Regulatory and memory T lymphocytes infiltrating prostate tumors predict long term clinical outcomes.

Introduction: The localization, density but mostly the phenotype of tumor infiltrating lymphocytes (TIL) provide important information on the initial interaction between the host immune system and the tumor. Our objective was to assess the prognostic significance of T (CD3+), T regulatory (Treg) (FoxP3+) and T memory (Tmem) (CD45RO+) infiltrating lymphocytes and of genes associated with TIL in prostate cancer (PCa). Methods: Immunohistochemistry (IHC) was used to assess the infiltration of CD3+, FoxP3+ and CD45RO+ cells in the tumor area, tumor margin and adjacent normal-like epithelium of a series of 98 PCa samples with long clinical follow-up. Expression of a panel of 31 TIL-associated genes was analyzed by Taqman Low-Density Array (TLDA) technology in another series of 50 tumors with long clinical follow-up. Kaplan-Meier and Cox proportional hazards regression analyses were performed to determine association of these markers with biochemical recurrence (BCR), need for definitive androgen deprivation therapy (ADT) or lethal PCa. Results: TIL subtypes were present at different densities in the tumor, tumor margin and adjacent normal-like epithelium, but their density and phenotype in the tumor area were the most predictive of clinical outcomes. In multivariate analyses, a high density of Treg (high FoxP3+/CD3+ cell ratio) predicted a higher risk for need of definitive ADT (HR=7.69, p=0.001) and lethal PCa (HR=4.37, p=0.04). Conversely, a high density of Tmem (high CD45RO+/CD3+ cell ratio) predicted a reduced risk of lethal PCa (HR=0.06, p=0.04). TLDA analyses showed that a high expression of FoxP3 was associated with a higher risk of lethal PCa (HR=5.26, p=0.02). Expression of CTLA-4, PD-1, TIM-3 and LAG-3 were correlated with that of FoxP3. Amongst these, only a high expression of TIM-3 was associated with a significant higher risk for definitive ADT in univariate Cox regression analysis (HR=3.11, p=0.01). Conclusion: These results show that the proportion of Treg and Tmem found within the tumor area is a strong and independent predictor of late systemic progression of PCa. Our results also suggest that inhibition of TIM-3 might be a potential approach to counter the immunosuppressive functions of Treg in order to improve the anti-tumor immune response against PCa.

Long term evaluation of optimized Gleason grading in a large cohort of men with prostate cancer in Canada.

OBJECTIVES: To evaluate the International Society of Urological Pathology (ISUP) 5-tier grade grouping (GG) system of prostate cancers as well as previously proposed optimizations. PATIENTS AND METHODS: The PROCURE biobank is a prospective cohort study of patients with localized prostate cancer who underwent radical prostatectomy in Quebec province between 2005 and 2013. Surgical specimens were graded by experienced genitourinary pathologists using 2019 ISUP criteria. Follow-up was conducted until November 2021. The current 5-tier and a proposed 6-tier GG system were evaluated, the latter having two changes: 1) Gleason 3 + 4 and 4 + 3 tumors with minor/tertiary Gleason 5 patterns were upgraded to GG 3 and 4, respectively; and 2) patients in GG5 were separated based on primary Gleason pattern (4 or 5). Cox proportional hazards models and Harrell's concordance (C) indices were used for statistical analyses. RESULTS: 2003 patients were included (median follow-up: 8.7 years). The current 5-tier GG system predicted time to recurrence (hazard ratio [HR] 2.12, 95% confidence interval [95%CI] 1.99-2.25, C 0.717), androgen-deprivation therapy (HR 2.58, 95%CI 2.38-2.80, C 0.790), metastasis (HR 2.48, 95%CI 2.17-2.83, C 0.806), castration-resistant prostate cancer (HR 2.67, 95%CI 2.28-3.13, C 0.829), and cancer-specific mortality (HR 2.80, 95%CI 2.27-3.44, C 0.835). Goodness-of-fit further improved with the proposed 6-tier GG system, with Harrell's C of 0.733, 0.807, 0.827, 0.853, and 0.853, respectively. CONCLUSIONS: The 5-tier GG system predicted short- and long-term outcomes for patients with localized prostate cancer, and the proposed 6-tier GG system further improved its accuracy.

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.

The 'wrong pocket' problem as a barrier to the integration of telehealth in health organisations and systems.

The COVID-19 pandemic has accelerated the deployment of telehealth services in many countries around the world. It also revealed many barriers and challenges to the use of digital health technologies in health organisations and systems that have persisted for decades. One of these barriers is what is known as the 'wrong pocket' problem - where an organisation or sector makes expenditures and investments to address a given problem, but the benefits (return on investment) are captured by another organisation or sector (the wrong pocket). This problem is the origin of many difficulties in public policies and programmes (e.g. education, environment, justice and public health), especially in terms of sustainability and scaling-up of technology and innovation. In this essay/perspective, we address the wrong pocket problem in the context of a major telehealth project in Canada. We show how the problem of sharing investments and expenses, as well as the redistribution of economies among the different stakeholders involved, may have threatened the sustainability and scaling-up of this project, even though it has demonstrated the clinical utility and contributed to improving the health of populations. In conclusion, the wrong pocket problem may be decisive in the reduced take-up, and potential failure, of certain telehealth programmes and policies. It is not enough for a telehealth service to be clinically relevant and 'efficient', it must also be mutually beneficial to the various stakeholders involved, particularly in terms of the equitable sharing of costs and benefits (return on investment) associated with the implementation of this new service model. Finally, the wrong pocket concept offers a helpful lens for studying the success, sustainability, and scale-up of digital transformations in health organisations and systems. This needs to be considered in future research and evaluations in the field.

Impact of artificial intelligence on pathologists' decisions: an experiment.

OBJECTIVE: The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this paper is to determine the reliance of pathologists on AI and to investigate whether providing information on AI impacts this reliance. MATERIALS AND METHODS: The experiment using an online survey design. Under 3 conditions, 116 pathologists and pathology students were tasked with assessing the Gleason grade for a series of 12 prostate biopsies: (1) without AI recommendations, (2) with AI recommendations, and (3) with AI recommendations accompanied by information about the algorithm itself, specifically algorithm accuracy rate and algorithm decision-making process. RESULTS: Participant responses were significantly more accurate with the AI decision aids than without (92% vs 87%, odds ratio 13.30, P < .01). Unexpectedly, the provision of information on the algorithm made no significant difference compared to AI without information. The reliance on AI correlated with general beliefs on AI's usefulness but not with particular assessments of the AI tool offered. Decisions were made faster when AI was provided. DISCUSSION: These results suggest that pathologists are willing to rely on AI regardless of accuracy or explanations. Generalization beyond the specific tasks and explanations provided will require further studies. CONCLUSION: This study suggests that the factors that influence the reliance on AI differ in practice from beliefs expressed by clinicians in surveys. Implementation of AI in prospective settings should take individual behaviors into account.

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.

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.

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.

Omega-3 Fatty Acids Survey in Men under Active Surveillance for Prostate Cancer: from Intake to Prostate Tissue Level.

Dietary omega-3 fatty acids (ω3), particularly long-chain ω3 (LCω3), have protective effects against prostate cancer (PCa) in experimental studies. Observational studies are conflicting, possibly because of the biomarker used. This study aimed at evaluating associations between grade reclassification and ω3 levels assessed in prostatic tissue, red blood cells (RBC), and diet. We conducted a validation cross-sectional study nested within a phase II clinical trial. We identified 157 men diagnosed with low-risk PCa who underwent a first active surveillance repeat prostate biopsy session. Fatty acid (FA) intake was assessed using a food frequency questionnaire and their levels measured in prostate tissue and RBC. Associations were evaluated using logistic regression. At first repeat biopsy session, 39 (25%) men had high-grade PCa (grade group ≥2). We found that high LCω3-eicosapentaenoic acid (EPA) level in prostate tissue (odds ratio (OR) 0.25; 95% (confidence interval (CI) 0.08-0.79; p-trend = 0.03) was associated with lower odds of high-grade PCa. Similar results were observed for LCω3 dietary intake (OR 0.30; 95% CI 0.11-0.83; p-trend = 0.02) but no association for RBC. LCω3-EPA levels in the target prostate tissue are inversely associated with high-grade PCa in men with low-risk PCa, supporting that prostate tissue FA, but not RBC FA, is a reliable biomarker of PCa risk.

Performance of preoperative plasma tumor markers HE4 and CA125 in predicting ovarian cancer mortality in women with epithelial ovarian cancer.

Clinical utility of new biomarkers often requires the identification of their optimal threshold. This external validation study was conducted to assess the performance of the preoperative plasma tumor markers HE4 and CA125 optimal cut-offs to predict cancer mortality in women with epithelial ovarian cancer (EOC). Participating women had upfront debulking surgery in the University Hospital of Quebec City (Canada) between 1998 and 2013. A total of 136 women participated in the training cohort (cohort 1) and 177 in the validation cohort (cohort 2). Preoperative plasma HE4 and CA125 levels were measured by Elecsys. Optimal thresholds were identified in the cohort 1 using time-dependent receiver operating characteristic (ROC) curves. Multivariate Cox models were used to validate the biomarkers using their optimal cut-offs in the cohort 2. The likelihood ratio (LR) test was done to test whether the biomarkers added prognostic information beyond that provided by standard prognostic factors. The Areas Under the Curves (AUC) for HE4 and CA125 were respectively 64.2 (95% CI: 54.7-73.6) and 63.1 (95%CI: 53.6-72.6). The optimal thresholds were 277 pmol/L for HE4 and 282 U/ml for CA125. Preoperative plasma HE4 (≥277 pmol/L) was significantly associated with EOC mortality (adjusted hazard ratio (aHR): 1.90; 95% CI:1.09-3.29). The prognostic effect of HE4 was strongest in the subgroup of women with serous ovarian cancer (aHR: 2.42; 95% CI: 1.25-4.68). Using a multivariate model including all standard prognostic factors, this association was maintained (aHR: 2.21; 95% CI: 1.15-4.23). In addition, preoperative plasma HE4 added prediction for death over the standard prognostic markers in women with serous tumors (p-value for LR-test: 0.01). Preoperative CA125 was not associated with cancer mortality, both in women with EOC and in those with serous tumors. Preoperative HE4 is a promising prognostic biomarker in EOC, especially in serous tumor.

Proteases and their inhibitors as prognostic factors for high-grade serous ovarian cancer.

Ovarian carcinoma is one of the most lethal malignancies, but only very few prognostic biomarkers are known. The degradome, comprising proteases, protease non-proteolytic homologues and inhibitors, have been involved in the prognosis of many cancer types, including ovarian carcinoma. The prognostic significance of the whole degradome family has not been specifically studied in high-grade serous ovarian cancer. A targeted DNA microarray known as the CLIP-CHIP microarray was used to identify potential prognostic factors in ten high-grade serous ovarian cancer women who had early recurrence (<1.6 years) or late/no recurrence after first line surgery and chemotherapy. In women with early recurrence, we identified seven upregulated genes (TMPRSS4, MASP1/3, SPC18, PSMB1, IGFBP2, CFI - encoding Complement Factor I - and MMP9) and one down-regulated gene (ADAM-10). Using immunohistochemistry, we evaluated the prognostic effect of these 8 candidate genes in an independent cohort of 112 high-grade serous ovarian cancer women. Outcomes were progression, defined according to CA-125 criteria, and death. Multivariate Cox proportional hazard regression models were done to estimate the associations between each protein and each outcome. High ADAM-10 expression (intensity of 2-3) was associated with a lower risk of progression (adjusted hazard ratio (HR): 0.51; 95% confidence interval (CI): 0.29-0.87). High complement factor I expression (intensity 2-3) was associated with a higher risk of progression (adjusted HR: 2.30, 95% CI: 1.17-4.53) and death (adjusted HR: 3.42; 95% CI: 1.72-6.79). Overall, we identified the prognostic value of two proteases, ADAM-10 and complement factor I, for high-grade serous ovarian cancer which could have clinical significance.

The Proteogenomic Landscape of Curable Prostate Cancer.

DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

Factors Affecting Interindividual Variability of Hepatic UGT2B17 Protein Expression Examined Using a Novel Specific Monoclonal Antibody.

Accurate quantification of the metabolic enzyme uridine diphospho-glucuronosyltransferase (UGT) UGT2B17 has been hampered by the high sequence identity with other UGT2B enzymes (as high as 94%) and by the lack of a specific antibody. Knowing the significance of the UGT2B17 pathway in drug and hormone metabolism and cancer, we developed a specific monoclonal antibody (EL-2B17mAb), initially validated by the lack of detection in liver microsomes of an individual carrying no UGT2B17 gene copy and in supersomes expressing UGT2B enzymes. Immunohistochemical detection in livers revealed strong labeling of bile ducts and variable labeling of hepatocytes. Expression levels assessed by immunoblotting were highly correlated to mass spectrometry-based quantification (r = 0.93), and three major expression patterns (absent, low, or high) were evidenced. Livers with very low expression were carriers of the functional rs59678213 G variant, located in the binding site for the transcription factor forkhead box A1 (FOXA1) of the UGT2B17 promoter. The highest level of expression was observed for individuals carrying at least one rs59678213 A allele. Multiple regression analysis indicated that the number of gene copies explained only 8% of UGT2B17 protein expression, 49% when adding rs59678213, reaching 54% when including sex. The novel EL-2B17mAb antibody allowed specific UGT2B17 quantification and exposed different patterns of hepatic expression. It further suggests that FOXA1 is a key driver of UGT2B17 expression in the liver. The availability of this molecular tool will help characterize the UGT2B17 level in various disease states and establish more precisely the contribution of the UGT2B17 enzyme to drug and hormone metabolism.

Widespread and Functional RNA Circularization in Localized Prostate Cancer.

The cancer transcriptome is remarkably complex, including low-abundance transcripts, many not polyadenylated. To fully characterize the transcriptome of localized prostate cancer, we performed ultra-deep total RNA-seq on 144 tumors with rich clinical annotation. This revealed a linear transcriptomic subtype associated with the aggressive intraductal carcinoma sub-histology and a fusion profile that differentiates localized from metastatic disease. Analysis of back-splicing events showed widespread RNA circularization, with the average tumor expressing 7,232 circular RNAs (circRNAs). The degree of circRNA production was correlated to disease progression in multiple patient cohorts. Loss-of-function screening identified 11.3% of highly abundant circRNAs as essential for cell proliferation; for ∼90% of these, their parental linear transcripts were not essential. Individual circRNAs can have distinct functions, with circCSNK1G3 promoting cell growth by interacting with miR-181. These data advocate for adoption of ultra-deep RNA-seq without poly-A selection to interrogate both linear and circular transcriptomes.

The relationship between body-mass index, physical activity, and pathologic and clinical outcomes after radical prostatectomy for prostate cancer.

PURPOSE: We evaluated whether an increased body-mass index (BMI) and decreased physical activity increase the risk of locally advanced or high-risk prostate cancer (PCa) at radical prostatectomy (RP), and treatment failure after surgery. METHODS: Data were collected from the PROCURE Biobank, a prospective cohort of patients with localized PCa undergoing RP in four academic centers in Québec between 2006 and 2013. Treatment failure was defined as biochemical recurrence and/or initiation of secondary, non-adjuvant therapy, and analyzed using the Kaplan-Meier method, log-rank tests, and Cox proportional-hazards models. Uni- and multivariate (ordered) logistic regression was used for time-independent variables. RESULTS: 1813 patients were included. Median follow-up time was 69 months. Patients who reported a lower BMI were generally older, of Asian descent, and physically more active (p < 0.05). Younger, black, and overweight/obese patients reported less physical activity (p < 0.05). In multivariate analyses, a higher BMI increased the risk for locally advanced, high-risk PCa (defined as a pT3, N1 and/or Gleason 8-10 tumor; odds ratio 1.33, p < 0.001), but increased physical activity did not predict high-risk disease (odds ratio 0.84, p = 0.39). Patients with a higher BMI also had a larger prostate at surgery (odds ratio 1.13, p = 0.03). BMI and physical activity were not associated with positive surgical margins or time to treatment failure (p > 0.05). CONCLUSIONS: BMI was an independent predictor for locally advanced, high-risk disease in this cohort of PCa patients undergoing RP, but was unrelated to treatment failure. Physical activity was not related to locally advanced, high-risk PCa or treatment failure.

Optimization of the 2014 Gleason grade grouping in a Canadian cohort of patients with localized prostate cancer.

OBJECTIVES: To evaluate the five-tier Gleason grade group (GG) scoring of prostate cancers adopted by the International Society of Urology Pathology (ISUP) in 2014, and to propose modifications to optimize its performance. PATIENTS AND METHODS: Data were obtained from PROCURE, a prospective cohort of patients with localized prostate cancer undergoing radical prostatectomy in Québec, 2006-2013. Surgical specimens were evaluated by genitourinary pathologists using 2014 ISUP criteria. Treatment failure was defined as biochemical recurrence and/or initiation of secondary, non-adjuvant therapy. Analyses were conducted using Kaplan-Meier methods, log-rank tests, Cox proportional hazards models and Harrell's concordance indices. RESULTS: A total of 1 917 patients were included, with a median follow-up of 69 months. The 5-year treatment failure rates were 9.6%, 23.5%, 43.1%, 52.6% and 84.3% in GG1-5, respectively (P < 0.001 when comparing GG2 with GG3). Treatment failure rates for patients in GG2 and GG3 with tertiary Gleason 5 pattern were higher than patients in the same group without a tertiary pattern (P < 0.001), but were similar to rates for patients in GGs 3 or 4 without a tertiary pattern (P > 0.3). Primary Gleason pattern (4/5) predicted treatment failure in GG5 (5-year failure rates 82.3% vs 97.1%, respectively; P = 0.001). The five-tier GG system had greater accuracy as a prognostic indicator compared with the four-tier system (Harrell's concordance index 0.716 vs 0.676). When upgrading patients in GG2/3 with tertiary Gleason 5 pattern to patients in GG3/4, and separating patients in GG5 by primary Gleason pattern, the Harrell's concordance index increased to 0.730. CONCLUSION: The five-tier GG system increased accuracy for predicting treatment failure compared with the previous grading systems, but can be further improved.

Correction to: HtrA1 expression and the prognosis of high-grade serous ovarian carcinoma: a cohort study using digital analysis.

It has been highlighted that the original article [1] contained a typesetting mistake in the family name of Dominique Trudel.

HtrA1 expression and the prognosis of high-grade serous ovarian carcinoma: a cohort study using digital analysis.

BACKGROUND: The expression of high temperature requirement factor A1 (Htra1) has been reported to be decreased in ovarian carcinoma, but its prognostic effect remains undetermined. METHODS: We evaluated the impact of HtrA1 downregulation in tumoral tissues on cancer progression and death in women with serous ovarian carcinoma. HtrA1 staining was performed on tissue microarrays (TMA) comprised of tumor samples from a cohort of 106 women who were diagnosed with primary high-grade serous ovarian carcinoma and receiving standard treatment at the Québec University Hospital between 1993 and 2006. HtrA1 expression was assessed visually (percentage of positive nuclei) and by digital image analysis (percentage of positive area). Cox regression multivariate models included standard prognostic factors and were used to estimate adjusted hazard ratios (aHR) for progression or death in the cohort. RESULTS: By visual analysis, a low percentage of HtrA1-positive nuclei (< 10% vs ≥10%) tend to be associated with a lower risk of progression (aHR = 0.71; 95% Confidence interval (CI) = 0.46-1.09; P = 0.11) and mortality (aHR = 0.65; 95% CI = 0.41-1.04; P = 0.07). Low nuclear HtrA1 expression assessed by digital image analysis (< median % vs ≥ median %) showed a significant association with lower risk of progression (aHR = 0.62; 95% CI = 0.40-0.95; p = 0.03) and death (aHR = 0.60; 95% CI = 0.38-0.95; p = 0.03). CONCLUSION: Altogether, our results demonstrate that nuclear downregulation of HtrA1 is associated with a better prognosis in women with high grade serous ovarian carcinoma.