A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact

Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population-based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic variants each of small effect, where . Based on published studies of 26 SNPs that are currently known to be associated with prostate cancer, we have extended our model to incorporate these SNPs by decomposing the polygenic component into two parts: a polygenic component due to the known susceptibility SNPs, , and the residual polygenic component due to the postulated but as yet unknown genetic variants, . The resulting algorithm can be used for predicting the probability of developing prostate cancer in the future based on both SNP profiles and explicit family history information. This approach can be applied to other diseases for which population-based family data and established risk variants exist.

Prostate cancer in BRCA2 germline mutation carriers is associated with poorer prognosis

Background:

The germline BRCA2 mutation is associated with increased prostate cancer (PrCa) risk. We have assessed survival in young PrCa cases with a germline mutation in BRCA2 and investigated loss of heterozygosity at BRCA2 in their tumours.

Methods:

Two cohorts were compared: one was a group with young-onset PrCa, tested for germline BRCA2 mutations (6 of 263 cases had a germline BRAC2 mutation), and the second was a validation set consisting of a clinical set from Manchester of known BRCA2 mutuation carriers (15 cases) with PrCa. Survival data were compared with a control series of patients in a single clinic as determined by Kaplan–Meier estimates. Loss of heterozygosity was tested for in the DNA of tumour tissue of the young-onset group by typing four microsatellite markers that flanked the BRCA2 gene, followed by sequencing.

Results:

Median survival of all PrCa cases with a germline BRCA2 mutation was shorter at 4.8 years than was survival in controls at 8.5 years (P=0.002). Loss of heterozygosity was found in the majority of tumours of BRCA2 mutation carriers. Multivariate analysis confirmed that the poorer survival of PrCa in BRCA2 mutation carriers is associated with the germline BRCA2 mutation per se.

Conclusion:

BRCA2 germline mutation is an independent prognostic factor for survival in PrCa. Such patients should not be managed with active surveillance as they have more aggressive disease.

Prostate cancer segregation analyses using 4390 families from UK and Australian population-based studies

Familial aggregation of prostate cancer is likely to be due to multiple susceptibility loci, perhaps acting in conjunction with shared lifestyle risk factors. Models that assume a single mode of inheritance may be unrealistic. We analyzed genetic models of susceptibility to prostate cancer using segregation analysis of occurrence in families ascertained through population-based series totaling 4390 incident cases. We investigated major gene models (dominant, recessive, general, X-linked), polygenic models, and mixed models of susceptibility using the pedigree analysis software MENDEL. The hypergeometric model was used to approximate polygenic inheritance. The best-fitting model for the familial aggregation of prostate cancer was the mixed recessive model. The frequency of the susceptibility allele in the population was estimated to be 0.15 (95% confidence interval (CI) 0.11-0.20), with a relative risk for homozygote carriers of 94 (95% CI 46-192), and a polygenic standard deviation of 2.01 (95% CI 1.72-2.34). These analyses suggest that one or more genes having a strong recessively inherited effect on risk, as well as a number of genes with variants having small multiplicative effects on risk, may account for the genetic susceptibility to prostate cancer. The recessive component would predict the observed higher familial risk for siblings of cases than for fathers, but this could also be due to other factors such as shared lifestyle by siblings, targeted screening effects, and/or non-additive effects of one or more genes.

Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

Prostate cancer (PrCa) is the most frequently diagnosed cancer in males in developed countries. To identify common PrCa susceptibility alleles, we previously conducted a genome-wide association study in which 541,129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and in 1,894 controls. We have now extended the study to evaluate promising associations in a second stage in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls and in a third stage involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to replicating previous associations, we identified seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11 and 22 (with P = 1.6 x 10(-8) to P = 2.7 x 10(-33)).

Identification of new genetic risk factors for prostate cancer

There is evidence that a substantial part of genetic predisposition to prostate cancer (PCa) may be due to lower penetrance genes which are found by genome-wide association studies. We have recently conducted such a study and seven new regions of the genome linked to PCa risk have been identified. Three of these loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK2/3. The MSMB and KLK2/3 genes may be useful for PCa screening, and the LMTK2 gene might provide a potential therapeutic target. Together with results from other groups, there are now 23 germline genetic variants which have been reported. These results have the potential to be developed into a genetic test. However, we consider that marketing of tests to the public is premature, as PCa risk can not be evaluated fully at this stage and the appropriate screening protocols need to be developed. Follow-up validation studies, as well as studies to explore the psychological implications of genetic profile testing, will be vital prior to roll out into healthcare.

Multiple loci with different cancer specificities within the 8q24 gene desert

Recent studies based on genome-wide association, linkage, and admixture scan analysis have reported associations of various genetic variants in 8q24 with susceptibility to breast, prostate, and colorectal cancer. This locus lies within a 1.18-Mb region that contains no known genes but is bounded at its centromeric end by FAM84B and at its telomeric end by c-MYC, two candidate cancer susceptibility genes. To investigate the associations of specific loci within 8q24 with specific cancers, we genotyped the nine previously reported cancer-associated single-nucleotide polymorphisms across the region in four case-control sets of prostate (1854 case subjects and 1894 control subjects), breast (2270 case subjects and 2280 control subjects), colorectal (2299 case subjects and 2284 control subjects), and ovarian (1975 case subjects and 3411 control subjects) cancer. Five different haplotype blocks within this gene desert were specifically associated with risks of different cancers. One block was solely associated with risk of breast cancer, three others were associated solely with the risk of prostate cancer, and a fifth was associated with the risk of prostate, colorectal, and ovarian cancer, but not breast cancer. We conclude that there are at least five separate functional variants in this region.