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Aneuploidy, defined as chromosome gains and losses, is a hallmark of cancer. However, compared with other tumor types, extensive aneuploidy is relatively rare in prostate cancer. Thus, whether numerical chromosome aberrations dictate disease progression in prostate cancer patients is not known. Here, we report the development of a method based on whole-transcriptome profiling that allowed us to identify chromosome-arm gains and losses in 333 primary prostate tumors. In two independent cohorts (n = 404) followed prospectively for metastases and prostate cancer-specific death for a median of 15 years, increasing extent of tumor aneuploidy as predicted from the tumor transcriptome was strongly associated with higher risk of lethal disease. The 23% of patients whose tumors had five or more predicted chromosome-arm alterations had 5.3 times higher odds of lethal cancer (95% confidence interval, 2.2 to 13.1) than those with the same Gleason score and no predicted aneuploidy. Aneuploidy was associated with lethality even among men with high-risk Gleason score 8-to-10 tumors. These results point to a key role of aneuploidy in driving aggressive disease in primary prostate cancer.

Intermittent androgen deprivation therapy (IADT) is an attractive treatment for biochemically recurrent prostate cancer (PCa), whereby cycling treatment on and off can reduce cumulative dose and limit toxicities. We simulate prostate-specific antigen (PSA) dynamics, with enrichment of PCa stem-like cell (PCaSC) during treatment as a plausible mechanism of resistance evolution. Simulated PCaSC proliferation patterns correlate with longitudinal serum PSA measurements in 70 PCa patients. Learning dynamics from each treatment cycle in a leave-one-out study, model simulations predict patient-specific evolution of resistance with an overall accuracy of 89% (sensitivity = 73%, specificity = 91%). Previous studies have shown a benefit of concurrent therapies with ADT in both low- and high-volume metastatic hormone-sensitive PCa. Model simulations based on response dynamics from the first IADT cycle identify patients who would benefit from concurrent docetaxel, demonstrating the feasibility and potential value of adaptive clinical trials guided by patient-specific mathematical models of intratumoral evolutionary dynamics. Prostate specific antigen (PSA) is a biomarker for prostate cancer. Here, the authors develop a mathematical model where longitudinal changes in PSA levels predict responses to intermittent androgen deprivation in patients with prostate cancer.

Epigenetic modifications control cancer development and clonal evolution in various cancer types. Here, we show that loss of the male-specific histone demethylase lysine-specific demethylase 5D (KDM5D) encoded on the Y chromosome epigenetically modifies histone methylation marks and alters gene expression, resulting in aggressive prostate cancer. Fluorescent in situ hybridization demonstrated that segmental or total deletion of the Y chromosome in prostate cancer cells is one of the causes of decreased KDM5D mRNA expression. The result of ChIP-sequencing analysis revealed that KDM5D preferably binds to promoter regions with coenrichment of the motifs of crucial transcription factors that regulate the cell cycle. Loss of KDM5D expression with dysregulated H3K4me3 transcriptional marks was associated with acceleration of the cell cycle and mitotic entry, leading to increased DNA-replication stress. Analysis of multiple clinical data sets reproducibly showed that loss of expression of KDM5D confers a poorer prognosis. Notably, we also found stress-induced DNA damage on the serine/threonine protein kinase ATR with loss of KDM5D. In KDM5D-deficient cells, blocking ATR activity with an ATR inhibitor enhanced DNA damage, which led to subsequent apoptosis. These data start to elucidate the biological characteristics resulting from loss of KDM5D and also provide clues for a potential novel therapeutic approach for this subset of aggressive prostate cancer.

Chromosome 8q gain is associated with poor clinical outcomes in prostate cancer, but the underlying biological mechanisms remain to be clarified. CSN5, a putative androgen receptor (AR) partner that is located on chromosome 8q, is the key subunit of the COP9 signalosome, which deactivates ubiquitin ligases. Deregulation of CSN5 could affect diverse cellular functions that contribute to tumor development, but there has been no comprehensive study of its function in prostate cancer. The clinical significance of CSN5 amplification/overexpression was evaluated in 16 prostate cancer clinical cohorts. Its oncogenic activity was assessed by genetic and pharmacologic perturbations of CSN5 activity in prostate cancer cell lines. The molecular mechanisms of CSN5 function were assessed, as was the efficacy of the CSN5 inhibitor CSN5i-3 in vitro and in vivo. Finally, the transcription cofactor activity of CSN5 in prostate cancer cells was determined. The prognostic significance of CSN5 amplification and overexpression in prostate cancer was independent of MYC amplification. Inhibition of CSN5 inhibited its oncogenic function by targeting AR signaling, DNA repair, multiple oncogenic pathways, and spliceosome regulation. Furthermore, inhibition of CSN5 repressed metabolic pathways, including oxidative phosphorylation and glycolysis in AR-negative prostate cancer cells. Targeting CSN5 with CSN5i-3 showed potent antitumor activity in vitro and in vivo. Importantly, CSN5i-3 synergizes with PARP inhibitors to inhibit prostate cancer cell growth. CSN5 functions as a transcription cofactor to cooperate with multiple transcription factors in prostate cancer. Inhibiting CSN5 strongly attenuates prostate cancer progression and could enhance PARP inhibition efficacy in the treatment of prostate cancer.

Prostate cancer is a highly heterogeneous disease, understanding the crosstalk between complex genomic and epigenomic alterations will aid in developing targeted therapeutics. We demonstrate that, even though snail family transcriptional repressor 2 (SNAI2) is frequently amplified in prostate cancer, it is epigenetically silenced in this disease, with dynamic changes in SNAI2 levels showing distinct clinical relevance. Integrative clinical data from 18 prostate cancer cohorts and experimental evidence showed that gene fusion between transmembrane serine protease 2 (TMPRSS2) and ETS transcription factor ERG (ERG) (TMPRSS2–ERG fusion) is involved in the silencing of SNAI2. We created a silencer score to evaluate epigenetic repression of SNAI2, which can be reversed by treatment with DNA methyltransferase inhibitors and histone deacetylase inhibitors. Silencing of SNAI2 facilitated tumor cell proliferation and luminal differentiation. Furthermore, SNAI2 has a major influence on the tumor microenvironment by reactivating tumor stroma and creating an immunosuppressive microenvironment in prostate cancer. Importantly, SNAI2 expression levels in part determine sensitivity to the cancer drugs dasatinib and panobinostat. For the first time, we defined the distinct clinical relevance of SNAI2 expression at different disease stages. We elucidated how epigenetic silencing of SNAI2 controls the dynamic changes of SNAI2 expression that are essential for tumor initiation and progression and discovered that restoring SNAI2 expression by treatment with panobinostat enhances dasatinib sensitivity, indicating a new therapeutic strategy for prostate cancer. Here, the authors define, for the first time, the distinct clinical relevance of SNAI2 expression at different disease stages of prostate cancer (PC). They elucidated how the epigenetic silencing of SNAI2 controls the dynamic changes in SNAI2 expression that are essential for tumor initiation and progression. Importantly, restoring SNAI2 expression by LBH589 (HDACi) enhances dasatinib sensitivity, indicating a new therapeutic strategy for PC.

Background Conflicting evidence suggests that statins act chemopreventively against prostate cancer (PCa). Whether the association of statin use with PCa risk is Gleason score‐dependent, time‐, dose‐respondent is not well studied. Methods We conducted a cohort study at a tertiary hospital in the Southeastern US using longitudinal data of electronic medical records (EMR) from 1994 to 2016. Only cancer‐free men aged >18 years at baseline with follow‐up time of ≥12 months were included. Time‐dependent Cox proportional hazards regression was used to estimate adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs). Results Among 13 065 men, 2976 were diagnosed with PCa over median follow‐up of 6.6 years. Statin use was associated with lower risk of both Gleason low‐ (score <7: aHR, 0.85; 95% CI, 0.74‐0.96) and high‐grade PCa (score ≥7: aHR, 0.54; 95% CI, 0.42‐0.69). The protective association was observed only when statins had been used for a relatively longer duration (≥11 months) or higher dose (≥121 defined daily doses), and were more pronounced for PCa of higher Gleason score (<7: aHR, 0.85, 95% CI, 0.74‐0.96; 7 [3 + 4]: aHR, 0.62, 95% CI, 0.43‐0.90; 7 [4 + 3]: aHR, 0.49, 95% CI, 0.29‐0.82; 8: aHR, 0.60, 95% CI, 0.37‐0.96; 9‐10: aHR, 0.24, 95% CI, 0.11‐0.54). Lipophilic statins (aHR, 0.83; 95% CI, 0.72‐0.95) might be more protective than hydrophilic statins (aHR, 0.91, 95% CI, 0.63‐1.33) against PCa. Conclusion Statin use might be associated with reduced PCa risk only when used for a relatively longer duration, and the risk reduction was higher for PCa of higher Gleason score. We found that statin use might be associated with reduced risk of both low‐ and high‐grade prostate cancer, but the reduced risk was observed only when statins had been used for a relatively longer duration or higher dose. Also, the statin‐related risk reduction was higher for prostate cancer of a higher Gleason score, and lipophilic statins might be more protective than hydrophilic statins against prostate cancer.

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1–48%). We implemented different methods to mitigate batch effects (R package batchtma ), tested in plasmode simulation. Biomarker levels were more similar between mitigation approaches compared to uncorrected values. For some biomarkers, associations with clinical features changed substantially after addressing batch effects. Batch effects and resulting bias are not an error of an individual study but an inherent feature of TMA-based protein biomarker studies. They always need to be considered during study design and addressed analytically in studies using more than one TMA. To understand cancer, researchers need to know which molecules tumor cells use. These so-called ‘biomarkers’ tag cancer cells as being different from healthy cells, and can be used to predict how aggressive a tumor may be, or how well it might respond to treatment. A popular technique for assessing biomarkers across multiple tumors is to use tissue microarrays. This involves taking samples from different tumors and embedding them in a block of wax, which is then cut into micro-thin slices and stained with reagents that can detect specific biomarkers, such as proteins. Each block contains hundreds of samples, which all experience the same conditions. So, any patterns detected in the staining are likely to represent real variations in the biomarkers present. Many cancer studies, however, often compare samples from multiple tissue microarrays, which may increase the risk of technical artifacts: for example, staining may look stronger in one batch of tissue samples than another, even though the amount of biomarker present in these different arrays is roughly the same. These ‘batch effects’ could potentially bias the results of the experiment and lead to the identification of misleading patterns. To evaluate how batch effects impact tissue microarray studies, Stopsack et al. examined 14 wax blocks which contained tumor samples from 1,448 men with prostate cancer. This revealed that for some biomarkers, but not others, there were noticeable differences between tissue microarrays that were clearly the result of batch effects. Stopsack et al. then tested six different ways of fixing these discrepancies using statistical methods. All six approaches were successful, even if the arrays included tumors with different characteristics, such as tumors that had been diagnosed more or less recently. This work highlights the importance of considering batch effects when using tissue microarrays to study cancer. Stopsack et al. have used their statistical approaches to develop freely available software which can reduce the biases that sometimes arise from these technical artifacts. This could help researchers avoid misleading patterns in their data and make it easier to detect real variations in the biomarkers present between tumor samples.

PurposeTo investigate whether the use of pre-orchiectomy instead of pre-chemotherapy tumor marker (TM) levels has an impact on the International Germ Cell Consensus Classification (IGCCCG) risk group assignment in patients with metastatic germ cell tumors (GCT).MethodsDemographic and clinical information of all patients treated for primary metastatic testicular non-seminomatous GCT in our tertiary care academic center were extracted from medical charts. IGCCCG risk group assignment was correctly performed with pre-chemotherapy marker levels and additionally with pre-orchiectomy marker levels. Agreement between pre-chemotherapy and pre-orchiectomy risk group assignments was assessed using Cohen’s kappa.ResultsOur cohort consisted of 83 patients. The use of pre-orchiectomy TMs resulted in an IGCCCG risk group upstaging in 12 patients (16%, 8 patients from good to intermediate risk and 4 patients from intermediate to poor risk) and a downstaging in 1 patient (1.2%, from intermediate- to good-risk). The agreement between pre-orchiectomy and pre-chemotherapy IGCCCG risk groups resulted in a Cohen’s kappa of 0.888 (p < 0.001).ConclusionsUsing pre-orchiectomy TMs can result in incorrect IGCCCG risk group assignment, which in turn can impact on the clinical management and follow-up of patients with metastatic GCT. Thus, adherence to the IGCCCG standard using pre-chemotherapy TMs levels is recommended.

The role of growth factors and inflammation in the onset of glioma is poorly understood, and conflicting reports of associations of circulating IGF-1 and inflammatory biomarkers with glioma risk exist in the literature. We examined associations between C-reactive protein (CRP), white blood cell count (WBC), neutrophil-to-lymphocyte ratio (NLR), and insulin-like growth factor-1 (IGF-1) and glioma risk in the UK Biobank cohort. Hazard ratios (HR) and 95% confidence intervals (CI) for glioma according to circulating biomarkers concentrations were calculated using Cox proportional hazards regression, adjusted for age, sex, race, and education. Analyses were conducted separately for glioma overall and by glioma subtype. We identified 417 incident glioma cases among 428,537 participants with 3,255,815 person-years of follow up. Weak, non-significant associations were observed with increasing levels of these biomarkers for risk of glioma overall or by glioma subtype. Among women only, IGF-1 in the highest quartile was positively associated with glioma risk compared to the lowest quartile (HR=1.64, 95%CI: 1.03–2.60, p-trend=0.08), as was NLR (HR=1.54, 95%CI: 1.00–2.39, p-trend=0.05). In this prospective cohort, we found no significant associations between the inflammatory biomarkers CRP and WBC and the development of glioma. NLR and IGF-1 were associated with risk in women, but not men. When considered with previous studies, further investigation of NLR and IGF-1 as markers of glioma risk appears warranted, particularly in women. •This was a large study of more than 400,000 participants in the UK Biobank.•There were no significant associations between CRP and WBC and later risk of glioma.•Higher NLR and IGF-1 were associated with higher risk in women, but not in men.

Methylmercury (MeHg) is an environmental neurotoxin with human exposure mainly from dietary intake of contaminated fish. Exposure to MeHg has been implicated in neurological damage, but research on its role in cancers, specifically glioma, is limited. In a glioma case-control study, we examined associations between toenail mercury (Hg) and glioma risk. We also examined genetic polymorphisms in 13 genes related to MeHg metabolism for association with glioma risk; genetic associations were also studied in the UK Biobank cohort. Median toenail Hg in cases and controls, respectively, was 0.066 μg/g and 0.069 μg/g (interquartile range (IQR): 0.032–0.161 and 0.031–0.150 μg/g). Toenail Hg was not found to be significantly associated with glioma risk (Odds Ratio: 1.02; 95% Confidence Interval: 0.91, 1.14; p = 0.70 in analysis for ordinal trend with increasing quartile of toenail MeHg). No genetic variant was statistically significant in both of the studies; one variant, rs11859163 ( MMP2 ) had a combined p-value of 0.02 though it was no longer significant after adjustment for multiple testing (Bonferroni corrected p = 1). This study does not support the hypothesis that exposure to MeHg plays a role in the development of glioma at levels of exposure found in this study population.