysis of this genomic region will be necessary to clarify the functional consequences of these genetic markers.
It is worthwhile to highlight the strategy used by Amundadottir et al. to identify these two significant markers (13). Given that the identification of susceptibility genes by linkage analysis alone has proven to be extremely difficult for all completed PC genome scans (1), it is clear that additional approaches are required. Targeting candidate regions identified by linkage for high-density SNP association studies provides an alternative strategy to identify candidate susceptibility genes. The study by Amundadottir et al. (13) provides an example of how association studies can be used in combination with linkage analysis to successfully identify candidate genes/regions in a complex disease.
In summary, we have detected significant association of two genetic markers (DG8S737 and rs1447295) with PC. This result suggests a role for these polymorphisms or other linked variants in the development of PC, and supports the original finding reported by Amundadottir et al. (13). Although more studies are needed to elucidate the mechanism responsible for this association, our results provide strong guidance for taking the next steps.
|
Acknowledgments |
|---|
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
We thank Debora Johnson for her excellent secretarial support.
Received 8/31/06. Revised 12/21/06. Accepted 2/22/07.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Related Article
This article has been cited by other articles:
|
|
 |
|
  J. Beuten, J. A. L. Gelfond, M. L. Martinez-Fierro, K. S. Weldon, A. C. Crandall, A. Rojas-Martinez, I. M. Thompson, and R. J. Leach Association of chromosome 8q variants with prostate cancer risk in Caucasian and Hispanic men Carcinogenesis, August 1, 2009; 30(8): 1372 - 1379. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. P. Breyer, K. M. McReynolds, B. L. Yaspan, K. M. Bradley, W. D. Dupont, and J. R. Smith Genetic Variants and Prostate Cancer Risk: Candidate Replication and Exploration of Viral Restriction Genes Cancer Epidemiol. Biomarkers Prev., July 1, 2009; 18(7): 2137 - 2144. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. M. Pomerantz, C. A. Beckwith, M. M. Regan, S. K. Wyman, G. Petrovics, Y. Chen, D. J. Hawksworth, F. R. Schumacher, L. Mucci, K. L. Penney, et al. Evaluation of the 8q24 Prostate Cancer Risk Locus and MYC Expression Cancer Res., July 1, 2009; 69(13): 5568 - 5574. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. E. Wiklund, H.-O. Adami, S. L. Zheng, P. Stattin, W. B. Isaacs, H. Gronberg, and J. Xu Established Prostate Cancer Susceptibility Variants are not Associated with Disease Outcome Cancer Epidemiol. Biomarkers Prev., May 1, 2009; 18(5): 1659 - 1662. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. M. FitzGerald, E. M. Kwon, J. S. Koopmeiners, C. A. Salinas, J. L. Stanford, and E. A. Ostrander Analysis of Recently Identified Prostate Cancer Susceptibility Loci in a Population-based Study: Associations with Family History and Clinical Features Clin. Cancer Res., May 1, 2009; 15(9): 3231 - 3237. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. L. Penney, C. A. Salinas, M. Pomerantz, F. R. Schumacher, C. A. Beckwith, G.-S. Lee, W. K. Oh, O. Sartor, E. A. Ostrander, T. Kurth, et al. Evaluation of 8q24 and 17q Risk Loci and Prostate Cancer Mortality Clin. Cancer Res., May 1, 2009; 15(9): 3223 - 3230. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. L. Zheng, J. Sun, F. Wiklund, Z. Gao, P. Stattin, L. D. Purcell, H.-O. Adami, F.-C. Hsu, Y. Zhu, J. Adolfsson, et al. Genetic Variants and Family History Predict Prostate Cancer Similar to Prostate-Specific Antigen Clin. Cancer Res., February 1, 2009; 15(3): 1105 - 1111. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. D. Hofer, R. Kuefer, C. Maier, K. Herkommer, S. Perner, F. Demichelis, T. Paiss, W. Vogel, M. A. Rubin, and J. Hoegel Genome-Wide Linkage Analysis of TMPRSS2-ERG Fusion in Familial Prostate Cancer Cancer Res., January 15, 2009; 69(2): 640 - 646. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. W. Hsing, L. W. Chu, and F. Z. Stanczyk Androgen and Prostate Cancer: Is the Hypothesis Dead? Cancer Epidemiol. Biomarkers Prev., October 1, 2008; 17(10): 2525 - 2530. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Xu, S. D. Isaacs, J. Sun, G. Li, K. E. Wiley, Y. Zhu, F.-C. Hsu, F. Wiklund, A. R. Turner, T. S. Adams, et al. Association of Prostate Cancer Risk Variants with Clinicopathologic Characteristics of the Disease Clin. Cancer Res., September 15, 2008; 14(18): 5819 - 5824. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. M. Lange, J. Sun, L. A. Lange, S. L. Zheng, D. Duggan, J. D. Carpten, H. Gronberg, W. B. Isaacs, J. Xu, and B.-L. Chang Family-Based Samples Can Play an Important Role in Genetic Association Studies Cancer Epidemiol. Biomarkers Prev., September 1, 2008; 17(9): 2208 - 2214. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Y.-C. Tan, C. Zeigler-Johnson, R. D. Mittal, A. Mandhani, B. Mital, T. R. Rebbeck, and H. Rennert Common 8q24 Sequence Variations Are Associated with Asian Indian Advanced Prostate Cancer Risk Cancer Epidemiol. Biomarkers Prev., September 1, 2008; 17(9): 2431 - 2435. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
O. Cussenot, A.-R. Azzouzi, G. Bantsimba-Malanda, C. Gaffory, P. Mangin, L. Cormier, G. Fournier, A. Valeri, L. Jouffe, M. Roupret, et al. Effect of Genetic Variability within 8q24 on Aggressiveness Patterns at Diagnosis and Familial Status of Prostate Cancer Clin. Cancer Res., September 1, 2008; 14(17): 5635 - 5639. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. A. Salinas, E. Kwon, C. S. Carlson, J. S. Koopmeiners, Z. Feng, D. M. Karyadi, E. A. Ostrander, and J. L. Stanford Multiple Independent Genetic Variants in the 8q24 Region Are Associated with Prostate Cancer Risk Cancer Epidemiol. Biomarkers Prev., May 1, 2008; 17(5): 1203 - 1213. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. L. Zheng, J. Sun, F. Wiklund, S. Smith, P. Stattin, G. Li, H.-O. Adami, F.-C. Hsu, Y. Zhu, K. Balter, et al. Cumulative Association of Five Genetic Variants with Prostate Cancer N. Engl. J. Med., February 28, 2008; 358(9): 910 - 919. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Robbins, J. B. Torres, S. Hooker, C. Bonilla, W. Hernandez, A. Candreva, C. Ahaghotu, R. Kittles, and J. Carpten Confirmation study of prostate cancer risk variants at 8q24 in African Americans identifies a novel risk locus Genome Res., December 1, 2007; 17(12): 1717 - 1722. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. A. Savage and M. H. Greene The Evidence for Prostate Cancer Risk Loci at 8q24 Grows Stronger J Natl Cancer Inst, October 17, 2007; 99(20): 1499 - 1501. [Full Text] [PDF]
|
|
|
|
|
|
E. A. Platz Genetic Variation at 8q24 as a Susceptibility Factor for Prostate Cancer: Definitive Results from Epidemiologic Studies? Cancer Res., April 1, 2007; 67(7): 2905 - 2907. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
