The gut microbiome-prostate cancer crosstalk is modulated by dietary polyunsaturated long-chain fatty acids.

The gut microbiota modulates response to hormonal treatments in prostate cancer (PCa) patients, but whether it influences PCa progression remains unknown. Here, we show a reduction in fecal microbiota alpha-diversity correlating with increase tumour burden in two distinct groups of hormonotherapy naïve PCa patients and three murine PCa models. Fecal microbiota transplantation (FMT) from patients with high PCa volume is sufficient to stimulate the growth of mouse PCa revealing the existence of a gut microbiome-cancer crosstalk. Analysis of gut microbial-related pathways in mice with aggressive PCa identifies three enzymes responsible for the metabolism of long-chain fatty acids (LCFA). Supplementation with LCFA omega-3 MAG-EPA is sufficient to reduce PCa growth in mice and cancer up-grading in pre-prostatectomy PCa patients correlating with a reduction of gut Ruminococcaceae in both and fecal butyrate levels in PCa patients. This suggests that the beneficial effect of omega-3 rich diet is mediated in part by modulating the crosstalk between gut microbes and their metabolites in men with PCa.

The estrogen signaling pathway reprograms prostate cancer cell metabolism and supports proliferation and disease progression.

Just as the androgen receptor (AR), the estrogen receptor α (ERα) is expressed in the prostate and is thought to influence prostate cancer (PCa) biology. Yet, the incomplete understanding of ERα functions in PCa hinders our ability to fully comprehend its clinical relevance and restricts the repurposing of estrogen-targeted therapies for the treatment of this disease. Using two human PCa tissue microarray cohorts, we first demonstrated that nuclear ERα expression was heterogeneous among patients, being only detected in half of tumors. Positive nuclear ERα levels were correlated with disease recurrence, progression to metastatic PCa, and patient survival. Using in vitro and in vivo models of the normal prostate and PCa, bulk and single-cell RNA-Seq analyses revealed that estrogens partially mimic the androgen transcriptional response and induce specific biological pathways linked to proliferation and metabolism. Bioenergetic flux assays and metabolomics confirmed the regulation of cancer metabolism by estrogens, supporting proliferation. Using cancer cell lines and patient-derived organoids, selective estrogen receptor modulators, a pure anti-estrogen, and genetic approaches impaired cancer cell proliferation and growth in an ERα-dependent manner. Overall, our study revealed that, when expressed, ERα functionally reprograms PCa metabolism, is associated with disease progression, and could be targeted for therapeutic purposes.

High infiltration of CD209+ dendritic cells and CD163+ macrophages in the peritumor area of prostate cancer is predictive of late adverse outcomes.

Introduction: Prostate cancer (PCa) shows considerable variation in clinical outcomes between individuals with similar diseases. The initial host-tumor interaction as assessed by detailed analysis of tumor infiltrating immune cells within the primary tumor may dictate tumor evolution and late clinical outcomes. In this study, we assessed the association between clinical outcomes and dendritic cell (DC) or macrophage (MΦ) tumor infiltration as well as with expression of genes related to their functions. Methods: Infiltration and localization of immature DC, mature DC, total MΦ and M2-type MΦ was analyzed by immunohistochemistry in 99 radical prostatectomy specimens from patients with 15.5 years median clinical follow-up using antibodies against CD209, CD83, CD68 and CD163, respectively. The density of positive cells for each marker in various tumor areas was determined. In addition, expression of immune genes associated with DC and MΦ was tested in a series of 50 radical prostatectomy specimens by Taqman Low-Density Array with similarly long follow-up. Gene expression was classified as low and high after unsupervised hierarchical clustering. Numbers and ratio of positive cells and levels of gene expression were correlated with endpoints such as biochemical recurrence (BCR), need for definitive androgen deprivation therapy (ADT) or lethal PCa using Cox regression analyses and/or Kaplan-Meier curves. Results: Positive immune cells were observed in tumor, tumor margin, and normal-like adjacent epithelium areas. CD209+ and CD163+ cells were more abundant at the tumor margin. Higher CD209+/CD83+ cell density ratio at the tumor margin was associated with higher risk of ADT and lethal PCa while higher density of CD163+ cells in the normal-like adjacent epithelium was associated with a higher risk of lethal PCa. A combination of 5 genes expressed at high levels correlated with a shorter survival without ADT and lethal PCa. Among these five genes, expression of IL12A and CD163 was correlated to each other and was associated with shorter survival without BCR and ADT/lethal PCa, respectively. Conclusion: A higher level of infiltration of CD209+ immature DC and CD163+ M2-type MΦ in the peritumor area was associated with late adverse clinical outcomes.

Leukocytic Infiltration of Intraductal Carcinoma of the Prostate: An Exploratory Study.

Intraductal carcinoma of the prostate (IDC-P) is an aggressive histological subtype of prostate cancer (PCa) detected in approximately 20% of radical prostatectomy (RP) specimens. As IDC-P has been associated with PCa-related death and poor responses to standard treatment, the purpose of this study was to explore the immune infiltrate of IDC-P. Hematoxylin- and eosin-stained slides from 96 patients with locally advanced PCa who underwent RP were reviewed to identify IDC-P. Immunohistochemical staining of CD3, CD8, CD45RO, FoxP3, CD68, CD163, CD209 and CD83 was performed. For each slide, the number of positive cells per mm2 in the benign tissues, tumor margins, cancer and IDC-P was calculated. Consequently, IDC-P was found in a total of 33 patients (34%). Overall, the immune infiltrate was similar in the IDC-P-positive and the IDC-P-negative patients. However, FoxP3+ regulatory T cells (p < 0.001), CD68+ and CD163+ macrophages (p < 0.001 for both) and CD209+ and CD83+ dendritic cells (p = 0.002 and p = 0.013, respectively) were less abundant in the IDC-P tissues compared to the adjacent PCa. Moreover, the patients were classified as having immunologically "cold" or "hot" IDC-P, according to the immune-cell densities averaged in the total IDC-P or in the immune hotspots. The CD68/CD163/CD209-immune hotspots predicted metastatic dissemination (p = 0.014) and PCa-related death (p = 0.009) in a Kaplan-Meier survival analysis. Further studies on larger cohorts are necessary to evaluate the clinical utility of assessing the immune infiltrate of IDC-P with regards to patient prognosis and the use of immunotherapy for lethal PCa.

Isocitrate dehydrogenase 1 sustains a hybrid cytoplasmic-mitochondrial tricarboxylic acid cycle that can be targeted for therapeutic purposes in prostate cancer.

The androgen receptor (AR) is an established orchestrator of cell metabolism in prostate cancer (PCa), notably by inducing an oxidative mitochondrial program. Intriguingly, AR regulates cytoplasmic isocitrate dehydrogenase 1 (IDH1), but not its mitochondrial counterparts IDH2 and IDH3. Here, we aimed to understand the functional role of IDH1 in PCa. Mouse models, in vitro human PCa cell lines, and human patient-derived organoids (PDOs) were used to study the expression and activity of IDH enzymes in the normal prostate and PCa. Genetic and pharmacological inhibition of IDH1 was then combined with extracellular flux analyses and gas chromatography-mass spectrometry for metabolomic analyses and cancer cell proliferation in vitro and in vivo. In PCa cells, more than 90% of the total IDH activity is mediated through IDH1 rather than its mitochondrial counterparts. This profile seems to originate from the specialized prostate metabolic program, as observed using mouse prostate and PDOs. Pharmacological and genetic inhibition of IDH1 impaired mitochondrial respiration, suggesting that this cytoplasmic enzyme contributes to the mitochondrial tricarboxylic acid cycle (TCA) in PCa. Mass spectrometry-based metabolomics confirmed this hypothesis, showing that inhibition of IDH1 impairs carbon flux into the TCA cycle. Consequently, inhibition of IDH1 decreased PCa cell proliferation in vitro and in vivo. These results demonstrate that PCa cells have a hybrid cytoplasmic-mitochondrial TCA cycle that depends on IDH1. This metabolic enzyme represents a metabolic vulnerability of PCa cells and a potential new therapeutic target.

UGT2B28 accelerates prostate cancer progression through stabilization of the endocytic adaptor protein HIP1 regulating AR and EGFR pathways.

The androgen inactivating UGT2B28 pathway emerges as a predictor of progression in prostate cancer (PCa). However, the clinical significance of UGT2B28 tumoral expression and its contribution to PCa progression remain unclear. Using the Canadian Prostate Cancer Biomarker Network biobank (CPCBN; n = 1512), we analyzed UGT2B28 tumor expression in relation to clinical outcomes in men with localized PCa. UGT2B28 was overexpressed in tumors compared to paired normal adjacent prostatic tissue and was associated with inferior outcomes. Functional analyses indicated that UGT2B28 promoted cell proliferation, and its expression was regulated by the androgen receptor (AR)/ARv7. Mechanistically, UGT2B28 was shown to be a protein partner of the endocytic adaptor protein huntingtin-interacting protein 1 (HIP1), increasing its stability and priming AR/epidermal growth factor receptor (EGFR) pathways, leading to ERK1/2 activation triggering cell proliferation and epithelial-to-mesenchymal transition (EMT). HIP1 knockdown in UGT2B28 positive cells, and dual pharmacological targeting of AR and EGFR pathways, abolished cell proliferative advantages conferred by UGT2B28. In conclusion, UGT2B28 is a prognosticator of progression in localized PCa, regulates both AR and EGFR oncogenic signaling pathways via HIP1, and therefore can be therapeutically targeted by using combination of existing AR/EGFR inhibitors.

Combining Antiandrogens with Immunotherapy for Bladder Cancer Treatment.

Background: Men are three to four times more likely to be diagnosed with bladder cancer (BCa) than women, who often have more aggressive tumors. Intravesical bacillus Calmette-Guerin (BCG) for non-muscle-invasive bladder cancer (NMIBC) is one of the first immunotherapies, with use of immune checkpoint inhibitors for BCa immunotherapy expanding. Sex hormones, and notably androgens, might impact the outcome of these therapies. Objective: To understand immunological sex differences in BCa and investigate androgen receptor (AR) inhibition as a novel strategy to improve the response to BCa immunotherapy. Design setting and participants: Human NMIBC tumors were freshly collected following transurethral resection. In vivo studies used the subcutaneous MBT-2 BCa model in male and female C3H mice. The AR antagonist enzalutamide was given alone or in combination with anti-programmed cell death protein-1 (anti-PD-1) or intratumoral BCG + poly(I:C) treatments. Outcome measurements and statistical analysis: Tumor growth and survival were evaluated in vivo. Flow cytometry and RNA sequencing characterized the immune cells present in murine and human tumors. Descriptive comparisons were performed for MBT-2 tumors between sexes and with human NMIBC tumors. Results and limitations: The MBT-2 model shows multiple similarities to the immune composition of human NMIBC tumors and recapitulates previously observed human tumor immune cell sex differences. Enzalutamide in combination with either anti-PD-1 or BCG + poly(I:C) treatment in male mice synergized to improve response rates. Notably, the proportion of complete responses in male mice treated with the combination treatment resembles that observed in female mice with either immunotherapy alone. Limitations include the sample size for murine experiments. Conclusions: Our results suggest that combining AR antagonism with immunotherapy in male BCa patients may potentiate the antitumor immune response and increase response rates. The MBT-2 model appears relevant to investigate immunological BCa sex differences. Patient summary: Our studies suggest that combining antiandrogen treatments with BCa immunotherapy may improve response rates in men. We also demonstrate the utility of the MBT-2 mouse model to study sex differences in BCa.

Multiple metabolic pathways fuel the truncated tricarboxylic acid cycle of the prostate to sustain constant citrate production and secretion.

OBJECTIVE: The prostate is metabolically unique: it produces high levels of citrate for secretion via a truncated tricarboxylic acid (TCA) cycle to maintain male fertility. In prostate cancer (PCa), this phenotype is reprogrammed, making it an interesting therapeutic target. However, how the truncated prostate TCA cycle works is still not completely understood. METHODS: We optimized targeted metabolomics in mouse and human organoid models in ex vivo primary culture. We then used stable isotope tracer analyses to identify the pathways that fuel citrate synthesis. RESULTS: First, mouse and human organoids were shown to recapitulate the unique citrate-secretory program of the prostate, thus representing a novel model that reproduces this unusual metabolic profile. Using stable isotope tracer analysis, several key nutrients were shown to allow the completion of the prostate TCA cycle, revealing a much more complex metabolic profile than originally anticipated. Indeed, along with the known pathway of aspartate replenishing oxaloacetate, glutamine was shown to fuel citrate synthesis through both glutaminolysis and reductive carboxylation in a GLS1-dependent manner. In human organoids, aspartate entered the TCA cycle at the malate entry point, upstream of oxaloacetate. Our results demonstrate that the citrate-secretory phenotype of prostate organoids is supported by the known aspartate-oxaloacetate-citrate pathway, but also by at least three additional pathways: glutaminolysis, reductive carboxylation, and aspartate-malate conversion. CONCLUSIONS: Our results add a significant new dimension to the prostate citrate-secretory phenotype, with at least four distinct pathways being involved in citrate synthesis. Better understanding this distinctive citrate metabolic program will have applications in both male fertility as well as in the development of novel targeted anti-metabolic therapies for PCa.

Subversion of infiltrating prostate macrophages to a mixed immunosuppressive tumor-associated macrophage phenotype.

Tumor-associated macrophages (TAMs) support tumor progression within the tumor microenvironment (TME). Many questions remain as to the origin, development, and function of TAMs within the prostate TME. Evaluation of TAMs in prostate cancer (PCa) patients identified the immunosuppressive TAM marker CD163 in adjacent normal epithelium as an independent predictor of metastases or PCa death. Flow cytometry analyses identified prostate TAMs as frequently expressing both proinflammatory M1 (CCR7+) and immunosuppressive M2 (CD163+) markers. In vitro, we demonstrate PCa cells similarly subvert human M1 macrophages toward a mixed M1/M2 macrophage phenotype favoring tumor growth. Further the cytokine milieu-induced transition between immunosuppressive M2 to proinflammatory M1 (M2→M1) macrophages is abrogated by the presence of PCa cells. RNA sequencing suggests alterations in chemokine expression in prostate TAMs due to the presence of PCa cells. Together, our results suggest that prostate TAMs originate from inflammatory infiltrating macrophages, which are then reprogrammed mainly by PCa cells, but also the cytokine milieu. A better understanding of this subversion of macrophages within the prostate may lead to novel treatment strategies.

Identification of Morphologic Criteria Associated with Biochemical Recurrence in Intraductal Carcinoma of the Prostate.

Intraductal carcinoma of the prostate (IDC-P) is an aggressive subtype of prostate cancer strongly associated with an increased risk of biochemical recurrence (BCR). However, approximately 40% of men with IDC-P remain BCR-free five years after radical prostatectomy. In this retrospective multicenter study, we aimed to identify histologic criteria associated with BCR for IDC-P lesions. A total of 108 first-line radical prostatectomy specimens were reviewed. In our test cohort (n = 39), presence of larger duct size (>573 µm in diameter), cells with irregular nuclear contours (CINC) (≥5 CINC in two distinct high-power fields), high mitotic score (>1.81 mitoses/mm2), blood vessels, and comedonecrosis were associated with early BCR (<18 months) (p < 0.05). In our validation cohort (n = 69), the presence of CINC or blood vessels was independently associated with an increased risk of BCR (hazard ratio [HR] 2.32, 95% confidence interval [CI] 1.09-4.96, p = 0.029). When combining the criteria, the presence of any CINC, blood vessels, high mitotic score, or comedonecrosis showed a stronger association with BCR (HR 2.74, 95% CI 1.21-6.19, p = 0.015). Our results suggest that IDC-P can be classified as low versus high-risk of BCR. The defined morphologic criteria can be easily assessed and should be integrated for clinical application following validation in larger cohorts.

Dimensional reduction based on peak fitting of Raman micro spectroscopy data improves detection of prostate cancer in tissue specimens.

SIGNIFICANCE: Prostate cancer is the most common cancer among men. An accurate diagnosis of its severity at detection plays a major role in improving their survival. Recently, machine learning models using biomarkers identified from Raman micro-spectroscopy discriminated intraductal carcinoma of the prostate (IDC-P) from cancer tissue with a ≥85 % detection accuracy and differentiated high-grade prostatic intraepithelial neoplasia (HGPIN) from IDC-P with a ≥97.8 % accuracy. AIM: To improve the classification performance of machine learning models identifying different types of prostate cancer tissue using a new dimensional reduction technique. APPROACH: A radial basis function (RBF) kernel support vector machine (SVM) model was trained on Raman spectra of prostate tissue from a 272-patient cohort (Centre hospitalier de l'Université de Montréal, CHUM) and tested on two independent cohorts of 76 patients [University Health Network (UHN)] and 135 patients (Centre hospitalier universitaire de Québec-Université Laval, CHUQc-UL). Two types of engineered features were used. Individual intensity features, i.e., Raman signal intensity measured at particular wavelengths and novel Raman spectra fitted peak features consisting of peak heights and widths. RESULTS: Combining engineered features improved classification performance for the three aforementioned classification tasks. The improvements for IDC-P/cancer classification for the UHN and CHUQc-UL testing sets in accuracy, sensitivity, specificity, and area under the curve (AUC) are (numbers in parenthesis are associated with the CHUQc-UL testing set): +4 % (+8 % ), +7 % (+9 % ), +2 % (6%), +9 (+9) with respect to the current best models. Discrimination between HGPIN and IDC-P was also improved in both testing cohorts: +2.2 % (+1.7 % ), +4.5 % (+3.6 % ), +0 % (+0 % ), +2.3 (+0). While no global improvements were obtained for the normal versus cancer classification task [+0 % (-2 % ), +0 % (-3 % ), +2 % (-2 % ), +4 (+3)], the AUC was improved in both testing sets. CONCLUSIONS: Combining individual intensity features and novel Raman fitted peak features, improved the classification performance on two independent and multicenter testing sets in comparison to using only individual intensity features.

Using ex vivo culture to assess dynamic phenotype changes in human prostate macrophages following exposure to therapeutic drugs.

Within the prostate tumor microenvironment (TME) there are complex multi-faceted and dynamic communication occurring between cancer cells and immune cells. Macrophages are key cells which infiltrate and surround tumor cells and are recognized to significantly contribute to tumor resistance and metastases. Our understanding of their function in the TME is commonly based on in vitro and in vivo models, with limited research to confirm these model observations in human prostates. Macrophage infiltration was evaluated within the TME of human prostates after 72 h culture of fresh biopsies samples in the presence of control or enzalutamide. In addition to immunohistochemistry, an optimized protocol for multi-parametric evaluation of cellular surface markers was developed using flow cytometry. Flow cytometry parameters were compared to clinicopathological features. Immunohistochemistry staining for 19 patients with paired samples suggested enzalutamide increased the expression of CD163 relative to CD68 staining. Techniques to validate these results using flow cytometry of dissociated biopsies after 72 h of culture are described. In a second cohort of patients with Gleason grade group ≥ 3 prostate cancer, global macrophage expression of CD163 was unchanged with enzalutamide treatment. However, exploratory analyses of our results using multi-parametric flow cytometry for multiple immunosuppressive macrophage markers suggest subgroup changes as well as novel associations between circulating biomarkers like the neutrophil to lymphocyte ratio (NLR) and immune cell phenotype composition in the prostate TME. Further, we observed an association between B7-H3 expressing tumor-associated macrophages and the presence of intraductal carcinoma. The use of flow cytometry to evaluate ex vivo cultured prostate biopsies fills an important gap in our ability to understand the immune cell composition of the prostate TME. Our results highlight novel associations for further investigation.

Identification of Abundant and Functional dodecaRNAs (doRNAs) Derived from Ribosomal RNA.

Using a modified RNA-sequencing (RNA-seq) approach, we discovered a new family of unusually short RNAs mapping to ribosomal RNA 5.8S, which we named dodecaRNAs (doRNAs), according to the number of core nucleotides (12 nt) their members contain. Using a new quantitative detection method that we developed, we confirmed our RNA-seq data and determined that the minimal core doRNA sequence and its 13-nt variant C-doRNA (doRNA with a 5' Cytosine) are the two most abundant doRNAs, which, together, may outnumber microRNAs. The C-doRNA/doRNA ratio is stable within species but differed between species. doRNA and C-doRNA are mainly cytoplasmic and interact with heterogeneous nuclear ribonucleoproteins (hnRNP) A0, A1 and A2B1, but not Argonaute 2. Reporter gene activity assays suggest that C-doRNA may function as a regulator of Annexin II receptor (AXIIR) expression. doRNAs are differentially expressed in prostate cancer cells/tissues and may control cell migration. These findings suggest that unusually short RNAs may be more abundant and important than previously thought.

Androgen receptor and immune cell PD-L1 expression in bladder tumors predicts disease recurrence and survival.

PURPOSE: The impact of sex hormones on cancer immunotherapy remains controversial. Androgens, via the androgen receptor (AR), may impact the success of immune checkpoint blockade. This study characterizes AR and programmed death ligand-1 (PD-L1) expression in bladder tumors with long clinical follow-up. METHODS: AR and PD-L1 expression was analyzed using immunohistochemistry on 143 transurethral resection (TUR) and 203 radical cystectomy (RC) specimens. Descriptive statistics and survival analyses assessed the relationship of AR and PD-L1 staining with clinical outcomes of tumor recurrence, progression, and overall survival. RESULTS: AR expression was observed in a higher proportion of TUR than RC specimens (59% vs 35%, p < 0.001). High immune cell (IC) PD-L1 expression was associated with higher stage and grade. Patients with the combination of an absence of AR expression and the highest (> 10%) IC PD-L1 expression in TUR tumors had an increased risk of recurrence and progression. In RC specimens, the expression of AR increased the risk of local recurrence (adjusted hazard ratio (HR) 2.09, 95% CI 0.98-4.45), which was even higher among patients who also had IC PD-L1 expression (HR 4.16, 95% CI 1.28-13.52). For 28 paired metastatic lymph nodes among RC patients, tumor cell PD-L1 expression was significantly correlated (r = 0.48, p = 0.01), while no relationship with IC PD-L1 expression was observed. CONCLUSIONS: The expression of AR and its relationship to clinical outcomes appears to vary between non-muscle invasive and muscle-invasive bladder cancer. Our results support the role of IC PD-L1 expression as an independent risk factor for bladder cancer outcomes.

Omega-3 Eicosapentaenoic Acid Reduces Prostate Tumor Vascularity.

The impact of omega (ω)-3 fatty acids on prostate cancer is controversial in epidemiological studies but experimental studies suggest a protective effect. However, little is known about the mechanism of action. Here, we studied the effects of purified fatty acid molecules on prostate tumor progression using the TRAMP-C2 syngeneic immunocompetent mouse model. Compared with ω-6 or ω-9-supplemented animals, we observed that late-stage prostate tumor growth was reduced with a monoacylglyceride (MAG)-conjugated form of eicosapentaenoic acid (EPA) supplementation, whereas docosahexanenoic acid (DHA) caused an early reduction. MAG-EPA significantly decreased tumor blood vessel diameter (P < 0.001). RNA sequencing analysis revealed that MAG-EPA downregulated angiogenesis- and vascular-related pathways in tumors. We also observed this tissue vascular phenotype in a clinical trial testing MAG-EPA versus a high oleic sunflower oil placebo. Using anti-CD31 IHC, we observed that MAG-EPA reduced blood vessel diameter in prostate tumor tissue (P = 0.03) but not in normal adjacent tissue. Finally, testing autocrine and paracrine effects in an avascular tumor spheroid growth assay, both exogenous MAG-EPA and endogenous ω3 reduced VEGF secretion and in vitro endothelial cell tube formation and blocked tumor spheroid growth, suggesting that ω3 molecules can directly hinder prostate cancer cell growth. Altogether, our results suggest that fatty acids regulate prostate cancer growth and that a tumor-specific microenvironment is required for the anti-vascular effect of MAG-EPA in patients with prostate cancer. IMPLICATIONS: Increasing the amount of ingested EPA omega-3 subtype for patients with prostate cancer might help to reduce prostate tumor progression by reducing tumor vascularization.

Long chain omega-3 fatty acids and their oxidized metabolites are associated with reduced prostate tumor growth.

INTRODUCTION: Cancer has been associated with increased oxidative stress and deregulation of bioactive oxylipins derived from long-chain polyunsaturated fatty acids (LC-PUFA) like arachidonic acid (AA). There is a debate whether ω-3 LC-PUFA could promote or prevent prostate tumor growth through immune modulation and reduction of oxidative stress. Our aim was to study the association between enzymatically or non-enzymatically produced oxidized-LC-PUFA metabolites and tumor growth in an immune-competent eugonadal and castrated C57BL/6 male mice injected with TRAMP-C2 prostate tumor cells, fed with ω-3 or ω-6 LC-PUFA-rich diets. MATERIALS AND METHODS: Tumor fatty acids were profiled by gas chromatography and 26 metabolites derived from either AA, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were assessed by liquid chromatography-mass spectrometry. RESULTS: The enriched ω-3 diet did not reduce oxidative stress overall in tumors but favored the formation of ω-3 rather than ω-6 derived isoprostanoids. We discovered that EPA and its oxidized-derivatives like F3-isoprostanes and prostaglandin (PG)F3α, were inversely correlated with tumor volume (spearman correlations and T-test, p<0.05). In contrast, F2-isoprostanes, adrenic acid, docosapentaenoic acid (DPAω-6) and PGE2 were positively correlated with tumor volume. Interestingly, F4-neuroprostanes, PGD2, PGF2α, and thromboxane were specifically increased in TRAMP-C2 tumors of castrated mice compared to those of eugonadal mice. DISCUSSION: Decreasing tumor growth under ω-3 diet could be attributed in part to increased levels of EPA and its oxidized-derivatives, a reduced level of pro-angiogenic PGE2 and increased levels of F4-neuroprostanes and resolvins content in tumors, suspected of having anti-proliferative and anti-inflammatory effects.

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer.

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

Immune-focused multi-omics analysis of prostate cancer: leukocyte Ig-Like receptors are associated with disease progression.

Prostate cancer (PCa) immunotherapy has shown limited efficacy so far, even in advanced-stage cancers. The success rate of PCa immunotherapy might be improved by approaches more adapted to the immunobiology of the disease. The objective of this study was to perform a multi-omics analysis to identify immune genes associated with PCa progression to better characterize PCa immunobiology and propose new immunotherapeutic targets. mRNA, miRNA, methylation, copy number aberration, and single nucleotide variant datasets from The Cancer Genome Atlas PRAD cohort were analyzed after filtering for genes associated with immunity. Sparse partial least squares-discriminant analyses were performed to identify features associated with biochemical recurrence (BCR) in each type of omics data. Selected features predicted BCR with a balanced error rate (BER) of 0.20 to 0.51 in single-omics and of 0.05 in multi-omics analyses. Amongst features associated with BCR were genes from the Immunoglobulin Ig-like Receptor (LILR) family which are immune checkpoints with immunotherapeutic potential. Using Multivariate INTegrative (MINT) analysis, the association of five LILR genes with BCR was quantified in a combination of three RNA-seq datasets and confirmed with Kaplan-Meier analysis in both these and in an independent RNA-seq dataset. Finally, immunohistochemistry showed that a high number of LILRB1 positive cells within the tumors predicted long-term adverse outcomes. Thus, tumors characterized by abnormal expression of LILR genes have an elevated risk of recurring after definitive local therapy. The immunotherapeutic potential of these regulators to stimulate the immune response against PCa should be evaluated in pre-clinical models.

Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation.

BACKGROUND: Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy (RµS) and machine learning technology following a protocol suitable for routine clinical histopathology laboratories. METHODS AND FINDINGS: We used RµS to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays [TMAs]) from 483 patients treated in 3 Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. The median age at radical prostatectomy was 62 years. Most of the specimens from the first cohort (Centre hospitalier de l'Université de Montréal) were of Gleason score 3 + 3 = 6 (51%) while most of the specimens from the 2 other cohorts (University Health Network and Centre hospitalier universitaire de Québec-Université Laval) were of Gleason score 3 + 4 = 7 (51% and 52%, respectively). Most of the 483 patients were pT2 stage (44%-69%), and pT3a (22%-49%) was more frequent than pT3b (9%-12%). To investigate the prostate tissue of each patient, 2 consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions/TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. Models were trained and cross-validated using data from 1 institution. Accuracy, sensitivity, and specificity were 87% ± 5%, 86% ± 6%, and 89% ± 8%, respectively, to differentiate PC from benign tissue, and 95% ± 2%, 96% ± 4%, and 94% ± 2%, respectively, to differentiate IDC-P from PC. The trained models were then tested on Raman spectra from 2 independent institutions, reaching accuracies, sensitivities, and specificities of 84% and 86%, 84% and 87%, and 81% and 82%, respectively, to diagnose PC, and of 85% and 91%, 85% and 88%, and 86% and 93%, respectively, for the identification of IDC-P. IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation that can be mistaken as IDC-P, with accuracies, sensitivities, and specificities > 95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult-to-classify lesions from our datasets. CONCLUSIONS: In this study, we developed classification models for the analysis of RµS data to differentiate IDC-P, PC, and benign tissue, including HGPIN. RµS could be a next-generation histopathological technique used to reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer.

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.