A recurrent mutation in PALB2 in Finnish cancer families.

BRCA1, BRCA2 and other known susceptibility genes account for less than half of the detectable hereditary predisposition to breast cancer. Other relevant genes therefore remain to be discovered. Recently a new BRCA2-binding protein, PALB2, was identified. The BRCA2-PALB2 interaction is crucial for certain key BRCA2 DNA damage response functions as well as its tumour suppression activity. Here we show, by screening for PALB2 mutations in Finland that a frameshift mutation, c.1592delT, is present at significantly elevated frequency in familial breast cancer cases compared with ancestry-matched population controls. The truncated PALB2 protein caused by this mutation retained little BRCA2-binding capacity and was deficient in homologous recombination and crosslink repair. Further screening of c.1592delT in unselected breast cancer individuals revealed a roughly fourfold enrichment of this mutation in patients compared with controls. Most of the mutation-positive unselected cases had a familial pattern of disease development. In addition, one multigenerational prostate cancer family that segregated the c.1592delT truncation allele was observed. These results indicate that PALB2 is a breast cancer susceptibility gene that, in a suitably mutant form, may also contribute to familial prostate cancer development.

NMD and microRNA expression profiling of the HPCX1 locus reveal MAGEC1 as a candidate prostate cancer predisposition gene.

BACKGROUND: Several predisposition loci for hereditary prostate cancer (HPC) have been suggested, including HPCX1 at Xq27-q28, but due to the complex structure of the region, the susceptibility gene has not yet been identified. METHODS: In this study, nonsense-mediated mRNA decay (NMD) inhibition was used for the discovery of truncating mutations. Six prostate cancer (PC) patients and their healthy brothers were selected from a group of HPCX1-linked families. Expression analyses were done using Agilent 44 K oligoarrays, and selected genes were screened for mutations by direct sequencing. In addition, microRNA expression levels in the lymphoblastic cells were analyzed to trace variants that might alter miRNA expression and explain partly an inherited genetic predisposion to PC. RESULTS: Seventeen genes were selected for resequencing based on the NMD array, but no truncating mutations were found. The most interesting variant was MAGEC1 p.Met1?. An association was seen between the variant and unselected PC (OR = 2.35, 95% CI = 1.10-5.02) and HPC (OR = 3.38, 95% CI = 1.10-10.40). miRNA analysis revealed altogether 29 miRNAs with altered expression between the PC cases and controls. miRNA target analysis revealed that 12 of them also had possible target sites in the MAGEC1 gene. These miRNAs were selected for validation process including four miRNAs located in the X chromosome. The expressions of 14 miRNAs were validated in families that contributed to the significant signal differences in Agilent arrays. CONCLUSIONS: Further functional studies are needed to fully understand the possible contribution of these miRNAs and MAGEC1 start codon variant to PC.

The interaction of CYP3A5 polymorphisms along the androgen metabolism pathway in prostate cancer.

Prostate cancer is a leading solid tumor among men in the Western world. Androgens play an important role in the carcinogenesis and treatment of prostate cancer. CYP3A5 is a cytochrome P450 superfamily member which also has activity in testosterone metabolism. In this study, we looked for two-gene interactions associated with clinical characteristics of prostate cancer in the Finnish population. We used multifactor-dimensionality reduction for the identification of the two-gene interactions in androgen metabolism pathway genes together with clinical characteristics of prostate cancer among 754 genotyped prostate cancer patients. The CYP3A5*3/*3 and SRD5A2 A49T GG genotype interaction was associated with the clinical tumor stage T2-T4 (T-stage, TNM classification) with odds ratio (OR) 2.14, 95% confidence interval (CI) 1.35-3.40. Patients with CYP3A5*3/*3 and KLK3 I179T CC/TC genotypes had increased OR 2.30, 95% CI 1.16-4.58 for metastatic disease. Further, two-gene interaction CYP3A5*3/*3 and KLK3 -252A > G AA was associated with Gleason scores >or=7 with OR 1.52, 95% CI 1.11-2.09. Prostate cancer patients with CYP3A5*3/*3 and KLK -252A > G GG/AG genotypes had decreased OR of 0.70 with 95% CI 0.50-0.98 for high prostate-specific antigen levels at diagnosis. For prostate cancer patients aged below 65 years, the OR for interaction of CYP3A5*1/*3 or *1/*1 and AKR1C3 Q5H CC genotypes was 1.84 with 95% CI 1.03-3.28. For prostate cancer, the best two-gene interaction included genotypes SRD5A2 V89L GG and AKR1C3 Q5H CC with OR 1.30, 95% CI 1.01-1.66. It remains to be clarified whether these polymorphism associations identified here are also present in other populations.

MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families.

BACKGROUND: Heritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS). The thus far identified Single Nucleotide Polymorphisms (SNPs) explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer. RESULTS: In this study microRNA (miRNA) profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL) analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found. CONCLUSION: Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening, together with Prostate Specific Antigene (PSA) testing, to identify men with an elevated PrCa risk.