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In a prospective study of 31 925 men with 18 yr of follow-up, higher ejaculation frequency (EF) throughout adulthood was associated with lower rates of prostate cancer. To further explore this association, we evaluated whole transcriptome gene expression in the prostate tissue from study participants who developed prostate cancer between 1992 and 2004 (n=157 tumor tissue, n=85 adjacent normal). We tested for trends in gene expression according to the level of EF as self-reported in 1992 for ages 20-29 yr, 40-49 yr, and the year prior to the questionnaire, 1991. There were no associations between EF and gene expression in areas of tumor after accounting for multiple testing. In contrast, in the adjacent normal tissue, 409 genes and six pathways were differentially expressed at a false discovery rate ≤0.2 across categories of EF in 1991. These results suggest that ejaculation affects the expression of genes in the normal prostate tissue. The identified genes and pathways provide potential biological links between EF and prostate tumorigenesis., Patient Summary: To explore previous findings that men who ejaculate more frequently have lower risk of prostate cancer, we evaluated molecular alterations in the prostate tissue according to each man's frequency of ejaculation prior to diagnosis. We identified biological processes that could link ejaculation frequency and prostate cancer., (Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Background: Obese men are at higher risk of advanced prostate cancer and cancer-specific mortality; however, the biology underlying this association remains unclear. This study examined gene expression profiles of prostate tissue to identify biological processes differentially expressed by obesity status and lethal prostate cancer., Methods: Gene expression profiling was performed on tumor (n = 402) and adjacent normal (n = 200) prostate tissue from participants in 2 prospective cohorts who had been diagnosed with prostate cancer from 1982 to 2005. Body mass index (BMI) was calculated from the questionnaire immediately preceding cancer diagnosis. Men were followed for metastases or prostate cancer-specific death (lethal disease) through 2011. Gene Ontology biological processes differentially expressed by BMI were identified using gene set enrichment analysis. Pathway scores were computed by averaging the signal intensities of member genes. Odds ratios (ORs) for lethal prostate cancer were estimated with logistic regression., Results: Among 402 men, 48% were healthy weight, 31% were overweight, and 21% were very overweight/obese. Fifteen gene sets were enriched in tumor tissue, but not normal tissue, of very overweight/obese men versus healthy-weight men; 5 of these were related to chromatin modification and remodeling (false-discovery rate < 0.25). Patients with high tumor expression of chromatin-related genes had worse clinical characteristics (Gleason grade > 7, 41% vs 17%; P = 2 × 10 -4 ) and an increased risk of lethal disease that was independent of grade and stage (OR, 5.26; 95% confidence interval, 2.37-12.25)., Conclusions: This study improves our understanding of the biology of aggressive prostate cancer and identifies a potential mechanistic link between obesity and prostate cancer death that warrants further study. Cancer 2017;123:4130-4138. © 2017 American Cancer Society., (© 2017 American Cancer Society.)

Background: Numerous germline genetic variants are associated with prostate cancer risk, but their biologic role is not well understood. One possibility is that these variants influence gene expression in prostate tissue. We therefore examined the association of prostate cancer risk variants with the expression of genes nearby and genome-wide., Methods: We generated mRNA expression data for 20,254 genes with the Affymetrix GeneChip Human Gene 1.0 ST microarray from normal prostate (N = 160) and prostate tumor (N = 264) tissue from participants of the Physicians' Health Study and Health Professionals Follow-up Study. With linear models, we tested the association of 39 risk variants with nearby genes and all genes, and the association of each variant with canonical pathways using a global test., Results: In addition to confirming previously reported associations, we detected several new significant (P < 0.05) associations of variants with the expression of nearby genes including C2orf43, ITGA6, MLPH, CHMP2B, BMPR1B, and MTL5. Genome-wide, five genes (MSMB, NUDT11, RBPMS2, NEFM, and KLHL33) were significantly associated after accounting for multiple comparisons for each SNP (P < 2.5 × 10(-6)). Many more genes had an FDR <10%, including SRD5A1 and PSCA, and we observed significant associations with pathways in tumor tissue., Conclusions: The risk variants were associated with several genes, including promising prostate cancer candidates and lipid metabolism pathways, suggesting mechanisms for their impact on disease. These genes should be further explored in biologic and epidemiologic studies., Impact: Determining the biologic role of these variants can lead to improved understanding of prostate cancer etiology and identify new targets for chemoprevention., (©2014 American Association for Cancer Research.)

Purpose: Prostate-specific antigen screening has led to enormous overtreatment of prostate cancer because of the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and the most indeterminate in terms of prognosis., Patients and Methods: Using the complementary DNA-mediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (n = 358) and Physicians' Health Study (PHS; n = 109). We developed an mRNA signature of Gleason grade comparing individuals with Gleason ≤ 6 to those with Gleason ≥ 8 tumors and applied the model among patients with Gleason 7 to discriminate lethal cases., Results: We built a 157-gene signature using the Swedish data that predicted Gleason with low misclassification (area under the curve [AUC] = 0.91); when this signature was tested in the PHS, the discriminatory ability remained high (AUC = 0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4 + 3 or 3 + 4 (P = .006)., Conclusion: Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment.