SPOREs
Prostate
Projects
Projects
Project 2: Genetic and Clinical Characterization of the 8q24 Prostate Cancer Risk Locus
Co-Principal Investigators:
Matthew Freedman, MD
William K. Oh, MD
Participating Institution(s):
Dana-Farber Cancer Institute
Project 2: Specific Aims
Our specific aims for Project 2 are as follows:
Aim 1: To identify the causal germline allele through fine mapping of the 8q24 region
Aim 2: To characterize inherited variation at 8q24 and somatic molecular associations at 8q24
2a. To evaluate the association between germline 8q24 risk allele(s) and 8q tumor amplification
2b. To evaluate the association between germline 8q24 risk allele(s) and expression levels of nine candidate genes contained within the 8q24 region
2c. To evaluate the expression signature of 8q24 mediated CaP relative to non-8q24 driven CaP
Aim 3: To determine the effect of the germline 8q24 variant on clinical presentation and outcomes in CaP patients
3a. To determine the effect of the 8q24 germline variant on age, stage, and grade at the time of diagnosis in both pre- and post-PSA era patients
3b. To determine the effect of the 8q24 germline variant on metastasis/survival and progression-free survival
Substantial progress has been achieved over the past year for Project 2, “Genetic and Clinical Characterization of the 8q24 Prostate Cancer Risk Locus”. We have primarily focused on Aims 2 and 3. We have had strong interactions with the bioinformatics and pathology cores especially as they relate to Aim 3. We have worked closely with our epidemiologic colleagues for the design of Aim 3 and with the biostatistics core for the analysis of the results for Aims 2b and Aim 3. Finally, we have had extensive interactions with the pathology core for retrieval of specimens and for nucleic acid isolations for Aims 2 and 3.
Project 2: Studies and Results
Aim 2b, evaluation of the germline 8q24 risk allele and expression levels of candidate
genes, is now complete. We selected 12 candidate transcripts in the region, including 2 new putative transcripts identified from an expression tiling array experiment in this region. Using 121 samples from the pathology core, we have genotyped the 8q24 risk alleles. 6 single nucleotide polymorphisms (SNPs) on 8q24. RNA was isolated from histologically normal tissue and the 12 transcripts
were quantified using the Sequenom mass spectrometry platform. We then
evaluated if the risk alleles were associated with transcript abundance.
We are in the process of analyzing this dataset with the biostatistics core.
The 8q24 prostate cancer risk locus is complex. Currently, there are three regions spanning ~500 kilobases. Each region carries at least two polymorphisms that independently confer risk. Since there is no biological model to guide how these risk variants are exerting their effects, we will focus on 2 models: a) each risk variant will be analyzed independently, and b) each region will be tested as a unit (i.e., the number of risk alleles within a region will be summed together). Using the Kruskal-Wallis test, differences in the distribution of transcript abundance will be compared across genotypic classes.
The goal of Aim 3 was to determine the effect of the germline 8q24 variants on clinical parameters. We have now genotyped the 8q24 variants as well as the newly described 17q prostate risk variants in two cohorts comprising 7,388 men. We have examined the Physician’s Health Study (1347 ca/1477 co) as well as the SPORE core (4,564 cases). We evaluated the association of these variants with age at diagnosis, Gleason grade, Pathologic stage, and prostate cancer mortality. This is the largest study to date looking at prostate cancer mortality, arguably the most important clinical endpoint. Many studies have tested for association with aggressiveness using Gleason grade, however, no studies have looked at prostate cancer mortality.
No striking evidence is observed for an association with prostate cancer mortality. Two analyses were performed: a) comparison of long-term survivors (>10 years) to prostate cancer deaths and b) survival analysis looking at the hazard ratio for death for individuals who carry a risk allele. One variant, rs7000448, is nominally significantly associated with protective effect (i.e., more indolent course). Given the trend across both cohorts, this variant bears further study.
A striking age of onset effect was observed. Three variants (rs6983267, rs4430796, and rs1859962) were significantly associated with younger age of onset in the SPORE cohort, while rs13254738 was associated with later age of onset. Only rs4430796 was also significantly associated with younger age of onset in the PHS. One potential reason for this is that the average age of the PHS cohort is higher than the SPORE cohort (70.3 versus 62.0) and therefore, may be less powered to detect an age-of-onset effect. An analysis was also run looking at total number of risk alleles that a man carried (possible range 0-10) and we found a strong association with a younger age of onset in both the PHS and SPORE; with each additional risk allele, the age at diagnosis decreased by ~6 months (p=0.0002 and <0.0001, respectively).
Project 2: Significance
This entire project endeavors to have an impact on clinical medicine. First, by trying to identify the gene involved in prostate cancer development, insight will be gained into pathways that are crucial for tumor development. A more thorough understanding of the biology of the disease may provide a clearer direction for rationale therapeutic intervention.
One of the major hurdles in prostate is to identify men who are likely to die from their disease – currently, our ability to prognosticate for an individual patient at diagnosis is limited. Aim 3 of our project assesses the correlation between the inheritance of genetic risk factors for prostate cancer and the risk of death from prostate cancer. Answering this type of question would allow us to tell a man if he has a particularly aggressive form of prostate cancer that warrants therapy. Alternatively, it may shed light on men who have indolent forms of cancer requiring minimal intervention.
Project 2: Plans
Our plans for the upcoming year are to intensively focus on Aim 2. The primary goal is to identify which gene is causing this phenotype. Our data thus far strongly supports that these regions are likely to influence expression of a gene or set of genes. Based on our data analysis, we will have a much clearer sense of what path to pursue to implicate which gene this region is influencing.
Project 2: Publications
A common 8q24 variant in prostate and breast cancer from a large nested case-control study.
Schumacher FR, Feigelson HS, Cox DG, Haiman CA, Albanes D, Buring J, Calle EE, Chanock SJ, Colditz GA, Diver WR, Dunning AM, Freedman ML, Gaziano JM, Giovannucci E, Hankinson SE, Hayes RB, Henderson BE, Hoover RN, Kaaks R, Key T, Kolonel LN, Kraft P, Le Marchand L, Ma J, Pike MC, Riboli E, Stampfer MJ, Stram DO, Thomas G, Thun MJ, Travis R, Virtamo J, Andriole G, Gelmann E, Willett WC, Hunter DJ. Cancer Res. 2007 Apr 1;67(7):2951-6. PMID: 17409400 [PubMed - indexed for MEDLINE]
Multiple regions within 8q24 independently affect risk for prostate cancer.
Haiman CA, Patterson N, Freedman ML, Myers SR, Pike MC, Waliszewska A, Neubauer J, Tandon A, Schirmer C, McDonald GJ, Greenway SC, Stram DO, Le Marchand L, Kolonel LN, Frasco M, Wong D, Pooler LC, Ardlie K, Oakley-Girvan I, Whittemore AS, Cooney KA, John EM, Ingles SA, Altshuler D, Henderson BE, Reich D.
Nat Genet. 2007 May;39(5):638-44. Epub 2007 Apr 1. PMID: 17401364 [PubMed - indexed for MEDLINE]
Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men.
Freedman ML, Haiman CA, Patterson N, McDonald GJ, Tandon A, Waliszewska A, Penney K, Steen RG, Ardlie K, John EM, Oakley-Girvan I, Whittemore AS, Cooney KA, Ingles SA, Altshuler D, Henderson BE, Reich D. Proc Natl Acad Sci U S A. 2006 Sep 19;103(38):14068-73. Epub 2006 Aug 31. PMID: 16945910 [PubMed - indexed for MEDLINE]
Project 2: Project-Generated Resources
Not applicable at this time.
