Impact of comorbidities on prostate cancer-specific mortality: A population-based cohort study.

AIM: To assess the impact of comorbidities on prostate cancer mortality. METHODS: We studied 15,695 South Australian men diagnosed with prostate cancer between 2003 and 2019 from state-wide administrative linked data sets. Comorbidity was measured 1-year before prostate cancer diagnosis using Rx-Risk, a medication-based comorbidity index. Flexible parametric competing risk regression was used to estimate the independent association between comorbidities and prostate cancer-specific mortality. Specific common comorbidities within Rx-Risk (cardiac disorders, diabetes, chronic airway diseases, depression and anxiety, thrombosis, and pain) were also assessed to determine their association with mortality. All models were adjusted for sociodemographic variables, tumor characteristics, and treatment type. RESULTS: Prostate cancer-specific mortality was higher for patients with a Rx-Risk score ≥3 versus 0 (adjusted sub-hazard ratio (sHR) 1.34, 95% CI: 1.15-1.56). Lower comorbidity scores (Rx-Risk score 2 vs. 0 and Rx-Risk score 1 vs. 0) were not significantly associated with prostate cancer-specific mortality. Men who were using medications for cardiac disorders (sHR 1.31, 95% CI: 1.13-1.52), chronic airway disease (sHR 1.20, 95% CI: 1.01-1.44), depression and anxiety (sHR 1.17, 95% CI: 1.02-1.35), and thrombosis (sHR 1.21, 95% CI: 1.04-1.42) were at increased risk of dying from prostate cancer compared with men not on those medications. Use of medications for diabetes and chronic pain were not associated with prostate cancer-specific mortality. All Rx-Risk score categories and the specific comorbidities were also associated with increased risk of all-cause mortality. CONCLUSION: The findings showed that ≥3 comorbid conditions and specific comorbidities including cardiac disease, chronic airway disease, depression and anxiety, and thrombosis were associated with poor prostate cancer-specific survival. Appropriate management of these comorbidities may help to improve survival in prostate cancer patients.

Acquired copy number variation in prostate tumours: a review of common somatic copy number alterations, how they are formed and their clinical utility.

Prostate cancer is one of the most commonly diagnosed cancers in men and unfortunately, disease will progress in up to a third of patients despite primary treatment. Currently, there is a significant lack of prognostic tests that accurately predict disease course; however, the acquisition of somatic chromosomal variation in the form of DNA copy number variants may help understand disease progression. Notably, studies have found that a higher burden of somatic copy number alterations (SCNA) correlates with more aggressive disease, recurrence after surgery and metastasis. Here we will review the literature surrounding SCNA formation, including the roles of key tumour suppressors and oncogenes (PTEN, BRCA2, NKX3.1, ERG and AR), and their potential to inform diagnostic and prognostic clinical testing to improve predictive value. Ultimately, SCNAs, or inherited germline alterations that predispose to SCNAs, could have significant clinical utility in diagnostic and prognostic tests, in addition to guiding therapeutic selection.

Temporal trends in medication and service use patterns for mental health issues among men with prostate cancer.

OBJECTIVE: Prostate cancer can significantly impact mental wellbeing, creating uncertainty and morbidity. This study described patterns of psychotropic medication and mental health service use, as a proxy measure for mental health problems, 5 years before and 5 years after prostate cancer diagnosis. METHODS: Population-based registry data were linked with Pharmaceutical Benefits Scheme and Medicare Benefits Schedule data for all prostate cancer patients diagnosed in South Australia between 2012 and 2020 (n = 13,693). We estimated the proportion and rates of psychotropic medication and mental health service use before and after diagnosis. Multivariable adjusted interrupted time series analyses (ITSA) were conducted to uncover temporal patterns. RESULTS: Fifteen percent of men commenced psychotropic medications and 6.4% sought out mental health services for the first time after diagnosis. Psychotropic medication use rose from 34.5% 5 years before to 40.3% 5 years after diagnosis, including an increase in use of antidepressants (from 20.7% to 26.0%) and anxiolytics (from 11.3% to 12.8%). Mental health service use increased from 10.2% to 12.1%, with the increase mostly being general practice mental health visits (from 7.8% to 10.6%). Multivariable ITSA indicated a significant rise in medication and service utilisation immediately before and in the first 2 years following prostate cancer diagnosis. CONCLUSION: There is a clear increase in psychotropic medication use and mental health service use around the time of prostate cancer diagnosis. Mental health outcomes of men with prostate cancer may be improved with early mental health screening, particularly during the diagnosis process, to enable early intervention.

Identification of a novel recurrent EEF2 gene amplification in familial prostate tumors.

Recurrent tumor copy number variations (CNVs) in prostate cancer (PrCa) have predominantly been discovered in sporadic tumor cohorts. Here, we examined familial prostate tumors for novel CNVs as prior studies suggest these harbor distinct CNVs. Array comparative genomic hybridization of 12 tumors from an Australian PrCa family, PcTas9, highlighted multiple recurrent CNVs, including amplification of EEF2 (19p13.3) in 100% of tumors. The EEF2 CNV was examined in a further 26 familial and seven sporadic tumors from the Australian cohort and in 494 tumors unselected for family history from The Cancer Genome Atlas (TCGA). EEF2 overexpression was observed in seven PcTas9 tumors, in addition to seven other predominantly familial tumors (ntotal  = 34%). EEF2 amplification was only observed in 1.4% of TCGA tumors, however 7.5% harbored an EEF2 deletion. Analysis of genes co-expressed with EEF2 revealed significant upregulation of two genes, ZNF74 and ADSL, and downregulation of PLSCR1 in both EEF2 amplified familial tumors and EEF2 deleted TCGA tumors. Furthermore, in TCGA tumors, EEF2 amplification and deletion were significantly associated with a higher Gleason score. In summary, we identified a novel PrCa CNV that was predominantly amplified in familial tumors and deleted in unselected tumors. Our results provide further evidence that familial tumors harbor distinct CNVs, potentially due to an inherited predisposition, but also suggest that regardless of how EEF2 is dysregulated, a similar set of genes involved in key cancer pathways are impacted. Given the current lack of gene-based biomarkers and clinical targets in PrCa, further investigation of EEF2 is warranted.

Analysis of a large prostate cancer family identifies novel and recurrent gene fusion events providing evidence for inherited predisposition.

There is strong interest in the characterisation of gene fusions and their use to enhance clinical practices in prostate cancer (PrCa). Significantly, ~50% of prostate tumours harbour a gene fusion. Inherited factors are thought to predispose to these events but, to date, only one study has investigated gene fusions in a familial context. Here, we examined the prevalence and diversity of gene fusions in 14 tumours from a single large PrCa family, PcTas9, using the TruSight® RNA Fusion Panel and Sanger sequencing validation. These fusions were then explored in The Cancer Genome Atlas (TCGA) PrCa data set (n = 494). Overall, 64.3% of PcTas9 tumours harboured a gene fusion, including known erythroblast transformation-specific (ETS) fusions involving ERG and ETV1, and two novel gene fusions, C19orf48:ETV4 and RYBP:FOXP1. Although 3' ETS genes were overexpressed in PcTas9 and TCGA tumour samples, 3' fusion of FOXP1 did not appear to alter its expression. In addition, PcTas9 fusion carriers were more likely to have lower-grade disease than noncarriers (p = 0.02). Likewise, TCGA tumours with high-grade disease were less likely to harbour fusions (p = 0.03). Our study further implicates an inherited predisposition to PrCa gene fusion events, which are associated with less aggressive tumours. This knowledge could lead to clinical strategies to predict men at risk for fusion-positive PrCa and, thus, identify patients who are more or less at risk of aggressive disease and/or responsive to particular therapies.

The effect of insulin on response to intravitreal anti-VEGF injection in diabetic macular edema in type 2 diabetes mellitus.

OBJECTIVES: To assess whether insulin therapy impacts the effectiveness of anti-vascular endothelial growth factor (anti-VEGF) injection for the treatment of diabetic macular edema (DME) in type 2 diabetes mellitus. METHODS: This was a retrospective multi-center analysis. The best-corrected visual acuity (BCVA) at 12 months, BCVA change, central macular thickness (CMT), CMT change, and cumulative injection number were compared between the insulin and the oral hypoglycemic agent (OHA) groups. RESULTS: The mean final BCVA and CMT improved in both the insulin (N = 137; p < 0.001; p < 0.001, respectively) and the OHA group (N = 61; p = 0.199; p < 0.001, respectively). The two treatment groups were comparable for final BCVA (p = 0.263), BCVA change (p = 0.184), final CMT (p = 0.741), CMT change (p = 0.458), and the cumulative injections received (p = 0.594). The results were comparable between the two groups when stratified by baseline vision (p > 0.05) and baseline HbA1c (p > 0.05). CONCLUSION: Insulin therapy does not alter treatment outcomes for anti-VEGF therapy in DME.

Identifying Genetic Biomarkers Predicting Response to Anti-Vascular Endothelial Growth Factor Injections in Diabetic Macular Edema.

Intraocular anti-vascular endothelial growth factor (VEGF) therapies are the front-line treatment for diabetic macular edema (DME); however, treatment response varies widely. This study aimed to identify genetic determinants associated with anti-VEGF treatment response in DME. We performed a genome-wide association study on 220 Australian patients with DME treated with anti-VEGF therapy, genotyped on the Illumina Global Screening Array, and imputed to the Haplotype Reference Consortium panel. The primary outcome measures were changes in central macular thickness (CMT in microns) and best-corrected visual acuity (BCVA in ETDRS letters) after 12 months. Association between single nucleotide polymorphism (SNP) genotypes and DME outcomes were evaluated by linear regression, adjusting for the first three principal components, age, baseline CMT/BCVA, duration of diabetic retinopathy, and HbA1c. Two loci reached genome-wide significance (p < 5 × 10−8) for association with increased CMT: a single SNP on chromosome 6 near CASC15 (rs78466540, p = 1.16 × 10−9) and a locus on chromosome 12 near RP11-116D17.1 (top SNP rs11614480, p = 2.69 × 10−8). Four loci were significantly associated with reduction in BCVA: two loci on chromosome 11, downstream of NTM (top SNP rs148980760, p = 5.30 × 10−9) and intronic in RP11-744N12.3 (top SNP rs57801753, p = 1.71 × 10−8); one near PGAM1P1 on chromosome 5 (rs187876551, p = 1.52 × 10−8); and one near TBC1D32 on chromosome 6 (rs118074968, p = 4.94 × 10−8). In silico investigations of each locus identified multiple expression quantitative trait loci and potentially relevant candidate genes warranting further analysis. Thus, we identified multiple genetic loci predicting treatment outcomes for anti-VEGF therapies in DME. This work may potentially lead to managing DME using personalized treatment approaches.

A rare variant in EZH2 is associated with prostate cancer risk.

Prostate cancer (PrCa) is highly heritable, and although rare variants contribute significantly to PrCa risk, few have been identified to date. Herein, whole-genome sequencing was performed in a large PrCa family featuring multiple affected relatives spanning several generations. A rare, predicted splice site EZH2 variant, rs78589034 (G > A), was identified as segregating with disease in all but two individuals in the family, one of whom was affected with lymphoma and bowel cancer and a female relative. This variant was significantly associated with disease risk in combined familial and sporadic PrCa datasets (n = 1551; odds ratio [OR] = 3.55, P = 1.20 × 10-5 ). Transcriptome analysis was performed on prostate tumour needle biopsies available for two rare variant carriers and two wild-type cases. Although no allele-dependent differences were detected in EZH2 transcripts, a distinct differential gene expression signature was observed when comparing prostate tissue from the rare variant carriers with the wild-type samples. The gene expression signature comprised known downstream targets of EZH2 and included the top-ranked genes, DUSP1, FOS, JUNB and EGR1, which were subsequently validated by qPCR. These data provide evidence that rs78589034 is associated with increased PrCa risk in Tasmanian men and further, that this variant may be associated with perturbed EZH2 function in prostate tissue. Disrupted EZH2 function is a driver of tumourigenesis in several cancers, including prostate, and is of significant interest as a therapeutic target.

A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

BACKGROUND: Molecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed. METHODS: Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic-lethal events from those who remained recurrence-free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan-Meier curves and receiver operating characteristic analyses to evaluate the model's performance. RESULTS: Thirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four-gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic-lethal events compared to those without recurrence in the testing dataset (P = 5.7 × 10-11 ). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC] = 0.76; 95% confidence interval [CI] = 0.69-0.83; partial area under the ROC curve [pAUC] = 0.008) than GS alone (AUC = 0.63; 95% CI = 0.56-0.70; pAUC = 0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment-Surgery). CONCLUSION: Our validated 4GT score has prognostic value for metastatic-lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.

Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens.

Prognostic genomic biomarkers that can be measured at diagnosis to aid choice of treatment options are unavailable for most common cancers. This is due in part to the poor quality and quantity of available diagnostic specimens for discovery research and to limitations in genomic technologies. Recent technical advances now enable high-density molecular analyses using suboptimal biological specimens. Here we describe the optimization of a transcriptome-specific protocol for use with formalin-fixed, paraffin-embedded (FFPE) diagnostic prostate cancer (PrCa) specimens. We applied the Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq Kit) to RNA samples extracted from 36 tumor-enriched and 16 adjacent normal tissues (ADJNT) from 37 FFPE PrCa specimens over a series of eight pilot studies, incorporating protocol modifications from Pilots 2 to 5. Data quality were measured by (1) the total number of mapped reads; (2) the percentage of reads that mapped to AmpliSeq target regions (OnTarget%); (3) the percentage of genes on the AmpliSeq panel with a read count ≥10 (TargetsDetected%); and (4) comparing the gene read-count distribution of the prostate tissue samples with the median gene read-count distribution of cell line-derived RNA samples. Modifications incorporated into Pilot study 5 provided gene expression data equivalent to cell line-derived RNA samples. These modifications included the use of freshly cut slides for macrodissection; increased tissue section thickness (8 µm); RNA extraction using the RecoverAll Total Nucleic Acid Isolation Kit for FFPE (ThermoFisher); 18 target amplification cycles; and processing six samples per Ion PI chip. This protocol will facilitate the discovery of prognostic biomarkers for cancer by allowing researchers to exploit previously underutilized diagnostic FFPE specimens.

Prostate cancer risk regions at 8q24 and 17q24 are differentially associated with somatic TMPRSS2:ERG fusion status.

Molecular and epidemiological differences have been described between TMPRSS2:ERG fusion-positive and fusion-negative prostate cancer (PrCa). Assuming two molecularly distinct subtypes, we have examined 27 common PrCa risk variants, previously identified in genome-wide association studies, for subtype specific associations in a total of 1221 TMPRSS2:ERG phenotyped PrCa cases. In meta-analyses of a discovery set of 552 cases with TMPRSS2:ERG data and 7650 unaffected men from five centers we have found support for the hypothesis that several common risk variants are associated with one particular subtype rather than with PrCa in general. Risk variants were analyzed in case-case comparisons (296 TMPRSS2:ERG fusion-positive versus 256 fusion-negative cases) and an independent set of 669 cases with TMPRSS2:ERG data was established to replicate the top five candidates. Significant differences (P < 0.00185) between the two subtypes were observed for rs16901979 (8q24) and rs1859962 (17q24), which were enriched in TMPRSS2:ERG fusion-negative (OR = 0.53, P = 0.0007) and TMPRSS2:ERG fusion-positive PrCa (OR = 1.30, P = 0.0016), respectively. Expression quantitative trait locus analysis was performed to investigate mechanistic links between risk variants, fusion status and target gene mRNA levels. For rs1859962 at 17q24, genotype dependent expression was observed for the candidate target gene SOX9 in TMPRSS2:ERG fusion-positive PrCa, which was not evident in TMPRSS2:ERG negative tumors. The present study established evidence for the first two common PrCa risk variants differentially associated with TMPRSS2:ERG fusion status. TMPRSS2:ERG phenotyping of larger studies is required to determine comprehensive sets of variants with subtype-specific roles in PrCa.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium.

This corrects the article DOI: 10.1038/bjc.2017.231.

Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study.

BACKGROUND: Global measures of peripheral blood DNA methylation have been associated with risk of some malignancies, including breast, bladder, and gastric cancer. Here, we examined genome-wide measures of peripheral blood DNA methylation in prostate cancer and its non-aggressive and aggressive disease forms. METHODS: We used a matched, case-control study of 687 incident prostate cancer samples, nested within a larger prospective cohort study. DNA methylation was measured in pre-diagnostic, peripheral blood samples using the Illumina Infinium HM450K BeadChip. Genome-wide measures of DNA methylation were computed as the median M-value of all CpG sites and according to CpG site location and regulatory function. We used conditional logistic regression to test for associations between genome-wide measures of DNA methylation and risk of prostate cancer and its subtypes, and by time between blood draw and diagnosis. RESULTS: We observed no associations between the genome-wide measure of DNA methylation based on all CpG sites and risk of prostate cancer or aggressive disease. Risk of non-aggressive disease was associated with higher methylation of CpG islands (OR = 0.80; 95%CI = 0.68-0.94), promoter regions (OR = 0.79; 95%CI = 0.66-0.93), and high density CpG regions (OR = 0.80; 95%CI = 0.68-0.94). Additionally, higher methylation of all CpGs (OR = 0.66; 95%CI = 0.48-0.89), CpG shores (OR = 0.62; 95%CI = 0.45-0.84), and regulatory regions (OR = 0.68; 95% CI = 0.51-0.91) was associated with a reduced risk of overall prostate cancer within 5 years of blood draw but not thereafter. CONCLUSIONS: A reduced risk of overall prostate cancer within 5 years of blood draw and non-aggressive prostate cancer was associated with higher genome-wide methylation of peripheral blood DNA. While these data have no immediate clinical utility, with further work they may provide insight into the early events of prostate carcinogenesis. Prostate 77:471-478, 2017. © 2017 Wiley Periodicals, Inc.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium.

BACKGROUND: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. METHODS: We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. RESULTS: The results suggest that height is associated with high-grade prostate cancer risk. Men with height >180 cm are at a 22% increased risk as compared to men with height <173 cm (OR 1.22, 95% CI 1.01-1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. CONCLUSIONS: There was no evidence of gene-environment interaction between height and the selected candidate SNPs.Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.

Genome-wide measures of DNA methylation in peripheral blood and the risk of urothelial cell carcinoma: a prospective nested case-control study.

BACKGROUND: Global DNA methylation has been reported to be associated with urothelial cell carcinoma (UCC) by studies using blood samples collected at diagnosis. Using the Illumina HumanMethylation450 assay, we derived genome-wide measures of blood DNA methylation and assessed them for their prospective association with UCC risk. METHODS: We used 439 case-control pairs from the Melbourne Collaborative Cohort Study matched on age, sex, country of birth, DNA sample type, and collection period. Conditional logistic regression was used to compute odds ratios (OR) of UCC risk per s.d. of each genome-wide measure of DNA methylation and 95% confidence intervals (CIs), adjusted for potential confounders. We also investigated associations by disease subtype, sex, smoking, and time since blood collection. RESULTS: The risk of superficial UCC was decreased for individuals with higher levels of our genome-wide DNA methylation measure (OR=0.71, 95% CI: 0.54-0.94; P=0.02). This association was particularly strong for current smokers at sample collection (OR=0.47, 95% CI: 0.27-0.83). Intermediate levels of our genome-wide measure were associated with decreased risk of invasive UCC. Some variation was observed between UCC subtypes and the location and regulatory function of the CpGs included in the genome-wide measures of methylation. CONCLUSIONS: Higher levels of our genome-wide DNA methylation measure were associated with decreased risk of superficial UCC and intermediate levels were associated with reduced risk of invasive disease. These findings require replication by other prospective studies.

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21.

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e(-8)) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e(-11)). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer predisposition locus.

Prediction of individual genetic risk to prostate cancer using a polygenic score.

BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Associations of prostate cancer risk variants with disease aggressiveness: results of the NCI-SPORE Genetics Working Group analysis of 18,343 cases.

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤ 6, 7, ≥ 8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR = 0.77; 95 % CI 0.69-0.87) and high-grade disease (OR = 0.77; 95 % CI 0.68-0.86) in European men. Similar associations with aggressive (OR = 0.72; 95 % CI 0.58-0.89) and high-grade disease (OR = 0.69; 95 % CI 0.54-0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (<4.0 ng/mL) in both European and African-American men. Our results provide further support that a PC-risk SNP rs2735839 near the KLK3 gene on chromosome 19q13 may be associated with aggressive and high-grade PC. Future prospectively designed, case-case GWAS are needed to identify additional SNPs associated with PC aggressiveness.

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease.

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ≤ 1E (-3)) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.

Utility of prescription-based comorbidity indices for predicting mortality among Australian men with prostate cancer.

BACKGROUND: Drug prescription registries has become an alternative data source to hospital admission databases for measuring comorbidities. However, the predictive validity of prescription-based comorbidity measures varies based on the population under investigation and outcome of interest. We aimed to determine which prescription-based index of comorbidity has most utility in Australian men with prostate cancer. METHODS: We studied 25,414 South Australian men diagnosed with prostate cancer between 2003 and 2019 from state-wide administrative linked datasets. The Rx-Risk index, Chronic Disease Score (CDS), Drug Comorbidity Index (DCI) and Pharmaceutical Prescribing Profile (P3) with one year lookback period from prostate cancer diagnosis were evaluated. The predictive ability of each index to determine all-cause deaths within two and five years of prostate cancer diagnosis was compared using the c-statistic from flexible parametric survival models, adjusting for age, socioeconomic status and year of prostate cancer diagnosis. RESULTS: The Rx-Risk index performed better in predicting two-year (c-statistic = 0.818) and five-year (c-statistic = 0.784) all-cause mortality than P3, CDS and DCI. Including comorbidity measures as continuous scores resulted in a better performance than including them as categories. Grouping scores into four categories (≤0, >0 - ≤1, >1 - ≤2, and >2) resulted in better performance and calibration than using fewer categories. CONCLUSION: Rx-Risk was validated in Australia and reflects Australian prescribing patterns. It showed better predictive performance for mortality in our study, with a modest improvement over P3, CDS and DCI. For research with prostate cancer populations, we recommend the use of drug-based comorbidity indices that have been validated in a similar population.