Integrating Tertiary Gleason 5 Patterns into Quantitative Gleason Grading in Prostate Biopsies and Prostatectomy Specimens

Robust, credible, and interpretable AI-based histopathological prostate cancer grading

Background

Prostate cancer (PCa) is among the most common cancers in men and its diagnosis requires the histopathological evaluation of biopsies by human experts. While several recent artificial intelligence-based (AI) approaches have reached human expert-level PCa grading, they often display significantly reduced performance on external datasets. This reduced performance can be caused by variations in sample preparation, for instance the staining protocol, section thickness, or scanner used. Another limiting factor of contemporary AI-based PCa grading is the prediction of ISUP grades, which leads to the perpetuation of human annotation errors.

Methods

We developed the prostate cancer aggressiveness index (PCAI), an AI-based PCa detection and grading framework that is trained on objective patient outcome, rather than subjective ISUP grades. We designed PCAI as a clinical application, containing algorithmic modules that offer robustness to data variation, medical interpretability, and a measure of prediction confidence. To train and evaluate PCAI, we generated a multicentric, retrospective, observational trial consisting of six cohorts with 25,591 patients, 83,864 images, and 5 years of median follow-up from 5 different centers and 3 countries. This includes a high-variance dataset of 8,157 patients and 28,236 images with variations in sample thickness, staining protocol, and scanner, allowing for the systematic evaluation and optimization of model robustness to data variation. The performance of PCAI was assessed on three external test cohorts from two countries, comprising 2,255 patients and 9,437 images.

Findings

Using our high-variance datasets, we show how differences in sample processing, particularly slide thickness and staining time, significantly reduce the performance of AI-based PCa grading by up to 6.2 percentage points in the concordance index (C-index). We show how a select set of algorithmic improvements, including domain adversarial training, conferred robustness to data variation, interpretability, and a measure of credibility to PCAI. These changes lead to significant prediction improvement across two biopsy cohorts and one TMA cohort, systematically exceeding expert ISUP grading in C-index and AUROC by up to 22 percentage points.

Interpretation

Data variation poses serious risks for AI-based histopathological PCa grading, even when models are trained on large datasets. Algorithmic improvements for model robustness, interpretability, credibility, and training on high-variance data as well as outcome-based severity prediction gives rise to robust models with above ISUP-level PCa grading performance.

Contemporary Diagnostic Reporting for Prostatic Adenocarcinoma: Morphologic Aspects, Molecular Correlates, and Management Perspectives

The diagnosis and reporting of prostatic adenocarcinoma have evolved from the classic framework promulgated by Dr Donald Gleason in the 1960s into a complex and nuanced system of grading and reporting that nonetheless retains the essence of his remarkable observations. The criteria for the "Gleason patterns" originally proposed have been continually refined by consensuses in the field, and Gleason scores have been stratified into a patient-friendly set of prognostically validated and widely adopted Grade Groups. One product of this successful grading approach has been the opportunity for pathologists to report diagnoses that signal carefully personalized management, placing the surgical pathologist's interpretation at the center of patient care. At one end of the continuum of disease aggressiveness, personalized diagnostic care means to sub-stratify patients with more indolent disease for active surveillance, while at the other end of the continuum, reporting histologic markers signaling aggression allows sub-stratification of clinically significant disease. Whether contemporary reporting parameters represent deeper nuances of more established ones (eg, new criteria and/or quantitation of Gleason patterns 4 and 5) or represent additional features reported alongside grade (intraductal carcinoma, cribriform patterns of carcinoma), assessment and grading have become more complex and demanding. Herein, we explore these newer reporting parameters, highlighting the state of knowledge regarding morphologic, molecular, and management aspects. Emphasis is made on the increasing value and stakes of histopathologists' interpretations and reporting into current clinical risk stratification and treatment guidelines.

An Apparent Diffusion Coefficient-Based Machine Learning Model Can Improve Prostate Cancer Detection in the Grey Area of the Prostate Imaging Reporting and Data System Category 3: A Single-Centre Experience

The Prostate Imaging and Reporting Data System (PI-RADS) has a key role in the management of prostate cancer (PCa). However, the clinical interpretation of PI-RADS 3 score lesions may be challenging and misleading, thus postponing PCa diagnosis to biopsy outcome. Multiparametric magnetic resonance imaging (mpMRI) radiomic analysis may represent a stand-alone noninvasive tool for PCa diagnosis. Hence, this study aims at developing a mpMRI-based radiomic PCa diagnostic model in a cohort of PI-RADS 3 lesions. We enrolled 133 patients with 155 PI-RADS 3 lesions, 84 of which had PCa confirmation by fusion biopsy. Local radiomic features were generated from apparent diffusion coefficient maps, and the four most informative were selected using LASSO, the Wilcoxon rank-sum test (p < 0.001), and support vector machines (SVMs). The selected features where augmented and used to train an SVM classifier, externally validated on a holdout subset. Linear and second-order polynomial kernels were exploited, and their predictive performance compared through receiver operating characteristics (ROC)-related metrics. On the test set, the highest performance, equally for both kernels, was specificity = 76%, sensitivity = 78%, positive predictive value = 80%, and negative predictive value = 74%. Our findings substantially improve radiologist interpretation of PI-RADS 3 lesions and let us advance towards an image-driven PCa diagnosis.

AI based prostate analysis system trained without human supervision to predict patient outcome from tissue samples

In order to plan the best treatment for prostate cancer patients, the aggressiveness of the tumor is graded based on visual assessment of tissue biopsies according to the Gleason scale. Recently, a number of AI models have been developed that can be trained to do this grading as well as human pathologists. But the accuracy of the AI grading will be limited by the accuracy of the subjective “ground truth” Gleason grades used for the training. We have trained an AI to predict patient outcome directly based on image analysis of a large biobank of tissue samples with known outcome without input of any human knowledge about cancer grading. The model has shown similar and in some cases better ability to predict patient outcome on an independent test-set than expert pathologists doing the conventional grading.

Alternative prostate cancer grading systems incorporating percent pattern 4/5 (IQ-Gleason) and cribriform architecture (cGrade) improve prediction of outcome after radical prostatectomy

Percentage Gleason pattern 4, invasive cribriform and/or intraductal carcinoma (IC/IDC) and minor pattern 5 are recognized as independent parameters for prostate cancer outcome, but are not incorporated in current grade groups (GGs). Two proof-of-principle studies have proposed alternative grading schemes based on percentage Gleason pattern 4/5 (integrated quantitative Gleason score; IQ-Gleason) and IC/IDC presence (cribriform grade; cGrade). Our objective was to compare the performance of GG, IQ-Gleason and cGrade for predicting biochemical recurrence and metastasis after radical prostatectomy (RP). RP specimens of 1064 patients were pathologically reviewed and graded according to the three schemes. Discriminative power for prediction of biochemical recurrence-free (BCRFS) and metastasis-free (MFS) survival was compared using Harrell's c-index. The GG distribution at RP was 207 (19.4%) GG1, 472 (44.4%) GG2, 126 (11.8%) GG3, 140 (13.2%) GG4 and 119 (11.2%) GG5. Grading according to 5-tier IQ-Gleason and cGrade systems led to categorical shifts in 49.8% and 29.7% of cases, respectively. Continuous IQ-Gleason had the best performance for predicting BCRFS (c-index 0.743, 95% confidence interval (CI) 0.715-0.771), followed by cGrade (c-index 0.738, 95%CI 0.712-0.759), 5-tier categorical IQ-Gleason (c-index 0.723, 95%CI 0.695-0.750) and GG (c-index 0.718, 95%CI 0.691-0.744). Continuous IQ-Gleason (c-index 0.834, 95%CI 0.802-0.863) and cGrade (c-index 0.834, 95%CI 0.808-0.866) both had better predictive value for MFS than categorical IQ-Gleason (c-index 0.823, 95%CI 0.788-0.857) and GG (c-index 0.806, 95%CI 0.777-0.839). In conclusion, the performance of prostate cancer grading can be improved by alternative grading schemes incorporating percent Gleason pattern 4/5 and IC/IDC.

AI Model for Prostate Biopsies Predicts Cancer Survival

An artificial intelligence (AI) algorithm for prostate cancer detection and grading was developed for clinical diagnostics on biopsies. The study cohort included 4221 scanned slides from 872 biopsy sessions at the HUS Helsinki University Hospital during 2016–2017 and a subcohort of 126 patients treated by robot-assisted radical prostatectomy (RALP) during 2016–2019. In the validation cohort (n = 391), the model detected cancer with a sensitivity of 98% and specificity of 98% (weighted kappa 0.96 compared with the pathologist’s diagnosis). Algorithm-based detection of the grade area recapitulated the pathologist’s grade group. The area of AI-detected cancer was associated with extra-prostatic extension (G5 OR: 48.52; 95% CI 1.11–8.33), seminal vesicle invasion (cribriform G4 OR: 2.46; 95% CI 0.15–1.7; G5 OR: 5.58; 95% CI 0.45–3.42), and lymph node involvement (cribriform G4 OR: 2.66; 95% CI 0.2–1.8; G5 OR: 4.09; 95% CI 0.22–3). Algorithm-detected grade group 3–5 prostate cancer depicted increased risk for biochemical recurrence compared with grade groups 1–2 (HR: 5.91; 95% CI 1.96–17.83). This study showed that a deep learning model not only can find and grade prostate cancer on biopsies comparably with pathologists but also can predict adverse staging and probability for recurrence after surgical treatment.

PITX1 Is a Regulator of TERT Expression in Prostate Cancer with Prognostic Power

Simple Summary

Most prostate cancer is of an indolent form and is curable. However, some prostate cancer belongs to rather aggressive subtypes leading to metastasis and death, and immediate therapy is mandatory. However, for these, the therapeutic options are highly invasive, such as radical prostatectomy, radiation or brachytherapy. Hence, a precise diagnosis of these tumor subtypes is needed, and the thus far applied diagnostic means are insufficient for this. Besides this, for their endless cell divisions, prostate cancer cells need the enzyme telomerase to elongate their telomeres (chromatin endings). In this study, we developed a gene regulatory model based on large data from transcription profiles from prostate cancer and chromatin-immuno-precipitation studies. We identified the developmental regulator PITX1 regulating telomerase. Besides observing experimental evidence of PITX1′s functional role in telomerase regulation, we also found PITX1 serving as a prognostic marker, as concluded from an analysis of more than 15,000 prostate cancer samples.

Abstract

The current risk stratification in prostate cancer (PCa) is frequently insufficient to adequately predict disease development and outcome. One hallmark of cancer is telomere maintenance. For telomere maintenance, PCa cells exclusively employ telomerase, making it essential for this cancer entity. However, TERT, the catalytic protein component of the reverse transcriptase telomerase, itself does not suit as a prognostic marker for prostate cancer as it is rather low expressed. We investigated if, instead of TERT, transcription factors regulating TERT may suit as prognostic markers. To identify transcription factors regulating TERT, we developed and applied a new gene regulatory modeling strategy to a comprehensive transcriptome dataset of 445 primary PCa. Six transcription factors were predicted as TERT regulators, and most prominently, the developmental morphogenic factor PITX1. PITX1 expression positively correlated with telomere staining intensity in PCa tumor samples. Functional assays and chromatin immune-precipitation showed that PITX1 activates TERT expression in PCa cells. Clinically, we observed that PITX1 is an excellent prognostic marker, as concluded from an analysis of more than 15,000 PCa samples. PITX1 expression in tumor samples associated with (i) increased Ki67 expression indicating increased tumor growth, (ii) a worse prognosis, and (iii) correlated with telomere length.

Fast hybrid optomechanical scanning photoacoustic remote sensing microscopy for virtual histology

A rapid scanning microscopy method for hematoxylin and eosin (H&E) like images is sought after for interoperative diagnosis of solid tumor margins. The rapid observation and diagnosis of histological samples can greatly lower surgical risk and improve patient outcomes from solid tumor resection surgeries. Photoacoustic remote sensing (PARS) has recently been demonstrated to provide images of virtual H&E stains with excellent concordance with true H&E staining of formalin-fixed, paraffin embedded tissues. By using PARS with constant velocity and 1D galvanometer mirror scanning we acquire large virtual H&E images (10mm x 5mm) of prostate tissue in less than 3.5 minutes without staining, and over two orders of magnitude faster data acquisition than the current PARS imaging speed.

Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading

Background

Gleason grading of prostate cancer is an important prognostic factor, but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial intelligence (A.I.) tools have demonstrated Gleason grading on-par with expert pathologists, it remains an open question whether and to what extent A.I. grading translates to better prognostication.

Methods

In this study, we developed a system to predict prostate cancer-specific mortality via A.I.-based Gleason grading and subsequently evaluated its ability to risk-stratify patients on an independent retrospective cohort of 2807 prostatectomy cases from a single European center with 5–25 years of follow-up (median: 13, interquartile range 9–17).

Results

Here, we show that the A.I.’s risk scores produced a C-index of 0.84 (95% CI 0.80–0.87) for prostate cancer-specific mortality. Upon discretizing these risk scores into risk groups analogous to pathologist Grade Groups (GG), the A.I. has a C-index of 0.82 (95% CI 0.78–0.85). On the subset of cases with a GG provided in the original pathology report (n = 1517), the A.I.’s C-indices are 0.87 and 0.85 for continuous and discrete grading, respectively, compared to 0.79 (95% CI 0.71–0.86) for GG obtained from the reports. These represent improvements of 0.08 (95% CI 0.01–0.15) and 0.07 (95% CI 0.00–0.14), respectively.

Conclusions

Our results suggest that A.I.-based Gleason grading can lead to effective risk stratification, and warrants further evaluation for improving disease management.

Gleason grading is the process by which pathologists assess the morphology of prostate tumors. The assigned Grade Group tells us about the likely clinical course of people with prostate cancer and helps doctors to make decisions on treatment. The process is complex and subjective, with frequent disagreement amongst pathologists. In this study, we develop and evaluate an approach to Gleason grading based on artificial intelligence, rather than pathologists’ assessment, to predict risk of dying of prostate cancer. Looking back at tumors and data from 2,807 people diagnosed with prostate cancer, we find that our approach is better at predicting outcomes compared to grading by pathologists alone. These findings suggest that artificial intelligence might help doctors to accurately determine the probable clinical course of people with prostate cancer, which, in turn, will guide treatment.

Wulczyn et al. utilise a deep learning-based Gleason grading model to predict prostate cancer-specific mortality in a retrospective cohort of radical prostatectomy patients. Their model enables improved risk stratification compared to pathologists’ grading and demonstrates the potential for computational pathology in the management of prostate cancer.

The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer

CONTEXT.—

Controversies and uncertainty persist in prostate cancer grading.

OBJECTIVE.—

To update grading recommendations.

DATA SOURCES.—

Critical review of the literature along with pathology and clinician surveys.

CONCLUSIONS.—

Percent Gleason pattern 4 (%GP4) is as follows: (1) report %GP4 in needle biopsy with Grade Groups (GrGp) 2 and 3, and in needle biopsy on other parts (jars) of lower grade in cases with at least 1 part showing Gleason score (GS) 4 + 4 = 8; and (2) report %GP4: less than 5% or less than 10% and 10% increments thereafter. Tertiary grade patterns are as follows: (1) replace "tertiary grade pattern" in radical prostatectomy (RP) with "minor tertiary pattern 5 (TP5)," and only use in RP with GrGp 2 or 3 with less than 5% Gleason pattern 5; and (2) minor TP5 is noted along with the GS, with the GrGp based on the GS. Global score and magnetic resonance imaging (MRI)-targeted biopsies are as follows: (1) when multiple undesignated cores are taken from a single MRI-targeted lesion, an overall grade for that lesion is given as if all the involved cores were one long core; and (2) if providing a global score, when different scores are found in the standard and the MRI-targeted biopsy, give a single global score (factoring both the systematic standard and the MRI-targeted positive cores). Grade Groups are as follows: (1) Grade Groups (GrGp) is the terminology adopted by major world organizations; and (2) retain GS 3 + 5 = 8 in GrGp 4. Cribriform carcinoma is as follows: (1) report the presence or absence of cribriform glands in biopsy and RP with Gleason pattern 4 carcinoma. Intraductal carcinoma (IDC-P) is as follows: (1) report IDC-P in biopsy and RP; (2) use criteria based on dense cribriform glands (>50% of the gland is composed of epithelium relative to luminal spaces) and/or solid nests and/or marked pleomorphism/necrosis; (3) it is not necessary to perform basal cell immunostains on biopsy and RP to identify IDC-P if the results would not change the overall (highest) GS/GrGp part per case; (4) do not include IDC-P in determining the final GS/GrGp on biopsy and/or RP; and (5) "atypical intraductal proliferation (AIP)" is preferred for an intraductal proliferation of prostatic secretory cells which shows a greater degree of architectural complexity and/or cytological atypia than typical high-grade prostatic intraepithelial neoplasia, yet falling short of the strict diagnostic threshold for IDC-P. Molecular testing is as follows: (1) Ki67 is not ready for routine clinical use; (2) additional studies of active surveillance cohorts are needed to establish the utility of PTEN in this setting; and (3) dedicated studies of RNA-based assays in active surveillance populations are needed to substantiate the utility of these expensive tests in this setting. Artificial intelligence and novel grading schema are as follows: (1) incorporating reactive stromal grade, percent GP4, minor tertiary GP5, and cribriform/intraductal carcinoma are not ready for adoption in current practice.

Prognostic significance of tertiary Gleason pattern in the contemporary era of Gleason grade grouping: A narrative review

Since the Gleason score was developed in 1966 as a histological classification for prostate cancer, it has been widely used in clinical practice and has evolved over time. The concept of a "tertiary Gleason pattern" (also known as a minor Gleason pattern) was first proposed in 2000, and has been used in clinical practice since the 2005 International Society of Urological Pathology conference. The prognostic significance of a tertiary Gleason pattern has been widely validated in various settings of prostate cancer, whereas its definition has yet to be fully established. Currently, a provisional definition of tertiary Gleason pattern is "<5% Gleason pattern 4 or 5 in radical prostatectomy specimens." In contrast, "Gleason grade grouping" was proposed in 2013 and came into use in clinical practice in 2016 according to the 2014 International Society of Urological Pathology conference. Although the prognostic significance of Gleason grade grouping has already been widely confirmed, it does not incorporate the concept of tertiary Gleason pattern. Recently, the 2019 International Society of Urological Pathology conference discussed how to handle tertiary Gleason pattern in the current Gleason scoring system, but no consensus was reached on the issue. This review summarizes the evidence on the prognostic significance of tertiary Gleason pattern and discusses how to deal with it in the context of the contemporary Gleason grade grouping. It also refers to reporting of the percentage of Gleason patterns 4 and 5, as well as quantitative Gleason score models incorporating tertiary Gleason pattern.

Grading Evolution and Contemporary Prognostic Biomarkers of Clinically Significant Prostate Cancer

Simple Summary

Prostate cancer treatment decisions are based on clinical stage and histological diagnosis, including Gleason grading assessed by a pathologist, in biopsies. Prior to staging and grading, serum or blood prostate-specific antigen (PSA) levels are measured and often trigger diagnostic examinations. However, PSA is best suited as a marker of cancer relapse after initial treatment. In this review, we first narratively describe the evolution of histological grading, the current status of Gleason pattern-based diagnostics and glance into future methodology of risk assessment by histological examination. In the second part, we systematically review the biomarkers that have been shown, independent from clinical characteristics, to correlate with clinically relevant end-points, i.e., occurrence of metastases, disease-specific mortality and overall survival after initial treatment of localized prostate cancer.

Abstract

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.

Report From the International Society of Urological Pathology (ISUP) Consultation Conference on Molecular Pathology of Urogenital Cancers. I. Molecular Biomarkers in Prostate Cancer

The combined clinical and molecular heterogeneity of prostate cancer necessitates the use of prognostic, predictive, and diagnostic biomarkers to assist the clinician with treatment selection. The pathologist plays a critical role in guiding molecular biomarker testing in prostate cancer and requires a thorough knowledge of the current testing options. In the setting of clinically localized prostate cancer, prognostic biomarkers such as Ki-67 labeling, PTEN loss or mRNA-based genomic signatures can be useful to help determine whether definitive therapy is required. In the setting of advanced disease, predictive biomarkers, such as the presence of DNA repair deficiency mediated by BRCA2 loss or mismatch repair gene defects, may suggest the utility of poly-ADP ribosylase inhibition or immune checkpoint blockade. Finally, androgen receptor-related biomarkers or diagnostic biomarkers indicating the presence of small cell neuroendocrine prostate cancer may help guide the use of androgen receptor signaling inhibitors and chemotherapy. In this review, we examine the current evidence for several prognostic, predictive and diagnostic tissue-based molecular biomarkers in prostate cancer management. For each assay, we summarize a recent survey of the International Society of Urology Pathology (ISUP) members on current testing practices and include recommendations for testing that emerged from the ISUP Working Group on Molecular Pathology of Prostate Cancer and the 2019 Consultation Conference on Molecular Pathology of Urogenital Cancers.

Reduced KLK2 expression is a strong and independent predictor of poor prognosis in ERG-negative prostate cancer

BACKGROUND

Kallikrein-related peptidase 2 (KLK2)-like KLK3 (prostate-specific antigen [PSA])-belongs to the highly conserved serine proteases of the glandular kallikrein protein family (KLK family). Studies suggested that measurement of KLK2 serum levels advanced the predictive accuracy of PSA testing in prostate cancer.

METHODS

To clarify the potential utility of KLK2 as a prognostic tissue biomarker, KLK2 expression was analyzed by immunohistochemistry in more than 12 000 prostate cancers.

RESULTS

Normal epithelium cells usually showed weak to moderate KLK2 immunostaining, whereas KLK2 was negative in 23%, weak in 38%, moderate in 35%, and strong in 4% of 9576 analyzable cancers. Lost or reduced KLK2 immunostaining was associated with advanced tumor stage, high Gleason score, lymph node metastasis, increased cell proliferation, positive resection margin, and early PSA recurrence (P < .0001). Comparison with previously analyzed molecular alterations revealed a strong association of KLK2 loss and presence of TMPRSS2:ERG fusion (P < .0001), most of all analyzed common deletions (9 of 11; P ≤ .03), and decreased PSA immunostaining (P < .0001 each). Cancers with combined negative or weak immunostaining of KLK2 and PSA showed worse prognosis than cancers with at least moderate staining of one or both proteins (P < .0001). Multivariate analyses including established preoperative and postoperative prognostic parameters showed a strong independent prognostic impact of KLK2 loss alone or in combination of PSA, especially in erythroblast transformation-specific-negative cancers (P ≤ .006).

CONCLUSIONS

Loss of KLK2 expression is a potentially useful prognostic marker in prostate cancer. Analysis of KLK2 alone or in combination with PSA may be useful for estimating cancer aggressiveness at the time of biopsy.

Inter-observer variability of cribriform architecture and percent Gleason pattern 4 in prostate cancer: relation to clinical outcome

The Grade group is an important parameter for clinical decision-making in prostate cancer. Recently, percent Gleason pattern 4 and presence of invasive cribriform and/or intraductal carcinoma (CR/IDC) have been recognized for their independent predictive value for prostate cancer outcome. There is sparse data on the inter-observer agreement for these pathologic features in practice. Our objectives were to investigate inter-observer variability of percent Gleason pattern and CR/IDC and to relate individual tumour scores to clinical outcome. Our cohort included 80 consecutive radical prostatectomies with a median follow-up 87.1 months (interquartile range 43.3-119.2), of which the slide with largest tumour volume was scored by six pathologists for Grade group (four tiers: 1, 2, 3 and 4/5), percent Gleason pattern 4 (four tiers: 0-25%, 26-50%, 51-75% and 76-100%) and presence of CR/IDC (two tiers: absent, present). The individual assignments were related to post-operative biochemical recurrence (20/80). Inter-observer agreement was substantial (Krippendorff's α 0.626) for assessment of Grade group and moderate for CR/IDC (α 0.507) and percent Gleason pattern 4 (α 0.551). For each individual pathologist, biochemical recurrence rates incremented by Grade group and presence of CR/IDC, although such relation was less clear for percent Gleason pattern 4. In conclusion, inter-observer agreement for CR/IDC and percent Gleason pattern 4 is lower than for Grade groups, indicating awareness of these features needs further improvement. Grade group and CR/IDC, but not percent Gleason pattern 4 was related to biochemical recurrence for each pathologist, indicating overall validity of individual grade assignments despite inter-observer variability.

The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

Five years after the last prostatic carcinoma grading consensus conference of the International Society of Urological Pathology (ISUP), accrual of new data and modification of clinical practice require an update of current pathologic grading guidelines. This manuscript summarizes the proceedings of the ISUP consensus meeting for grading of prostatic carcinoma held in September 2019, in Nice, France. Topics brought to consensus included the following: (1) approaches to reporting of Gleason patterns 4 and 5 quantities, and minor/tertiary patterns, (2) an agreement to report the presence of invasive cribriform carcinoma, (3) an agreement to incorporate intraductal carcinoma into grading, and (4) individual versus aggregate grading of systematic and multiparametric magnetic resonance imaging-targeted biopsies. Finally, developments in the field of artificial intelligence in the grading of prostatic carcinoma and future research perspectives were discussed.

Up regulation of the Hippo signalling effector YAP1 is linked to early biochemical recurrence in prostate cancers

The transcriptional coactivator YAP1 controls the balance between cell proliferation and apoptosis. YAP1 overexpression is linked to poor prognosis in many cancer types, yet its role in prostate cancer is unknown. Here, we applied YAP1 immunohistochemistry to a tissue microarray containing 17,747 clinical prostate cancer specimens. Cytoplasmic and nuclear YAP1 staining was seen in 81% and 63% of tumours. For both cytoplasmic and nuclear YAP1 staining, high levels were associated with advanced tumour stage, classical and quantitative Gleason grade, positive nodal stage, positive surgical margin, high KI67 labelling index, and early biochemical recurrence (p < 0.0001 each). The prognostic role of YAP1 staining was independent of established prognostic features in multivariate models (p < 0.001). Comparison with previously studied molecular markers identified associations between high YAP1 staining, TMPRSS2:ERG fusion (p < 0.0001), high androgen receptor (AR) expression (p < 0.0001), high Ki67 labelling index (p < 0.0001), and PTEN and 8p deletions (p < 0.0001 each). In conclusion, high YAP1 protein expression is an independent predictor of unfavourable disease course in prostate cancer. That cytoplasmic and nuclear YAP1 staining is equally linked to phenotype and prognosis fits well to a model where YAP1 activation during tumour progression includes up regulation, cytoplasmic accumulation and subsequent translocation to the nucleus.

Evolution of prostate cancer histopathology

PURPOSE OF REVIEW

During the last 15 years several updates in the Gleason grading have been made. With the help of pertinent research results pathologists have gained a better insight into the meanings of several prostate cancer (PCa) patterns and know better how to classify them in the Gleason grade system.

RECENT FINDINGS

During the last years PCa with cribriform architecture has be given much attention. Many data have also been published about the meaning of comedonecrosis and its relationship with Gleason pattern 4 and 5. The correlationship between comedonecrosis and intraductal PCa has also been highlighted in the recent literature. Intraductal PCa is one of the most described topics at the moment with implications to treatment such as radiation therapy. We also highlight several practical issues such as the differences of grading in prostate biopsies and prostatectomies and describe the problematic of reporting a minor high-grade pattern.

SUMMARY

Many new and recent data have allowed to refine diagnosis in PCa and improve the patients's treatment. We show that comedonecrosis can be overgraded and insist on the implication with cribriform and intraducatal carcinomas. Furthermore, we describe the importance of these PCa types especially in the consideration of further treatment.

Nuclear up regulation of the BRCA1-associated ubiquitinase BAP1 is associated with tumor aggressiveness in prostate cancers lacking the TMPRSS2:ERG fusion

Loss of the putative tumor suppressor BAP1 is a candidate biomarker for adverse prognosis in many cancer types, but conversely for improved survival in others. Studies on the expression and prognostic role of BAP1 in prostate cancer are currently lacking. We used a tissue microarray of 17,747 individual prostate cancer samples linked with comprehensive pathological, clinical and molecular data and studied the immunohistochemical expression of BAP1. BAP1 expression was typically up regulated in cancers as compared to adjacent normal prostatic glands. In 15,857 cancers, BAP1 staining was weak in 3.3%, moderate in 41.6% and strong in 17.4%. Strong BAP1 staining was associated with advanced tumor stage (p<0.0001), high classical and quantitative Gleason grade (p<0.0001), lymph node metastasis (p<0.0001), a positive surgical margin (p=0.0019) and early biochemical recurrence (p<0.0001). BAP1 expression was linked to ERG-fusion type cancers, with strong BAP1 staining in 12% of ERG-negative, but 30% of ERG-positive cancers (p<0.0001). Subset analyses in 5,415 cancers with and 4,217 cancers without TMPRSS2:ERG fusion revealed that these associations with tumor phenotype and patient outcome were largely driven by the subset of ERG-negative tumors. Multivariate analysis revealed that the prognostic impact was independent of established prognostic features in ERG negative p<0.001) but not in ERG positive cancers. BAP1 expression was further linked to androgen receptor (AR) expression: Only 2% of AR-negative, but 33% of strongly AR expressing cancers had strong BAP1 expression (p<0.0001). In conclusion, this study shows that BAP1 up regulation is linked to prostate cancer progression and aggressiveness.

Expression of CCCTC-binding factor (CTCF) is linked to poor prognosis in prostate cancer

The chromatin-organizing factor CCCTC-binding factor (CTCF) is involved in transcriptional regulation, DNA-loop formation, and telomere maintenance. To evaluate the clinical impact of CTCF in prostate cancer, we analyzed CTCF expression by immunohistochemistry on a tissue microarray containing 17 747 prostate cancers. Normal prostate tissue showed negative to low CTCF expression, while in prostate cancers, CTCF expression was seen in 7726 of our 12 555 (61.5%) tumors and was considered low in 44.6% and high in 17% of cancers. Particularly, high CTCF expression was significantly associated with the presence of the transmembrane protease, serine 2:ETS-related gene fusion: Only 10% of ERG-negative cancers, but 30% of ERG-positive cancers had high-level CTCF expression (P < 0.0001). CTCF expression was significantly associated with advanced pathological tumor stage, high Gleason grade (P < 0.0001 each), nodal metastasis (P = 0.0122), and early biochemical recurrence (P < 0.0001). Multivariable modeling revealed that the prognostic impact of CTCF was independent from established presurgical parameters such as clinical stage and Gleason grade of the biopsy. Comparison with key molecular alterations showed strong associations with the expression of the Ki-67 proliferation marker and presence of phosphatase and tensin homolog deletions (P < 0.0001 each). The results of our study identify CTCF expression as a candidate biomarker for prognosis assessment in prostate cancer.

Significance of tertiary Gleason pattern 5 in patients with Gleason score 7 after radical prostatectomy: a retrospective cohort study

PURPOSE

To evaluate the association between tertiary Gleason pattern 5 (TGP5) and biochemical recurrence (BCR) in patients with prostate cancer (PCa) with a Gleason score (GS) of 7 after radical prostatectomy (RP).

PATIENTS AND METHODS

This retrospective study identified 350 patients who received RP and were graded as GS 7 (3+4 or 4+3) at the West China Hospital from January 2009 to December 2017. Initially, the patients were divided into two groups, TGP5 absence and TGP5 presence, independent of Gleason score. We further stratified the patients by adding the Gleason score into four groups: GS 3+4, GS 3+4/TGP5, GS 4+3, and GS 4+3/TGP5. Cox proportional-hazards models were used to evaluate the association between the status of TGP5 and BCR after adjusting for the confounding factors.

RESULTS

The risk of BCR was significantly higher in patients with TGP5 when compared to patients without TGP5 (P=0.04, HR=2.17 95%, Cl: 1.03-4.59). For patients with primary Gleason pattern 4, the risk of BCR for patients with Gleason 4+3/TGP5 was statistically significantly higher than Gleason 4+3 (P=0.04, HR=2.45, 95% Cl: 1.04-5.76).

CONCLUSION

The TGP5 in patients with GS 7 had strong association with the risk of BCR and was an independent predictor for BCR. Further research on larger data sets is needed to confirm these findings.

The percentage of high-grade prostatic adenocarcinoma in prostate biopsies significantly improves on Grade Groups in the prediction of prostate cancer death

Aims

It has been recommended that the percentage of high‐grade (HG) Gleason patterns 4 and 5 should be quantified in prostate cancer. However, this has not been assessed in a cohort using prostate cancer death as an outcome, and there is debate as to whether the biopsy with the ‘worst’ percentage of HG disease or an ‘overall’ percentage of HG disease should be reported. Such data may assist in active surveillance decisions.

Methods and results

Men with clinically localised prostate cancer diagnosed by needle biopsy from 1990 to 2003 were included. The endpoint was prostate cancer death. Clinical variables included Gleason score (GS), prostate‐specific antigen level, age, clinical stage, and disease extent. Deaths were divided into those from prostate cancer and those from other causes, according to World Health Organization criteria. Nine hundred and eighty‐eight biopsy cases were centrally reviewed according to criteria agreed at the Chicago International Society of Urological Pathology conference in 2014. Cores were given individual GSs and Grade Groups (GGs), and a percentage of each grade was given for each core. Both the worst percentage of HG disease seen in a biopsy series and overall percentage of HG disease were calculated. The overall percentage of HG disease was highly significant, with a hazard ratio of 4.45 for the interquartile range (95% confidence interval 3.30–6.01, P < 2.2 × 10⁻¹⁶), and was similar to the percentage of HG disease seen in the worst core. In multivariate analysis, both were highly significant. GG2 cases with ≤5% Gleason pattern 4 showed similar survival to GG1 cases.

Conclusions

These data validate the use of percentage of HG disease to predict prostate cancer death. As both worst and overall percentage of HG disease are powerful predictors of outcome, either could be chosen to provide prognostic information.

Grading of prostate cancer: a work in progress

Grading of prostate cancer has evolved substantially over time, not least because of major changes in diagnostic approach and concomitant shifts from late- to early-stage detection since the adoption of PSA testing from the late 1980s. After the conception of the architecture-based nine-tier Gleason grading system more than 50 years ago, several changes were made in order to increase its prognostic impact, to reduce interobserver variation and to improve concordance between prostate needle biopsy and radical prostatectomy grading. This eventually resulted in the current five-tier grading system, with a much more detailed description of the individual architectural patterns constituting the remaining three Gleason patterns (i.e. grades 3-5). Nevertheless, there is room for improvement. For instance, distinction of common grade 4 subpatterns such as ill-formed and fused glands from the grade 3 pattern is challenging, blurring the division between low-risk patients who could be eligible for deferred therapy and those who need curative therapy. The last few years have witnessed the publication of several studies on the prognostic impact of individual architectural subpatterns showing that, in particular, the cribriform pattern exceeded the prognostic impact of other grade 4 subpatterns. This review provides an overview of the changes in prostate cancer grading over time and provides a thorough description of the various Gleason subpatterns, the current evidence of their prognostic impact and areas of contention. Potential practical ways for improvements of the current grading system are also put forward.

Gleason Pattern 5 is a Possible Pathologic Predictor for Biochemical Recurrence after Laparoscopic Radical Prostatectomy

Objective:

Several prognostic factors for biochemical recurrence after radical prostatectomy have been reported, including initial prostate-specific antigen level, Gleason score, positive surgical margin, and seminal vesicle invasion. Here we investigate whether Gleason pattern 5 is a predictor for biochemical recurrence.

Methods:

This retrospective study included 168 patients who underwent laparoscopic radical prostatectomy from 2006 to 2015. The relationship between biochemical recurrence after laparoscopic radical prostatectomy and the presence of Gleason pattern 5, even as a tertiary pattern, was investigated. Biochemical recurrence was defined when the prostate-specific antigen level rose to >0.2 ng/ml after having decreased to <0.1 ng/ml following laparoscopic radical prostatectomy. Biochemical recurrence-free survival was estimated by the Kaplan-Meier method. Multivariate analysis was performed using a Cox proportional hazards regression model.

Results:

The median age was 66 years, median initial prostate-specific antigen level was 6.9 ng/ml, and median follow-up period was 47.3 months. Biochemical recurrence was recognized in 27 patients (16.1%) after laparoscopic radical prostatectomy, and 5-year biochemical recurrence-free survival was 78.6%. Gleason pattern 5 was noted in 5 patients as the primary pattern, in 10 as the secondary pattern, and in 5 as the tertiary pattern. According to multivariate analysis, presence of Gleason pattern 5 (HR = 4.75, p=0.001) and positive surgical margin (HR = 4.66, p=0.001) were independent predictive factors for biochemical recurrence-free survival.

Conclusion:

Gleason pattern 5 appears to be an important predictive factor for biochemical recurrence after laparoscopic radical prostatectomy.

Updates on Grading and Staging of Prostate Cancer

Since its development between 1966 and 1977, the Gleason grading system has remained one of the most important prognostic indicators in prostatic acinar adenocarcinoma. The grading system was first majorly revised in 2005 and again in 2014. With the publication of the 8th edition of the American Joint Committee on Cancer TNM staging manual in 2018, the classification of prostate cancer and its reporting have further evolved and are now included as part of staging criteria. This article reflects the aspects that are most influential on daily practice. A brief summary of 3 ancillary commercially available genomic tests is also provided.

Upregulation of centromere protein F is linked to aggressive prostate cancers

Background

Centromere protein F (CENPF) is a key component of the kinetochore complex and plays a crucial role in chromosome segregation and cell cycle progression. Recent work suggests that CENPF upregulation is linked to aggressive tumor features in a variety of malignancies including prostate cancer.

Materials and methods

Using a highly annotated tissue microarray, we analyzed CENPF protein expression from a cohort of 8,298 prostatectomized patients by immunohistochemistry to study its effect on prostate-specific antigen recurrence-free survival.

Results

CENPF overexpression was found in 53% of cancers, and was linked to higher Gleason grade, advanced pathological tumor stage, accelerated cell proliferation, and lymph node metastasis (p<0.0001, each). A comparison with other key molecular features accessible through the microarray revealed strong associations between CENPF overexpression and presence of erythroblast transformation-specific (ETS)-related gene (ERG) fusion as well as phosphatase and tensin homolog deletion (p<0.0001, each). CENPF overexpression was linked to early biochemical recurrence. A subset analysis revealed that this was driven by the ERG-negative subset (p<0.0001). This was independent of established preoperative and postoperative prognostic parameters in multivariate analyses.

Conclusion

The results of our study identify CENPF overexpression as an important mechanism and a potential biomarker for prostate cancer aggressiveness.

Percent Gleason pattern 4 in stratifying the prognosis of patients with intermediate-risk prostate cancer

The Gleason score remains the most reliable prognosticator in men with prostate cancer. One of the recent important modifications in the Gleason grading system recommended from the International Society of Urological Pathology consensus conference is recording the percentage of Gleason pattern 4 in the pathology reports of prostate needle biopsy and radical prostatectomy cases with Gleason score 7 prostatic adenocarcinoma. Limited data have indeed suggested that the percent Gleason pattern 4 contributes to stratifying the prognosis of patients who undergo radical prostatectomy. An additional obvious benefit of reporting percent pattern 4 includes providing critical information for treatment decisions. This review summarizes and discusses available studies assessing the utility of the percentage of Gleason pattern 4 in the management of prostate cancer patients.

Marked Prognostic Impact of Minimal Lymphatic Tumor Spread in Prostate Cancer

BACKGROUND

Nodal metastasis (N1) is a strong prognostic parameter in prostate cancer; however, lymph node evaluation is always incomplete.

OBJECTIVE

To study the prognostic value of lymphatic invasion (L1) and whether it might complement or even replace lymph node analysis in clinical practice.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective analysis of pathological and clinical data from 14 528 consecutive patients.

INTERVENTION

Radical prostatectomy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The impact of L1 and N1 on patient prognosis was measured with time to biochemical recurrence as the primary endpoint.

RESULTS AND LIMITATIONS

Nodal metastases were found in 1602 (12%) of 13 070 patients with lymph node dissection. L1 was seen in 2027 of 14 528 patients (14%) for whom lymphatic vessels had been visualized by immunohistochemistry. N1 and L1 continuously increased with unfavorable Gleason grade, advanced pT stage, and preoperative prostate-specific antigen (PSA) values (p<0.0001 each). N1 was found in 4.3% of 12 501 L0 and in 41% of 2027 L1 carcinomas (p<0.0001). L1 was seen in 11% of 9868 N0 and in 61% of 1360 N1 carcinomas (p<0.0001). Both N1 and L1 were linked to PSA recurrence (p<0.0001 each). This was also true for 17 patients with isolated tumor cells (ie, <200 unequivocal cancer cells without invasive growth) and 193 metastases ≤1mm. Combined analysis of N and L status showed that L1 had no prognostic effect in N1 patients but L1 was strikingly linked to PSA recurrence in N0 patients. N0L1 patients showed a similar outcome as N1 patients.

CONCLUSIONS

Analysis of lymphatic invasion provides comparable prognostic information than lymph node analysis. Even minimal involvement of the lymphatic system has pivotal prognostic impact in prostate cancer. Thus, a thorough search for lymphatic involvement helps to identify more patients with an increased risk for disease recurrence.

PATIENT SUMMARY

Already minimal amounts of tumor cells inside the lymph nodes or intraprostatic lymphatic vessels have a severe impact on patient prognosis.

The Impact of Pathologic Upgrading of Gleason Score 7 Prostate Cancer on the Risk of the Biochemical Recurrence after Radical Prostatectomy

Objective

To investigate the impact of pathologic upgrading of Gleason score (GS) 7 prostate cancer on the risk of the biochemical recurrence.

Materials and Methods

A total of 1678 patients with postoperative GS 7 prostate cancer without lymph node metastasis were reviewed retrospectively. The patients were categorized into four groups depending on pathologic upgrading: upgraded GS 3+4, nonupgraded GS 3+4, upgraded GS 4+3, and nonupgraded GS 4+3. Kaplan-Meier multivariate model was created.

Results

The mean age was significantly higher in the nonupgraded GS 4+3 group than in other groups, whereas the mean prostate-specific antigen (PSA) level was lower in the upgraded GS 3+4 group. Pathologic findings, such as extracapsular extension, seminal vesical invasion, and the surgical margin rate, were different from each other. Five-year biochemical recurrence-free survival rate was 85%, 73%, 69%, and 60% in upgraded GS 3+4, nonupgraded GS 3+4, upgraded GS 4+3, and nonupgraded GS 4+3 group, respectively. There was significant difference between the nonupgraded 4+3 and upgraded 4+3 group, as well as between upgraded 3+4 and nonupgraded 3+4 group. However, the two middle patient groups, that is, the nonupgraded GS 3+4 group and the upgraded GS 4+3 group, did not show the statistical difference (Log-rank test, p value = 0.259).

Conclusion

The information on pathologic upgrading in the biopsy reports of patients could help to provide more detailed analysis for the biochemical recurrence of GS 7 prostate cancer.

Prostate Cancer Pathology: Recent Updates and Controversies

Prostate cancer is common, and recent efforts in clinical management have focused on identifying patients who could be candidates from less aggressive management or who could benefit from more aggressive therapy. As prostate cancer histology, especially Gleason score, plays a critical role in predicting patient outcomes, attempts have been made to refine histologic classification and reporting in prostate cancer to facilitate patient risk stratification. This review discusses recent updates in prostate cancer grading and reporting.

Concordance of Gleason grading with three-dimensional ultrasound systematic biopsy and biopsy core pre-embedding

PURPOSE

To determine the value of a three-dimensional (3D) greyscale transrectal ultrasound (TRUS)-guided prostate biopsy system and biopsy core pre-embedding method on concordance between Gleason scores of needle biopsies and radical prostatectomy (RP) specimens.

METHODS

Retrospective analysis of prostate biopsies and subsequent RP for PCa in the Jeroen Bosch Hospital, the Netherlands, from 2007 to 2016. Two cohorts were analysed: conventional 2D TRUS-guided biopsies and RP (2007-2013, n = 266) versus 3D TRUS-guided biopsies with pre-embedding (2013-2016, n = 129). The impact of 3D TRUS-guidance with pre-embedding on Gleason score (GS) concordance between biopsy and RP was evaluated using the κ-coefficient. Predictors of biopsy GS 6 upgrading were assessed using logistic regression models.

RESULTS

Gleason concordance was comparable between the two cohorts with a κ = 0.44 for the 3D cohort, compared to κ = 0.42 for the 2D cohort. 3D TRUS-guidance with pre-embedding, did not significantly affect the risk of biopsy GS 6 upgrading in univariate and multivariate analysis.

CONCLUSIONS

3D TRUS-guidance with biopsy core pre-embedding did not improve Gleason concordance. Improved detection techniques are needed for recognition of low-grade disease upgrading.

Whom to Treat: Postdiagnostic Risk Assessment with Gleason Score, Risk Models, and Genomic Classifier

Management of prostate cancer presents unique challenges because of the disease's variable natural history. Accurate risk stratification at the time of diagnosis in clinically localized disease is crucial in providing optimal counseling about management options. To accurately distinguish pathologically indolent tumors from aggressive disease, risk groups are no longer sufficient. Rather, multivariable prognostic models reflecting the complete information known at time of diagnosis offer improved accuracy and interpretability. After diagnosis, further testing with genomic assays or other biomarkers improves risk classification. These postdiagnostic risk assessment tools should not supplant shared decision making, but rather facilitate risk classification and enable more individualized care.

Contemporary grading of prostate cancer: 2017 update for pathologists and clinicians

The Gleason grading system for prostate cancer (PCa) was developed in the 1960s by DF Gleason. Due to changes in PCa detection and treatment, the application of the Gleason grading system has changed considerably in pathology routine practice. Two consensus conferences were held in 2005 and in 2014 to update PCa Gleason grading. This review provides a summary of the changes in the grading of PCa from the original Gleason grading system to the prognostic grade grouping, as well as a discussion of the clinical significance of the percentage of Gleason patterns 4 and 5.