Search

Background The development of prostate cancer can be influenced by genetic and environmental factors. Numerous germline SNPs influence prostate cancer susceptibility. The functional pathways in which these SNPs increase prostate cancer susceptibility are unknown. Finasteride is currently not being used routinely as a chemoprevention agent but the long term outcomes of the PCPT trial are awaited. The outcomes of the SELECT trial have not recommended the use of chemoprevention in preventing prostate cancer. This study investigated whether germline risk SNPs could be used to predict outcomes in the PCPT and SELECT trial. Methods Genotyping was performed in European men entered into the PCPT trial (n = 2434) and SELECT (n = 4885). Next generation genotyping was performed using Affymetrix® Eureka™ Genotyping protocols. Logistic regression models were used to test the association of risk scores and the outcomes in the PCPT and SELECT trials. Results Of the 100 SNPs, 98 designed successfully and genotyping was validated for samples genotyped on other platforms. A number of SNPs predicted for aggressive disease in both trials. Men with a higher polygenic score are more likely to develop prostate cancer in both trials, but the score did not predict for other outcomes in the trial. Conclusion Men with a higher polygenic risk score are more likely to develop prostate cancer. There were no interactions of these germline risk SNPs and the chemoprevention agents in the SELECT and PCPT trials.

Ifosfamide is used to treat soft-tissue sarcoma (STS) and bone sarcoma (BS), with improved efficacy at doses above 9 g/m2/cycle. To mitigate treatment-associated toxicity with higher doses, continuous infusional ifosfamide is increasingly used. However, clinical outcome data remain limited. Single-centre retrospective analysis of patients treated with four-weekly infusional ifosfamide (14 g/m2/14d) between August 2012 and February 2019 was conducted. Radiological response, progression-free survival (PFS), overall survival (OS) and toxicity were evaluated. Eighty patients were treated&mdash, 46 with STS and 34 with BS. Patients received a median of three cycles of infusional ifosfamide (1&ndash, 24). Overall disease control rate (DCR) in STS was 50% (23 of 46 patients), with a median PFS of 3.8 months, and median OS of 13.0 months. In synovial sarcoma (SS), DCR was 80% (12/15), median PFS 8.1 months and median OS 20.9 months. Overall DCR in BS (34 patients) was 30%, with a median PFS of 2.5 months and median OS of 6.2 months. Five patients (6%) stopped treatment due to toxicity alone within the first two cycles. A further 10 patients stopped treatment due to toxicity during later treatment cycles (12%) and 18 patients (23%) required dose modification. Forty-five patients (56%) experienced grade (G) 3/4 haematological toxicity, with 12 episodes of febrile neutropenia and one treatment-related death. Twenty-seven patients (34%) experienced G3/4 non-haematological toxicity, most commonly nausea and vomiting (10, 13%). In summary, infusional ifosfamide has efficacy in STS, most notable in SS. Benefit appears limited in BS. Treatment is associated with toxicity that requires specialist supportive care.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials. Postprint

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .

Familial and twin studies have demonstrated a significant inherited component to prostate cancer predisposition. Genome wide association studies have shown that there are 100 single nucleotide polymorphisms which have been associated with the development of prostate cancer. This review aims to discuss the scientific methods used to identify these susceptibility loci. It will also examine the current clinical utility of these loci, which include the development of risk models as well as predicting treatment efficacy and toxicity. In order to refine the clinical utility of the susceptibility loci, international consortia have been developed to combine statistical power as well as skills and knowledge to further develop models that could be used to predict risk and treatment outcomes., Prostate cancer is one of the most common cancers to occur in men in the western world. The incidence of prostate cancer is however lower in Asian countries. There are some families who have many male members affected with prostate cancer. The incidence of prostate cancer is also increased in men of Afro-Caribbean ancestry. Studies have shown that there are inherited genetic changes that may be accounting for these differences, however only one third of these changes have been discovered so far. This review aims to discuss how these genetic changes have been discovered and how they can potentially be used in every day clinical practice.

1 Background: Currently genome-wide association studies (GWAS) have identified over 100 prostate cancer (PrCa) susceptibility loci, capturing 33% of the PrCa familial relative risk (FRR) in Europeans. To identify further susceptibility variants, we conducted a PrCa GWAS, larger than previous studies, comprising ~49,000 cases and ~29,000 controls among individuals of European and Asian descent using the OncoArray, a platform consisting of a 260K GWAS backbone and 310K custom content selected from previous GWAS and fine-mapping studies of multiple cancers ( http://epi.grants.cancer.gov/oncoarray/ ). Methods: Genotypes from the OncoArray were used to impute genotypes from ~70M variants using the October 2014 release of the 1000 genomes project as a reference, and then combined with several previous PrCa GWAS of European ancestry: UK stage 1 (1,906 cases/1,934 controls) and stage 2 (3,888 cases/3,956 controls); CaPS 1 (498 cases/502 controls) and CaPS 2 (1,483 cases/519 controls); BPC3 (2,137 cases/3,101 controls); NCI PEGASUS (4,622 cases/2,954 controls); and iCOGS (21,209 cases/ 20,440 controls). Risk analyses for overall PrCa risk, aggressive PrCa (several definitions defined by PrCa clinical characteristics), and Gleason score were performed. Logistic and linear regression summary statistics were meta-analysed using an inverse variance fixed effect approach. Results: We identified novel loci significantly associated ( P < 5.0x10-8) with overall PrCa (N = 65). Our novel findings are comprised of several missense variants, including a SNP in the ATM gene - a key member of the DNA repair pathway. When combined multiplicatively, the 65 novel PrCa loci identified here increases the captured heritability of PrCa, explaining 38.5% of the FRR when combining novel and previously identified PrCa loci. Conclusions: In risk stratification, men in the top 1% of the genetic risk score group have a relative risk of 5.6 fold for developing PrCa compared with the median risk group. These results will improve the utility of genetic risk scores for targeted screening and prevention for prostate cancer.