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Prostate cancer has a heterogeneous prognosis. Most previous studies have focused on the identification of prognostic biomarkers in the prostate cancer tumor. However, it is increasingly recognized that the tumor microenvironment contributes to prostate cancer aggressiveness and progression. We therefore examined whole transcriptome expression of the prostate stroma and associations with aggressive and lethal prostate cancer. We performed RNA sequencing (Illumina TruSeq Exome Capture) of 272 tumor-adjacent and 120 benign-adjacent macrodissected prostate stromal samples from 293 men with prostate cancer from the Health Professionals Follow-up Study and Physicians’ Health Study. We performed differential expression analysis comparing gene expression and pathways by Gleason score and lethal outcome. We also tested a previously developed stromal gene signature of Gleason score in these datasets. Comparing high- with low-Gleason score cancers, 26 genes (P < 0.001) and 12 pathways (FDR < 0.20) were significantly differentially expressed in tumor-adjacent stroma, including pathways related to stroma composition remodeling and DNA repair, with 73 genes and 65 pathways significant in benign-adjacent stroma. Comparing lethal with nonlethal prostate cancer, 11 genes were differentially expressed in tumor-adjacent and 15 genes in benign-adjacent stroma, and pathways involved in inflammatory response were differentially enriched in both tumor and benign-adjacent stroma. In addition, our previously identified Gleason stromal gene signature was validated to be associated with Gleason score in these data.Implications: Our study uncovers stroma-specific genes and pathways that are differentially enriched with high Gleason score and lethal prostate cancer, demonstrating that the molecular investigation of the tumor microenvironment can provide additional information about prostate cancer prognosis.

The most common somatic event in primary prostate cancer is a fusion between the androgen-related TMPRSS2 gene and the ERG oncogene. Tumors with these fusions, which occur early in carcinogenesis, have a distinctive etiology. A smaller subset of other tumors harbor fusions between TMPRSS2 and members of the ETS transcription factor family other than ERG. To assess the genomic similarity of tumors with non-ERG ETS fusions and those with fusions involving ERG, this study derived a transcriptomic signature of non-ERG ETS fusions and assessed this signature and ERG-related gene expression in 1,050 men with primary prostate cancer from three independent population-based and hospital-based studies. Although non-ERG ETS fusions involving ETV1, ETV4, ETV5, or FLI1 were individually rare, they jointly accounted for one in seven prostate tumors. Genes differentially regulated between non-ERG ETS tumors and tumors without ETS fusions showed similar differential expression when ERG tumors and tumors without ETS fusions were compared (differences explained: R2 = 69–77%), including ETS-related androgen receptor (AR) target genes. Differences appeared to result from similarities among ETS tumors rather than similarities among non-ETS tumors. Gene sets associated with ERG fusions were consistent with gene sets associated with non-ERG ETS fusions, including fatty acid and amino acid metabolism, an observation that was robust across cohorts. Implications: Considering ETS fusions jointly may be useful for etiologic studies on prostate cancer, given that the transcriptome is profoundly impacted by ERG and non-ERG ETS fusions in a largely similar fashion, most notably genes regulating metabolic pathways.

Adverse neighborhood social and natural (greenspace) environments may contribute to prostate cancer (CaP) etiology, but mechanisms are unclear. We examined associations between neighborhood environment and prostate intratumoral inflammation in 967 men diagnosed with CaP with available tissue from 1986-2009 in the Health Professionals Follow-up Study. Exposures were linked to work or residential addresses in 1988. We estimated indices of neighborhood socioeconomic status (nSES) and segregation (Index of Concentration at Extremes (ICE)) using Census tract-level data. Surrounding greenness was estimated using seasonal averaged Normalized Difference Vegetation Index (NDVI). Surgical tissue underwent pathological review for acute and chronic inflammation, corpora amylacea, and focal atrophic lesions. Adjusted odds ratios (aOR) for inflammation (ordinal) and focal atrophy (binary) were estimated using logistic regression. No associations were observed for acute or chronic inflammation. Each IQR increase in NDVI within 1230m (aOR: 0.74, 95% CI: 0.59, 0.93), ICE-income (aOR: 0.79, 95% CI: 0.61, 1.04) and ICE-race/income (aOR: 0.79, 95% CI: 0.63, 0.99) was associated with lower postatrophic hyperplasia. IQR increases in nSES (aOR: 0.76, 95% CI: 0.57, 1.02) and ICE-race/income (aOR: 0.73, 95% CI: 0.54, 0.99) were associated with lower tumor corpora amylacea. Histopathological inflammatory features of prostate tumors may be influenced by neighborhood

Metabolite profiling has significantly contributed to a deeper understanding of the biochemical metabolic networks and pathways in cancer cells. Metabolomics-based biomarker discovery would greatly benefit from the ability to interrogate retrospective annotated clinical specimens archived as formalin-fixed, paraffin-embedded (FFPE) material. Mass spectrometry–based metabolomic analysis was performed in matched frozen and FFPE human prostate cancers as well as isogenic prostate cancer cell lines. A total of 352 and 460 metabolites were profiled in human tissues and cell lines, respectively. Classes and physical–chemical characteristics of the metabolites preserved in FFPE material were characterized and related to their preservation or loss following fixation and embedding. Metabolite classes were differentially preserved in archival FFPE tissues, regardless of the age of the block, compared with matched frozen specimen, ranging from maximal preservation of fatty acids (78%) to loss of the majority of peptides and steroids. Generally, FFPE samples showed a decrease of metabolites with functional groups, such as carboxamide. As an adjunct technique, metabolic profiles were also obtained in situ from FFPE tissue sections where metabolites were extracted in a manner that preserves tissue architecture. Despite the fact that selected metabolites were not retained after processing, global metabolic profiles obtained from FFPE can be used to predict biologic states and study biologic pathways. These results pave the way for metabolomics-based biomarker discovery/validation utilizing retrospective and clinically annotated FFPE collections.Implications: Metabolic profiles can be performed in archival tissue and may be used to complement other profiling methods such as gene expression for biomarker discovery or pathway analysis in the assessment of biologic states. Mol Cancer Res; 15(4); 439–47. ©2017 AACR.

Metabolite score values of reliability.

Supplemental figure 1: Examples of cribriform and noncribriform carcinoma; Supplemental figure 2: Scheme of Sample Selection; Supplemental figure 3: Examples of PTEN Immunostaining of Tissue Microarray (TMA) Cores, HPFS/ PHS Prostate Cancer Cohorts; Supplementary figure 4: Invasive Cribriform Carcinoma is Associated with High Gleason Score and Tumor Stage (TCGA datasets); Supplementary figure 5. Difference in FGA between Cribriform Carcinoma (ICC) and Noncribriform Carcinoma (NC4) as well as between Gleason scores (in TCGA dataset); Supplementary figure 6: Cribriform Morphology in PTENloss and SPOPmut Transgenic Mouse Prostate Model.

Difference in FGA between Cribriform Carcinoma (ICC) and Noncribriform Carcinoma (NC4) as well as between Gleason scores.

Function and aberration of differentially methylated genes between Cribriform and noncribriform.

Perspective on this Article from A Large Prospective Study of SEP15 Genetic Variation, Interaction with Plasma Selenium Levels, and Prostate Cancer Risk and Survival

Supplementary Figure 3. Scatterplots for metabolites with high correlations between their abundances in tissue and serum.

Supplementary Table S1. Descriptive factors for KP study population, broken down by study. Supplementary Table S2. Genome-wide significant SNPs found in our cohort. Supplementary Table S3. Cis-eQTL expression of rs4646284. Supplementary Table S4. Results at the 105 loci previously found to be associated with prostate cancer. Supplementary Table S5. Risk score of and variance explained by the 105 previously reported hits. Supplementary Figure S1. Manhattan and Q-Q plots of each race/ethnicity and meta-analysis. Supplementary Figure S2. Local plots of novel replicated rs4646284 and suggestive rs2659124. Supplementary Figure S3. Cis-eQTL of SLC22A1 and SLC22A3. Supplementary Figure S4. Comparison of ORs of KP to previous reports by race/ethnicity. Supplementary Figure S5. KP AUC estimates.

Full results of 10-fold cross-validation performance assessment for all ML models and prediction tasks (mean +/- SD).

Supplemental material

Table S1: IDs of Cribriform (ICC) & Non-cribriform (NC4) TCGA cases; Table S2: Comparison between cribriform and non-cribriform based on TCGA clusters; Table S3: Somatic Copy Number Variation (SCNV) enriched in Cribriform Carcinoma (ICC) compared to Noncribriform (NC4), corrected for Fraction Genome Altered (FGA) and Gleason Score (GS).

Among prostate cancers containing Gleason pattern 4, cribriform morphology is associated with unfavorable clinicopathologic factors, but its genetic features and association with long-term outcomes are incompletely understood. In this study, genetic, transcriptional, and epigenetic features of invasive cribriform carcinoma (ICC) tumors were compared with non-cribriform Gleason 4 (NC4) in The Cancer Genome Atlas (TCGA) cohort. ICC (n = 164) had distinctive molecular features when compared with NC4 (n = 102). These include: (i) increased somatic copy number variations (SCNV), specifically deletions at 6q, 8p and 10q, which encompassed PTEN and MAP3K7 losses and gains at 3q; (ii) increased SPOPmut and ATMmut; (iii) enrichment for mTORC1 and MYC pathways by gene expression; and (iv) increased methylation of selected genes. In addition, when compared with the metastatic prostate cancer, ICC clustered more closely to metastatic prostate cancer than NC4. Validation in clinical cohorts and genomically annotated murine models confirmed the association with SPOPmut (n = 38) and PTENloss (n = 818). The association of ICC with lethal disease was evaluated in the Health Professionals Follow-up Study (HPFS) and Physicians' Health Study (PHS) prospective prostate cancer cohorts (median follow-up, 13.4 years; n = 818). Patients with ICC were more likely to develop lethal cancer [HR, 1.62; 95% confidence interval (CI), 1.05–2.49], independent from Gleason score (GS).Implications:ICC has a distinct molecular phenotype that resembles metastatic prostate cancer and is associated with progression to lethal disease.

Supplementary materials, Supplementary Tables 1-12, Supplementary Figures 1-2

Table S9: Differentially methylated CpG islands in invasive cribriform vs Noncribriform; Table S10: mRNA expression of the differentially hypermethylated in cribriform with concomitant reduction of mRNA expression.

Supplementary figure legends Supplementary table 2

Supplementary Figure 4. Heatmap of the top twenty metabolites as identified by permutation feature importance analysis of AutoML model.

Supplementary Table 1. Differentially expressed genes between tumor- and benign-adjacent stroma Supplementary Table 2. Differentially enriched pathways between tumor- and benign-adjacent stroma Supplementary Table 3. Differentially expressed genes between high- and low-Gleason score in tumor-adjacent stroma Supplementary Table 4. Differentially expressed genes between high- and low-Gleason score in benign-adjacent stroma Supplementary Table 5. Differentially enriched pathways between high- and low-Gleason score in tumor-adjacent stroma Supplementary Table 6. Differentially enriched pathways between high- and low-Gleason score in benign-adjacent stroma Supplementary Table 7. Differentially expressed genes between cribriform and non-cribriform patterns Supplementary Table 8. Differentially enriched pathways between cribriform and non-cribriform patterns Supplementary Table 9. Differentially expressed genes between lethal and non-lethal cases in tumor-adjacent stroma Supplementary Table 10. Differentially expressed genes between lethal and non-lethal cases in benign-adjacent stroma Supplementary Table 11. Differentially enriched pathways between lethal and non-lethal cases in tumor-adjacent stroma Supplementary Table 12. Differentially enriched pathways between lethal and non-lethal cases in benign-adjacent stroma Supplementary Figure 1. Single sample gene set enrichment signature scores by Gleason score and lethal outcome in tumor-adjacent stromal samples. Supplementary Figure 2. Correlation of log2 fold change values between the current data and the LCM data (GSE97284)

Supplementary Figure 2. Heatmap of top differential (unadjusted p

Supplemental Figure 1. Fresh radical prostatectomy specimens were inked and transverse sliced from apex to base.

Supplementary Data from Family History of Prostate and Breast Cancer Integrated with a Polygenic Risk Score Identifies Men at Highest Risk of Dying from Prostate Cancer before Age 75 Years

Purpose:Family history of prostate cancer is one of the few universally accepted risk factors for prostate cancer. How much an assessment of inherited polygenic risk for prostate cancer adds to lifetime risk stratification beyond family history is unknown.Experimental Design:We followed 10,120 men in the Health Professionals Follow-up Study with existing genotype data for risk of prostate cancer and prostate cancer–specific death. We assessed to what extent family history of prostate or breast cancer, combined with a validated polygenic risk score (PRS) including 269 prostate cancer risk variants, identifies men at risk of prostate cancer and prostate cancer death across the age span.Results:During 20 years of follow-up, 1,915 prostate cancer and 166 fatal prostate cancer events were observed. Men in the top PRS quartile with a family history of prostate or breast cancer had the highest rate of both prostate cancer and prostate cancer–specific death. Compared with men at lowest genetic risk (bottom PRS quartile and no family history), the HR was 6.95 [95% confidence interval (CI), 5.57–8.66] for prostate cancer and 4.84 (95% CI, 2.59–9.03) for prostate cancer death. Men in the two upper PRS quartiles (50%–100%) or with a family history of prostate or breast cancer (61.8% of the population) accounted for 97.5% of prostate cancer deaths by age 75 years.Conclusions:Our study shows that prostate cancer risk stratification on the basis of family history and inherited polygenic risk can identify men at highest risk of dying from prostate cancer before age 75 years.

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Frequency of risk SNP genotypes in the ERG+ cases, ERG- cases, and controls

Supplemental Table 1: Minor allele frequencies and Hardy Weinberg Equilibrium (HWE) p-values for SNPs across antioxidant & transport related genes. Supplemental Table 2: Full results for the associations between antioxidant SNPs x selenium supplementation. Supplemental Table 3: Full results for the associations between antioxidant, transport, & DNA repair SNPs x vitamin E supplementation and risk of high-grade and overall prostate cancer (N=1,538) in SELECT. Supplemental Table 4: Full results for the independent associations of SNPs and risk high-grade and overall prostate cancer in the placebo arm of SELECT.

Purpose: Variants at chromosomal loci 8q24 and 17q are established risk factors for prostate cancer. Many studies have confirmed the findings for risk, but few have examined aggressiveness and other clinical variables in detail. Additionally, Gleason score is typically used as a surrogate for the primary end point of prostate cancer mortality. We investigated whether the 8q24 and 17q risk variants are associated with clinical variables as well as prostate cancer mortality.Experimental Design: In the Physicians' Health Study (1,347 cases and 1,462 controls), the Dana-Farber Harvard Cancer Center Specialized Program of Research Excellence (Gelb Center; 3,714 cases), and the Fred Hutchinson Cancer Research Center King County Case-Control Studies (1,308 cases and 1,266 controls), we examined eight previously identified 8q24 and 17q risk variants for association with prostate cancer mortality in men of European ancestry. We considered associations with other surrogate markers of prostate cancer aggressiveness, such as Gleason score, pathologic stage, prostate-specific antigen at diagnosis, and age at diagnosis.Results: Six of the eight variants were confirmed as prostate cancer risk factors. Several variants were nominally associated with age at diagnosis; when totaling all alleles for single nucleotide polymorphisms significantly associated with risk, each additional allele decreased age at diagnosis by an average of 6 months in the Physicians' Health Study (P = 0.0005) and 4 months in the Dana-Farber Harvard Cancer Center Specialized Program of Research Excellence (Gelb Center) cohort (P = 0.0016). However, there were no statistically significant associations with prostate cancer mortality.Conclusions: Our results suggest that the 8q24 and 17q prostate cancer risk variants may influence age at diagnosis but not disease aggressiveness.

Cholesterol metabolism has been implicated in prostate cancer pathogenesis. Here, we assessed the association of intratumoral mRNA expression of cholesterol synthesis enzymes, transporters, and regulators in tumor specimen at diagnosis and lethal prostate cancer, defined as mortality or metastases from prostate cancer in contrast to nonlethal disease without evidence of metastases after at least 8 years of follow-up. We analyzed the prospective prostate cancer cohorts within the Health Professionals Follow-up Study (n = 249) and the Physicians' Health Study (n = 153) as well as expectantly managed patients in the Swedish Watchful Waiting Study (n = 338). The expression of squalene monooxygenase (SQLE) was associated with lethal cancer in all three cohorts. Men with high SQLE expression (>1 standard deviation above the mean) were 8.3 times (95% confidence interval, 3.5 to 19.7) more likely to have lethal cancer despite therapy compared with men with the mean level of SQLE expression. Absolute SQLE expression was associated with lethal cancer independently from Gleason grade and stage, as was a SQLE expression ratio in tumor versus surrounding benign prostate tissue. Higher SQLE expression was tightly associated with increased histologic markers of angiogenesis. Collectively, this study establishes the prognostic value of intratumoral cholesterol synthesis as measured via SQLE, its second rate-limiting enzyme. SQLE expression at cancer diagnosis is prognostic for lethal prostate cancer both after curative-intent prostatectomy and in a watchful waiting setting, possibly by facilitating micrometastatic disease. Cancer Res; 76(16); 4785–90. ©2016 AACR.

Background: A pressing clinical issue in prostate cancer is to distinguish which men will have an indolent or aggressive course of disease. Clinical variables such as Gleason grade and stage are useful predictors of lethal cancer; however, the low predictive values of the common Gleason scores, changes in grading over time, and earlier diagnosis of patients due to screening limits their clinical utility. Identifying genetic variants associated with lethal prostate cancer could inform clinical decision making.Methods: We conducted a genome-wide association study, comparing lethal prostate cancer cases to cases surviving at least 10 years beyond their initial diagnosis. Genotyping was done with the Affymetrix 5.0 chip [∼500,000 single nucleotide polymorphisms (SNP) and 1,483 copy number variants (CNV)] on DNA from participants in the Physicians' Health Study and Health Professionals Follow-up Study (196 lethal cases, 368 long-term survivors). After excluding SNPs and individuals based on quality control criteria, logistic regression assuming an additive model was done using the PLINK software.Results: No SNP reached genome-wide significance (P ≤ 1 × 10−7); however, three independent SNPs had P < 1 × 10−5. One top-ranked SNP replicated (P = 0.05) in an independent follow-up study. Although no CNV had genome-wide significance, 14 CNVs showed nominal association with prostate cancer mortality (P < 0.05).Conclusions: No variants were significantly associated at a genome-wide level with prostate cancer mortality. Common genetic determinants of lethal prostate cancer are likely to have odds ratios Impact: Genetic markers identified could provide biological insight to improve therapy for men with potentially fatal cancer. Larger studies are necessary to detect the genetic causes of prostate cancer mortality. Cancer Epidemiol Biomarkers Prev; 19(11); 2869–76. ©2010 AACR.

Supplementary Tables and Figures from Genome-wide Association Study of Prostate Cancer Mortality

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Purpose: Gleason score strongly predicts prostate cancer mortality; however, scoring varies among pathologists, and many men are diagnosed with intermediate-risk Gleason score 7. We previously developed a 157-gene signature for Gleason score using a limited gene panel. Using a new whole-transcriptome expression dataset, we verified the previous signature's performance and developed a new Gleason signature to improve lethal outcome prediction among men with Gleason score 7.Experimental Design: We generated mRNA expression data from prostate tumor tissue from men in the Physicians' Health Study and Health Professionals Follow-Up Study (N = 404) using the Affymetrix Human Gene 1.0 ST microarray. The Prediction Analysis for Microarrays method was used to develop a signature to distinguish high (≥8) versus low (≤6) Gleason score. We evaluated the signature's ability to improve prediction of lethality among men with Gleason score 7, adjusting for 3 + 4/4 + 3 status, by quantifying the area under the receiver operating characteristic (ROC) curve (AUC).Results: We identified a 30-gene signature that best distinguished Gleason score ≤6 from ≥8. The AUC to predict lethal disease among Gleason score 7 men was 0.76 [95% confidence interval (CI), 0.67–0.84] compared with 0.68 (95% CI, 0.59–0.76) using 3 + 4/4 + 3 status alone (P = 0.0001). This signature was a nonsignificant (P = 0.09) improvement over our previous signature (AUC = 0.72).Conclusions: Our new 30-gene signature improved prediction of lethality among men with Gleason score 7. This signature can potentially become a useful prognostic tool for physicians to improve treatment decision making. Clin Cancer Res; 23(1); 81–87. ©2016 AACR.See related commentary by Yin et al., p. 6

Background: Numerous genetic variants have been confirmed as prostate cancer risk factors. These variants may confer susceptibility to the development of specific molecular alterations during tumor initiation and progression. The TMPRSS2:ERG gene fusion occurs in roughly 50% of prostate cancers. Genetic risk variants may influence the development of this fusion. We sought to determine whether prostate cancer risk variants are differentially associated with TMPRSS2:ERG fusion–positive and negative cancer.Methods: In the Health Professionals Follow-up Study and Physicians' Health Study Tumor Cohort, we evaluated the associations of 39 prostate cancer risk SNPs with TMPRSS2:ERG fusion status, measured by ERG protein expression. Logistic regression was performed to generate OR and 95% confidence intervals. The primary outcome was ERG+ (n = 227) versus ERG− (n = 260) prostate cancer. A secondary outcome was ERG+ or ERG− cancer versus controls without cancer.Results: Six of 39 SNPs were significantly associated (P < 0.05) with ERG+ versus ERG− disease. Three SNPs were exclusively associated with the risk of ERG+, one with risk of ERG−, and two with associations trending in opposite directions for ERG+ and ERG−. Only two significant SNPs would be expected by chance.Conclusions: Prostate cancer genetic risk variants are differentially associated with the development of ERG+ and ERG− prostate cancer.Impact: Our findings suggest the molecular process of prostate carcinogenesis may be distinct for men with different underlying genetic predisposition. When examining risk factors for prostate cancer, the integration of molecular subtypes may enhance understanding of the etiology of this disease. Cancer Epidemiol Biomarkers Prev; 25(5); 745–9. ©2016 AACR.

Supplementary Table 1. Comparison of signature gene expression in normal, Gleason score {less than or equal to}6, and Gleason score {greater than or equal to}8 using t-tests with p-values calculated using the bootstrap to account for the matching between some tumor and normal samples.