Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

MRI-Targeted or Standard Biopsy in Prostate Cancer Screening.

BACKGROUND: High rates of overdiagnosis are a critical barrier to organized prostate cancer screening. Magnetic resonance imaging (MRI) with targeted biopsy has shown the potential to address this challenge, but the implications of its use in the context of organized prostate cancer screening are unknown. METHODS: We conducted a population-based noninferiority trial of prostate cancer screening in which men 50 to 74 years of age from the general population were invited by mail to participate; participants with prostate-specific antigen (PSA) levels of 3 ng per milliliter or higher were randomly assigned, in a 2:3 ratio, to undergo a standard biopsy (standard biopsy group) or to undergo MRI, with targeted and standard biopsy if the MRI results suggested prostate cancer (experimental biopsy group). The primary outcome was the proportion of men in the intention-to-treat population in whom clinically significant cancer (Gleason score ≥7) was diagnosed. A key secondary outcome was the detection of clinically insignificant cancers (Gleason score 6). RESULTS: Of 12,750 men enrolled, 1532 had PSA levels of 3 ng per milliliter or higher and were randomly assigned to undergo biopsy: 603 were assigned to the standard biopsy group and 929 to the experimental biopsy group. In the intention-to-treat analysis, clinically significant cancer was diagnosed in 192 men (21%) in the experimental biopsy group, as compared with 106 men (18%) in the standard biopsy group (difference, 3 percentage points; 95% confidence interval [CI], -1 to 7; P<0.001 for noninferiority). The percentage of clinically insignificant cancers was lower in the experimental biopsy group than in the standard biopsy group (4% [41 participants] vs. 12% [73 participants]; difference, -8 percentage points; 95% CI, -11 to -5). CONCLUSIONS: MRI with targeted and standard biopsy in men with MRI results suggestive of prostate cancer was noninferior to standard biopsy for detecting clinically significant prostate cancer in a population-based screening-by-invitation trial and resulted in less detection of clinically insignificant cancer. (Funded by the Swedish Research Council and others; STHLM3-MRI ClinicalTrials.gov number, NCT03377881.).

Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks.

MOTIVATION: Molecular phenotyping by gene expression profiling is central in contemporary cancer research and in molecular diagnostics but remains resource intense to implement. Changes in gene expression occurring in tumours cause morphological changes in tissue, which can be observed on the microscopic level. The relationship between morphological patterns and some of the molecular phenotypes can be exploited to predict molecular phenotypes from routine haematoxylin and eosin-stained whole slide images (WSIs) using convolutional neural networks (CNNs). In this study, we propose a new, computationally efficient approach to model relationships between morphology and gene expression. RESULTS: We conducted the first transcriptome-wide analysis in prostate cancer, using CNNs to predict bulk RNA-sequencing estimates from WSIs for 370 patients from the TCGA PRAD study. Out of 15 586 protein coding transcripts, 6618 had predicted expression significantly associated with RNA-seq estimates (FDR-adjusted P-value <1×10-4) in a cross-validation and 5419 (81.9%) of these associations were subsequently validated in a held-out test set. We furthermore predicted the prognostic cell-cycle progression score directly from WSIs. These findings suggest that contemporary computer vision models offer an inexpensive and scalable solution for prediction of gene expression phenotypes directly from WSIs, providing opportunity for cost-effective large-scale research studies and molecular diagnostics. AVAILABILITY AND IMPLEMENTATION: A self-contained example is available from http://github.com/phiwei/prostate_coexpression. Model predictions and metrics are available from doi.org/10.5281/zenodo.4739097. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prognostic Value of Low-Pass Whole Genome Sequencing of Circulating Tumor DNA in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: Multiple treatments are available for metastatic castration-resistant prostate cancer (mCRPC), including androgen receptor signaling inhibitors (ARSI) enzalutamide and abiraterone, but therapy resistance remains a major clinical obstacle. We examined the clinical utility of low-pass whole-genome sequencing (LPWGS) of circulating tumor DNA (ctDNA) for prognostication in mCRPC. METHODS: A total of 200 plasma samples from 143 mCRPC patients collected at the start of first-line ARSI treatment (baseline) and at treatment termination (n = 57, matched) were analyzed by LPWGS (median: 0.50X) to access ctDNA% and copy number alteration (CNA) patterns. The best confirmed prostate specific antigen (PSA) response (≥50% decline [PSA50]), PSA progression-free survival (PFS), and overall survival (OS) were used as endpoints. For external validation, we used plasma LPWGS data from an independent cohort of 70 mCRPC patients receiving first-line ARSI. RESULTS: Baseline ctDNA% ranged from ≤3.0% to 73% (median: 6.6%) and CNA burden from 0% to 82% (median: 13.1%) in the discovery cohort. High ctDNA% and high CNA burden at baseline was associated with poor PSA50 response (P = 0.0123/0.0081), poor PFS (P < 0.0001), and poor OS (P < 0.0001). ctDNA% and CNA burden was higher at PSA progression than at baseline in 32.7% and 42.3% of the patients. High ctDNA% and high CNA burden at baseline was also associated with poor PFS and OS (P ≤ 0.0272) in the validation cohort. CONCLUSIONS: LPWGS of ctDNA provides clinically relevant information about the tumor genome in mCRPC patients. Using LPWGS data, we show that high ctDNA% and CNA burden at baseline is associated with short PFS and OS in 2 independent cohorts.

Prostate cancer screening using a combination of risk-prediction, MRI, and targeted prostate biopsies (STHLM3-MRI): a prospective, population-based, randomised, open-label, non-inferiority trial.

BACKGROUND: Screening for prostate cancer using prostate-specific antigen (PSA) reduces prostate cancer mortality but can lead to adverse outcomes. We aimed to compare a traditional screening approach with a diagnostic strategy of blood-based risk prediction combined with MRI-targeted biopsies. METHODS: We did a prospective, population-based, randomised, open-label, non-inferiority trial (STHLM3-MRI) in Stockholm county, Sweden. Men aged 50-74 years were randomly selected by Statistics Sweden and invited by mail to participate in screening; those with an elevated risk of prostate cancer, defined as either a PSA of 3 ng/mL or higher or a Stockholm3 score of 0·11 or higher were eligible for randomisation. Men with a previous prostate cancer diagnosis, who had undergone a prostate biopsy within 60 days before the invitation to participate, with a contraindication for MRI, or with severe illness were excluded. Eligible participants were randomly assigned (2:3) using computer-generated blocks of five, stratified by clinically significant prostate cancer risk, to receive either systematic prostate biopsies (standard group) or biparametric MRI followed by MRI-targeted and systematic biopsy in MRI-positive participants (experimental group). The primary outcome was the detection of clinically significant prostate cancer at prostate biopsy, defined as a Gleason score of 3 + 4 or higher. We used a margin of 0·78 to assess non-inferiority for the primary outcome. Key secondary outcome measures included the proportion of men with clinically insignificant prostate cancer (defined as a Gleason score of 3 + 3), and the number of any prostate MRI and biopsy procedures done. We did two comparisons: Stockholm3 (using scores of 0·11 and 0·15 as cutoffs) versus PSA in the experimental group (paired analyses) and PSA plus standard biopsy versus Stockholm3 plus MRI-targeted and systematic biopsy (unpaired, randomised analyses). All analyses were intention to treat. This study is registered with ClinicalTrials.gov, NCT03377881. FINDINGS: Between Feb 5, 2018, and March 4, 2020, 49 118 men were invited to participate, of whom 12 750 were enrolled and provided blood specimens, and 2293 with elevated risk were randomly assigned to the experimental group (n=1372) or the standard group (n=921). The area under the receiver-operating characteristic curve for detection of clinically significant prostate cancer was 0·76 (95% CI 0·72-0·80) for Stockholm3 and 0·60 (0·54-0·65) for PSA. In the experimental group, a Stockholm3 of 0·11 or higher was non-inferior to a PSA of 3 ng/mL or higher for detection of clinically significant prostate cancer (227 vs 192; relative proportion [RP] 1·18 [95% CI 1·09-1·28], p<0·0001 for non-inferiority), and also detected a similar number of low-grade prostate cancers (50 vs 41; 1·22 [0·96-1·55], p=0·053 for superiority) and was associated with more MRIs and biopsies. Compared with PSA of 3 ng/mL or higher, a Stockholm3 of 0·15 or higher provided identical sensitivity to detect clinically significant cancer, and led to fewer MRI procedures (545 vs 846; 0·64 [0·55-0·82]) and fewer biopsy procedures (311 vs 338; 0·92 (0·86-1·03). Compared with screening using PSA and systematic biopsies, a Stockholm3 of 0·11 or higher combined with MRI-targeted and systematic biopsies was associated with higher detection of clinically significant cancers (227 [3·0%] men tested vs 106 [2·1%] men tested; RP 1·44 [95% CI 1·15-1·81]), lower detection of low-grade cancers (50 [0·7%] vs 73 [1·4%]; 0·46 [0·32-0·66]), and led to fewer biopsy procedures. Patients randomly assigned to the experimental group had a lower incidence of prescription of antibiotics for infection (25 [1·8%] of 1372 vs 41 [4·4%] of 921; p=0·0002) and a lower incidence of admission to hospital (16 [1·2%] vs 31 [3·4%]; p=0·0003) than those in the standard group. INTERPRETATION: The Stockholm3 test can inform risk stratification before MRI and targeted biopsies in prostate cancer screening. Combining the Stockholm3 test with an MRI-targeted biopsy approach for prostate cancer screening decreases overdetection while maintaining the ability to detect clinically significant cancer. FUNDING: The Swedish Cancer Society, the Swedish Research Council, and Stockholm City Council.

Predictors of adverse pathology on radical prostatectomy specimen in men initially enrolled in active surveillance for low-risk prostate cancer.

PURPOSE: To evaluate clinical variables, including magnetic resonance imaging (MRI) predictive of adverse pathology (AP) at radical prostatectomy (RP) in men initially enrolled in active surveillance (AS). METHODS: A population-based cohort study of men diagnosed with low-risk prostate cancer (PCa), in Stockholm County, Sweden, during 2008-2017 enrolled in AS their intended primary treatment followed by RP. AP was defined as ISUP grade group ≥ 3 and/or pT-stage ≥ T3. Association between clinical variables at diagnosis and time to AP was evaluated using Cox regression and multivariate logistic regression to evaluate the association between AP and clinical variables at last biopsy before RP. RESULTS: In a cohort of 6021 patients with low-risk PCa, 3116 were selected for AS and 216 underwent RP. Follow-up was 10 years, with a median time on AS of 23 months. 37.7% of patients had AP at RP. Clinical T-stage [Hazard ratio (HR): 1.81, 95% confidence interval (CI) 1.04-3.18] and PSA (HR: 1.31, 95% CI 1.17-1.46) at diagnosis and age [Odds Ratio (OR): 1.09, 95% CI 1.02-1.18), PSA (OR: 1.22, 95% CI 1.07-1.41), and PI-RADS (OR 1.66, 95% CI 1.11-2.55)] at last re-biopsy were significantly associated with AP. CONCLUSION: PI-RADS score is significantly associated with AP at RP and support current guidelines recommending MRI before enrollment in AS. Furthermore, age, cT-stage, and PSA are significantly associated with AP.

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatment and undertreatment of prostate cancer. To alleviate these problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accuracy for prostate cancer detection, localisation, and Gleason grading. METHODS: We digitised 6682 slides from needle core biopsies from 976 randomly selected participants aged 50-69 in the Swedish prospective and population-based STHLM3 diagnostic study done between May 28, 2012, and Dec 30, 2014 (ISRCTN84445406), and another 271 from 93 men from outside the study. The resulting images were used to train deep neural networks for assessment of prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test dataset comprising 1631 biopsies from 246 men from STHLM3 and an external validation dataset of 330 biopsies from 73 men. We also evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics and tumour extent predictions by correlating predicted cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI system and the expert urological pathologists using Cohen's kappa. FINDINGS: The AI achieved an area under the receiver operating characteristics curve of 0·997 (95% CI 0·994-0·999) for distinguishing between benign (n=910) and malignant (n=721) biopsy cores on the independent test dataset and 0·986 (0·972-0·996) on the external validation dataset (benign n=108, malignant n=222). The correlation between cancer length predicted by the AI and assigned by the reporting pathologist was 0·96 (95% CI 0·95-0·97) for the independent test dataset and 0·87 (0·84-0·90) for the external validation dataset. For assigning Gleason grades, the AI achieved a mean pairwise kappa of 0·62, which was within the range of the corresponding values for the expert pathologists (0·60-0·73). INTERPRETATION: An AI system can be trained to detect and grade cancer in prostate needle biopsy samples at a ranking comparable to that of international experts in prostate pathology. Clinical application could reduce pathology workload by reducing the assessment of benign biopsies and by automating the task of measuring cancer length in positive biopsy cores. An AI system with expert-level grading performance might contribute a second opinion, aid in standardising grading, and provide pathology expertise in parts of the world where it does not exist. FUNDING: Swedish Research Council, Swedish Cancer Society, Swedish eScience Research Center, EIT Health.

The economic burden of prostate cancer - a Swedish prevalence-based register study.

BACKGROUND: Incidence and prevalence of prostate cancer in Sweden have increased markedly due to prostate-specific antigen (PSA) testing. Moreover, new diagnostic tests and treatment technologies are expected to further increase the overall costs. Our aims were (i) to estimate the societal costs for existing testing, diagnosis, management and treatment of prostate cancer, and (ii) to provide reference values for future cost-effectiveness analyses of prostate cancer screening and treatment. METHODS: Taking a societal perspective, this study aimed to investigate the annual cost of prostate cancer in Sweden using a prevalence-based cost-of-illness approach. Resource utilisation and related costs within Stockholm Region during 2016 were quantified using data from the Stockholm PSA and Biopsy Register and other health and population registers. Costs included: (i) direct medical costs for health care utilisation at primary care, hospitals, palliative care and prescribed drugs; (ii) informal care; and (iii) indirect costs due to morbidity and premature mortality. The resource utilisation was valued using unit costs for direct medical costs and the human capital method for informal care and indirect costs. Costs for the Stockholm region were extrapolated to Sweden based on cancer prevalence and the average costs by age and resource type. RESULTS: The societal costs due to prostate cancer in Stockholm in 2016 were estimated to be €64 million Euro (€Mn), of which the direct medical costs, informal care and productivity losses represented 62, 28 and 10% of the total costs, respectively. The total annual costs extrapolated to Sweden were calculated to be €281 Mn. The average direct medical cost, average costs for informal care and productivity losses per prevalent case were €1510, €828 and €271, respectively. These estimates were sensitive to assumptions related to the proportion of primary care visits associated with PSA testing and the valuation method for informal care. CONCLUSION: The societal costs due to prostate cancer were substantial and constitute a considerable burden to Swedish society. Data from this study are relevant for future cost-effectiveness evaluations of prostate cancer screening and treatment.

Prevalence of BRCA1 and BRCA2 pathogenic variants in a large, unselected breast cancer cohort.

Breast cancer patients with BRCA1/2-driven tumors may benefit from targeted therapy. It is not clear whether current BRCA screening guidelines are effective at identifying these patients. The purpose of our study was to evaluate the prevalence of inherited BRCA1/2 pathogenic variants in a large, clinically representative breast cancer cohort and to estimate the proportion of BRCA1/2 carriers not detected by selectively screening individuals with the highest probability of being carriers according to current clinical guidelines. The study included 5,122 unselected Swedish breast cancer patients diagnosed from 2001 to 2008. Target sequence enrichment (48.48 Fluidigm Access Arrays) and sequencing were performed (Illumina Hi-Seq 2,500 instrument, v4 chemistry). Differences in patient and tumor characteristics of BRCA1/2 carriers who were already identified as part of clinical BRCA1/2 testing routines and additional BRCA1/2 carriers found by sequencing the entire study population were compared using logistic regression models. Ninety-two of 5,099 patients with valid variant calls were identified as BRCA1/2 carriers by screening all study participants (1.8%). Only 416 study participants (8.2%) were screened as part of clinical practice, but this identified 35 out of 92 carriers (38.0%). Clinically identified carriers were younger, less likely postmenopausal and more likely to be associated with familiar ovarian cancer compared to the additional carriers identified by screening all patients. More BRCA2 (34/42, 81.0%) than BRCA1 carriers (23/50, 46%) were missed by clinical screening. In conclusion, BRCA1/2 mutation prevalence in unselected breast cancer patients was 1.8%. Six in ten BRCA carriers were not detected by selective clinical screening of individuals.

Somatic alterations detected in diagnostic prostate biopsies provide an inadequate representation of multifocal prostate cancer.

BACKGROUND: The majority of clinical prostate cancers are multifocal with morphological and molecular heterogeneity. Adequate tissue representation is crucial for the clinical utility of multigene panel sequencing of core needle biopsies. The aim of this study was to evaluate the genomic heterogeneity in multifocal prostate cancer and to analyze how representative preoperative biopsies are of spatially separated tumor foci. METHODS: We analyzed at least 2 tumor foci and 1 to 3 preoperative biopsy cores from 11 patients. Diagnostic biopsies, as well as fresh frozen and formalin-fixed paraffin-embedded samples, from major tumor foci of radical prostatectomy specimens were macrodissected for the enrichment of tumor tissue. DNA was extracted and sequenced. We analyzed structural alterations, mutations, and copy number variations and compared the genomic profiles of tumor foci with those of preoperative biopsies. RESULTS: Alterations were rarely shared between foci, indicating a high degree of genomic heterogeneity. In 8 of 11 men at least 1 tumor focus was represented by the biopsies defined as harboring at least 1 common clonal somatic event. In only one case, somatic alterations from two spatially separate tumors were identified in the biopsies. Of the mutations and structural variants detected in fresh frozen or formalin-fixed paraffin-embedded prostatectomy material, only an average of 19% (range 0-44) and 55% (range 0-100), respectively, were found in preoperative biopsies where a common somatic origin was established. CONCLUSIONS: Multifocal prostate cancer is a somatically heterogeneous disease in which systematic needle biopsies do not provide sufficient molecular representation of the somatic alterations detected in spatially distinct tumor areas. Targeted biopsies, directed at separate tumor foci, could potentially improve tissue representation of these heterogeneous foci in preoperative biopsies.

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

Motivation: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. Results: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. Availability and implementation: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary information: Supplementary data are available at Bioinformatics online.

Summary statement on screening for prostate cancer in Europe.

The European Randomised Study of Screening for Prostate Cancer (ERSPC) showed that Prostate-Specific Antigen (PSA) based screening results in a significant prostate cancer mortality reduction. Although there are concerns on overdiagnosis and overtreatment, it has been shown that the benefits can outweigh the harms if screening is stopped in older ages to prevent overdiagnosis. A limited screening program (for example screening at ages 55-59 years), including active surveillance for men with low-risk tumors, can even be cost-saving, compared with testing in an opportunistic setting in the wrong ages, as currently in Europe. Further improvements are expected in the use of active surveillance and in discrimination between indolent and significant disease due to new biomarkers and magnetic resonance imaging. However, these future developments are no reason to postpone feasibility studies of high-quality PSA screening and reduce opportunistic testing at old ages.

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

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

Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array.

This corrects the article DOI: 10.1038/bjc.2016.50.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.

Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact: hlin1@lsuhsc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Effects of pre-notification, invitation length, questionnaire length and reminder on participation rate: a quasi-randomised controlled trial.

BACKGROUND: Improving participation rates in epidemiologic studies using questionnaires and biological sampling is important for the generalizability of the outcome. The aim of this study was to examine the effects of pre-notification, invitation length, questionnaire length, and reminder on participation rate and to investigate whether some factors contributed to participants doing both the questionnaire and blood sampling as oppose to only one part. METHODS: Our study was embedded within the pilot testing of a large population-based study about prostate cancer screening. Our study sample consisted of 28.134 men between 50 and 69 years of age and living in the region of Stockholm (Sweden) invited to respond to a web-based questionnaire and to provide blood for prostate cancer testing. The men were randomly allocated according to birth of date to receive either: (a) a pre-notification postcard or not; (b) a shorter or a longer invitation letter; (c) a shorter or a longer web-based questionnaire, and (d) a reminder or not. The effects of the survey design factors were tested using chi-square. RESULTS: The use of a pre-notification (p < 0.0001), a longer questionnaire (p = 0.004) and the use of a reminder (p = 0.02) were associated with an increase in overall participation, i.e. responding to the questionnaire or providing blood for PCT or performing both components. CONCLUSIONS: The results of this pilot study justified the use of a pre-notification and a reminder in the following large population based study since the benefits of increased participation traded off against the greater costs incurred. Furthermore, we were able to use the longer version of the questionnaire, which allowed us to collect more information without risking a lower response rate.

Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis.

Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high-grade compared to low-grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all-cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer-specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression.

Alcohol consumption and prostate cancer incidence and progression: A Mendelian randomisation study.

Prostate cancer is the most common cancer in men in developed countries, and is a target for risk reduction strategies. The effects of alcohol consumption on prostate cancer incidence and survival remain unclear, potentially due to methodological limitations of observational studies. In this study, we investigated the associations of genetic variants in alcohol-metabolising genes with prostate cancer incidence and survival. We analysed data from 23,868 men with prostate cancer and 23,051 controls from 25 studies within the international PRACTICAL Consortium. Study-specific associations of 68 single nucleotide polymorphisms (SNPs) in 8 alcohol-metabolising genes (Alcohol Dehydrogenases (ADHs) and Aldehyde Dehydrogenases (ALDHs)) with prostate cancer diagnosis and prostate cancer-specific mortality, by grade, were assessed using logistic and Cox regression models, respectively. The data across the 25 studies were meta-analysed using fixed-effect and random-effects models. We found little evidence that variants in alcohol metabolising genes were associated with prostate cancer diagnosis. Four variants in two genes exceeded the multiple testing threshold for associations with prostate cancer mortality in fixed-effect meta-analyses. SNPs within ALDH1A2 associated with prostate cancer mortality were rs1441817 (fixed effects hazard ratio, HRfixed = 0.78; 95% confidence interval (95%CI):0.66,0.91; p values = 0.002); rs12910509, HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.003); and rs8041922 (HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.002). These SNPs were in linkage disequilibrium with each other. In ALDH1B1, rs10973794 (HRfixed = 1.43; 95%CI:1.14,1.79; p values = 0.002) was associated with prostate cancer mortality in men with low-grade prostate cancer. These results suggest that alcohol consumption is unlikely to affect prostate cancer incidence, but it may influence disease progression.

Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study.

Epidemiological studies have reported inconsistent associations between telomere length (TL) and risk for various cancers. These inconsistencies are likely attributable, in part, to biases that arise due to post-diagnostic and post-treatment TL measurement. To avoid such biases, we used a Mendelian randomization approach and estimated associations between nine TL-associated SNPs and risk for five common cancer types (breast, lung, colorectal, ovarian and prostate cancer, including subtypes) using data on 51 725 cases and 62 035 controls. We then used an inverse-variance weighted average of the SNP-specific associations to estimate the association between a genetic score representing long TL and cancer risk. The long TL genetic score was significantly associated with increased risk of lung adenocarcinoma (P = 6.3 × 10(-15)), even after exclusion of a SNP residing in a known lung cancer susceptibility region (TERT-CLPTM1L) P = 6.6 × 10(-6)). Under Mendelian randomization assumptions, the association estimate [odds ratio (OR) = 2.78] is interpreted as the OR for lung adenocarcinoma corresponding to a 1000 bp increase in TL. The weighted TL SNP score was not associated with other cancer types or subtypes. Our finding that genetic determinants of long TL increase lung adenocarcinoma risk avoids issues with reverse causality and residual confounding that arise in observational studies of TL and disease risk. Under Mendelian randomization assumptions, our finding suggests that longer TL increases lung adenocarcinoma risk. However, caution regarding this causal interpretation is warranted in light of the potential issue of pleiotropy, and a more general interpretation is that SNPs influencing telomere biology are also implicated in lung adenocarcinoma risk.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.