Spatially resolved clonal copy number alterations in benign and malignant tissue.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

ScType enables fast and accurate cell type identification from spatial transcriptomics data.

SUMMARY: The limited resolution of spatial transcriptomics (ST) assays in the past has led to the development of cell type annotation methods that separate the convolved signal based on available external atlas data. In light of the rapidly increasing resolution of the ST assay technologies, we made available and investigated the performance of a deconvolution-free marker-based cell annotation method called scType. In contrast to existing methods, the spatial application of scType does not require computationally strenuous deconvolution, nor large single-cell reference atlases. We show that scType enables ultra-fast and accurate identification of abundant cell types from ST data, especially when a large enough panel of genes is detected. Examples of such assays are Visium and Slide-seq, which currently offer the best trade-off between high resolution and number of genes detected by the assay for cell type annotation. AVAILABILITY AND IMPLEMENTATION: scType source R and python codes for spatial data are openly available in GitHub (https://github.com/kris-nader/sp-type or https://github.com/kris-nader/sc-type-py). Step-by-step tutorials for R and python spatial data analysis can be found in https://github.com/kris-nader/sp-type and https://github.com/kris-nader/sc-type-py/blob/main/spatial_tutorial.md, respectively.

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures.

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.

Prognostic impact of kallikrein-related peptidase transcript levels in prostate cancer.

We aimed to study mRNA levels and prognostic impact of all 15 human kallikrein-related peptidases (KLKs) and their targets, proteinase-activated receptors (PARs), in surgically treated prostate cancer (PCa). Seventy-nine patients with localized grade group 2-4 PCas represented aggressive cases, based on metastatic progression during median follow-up of 11 years. Eighty-six patients with similar baseline characteristics, but no metastasis during follow-up, were assigned as controls. Transcript counts were detected with nCounter technology. KLK12 protein expression was investigated with immunohistochemistry. The effects of KLK12 and KLK15 were studied in LNCaP cells using RNA interference. KLK3, -2, -4, -11, -15, -10 and -12 mRNA, in decreasing order, were expressed over limit of detection (LOD). The expression of KLK2, -3, -4 and -15 was decreased and KLK12 increased in aggressive cancers, compared to controls (P < .05). Low KLK2, -3 and -15 expression was associated with short metastasis-free survival (P < .05) in Kaplan-Meier analysis. PAR1 and -2 were expressed over LOD, and PAR1 expression was higher, and PAR2 lower, in aggressive cases than controls. Together, KLKs and PARs improved classification of metastatic and lethal disease over grade, pathological stage and prostate-specific antigen combined, in random forest analyses. Strong KLK12 immunohistochemical staining was associated with short metastasis-free and PCa-specific survival in Kaplan-Meier analysis (P < .05). Knock-down of KLK15 reduced colony formation of LNCaP cells grown on Matrigel basement membrane preparation. These results support the involvement of several KLKs in PCa progression, highlighting, that they may serve as prognostic PCa biomarkers.

Multiplex immunohistochemical phenotyping of T cells in primary prostate cancer.

BACKGROUND: Most prostate cancers are "immune cold" and poorly responsive to immune checkpoint inhibitors. However, the mechanisms responsible for the lack of a robust antitumor adaptive immune response in the prostate are poorly understood, which hinders the development of novel immunotherapeutic approaches. AIMS: Most inflammatory infiltrates in the prostate are centered around benign glands and stroma, which can confound the molecular characterization of the antitumor immune response. We sought to analytically validate a chromogenic-based multiplex immunohistochemistry (IHC) approach applicable to whole slide digital image analysis to quantify T cell subsets from the tumor microenvironment of primary prostatic adenocarcinomas. As an initial application, we tested the hypothesis that PTEN loss leads to an altered antitumor immune response by comparing matched regions of tumors within the same individual with and without PTEN loss. MATERIALS & METHODS: Using the HALO Image Analysis Platform (Indica Labs), we trained a classifier to quantify the densities of eight T cell phenotypes separately in the tumor epithelial and stromal subcompartments. RESULTS: The iterative chromogenic approach using 7 different antibodies on the same slide provides highly similar findings to results using individually stained slides with single antibodies. Our main findings in carcinomas (benign removed) include the following: i) CD4+ T cells are present at higher density than CD8+ T cells; ii) all T cell subsets are present at higher densities in the stromal compartment compared to the epithelial tumor compartment; iii) most CD4+ and CD8+ T cells are PD1+; iv) cancer foci with PTEN loss harbored increased numbers of T cells compared to regions without PTEN loss, in both stromal and epithelial compartments; and v) the increases in T cells in PTEN loss regions were associated with ERG gene fusion status. DISCUSSION: This modular approach can apply to any IHC-validated antibody combination and sets the groundwork for more detailed spatial analyses. CONCLUSION: Iterative chromogenic IHC can be used for whole slide analysis of prostate tissue samples and can complement transcriptomic results including those using single cell and spatial genomic approaches.

Infectious complications after transrectal MRI-targeted and systematic prostate biopsy.

PURPOSE: To compare infectious complications after transrectal systematic prostate biopsy (SB) and magnetic resonance imaging (MRI)-targeted biopsy (TB) in a large retrospective cohort to assess whether one technique is superior to the other regarding infectious complications. METHODS: A total of 4497 patients underwent 5288 biopsies, 2875 (54%) SB and 2413 (46%) MRI-TB only. On average, 12 SB cores and 3.7 MRI-TB cores were taken per biopsy session during the study period. Infection-related complications within 30 days were compared. The primary endpoint was a positive urine culture. Secondary endpoints were positive blood cultures, urine tests with elevated leukocytes ≥ 100 E6/L and elevated C-reactive protein (CRP) ≥ 100 mg/L. Chi-square test was used to compare the cohorts. RESULTS: Positive urine cultures were found in 77 (2.7%) after SB and in 42 (1.7%) after MRI-TB (p = 0.022). In total, 46 (0.9%) blood culture positive infections were found, 23 (0.9%) occurred after SB and 23 (1.0%) after MRI-TB, (p = 0.848). Urine tests with elevated leukocytes ≥ 100 E6/L were found in 111 (3.9%) after SB and in 61 (2.5%) after MRI-TB (p = 0.006). Elevated CRP ≥ 100 mg/L was found in 122 (4.2%) after SB and in 72 (3.0%) after MRI-TB (p = 0.015). Blood cultures were drawn more often after SB than after MRI-TB, but the difference was not statistically significant. However, urine cultures and CRP were taken more often after SB than MRI-TB. CONCLUSION: Blood culture positive infections were equally rare after SB and MRI-TB. However, all other infectious complications were more common after SB than MRI-TB.

Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers.

BACKGROUND: Improved prognostication is needed to minimize overtreatment in grade group (GG) 2-4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris, and mutational panel MSK-IMPACT to predict metastasis-free and prostate cancer-specific death (PCSD) in patients with GG 2-4 prostate cancer at radical prostatectomy. METHODS: The retrospective cohort consisted of GG 2-4 patients treated with radical prostatectomy (median follow-up 10.4 years). Seventy-six cases with postoperative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index, and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan-Meier estimator. RESULTS: All gene sets outperformed clinical parameters and predicted metastasis-free and prostate cancer-specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73-0.74). Decipher, MSK-IMPACT and Prolaris showed similar NND (2.83-3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK-IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC = 0.69, p > .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22-5.66). CONCLUSION: Transcript analysis of genes included in commercial panels is feasible in survival prediction of GG 2-4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials.

PTEN and ERG expression in MRI-ultrasound guided fusion biopsy correlated with radical prostatectomy findings in men with prostate cancer.

BACKGROUND: Conventional systematic prostate biopsies (SBx) have multiple limitations, and magnetic resonance imaging (MRI)-ultrasound fusion targeting is increasingly applied (fusion biopsies [FBx]). In our previous studies, we have shown that loss of the tumor suppressor gene phosphatase and tensin homolog (PTEN) in radical prostatectomy (RP) specimens predicts poor disease-specific survival, and in active surveillance (AS), PTEN loss in SBx predicts an adverse AS outcome, although SBx PTEN status does not correlate well with the corresponding RP status. Here, we have hypothesized that PTEN and erythroblast transformation-specific related gene (ERG) status in FBx correlate better with RP than they would in SBx. METHODS: A total of 106 men, who had undergone FBx and subsequent RP in a single center between June 2015 and May 2017 were included. Fifty-three of the men had concomitant or previous SBx's. All biopsy and RP specimens were collected, and tissue microarrays (TMA) were constructed from RP specimens. Immunohistochemical stainings for PTEN and ERG expression were conducted on biopsies and RP TMAs and results were compared by using Fisher's exact test. RESULTS: The immunohistochemical predictive power of FBx, determined by the concordance of biopsy PTEN and ERG status with RP, is superior to SBx (77.6% vs 66.7% in PTEN, 92.4% vs 66.6% in ERG). FBx was superior to SBx in correlation with RP Gleason Grade Groups and MRI prostate imaging reporting and data system scores. CONCLUSION: FBx grading correlates with RP histology and MRI findings and predicts the biomarker status in the RP specimens more accurately than SBx. A longer follow-up is needed to evaluate if this translates to better prediction of disease outcomes, especially in AS and radiation therapy where prostatectomy specimens are not available for prognostication.

Fibroblast as a critical stromal cell type determining prognosis in prostate cancer.

BACKGROUND: Tumor stroma associates with prostate cancer (PCa) progression, but its specific cellular composition and association to patient survival outcome have not been characterized. METHODS: We analyzed stromal composition in human PCa using multiplex immunohistochemistry and quantitative, high-resolution image analysis in two retrospective, formalin-fixed paraffin embedded observational clinical cohorts (Cohort I, n = 117; Cohort II, n = 340) using PCa-specific mortality as outcome measurement. RESULTS: A high proportion of fibroblasts associated with aggressive disease and castration-resistant prostate cancer (CRPC). In a multivariate analysis, increase in fibroblast proportion predicted poor cancer-specific outcome independently in the two clinical cohorts studied. CONCLUSIONS: Fibroblasts were the most important cell type in determining prognosis in PCa and associated with CRPC. Thus, the stromal composition could be critically important in developing diagnostic and therapeutic approaches to aggressive prostate cancer.

Loss of PTEN expression in ERG-negative prostate cancer predicts secondary therapies and leads to shorter disease-specific survival time after radical prostatectomy.

The clinical course of prostate cancer is highly variable. Current prognostic variables, stage, and Gleason score have limitations in assessing treatment regimens for individual patients, especially in the intermediate-risk group of Gleason score 7. ERG:TMPRSS2 fusion and loss of PTEN are some of the most common genetic alterations in prostate cancer. Immunohistochemistry of PTEN and ERG has generated interest as a promising method for more precise outcome prediction but requires further validation in population-based cohorts. We studied the predictive value of ERG and PTEN expression by immunohistochemistry in two large radical prostatectomy cohorts comprising 815 patients with extensive follow-up information. Clinical end points were initiation of secondary therapy, overall survival, and disease-specific survival. Predictions of clinical outcomes were also assessed according to androgen receptor (AR) activity. PTEN loss, especially in ERG-negative cancers, predicted initiation of secondary treatments and shortened disease-specific survival time, as well as stratifying Gleason score 7 patients into different prognostic groups with regard to secondary treatments and disease-specific survival. High AR immunoreactivity in ERG-negative cancers with PTEN loss predicted worse disease-specific survival. We also observed that in Gleason score 7 ERG-negative cases with PTEN loss and high AR expression have significantly shorter disease-specific survival time compared with ERG-positive cases. Our conclusion is that loss of PTEN is a strong determining factor for shorter disease-specific survival time and initiation of secondary therapies after radical prostatectomy. The predictive value of PTEN immunoreactivity is further accentuated in ERG-negative cancers with high AR expression. Negative PTEN expression, accompanied by ERG status, can be used to stratify patients with Gleason score 7 into different survival groups. Assessment of PTEN and ERG status could provide an additional tool for initial diagnostics when determining the prognosis and subsequent follow-up regimen for patients treated by radical prostatectomy.

MRI-Targeted Prostate Biopsy Introduces Grade Inflation and Overtreatment.

Purpose: The use of MRI-targeted biopsies has led to lower detection of Gleason Grade Group 1 (GG1) prostate cancer and increased detection of GG2 disease. Although this finding is generally attributed to improved sensitivity and specificity of MRI for aggressive cancers, it might also be explained by grade inflation. Our objective was to determine the likelihood of definitive treatment and risk of post-treatment recurrence for patients with GG2 cancer diagnosed using targeted biopsies relative to men with GG1 cancer diagnosed using systematic biopsies. Methods: We performed a retrospective study on a large tertiary centre registry (HUS Acamedic Datalake) to retrieve data on prostate cancer diagnosis, treatment, and cancer recurrence. We included patients with either GG1 with systematic biopsies (3317 men) or GG2 with targeted biopsies (554 men) from 1993 to 2019. We assessed the risk of curative treatment and recurrence after treatment. Kaplan-Meier survival curves were computed to assess treatment- and recurrence-free survival. Cox proportional hazards regression analysis was performed to assess the risk of posttreatment recurrence. Results: Patients with systematic biopsy detected GG1 cancer had a significantly longer median time-to-treatment (31 months) than those with targeted biopsy detected GG2 cancer (4 months, p<0.0001). The risk of recurrence after curative treatment was similar between groups with the upper bound of 95% CI, excluding an important difference (HR: 0.94, 95% CI [0.71-1.25], p=0.7). Conclusion: GG2 cancers detected by MRI-targeted biopsy are treated more aggressively than GG1 cancers detected by systematic biopsy, despite having similar oncologic risk. To prevent further overtreatment related to the MRI pathway, treatment guidelines from the pre-MRI era need to be updated to consider changes in the diagnostic pathway.

PP2A methylesterase PME-1 suppresses anoikis and is associated with therapy relapse of PTEN-deficient prostate cancers.

While organ-confined prostate cancer (PCa) is mostly therapeutically manageable, metastatic progression of PCa remains an unmet clinical challenge. Resistance to anoikis, a form of cell death initiated by cell detachment from the surrounding extracellular matrix, is one of the cellular processes critical for PCa progression towards aggressive disease. Therefore, further understanding of anoikis regulation in PCa might provide therapeutic opportunities. Here, we discover that PCa tumours with concomitant inhibition of two tumour suppressor phosphatases, PP2A and PTEN, are particularly aggressive, having < 50% 5-year secondary-therapy-free patient survival. Functionally, overexpression of PME-1, a methylesterase for the catalytic PP2A-C subunit, inhibits anoikis in PTEN-deficient PCa cells. In vivo, PME-1 inhibition increased apoptosis in in ovo PCa tumour xenografts, and attenuated PCa cell survival in zebrafish circulation. Molecularly, PME-1-deficient PC3 cells display increased trimethylation at lysines 9 and 27 of histone H3 (H3K9me3 and H3K27me3), a phenotype known to correlate with increased apoptosis sensitivity. In summary, our results demonstrate that PME-1 supports anoikis resistance in PTEN-deficient PCa cells. Clinically, these results identify PME-1 as a candidate biomarker for a subset of particularly aggressive PTEN-deficient PCa.

Prospective Longitudinal Health-related Quality of Life Analysis of the Finnish Arm of the PRIAS Active Surveillance Cohort: 11 Years of Follow-up.

BACKGROUND: Living with an untreated cancer may alter quality of life (QoL) in the long term. OBJECTIVE: To prospectively study long-term changes in general, mental, and physical QoL in a contemporary active surveillance (AS) patient cohort with low-risk prostate cancer (PCa). DESIGN, SETTING, AND PARTICIPANTS: The study population consisted of patients enrolled in the PRIAS trial in Helsinki University Hospital (n = 348). The RAND-36 questionnaire was used to assess general QoL at the start of AS and at 1, 3, 5, 7, 9, and 11 years during follow-up. Patients who had undergone robot-assisted laparoscopic prostatectomy (RALP; n = 88) also received the questionnaire after treatment. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Changes over time were analysed using multilevel mixed-effects regression models, and reported as the mean and95% confidence interval. A rule of 0.5 × standard deviation was used to estimate changes of clinical importance. RESULTS AND LIMITATIONS: Median follow-up until the end of AS or last follow-up was 7.2 (range 0.3-12.7) yr. A decrease was observed in six of eight QoL subdomains at 7 yr. However, all scores were above age-stratified reference values. There was no difference between the group who continued AS throughout the study period and the group who discontinued AS and underwent RALP. More than half of the study cohort discontinued AS (n = 198; 57%), 135 men (68%) because of events specified in the protocol and only seven (3.5%) because of anxiety. Metastatic disease developed in six patients (1.7%), and two cases (0.6%) of PCa-related death were recorded among 348 patients in more than 12 yr of overall follow-up. The lack of a randomised control population is a limitation of the study. CONCLUSIONS: Contemporary protocolised AS does not impair general QoL. Men undergoing a treatment change (RALP) did not experience a decrease in QoL before or after their treatment change. PATIENT SUMMARY: Active surveillance is a safe treatment option for men with low-risk prostate cancer. We show that this follow-up strategy does not cause a decline in patients' general quality of life.

Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones.

The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identifies several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Certain cell populations present before treatment exhibit gene expression profiles that match those of resistant tumor cell clusters, present after treatment. We confirm that these clusters are resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrates that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identify differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors.

Increased Expression and Altered Cellular Localization of Fibroblast Growth Factor Receptor-Like 1 (FGFRL1) Are Associated with Prostate Cancer Progression.

Fibroblast growth factor receptors (FGFRs) 1-4 are involved in prostate cancer (PCa) regulation, but the role of FGFR-like 1 (FGFRL1) in PCa is unclear. FGFRL1 expression was studied by qRT-PCR and immunohistochemistry of patient tissue microarrays (TMAs) and correlated with clinical patient data. The effects of FGFRL1 knockdown (KD) in PC3M were studied in in vitro culture models and in mouse xenograft tumors. Our results showed that FGFRL1 was significantly upregulated in PCa. The level of membranous FGFRL1 was negatively associated with high Gleason scores (GSs) and Ki67, while increased cytoplasmic and nuclear FGFRL1 showed a positive correlation. Cox regression analysis indicated that nuclear FGFRL1 was an independent prognostic marker for biochemical recurrence after radical prostatectomy. Functional studies indicated that FGFRL1-KD in PC3M cells increases FGFR signaling, whereas FGFRL1 overexpression attenuates it, supporting decoy receptor actions of membrane-localized FGFRL1. In accordance with clinical data, FGFRL1-KD markedly suppressed PC3M xenograft growth. Transcriptomics of FGFRL1-KD cells and xenografts revealed major changes in genes regulating differentiation, ECM turnover, and tumor-stromal interactions associated with decreased growth in FGFRL1-KD xenografts. Our results suggest that FGFRL1 upregulation and altered cellular compartmentalization contribute to PCa progression. The nuclear FGFRL1 could serve as a prognostic marker for PCa patients.

The Movember Global Action Plan 1 (GAP1): Unique Prostate Cancer Tissue Microarray Resource.

BACKGROUND: The need to better understand the molecular underpinnings of the heterogeneous outcomes of patients with prostate cancer is a pressing global problem and a key research priority for Movember. To address this, the Movember Global Action Plan 1 Unique tissue microarray (GAP1-UTMA) project constructed a set of unique and richly annotated tissue microarrays (TMA) from prostate cancer samples obtained from multiple institutions across several global locations. METHODS: Three separate TMA sets were built that differ by purpose and disease state. RESULTS: The intended use of TMA1 (Primary Matched LN) is to validate biomarkers that help determine which clinically localized prostate cancers with associated lymph node metastasis have a high risk of progression to lethal castration-resistant metastatic disease, and to compare molecular properties of high-risk index lesions within the prostate to regional lymph node metastases resected at the time of prostatectomy. TMA2 (Pre vs. Post ADT) was designed to address questions regarding risk of castration-resistant prostate cancer (CRPC) and response to suppression of the androgen receptor/androgen axis, and characterization of the castration-resistant phenotype. TMA3 (CRPC Met Heterogeneity)'s intended use is to assess the heterogeneity of molecular markers across different anatomic sites in lethal prostate cancer metastases. CONCLUSIONS: The GAP1-UTMA project has succeeded in combining a large set of tissue specimens from 501 patients with prostate cancer with rich clinical annotation. IMPACT: This resource is now available to the prostate cancer community as a tool for biomarker validation to address important unanswered clinical questions around disease progression and response to treatment.

Improving suspended sediment measurements by automatic samplers.

Suspended solids either as total suspended solids (TSS) or suspended sediment concentration (SSC) is an integral particulate water quality parameter that is important in assessing particle-bound contaminants. At present, nearly all stormwater runoff quality monitoring is performed with automatic samplers in which the sampling intake is typically installed at the bottom of a storm sewer or channel. This method of sampling often results in a less accurate measurement of suspended sediment and associated pollutants due to the vertical variation in particle concentration caused by particle settling. In this study, the inaccuracies associated with sampling by conventional intakes for automatic samplers have been verified by testing with known suspended sediment concentrations and known particle sizes ranging from approximately 20 µm to 355 µm under various flow rates. Experimental results show that, for samples collected at a typical automatic sampler intake position, the ratio of sampled to feed suspended sediment concentration is up to 6600% without an intake strainer and up to 300% with a strainer. When the sampling intake is modified with multiple sampling tubes and fitted with a wing to provide lift (winged arm sampler intake), the accuracy of sampling improves substantially. With this modification, the differences between sampled and feed suspended sediment concentration were more consistent and the sampled to feed concentration ratio was accurate to within 10% for particle sizes up to 250 µm.

Grading Evolution and Contemporary Prognostic Biomarkers of Clinically Significant Prostate Cancer.

Gleason grading remains the strongest prognostic parameter in localized prostate adenocarcinoma. We have here outlined the evolution and contemporary practices in pathological evaluation of prostate tissue samples for Gleason score and Grade group. The state of more observer-independent grading methods with the aid of artificial intelligence is also reviewed. Additionally, we conducted a systematic review of biomarkers that hold promise in adding independent prognostic or predictive value on top of clinical parameters, Grade group and PSA. We especially focused on hard end points during the follow-up, i.e., occurrence of metastasis, disease-specific mortality and overall mortality. In peripheral blood, biopsy-detected prostate cancer or in surgical specimens, we can conclude that there are more than sixty biomarkers that have been shown to have independent prognostic significance when adjusted to conventional risk assessment or grouping. Our search brought up some known putative markers and panels, as expected. Also, the synthesis in the systematic review indicated markers that ought to be further studied as part of prospective trials and in well characterized patient cohorts in order to increase the resolution of the current clinico-pathological prognostic factors.

Does Protocol Make a Difference? Comparison of Two Prostate Cancer Active Surveillance Cohorts: A Non-protocol-based Follow-up and a Protocol-based Contemporary Follow-up.

BACKGROUND: Active surveillance (AS) is the preferred option for initial management for low-risk prostate cancer (PC). Although many AS protocols exist, there is little evidence to support one over another. OBJECTIVE: To assess whether there is difference in overall (OS), prostate cancer-specific (CSS), metastasis-free (MFS), or treatment-free (TFS) survival between a strict (Prostate cancer Research International: Active Surveillance [PRIAS]) and a loose (European Randomized study of Screening for Prostate Cancer [ERSPC]) AS protocol. DESIGN SETTING AND PARTICIPANTS: This study included two cohorts of men (n = 518) with low-risk, localized, Gleason score ≤7 PC. The ERSPC cohort included 241 men followed for 9.5 yr (median) with a non-protocol-based follow-up. The PRIAS cohort included 277 men followed for 5 yr (median) with a strict protocol. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: OS, CSS, MFS, and TFS were compared by the Kaplan-Meier method, competing risk analysis, and Cox proportional hazard regression. RESULTS AND LIMITATIONS: As expected, due to the difference in median follow-up time between the cohorts, a difference in the absolute number of events was seen. However, no difference in any of the survival outcomes was evident in the Kaplan-Meier or competing risks analysis. Furthermore, in Cox proportional hazard regression analysis, cohort (ERSPC vs PRIAS) was not associated with any of the outcomes. Results are limited by the retrospective study design, limited statistical power, and inability to match the cohorts for predictive factors. CONCLUSIONS: There was no difference in survival outcomes between a non-protocol-based follow-up and a protocol-based contemporary AS follow-up of patients with low-risk PC. However, a longer follow-up is needed. PATIENT SUMMARY: We compared survival outcomes of two cohorts of patients with low-risk prostate cancer: a strict and a loose follow-up protocol. We found no differences in survival measures between the cohorts.

Morphological Features Extracted by AI Associated with Spatial Transcriptomics in Prostate Cancer.

Prostate cancer is a common cancer type in men, yet some of its traits are still under-explored. One reason for this is high molecular and morphological heterogeneity. The purpose of this study was to develop a method to gain new insights into the connection between morphological changes and underlying molecular patterns. We used artificial intelligence (AI) to analyze the morphology of seven hematoxylin and eosin (H&E)-stained prostatectomy slides from a patient with multi-focal prostate cancer. We also paired the slides with spatially resolved expression for thousands of genes obtained by a novel spatial transcriptomics (ST) technique. As both spaces are highly dimensional, we focused on dimensionality reduction before seeking associations between them. Consequently, we extracted morphological features from H&E images using an ensemble of pre-trained convolutional neural networks and proposed a workflow for dimensionality reduction. To summarize the ST data into genetic profiles, we used a previously proposed factor analysis. We found that the regions were automatically defined, outlined by unsupervised clustering, associated with independent manual annotations, in some cases, finding further relevant subdivisions. The morphological patterns were also correlated with molecular profiles and could predict the spatial variation of individual genes. This novel approach enables flexible unsupervised studies relating morphological and genetic heterogeneity using AI to be carried out.