Radiologist Preferences for Artificial Intelligence-Based Decision Support During Screening Mammography Interpretation.

BACKGROUND: Artificial intelligence (AI) may improve cancer detection and risk prediction during mammography screening, but radiologists' preferences regarding its characteristics and implementation are unknown. PURPOSE: To quantify how different attributes of AI-based cancer detection and risk prediction tools affect radiologists' intentions to use AI during screening mammography interpretation. MATERIALS AND METHODS: Through qualitative interviews with radiologists, we identified five primary attributes for AI-based breast cancer detection and four for breast cancer risk prediction. We developed a discrete choice experiment based on these attributes and invited 150 US-based radiologists to participate. Each respondent made eight choices for each tool between three alternatives: two hypothetical AI-based tools versus screening without AI. We analyzed samplewide preferences using random parameters logit models and identified subgroups with latent class models. RESULTS: Respondents (n = 66; 44% response rate) were from six diverse practice settings across eight states. Radiologists were more interested in AI for cancer detection when sensitivity and specificity were balanced (94% sensitivity with <25% of examinations marked) and AI markup appeared at the end of the hanging protocol after radiologists complete their independent review. For AI-based risk prediction, radiologists preferred AI models using both mammography images and clinical data. Overall, 46% to 60% intended to adopt any of the AI tools presented in the study; 26% to 33% approached AI enthusiastically but were deterred if the features did not align with their preferences. CONCLUSION: Although most radiologists want to use AI-based decision support, short-term uptake may be maximized by implementing tools that meet the preferences of dissuadable users.

Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment.

Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.

DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs.

Genome-wide association studies have identified more than 100 SNPs that increase the risk of prostate cancer (PrCa). We identify and compare expression quantitative trait loci (eQTLs) and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The role of DNA methylation in eQTL regulation of gene expression was investigated by data triangulation using several causal inference approaches, including a proposed adaptation of the Causal Inference Test (CIT) for causal direction. Comparing eQTLs between tumors and benign samples, we show that 98 of the 147 risk SNPs were identified as eQTLs in the tumor-adjacent benign samples, and almost all 34 eQTL identified in tumor sets were also eQTLs in the benign samples. Three lines of results support the causal role of DNA methylation. First, nearly 100 of the 147 risk SNPs were identified as meQTLs in one tumor set, and almost all eQTLs in tumors were meQTLs. Second, the loss of eQTLs in tumors relative to benign samples was associated with altered DNA methylation. Third, among risk SNPs identified as both eQTLs and meQTLs, mediation analyses suggest that over two-thirds have evidence of a causal role for DNA methylation, mostly mediating genetic influence on gene expression. In summary, we provide a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PrCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in tumor genome. Finally, our mediation analyses illuminate the likely intermediary role of CpG methylation in eQTL regulation of gene expression.

17-Gene Genomic Prostate Score Test Results in the Canary Prostate Active Surveillance Study (PASS) Cohort.

PURPOSE: The 17-gene Oncotype DX Genomic Prostate Score (GPS) test predicts adverse pathology (AP) in patients with low-risk prostate cancer treated with immediate surgery. We evaluated the GPS test as a predictor of outcomes in a multicenter active surveillance cohort. MATERIALS AND METHODS: Diagnostic biopsy tissue was obtained from men enrolled at 8 sites in the Canary Prostate Active Surveillance Study. The primary endpoint was AP (Gleason Grade Group [GG] ≥ 3, ≥ pT3a) in men who underwent radical prostatectomy (RP) after initial surveillance. Multivariable regression models for interval-censored data were used to evaluate the association between AP and GPS. Inverse probability of censoring weighting was applied to adjust for informative censoring. Predictiveness curves were used to evaluate how models stratified risk of AP. Association between GPS and time to upgrade on surveillance biopsy was evaluated using Cox proportional hazards models. RESULTS: GPS results were obtained for 432 men (median follow-up, 4.6 years); 101 underwent RP after a median 2.1 years of surveillance, and 52 had AP. A total of 167 men (39%) upgraded at a subsequent biopsy. GPS was significantly associated with AP when adjusted for diagnostic GG (hazards ratio [HR]/5 GPS units, 1.18; 95% CI, 1.04 to 1.44; P = .030), but not when also adjusted for prostate-specific antigen density (PSAD; HR, 1.85; 95% CI, 0.99 to 4.19; P = .066). Models containing PSAD and GG, or PSAD, GG, and GPS may stratify risk better than a model with GPS and GG. No association was observed between GPS and subsequent biopsy upgrade (P = .48). CONCLUSION: In our study, the independent association of GPS with AP after initial active surveillance was not statistically significant, and there was no association with upgrading in surveillance biopsy. Adding GPS to a model containing PSAD and diagnostic GG did not significantly improve stratification of risk for AP over the clinical variables alone.

Copy number alterations are associated with metastatic-lethal progression in prostate cancer.

BACKGROUNDS: Aside from Gleason score few factors accurately identify the subset of prostate cancer (PCa) patients at high risk for metastatic progression. We hypothesized that copy number alterations (CNAs), assessed using CpG methylation probes on Illumina Infinium® Human Methylation450 (HM450K) BeadChip arrays, could identify primary prostate tumors with potential to develop metastatic progression. METHODS: Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from two cohorts of PCa patients with clinically localized disease who underwent radical prostatectomy (RP) as primary therapy and were followed prospectively for at least 5 years: (1) a Fred Hutchinson (FH) Cancer Research Center-based cohort (n = 323 patients); and (2) an Eastern Virginia (EV) Medical School-based cohort (n = 78 patients). CNAs were identified using the R package ChAMP. Metastasis was confirmed by positive bone scan, MRI, CT or biopsy, and death certificates confirmed cause of death. RESULTS: We detected 15 recurrent CNAs were associated with metastasis in the FH cohort and replicated in the EV cohort (p < 0.05) without adjusting for Gleason score in the model. Eleven of the recurrent CNAs were associated with metastatic progression in the FH cohort and validated in the EV cohort (p < 0.05) when adjusting for Gleason score. CONCLUSIONS: This study shows that CNAs can be reliably detected from HM450K-based DNA methylation data. There are 11 recurrent CNAs showing association with metastatic-lethal events following RP and improving prediction over Gleason score. Genes affected by these CNAs may functionally relate to tumor aggressiveness and metastatic progression.

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.

Vigorous Physical Activity Is Associated with Lower Risk of Metastatic-Lethal Progression in Prostate Cancer and Hypomethylation in the CRACR2A Gene.

BACKGROUND: There is preliminary evidence linking physical activity to better prostate cancer outcomes, though the molecular mechanisms underlying this association are not clear. METHODS: In a Seattle-based cohort of patients diagnosed with clinically localized prostate cancer and prospective follow-up for outcomes (n = 1,354), we studied the association between self-reported vigorous physical activity and prostate cancer progression to a metastatic-lethal phenotype. A subset of patients had prostate cancer tissue samples available for investigating DNA methylation (Infinium HumanMethylation450 BeadChip array) and exercise (n = 524). RESULTS: Patients who had vigorous physical activity at least once per week during the year before diagnosis (∼79% of the cohort) were significantly less likely to progress to metastatic-lethal prostate cancer compared with those who had vigorous physical activity less frequently (adjusted hazard ratio = 0.63; P = 0.029). Among the subset of men who had radical prostatectomy as primary treatment and tumor tissue available, a differentially methylated region (DMR) was identified (family-wise error rate = 0.03, hypomethylated in the weekly exercise group), with 9 methylation probes located in the promoter region of CRACR2A. This gene encodes a calcium binding protein involved in innate immune response. The methylation level of the nine CpGs was inversely correlated with CRACR2A gene expression (average correlation coefficient = -0.35). CONCLUSIONS: Vigorous physical activity before diagnosis is associated with epigenetic alterations of CRACR2A and prostate cancer metastatic-lethal progression. IMPACT: This analysis provides strong evidence for the association between vigorous physical activity and a less likelihood to develop metastatic-lethal progression, and a suggestive link between exercise and DNA methylation in the CRACRA2A gene.

DNA methylation profiles in African American prostate cancer patients in relation to disease progression.

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q≤0.25, mean methylation difference≥0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.

A five-CpG DNA methylation score to predict metastatic-lethal outcomes in men treated with radical prostatectomy for localized prostate cancer.

BACKGROUND: Prognostic biomarkers for localized prostate cancer (PCa) could improve personalized medicine. Our group previously identified a panel of differentially methylated CpGs in primary tumor tissue that predict disease aggressiveness, and here we further validate these biomarkers. METHODS: Pyrosequencing was used to assess CpG methylation of eight biomarkers previously identified using the HumanMethylation450 array; CpGs with strongly correlated (r >0.70) results were considered technically validated. Logistic regression incorporating the validated CpGs and Gleason sum was used to define and lock a final model to stratify men with metastatic-lethal versus non-recurrent PCa in a training dataset. Coefficients from the final model were then used to construct a DNA methylation score, which was evaluated by logistic regression and Receiver Operating Characteristic (ROC) curve analyses in an independent testing dataset. RESULTS: Five CpGs were technically validated and all were retained (P < 0.05) in the final model. The 5-CpG and Gleason sum coefficients were used to calculate a methylation score, which was higher in men with metastatic-lethal progression (P = 6.8 × 10-6 ) in the testing dataset. For each unit increase in the score there was a four-fold increase in risk of metastatic-lethal events (odds ratio, OR = 4.0, 95%CI = 1.8-14.3). At 95% specificity, sensitivity was 74% for the score compared to 53% for Gleason sum alone. The score demonstrated better prediction performance (AUC = 0.91; pAUC = 0.037) compared to Gleason sum alone (AUC = 0.87; pAUC = 0.025). CONCLUSIONS: The DNA methylation score improved upon Gleason sum for predicting metastatic-lethal progression and holds promise for risk stratification of men with aggressive tumors. This prognostic score warrants further evaluation as a tool for improving patient outcomes.

Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort.

Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide. Gleason score (GS) is one of the best predictors of PCa aggressiveness, but additional tumor biomarkers may improve its prognostic accuracy. We developed a gene expression signature of GS to enhance the prediction of PCa outcomes. Elastic net was used to construct a gene expression signature by contrasting GS 8-10 vs. ≤6 tumors in The Cancer Genome Atlas (TCGA) dataset. The constructed signature was then evaluated for its ability to predict recurrence and metastatic-lethal (ML) progression in a Fred Hutchinson (FH) patient cohort (N=408; NRecurrence=109; NMLprogression=27). The expression signature included transcripts representing 49 genes. In the FH cohort, a 25% increase in the signature was associated with a hazard ratio (HR) of 1.51 (P=2.7×10-5) for recurrence. The signature's area under the curve (AUC) for predicting recurrence and ML progression was 0.68 and 0.76, respectively. Compared to a model with age at diagnosis, pathological stage and GS, the gene expression signature improved the AUC for recurrence (3%) and ML progression (6%). Higher levels of the signature were associated with increased expression of genes in cell cycle-related pathways and decreased expression of genes in androgen response, estrogen response, oxidative phosphorylation, and apoptosis. This gene expression signature based on GS may improve the prediction of recurrence as well as ML progression in PCa patients after radical prostatectomy.

Gene expression panel predicts metastatic-lethal prostate cancer outcomes in men diagnosed with clinically localized prostate cancer.

Prognostic biomarkers are needed to distinguish patients with clinically localized prostate cancer (PCa) who are at high risk of metastatic progression. The tumor transcriptome may reveal its aggressiveness potential and have utility for predicting adverse patient outcomes. Genomewide gene expression levels were measured in primary tumor samples of 383 patients in a population-based discovery cohort, and from an independent clinical validation dataset of 78 patients. Patients were followed for ≥ 5 years after radical prostatectomy to ascertain outcomes. Area under the receiver-operating characteristic curve (AUC), partial AUC (pAUC, 95% specificity), and P-value criteria were used to detect and validate the differentially expressed transcripts. Twenty-three differentially expressed transcripts in patients with metastatic-lethal compared with nonrecurrent PCa were validated (P < 0.05; false discovery rate < 0.20) in the independent dataset. The addition of each validated transcript to a model with Gleason score showed that 17 transcripts significantly improved the AUC (range: 0.83-0.88; all P-values < 0.05). These differentially expressed mRNAs represent genes with diverse cellular functions related to tumor aggressiveness. This study validated 23 gene transcripts for predicting metastatic-lethal PCa in patients surgically treated for clinically localized disease. Several of these mRNA biomarkers have clinical potential for identifying the subset of PCa patients with more aggressive tumors who would benefit from closer monitoring and adjuvant therapy.

Epigenome-Wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-Lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer.

PURPOSE: Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential. EXPERIMENTAL DESIGN: Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum. RESULTS: Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P < 0.05) AUC (range, 0.66-0.75) or pAUC (range, 0.007-0.009). The biomarkers that improved discrimination of patients with metastatic-lethal prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P <0.05). CONCLUSIONS: Eight differentially methylated CpGs that distinguish patients with metastatic-lethal from nonrecurrent tumors were validated. These novel epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR.

Whole exome sequencing in 75 high-risk families with validation and replication in independent case-control studies identifies TANGO2, OR5H14, and CHAD as new prostate cancer susceptibility genes.

Prostate cancer (PCa) susceptibility is defined by a continuum from rare, high-penetrance to common, low-penetrance alleles. Research to date has concentrated on identification of variants at the ends of that continuum. Taking an alternate approach, we focused on the important but elusive class of low-frequency, moderately penetrant variants by performing disease model-based variant filtering of whole exome sequence data from 75 hereditary PCa families. Analysis of 341 candidate risk variants identified nine variants significantly associated with increased PCa risk in a population-based, case-control study of 2,495 men. In an independent nested case-control study of 7,121 men, there was risk association evidence for TANGO2 p.Ser17Ter and the established HOXB13 p.Gly84Glu variant. Meta-analysis combining the case-control studies identified two additional variants suggestively associated with risk, OR5H14 p.Met59Val and CHAD p.Ala342Asp. The TANGO2 and HOXB13 variants co-occurred in cases more often than expected by chance and never in controls. Finally, TANGO2 p.Ser17Ter was associated with aggressive disease in both case-control studies separately. Our analyses identified three new PCa susceptibility alleles in the TANGO2, OR5H14 and CHAD genes that not only segregate in multiple high-risk families but are also of importance in altering disease risk for men from the general population. This is the first successful study to utilize sequencing in high-risk families for the express purpose of identifying low-frequency, moderately penetrant PCa risk mutations.

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci.

BACKGROUND: Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. METHODS: We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. RESULTS: We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10-7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. IMPACT: A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor ß2 immunohistochemistry in prostate cancer.

BACKGROUND: Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-ß2 (ERß2). METHODS: Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERß2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. RESULTS: We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERß2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERß2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). CONCLUSIONS: Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

Prostate tumor DNA methylation is associated with cigarette smoking and adverse prostate cancer outcomes.

BACKGROUND: DNA methylation has been hypothesized as a mechanism for explaining the association between smoking and adverse prostate cancer (PCa) outcomes. This study was aimed at assessing whether smoking is associated with prostate tumor DNA methylation and whether these alterations may explain in part the association of smoking with PCa recurrence and mortality. METHODS: A total of 523 men had radical prostatectomy as their primary treatment, detailed smoking history data, long-term follow-up for PCa outcomes, and tumor tissue profiled for DNA methylation. Ninety percent of the men also had matched tumor gene expression data. A methylome-wide analysis was conducted to identify differentially methylated regions (DMRs) by smoking status. To select potential functionally relevant DMRs, their correlation with the messenger RNA (mRNA) expression of corresponding genes was evaluated. Finally, a smoking-related methylation score based on the top-ranked DMRs was created to assess its association with PCa outcomes. RESULTS: Forty DMRs were associated with smoking status, and 10 of these were strongly correlated with mRNA expression (aldehyde oxidase 1 [AOX1], claudin 5 [CLDN5], early B-cell factor 1 [EBF1], homeobox A7 [HOXA7], lectin galactoside-binding soluble 3 [LGALS3], microtubule-associated protein τ [MAPT], protocadherin γ A [PCDHGA]/protocadherin γ B [PCDHGB], paraoxonase 3 [PON3], synaptonemal complex protein 2 like [SYCP2L], and zinc finger and SCAN domain containing 12 [ZSCAN12]). Men who were in the highest tertile for the smoking-methylation score derived from these DMRs had a higher risk of recurrence (odds ratio [OR], 2.29; 95% confidence interval [CI], 1.42-3.72) and lethal disease (OR, 4.21; 95% CI, 1.65-11.78) in comparison with men in the lower 2 tertiles. CONCLUSIONS: This integrative molecular epidemiology study supports the hypothesis that smoking-associated tumor DNA methylation changes may explain at least part of the association between smoking and adverse PCa outcomes. Future studies are warranted to confirm these findings and understand the implications for improving patient outcomes. Cancer 2016;122:2168-77. © 2016 American Cancer Society.

Prostate Cancer Susceptibility in Men of African Ancestry at 8q24.

The 8q24 region harbors multiple risk variants for distinct cancers, including >8 for prostate cancer. In this study, we conducted fine mapping of the 8q24 risk region (127.8-128.8Mb) in search of novel associations with common and rare variation in 4853 prostate cancer case patients and 4678 control subjects of African ancestry. All statistical tests were two-sided. We identified three independent associations at P values of less than 5.00×10(-8), all of which were replicated in studies from Ghana and Uganda (combined sample = 5869 case patients, 5615 control subjects; rs114798100: risk allele frequency [RAF] = 0.04, per-allele odds ratio [OR] = 2.31, 95% confidence interval [CI] = 2.04 to 2.61, P = 2.38×10(-40); rs72725879: RAF = 0.33, OR = 1.37, 95% CI = 1.30 to 1.45, P = 3.04×10(-27); and rs111906932: RAF = 0.03, OR = 1.79, 95% CI = 1.53 to 2.08, P = 1.39×10(-13)). Risk variants rs114798100 and rs111906923 are only found in men of African ancestry, with rs111906923 representing a novel association signal. The three variants are located within or near a number of prostate cancer-associated long noncoding RNAs (lncRNAs), including PRNCR1, PCAT1, and PCAT2. These findings highlight ancestry-specific risk variation and implicate prostate-specific lncRNAs at the 8q24 prostate cancer susceptibility region.

Trichomonas vaginalis infection and risk of advanced prostate cancer.

BACKGROUND: The epidemiologic evidence for an association of Trichomonas vaginalis (Tv) with overall prostate cancer is mixed, but some studies suggest Tv may increase risk of more aggressive disease. The aim of this study was to assess whether Tv serostatus is associated with advanced or fatal prostate cancer. METHODS: A total of 146 men with advanced (metastatic or fatal) prostate cancer and 181 age-matched controls were selected from two prior population-based, case-control studies. Tv serostatus was determined with the same laboratory methods used in previous epidemiologic studies. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using multivariable logistic regression to compare Tv serostatus in prostate cancer cases and controls adjusted for potential confounders. RESULTS: The seroprevalence of Tv in controls was 23%. Tv serostatus was not associated with an increased risk of metastatic or fatal prostate cancer (ORs < 1). CONCLUSIONS: Our study does not support an increased risk of advanced or fatal prostate cancer in men seropositive for Tv.

Prostate Cancer Expression Profiles of Cytoplasmic ERß1 and Nuclear ERß2 are Associated with Poor Outcomes following Radical Prostatectomy.

PURPOSE: Existing data regarding the expression of estrogen receptors (ERs) and prostate cancer outcomes have been limited. We evaluated the relationship of expression profiles of ERß subtypes and the ER GPR30 (G-protein-coupled receptor-30) with patient factors at diagnosis and outcomes following radical prostatectomy. MATERIALS AND METHODS: Tissue microarrays constructed using samples from 566 men with long-term clinical followup were analyzed by immunohistochemistry targeting ERß1, ERß2, ERß5 and GPR30. An experienced pathologist scored receptor distribution and staining intensity. Tumor staining characteristics were evaluated for associations with patient characteristics, recurrence-free survival and prostate cancer specific mortality following radical prostatectomy. RESULTS: Prostate cancer cells had unique receptor subtype staining patterns. ERß1 demonstrated predominantly nuclear localization while ERß2, ERß5 and GPR30 were predominantly cytoplasmic. After controlling for patient factors intense cytoplasmic ERß1 staining was independently associated with time to recurrence (HR 1.7, 95% CI 1.1-2.6, p = 0.01) and prostate cancer specific mortality (HR 6.6, 95% CI 1.8-24.9, p = 0.01). Intense nuclear ERß2 staining was similarly independently associated with prostate cancer specific mortality (HR 3.9, 95% CI 1.1-13.4, p = 0.03). Patients with cytoplasmic ERß1 and nuclear ERß2 co-staining had significantly worse 15-year prostate cancer specific mortality than patients with expression of only cytoplasmic ERß1, only nuclear ERß2 and neither ER (16.4%, 4.3%, 0.0% and 2.0 %, respectively, p = 0.001). CONCLUSIONS: Increased cytoplasmic ERß1 and nuclear ERß2 expression is associated with worse cancer specific outcomes following radical prostatectomy. These findings suggest that tumor ERß1 and ERß2 staining patterns provide prognostic information on patients treated with radical prostatectomy.

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.